ytzi/the-stack-dedup-python-filtered-docstrings

bbc8b38a1aa611247709f106104e2e943fb0e7bb

282

py

Python

pykin/utils/mesh_utils.py

jdj2261/pykin

da952b8ec023382b8a324d1095b0cfd675c7452b

[ "MIT" ]

14

2021-08-09T06:59:10.000Z

2022-03-09T13:05:46.000Z

pykin/utils/mesh_utils.py

jdj2261/pykin

da952b8ec023382b8a324d1095b0cfd675c7452b

[ "MIT" ]

null

pykin/utils/mesh_utils.py

jdj2261/pykin

da952b8ec023382b8a324d1095b0cfd675c7452b

[ "MIT" ]

4

2021-12-13T03:23:36.000Z

2022-03-09T11:34:29.000Z

import sys, os pykin_path = os.path.abspath(os.path.dirname(__file__)+"/../../" ) sys.path.append(pykin_path)

31.333333

66

0.712766

import sys, os pykin_path = os.path.abspath(os.path.dirname(__file__)+"/../../" ) sys.path.append(pykin_path) def get_mesh_path(mesh_path, robot_name): result_path = pykin_path + "/asset/urdf/" + robot_name +"/" result_path = result_path + mesh_path return result_path

149

0

23

6bcaa7b3aa19a28e3ff196de1285bf96eb39458a

703

py

Python

LeetCode/0007.py

summertian4/Practice

3328025f84669ebc9df6036e39ac98d0432adf8f

[ "MIT" ]

2

2019-09-18T01:34:31.000Z

2019-09-18T01:34:36.000Z

LeetCode/0007.py

summertian4/Practice

3328025f84669ebc9df6036e39ac98d0432adf8f

[ "MIT" ]

null

LeetCode/0007.py

summertian4/Practice

3328025f84669ebc9df6036e39ac98d0432adf8f

[ "MIT" ]

null

var x = x < 0 ? -x: x var arr: [Int] = Array<Int>() var result = 0 while true { // 最后一位 let temp = x % 10 arr.append(temp) x = x / 10 if x == 0 { break } } for (index, value) in arr.enumerated() { result += value * Int(pow(10.0, Double(arr.count - index - 1))) } if result > Int(pow(2.0, 31.0)) { return 0; } result = result * sign return result } } var s = Solution() var result = s.reverse(-123) print(result)

24.241379

75

0.415363

class Solution { func reverse(_ x: Int) -> Int { let sign = x < 0 ? -1: 1 var x = x < 0 ? -x: x var arr: [Int] = Array<Int>() var result = 0 while true { // 最后一位 let temp = x % 10 arr.append(temp) x = x / 10 if x == 0 { break } } for (index, value) in arr.enumerated() { result += value * Int(pow(10.0, Double(arr.count - index - 1))) } if result > Int(pow(2.0, 31.0)) { return 0; } result = result * sign return result } } var s = Solution() var result = s.reverse(-123) print(result)

0

64

22

9be7df6f7474ab0961eec64a862720dbadcace71

17,409

py

Python

my_pybullet_envs/laikago_env_v4.py

jyf588/SimGAN

23283d7b5629f1653567b2437bb28aac1cc17169

[ "Apache-2.0" ]

30

2021-06-16T23:28:58.000Z

2022-03-23T17:20:58.000Z

my_pybullet_envs/laikago_env_v4.py

jyf588/SimGAN

23283d7b5629f1653567b2437bb28aac1cc17169

[ "Apache-2.0" ]

1

2021-06-25T09:21:29.000Z

2021-08-11T23:14:14.000Z

my_pybullet_envs/laikago_env_v4.py

jyf588/SimGAN

23283d7b5629f1653567b2437bb28aac1cc17169

[ "Apache-2.0" ]

8

2021-06-19T12:51:50.000Z

2021-12-23T08:31:10.000Z

# Copyright 2020 Google LLC and Stanford University # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from .laikago import LaikagoBullet from pybullet_utils import bullet_client import pybullet import pybullet_data import time import gym, gym.utils.seeding, gym.spaces import numpy as np from my_pybullet_envs import utils from collections import deque import os import inspect currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))

40.392111

108

0.574473

# Copyright 2020 Google LLC and Stanford University # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from .laikago import LaikagoBullet from pybullet_utils import bullet_client import pybullet import pybullet_data import time import gym, gym.utils.seeding, gym.spaces import numpy as np from my_pybullet_envs import utils from collections import deque import os import inspect currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe()))) class LaikagoBulletEnvV4(gym.Env): metadata = {'render.modes': ['human', 'rgb_array'], 'video.frames_per_second': 50} def __init__(self, render=True, init_noise=True, act_noise=True, obs_noise=True, control_skip=10, max_tar_vel=2.5, energy_weight=0.1, jl_weight=0.5, ab=4.5, q_pen_weight=0.35, acc_pen_weight=0.03, vel_r_weight=4.0, enlarge_act_range=0.0, # during data collection, make pi softer soft_floor_env=False, deform_floor_env=False, low_power_env=False, emf_power_env=False, heavy_leg_env=False, randomization_train=False, randomization_train_addi=False, randomforce_train=False, sysid_data_collection=False, final_test=False ): self.render = render self.init_noise = init_noise self.obs_noise = obs_noise self.act_noise = act_noise self.control_skip = int(control_skip) self._ts = 1. / 500. self.max_tar_vel = max_tar_vel self.energy_weight = energy_weight self.jl_weight = jl_weight self.ab = ab self.q_pen_weight = q_pen_weight self.acc_pen_weight = acc_pen_weight self.vel_r_weight = vel_r_weight self.enlarge_act_range = enlarge_act_range self.soft_floor_env = soft_floor_env self.deform_floor_env = deform_floor_env self.low_power_env = low_power_env self.emf_power_env = emf_power_env self.heavy_leg_env = heavy_leg_env self.randomization_train = randomization_train self.randomization_train_addi = randomization_train_addi if randomization_train_addi: assert randomization_train self.randomforce_train = randomforce_train self.sysid_data_collection = sysid_data_collection self.final_test = final_test self.randomize_params = {} if self.render: self._p = bullet_client.BulletClient(connection_mode=pybullet.GUI) else: self._p = bullet_client.BulletClient() self._p.setAdditionalSearchPath(pybullet_data.getDataPath()) # self._p.setPhysicsEngineParameter(deterministicOverlappingPairs=1) self.np_random = None self.robot = LaikagoBullet(init_noise=self.init_noise, time_step=self._ts, np_random=self.np_random, heavy_leg=self.heavy_leg_env, no_init_vel=self.sysid_data_collection) self.seed(0) # used once temporarily, will be overwritten outside though superclass api self.viewer = None self.timer = 0 self.floor_id = None self.velx = 0 # self.behavior_past_obs_t_idx = [0, 3, 6, 9] # t-3. t-6. t-9 self.behavior_past_obs_t_idx = np.array([0, 4, 8]) # self.behavior_past_obs_t_idx = [0] self.past_obs_array = deque(maxlen=10) self.past_act_array = deque(maxlen=10) self.reset_const = 100 self.reset_counter = self.reset_const # do a hard reset first self.init_state = None obs = self.reset() # and update init obs self.action_dim = len(self.robot.ctrl_dofs) self.act = [0.0] * len(self.robot.ctrl_dofs) self.action_space = gym.spaces.Box(low=np.array([-1.] * self.action_dim), high=np.array([+1.] * self.action_dim)) self.obs_dim = len(obs) # print(self.obs_dim) obs_dummy = np.array([1.12234567] * self.obs_dim) self.observation_space = gym.spaces.Box(low=-np.inf * obs_dummy, high=np.inf * obs_dummy) # self.b2d_feat_select = self.feature_selection_B2D_laika_v3 def reset(self): if self.reset_counter < self.reset_const: self.reset_counter += 1 self._p.restoreState(self.init_state) self.robot.soft_reset(self._p) else: if self.deform_floor_env or self.soft_floor_env or self.sysid_data_collection: self._p.resetSimulation(self._p.RESET_USE_DEFORMABLE_WORLD) # always use hard reset if soft-floor-env # always use hard reset if sysid collection else: self._p.resetSimulation() self.reset_counter = 0 # use soft reset later on self._p.setTimeStep(self._ts) self._p.setGravity(0, 0, -10) self._p.setPhysicsEngineParameter(numSolverIterations=100) self.robot.reset(self._p) if self.soft_floor_env: self.floor_id = self._p.loadURDF( os.path.join(currentdir, 'assets/plane.urdf'), [0, 0, 0.0], useFixedBase=1 ) # reset for ind in self.robot.feet: self._p.changeDynamics(self.robot.go_id, ind, contactDamping=100, contactStiffness=100) self._p.changeDynamics(self.floor_id, -1, contactDamping=50, contactStiffness=100) elif self.deform_floor_env: self.floor_id = self._p.loadURDF( os.path.join(currentdir, 'assets/plane.urdf'), [0, 0, -10.02], useFixedBase=1 ) _ = self._p.loadSoftBody(os.path.join(currentdir, "assets/cube_fat.obj"), basePosition=[7, 0, -5], scale=20, mass=4000., useNeoHookean=0, useBendingSprings=1, useMassSpring=1, springElasticStiffness=60000, springDampingStiffness=150, springDampingAllDirections=1, useSelfCollision=0, frictionCoeff=1.0, useFaceContact=1) else: if self.randomization_train: self.set_randomize_params() self.robot.randomize_robot( self.randomize_params["mass_scale"], self.randomize_params["inertia_scale"], self.randomize_params["power_scale"], self.randomize_params["joint_damping"] ) fric = self.randomize_params["friction"] if self.randomization_train else 0.5 resti = self.randomize_params["restitution"] if self.randomization_train else 0.0 spinfric = self.randomize_params["spinfric"] if self.randomization_train_addi else 0.0 damp = self.randomize_params["damping"] if self.randomization_train_addi else 2000 self.floor_id = self._p.loadURDF( os.path.join(currentdir, 'assets/plane.urdf'), [0, 0, 0.0], useFixedBase=1 ) self._p.changeDynamics(self.floor_id, -1, lateralFriction=fric, restitution=resti, contactStiffness=1.0, contactDamping=damp, spinningFriction=spinfric) for ind in self.robot.feet: self._p.changeDynamics(self.robot.go_id, ind, lateralFriction=1.0, restitution=1.0, contactStiffness=1.0, contactDamping=0.0, spinningFriction=0.0) if self.sysid_data_collection: # try sysID for emf self.emf_power_env = True self.init_state = self._p.saveState() if self.low_power_env: # deprecated self.robot.max_forces = [30.0] * 3 + [15.0] * 3 + [30.0] * 6 if not self.sysid_data_collection: self._p.stepSimulation() # may not be helpful if want to reproduce traj for foot in self.robot.feet: cps = self._p.getContactPoints(self.robot.go_id, self.floor_id, foot, -1) if len(cps) > 0: print("warning") self.timer = 0 self.past_obs_array.clear() self.past_act_array.clear() # # self.normal_forces = np.array([[0., 0, 0, 0]]) # self.tan_forces = np.array([[0., 0, 0, 0]]) obs = self.get_extended_observation() return np.array(obs) def set_randomize_params(self): self.randomize_params = { # robot "mass_scale": self.np_random.uniform(0.8, 1.2, 13), "inertia_scale": self.np_random.uniform(0.5, 1.5, 13), "power_scale": self.np_random.uniform(0.8, 1.2, 12), "joint_damping": self.np_random.uniform(0.2, 2.0, 12), # act/obs latency "act_latency": self.np_random.uniform(0, 0.02), "obs_latency": self.np_random.uniform(0, 0.02), # contact "friction": self.np_random.uniform(0.4, 1.25), "restitution": self.np_random.uniform(0., 0.5), # contact additional # uniform does not make sense for this param # "damping": np.power(10, self.np_random.uniform(1.0, 3.0)) * 5, # "spinfric": self.np_random.uniform(0.1, 0.5), # "damping": np.power(10, self.np_random.uniform(2.0, 3.0)) * 2, # "spinfric": self.np_random.uniform(0.0, 0.2), "damping": np.power(10, self.np_random.uniform(2.0, 3.2)), "spinfric": self.np_random.uniform(0.0, 0.1), } def step(self, a): root_pos, _ = self.robot.get_link_com_xyz_orn(-1) x_0 = root_pos[0] # TODO: parameter space noise. # make pi softer during data collection, different from hidden act_noise below # print(self.enlarge_act_range) a = utils.perturb(a, self.enlarge_act_range, self.np_random) a = np.tanh(a) # ***push in deque the a after tanh utils.push_recent_value(self.past_act_array, a) act_latency = self.randomize_params["act_latency"] if self.randomization_train else 0 a0 = np.array(self.past_act_array[0]) a1 = np.array(self.past_act_array[1]) interp = act_latency / 0.02 a = a0 * (1 - interp) + a1 * interp if self.act_noise: a = utils.perturb(a, 0.05, self.np_random) if self.emf_power_env: _, dq = self.robot.get_q_dq(self.robot.ctrl_dofs) max_force_ratio = np.clip(1 - dq/15., 0, 1) a *= max_force_ratio past_info = self.construct_past_traj_window() _, dq_old = self.robot.get_q_dq(self.robot.ctrl_dofs) for _ in range(self.control_skip): if a is not None: self.act = a self.robot.apply_action(a) if self.randomforce_train: for foot_ind, link in enumerate(self.robot.feet): # first dim represents fz fz = np.random.uniform(-80, 80) # second dim represents fx fx = np.random.uniform(-80, 80) # third dim represents fy fy = np.random.uniform(-80, 80) utils.apply_external_world_force_on_local_point(self.robot.go_id, link, [fx, fy, fz], [0, 0, 0], self._p) self._p.stepSimulation() if self.render: time.sleep(self._ts * 1.5) self.timer += 1 root_pos, _ = self.robot.get_link_com_xyz_orn(-1) x_1 = root_pos[0] self.velx = (x_1 - x_0) / (self.control_skip * self._ts) q, dq = self.robot.get_q_dq(self.robot.ctrl_dofs) reward = self.ab # alive bonus tar = np.minimum(self.timer / 500, self.max_tar_vel) reward += np.minimum(self.velx, tar) * self.vel_r_weight # print("v", self.velx, "tar", tar) reward += -self.energy_weight * np.square(a).sum() # print("act norm", -self.energy_weight * np.square(a).sum()) pos_mid = 0.5 * (self.robot.ll + self.robot.ul) q_scaled = 2 * (q - pos_mid) / (self.robot.ul - self.robot.ll) joints_at_limit = np.count_nonzero(np.abs(q_scaled) > 0.97) reward += -self.jl_weight * joints_at_limit # print("jl", -self.jl_weight * joints_at_limit) # instead pen joint vels, pen joint delta vels (accs) reward += -np.minimum(np.sum(np.abs(dq - dq_old)) * self.acc_pen_weight, 5.0) # print(np.minimum(np.sum(np.abs(dq - dq_old)) * self.dq_pen_weight, 5.0)) weight = np.array([2.0, 1.0, 1.0] * 4) reward += -np.minimum(np.sum(np.square(q - self.robot.init_q) * weight) * self.q_pen_weight, 5.0) y_1 = root_pos[1] reward += -y_1 * 0.5 # print("dev pen", -y_1*0.5) height = root_pos[2] obs = self.get_extended_observation() _, root_orn = self.robot.get_link_com_xyz_orn(-1) rpy = self._p.getEulerFromQuaternion(root_orn) diff = (np.array(rpy) - [1.5708, 0.0, 1.5708]) if self.final_test: # do not terminate as in multi-task it may be moving toward y axis diff[0] = diff[1] = diff[2] = 0.0 # during final testing, terminate more tolerantly, some policy can recover from low height # esp. in deform env where floor can be lower than 0. height_thres = 0.15 if self.final_test else 0.3 not_done = (np.abs(dq) < 90).all() and (height > height_thres) and (np.abs(diff) < 1.2).all() # during testing limit time, since final good policy might go beyond end of mattress if self.final_test and self.timer >= 3500: not_done = False past_info += [self.past_obs_array[0]] # s_t+1 return obs, reward, not not_done, {"sas_window": past_info} def construct_past_traj_window(self): # st, ... st-9, at, ..., at-9 # call this before s_t+1 enters deque # order does not matter as long as it is the same in policy & expert batch # print(list(self.past_obs_array) + list(self.past_act_array)) return list(self.past_obs_array) + list(self.past_act_array) def get_dist(self): return self.robot.get_link_com_xyz_orn(-1)[0][0] def get_ave_dx(self): return self.velx def get_extended_observation(self): obs = self.robot.get_robot_observation(with_vel=False) if self.obs_noise: obs = utils.perturb(obs, 0.1, self.np_random) utils.push_recent_value(self.past_obs_array, obs) obs_latency = self.randomize_params["obs_latency"] if self.randomization_train else 0 obs_all_0 = utils.select_and_merge_from_s_a( s_mt=list(self.past_obs_array), a_mt=list(self.past_act_array), s_idx=self.behavior_past_obs_t_idx, a_idx=np.array([]) ) obs_all_1 = utils.select_and_merge_from_s_a( s_mt=list(self.past_obs_array), a_mt=list(self.past_act_array), s_idx=self.behavior_past_obs_t_idx + 1, a_idx=np.array([]) ) interp = obs_latency / 0.02 obs_all = obs_all_0 * (1 - interp) + obs_all_1 * interp return list(obs_all) def seed(self, seed=None): self.np_random, seed = gym.utils.seeding.np_random(seed) self.robot.np_random = self.np_random # use the same np_randomizer for robot as for env return [seed] def getSourceCode(self): s = inspect.getsource(type(self)) s = s + inspect.getsource(type(self.robot)) return s def cam_track_torso_link(self): distance = 1.5 yaw = 0 root_pos, _ = self.robot.get_link_com_xyz_orn(-1) distance -= root_pos[1] self._p.resetDebugVisualizerCamera(distance, yaw, -20, [root_pos[0], 0.0, 0.1])

16,013

397

23

afa91199f0a53f11d7bdc9266405cc14c87b8d2e

6,411

py

Python

Contest/2019CUMCM/code/model_airline.py

iydon/homework

253d4746528ef62d33eba1de0b90dcb17ec587ed

[ "MIT" ]

8

2019-10-20T08:18:54.000Z

2021-07-11T12:14:56.000Z

Contest/2019CUMCM/code/model_airline.py

iydon/homework

253d4746528ef62d33eba1de0b90dcb17ec587ed

[ "MIT" ]

2

2022-01-13T03:04:10.000Z

2022-03-12T00:49:10.000Z

Contest/2019CUMCM/code/model_airline.py

iydon/homework

253d4746528ef62d33eba1de0b90dcb17ec587ed

[ "MIT" ]

2

2019-11-02T05:46:01.000Z

2020-03-12T23:11:28.000Z

# -*- encode: utf-8 -*- from typing import List, Tuple, Callable import numpy as np from models import Aircraft, Airport, City, Time from settings import time_limit, time_limit, distance_to_weights # Phantom class if __name__ == '__main__': from data import cities airline = Airline(cities, time_limit, distance_to_weights)

27.515021

97

0.519108

# -*- encode: utf-8 -*- from typing import List, Tuple, Callable import numpy as np from models import Aircraft, Airport, City, Time from settings import time_limit, time_limit, distance_to_weights # Phantom class class Airline: pass class Symmetric: pass class Airline: def __init__(self, cities:List[City], time_limit:int, distance_to_weights:Callable): '''Initialize Airline. Arguments: ========== cities: List[City, ...] time_limit: Integer (second) distance_to_weights: Callable Returns: ======== None ''' self.cities = cities self.city_number = len(cities) self.time_limit = time_limit self.distance_to_weights = distance_to_weights self.distances = Symmetric(self.city_number) for ith in range(self.city_number): self.distances[ith, ith] = None for jth in range(ith+1, self.city_number): self.distances[ith, jth] = self.distance_from_ith_jth(ith, jth) def __repr__(self) -> str: '''Return repr(self). ''' return '<Airline with {} path(s)>'.format(len(self)) def __len__(self) -> int: '''Return len(self). ''' return self.distances.nonnone() def __iter__(self) -> iter: '''Return iter(self). ''' for ith in range(len(self.distances)): for jth in range(ith+1, len(self.distances)): if self.distances[ith, jth] is not None: yield self.cities[ith], self.cities[jth] def remove_path_by_time_limit(self): '''Remove path by `time_limit`. Arguments: ========== None Returns: ======== None ''' for ith in range(self.city_number): for jth in range(ith+1, self.city_number): distance = self.distance_from_ith_jth(ith, jth) for airport in self.cities[ith].airports: for aircraft in airport.aircrafts: if aircraft is None: break time = distance/aircraft.speed*Time.MINUTE*Time.HOUR if time < self.time_limit: self.distances[ith, jth] = None break if self.distances[ith, jth] is None: break def normalize_distances_by_distance_to_weights(self): '''Normalize `self.distances` by `distance_to_weights`. Arguments: ========== None Returns: ======== None ''' for ith in range(self.city_number): for jth in range(ith+1, self.city_number): if self.distances[ith, jth] is not None: self.distances[ith, jth] = self.distance_to_weights(self.distances[ith, jth]) def distance_from_ith_jth(self, ith:int, jth:int) -> float: '''Calculate the distance from `ith` city and `jth` city. Arguments: ========== ith: Integer jth: Integer Returns: ======== Float ''' assert all((0<=ith,jth<self.city_number)), 'Length Error' return self.cities[ith].distance_from(self.cities[jth]) class Symmetric: def __init__(self, length:int): '''Symmetric matrix with initial value zero. Arguments: ========== length: Integer Returns: ======== None ''' self.length = length self.value = [[0.0]*(i+1) for i in range(length)] def __repr__(self) -> str: '''Return repr(self). ''' return '<SymmetricMatrix: ({0}x{0})>'.format(self.length) def __iter__(self) -> iter: '''Return iter(self). ''' for row in self.value: for ele in row: yield ele def __len__(self) -> int: '''Return len(self). ''' return self.length def __getitem__(self, index:[int, Tuple[int]]) -> float: '''Return self[index]. ''' assert isinstance(index, (int, Tuple)), 'Type Error' if isinstance(index, int): return self.__getitem__(self.idx_1d_to_2d(index)) assert len(index)==2, 'Type Error' ith, jth = index if ith < jth: return self.__getitem__((jth, ith)) return self.value[ith][jth] def __setitem__(self, index:[int, Tuple[int]], value:float): '''Set self[index] to value. ''' assert isinstance(index, (int, Tuple)), 'Type Error' if isinstance(index, int): return self.__setitem__(self.idx_1d_to_2d(index), value) assert len(index)==2, 'Length Error' ith, jth = index if ith < jth: return self.__setitem__((jth, ith), value) self.value[ith][jth] = value @property def T(self) -> Airline: '''Transpose.''' return self @property def shape(self) -> Tuple[int]: '''Shape of `self`.''' return self.length, self.length def nonnone(self) -> int: '''Count the number of non-None elements. ''' count = 0 for value in self: if value is not None: count += 1 return count def densify(self) -> np.matrix: '''Densify the symmetric matrix. Arguments: ========== None Returns: ======== numpy.matrix ''' result = np.zeros((self.length, ) * 2) for ith in range(self.length): result[ith, ith] = self.value[ith][ith] for jth in range(ith+1, self.length): result[ith, jth] = self.value[jth][ith] result[jth, ith] = self.value[jth][ith] return result def idx_1d_to_2d(self, idx:int) -> Tuple[int]: '''Convert 1d `idx` to 2d. Arguments: ========== idx: Integer Returns: ======== Tuple[Integer, Integer] ''' row = idx % self.length col = idx // self.length return row, col if __name__ == '__main__': from data import cities airline = Airline(cities, time_limit, distance_to_weights)

0

5,980

90

6c05ac6238b169fb230cd4810727fed0baba80f5

1,032

py

Python

setup.py

nokia-wroclaw/innovativeproject-django-sourcerer

955f360e98826c736ae6b2072e304a26ca3fffb3

[ "MIT" ]

2

2020-03-11T10:54:43.000Z

2020-05-22T11:05:53.000Z

setup.py

nokia-wroclaw/innovativeproject-django-sourcerer

955f360e98826c736ae6b2072e304a26ca3fffb3

[ "MIT" ]

8

2020-03-31T14:15:44.000Z

2021-09-22T18:42:44.000Z

setup.py

nokia-wroclaw/innovativeproject-django-sourcerer

955f360e98826c736ae6b2072e304a26ca3fffb3

[ "MIT" ]

null

import setuptools with open("README.md", "r") as fh: long_description = fh.read() setuptools.setup( name='django_sourcerer', version='2.1', author='Cem Arslan, Kadir Kocak, Ugur Dogus Hamarat, Cagatay Em, Farid Murmadov, Burak Karaca', author_email="[email protected]", description="Django app that import and correlating data from external sources.", long_description=long_description, long_description_content_type="text/markdown", url="https://github.com/nokia-wroclaw/innovativeproject-django-sourcerer", packages=setuptools.find_packages(), install_requires=[ 'django == 3.0.7', 'djangorestframework == 3.11.0', 'requests == 2.23.0', 'pyyaml == 5.3.1', 'pandas == 1.0.3', 'pytest == 5.4.1', 'requests-mock == 1.7.0', ], classifiers=[ "Programming Language :: Python :: 3", "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", ], python_requires='>=3.6', )

33.290323

99

0.630814

import setuptools with open("README.md", "r") as fh: long_description = fh.read() setuptools.setup( name='django_sourcerer', version='2.1', author='Cem Arslan, Kadir Kocak, Ugur Dogus Hamarat, Cagatay Em, Farid Murmadov, Burak Karaca', author_email="[email protected]", description="Django app that import and correlating data from external sources.", long_description=long_description, long_description_content_type="text/markdown", url="https://github.com/nokia-wroclaw/innovativeproject-django-sourcerer", packages=setuptools.find_packages(), install_requires=[ 'django == 3.0.7', 'djangorestframework == 3.11.0', 'requests == 2.23.0', 'pyyaml == 5.3.1', 'pandas == 1.0.3', 'pytest == 5.4.1', 'requests-mock == 1.7.0', ], classifiers=[ "Programming Language :: Python :: 3", "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", ], python_requires='>=3.6', )

0

43461cd5e70eb68bd540af320f66020a19b0538a

5,187

py

Python

stackimpact/reporters/cpu_reporter.py

cielo24/stackimpact-python

ac98f0c4d88ce31ae4baf54f36fb76f20cedf852

[ "BSD-3-Clause" ]

null

stackimpact/reporters/cpu_reporter.py

cielo24/stackimpact-python

ac98f0c4d88ce31ae4baf54f36fb76f20cedf852

[ "BSD-3-Clause" ]

null

stackimpact/reporters/cpu_reporter.py

cielo24/stackimpact-python

ac98f0c4d88ce31ae4baf54f36fb76f20cedf852

[ "BSD-3-Clause" ]

null

from __future__ import division import os import sys import time import threading import re import signal from ..runtime import min_version, runtime_info from ..profiler_scheduler import ProfilerScheduler from ..metric import Metric from ..metric import Breakdown from ..frame import Frame

27.737968

145

0.613071

from __future__ import division import os import sys import time import threading import re import signal from ..runtime import min_version, runtime_info from ..profiler_scheduler import ProfilerScheduler from ..metric import Metric from ..metric import Breakdown from ..frame import Frame class CPUReporter: SAMPLING_RATE = 0.01 MAX_TRACEBACK_SIZE = 25 # number of frames def __init__(self, agent): self.agent = agent self.setup_done = False self.started = False self.profiler_scheduler = None self.profile = None self.profile_lock = threading.Lock() self.profile_duration = 0 self.prev_signal_handler = None self.handler_active = False def setup(self): if self.agent.get_option('cpu_profiler_disabled'): return if runtime_info.OS_WIN: self.agent.log('CPU profiler is not available on Windows.') return def _sample(signum, signal_frame): if self.handler_active: return self.handler_active = True with self.profile_lock: try: self.process_sample(signal_frame) signal_frame = None except Exception: self.agent.exception() self.handler_active = False self.prev_signal_handler = signal.signal(signal.SIGPROF, _sample) self.setup_done = True def start(self): if self.agent.get_option('cpu_profiler_disabled'): return if not runtime_info.OS_LINUX and not runtime_info.OS_DARWIN: self.agent.log('CPU profiler is only supported on Linux and OS X.') return if not self.setup_done: return if self.started: return; self.started = True self.reset() self.profiler_scheduler = ProfilerScheduler(self.agent, 10, 2, 120, self.record, self.report) self.profiler_scheduler.start() def stop(self): if not self.started: return self.started = False self.profiler_scheduler.stop() def destroy(self): if not self.setup_done: return signal.setitimer(signal.ITIMER_PROF, 0) signal.signal(signal.SIGPROF, self.prev_signal_handler) def reset(self): with self.profile_lock: self.profile = Breakdown('root') self.profile_duration = 0 def record(self, duration): if self.agent.config.is_profiling_disabled(): return self.agent.log('Activating CPU profiler.') signal.setitimer(signal.ITIMER_PROF, self.SAMPLING_RATE, self.SAMPLING_RATE) time.sleep(duration) signal.setitimer(signal.ITIMER_PROF, 0) self.agent.log('Deactivating CPU profiler.') self.profile_duration += duration self.agent.log('CPU profiler CPU overhead per activity second: {0} seconds'.format(self.profile._overhead / self.profile_duration)) def process_sample(self, signal_frame): if self.profile: start = time.clock() if signal_frame: stack = self.recover_stack(signal_frame) if stack: self.update_profile(self.profile, stack) stack = None self.profile._overhead += (time.clock() - start) def recover_stack(self, signal_frame): stack = [] depth = 0 while signal_frame is not None and depth <= self.MAX_TRACEBACK_SIZE: if signal_frame.f_code and signal_frame.f_code.co_name and signal_frame.f_code.co_filename: func_name = signal_frame.f_code.co_name filename = signal_frame.f_code.co_filename lineno = signal_frame.f_lineno if self.agent.frame_cache.is_agent_frame(filename): return None frame = Frame(func_name, filename, lineno) stack.append(frame) signal_frame = signal_frame.f_back depth += 1 if len(stack) == 0: return None else: return stack def update_profile(self, profile, stack): current_node = profile current_node.increment(0, 1) for frame in reversed(stack): current_node = current_node.find_or_add_child(str(frame)) current_node.increment(0, 1) def report(self): if self.agent.config.is_profiling_disabled(): return if self.profile_duration == 0: return with self.profile_lock: self.profile.evaluate_percent(self.profile_duration / self.SAMPLING_RATE) self.profile.filter(2, 1, 100) metric = Metric(self.agent, Metric.TYPE_PROFILE, Metric.CATEGORY_CPU_PROFILE, Metric.NAME_MAIN_THREAD_CPU_USAGE, Metric.UNIT_PERCENT) measurement = metric.create_measurement(Metric.TRIGGER_TIMER, self.profile.measurement, None, self.profile) self.agent.message_queue.add('metric', metric.to_dict()) self.reset()

4,481

389

23

9f072760e795b01d4f2896bcd8e1d73470431328

8,845

py

Python

survol/class_type_all.py

AugustinMascarelli/survol

7a822900e82d1e6f016dba014af5741558b78f15

[ "BSD-3-Clause" ]

null

survol/class_type_all.py

AugustinMascarelli/survol

7a822900e82d1e6f016dba014af5741558b78f15

[ "BSD-3-Clause" ]

null

survol/class_type_all.py

AugustinMascarelli/survol

7a822900e82d1e6f016dba014af5741558b78f15

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python """ Generalised class: Displays data sources for a class """ import os import sys import lib_util import lib_common try: import lib_wbem wbemOk = True except ImportError: wbemOk = False import lib_wmi from lib_properties import pc # Now, adds the base classes of this one, at least one one level. # Adds the list of base classes. Returns the list of pairs (name node), # so it can be matched againt another inheritance tree. # Adds a WMI node and other stuff, for the class name. # entity_type = "CIM_Process", "Win32_Service" etc... # This might happen at an intermediary level, with inheritance (To be implemented). if __name__ == '__main__': Main()

38.290043

157

0.758508

#!/usr/bin/env python """ Generalised class: Displays data sources for a class """ import os import sys import lib_util import lib_common try: import lib_wbem wbemOk = True except ImportError: wbemOk = False import lib_wmi from lib_properties import pc # Now, adds the base classes of this one, at least one one level. def WbemAddBaseClass(grph,connWbem,wbemNode,entity_host, wbemNamespace, entity_type): wbemKlass = lib_wbem.WbemGetClassObj(connWbem,entity_type,wbemNamespace) if not wbemKlass: return ( None, None ) superKlassName = wbemKlass.superclass # sys.stderr.write("WBEM superKlassName=%s\n" % superKlassName) # An empty string or None. if not superKlassName: return ( None, None ) # TODO: Should be changed, this is slow and inconvenient. wbemSuperUrlsList = lib_wbem.GetWbemUrls( entity_host, wbemNamespace, superKlassName, "" ) if not wbemSuperUrlsList: return ( None, None ) # TODO: Which one should we take, http or https ??? wbemSuperUrl = wbemSuperUrlsList[0][0] DEBUG("WBEM wbemSuperUrl=%s", wbemSuperUrl) wbemSuperNode = lib_common.NodeUrl(wbemSuperUrl) grph.add( ( wbemSuperNode, pc.property_cim_subclass, wbemNode ) ) klaDescrip = lib_wbem.WbemClassDescription(connWbem,superKlassName,wbemNamespace) if not klaDescrip: klaDescrip = "Undefined class %s %s" % ( wbemNamespace, superKlassName ) grph.add( ( wbemSuperNode, pc.property_information, lib_common.NodeLiteral(klaDescrip ) ) ) return ( wbemSuperNode, superKlassName ) # Adds the list of base classes. Returns the list of pairs (name node), # so it can be matched againt another inheritance tree. def WbemAddBaseClasses(grph,connWbem,wbemNode,entity_host, wbemNamespace, entity_type): pairNameNode = dict() while wbemNode: ( wbemSuperNode, superClass ) = WbemAddBaseClass(grph,connWbem,wbemNode,entity_host, wbemNamespace, entity_type) pairNameNode[entity_type] = wbemNode wbemNode = wbemSuperNode entity_type = superClass return pairNameNode def CreateWbemNode(grph,rootNode,entity_host, nameSpace, className, entity_id): wbemNamespace = nameSpace.replace("\\","/") wbem_servers_desc_list = lib_wbem.GetWbemUrls( entity_host, wbemNamespace, className, entity_id ) # If there are no servers. pairNameNode = None for url_server in wbem_servers_desc_list: wbemNode = lib_common.NodeUrl(url_server[0]) grph.add( ( rootNode, pc.property_wbem_data, wbemNode ) ) wbemHostNode = lib_common.gUriGen.HostnameUri( url_server[1] ) grph.add( ( wbemNode, pc.property_host, wbemHostNode ) ) # TODO: Add a Yawn server ?? grph.add( ( wbemNode, pc.property_wbem_server, lib_common.NodeLiteral( url_server[1] ) ) ) # Now adds the description of the class. connWbem = lib_wbem.WbemConnection(entity_host) klaDescrip = lib_wbem.WbemClassDescription(connWbem,className,wbemNamespace) okWbemClass = True if not klaDescrip: okWbemClass = False klaDescrip = "Undefined class %s %s" % ( wbemNamespace, className ) grph.add( ( wbemNode, pc.property_information, lib_common.NodeLiteral(klaDescrip) ) ) # Maybe this class is not Known in WBEM. try: pairNameNode = WbemAddBaseClasses(grph,connWbem,wbemNode,entity_host, nameSpace, className) except: pairNameNode = None if okWbemClass and wbemOk and nameSpace != "" and entity_host != "": namespaceUrl = lib_wbem.NamespaceUrl(nameSpace,entity_host,className) namespaceNode = lib_common.NodeUrl( namespaceUrl ) grph.add( ( wbemNode, pc.property_information, namespaceNode ) ) # TODO: This is a bit absurd because we return just one list. return pairNameNode # Adds a WMI node and other stuff, for the class name. def CreateWmiNode(grph,rootNode,entity_host, nameSpace, className, entity_id): wmiurl = lib_wmi.GetWmiUrl( entity_host, nameSpace, className, entity_id ) if wmiurl is None: return # There might be "http:" or the port number around the host. # hostOnly = lib_util.EntHostToIp(entity_host) # sys.stderr.write("entity_host=%s nameSpace=%s entity_type=%s className=%s wmiurl=%s\n" % ( entity_host, nameSpace, entity_type, className, str(wmiurl) ) ) wmiNode = lib_common.NodeUrl(wmiurl) grph.add( ( rootNode, pc.property_wmi_data, wmiNode ) ) # TODO: Shame, we just did it in GetWmiUrl. ipOnly = lib_util.EntHostToIp(entity_host) try: # It simply returns if it cannot connect. connWmi = lib_wmi.WmiConnect(ipOnly,nameSpace,False) if not connWmi: raise Exception("Cannot connect") lib_wmi.WmiAddClassQualifiers( grph, connWmi, wmiNode, className, False ) # Now displays the base classes, to the top of the inheritance tree. pairNameNode = lib_wmi.WmiAddBaseClasses(grph,connWmi,wmiNode,ipOnly, nameSpace, className) except Exception: pairNameNode = None # TODO: If the class is not defined, maybe do not display it. exc = sys.exc_info()[1] errMsg = "WMI connection %s: %s" % (ipOnly,str(exc)) grph.add( ( wmiNode, lib_common.MakeProp("WMI Error"), lib_common.NodeLiteral(errMsg) ) ) urlNameSpace = lib_wmi.NamespaceUrl(nameSpace,ipOnly,className) # sys.stderr.write("entity_host=%s urlNameSpace=%s\n"%(entity_host,urlNameSpace)) grph.add( ( wmiNode, pc.property_information, lib_common.NodeUrl(urlNameSpace) ) ) return pairNameNode # entity_type = "CIM_Process", "Win32_Service" etc... # This might happen at an intermediary level, with inheritance (To be implemented). def AddCIMClasses(grph,rootNode,entity_host, nameSpace, className, entity_id): # Maybe some of these servers are not able to display anything about this object. pairNameNodeWbem = None if wbemOk: if lib_wbem.ValidClassWbem(className): pairNameNodeWbem = CreateWbemNode(grph,rootNode,entity_host, nameSpace, className, entity_id) pairNameNodeWmi = None if lib_wmi.ValidClassWmi(className): pairNameNodeWmi = CreateWmiNode(grph,rootNode,entity_host, nameSpace, className, entity_id) # Match the two inheritance trees. if pairNameNodeWbem and pairNameNodeWmi: for ( baseClsNam, nodeWbem ) in lib_util.six_iteritems( pairNameNodeWbem ): try: nodeWmi = pairNameNodeWmi[baseClsNam] except KeyError: continue nodeClsAll = lib_util.EntityClassNode( baseClsNam, nameSpace, entity_host, "WBEM ou WMI" ) grph.add( ( nodeClsAll, pc.property_wbem_data, nodeWbem)) grph.add( ( nodeClsAll, pc.property_wmi_data, nodeWmi)) def CreateOurNode(grph,rootNode,entity_host, nameSpace, className, entity_id): # This try to find a correct url for an entity type, without an entity id. # At the moment, we just expect a file called "enumerate_<entity>.py" enumerateScript = "enumerate_" + className + ".py" # sys.stderr.write("enumerateScript=%s\n" % enumerateScript) baseDir = lib_util.gblTopScripts + "/sources_types" # TODO: This is absurd !!! Why looping, because the filename is already known !?!? for dirpath, dirnames, filenames in os.walk( baseDir ): # sys.stderr.write("dirpath=%s\n" % dirpath) for filename in [f for f in filenames if f == enumerateScript ]: shortDir = dirpath[ len(lib_util.gblTopScripts) : ] fullScriptNam = os.path.join(shortDir, filename).replace('\\','/') DEBUG("fullScriptNam=%s", fullScriptNam) # TODO: Maybe remove the beginning of the file. localClassUrl = lib_util.ScriptizeCimom( fullScriptNam, className, entity_host ) localClassNode = lib_common.NodeUrl( localClassUrl ) grph.add( ( rootNode, pc.property_directory, localClassNode ) ) def Main(): # This should be able to process remote hosts because it calls scripts which can access remote data. cgiEnv = lib_common.CgiEnv(can_process_remote = True) ( nameSpace, className, entity_type ) = cgiEnv.get_namespace_type() # If nameSpace is not provided, it is set to "root/CIMV2" by default. if not className: lib_common.ErrorMessageHtml("Class name should not be empty") # Just in case ... if nameSpace == "/": nameSpace = "" entity_host = cgiEnv.GetHost() entity_id = cgiEnv.m_entity_id # QUERY_STRING=xid=http%3A%2F%2F192.168.1.88%3A5988%2Froot%2FPG_Internal%3APG_WBEMSLPTemplate DEBUG("class_type_all entity_host=%s entity_id=%s", entity_host, entity_id ) grph = cgiEnv.GetGraph() rootNode = lib_util.RootUri() objtypeNode = lib_common.NodeUrl( lib_util.uriRoot + '/objtypes.py' ) grph.add( ( rootNode, pc.property_rdf_data_nolist2, objtypeNode ) ) # This displays the documentation of the Python module of this entity class. entity_module = lib_util.GetEntityModule(className) entDoc = entity_module.__doc__ if entDoc: entDoc = entDoc.strip() grph.add( ( rootNode, pc.property_information, lib_common.NodeLiteral(entDoc) ) ) CreateOurNode(grph,rootNode,entity_host, nameSpace, className, entity_id) # Do this for each intermediary entity type (Between slashes). AddCIMClasses(grph,rootNode,entity_host, nameSpace, className, entity_id) cgiEnv.OutCgiRdf("LAYOUT_RECT_TB") if __name__ == '__main__': Main()

8,003

0

157

ea058d7fe6c4f36a7c2cc59a5c7433969c008b04

2,022

py

Python

main.py

vlameiras/poe-trade-scraper

bffed681973045fb0e555fe5cfb0491bacb36b74

[ "MIT" ]

8

2017-08-23T09:11:22.000Z

2021-12-10T10:28:32.000Z

main.py

vlameiras/poe-trade-scraper

bffed681973045fb0e555fe5cfb0491bacb36b74

[ "MIT" ]

1

2018-01-02T09:25:39.000Z

main.py

vlameiras/poe-trade-scraper

bffed681973045fb0e555fe5cfb0491bacb36b74

[ "MIT" ]

3

2018-01-01T14:36:29.000Z

2020-01-26T22:31:41.000Z

import websocket import threading import time import requests from bs4 import BeautifulSoup import pygame import pyperclip import settings new_id = -1 poe_trade_url = None if __name__ == "__main__": poe_trade_url_ini = input("Please enter your poe.trade URL: ") poe_trade_url_split = poe_trade_url_ini.split("search/", 1)[1] poe_trade_url = poe_trade_url_split.split("/live",1)[0] websocket.enableTrace(False) ws = websocket.WebSocketApp(settings.WS_URL + poe_trade_url, on_message = on_message, on_error = on_error, on_close = on_close) ws.run_forever()

39.647059

308

0.602868

import websocket import threading import time import requests from bs4 import BeautifulSoup import pygame import pyperclip import settings new_id = -1 poe_trade_url = None def on_message(ws, message): global new_id global poe_trade_url payload = {'id': new_id} r = requests.post(settings.SEARCH_URL + poe_trade_url + "/live", data=payload, headers={'Content-Type': 'application/x-www-form-urlencoded'}) new_id = r.json()['newid'] if 'data' in r.json(): html_doc = r.json()['data'] soup = BeautifulSoup(html_doc, 'html.parser') items = soup.find_all("tbody", { "class" : "item" }) pygame.mixer.init() pygame.mixer.music.load("beep.wav") pygame.mixer.music.play() for item in items: pyperclip.copy('@'+item.get('data-ign') + ' Hi, I would like to buy your ' + item.get('data-name') + ' listed for ' + item.get('data-buyout') + ' in ' + item.get('data-league')+' (stash tab \"' + item.get('data-tab')+ '\"; position: left ' + item.get('data-x')+ ', top ' +item.get('data-y') +')') #should put some placeholders instead print('@'+item.get('data-ign') + ' Hi, I would like to buy your ' + item.get('data-name') + ' listed for ' + item.get('data-buyout') + ' in ' + item.get('data-league')+' (stash tab \"' + item.get('data-tab')+ '\"; position: left ' + item.get('data-x')+ ', top ' +item.get('data-y') +')') def on_error(ws, error): print(error) def on_close(ws): print("### closed ###") if __name__ == "__main__": poe_trade_url_ini = input("Please enter your poe.trade URL: ") poe_trade_url_split = poe_trade_url_ini.split("search/", 1)[1] poe_trade_url = poe_trade_url_split.split("/live",1)[0] websocket.enableTrace(False) ws = websocket.WebSocketApp(settings.WS_URL + poe_trade_url, on_message = on_message, on_error = on_error, on_close = on_close) ws.run_forever()

1,281

0

69

d28096553f4f5e1996a89c9a8ad796da77af7e82

6,325

py

Python

lib/surface/storage/buckets/notifications/create.py

google-cloud-sdk-unofficial/google-cloud-sdk

2a48a04df14be46c8745050f98768e30474a1aac

[ "Apache-2.0" ]

2

2019-11-10T09:17:07.000Z

2019-12-18T13:44:08.000Z

lib/surface/storage/buckets/notifications/create.py

google-cloud-sdk-unofficial/google-cloud-sdk

2a48a04df14be46c8745050f98768e30474a1aac

[ "Apache-2.0" ]

null

lib/surface/storage/buckets/notifications/create.py

google-cloud-sdk-unofficial/google-cloud-sdk

2a48a04df14be46c8745050f98768e30474a1aac

[ "Apache-2.0" ]

1

2020-07-25T01:40:19.000Z

# -*- coding: utf-8 -*- # # Copyright 2021 Google LLC. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Implementation of create command for notifications.""" from __future__ import absolute_import from __future__ import division from __future__ import unicode_literals import textwrap from googlecloudsdk.calliope import base @base.Hidden class Create(base.Command): """Create a notification config on a bucket.""" detailed_help = { 'DESCRIPTION': """ *{command}* creates a notification config on a bucket, establishing a flow of event notifications from Cloud Storage to a Cloud Pub/Sub topic. As part of creating this flow, it also verifies that the destination Cloud Pub/Sub topic exists, creating it if necessary, and verifies that the Cloud Storage bucket has permission to publish events to that topic, granting the permission if necessary. If a destination Cloud Pub/Sub topic is not specified with the `-t` flag, Cloud Storage chooses a topic name in the default project whose ID is the same as the bucket name. For example, if the default project ID specified is `default-project` and the bucket being configured is `gs://example-bucket`, the create command uses the Cloud Pub/Sub topic `projects/default-project/topics/example-bucket`. In order to enable notifications, your project's [Cloud Storage service agent](https://cloud.google.com/storage/docs/projects#service-accounts) must have the IAM permission "pubsub.topics.publish". This command checks to see if the destination Cloud Pub/Sub topic grants the service agent this permission. If not, the create command attempts to grant it. A bucket can have up to 100 total notification configurations and up to 10 notification configurations set to trigger for a specific event. """, 'EXAMPLES': """ Begin sending notifications of all changes to the bucket `example-bucket` to the Cloud Pub/Sub topic `projects/default-project/topics/example-bucket`: $ {command} -f json gs://example-bucket The same as above, but specifies the destination topic ID `files-to-process` in the default project: $ {command} -f json -t files-to-process gs://example-bucket The same as above, but specifies a Cloud Pub/Sub topic belonging to the specific cloud project `example-project`: $ {command} -f json \ -t projects/example-project/topics/files-to-process gs://example-bucket Create a notification config that only sends an event when a new object has been created: $ {command} -f json -e OBJECT_FINALIZE gs://example-bucket Create a topic and notification config that only sends an event when an object beginning with `photos/` is affected: $ {command} -p photos/ gs://example-bucket """, } @staticmethod

40.806452

100

0.66087

# -*- coding: utf-8 -*- # # Copyright 2021 Google LLC. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Implementation of create command for notifications.""" from __future__ import absolute_import from __future__ import division from __future__ import unicode_literals import textwrap from googlecloudsdk.calliope import base @base.Hidden class Create(base.Command): """Create a notification config on a bucket.""" detailed_help = { 'DESCRIPTION': """ *{command}* creates a notification config on a bucket, establishing a flow of event notifications from Cloud Storage to a Cloud Pub/Sub topic. As part of creating this flow, it also verifies that the destination Cloud Pub/Sub topic exists, creating it if necessary, and verifies that the Cloud Storage bucket has permission to publish events to that topic, granting the permission if necessary. If a destination Cloud Pub/Sub topic is not specified with the `-t` flag, Cloud Storage chooses a topic name in the default project whose ID is the same as the bucket name. For example, if the default project ID specified is `default-project` and the bucket being configured is `gs://example-bucket`, the create command uses the Cloud Pub/Sub topic `projects/default-project/topics/example-bucket`. In order to enable notifications, your project's [Cloud Storage service agent](https://cloud.google.com/storage/docs/projects#service-accounts) must have the IAM permission "pubsub.topics.publish". This command checks to see if the destination Cloud Pub/Sub topic grants the service agent this permission. If not, the create command attempts to grant it. A bucket can have up to 100 total notification configurations and up to 10 notification configurations set to trigger for a specific event. """, 'EXAMPLES': """ Begin sending notifications of all changes to the bucket `example-bucket` to the Cloud Pub/Sub topic `projects/default-project/topics/example-bucket`: $ {command} -f json gs://example-bucket The same as above, but specifies the destination topic ID `files-to-process` in the default project: $ {command} -f json -t files-to-process gs://example-bucket The same as above, but specifies a Cloud Pub/Sub topic belonging to the specific cloud project `example-project`: $ {command} -f json \ -t projects/example-project/topics/files-to-process gs://example-bucket Create a notification config that only sends an event when a new object has been created: $ {command} -f json -e OBJECT_FINALIZE gs://example-bucket Create a topic and notification config that only sends an event when an object beginning with `photos/` is affected: $ {command} -p photos/ gs://example-bucket """, } @staticmethod def Args(parser): parser.add_argument( 'url', help=('The url of the bucket for which the notification config' ' must be created.')) parser.add_argument( '-e', '--event-type', choices={ 'OBJECT_FINALIZE': 'An object has been created.', 'OBJECT_METADATA_UPDATE': 'The metadata of an object has changed.', 'OBJECT_DELETE': 'An object has been permanently deleted.', 'OBJECT_ARCHIVE': ('A live version of an object has' ' become a noncurrent version.'), }, help=textwrap.dedent("""\ Specify an event type filter for this notification config. Cloud Storage only sends notifications of this type. You may specify this parameter multiple times to allow multiple event types. If not specified, Cloud Storage sends notifications for all event types.""")) parser.add_argument( '-f', '--payload-format', choices={ 'json': 'Payload matches the object metadata for the JSON API.', 'none': 'No payload.', }, help=textwrap.dedent("""\ Specifies the payload format of notification messages. Notification details are available in the message attributes."""), required=True) parser.add_argument( '-m', '--metadata', help=textwrap.dedent("""\ Specifies a key:value attribute that is appended to the set of attributes sent to Cloud Pub/Sub for all events associated with this notification config. You may specify this parameter multiple times to set multiple attributes.""")) parser.add_argument( '-p', '--prefix', help=textwrap.dedent("""\ Specifies a prefix path filter for this notification config. Cloud Storage only sends notifications for objects in this bucket whose names begin with the specified prefix.""")) parser.add_argument( '-s', '--skip', help=textwrap.dedent("""\ Skips creation and permission assignment of the Cloud Pub/Sub topic. This is useful if the caller does not have permission to access the topic in question, or if the topic already exists and has the appropriate publish permission assigned.""")) parser.add_argument( '-t', '--topic', help=textwrap.dedent("""\ The Cloud Pub/Sub topic to which notifications should be sent. If not specified, this command chooses a topic whose project is your default project and whose ID is the same as the Cloud Storage bucket name.""")) def Run(self, args): raise NotImplementedError

2,798

0

49

6ae278c26882f05c348f1ec4016ef5b9ac08e441

1,751

py

Python

manager/logger.py

PlatonaM/lopco-job-manager

3286b1d6ac0c322ef525dcde6a5f026db0e5d2e3

[ "Apache-2.0" ]

null

manager/logger.py

PlatonaM/lopco-job-manager

3286b1d6ac0c322ef525dcde6a5f026db0e5d2e3

[ "Apache-2.0" ]

null

manager/logger.py

PlatonaM/lopco-job-manager

3286b1d6ac0c322ef525dcde6a5f026db0e5d2e3

[ "Apache-2.0" ]

null

""" Copyright 2020 InfAI (CC SES) Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ __all__ = ("getLogger", "initLogger") from .configuration import conf import simple_env_var import logging logging_levels = { 'info': logging.INFO, 'warning': logging.WARNING, 'error': logging.ERROR, 'critical': logging.CRITICAL, 'debug': logging.DEBUG } msg_fmt = '%(asctime)s - %(levelname)s: [%(name)s] %(message)s' date_fmt = '%m.%d.%Y %I:%M:%S %p' handler = logging.StreamHandler() handler.setFormatter(logging.Formatter(fmt=msg_fmt, datefmt=date_fmt)) conf_logger = logging.getLogger("simple-env-var") conf_logger.addHandler(handler) conf_logger.setLevel(logging.INFO) kvs_logger = logging.getLogger("snorkels") kvs_logger.addHandler(handler) kvs_logger.setLevel(logging.INFO) simple_env_var.loadConfig(conf) logger = logging.getLogger("job-manager") logger.propagate = False logger.addHandler(handler)

25.014286

75

0.728726

""" Copyright 2020 InfAI (CC SES) Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ __all__ = ("getLogger", "initLogger") from .configuration import conf import simple_env_var import logging logging_levels = { 'info': logging.INFO, 'warning': logging.WARNING, 'error': logging.ERROR, 'critical': logging.CRITICAL, 'debug': logging.DEBUG } class LoggerError(Exception): pass msg_fmt = '%(asctime)s - %(levelname)s: [%(name)s] %(message)s' date_fmt = '%m.%d.%Y %I:%M:%S %p' handler = logging.StreamHandler() handler.setFormatter(logging.Formatter(fmt=msg_fmt, datefmt=date_fmt)) conf_logger = logging.getLogger("simple-env-var") conf_logger.addHandler(handler) conf_logger.setLevel(logging.INFO) kvs_logger = logging.getLogger("snorkels") kvs_logger.addHandler(handler) kvs_logger.setLevel(logging.INFO) simple_env_var.loadConfig(conf) logger = logging.getLogger("job-manager") logger.propagate = False logger.addHandler(handler) def initLogger(level): if level not in logging_levels.keys(): err = "unknown log level '{}'".format(level) raise LoggerError(err) logger.setLevel(logging_levels[level]) def getLogger(name: str) -> logging.Logger: return logger.getChild(name)

226

17

69

831480df538b5c1257edf6b57341639a13339728

173

py

Python

boa3_test/test_sc/interop_test/contract/GasScriptHashCantAssign.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

25

2020-07-22T19:37:43.000Z

2022-03-08T03:23:55.000Z

boa3_test/test_sc/interop_test/contract/GasScriptHashCantAssign.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

419

2020-04-23T17:48:14.000Z

2022-03-31T13:17:45.000Z

boa3_test/test_sc/interop_test/contract/GasScriptHashCantAssign.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

15

2020-05-21T21:54:24.000Z

2021-11-18T06:17:24.000Z

from boa3.builtin.interop.contract import GAS from boa3.builtin.type import UInt160

19.222222

45

0.734104

from boa3.builtin.interop.contract import GAS from boa3.builtin.type import UInt160 def Main(example: UInt160) -> UInt160: global GAS GAS = example return GAS

65

0

23

3d036d04b9c1f69c6e1283cf42a7ebda73420377

2,976

py

Python

tests/sqpdfo_swap_in_Y_test.py

DLR-SC/sqpdfo

ae3213764fdd8d0d0a05bcc3d13be63d811a0a37

[ "BSD-3-Clause" ]

10

2020-03-03T21:56:01.000Z

2022-03-29T08:36:01.000Z

tests/sqpdfo_swap_in_Y_test.py

DLR-SC/sqpdfo

ae3213764fdd8d0d0a05bcc3d13be63d811a0a37

[ "BSD-3-Clause" ]

6

2020-03-03T22:02:41.000Z

2021-11-18T12:31:00.000Z

tests/sqpdfo_swap_in_Y_test.py

DLR-SC/sqpdfo

ae3213764fdd8d0d0a05bcc3d13be63d811a0a37

[ "BSD-3-Clause" ]

3

2021-02-17T14:43:30.000Z

2022-03-05T08:46:48.000Z

# -*- coding: utf-8 -*- """ Created on Fri Nov 14 18:53:38 2014 % TESTS : % Y = [ 0 1 0 2 1 0 ; 0 0 1 0 0.01 2 ]; ind_Y = [1 2 3 4 5 6]; % fY = [2 5 1 3 2 6]; % [QZ,RZ,xbase,scale] = bcdfo_build_QR_of_Y( Y, 0, 0, 1, 1, 1e15 ); % Z = QZ*RZ; % [ QZ, RZ, Y, xbase, scale ] = sqpdfo_swap_in_Y( 1, 3, QZ, RZ, Y, ind_Y, ... % fY, [],[],xbase, 0, scale, 0, 1, 1, 1e15 ) % [ QZ, RZ, Y, xbase, scale ] = sqpdfo_swap_in_Y( 1, 3, QZ, RZ, Y, ind_Y, ... % fY, [],[],xbase, 0, scale, 0, 1, 1, 1e15 ) % norm( Z - QZ*RZ) % should give something very small. % % The same holds for the scaled version: % Y = [ 0 1 0 2 1 0 ; 0 0 1 0 0.01 2 ]; ind_Y = [1 2 3 4 5 6]; % fY = [2 5 1 3 2 6]; % [QZ,RZ,xbase,scale] = bcdfo_build_QR_of_Y( Y, 0, 1, 1, 1, 1e15 ); % Z = QZ*RZ; % [ QZ, RZ, Y, xbase, scale ] = sqpdfo_swap_in_Y( 1, 3, QZ, RZ, Y, ind_Y, ... % fY, [], [], xbase, 0, scale, 1, 1, 1, 1e15 ) % [ QZ, RZ, Y, xbase, scale ] = sqpdfo_swap_in_Y( 1, 3, QZ, RZ, Y, ind_Y, ... % fY, [],[],xbase, 0, scale, 1, 1, 1, 1e15 ) % norm( Z - QZ*RZ) @author: jaco_da """ import unittest from sqpdfo.sqpdfo_swap_in_Y import * from sqpdfo.bcdfo_build_QR_of_Y import * from numpy import array class Test_sqpdfo_swap_in_Y(unittest.TestCase): """ Reminder : This class is a test for sqpdfo_swap_in_Y which swaps the position of interpolation points i and j in Y, and updates the factorization of Z(Y) accordingly. """ def test_sqpdfo_swap_in_Y(self): """ Matlab test """ QZ,RZ,xbase,scale = bcdfo_build_QR_of_Y_( self.Y, 0, 0, 1, 1, 1e15 ) Z = QZ.dot(RZ) # ceY = array([]) ciY = array([]) QZ,RZ,Y,ind_Y,fY,ciY,ceY,xbase,scale = sqpdfo_swap_in_Y_( 0, 2, QZ, RZ, self.Y, self.ind_Y, self.fY, ciY, ceY, xbase, 0, scale, 0, 1, 1, 1e15 ) QZ,RZ,Y,ind_Y,fY,ciY,ceY,xbase,scale = sqpdfo_swap_in_Y_( 0, 2, QZ, RZ, Y, ind_Y, fY, ciY, ceY, xbase, 0, scale, 0, 1, 1, 1e15 ) ret = norm_( Z - QZ.dot(RZ)) self.assertTrue(ret < 1e-15) # # #Scaled version : QZ,RZ,xbase,scale = bcdfo_build_QR_of_Y_( self.Y, 0, 1, 1, 1, 1e15 ) Z = QZ.dot(RZ) ceY = array([]) ciY = array([]) QZ,RZ,Y,ind_Y,fY,ciY,ceY,xbase,scale = sqpdfo_swap_in_Y_( 0, 2, QZ, RZ, self.Y, self.ind_Y, self.fY, ciY, ceY, xbase, 0, scale, 1, 1, 1, 1e15 ) QZ,RZ,Y,ind_Y,fY,ciY,ceY,xbase,scale = sqpdfo_swap_in_Y_( 0, 2, QZ, RZ, Y, ind_Y, fY, ciY, ceY, xbase, 0, scale, 1, 1, 1, 1e15 ) ret = norm_( Z - QZ.dot(RZ)) self.assertTrue(ret < 1e-15) if __name__ == '__main__': unittest.main()

36.292683

126

0.540659

# -*- coding: utf-8 -*- """ Created on Fri Nov 14 18:53:38 2014 % TESTS : % Y = [ 0 1 0 2 1 0 ; 0 0 1 0 0.01 2 ]; ind_Y = [1 2 3 4 5 6]; % fY = [2 5 1 3 2 6]; % [QZ,RZ,xbase,scale] = bcdfo_build_QR_of_Y( Y, 0, 0, 1, 1, 1e15 ); % Z = QZ*RZ; % [ QZ, RZ, Y, xbase, scale ] = sqpdfo_swap_in_Y( 1, 3, QZ, RZ, Y, ind_Y, ... % fY, [],[],xbase, 0, scale, 0, 1, 1, 1e15 ) % [ QZ, RZ, Y, xbase, scale ] = sqpdfo_swap_in_Y( 1, 3, QZ, RZ, Y, ind_Y, ... % fY, [],[],xbase, 0, scale, 0, 1, 1, 1e15 ) % norm( Z - QZ*RZ) % should give something very small. % % The same holds for the scaled version: % Y = [ 0 1 0 2 1 0 ; 0 0 1 0 0.01 2 ]; ind_Y = [1 2 3 4 5 6]; % fY = [2 5 1 3 2 6]; % [QZ,RZ,xbase,scale] = bcdfo_build_QR_of_Y( Y, 0, 1, 1, 1, 1e15 ); % Z = QZ*RZ; % [ QZ, RZ, Y, xbase, scale ] = sqpdfo_swap_in_Y( 1, 3, QZ, RZ, Y, ind_Y, ... % fY, [], [], xbase, 0, scale, 1, 1, 1, 1e15 ) % [ QZ, RZ, Y, xbase, scale ] = sqpdfo_swap_in_Y( 1, 3, QZ, RZ, Y, ind_Y, ... % fY, [],[],xbase, 0, scale, 1, 1, 1, 1e15 ) % norm( Z - QZ*RZ) @author: jaco_da """ import unittest from sqpdfo.sqpdfo_swap_in_Y import * from sqpdfo.bcdfo_build_QR_of_Y import * from numpy import array class Test_sqpdfo_swap_in_Y(unittest.TestCase): """ Reminder : This class is a test for sqpdfo_swap_in_Y which swaps the position of interpolation points i and j in Y, and updates the factorization of Z(Y) accordingly. """ def setUp(self): self.Y = array([[ 0, 1, 0, 2, 1, 0], [0, 0, 1, 0, 0.01, 2 ]]) self.ind_Y = array([0, 1, 2, 3, 4, 5]) self.fY = array([2, 5, 1, 3, 2, 6]) #self.options = helper.dummyOptions() #self.values = helper.dummyValues() pass def test_sqpdfo_swap_in_Y(self): """ Matlab test """ QZ,RZ,xbase,scale = bcdfo_build_QR_of_Y_( self.Y, 0, 0, 1, 1, 1e15 ) Z = QZ.dot(RZ) # ceY = array([]) ciY = array([]) QZ,RZ,Y,ind_Y,fY,ciY,ceY,xbase,scale = sqpdfo_swap_in_Y_( 0, 2, QZ, RZ, self.Y, self.ind_Y, self.fY, ciY, ceY, xbase, 0, scale, 0, 1, 1, 1e15 ) QZ,RZ,Y,ind_Y,fY,ciY,ceY,xbase,scale = sqpdfo_swap_in_Y_( 0, 2, QZ, RZ, Y, ind_Y, fY, ciY, ceY, xbase, 0, scale, 0, 1, 1, 1e15 ) ret = norm_( Z - QZ.dot(RZ)) self.assertTrue(ret < 1e-15) # # #Scaled version : QZ,RZ,xbase,scale = bcdfo_build_QR_of_Y_( self.Y, 0, 1, 1, 1, 1e15 ) Z = QZ.dot(RZ) ceY = array([]) ciY = array([]) QZ,RZ,Y,ind_Y,fY,ciY,ceY,xbase,scale = sqpdfo_swap_in_Y_( 0, 2, QZ, RZ, self.Y, self.ind_Y, self.fY, ciY, ceY, xbase, 0, scale, 1, 1, 1, 1e15 ) QZ,RZ,Y,ind_Y,fY,ciY,ceY,xbase,scale = sqpdfo_swap_in_Y_( 0, 2, QZ, RZ, Y, ind_Y, fY, ciY, ceY, xbase, 0, scale, 1, 1, 1, 1e15 ) ret = norm_( Z - QZ.dot(RZ)) self.assertTrue(ret < 1e-15) if __name__ == '__main__': unittest.main()

260

0

26

09e880a9992ededfaab7b1da096edc33e40dc3f1

317

py

Python

vacation/users/migrations/0003_remove_user_gender.py

mash-up-kr/vacation-homework-backend

21698b843e027f290c5289e4b663d158a8e67386

[ "MIT" ]

null

vacation/users/migrations/0003_remove_user_gender.py

mash-up-kr/vacation-homework-backend

21698b843e027f290c5289e4b663d158a8e67386

[ "MIT" ]

4

2020-06-05T18:24:33.000Z

2021-09-08T00:01:00.000Z

vacation/users/migrations/0003_remove_user_gender.py

mash-up-kr/vacation-homework-backend

21698b843e027f290c5289e4b663d158a8e67386

[ "MIT" ]

null

# Generated by Django 2.0.6 on 2018-06-30 15:59 from django.db import migrations

17.611111

47

0.577287

# Generated by Django 2.0.6 on 2018-06-30 15:59 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('users', '0002_user_gender'), ] operations = [ migrations.RemoveField( model_name='user', name='gender', ), ]

0

211

23

603b464d2e852e6e348b25c0234d6f9425151939

1,379

py

Python

models/component/word_embeding.py

wengithz/t-wji

482c5a435a72dbf88fdfab385f74d4f42f4afec1

[ "MIT" ]

246

2019-07-03T12:03:33.000Z

2022-03-19T08:43:38.000Z

models/component/word_embeding.py

wengithz/t-wji

482c5a435a72dbf88fdfab385f74d4f42f4afec1

[ "MIT" ]

3

2019-08-19T02:23:24.000Z

2020-04-20T07:45:03.000Z

models/component/word_embeding.py

wengithz/t-wji

482c5a435a72dbf88fdfab385f74d4f42f4afec1

[ "MIT" ]

70

2019-07-03T13:29:11.000Z

2022-03-01T06:49:08.000Z

''' Filename: word_embeding.py Project: models File Created: Sunday, 2nd December 2018 2:38:45 pm Author: xiaofeng ([email protected]) -------------------------- Last Modified: Sunday, 2nd December 2018 2:39:14 pm Modified By: xiaofeng ([email protected]) --------------------------- : 2018.06 - 2018 . ''' import tensorflow as tf def Embedding(name, vocab_embeding, input_sequence): """ Creates an embedding matrix of dimensions n_symbols x embeding_dim upon first use. Looks up embedding vector for each input symbol :parameters: name: name of embedding matrix tensor variable vocab_embeding: full vocabulary embedings input_sequence: input symbols tensor return: word embeding for current input_sequence tensor shape is (batch_size,1+input_sequence_length,embeding_dim) """ with tf.device("/cpu:0"), tf.variable_scope(name): label_embeding = tf.nn.embedding_lookup(vocab_embeding, input_sequence) return label_embeding def embedding_initializer(): """Returns initializer for embeddings""" return _initializer

31.340909

86

0.686004

''' Filename: word_embeding.py Project: models File Created: Sunday, 2nd December 2018 2:38:45 pm Author: xiaofeng ([email protected]) -------------------------- Last Modified: Sunday, 2nd December 2018 2:39:14 pm Modified By: xiaofeng ([email protected]) --------------------------- : 2018.06 - 2018 . ''' import tensorflow as tf def Embedding(name, vocab_embeding, input_sequence): """ Creates an embedding matrix of dimensions n_symbols x embeding_dim upon first use. Looks up embedding vector for each input symbol :parameters: name: name of embedding matrix tensor variable vocab_embeding: full vocabulary embedings input_sequence: input symbols tensor return: word embeding for current input_sequence tensor shape is (batch_size,1+input_sequence_length,embeding_dim) """ with tf.device("/cpu:0"), tf.variable_scope(name): label_embeding = tf.nn.embedding_lookup(vocab_embeding, input_sequence) return label_embeding def embedding_initializer(): """Returns initializer for embeddings""" def _initializer(shape, dtype, partition_info=None): _Em = tf.random_uniform(shape, minval=-1.0, maxval=1.0, dtype=dtype) # _init_func = tf.orthogonal_initializer(dtype=dtype) _Em = tf.nn.l2_normalize(_Em, -1) return _Em return _initializer

231

0

26

3cff875996b3bcdf6d5415c896d96f0355772caf

1,844

py

Python

buttons.py

Acidburn0zzz/difio

1485f657f099f6a8401ad7cfe155f524a8a9a422

[ "Apache-2.0" ]

4

2016-06-01T12:48:54.000Z

2021-08-19T22:21:47.000Z

buttons.py

Acidburn0zzz/difio

1485f657f099f6a8401ad7cfe155f524a8a9a422

[ "Apache-2.0" ]

3

2016-01-20T17:06:45.000Z

2016-01-20T17:07:06.000Z

buttons.py

Acidburn0zzz/difio

1485f657f099f6a8401ad7cfe155f524a8a9a422

[ "Apache-2.0" ]

2

2015-01-21T21:30:19.000Z

2017-08-08T06:03:02.000Z

################################################################################ # # Originally based on http://djangosnippets.org/snippets/1016/ # with small modifications # ################################################################################ import re from django.contrib import admin from django.conf.urls import patterns, url from django.http import HttpResponseRedirect class ButtonableModelAdmin(admin.ModelAdmin): """ A subclass of this admin will let you add buttons (like history) in the change view of an entry. """ buttons = []

36.156863

105

0.550976

################################################################################ # # Originally based on http://djangosnippets.org/snippets/1016/ # with small modifications # ################################################################################ import re from django.contrib import admin from django.conf.urls import patterns, url from django.http import HttpResponseRedirect class ButtonableModelAdmin(admin.ModelAdmin): """ A subclass of this admin will let you add buttons (like history) in the change view of an entry. """ buttons = [] def change_view(self, request, object_id, form_url='', extra_context=None): if not extra_context: extra_context = {'buttons' : []} for b in self.buttons: extra_context['buttons'].append({'name' : b.short_description, 'url' : b.func_name}) return super(ButtonableModelAdmin, self).change_view(request, object_id, form_url, extra_context) def get_urls(self): urls = super(ButtonableModelAdmin, self).get_urls() my_urls = patterns('',) for b in self.buttons: my_urls += patterns('', url(r'^(?P<id>\d+)/%s/$' % b.func_name, self.admin_site.admin_view(b)) ) return my_urls + urls def __call__(self, request, url): if url is not None: res=re.match('(.*/)?(?P<id>\d+)/(?P<command>.*)/', url) if res: if res.group('command') in [b.func_name for b in self.buttons]: obj = self.model._default_manager.get(pk=res.group('id')) getattr(self, res.group('command'))(obj) return HttpResponseRedirect(request.META['HTTP_REFERER']) return super(ButtonableModelAdmin, self).__call__(request, url)

1,177

0

81

50628d0ffe8f1b285b5e647d287ada17e06654dc

3,956

py

Python

cms/tests/placeholder.py

DrMeers/django-cms-2.0

d563d912c99f0c138a66d99829d8d0133226894e

[ "BSD-3-Clause" ]

4

2016-05-07T11:50:25.000Z

2017-12-04T10:30:20.000Z

cms/tests/placeholder.py

DrMeers/django-cms-2.0

d563d912c99f0c138a66d99829d8d0133226894e

[ "BSD-3-Clause" ]

1

2015-06-08T08:27:11.000Z

2015-06-08T10:40:27.000Z

cms/tests/placeholder.py

DrMeers/django-cms-2.0

d563d912c99f0c138a66d99829d8d0133226894e

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- from django.conf import settings from cms.tests.base import CMSTestCase from cms.utils.plugins import get_placeholders from cms.exceptions import DuplicatePlaceholderWarning import sys import warnings

41.642105

161

0.674924

# -*- coding: utf-8 -*- from django.conf import settings from cms.tests.base import CMSTestCase from cms.utils.plugins import get_placeholders from cms.exceptions import DuplicatePlaceholderWarning import sys import warnings class _Warning(object): def __init__(self, message, category, filename, lineno): self.message = message self.category = category self.filename = filename self.lineno = lineno def _collectWarnings(observeWarning, f, *args, **kwargs): def showWarning(message, category, filename, lineno, file=None, line=None): assert isinstance(message, Warning) observeWarning(_Warning( message.args[0], category, filename, lineno)) # Disable the per-module cache for every module otherwise if the warning # which the caller is expecting us to collect was already emitted it won't # be re-emitted by the call to f which happens below. for v in sys.modules.itervalues(): if v is not None: try: v.__warningregistry__ = None except: # Don't specify a particular exception type to handle in case # some wacky object raises some wacky exception in response to # the setattr attempt. pass origFilters = warnings.filters[:] origShow = warnings.showwarning warnings.simplefilter('always') try: warnings.showwarning = showWarning result = f(*args, **kwargs) finally: warnings.filters[:] = origFilters warnings.showwarning = origShow return result class PlaceholderTestCase(CMSTestCase): def test_01_placeholder_scanning_extend(self): placeholders = get_placeholders('placeholder_tests/test_one.html') self.assertEqual(sorted(placeholders), sorted([u'new_one', u'two', u'three'])) def test_02_placeholder_scanning_include(self): placeholders = get_placeholders('placeholder_tests/test_two.html') self.assertEqual(sorted(placeholders), sorted([u'child', u'three'])) def test_03_placeholder_scanning_double_extend(self): placeholders = get_placeholders('placeholder_tests/test_three.html') self.assertEqual(sorted(placeholders), sorted([u'new_one', u'two', u'new_three'])) def test_04_placeholder_scanning_complex(self): placeholders = get_placeholders('placeholder_tests/test_four.html') self.assertEqual(sorted(placeholders), sorted([u'new_one', u'child', u'four'])) def test_05_placeholder_scanning_super(self): placeholders = get_placeholders('placeholder_tests/test_five.html') self.assertEqual(sorted(placeholders), sorted([u'one', u'extra_one', u'two', u'three'])) def test_06_placeholder_scanning_nested(self): placeholders = get_placeholders('placeholder_tests/test_six.html') self.assertEqual(sorted(placeholders), sorted([u'new_one', u'new_two', u'new_three'])) def test_07_placeholder_scanning_duplicate(self): placeholders = self.assertWarns(DuplicatePlaceholderWarning, "Duplicate placeholder found: `one`", get_placeholders, 'placeholder_tests/test_seven.html') self.assertEqual(sorted(placeholders), sorted([u'one'])) def failUnlessWarns(self, category, message, f, *args, **kwargs): warningsShown = [] result = _collectWarnings(warningsShown.append, f, *args, **kwargs) if not warningsShown: self.fail("No warnings emitted") first = warningsShown[0] for other in warningsShown[1:]: if ((other.message, other.category) != (first.message, first.category)): self.fail("Can't handle different warnings") self.assertEqual(first.message, message) self.assertTrue(first.category is category) return result assertWarns = failUnlessWarns

3,291

343

95

4faa38226dfbda6e0fa802c404b9b102b7bac67d

1,071

py

Python

src/mecab.py

chimerast/scdv-docker

c833c02f5f63ca9cc3e1ccc45b75e597fc5503a8

[ "Apache-2.0" ]

null

src/mecab.py

chimerast/scdv-docker

c833c02f5f63ca9cc3e1ccc45b75e597fc5503a8

[ "Apache-2.0" ]

null

src/mecab.py

chimerast/scdv-docker

c833c02f5f63ca9cc3e1ccc45b75e597fc5503a8

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 # -*- Coding: utf-8 -*- import subprocess from subprocess import PIPE

24.340909

134

0.568627

#!/usr/bin/env python3 # -*- Coding: utf-8 -*- import subprocess from subprocess import PIPE class MeCab: def __init__(self, command='mecab'): try: self.process = subprocess.Popen([command, '-b', '81920', '-F', '%t\t%f[6]\n'], stdin=PIPE, stdout=PIPE, universal_newlines=True) self.stdin = self.process.stdin self.stdout = self.process.stdout except OSError: raise def __del__(self): self.process.stdin.close() try: self.process.kill() self.process.wait() except (OSError, TypeError, AttributeError): pass def analysis(self, sentence): self.stdin.write(sentence.lower() + '\n') self.stdin.flush() result = [] while True: line = self.stdout.readline().rstrip() if line == 'EOS': break else: cols = line.split('\t') try: if cols[0] == '6' or cols[0] == '3': pass elif len(cols) == 2: result.append(cols[1].lower()) except IndexError: print(line) raise return result

889

-9

97

cdb0fe98f9840947e902a931457917ab07a33644

2,452

py

Python

dashboard/app/helpers/helpers_mongodb.py

rodriguesfas/ipm

596382123c3d45bde6410672692d1f59ec2d734a

[ "MIT" ]

null

dashboard/app/helpers/helpers_mongodb.py

rodriguesfas/ipm

596382123c3d45bde6410672692d1f59ec2d734a

[ "MIT" ]

null

dashboard/app/helpers/helpers_mongodb.py

rodriguesfas/ipm

596382123c3d45bde6410672692d1f59ec2d734a

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- from config import database from pymongo import MongoClient from mongoengine import *

27.863636

79

0.539152

#!/usr/bin/env python # -*- coding: utf-8 -*- from config import database from pymongo import MongoClient from mongoengine import * class ConnectMongoDB(object): def __init__(self): self.client = MongoClient(database.DB['hostname'], database.DB['port']) self.db = self.client[database.DB['database']] self.conn() def conn(self): return self.db def insert_document(self, collection_name, document): try: collection = self.db[collection_name] _id = collection.insert_one(document).inserted_id return _id except Exception as err: print(err) def select_document(self, collection_name, key): try: collection = self.db[collection_name] result = collection.find_one(key) if(result): return result else: return False except Exception as err: log.logging.error(err) return result def select_document_all_key(self, collection_name, key): try: collection = self.db[collection_name] result = collection.find(key) annotations = [] for anotation in result: annotations.append(anotation) return annotations except Exception as err: log.logging.error(err) return result def select_document_all(self, collection_name): try: collection = self.db[collection_name] item = [] for data in collection.find(): item.append( { "id": data['_id'], "name": data['name'], "register": data['register'] } ) return item except Exception as err: print(err) def update_document(self, collection_name, key, document): try: collection = self.db[collection_name] result = collection.update_one(key, document) return result except Exception as err: print(err) def delete_document(self, collection_name, key): try: collection = self.db[collection_name] result = collection.delete_one(key) return result except Exception as err: print(err)

2,070

8

239

5bd3c0b18eba7661b447a339dafcedcbb8ede1bd

349

py

Python

archive/nucleus_encoder/aux_src/make_img_list.py

peterdonnelly1/u24_lymphocyte

dff7ceed404c38582feb81aa9b8a55d80ada0f77

[ "BSD-3-Clause" ]

23

2018-08-23T03:58:37.000Z

2022-02-23T05:04:54.000Z

archive/nucleus_encoder/aux_src/make_img_list.py

peterdonnelly1/u24_lymphocyte

dff7ceed404c38582feb81aa9b8a55d80ada0f77

[ "BSD-3-Clause" ]

8

2018-07-20T20:54:51.000Z

2020-06-12T05:36:04.000Z

archive/nucleus_encoder/aux_src/make_img_list.py

peterdonnelly1/u24_lymphocyte

dff7ceed404c38582feb81aa9b8a55d80ada0f77

[ "BSD-3-Clause" ]

22

2018-05-21T23:57:20.000Z

2022-02-21T00:48:32.000Z

import glob folder = '/data03/shared/lehhou/lym_project/svs_tiles/TCGA-38-4629-01Z-00-DX1.d00cc280-5370-4b9f-9655-6c35deb94647.svs/'; outfile = folder + 'list.txt'; filevar = open(outfile, 'w'); filelist = []; for filename in glob.glob(folder + '/*.png'): name = filename[len(folder):-4]; filevar.write("%s\n" % name); filevar.close();

23.266667

121

0.676218

import glob folder = '/data03/shared/lehhou/lym_project/svs_tiles/TCGA-38-4629-01Z-00-DX1.d00cc280-5370-4b9f-9655-6c35deb94647.svs/'; outfile = folder + 'list.txt'; filevar = open(outfile, 'w'); filelist = []; for filename in glob.glob(folder + '/*.png'): name = filename[len(folder):-4]; filevar.write("%s\n" % name); filevar.close();

0

ef439acb79cc5b2c099076332fae80714cbee0b5

9,953

py

Python

spotdl/metadata/providers/youtube.py

Sigill/spotify-downloader

f65f2f97a10e46b7528f8a1666be30eac6de8a73

[ "MIT" ]

null

spotdl/metadata/providers/youtube.py

Sigill/spotify-downloader

f65f2f97a10e46b7528f8a1666be30eac6de8a73

[ "MIT" ]

null

spotdl/metadata/providers/youtube.py

Sigill/spotify-downloader

f65f2f97a10e46b7528f8a1666be30eac6de8a73

[ "MIT" ]

1

2021-01-27T04:31:16.000Z

import pytube from bs4 import BeautifulSoup import urllib.request import threading from collections.abc import Sequence from spotdl.metadata import StreamsBase from spotdl.metadata import ProviderBase from spotdl.metadata.exceptions import YouTubeMetadataNotFoundError import spotdl.util import spotdl.patch spotdl.patch.youtube.apply_patches() import logging logger = logging.getLogger(__name__) BASE_SEARCH_URL = "https://www.youtube.com/results?sp=EgIQAQ%253D%253D&q={}" HEADERS = [('Range', 'bytes=0-'),]

34.439446

95

0.589671

import pytube from bs4 import BeautifulSoup import urllib.request import threading from collections.abc import Sequence from spotdl.metadata import StreamsBase from spotdl.metadata import ProviderBase from spotdl.metadata.exceptions import YouTubeMetadataNotFoundError import spotdl.util import spotdl.patch spotdl.patch.youtube.apply_patches() import logging logger = logging.getLogger(__name__) BASE_SEARCH_URL = "https://www.youtube.com/results?sp=EgIQAQ%253D%253D&q={}" HEADERS = [('Range', 'bytes=0-'),] class YouTubeVideos(Sequence): def __init__(self, videos): self.videos = videos super().__init__() def __repr__(self): return "YouTubeVideos({})".format(self.videos) def __len__(self): return len(self.videos) def __getitem__(self, index): return self.videos[index] def __eq__(self, instance): return self.videos == instance.videos def bestmatch(self): video = self.videos[0] logger.debug("Matched with: {title} ({url}) [{duration}]".format( title=video["title"], url=video["url"], duration=video["duration"] )) return video class YouTubeSearch: def __init__(self): self.base_search_url = BASE_SEARCH_URL def generate_search_url(self, query): quoted_query = urllib.request.quote(query) return self.base_search_url.format(quoted_query) def _fetch_response_html(self, url): response = urllib.request.urlopen(url) soup = BeautifulSoup(response.read(), "html.parser") return soup def _extract_video_details_from_result(self, html): video_time = html.find("span", class_="video-time").get_text() inner_html = html.find("div", class_="yt-lockup-content") video_id = inner_html.find("a")["href"][-11:] video_title = inner_html.find("a")["title"] video_details = { "url": "https://www.youtube.com/watch?v=" + video_id, "title": video_title, "duration": video_time, } return video_details def _fetch_search_results(self, html, limit=10): result_source = html.find_all( "div", {"class": "yt-lockup-dismissable yt-uix-tile"} ) videos = [] for result in result_source: if not self._is_video(result): continue video = self._extract_video_details_from_result(result) videos.append(video) if len(videos) >= limit: break return videos def _is_video(self, result): # ensure result is not a channel not_video = ( result.find("channel") is not None or "yt-lockup-channel" in result.parent.attrs["class"] or "yt-lockup-channel" in result.attrs["class"] ) # ensure result is not a mix/playlist not_video = not_video or "yt-lockup-playlist" in result.parent.attrs["class"] # ensure video result is not an advertisement not_video = not_video or result.find("googleads") is not None # ensure video result is not a live stream not_video = not_video or result.find("span", class_="video-time") is None video = not not_video return video def _is_server_side_invalid_response(self, videos, html): if videos: return False search_message = html.find("div", {"class":"search-message"}) return search_message is None def search(self, query, limit=10, retries=5): """ Search and scrape YouTube to return a list of matching videos. """ search_url = self.generate_search_url(query) logger.debug('Fetching YouTube results for "{}" at "{}".'.format(query, search_url)) html = self._fetch_response_html(search_url) videos = self._fetch_search_results(html, limit=limit) to_retry = retries > 0 and self._is_server_side_invalid_response(videos, html) if to_retry: logger.debug( "Retrying since YouTube returned invalid response for search " "results. Retries left: {retries}.".format(retries=retries) ) return self.search(query, limit=limit, retries=retries-1) return YouTubeVideos(videos) class YouTubeStreams(StreamsBase): def __init__(self, streams): self.network_headers = HEADERS audiostreams = streams.filter(only_audio=True).order_by("abr").desc() thread_pool = [] self.all = [] for stream in audiostreams: encoding = "m4a" if "mp4a" in stream.audio_codec else stream.audio_codec standard_stream = { # Store only the integer part for bitrate. For example # the given bitrate would be "192kbps", we store only # the integer part (192) here and drop the rest. "bitrate": int(stream.abr[:-4]), "connection": None, "download_url": stream.url, "encoding": encoding, "filesize": None, } establish_connection = threading.Thread( target=self._store_connection, args=(standard_stream,), ) thread_pool.append(establish_connection) establish_connection.start() self.all.append(standard_stream) for thread in thread_pool: thread.join() def _store_connection(self, stream): response = self._make_request(stream["download_url"]) stream["connection"] = response stream["filesize"] = int(response.headers["Content-Length"]) def _make_request(self, url): request = urllib.request.Request(url) for header in self.network_headers: request.add_header(*header) return urllib.request.urlopen(request) def get(self, quality="best", preftype="automatic"): if quality == "best": return self.getbest(preftype=preftype) elif quality == "worst": return self.getworst(preftype=preftype) else: return None def getbest(self, preftype="automatic"): selected_stream = None if preftype == "automatic": selected_stream = self.all[0] else: for stream in self.all: if stream["encoding"] == preftype: selected_stream = stream break logger.debug('Selected best quality stream for "{preftype}" format:\n{stream}'.format( preftype=preftype, stream=selected_stream, )) return selected_stream def getworst(self, preftype="automatic"): selected_stream = None if preftype == "automatic": selected_stream = self.all[-1] else: for stream in self.all[::-1]: if stream["encoding"] == preftype: selected_stream = stream break logger.debug('Selected worst quality stream for "{preftype}" format:\n{stream}'.format( preftype=preftype, stream=selected_stream, )) return selected_stream class ProviderYouTube(ProviderBase): def from_query(self, query): watch_urls = self.search(query) if not watch_urls: raise YouTubeMetadataNotFoundError( 'YouTube returned nothing for the given search ' 'query ("{}")'.format(query) ) return self.from_url(watch_urls[0]) def from_url(self, url, retries=5): logger.debug('Fetching YouTube metadata for "{url}".'.format(url=url)) try: content = pytube.YouTube(url) except KeyError: # Sometimes YouTube can return unexpected response, in such a case # retry a few times before finally failing. if retries > 0: retries -= 1 logger.debug( "YouTube returned an unexpected response for " "`pytube.YouTube({url})`. Retries left: {retries}".format( url=url, retries=retries ) ) return self.from_url(url, retries=retries) else: raise else: return self.from_pytube_object(content) def from_pytube_object(self, content): return self.metadata_to_standard_form(content) def search(self, query): return YouTubeSearch().search(query) def _fetch_publish_date(self, content): # XXX: This needs to be supported in PyTube itself # See https://github.com/nficano/pytube/issues/595 position = content.watch_html.find("publishDate") publish_date = content.watch_html[position+16:position+25] return publish_date def metadata_to_standard_form(self, content): """ Fetch a song's metadata from YouTube. """ publish_date = self._fetch_publish_date(content) metadata = { "name": content.title, "artists": [{"name": content.author}], "duration": content.length, "external_urls": {"youtube": content.watch_url}, "album": { "images": [{"url": content.thumbnail_url}], "artists": [{"name": None}], "name": None, }, "year": publish_date.split("-")[0], "release_date": publish_date, "type": "track", "disc_number": 1, "track_number": 1, "total_tracks": 1, "publisher": None, "external_ids": {"isrc": None}, "lyrics": None, "copyright": None, "genre": None, "streams": YouTubeStreams(content.streams), "provider": "youtube", } return metadata

6,820

2,200

414

49f9d7712dcdc05ba93f2647b7aa24930e8eb505

3,029

py

Python

distribution/scripts/cloudformation/create-template.py

menuka94/performance-common

93a412656baddc89d9643950b252b33e4b5473f4

[ "Apache-2.0" ]

null

distribution/scripts/cloudformation/create-template.py

menuka94/performance-common

93a412656baddc89d9643950b252b33e4b5473f4

[ "Apache-2.0" ]

null

distribution/scripts/cloudformation/create-template.py

menuka94/performance-common

93a412656baddc89d9643950b252b33e4b5473f4

[ "Apache-2.0" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- # Copyright (c) 2018, WSO2 Inc. (http://wso2.org) All Rights Reserved. # # WSO2 Inc. licenses this file to you under the Apache License, # Version 2.0 (the "License"); you may not use this file except # in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. # # ---------------------------------------------------------------------------- # Create AWS CloudFormation template # ---------------------------------------------------------------------------- import argparse import csv import json import os from jinja2 import Environment, FileSystemLoader PATH = os.path.dirname(os.path.abspath(__file__)) TEMPLATE_ENVIRONMENT = Environment( autoescape=False, loader=FileSystemLoader(os.path.join(PATH, 'templates')), trim_blocks=False, keep_trailing_newline=True) if __name__ == "__main__": main()

37.8625

92

0.648729

#!/usr/bin/env python # -*- coding: utf-8 -*- # Copyright (c) 2018, WSO2 Inc. (http://wso2.org) All Rights Reserved. # # WSO2 Inc. licenses this file to you under the Apache License, # Version 2.0 (the "License"); you may not use this file except # in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. # # ---------------------------------------------------------------------------- # Create AWS CloudFormation template # ---------------------------------------------------------------------------- import argparse import csv import json import os from jinja2 import Environment, FileSystemLoader PATH = os.path.dirname(os.path.abspath(__file__)) TEMPLATE_ENVIRONMENT = Environment( autoescape=False, loader=FileSystemLoader(os.path.join(PATH, 'templates')), trim_blocks=False, keep_trailing_newline=True) def render_template(template_filename, context): return TEMPLATE_ENVIRONMENT.get_template(template_filename).render(context) class StoreDictKeyPair(argparse.Action): def __call__(self, parser, namespace, values, option_string=None): my_dict = {} for kv in values.split(","): k, v = kv.split("=") my_dict[k] = v setattr(namespace, self.dest, my_dict) def main(): parser = argparse.ArgumentParser( description='Create AWS CloudFormation template.') parser.add_argument('--template-name', required=True, help='The template file name.', type=str) parser.add_argument('--output-name', required=True, help='Output file name.', type=str) parser.add_argument('--jmeter-servers', required=True, help='Number of JMeter Servers.', type=int) parser.add_argument("--parameters", dest="parameters", action=StoreDictKeyPair, help="Additional parameters.", metavar="key1=value1,key2=value2...") parser.add_argument("--start-bastion", default=False, action="store_true", help="Start bastion instance") parser.add_argument("--enable-cloudwatch-logs", default=False, action="store_true", help="Enable AWS CloudWatch logs") args = parser.parse_args() context = {'jmeter_servers': args.jmeter_servers, 'start_bastion': args.start_bastion, 'enable_cloudwatch_logs': args.enable_cloudwatch_logs} if args.parameters is not None: context.update(args.parameters) with open(args.output_name, 'w') as f: markdown_file = render_template(args.template_name, context) f.write(markdown_file.encode("utf-8")) if __name__ == "__main__": main()

1,659

19

95

43c3b24d757b1797e1e2876663de7edbab7410d5

6,716

py

Python

report/is_stock_move.py

tonygalmiche/is_plastigray

10669dda26f5a8653371a52798f41fdc805c61f2

[ "MIT" ]

1

2018-12-29T08:34:25.000Z

report/is_stock_move.py

tonygalmiche/is_plastigray

10669dda26f5a8653371a52798f41fdc805c61f2

[ "MIT" ]

null

report/is_stock_move.py

tonygalmiche/is_plastigray

10669dda26f5a8653371a52798f41fdc805c61f2

[ "MIT" ]

null

# -*- coding: utf-8 -*- from openerp import tools from openerp import models,fields,api from openerp.tools.translate import _ import datetime import pytz

48.316547

106

0.453395

# -*- coding: utf-8 -*- from openerp import tools from openerp import models,fields,api from openerp.tools.translate import _ import datetime import pytz class is_stock_move(models.Model): _name='is.stock.move' _order='date desc' _auto = False move_id = fields.Many2one('stock.move', 'Mouvement') date = fields.Datetime('Date') product_id = fields.Many2one('product.product', 'Article') category = fields.Char('Cat') mold = fields.Char('Moule / DossierF') type_mv = fields.Char('Type') name = fields.Char('Description') picking_id = fields.Many2one('stock.picking', 'Rcp/Liv') lot_id = fields.Many2one('stock.production.lot', 'Lot') lot_fournisseur = fields.Char('Lot fournisseur') qty = fields.Float('Quantité') product_uom = fields.Many2one('product.uom', 'Unité') location_dest = fields.Char("Lieu") login = fields.Char('Utilisateur') purchase_line_id = fields.Many2one('purchase.order.line', 'Ligne commande achat') raw_material_production_id = fields.Many2one('mrp.production' , 'Composant ordre de fabrication') production_id = fields.Many2one('mrp.production' , 'Ordre de fabrication') is_sale_line_id = fields.Many2one('sale.order.line' , 'Ligne commande vente') @api.multi def refresh_stock_move_action(self): cr = self._cr cr.execute("REFRESH MATERIALIZED VIEW is_stock_move;") now = datetime.datetime.now(pytz.timezone('Europe/Paris')).strftime('%H:%M:%S') return { 'name': u'Mouvements de stocks actualisés à '+str(now), 'view_mode': 'tree,form', 'view_type': 'form', 'res_model': 'is.stock.move', 'type': 'ir.actions.act_window', } def init(self, cr): # DROP MATERIALIZED VIEW IF EXISTS is_stock_move; # CREATE MATERIALIZED view is_stock_move AS ( #tools.drop_view_if_exists(cr, 'is_stock_move') # CREATE OR REPLACE view is_stock_move AS ( cr.execute(""" DROP MATERIALIZED VIEW IF EXISTS is_stock_move; CREATE MATERIALIZED view is_stock_move AS ( select row_number() over(order by sm.id ) as id, sm.id as move_id, sm2.date as date, sm2.product_id as product_id, ic.name as category, COALESCE(im.name,id.name) as mold, COALESCE(spt.name,sm.src) as type_mv, COALESCE(spt.name,sp.name,sm2.name) as name, sm2.picking_id as picking_id, sm2.purchase_line_id, sm2.raw_material_production_id, sm2.production_id, sm2.is_sale_line_id, sm.lot_id as lot_id, spl.is_lot_fournisseur as lot_fournisseur, sm.qty as qty, pt.uom_id as product_uom, sm.dest as location_dest, rp.name as login from ( select sm.id, sq.lot_id as lot_id, sum(sq.qty) as qty, sl1.name as src, sl2.name as dest from stock_move sm inner join stock_location sl1 on sm.location_id=sl1.id inner join stock_location sl2 on sm.location_dest_id=sl2.id left outer join stock_quant_move_rel sqmr on sm.id=sqmr.move_id left outer join stock_quant sq on sqmr.quant_id=sq.id where sm.state='done' and sl2.usage='internal' group by sm.id, sq.lot_id, sl1.name, sl2.name union select sm.id, sq.lot_id as lot_id, -sum(sq.qty) as qty, sl1.name as dest, sl2.name as src from stock_move sm inner join stock_location sl1 on sm.location_dest_id=sl1.id inner join stock_location sl2 on sm.location_id=sl2.id left outer join stock_quant_move_rel sqmr on sm.id=sqmr.move_id left outer join stock_quant sq on sqmr.quant_id=sq.id where sm.state='done' and sl2.usage='internal' group by sm.id, sq.lot_id, sl1.name, sl2.name ) sm inner join stock_move sm2 on sm.id=sm2.id inner join product_product pp on sm2.product_id=pp.id inner join product_template pt on pp.product_tmpl_id=pt.id inner join res_users ru on sm2.write_uid=ru.id inner join res_partner rp on ru.partner_id=rp.id left outer join stock_picking_type spt on sm2.picking_type_id=spt.id left outer join stock_picking sp on sm2.picking_id=sp.id left outer join is_category ic on pt.is_category_id=ic.id left outer join is_mold im on pt.is_mold_id=im.id left outer join is_dossierf id on pt.is_dossierf_id=id.id left outer join stock_production_lot spl on sm.lot_id=spl.id order by sm2.date desc, sm2.id ); """)

5,151

1,375

24

f4678d3f7a4d0345c9ea15387eb70169f82ab90a

1,168

py

Python

corehq/motech/const.py

shyamkumarlchauhan/commcare-hq

99df931bcf56e9fbe15d8fcb0dc98b5a3957fb48

[ "BSD-3-Clause" ]

null

corehq/motech/const.py

shyamkumarlchauhan/commcare-hq

99df931bcf56e9fbe15d8fcb0dc98b5a3957fb48

[ "BSD-3-Clause" ]

null

corehq/motech/const.py

shyamkumarlchauhan/commcare-hq

99df931bcf56e9fbe15d8fcb0dc98b5a3957fb48

[ "BSD-3-Clause" ]

null

BASIC_AUTH = "basic" DIGEST_AUTH = "digest" OAUTH1 = "oauth1" BEARER_AUTH = "bearer" PASSWORD_PLACEHOLDER = '*' * 16 CONNECT_TIMEOUT = 60 # If any remote service does not respond within 5 minutes, time out. # (Some OpenMRS reports can take a long time. Cut them a little slack, # but not too much.) READ_TIMEOUT = 5 * 60 REQUEST_TIMEOUT = (CONNECT_TIMEOUT, READ_TIMEOUT) ALGO_AES = 'aes' DATA_TYPE_UNKNOWN = None COMMCARE_DATA_TYPE_TEXT = 'cc_text' COMMCARE_DATA_TYPE_INTEGER = 'cc_integer' COMMCARE_DATA_TYPE_DECIMAL = 'cc_decimal' COMMCARE_DATA_TYPE_BOOLEAN = 'cc_boolean' COMMCARE_DATA_TYPE_DATE = 'cc_date' COMMCARE_DATA_TYPE_DATETIME = 'cc_datetime' COMMCARE_DATA_TYPE_TIME = 'cc_time' COMMCARE_DATA_TYPES = ( COMMCARE_DATA_TYPE_TEXT, COMMCARE_DATA_TYPE_INTEGER, COMMCARE_DATA_TYPE_DECIMAL, COMMCARE_DATA_TYPE_BOOLEAN, COMMCARE_DATA_TYPE_DATE, COMMCARE_DATA_TYPE_DATETIME, COMMCARE_DATA_TYPE_TIME, ) COMMCARE_DATA_TYPES_AND_UNKNOWN = COMMCARE_DATA_TYPES + (DATA_TYPE_UNKNOWN,) DIRECTION_IMPORT = 'in' DIRECTION_EXPORT = 'out' DIRECTION_BOTH = None DIRECTIONS = ( DIRECTION_IMPORT, DIRECTION_EXPORT, DIRECTION_BOTH, )

25.955556

76

0.78339

BASIC_AUTH = "basic" DIGEST_AUTH = "digest" OAUTH1 = "oauth1" BEARER_AUTH = "bearer" PASSWORD_PLACEHOLDER = '*' * 16 CONNECT_TIMEOUT = 60 # If any remote service does not respond within 5 minutes, time out. # (Some OpenMRS reports can take a long time. Cut them a little slack, # but not too much.) READ_TIMEOUT = 5 * 60 REQUEST_TIMEOUT = (CONNECT_TIMEOUT, READ_TIMEOUT) ALGO_AES = 'aes' DATA_TYPE_UNKNOWN = None COMMCARE_DATA_TYPE_TEXT = 'cc_text' COMMCARE_DATA_TYPE_INTEGER = 'cc_integer' COMMCARE_DATA_TYPE_DECIMAL = 'cc_decimal' COMMCARE_DATA_TYPE_BOOLEAN = 'cc_boolean' COMMCARE_DATA_TYPE_DATE = 'cc_date' COMMCARE_DATA_TYPE_DATETIME = 'cc_datetime' COMMCARE_DATA_TYPE_TIME = 'cc_time' COMMCARE_DATA_TYPES = ( COMMCARE_DATA_TYPE_TEXT, COMMCARE_DATA_TYPE_INTEGER, COMMCARE_DATA_TYPE_DECIMAL, COMMCARE_DATA_TYPE_BOOLEAN, COMMCARE_DATA_TYPE_DATE, COMMCARE_DATA_TYPE_DATETIME, COMMCARE_DATA_TYPE_TIME, ) COMMCARE_DATA_TYPES_AND_UNKNOWN = COMMCARE_DATA_TYPES + (DATA_TYPE_UNKNOWN,) DIRECTION_IMPORT = 'in' DIRECTION_EXPORT = 'out' DIRECTION_BOTH = None DIRECTIONS = ( DIRECTION_IMPORT, DIRECTION_EXPORT, DIRECTION_BOTH, )

0

b2c0f702a792a12b6aa85cd23ca049cb59be36d1

300

py

Python

exercicio74Corrigido.py

adrianomdantas/Exercicios-Python

ef5025a186615258aec0cf35ed839fe49577d983

[ "MIT" ]

null

exercicio74Corrigido.py

adrianomdantas/Exercicios-Python

ef5025a186615258aec0cf35ed839fe49577d983

[ "MIT" ]

null

exercicio74Corrigido.py

adrianomdantas/Exercicios-Python

ef5025a186615258aec0cf35ed839fe49577d983

[ "MIT" ]

null

from random import randint numeros = (randint(1, 10), randint(1, 10), randint(1, 10), randint(1, 10), randint(1, 10)) print('os numeros sorteados são: ', end='') for n in numeros: print(f'{n}', end=' ') print(f'\no maior numero foi {max(numeros)}') print(f'O menor numero foi {min(numeros)}')

27.272727

90

0.65

from random import randint numeros = (randint(1, 10), randint(1, 10), randint(1, 10), randint(1, 10), randint(1, 10)) print('os numeros sorteados são: ', end='') for n in numeros: print(f'{n}', end=' ') print(f'\no maior numero foi {max(numeros)}') print(f'O menor numero foi {min(numeros)}')

0

3ef1b744c3868ea130c204e25377d5aac59213f7

4,657

py

Python

bracket/get_training_data.py

henry-li-06/march-madness-bracket

17b4eb83128153a8406893547c70198114f82636

[ "MIT" ]

null

bracket/get_training_data.py

henry-li-06/march-madness-bracket

17b4eb83128153a8406893547c70198114f82636

[ "MIT" ]

null

bracket/get_training_data.py

henry-li-06/march-madness-bracket

17b4eb83128153a8406893547c70198114f82636

[ "MIT" ]

null

import numpy as np import pandas as pd import scrape_data import csv team_data = pd.read_csv('data/cbb19.csv') team_data = team_data.drop(columns=['POSTSEASON', 'SEED']) t = list(team_data['TEAM']) all_games = scrape_data.all_games winners = scrape_data.winners name_mappings = {'UNC': 'North Carolina', 'Citadel': 'The Citadel', 'Purdue-Fort Wayne': 'Fort Wayne', 'Arkansas-Pine Bluff': 'Arkansas Pine Bluff', 'UT-Martin': 'Tennessee Martin', 'ETSU': 'East Tennessee St.', 'Gardner-Webb': 'Gardner Webb', 'UIC': 'Illinois Chicago', 'Louisiana-Monroe': 'Louisiana Monroe', 'Ole Miss': 'Mississippi', 'Prairie View': 'Prairie View A&M', "St. John's (NY)": "St. John's", 'Miami (FL)': 'Miami FL', 'Miami (OH)': 'Miami OH', "Loyola (IL)": "Loyola Chicago", "Loyola (MD)": "Loyola MD", "Pitt": "Pittsburgh", "Texas-Arlington": "UT Arlington", "Alabama-Birmingham": "UAB", "St. Joseph's": "Saint Joseph's", 'Louisiana': 'Louisiana Lafayette', 'Omaha': 'Nebraska Omaha', 'California Baptist': 'Cal Baptist', 'Texas-Rio Grande Valley': 'UT Rio Grande Valley', 'Florida International': 'FIU', 'William ': 'William & Mary', 'UMass': 'Massachusetts', 'Saint Francis (PA)': 'St. Francis PA', 'LIU': 'LIU Brooklyn', 'Albany (NY)': 'Albany', 'St. Francis (NY)': 'St. Francis NY', 'Grambling': 'Grambling St.', 'Texas A&M-Corpus': 'Texas A&M Corpus Chris', 'UMass-Lowell': 'UMass Lowell', 'Bethune-Cookman': 'Bethune Cookman', "St. Peter's": "Saint Peter's", "Maryland-Eastern Shore": "Maryland Eastern Shore", "SIU-Edwardsville": "SIU Edwardsville"} for i in range(len(all_games)): for j in range(len(all_games[0])): if('UC' in all_games[i][j]): if(all_games[i][j] == 'UCSB'): all_games[i][j] = 'UC Santa Barbara' elif(all_games[i][j] == "UConn"): all_games[i][j] = 'Connecticut' else: pos = all_games[i][j].find('-') if(pos != -1): all_games[i][j] = all_games[i][j][:pos] + \ ' ' + all_games[i][j][pos+1:] elif('cal state' in all_games[i][j].lower()): pos = all_games[i][j].lower().find('state') all_games[i][j] = all_games[i][j][:pos] + \ 'St. ' + all_games[i][j][pos + 6:] elif('state' in all_games[i][j].lower()): if(all_games[i][j] == 'NC State'): all_games[i][j] = 'North Carolina St.' elif(all_games[i][j] == 'Bowling Green State'): all_games[i][j] = 'Bowling Green' elif(all_games[i][j] != "USC Upstate"): all_games[i][j] = all_games[i][j][:-3] + '.' elif(all_games[i][j] in name_mappings.keys()): all_games[i][j] = name_mappings[all_games[i][j]] for i in range(len(winners)): if('UC' in winners[i]): if(winners[i] == 'UCSB'): winners[i] = 'UC Santa Barbara' elif(winners[i] == "UConn"): winners[i] = 'Connecticut' else: pos = winners[i].find('-') if(pos != -1): winners[i] = winners[i][:pos] + ' ' + winners[i][pos+1:] elif('cal state' in winners[i].lower()): pos = winners[i].lower().find('state') winners[i] = winners[i][:pos] + 'St. ' + winners[i][pos + 6:] elif('state' in winners[i].lower()): if(winners[i] == 'NC State'): winners[i] = 'North Carolina St.' elif(winners[i] == 'Bowling Green State'): winners[i] = 'Bowling Green' elif(winners[i] != "USC Upstate"): winners[i] = winners[i][:-3] + '.' elif(winners[i] in name_mappings.keys()): winners[i] = name_mappings[winners[i]] games = pd.DataFrame(all_games, columns=['Away Team', 'Home Team']) games['Winner'] = winners games_to_drop = [] for i in range(len(games)): if(not(games['Away Team'][i] in t and games['Home Team'][i] in t)): games_to_drop.append(i) games = games.drop(games_to_drop) games = games.reset_index() games = games.drop(columns=['index']) with open('data/all_games_19.csv', 'w', newline='') as csvfile: writer = csv.writer(csvfile, delimiter=',') writer.writerow(['Away Team', 'Home Team', 'Winner']) for i in range(len(games)): writer.writerow( [games['Away Team'][i], games['Home Team'][i], games['Winner'][i]])

50.075269

121

0.535538

import numpy as np import pandas as pd import scrape_data import csv team_data = pd.read_csv('data/cbb19.csv') team_data = team_data.drop(columns=['POSTSEASON', 'SEED']) t = list(team_data['TEAM']) all_games = scrape_data.all_games winners = scrape_data.winners name_mappings = {'UNC': 'North Carolina', 'Citadel': 'The Citadel', 'Purdue-Fort Wayne': 'Fort Wayne', 'Arkansas-Pine Bluff': 'Arkansas Pine Bluff', 'UT-Martin': 'Tennessee Martin', 'ETSU': 'East Tennessee St.', 'Gardner-Webb': 'Gardner Webb', 'UIC': 'Illinois Chicago', 'Louisiana-Monroe': 'Louisiana Monroe', 'Ole Miss': 'Mississippi', 'Prairie View': 'Prairie View A&M', "St. John's (NY)": "St. John's", 'Miami (FL)': 'Miami FL', 'Miami (OH)': 'Miami OH', "Loyola (IL)": "Loyola Chicago", "Loyola (MD)": "Loyola MD", "Pitt": "Pittsburgh", "Texas-Arlington": "UT Arlington", "Alabama-Birmingham": "UAB", "St. Joseph's": "Saint Joseph's", 'Louisiana': 'Louisiana Lafayette', 'Omaha': 'Nebraska Omaha', 'California Baptist': 'Cal Baptist', 'Texas-Rio Grande Valley': 'UT Rio Grande Valley', 'Florida International': 'FIU', 'William ': 'William & Mary', 'UMass': 'Massachusetts', 'Saint Francis (PA)': 'St. Francis PA', 'LIU': 'LIU Brooklyn', 'Albany (NY)': 'Albany', 'St. Francis (NY)': 'St. Francis NY', 'Grambling': 'Grambling St.', 'Texas A&M-Corpus': 'Texas A&M Corpus Chris', 'UMass-Lowell': 'UMass Lowell', 'Bethune-Cookman': 'Bethune Cookman', "St. Peter's": "Saint Peter's", "Maryland-Eastern Shore": "Maryland Eastern Shore", "SIU-Edwardsville": "SIU Edwardsville"} for i in range(len(all_games)): for j in range(len(all_games[0])): if('UC' in all_games[i][j]): if(all_games[i][j] == 'UCSB'): all_games[i][j] = 'UC Santa Barbara' elif(all_games[i][j] == "UConn"): all_games[i][j] = 'Connecticut' else: pos = all_games[i][j].find('-') if(pos != -1): all_games[i][j] = all_games[i][j][:pos] + \ ' ' + all_games[i][j][pos+1:] elif('cal state' in all_games[i][j].lower()): pos = all_games[i][j].lower().find('state') all_games[i][j] = all_games[i][j][:pos] + \ 'St. ' + all_games[i][j][pos + 6:] elif('state' in all_games[i][j].lower()): if(all_games[i][j] == 'NC State'): all_games[i][j] = 'North Carolina St.' elif(all_games[i][j] == 'Bowling Green State'): all_games[i][j] = 'Bowling Green' elif(all_games[i][j] != "USC Upstate"): all_games[i][j] = all_games[i][j][:-3] + '.' elif(all_games[i][j] in name_mappings.keys()): all_games[i][j] = name_mappings[all_games[i][j]] for i in range(len(winners)): if('UC' in winners[i]): if(winners[i] == 'UCSB'): winners[i] = 'UC Santa Barbara' elif(winners[i] == "UConn"): winners[i] = 'Connecticut' else: pos = winners[i].find('-') if(pos != -1): winners[i] = winners[i][:pos] + ' ' + winners[i][pos+1:] elif('cal state' in winners[i].lower()): pos = winners[i].lower().find('state') winners[i] = winners[i][:pos] + 'St. ' + winners[i][pos + 6:] elif('state' in winners[i].lower()): if(winners[i] == 'NC State'): winners[i] = 'North Carolina St.' elif(winners[i] == 'Bowling Green State'): winners[i] = 'Bowling Green' elif(winners[i] != "USC Upstate"): winners[i] = winners[i][:-3] + '.' elif(winners[i] in name_mappings.keys()): winners[i] = name_mappings[winners[i]] games = pd.DataFrame(all_games, columns=['Away Team', 'Home Team']) games['Winner'] = winners games_to_drop = [] for i in range(len(games)): if(not(games['Away Team'][i] in t and games['Home Team'][i] in t)): games_to_drop.append(i) games = games.drop(games_to_drop) games = games.reset_index() games = games.drop(columns=['index']) with open('data/all_games_19.csv', 'w', newline='') as csvfile: writer = csv.writer(csvfile, delimiter=',') writer.writerow(['Away Team', 'Home Team', 'Winner']) for i in range(len(games)): writer.writerow( [games['Away Team'][i], games['Home Team'][i], games['Winner'][i]])

0

59059b9c66827dca12ada6526a8b904010258d99

17,152

py

Python

Alpha/calendarHelperFun.py

timchenggu123/BitTimeScheduler

10a90d7a6189b8e17ee736c662f8226041bfd0c8

[ "MIT" ]

1

2019-01-23T16:40:52.000Z

Alpha/calendarHelperFun.py

timchenggu123/BitTimeScheduler

10a90d7a6189b8e17ee736c662f8226041bfd0c8

[ "MIT" ]

null

Alpha/calendarHelperFun.py

timchenggu123/BitTimeScheduler

10a90d7a6189b8e17ee736c662f8226041bfd0c8

[ "MIT" ]

null

import datetime, pytz def getEventStartEnd(event): '''returns start time & end time as datetime objects from an event struct''' start_string = event['start'].get('dateTime',event['start'].get('date')) start_time = str2time(start_string) end_string = event['end'].get('dateTime',0) whole_day_event = 0 if not end_string: end_time = start_time + datetime.timedelta(days = 1) whole_day_event = 1 else: end_time = str2time(end_string) return start_time,end_time,whole_day_event def daily_insert(service,event,time_begin,duration, effective_days,date_start = datetime.datetime.today(), repeat_on_day_of_week = {0,1,2,3,4,5,6}): """ service: googleCalendar API connection. See connection.py event: event struct. Can be created from eventCreator() ***Note that event does not need to contain start and end dates. If it does, then it is going to overwritten*** repeat_on_day_of_week: an integer list with len 1~7 and values 0-6 each integer value represent a day of week. e.g. 0 is Monday, 2 is Wednesday, etc. This determines on what day of the week the event shall repeat time_start: datetime.time() object. When the event take place on each day even_duartion: datetime.timedelta() object. Duration of the event effective_days: over how many days do you want the event repeated? e.g. 365 days (1 year) date_start (optional) : when do you want the event to start repeating? By default it is going to be the date when this function is executed. Note that if the day is not one of the day specified in repeat_day_of_week, the next closest date meeting the criterial is when the event going to start. """ datetime_begin = datetime.datetime.combine(date_start,time_begin) datetime_end = datetime_begin + duration for days in range(effective_days): datetime_begin = datetime_begin + datetime.timedelta(days = 1) datetime_end = datetime_end + datetime.timedelta(days = 1) #check if right weekday if not datetime_begin.weekday() in repeat_on_day_of_week: continue start_string = time2str(datetime_begin) end_string = time2str(datetime_end) event['start']['dateTime'] = start_string event['end']['dateTime'] = end_string service.events().insert(calendarId = "primary",body = event).execute() def getFreeTime(service,start_datetime = datetime.datetime.now(),check_ndays = 14,min_free_len_mins = 10): """returns a list of free time psuedo-events starting from start_date for n effective_days service: googleCalendar API connection. See connection.py start_date: datetime.datetime obj effective_days: datetime.timedelta obj check_ndays: how many days from the start date to check for min_free_len_mins: minumn lenth of free time. Any free time shorter will be ignored """ calendar_result = service.calendarList().list().execute() calendars = calendar_result.get('items',[]) all_events = [] for calendar in calendars: cal_id = calendar['id'] events = getEvents(service,cal_id,start_datetime,check_ndays) all_events = all_events + events #now we remove all day events remove_list = list() for event in all_events: if not event['start'].get('dateTime',0): remove_list.append(event) for event in remove_list: all_events.remove(event) #now we sort all events by their start time all_events = sorted(all_events, key = lambda t: t['start'].get('dateTime')) #we set the first end time to be start_time end_datetime = start_datetime #create a list holder of free_time events free_times = [] for event in all_events: start_string = event['start']['dateTime'] start_datetime = str2time(start_string) duration_timedelta = start_datetime - end_datetime #we calculate duration by using the start time of the second event minus the end time of the first event duration = divmod(duration_timedelta.total_seconds(),60) duration = duration[0] if duration < min_free_len_mins: # if duration is too short skip end_datetime = str2time(event['end']['dateTime']) continue else: #if duration is good, create free time event free_time = eventCreator(end_datetime,start_datetime,-2,0,'free event',0,0,'Free Time',0) #not the start_datetime field is actually filled by the end_datetime vairable, and vice versa free_times.append(free_time) #update end_datetime for next loop end_datetime = str2time(event['end']['dateTime']) return free_times def getCalendarId(service,calendar_summary): '''returns a calendar_Id from a calendar_summary. Always returns the first one found. If none found, return -1''' calendar_result = service.calendarList().list().execute() calendars = calendar_result.get('items',[]) for calendar in calendars: if calendar['summary'] == calendar_summary: return calendar['id'] return -1 def getEvents(service,calId,start_datetime,search_for_ndays): '''do not use this unless you intend to pull only raw Google Calendar Events from the server. This is intended to be used as a component for methods such as getAllEvents()''' end_datetime = start_datetime.date() + datetime.timedelta(days = int(search_for_ndays) + 1) #+1 here because timeMax is exclusive end_datetime = datetime.datetime.combine(end_datetime, datetime.time(0,0)) #note the end time always at 0:00 start_datetime = utcFormat(start_datetime) end_datetime = utcFormat(end_datetime) events_result = service.events().list(calendarId= calId, timeMin=start_datetime, maxResults= 1000, singleEvents=True, timeMax= end_datetime, orderBy='startTime').execute() events = events_result.get('items', []) return events def createRecurringEvent(event,by_day ='MO,TU,WE,TH,FR,SA,SU',until = 0): '''until needs to be a string in the formta "YYYYMMDD" ''' '''needs more work''' event['recurrence'] = list() if until: until_statement = 'UNTIL=' + until + ';' else: until_statement = '' event['recurrence'].append( 'RRULE:FREQ=WEEKLY;'+ until_statement+'BYDAY=' + by_day) return event

37.531729

194

0.626341

import datetime, pytz def str2time(string): if len(string) > 10: nchar = len(string) string = string[0:nchar -6] # -6 to get ride of the -05:00 trailler timeformat = ('%Y-%m-%dT%H:%M:%S') dt = datetime.datetime.strptime(string, timeformat) else: timeformat = ('%Y-%m-%d') dt = datetime.datetime.strptime(string,timeformat) return dt def time2str(datetime): timeformat = ('%Y-%m-%dT%H:%M:%S-05:00') return(datetime.strftime(timeformat)) def minsLeftinWeek(): now = datetime.datetime.now() day = now.weekday() week_remain_days = 6 - day day_remain_mins = datetime.datetime.fromordinal( datetime.date.today().toordinal()) day_remain_mins = now - day_remain_mins day_remain_mins = divmod(day_remain_mins.total_seconds(),60) day_remain_mins = 24*60 - (day_remain_mins[0] + day_remain_mins[1]) total_remain_mins = week_remain_days * 24 * 60 + day_remain_mins print('You have ' + str(total_remain_mins) + ' minutes left this week!') def getEventStartEnd(event): '''returns start time & end time as datetime objects from an event struct''' start_string = event['start'].get('dateTime',event['start'].get('date')) start_time = str2time(start_string) end_string = event['end'].get('dateTime',0) whole_day_event = 0 if not end_string: end_time = start_time + datetime.timedelta(days = 1) whole_day_event = 1 else: end_time = str2time(end_string) return start_time,end_time,whole_day_event def eventCreator(start, end, reschedulability, expirary_date, event_type, urgency, importance, custom_name = -1, extensibility = 0, days_till_expire = 0, time_zone = 'America/Toronto',cal_id = 'primary',shortenability = 0): if custom_name == -1: custom_name = event_type if not type(start) is str: start = time2str(start) if not type(end) is str: end = time2str(end) event = { "start":{"dateTime":start, "timeZone":time_zone}, "end":{"dateTime":end, "timeZone":time_zone}, "summary": custom_name, } if type(expirary_date) is datetime.datetime : days_till_expire = expirary_date - str2time(start) days_till_expire = divmod(days_till_expire.total_seconds(),86400)[0] expirary_date = expirary_date.date() elif type(expirary_date) is datetime.date: days_till_expire = expirary_date - str2time(start).date() days_till_expire = days_till_expire.days elif expirary_date == str(-999): expirary_date = str2time(start).date() description_info = ("&reschedulability:" + str(reschedulability) + "&expirary_date:" + str(expirary_date) + "&days_till_expire:" + str(days_till_expire) + "&event_type:" + str(event_type) + "&urgency:" + str(urgency) + "&importance:" + str(importance) + "&extensibility:" + str(extensibility)+ "&shortenability:" + str(shortenability)) event['description'] = description_info event_duration_timedelta = str2time(end) - str2time(start) event_duration = divmod(event_duration_timedelta.total_seconds(),60) event_duration = event_duration[0] event['duration'] = event_duration event['cal_id'] = cal_id return event def addCustomTags(event, description = '', custom_tags = {}): if description and not custom_tags: custom_tags = getCustomTags(description = description) elif description and custom_tags: raise ValueError('Too many arguments. Please only provid one') expirary_date = custom_tags['expirary_date'] days_till_expire = custom_tags['days_till_expire'] start = event['start']['dateTime'] if type(expirary_date) is datetime.datetime : days_till_expire = expirary_date - str2time(start) days_till_expire = divmod(days_till_expire.total_seconds(),86400)[0] expirary_date = expirary_date.date() elif type(expirary_date) is datetime.date: days_till_expire = expirary_date - str2time(start).date() days_till_expire = days_till_expire.days elif expirary_date == str(-999): expirary_date = str2time(start).date() custom_tags['expirary_date'] = expirary_date custom_tags['days_till_expire'] = days_till_expire description_info = '' for custom_tag in custom_tags: custom_string = '&' + custom_tag +':'+str(custom_tags[custom_tag]) description_info += custom_string event['description'] = description_info return event def changeCustomTags(event,custom_tags): event_custom_tags = getCustomTags(event) for custom_tag in custom_tags: event_custom_tags[custom_tag] = custom_tags[custom_tag] description_info = '' for custom_tag in event_custom_tags: custom_string = '&' + custom_tag +':'+str(event_custom_tags[custom_tag]) description_info += custom_string event['description'] = description_info def daily_insert(service,event,time_begin,duration, effective_days,date_start = datetime.datetime.today(), repeat_on_day_of_week = {0,1,2,3,4,5,6}): """ service: googleCalendar API connection. See connection.py event: event struct. Can be created from eventCreator() ***Note that event does not need to contain start and end dates. If it does, then it is going to overwritten*** repeat_on_day_of_week: an integer list with len 1~7 and values 0-6 each integer value represent a day of week. e.g. 0 is Monday, 2 is Wednesday, etc. This determines on what day of the week the event shall repeat time_start: datetime.time() object. When the event take place on each day even_duartion: datetime.timedelta() object. Duration of the event effective_days: over how many days do you want the event repeated? e.g. 365 days (1 year) date_start (optional) : when do you want the event to start repeating? By default it is going to be the date when this function is executed. Note that if the day is not one of the day specified in repeat_day_of_week, the next closest date meeting the criterial is when the event going to start. """ datetime_begin = datetime.datetime.combine(date_start,time_begin) datetime_end = datetime_begin + duration for days in range(effective_days): datetime_begin = datetime_begin + datetime.timedelta(days = 1) datetime_end = datetime_end + datetime.timedelta(days = 1) #check if right weekday if not datetime_begin.weekday() in repeat_on_day_of_week: continue start_string = time2str(datetime_begin) end_string = time2str(datetime_end) event['start']['dateTime'] = start_string event['end']['dateTime'] = end_string service.events().insert(calendarId = "primary",body = event).execute() def getFreeTime(service,start_datetime = datetime.datetime.now(),check_ndays = 14,min_free_len_mins = 10): """returns a list of free time psuedo-events starting from start_date for n effective_days service: googleCalendar API connection. See connection.py start_date: datetime.datetime obj effective_days: datetime.timedelta obj check_ndays: how many days from the start date to check for min_free_len_mins: minumn lenth of free time. Any free time shorter will be ignored """ calendar_result = service.calendarList().list().execute() calendars = calendar_result.get('items',[]) all_events = [] for calendar in calendars: cal_id = calendar['id'] events = getEvents(service,cal_id,start_datetime,check_ndays) all_events = all_events + events #now we remove all day events remove_list = list() for event in all_events: if not event['start'].get('dateTime',0): remove_list.append(event) for event in remove_list: all_events.remove(event) #now we sort all events by their start time all_events = sorted(all_events, key = lambda t: t['start'].get('dateTime')) #we set the first end time to be start_time end_datetime = start_datetime #create a list holder of free_time events free_times = [] for event in all_events: start_string = event['start']['dateTime'] start_datetime = str2time(start_string) duration_timedelta = start_datetime - end_datetime #we calculate duration by using the start time of the second event minus the end time of the first event duration = divmod(duration_timedelta.total_seconds(),60) duration = duration[0] if duration < min_free_len_mins: # if duration is too short skip end_datetime = str2time(event['end']['dateTime']) continue else: #if duration is good, create free time event free_time = eventCreator(end_datetime,start_datetime,-2,0,'free event',0,0,'Free Time',0) #not the start_datetime field is actually filled by the end_datetime vairable, and vice versa free_times.append(free_time) #update end_datetime for next loop end_datetime = str2time(event['end']['dateTime']) return free_times def getCalendarId(service,calendar_summary): '''returns a calendar_Id from a calendar_summary. Always returns the first one found. If none found, return -1''' calendar_result = service.calendarList().list().execute() calendars = calendar_result.get('items',[]) for calendar in calendars: if calendar['summary'] == calendar_summary: return calendar['id'] return -1 def getEvents(service,calId,start_datetime,search_for_ndays): '''do not use this unless you intend to pull only raw Google Calendar Events from the server. This is intended to be used as a component for methods such as getAllEvents()''' end_datetime = start_datetime.date() + datetime.timedelta(days = int(search_for_ndays) + 1) #+1 here because timeMax is exclusive end_datetime = datetime.datetime.combine(end_datetime, datetime.time(0,0)) #note the end time always at 0:00 start_datetime = utcFormat(start_datetime) end_datetime = utcFormat(end_datetime) events_result = service.events().list(calendarId= calId, timeMin=start_datetime, maxResults= 1000, singleEvents=True, timeMax= end_datetime, orderBy='startTime').execute() events = events_result.get('items', []) return events def getEventDuration(event): start = event['start'].get('dateTime') end = event['end'].get('dateTime') event_duration_timedelta = str2time(end) - str2time(start) event_duration = divmod(event_duration_timedelta.total_seconds(),60) event_duration = round(event_duration[0]) return event_duration def getAllEvents(service,start_datetime,search_for_ndays,cal_presets = {}): #pulling all available calendars from server calendar_result = service.calendarList().list().execute() calendars = calendar_result.get('items',[]) all_events = [] #Now looping through the calendars to get all events for calendar in calendars: cal_id = calendar['id'] events = getEvents(service,cal_id,start_datetime,search_for_ndays) for event in events: event['cal_id'] = cal_id if 'description' in event: if not hasCustomTags(event) and cal_presets: for cal_preset in cal_presets: if cal_preset['cal_id'] == cal_id: event['description'] = cal_preset['description'] if not event['description']: raise ValueError('Calendar preset description info missing for ' + cal_id) elif not event['description']: #in the case when there no description and cal_preset is empty... raise ValueError('Calendar preset description info missing for ' + cal_id) elif len(cal_presets) > 0: for cal_preset in cal_presets: if cal_preset['cal_id'] == cal_id: addCustomTags(event,cal_preset['description']) else: raise ValueError('Calendar preset description info missing for ' + cal_id) all_events = all_events + events #now we remove all day events remove_list = list() for event in all_events: if not event['start'].get('dateTime',0): remove_list.append(event) for event in remove_list: all_events.remove(event) for event in all_events: if not event['start'].get('dateTime',0): stop = 1 #now we sort all events by their start time all_events = sorted(all_events, key = lambda t: t['start'].get('dateTime')) return all_events def hasCustomTags(event): if 'description' in event: custom_tags = getCustomTags(event) if 'days_till_expire' in custom_tags: return True return False def utcFormat(DST_datetime): local = pytz.timezone ("America/Toronto") local_dt = local.localize(DST_datetime, is_dst=True) utc_dt = local_dt.astimezone(pytz.utc) utc_dt = utc_dt.isoformat() utc_dt = utc_dt[0:len(utc_dt)-6] + 'Z' return utc_dt def getCustomTags(event = {},description = ''): if event: string = event['description'] elif description: string = description else: raise ValueError('not enough arguments') keys = [] keys1 = [] key = -1 key1 = -1 while True: key = string.find('&',key+1) if key == -1: break keys.append(key) key1 = string.find(':',key1+1) keys1.append(key1) custom_tags = {} for i in range(len(keys)): key = keys[i] key1 = keys1[i] custom_field = string[(key+1):key1] try: custom_value = string[(key1+1):keys[i+1]] except: custom_value = string[(key1+1):len(string)] custom_tags[custom_field] = custom_value return custom_tags def calcEventExpireDays(event): custom_tags = getCustomTags(event) expirary_date = custom_tags['expirary_date'] start = event['start']['dateTime'] days_till_expire = int(custom_tags['days_till_expire']) if expirary_date == str(0): expirary_date = str2time(start).date() + datetime.timedelta(days = days_till_expire) elif expirary_date == str(-999): expirary_date = str2time(start).date() else: try: expirary_date = str2time(expirary_date).date() except: raise ValueError('expirary date format invalid') today = datetime.date.today() expire_days = expirary_date - today expire_days = expire_days.days return expire_days def updateEvent(service,event): if 'id' in event: updated_event = service.events().update(calendarId=event['cal_id'], eventId=event['id'], body=event).execute() print (updated_event['updated']) else: insertEvent(service,event) def dropEvent(service,event): confirm = input('Event drop proposed. Do you want to drop event ' + event['summary'] + ' on ' + event['start']['dateTime'] + '?') if not confirm: return False to_be_dropped = service.events().delete(calendarId = event['cal_id'],eventId = event['id']).execute() print('Event ' + to_be_dropped['summary'] + 'is dropped') return True def insertEvent(service,event): to_be_inserted = service.events().insert(calendarId = event['cal_id'],body = event).execute() print() print('Event ' + to_be_inserted['summary'] + ' has been created. link: %s' % (to_be_inserted.get('htmlLink'))) print() def createRecurringEvent(event,by_day ='MO,TU,WE,TH,FR,SA,SU',until = 0): '''until needs to be a string in the formta "YYYYMMDD" ''' '''needs more work''' event['recurrence'] = list() if until: until_statement = 'UNTIL=' + until + ';' else: until_statement = '' event['recurrence'].append( 'RRULE:FREQ=WEEKLY;'+ until_statement+'BYDAY=' + by_day) return event

9,919

0

368

2e5ee35497095379e45d8e54fbc6320972173c3a

771

py

Python

backend/base/migrations/0005_cafe_num_reviews_cafe_rating_review_name.py

ivanbaug/cafe-wifi

49b240c460d73f7f4602cb78e230bf12c160604d

[ "MIT" ]

null

backend/base/migrations/0005_cafe_num_reviews_cafe_rating_review_name.py

ivanbaug/cafe-wifi

49b240c460d73f7f4602cb78e230bf12c160604d

[ "MIT" ]

null

backend/base/migrations/0005_cafe_num_reviews_cafe_rating_review_name.py

ivanbaug/cafe-wifi

49b240c460d73f7f4602cb78e230bf12c160604d

[ "MIT" ]

null

# Generated by Django 4.0.2 on 2022-02-19 16:35 from django.db import migrations, models

26.586207

93

0.577173

# Generated by Django 4.0.2 on 2022-02-19 16:35 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('base', '0004_alter_cafe_img_url'), ] operations = [ migrations.AddField( model_name='cafe', name='num_reviews', field=models.IntegerField(blank=True, default=0, null=True), ), migrations.AddField( model_name='cafe', name='rating', field=models.DecimalField(blank=True, decimal_places=2, max_digits=7, null=True), ), migrations.AddField( model_name='review', name='name', field=models.CharField(blank=True, max_length=200, null=True), ), ]

0

657

23

bd00b88b455ab668abae3b2ddac0269677e5a2b3

6,003

py

Python

api_doc/components/models/function.py

adrienbrunet/mixt

d725ec752ce430d135e993bc988bfdf2b8457c4b

[ "MIT" ]

27

2018-06-04T19:11:42.000Z

2022-02-23T22:46:39.000Z

api_doc/components/models/function.py

adrienbrunet/mixt

d725ec752ce430d135e993bc988bfdf2b8457c4b

[ "MIT" ]

7

2018-06-09T15:27:51.000Z

2021-03-11T20:00:35.000Z

api_doc/components/models/function.py

adrienbrunet/mixt

d725ec752ce430d135e993bc988bfdf2b8457c4b

[ "MIT" ]

3

2018-07-29T10:20:02.000Z

2021-11-18T19:55:07.000Z

# coding: mixt from mixt import Element, NotProvided, Required, html from mixt.contrib.css import css_vars from ... import datatypes from ..doc import DocPart, DocHeader from ..generic import Details from . import Code, DocString, NamedValue, UnnamedValue </Details> </if> </DocPart>

34.901163

124

0.463935

# coding: mixt from mixt import Element, NotProvided, Required, html from mixt.contrib.css import css_vars from ... import datatypes from ..doc import DocPart, DocHeader from ..generic import Details from . import Code, DocString, NamedValue, UnnamedValue class Function(Element): class PropTypes: id_prefix: str = '' h_level: int = 2 obj: Required[datatypes.Function] open: bool = True open_details: bool = False # noinspection PyUnresolvedReferences @css_vars(globals()) @classmethod def render_css_global(cls, context): tagged = tuple( f'.function-{name}' for name in [ 'staticmethod', 'property', 'classmethod' ] ) return combine({ comment(): f"<{cls.__module__}.{cls.__name__}>", ".function-kind": { display: none, }, tagged: { " > summary > .h:after": extend('TAG', 'HL') }, ".function": { "> .content > details:not(.doc-part) > summary": { opacity: 0.25, }, "&:hover > .content > details:not(.doc-part):not([open]) > summary": { opacity: 1, } }, media({max-width: context.styles.breakpoint}): { ".function-arg": { display: block, margin-left: 1*em, } } }, { f"{t} > summary > .h:after": { content: str(t.split('-')[-1]) } for t in tagged }, { comment(): f"</{cls.__module__}.{cls.__name__}>", }) def render(self, context): func = self.obj kind = func.kind or 'function' id_prefix = f'{self.id_prefix}{func.name}' docstring_details = doc_arguments = doc_return = doc_raises = doc_example = None if func.doc.details: docstring_details = <DocString doc={func.doc} hide_summary=True /> args = None len_args = len(func.args) if len_args: args = [ [ html.Span(_class="function-arg")( arg.name, ': ', html.Code()(arg.type), [ ' = ', html.Code()(getattr(arg.default, '__name__', str(arg.default))) ] if arg.has_default else '', ', ' if index < len_args - 1 else '' ) ] for index, arg in enumerate(func.args) ], doc_arguments = <DocPart kind="function" subkind="arguments" id_prefix={id_prefix} level={self.h_level+1} open> <DocHeader menu="Arguments">Arguments</DocHeader> {[ <NamedValue value={arg} h_level={self.h_level+2} id_prefix="{id_prefix}-arguments-" /> for arg in func.args ]} </DocPart> return_type = '' len_ret = 0 if func.ret: len_ret = len(func.ret) if len_ret > 1: return_type = 'Tuple[' + ', '.join([ ret.type for ret in func.ret ]) + ']' else: return_type = func.ret[0].type return_type = [' → ', html.Code()(return_type)] doc_return = <DocPart kind="function" subkind="returns" id_prefix={id_prefix} level={self.h_level+1} open> <DocHeader menu="Returns">Returns</DocHeader> <if cond={len_ret > 1}> <p>Multiple return values ({len_ret}):</p> </if> {[ <UnnamedValue value={ret} h_level={self.h_level+2} index={index if len_ret > 1 else NotProvided} id_prefix="{id_prefix}-returns-" /> for index, ret in enumerate(func.ret, 1) ]} </DocPart> if func.raises: doc_raises = <DocPart kind="function" subkind="raises" id_prefix={id_prefix} level={self.h_level+1} open> <DocHeader menu="Raises">Raises</DocHeader> {[ <NamedValue value={raise_info} h_level={self.h_level+2} id_prefix="{id_prefix}-raises-" /> for raise_info in func.raises ]} </DocPart> if func.example: doc_example = <DocPart kind="function" subkind="example" id_prefix={id_prefix} level={self.h_level+1} open> <DocHeader menu="Example">Example</DocHeader> <Code code={func.example} /> </DocPart> return <DocPart kind="function" id_prefix={id_prefix} level={self.h_level} open={self.open} class="function-{kind}"> <DocHeader menu={func.name} menu-class="menu-function-{kind}"> <if cond={kind not in ('method', 'function')}> <span class="function-kind">@{kind}<br /></span> </if> {func.name}<if cond={kind != 'property'}>({args})</if>{return_type} </DocHeader> <DocString doc={func.doc} hide_details=True /> <if cond={func.doc.details or func.example or func.args or func.ret or func.raises}> <Details class="linked-to-parent" open={self.open_details}> <summary>Details</summary> {docstring_details} {doc_arguments} {doc_return} {doc_raises} {doc_example} </Details> </if> </DocPart>

4,854

801

23

52153a5e56328e72603ec68c59cbb35fba1107f2

1,697

py

Python

aoc_cas/aoc2021/day17.py

TedCassirer/advent-of-code

fb87dfdbb48b44f864337750aa58a809dcf72392

[ "MIT" ]

1

2020-11-30T19:17:50.000Z

aoc_cas/aoc2021/day17.py

TedCassirer/advent-of-code

fb87dfdbb48b44f864337750aa58a809dcf72392

[ "MIT" ]

null

aoc_cas/aoc2021/day17.py

TedCassirer/advent-of-code

fb87dfdbb48b44f864337750aa58a809dcf72392

[ "MIT" ]

null

from math import sqrt, ceil if __name__ == "__main__": from aocd import get_data data = get_data(year=2021, day=17) print(part1(data)) print(part2(data))

22.932432

47

0.437242

from math import sqrt, ceil def getSquare(data): _, coords = data.split(": ") x, y = coords.split(", ") y, x = y[2:], x[2:] y2, y1 = [-int(n) for n in y.split("..")] x1, x2 = map(int, x.split("..")) return y1, x1, y2, x2 def trajectory(vy, vx): y, x = 0, 0 yield y, x while True: y += vy x += vx vy += 1 if vx > 0: vx -= 1 elif vx < 0: vx += 1 yield y, x def hit(y, x, y1, x1, y2, x2): return y1 <= y <= y2 and x1 <= x <= x2 def part1(data): square = getSquare(data) y1, x1, y2, x2 = square minVx = ceil(-1 / 2 + sqrt(1 / 4 + 2 * x1)) peakestPeak = 0 for vy in range(0, -y2 - 1, -1): peak = ((-vy) * ((-vy) + 1)) // 2 for vx in range(minVx, x2 + 1): for y, x in trajectory(vy, vx): if hit(y, x, *square): peakestPeak = peak break if y > y2 or x > x2: break if peak == peakestPeak: break return peakestPeak def part2(data): square = getSquare(data) y1, x1, y2, x2 = square minVx = ceil(-1 / 2 + sqrt(1 / 4 + 2 * x1)) hits = set() for vy in range(y2, -y2 - 1, -1): for vx in range(minVx, x2 + 1): for y, x in trajectory(vy, vx): if hit(y, x, *square): hits.add((vx, -vy)) break if y > y2 or x > x2: break return len(hits) if __name__ == "__main__": from aocd import get_data data = get_data(year=2021, day=17) print(part1(data)) print(part2(data))

1,403

0

115

2be8e7d6b997d8dd186e251e784db3b07f6ff9d5

4,992

py

Python

posts/migrations/0001_initial.py

ant-willow/yatube-pub

a42e4dd7fd353c40ccbc314841a04e6144900bc3

[ "MIT" ]

null

posts/migrations/0001_initial.py

ant-willow/yatube-pub

a42e4dd7fd353c40ccbc314841a04e6144900bc3

[ "MIT" ]

null

posts/migrations/0001_initial.py

ant-willow/yatube-pub

a42e4dd7fd353c40ccbc314841a04e6144900bc3

[ "MIT" ]

null

# Generated by Django 2.2.6 on 2020-11-14 23:01 from django.conf import settings from django.db import migrations, models import django.db.models.deletion

52.547368

181

0.604768

# Generated by Django 2.2.6 on 2020-11-14 23:01 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ] operations = [ migrations.CreateModel( name='Group', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title', models.CharField(max_length=100, verbose_name='Название сообщества')), ('slug', models.SlugField(unique=True)), ('description', models.TextField(verbose_name='Описание сообщества')), ], ), migrations.CreateModel( name='Post', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('text', models.TextField(verbose_name='Текст записи')), ('pub_date', models.DateTimeField(auto_now_add=True, verbose_name='Дата публикации')), ('image', models.ImageField(blank=True, null=True, upload_to='posts/', verbose_name='Изображение')), ('author', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='posts', to=settings.AUTH_USER_MODEL, verbose_name='Автор')), ('group', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='posts', to='posts.Group', verbose_name='Сообщество')), ], options={ 'ordering': ['-pub_date'], }, ), migrations.CreateModel( name='Comment', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('text', models.TextField(verbose_name='Текст комментария')), ('created', models.DateTimeField(auto_now_add=True, verbose_name='Дата комментария')), ('author', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='comments', to=settings.AUTH_USER_MODEL, verbose_name='Автор')), ('post', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='comments', to='posts.Post', verbose_name='Пост')), ], options={ 'ordering': ['-created'], }, ), migrations.CreateModel( name='Activity', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('time', models.DateTimeField(blank=True, null=True, verbose_name='Дата посещения')), ('user', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, related_name='seen', to=settings.AUTH_USER_MODEL, verbose_name='Пользователь')), ], ), migrations.CreateModel( name='Like', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('post', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='liked', to='posts.Post', verbose_name='Пост')), ('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='likes', to=settings.AUTH_USER_MODEL, verbose_name='Пользователь')), ], options={ 'unique_together': {('user', 'post')}, }, ), migrations.CreateModel( name='FollowGroup', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('group', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='group_following', to='posts.Group', verbose_name='Сообщество')), ('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='group_follower', to=settings.AUTH_USER_MODEL, verbose_name='Пользователь')), ], options={ 'unique_together': {('user', 'group')}, }, ), migrations.CreateModel( name='Follow', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('author', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='following', to=settings.AUTH_USER_MODEL, verbose_name='Автор')), ('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='follower', to=settings.AUTH_USER_MODEL, verbose_name='Пользователь')), ], options={ 'unique_together': {('user', 'author')}, }, ), ]

0

5,019

23

f2c5636f32094a0ea2b3748db2dc49208407d338

4,754

py

Python

scripts/osfstorage/fix_download_counts.py

DanielSBrown/osf.io

98dda2ac237377197acacce78274bc0a4ce8f303

[ "Apache-2.0" ]

1

2015-10-02T18:35:53.000Z

scripts/osfstorage/fix_download_counts.py

DanielSBrown/osf.io

98dda2ac237377197acacce78274bc0a4ce8f303

[ "Apache-2.0" ]

13

2020-03-24T15:29:41.000Z

2022-03-11T23:15:28.000Z

scripts/osfstorage/fix_download_counts.py

DanielSBrown/osf.io

98dda2ac237377197acacce78274bc0a4ce8f303

[ "Apache-2.0" ]

null

from __future__ import unicode_literals import sys import logging from datetime import datetime from framework.mongo import database from website.app import init_app from scripts import utils as script_utils from framework.transactions.context import TokuTransaction logger = logging.getLogger(__name__) # 2015 Sept 18 CUT_OFF_DATE = (2015, 9, 18) BACKUP_COLLECTION = 'zzz20151009pagecounters' NEW_COLLECTION = '20151009pagecountersmigrated' if __name__ == '__main__': dry = 'dry' in sys.argv if not dry: script_utils.add_file_logger(logger, __file__) # Allow setting the log level just by appending the level to the command if 'debug' in sys.argv: logger.setLevel(logging.DEBUG) elif 'warning' in sys.argv: logger.setLevel(logging.WARNING) elif 'info' in sys.argv: logger.setLevel(logging.INFO) elif 'error' in sys.argv: logger.setLevel(logging.ERROR) main(dry=dry)

36.852713

131

0.625578

from __future__ import unicode_literals import sys import logging from datetime import datetime from framework.mongo import database from website.app import init_app from scripts import utils as script_utils from framework.transactions.context import TokuTransaction logger = logging.getLogger(__name__) # 2015 Sept 18 CUT_OFF_DATE = (2015, 9, 18) BACKUP_COLLECTION = 'zzz20151009pagecounters' NEW_COLLECTION = '20151009pagecountersmigrated' def get_keys_after(obj, y, m, d): cut_off = datetime(year=y, month=m, day=d) keys = [] for date in obj['date'].keys(): year, month, day = date.split('/') if datetime(year=int(year), month=int(month), day=int(day)) >= cut_off: keys.append(date) return keys def do_migration(): # database.pagecounters.rename(BACKUP_COLLECTION) for current_version in database['pagecounters'].find(): if not current_version['_id'].startswith('download'): database[NEW_COLLECTION].insert(current_version) continue try: _, nid, fid, version = current_version['_id'].split(':') except ValueError: if current_version['_id'].count(':') != 2: logging.warning('Found malformed _id {}'.format(current_version['_id'])) database[NEW_COLLECTION].insert(current_version) continue try: version = int(version) except ValueError: logging.warning('Found malformed version in _id {}'.format(current_version['_id'])) database[NEW_COLLECTION].insert(current_version) continue next_version = database['pagecounters'].find_one({ '_id': ':'.join(['download', nid, fid, str(version + 1)]) }) if next_version: logger.debug('Found next version for {}'.format(current_version['_id'])) next_version_keys = get_keys_after(next_version, *CUT_OFF_DATE) else: logger.debug('No next version found for {}'.format(current_version['_id'])) next_version_keys = [] # 2015 Sept 18 current_version_keys = get_keys_after(current_version, *CUT_OFF_DATE) if current_version_keys: if not database['pagecounters'].find_one({'_id': ':'.join(['download', nid, fid, str(version - 1)])}): previous_version = {'_id': ':'.join(['download', nid, fid, str(version - 1)]), 'date': {}, 'total': 0, 'unique': 0} for key in current_version_keys: date = current_version['date'][key] previous_version['date'][key] = date previous_version['total'] += date['total'] previous_version['unique'] += date['unique'] database[NEW_COLLECTION].insert(previous_version) for key in current_version_keys: date = current_version['date'].pop(key) current_version['total'] -= date['total'] current_version['unique'] -= date['unique'] for key in next_version_keys: date = next_version['date'][key] assert key not in current_version current_version['date'][key] = date current_version['total'] += date['total'] current_version['unique'] += date['unique'] assert current_version['unique'] > -1 assert current_version['total'] > -1 if current_version['total'] == 0 or current_version['unique'] == 0 or not current_version['date']: assert not current_version['date'] assert current_version['total'] == 0 assert current_version['unique'] == 0 logger.warning('Skipping {} as it is a null record'.format(current_version['_id'])) continue logger.debug('Updating entry {}'.format(current_version['_id'])) database[NEW_COLLECTION].insert(current_version) database['pagecounters'].rename(BACKUP_COLLECTION) database[NEW_COLLECTION].rename('pagecounters') def main(dry=True): init_app(set_backends=True, routes=False) # Sets the storage backends on all models with TokuTransaction(): do_migration() if dry: raise Exception('Abort Transaction - Dry Run') if __name__ == '__main__': dry = 'dry' in sys.argv if not dry: script_utils.add_file_logger(logger, __file__) # Allow setting the log level just by appending the level to the command if 'debug' in sys.argv: logger.setLevel(logging.DEBUG) elif 'warning' in sys.argv: logger.setLevel(logging.WARNING) elif 'info' in sys.argv: logger.setLevel(logging.INFO) elif 'error' in sys.argv: logger.setLevel(logging.ERROR) main(dry=dry)

3,737

0

69

5e73e37f9f9cb5a97a7e27512ed98bc9848c2f98

5,800

py

Python

trustlab/consumers/lab_consumer.py

ValentinSiegert/aTLAS

a2e7521447f81add83a0c958d61846a1cbfbbe9c

[ "MIT" ]

null

trustlab/consumers/lab_consumer.py

ValentinSiegert/aTLAS

a2e7521447f81add83a0c958d61846a1cbfbbe9c

[ "MIT" ]

null

trustlab/consumers/lab_consumer.py

ValentinSiegert/aTLAS

a2e7521447f81add83a0c958d61846a1cbfbbe9c

[ "MIT" ]

null

import json import trustlab.lab.config as config import time from trustlab.consumers.chunk_consumer import ChunkAsyncJsonWebsocketConsumer from trustlab.models import * from trustlab.serializers.scenario_serializer import ScenarioSerializer from trustlab.lab.director import Director class LabConsumer(ChunkAsyncJsonWebsocketConsumer): """ LabConsumer class, with sequential process logic of the Director in its receive_json method. It is therewith the main interface between User Agent and Director. """

46.774194

119

0.514655

import json import trustlab.lab.config as config import time from trustlab.consumers.chunk_consumer import ChunkAsyncJsonWebsocketConsumer from trustlab.models import * from trustlab.serializers.scenario_serializer import ScenarioSerializer from trustlab.lab.director import Director class LabConsumer(ChunkAsyncJsonWebsocketConsumer): """ LabConsumer class, with sequential process logic of the Director in its receive_json method. It is therewith the main interface between User Agent and Director. """ async def connect(self): await self.accept() async def disconnect(self, close_code): pass async def receive_json(self, content, **kwargs): if content['type'] == 'run_scenario': try: Scenario.correct_number_types(content['scenario']) except (ModuleNotFoundError, SyntaxError) as error: await self.send_json({ 'message': f'Scenario Description Error: {str(error)}', 'type': 'error' }) return serializer = ScenarioSerializer(data=content['scenario']) if serializer.is_valid(): try: scenario_factory = ScenarioFactory() scenario = serializer.create(serializer.data) except (ValueError, AttributeError, TypeError, ModuleNotFoundError, SyntaxError) as error: await self.send_json({ 'message': f'Scenario Error: {str(error)}', 'type': 'error' }) return if len(scenario.agents) > 0: if scenario not in scenario_factory.scenarios: scenario_factory.scenarios.append(scenario) else: if not any([True if scen.name == scenario.name else False for scen in scenario_factory.scenarios]): await self.send_json({ 'message': f'Scenario Error: Scenario transmitted is empty and not known.', 'type': 'error' }) return else: scenario = [scen for scen in scenario_factory.scenarios if scenario.name == scen.name][0] director = Director(scenario) try: async with config.PREPARE_SCENARIO_SEMAPHORE: if config.TIME_MEASURE: preparation_start_timer = time.time() await director.prepare_scenario() await self.send_json({ 'scenario_run_id': director.scenario_run_id, 'type': "scenario_run_id" }) if config.TIME_MEASURE: preparation_end_timer = time.time() print(f"Preparation took {preparation_end_timer - preparation_start_timer} s") execution_start_timer = time.time() trust_log, agent_trust_logs = await director.run_scenario() if config.TIME_MEASURE: execution_end_timer = time.time() # noinspection PyUnboundLocalVariable print(f"Execution took {execution_end_timer - execution_start_timer} s") cleanup_start_timer = time.time() await director.end_scenario() if config.TIME_MEASURE: cleanup_end_timer = time.time() # noinspection PyUnboundLocalVariable print(f"CleanUp took {cleanup_end_timer - cleanup_start_timer} s") for agent in agent_trust_logs: agent_trust_logs[agent] = "".join(agent_trust_logs[agent]) await self.send_json({ 'agents_log': json.dumps(agent_trust_logs), 'trust_log': "".join(trust_log), 'scenario_run_id': director.scenario_run_id, 'type': "scenario_results" }) except Exception as exception: await self.send_json({ 'message': str(exception), 'type': 'error' }) else: await self.send(text_data=json.dumps({ 'message': serializer.errors, 'type': 'error' })) elif content['type'] == 'get_scenario_results': result_factory = ResultFactory() current_id = content['scenario_run_id'] if config.validate_scenario_run_id(current_id): try: scenario_result = result_factory.get_result(current_id) await self.send_json({ 'agents_log': json.dumps(scenario_result.agent_trust_logs), 'trust_log': "".join(scenario_result.trust_log), 'scenario_run_id': scenario_result.scenario_run_id, 'type': "scenario_results" }) except OSError as exception: await self.send_json({ 'message': "Scenario Result not found", 'exception': str(exception), 'type': 'scenario_result_error' }) else: await self.send_json({ 'message': "Scenario Run ID is not valid", 'type': 'scenario_result_error' })

5,193

0

80

da023300272a3b0a819ca98ca66851e3312e328b

74

py

Python

telegapi/__init__.py

p0o0uya/telegapi

ba250d659e6a9fd7b3b252d88aefada5a3dc617e

[ "MIT" ]

null

telegapi/__init__.py

p0o0uya/telegapi

ba250d659e6a9fd7b3b252d88aefada5a3dc617e

[ "MIT" ]

null

telegapi/__init__.py

p0o0uya/telegapi

ba250d659e6a9fd7b3b252d88aefada5a3dc617e

[ "MIT" ]

null

from telegapi.reqs import reqs as reqs from telegapi.telapi import telapi

24.666667

38

0.837838

from telegapi.reqs import reqs as reqs from telegapi.telapi import telapi

0

e52bc9e6bae8350ede8163a0814ef8dbef8ca8fe

10,743

py

Python

examples/core_examples/15d_gaussian.py

deepchatterjeeligo/bilby

6532c63d0d970ad33478ae0b1c28d4c570b74047

[ "MIT" ]

null

examples/core_examples/15d_gaussian.py

deepchatterjeeligo/bilby

6532c63d0d970ad33478ae0b1c28d4c570b74047

[ "MIT" ]

null

examples/core_examples/15d_gaussian.py

deepchatterjeeligo/bilby

6532c63d0d970ad33478ae0b1c28d4c570b74047

[ "MIT" ]

null

import bilby import numpy as np from bilby.core.likelihood import ( AnalyticalMultidimensionalBimodalCovariantGaussian, AnalyticalMultidimensionalCovariantGaussian, ) logger = bilby.core.utils.logger cov = [ [ 0.045991865933182365, -0.005489748382557155, -0.01025067223674548, 0.0020087713726603213, -0.0032648855847982987, -0.0034218261781145264, -0.0037173401838545774, -0.007694897715679858, 0.005260905282822458, 0.0013607957548231718, 0.001970785895702776, 0.006708452591621081, -0.005107684668720825, 0.004402554308030673, -0.00334987648531921, ], [ -0.005489748382557152, 0.05478640427684032, -0.004786202916836846, -0.007930397407501268, -0.0005945107515129139, 0.004858466255616657, -0.011667819871670204, 0.003169780190169035, 0.006761345004654851, -0.0037599761532668475, 0.005571796842520162, -0.0071098291510566895, -0.004477773540640284, -0.011250694688474672, 0.007465228985669282, ], [ -0.01025067223674548, -0.004786202916836844, 0.044324704403674524, -0.0010572820723801645, -0.009885693540838514, -0.0048321205972943464, -0.004576186966267275, 0.0025107211483955676, -0.010126911913571181, 0.01153595152487264, 0.005773054728678472, 0.005286558230422045, -0.0055438798694137734, 0.0044772210361854765, -0.00620416958073918, ], [ 0.0020087713726603213, -0.007930397407501268, -0.0010572820723801636, 0.029861342087731065, -0.007803477134405363, -0.0011466944120756021, 0.009925736654597632, -0.0007664415942207051, -0.0057593957402320385, -0.00027248233573270216, 0.003885350572544307, 0.00022362281488693097, 0.006609741178005571, -0.003292722856107429, -0.005873218251875897, ], [ -0.0032648855847982987, -0.0005945107515129156, -0.009885693540838514, -0.007803477134405362, 0.0538403407841302, -0.007446654755103316, -0.0025216534232170153, 0.004499568241334517, 0.009591034277125177, 0.00008612746932654223, 0.003386296829505543, -0.002600737873367083, 0.000621148057330571, -0.006603857049454523, -0.009241221870695395, ], [ -0.0034218261781145264, 0.004858466255616657, -0.004832120597294347, -0.0011466944120756015, -0.007446654755103318, 0.043746559133865104, 0.008962713024625965, -0.011099652042761613, -0.0006620240117921668, -0.0012591530037708058, -0.006899982952117269, 0.0019732354732442878, -0.002445676747004324, -0.006454778807421816, 0.0033303577606412765, ], [ -0.00371734018385458, -0.011667819871670206, -0.004576186966267273, 0.009925736654597632, -0.0025216534232170153, 0.008962713024625965, 0.03664582756831382, -0.009470328827284009, -0.006213741694945105, 0.007118775954484294, -0.0006741237990418526, -0.006003374957986355, 0.005718636997353189, -0.0005191095254772077, -0.008466566781233205, ], [ -0.007694897715679857, 0.0031697801901690347, 0.002510721148395566, -0.0007664415942207059, 0.004499568241334515, -0.011099652042761617, -0.009470328827284016, 0.057734267068088, 0.005521731225009532, -0.017008048805405164, 0.006749693090695894, -0.006348460110898, -0.007879244727681924, -0.005321753837620446, 0.011126783289057604, ], [ 0.005260905282822458, 0.0067613450046548505, -0.010126911913571181, -0.00575939574023204, 0.009591034277125177, -0.0006620240117921668, -0.006213741694945106, 0.005521731225009532, 0.04610670018969681, -0.010427010812879566, -0.0009861561285861987, -0.008896020395949732, -0.0037627528719902485, 0.00033704453138913093, -0.003173552163182467, ], [ 0.0013607957548231744, -0.0037599761532668475, 0.01153595152487264, -0.0002724823357326985, 0.0000861274693265406, -0.0012591530037708062, 0.007118775954484294, -0.01700804880540517, -0.010427010812879568, 0.05909125052583998, 0.002192545816395299, -0.002057672237277737, -0.004801518314458135, -0.014065326026662672, -0.005619012077114913, ], [ 0.0019707858957027763, 0.005571796842520162, 0.005773054728678472, 0.003885350572544309, 0.003386296829505542, -0.006899982952117272, -0.0006741237990418522, 0.006749693090695893, -0.0009861561285862005, 0.0021925458163952988, 0.024417715762416557, -0.003037163447600162, -0.011173674374382736, -0.0008193127407211239, -0.007137012700864866, ], [ 0.006708452591621083, -0.0071098291510566895, 0.005286558230422046, 0.00022362281488693216, -0.0026007378733670806, 0.0019732354732442886, -0.006003374957986352, -0.006348460110897999, -0.008896020395949732, -0.002057672237277737, -0.003037163447600163, 0.04762367868805726, 0.0008818947598625008, -0.0007262691465810616, -0.006482422704208912, ], [ -0.005107684668720825, -0.0044777735406402895, -0.005543879869413772, 0.006609741178005571, 0.0006211480573305693, -0.002445676747004324, 0.0057186369973531905, -0.00787924472768192, -0.003762752871990247, -0.004801518314458137, -0.011173674374382736, 0.0008818947598624995, 0.042639958466440225, 0.0010194948614718209, 0.0033872675386130637, ], [ 0.004402554308030674, -0.011250694688474675, 0.004477221036185477, -0.003292722856107429, -0.006603857049454523, -0.006454778807421815, -0.0005191095254772072, -0.005321753837620446, 0.0003370445313891318, -0.014065326026662679, -0.0008193127407211239, -0.0007262691465810616, 0.0010194948614718226, 0.05244900188599414, -0.000256550861960499, ], [ -0.00334987648531921, 0.007465228985669282, -0.006204169580739178, -0.005873218251875899, -0.009241221870695395, 0.003330357760641278, -0.008466566781233205, 0.011126783289057604, -0.0031735521631824654, -0.005619012077114915, -0.007137012700864866, -0.006482422704208912, 0.0033872675386130632, -0.000256550861960499, 0.05380987317762257, ], ] dim = 15 mean = np.zeros(dim) label = "multidim_gaussian_unimodal" outdir = "outdir" likelihood = AnalyticalMultidimensionalCovariantGaussian(mean, cov) priors = bilby.core.prior.PriorDict() priors.update( { "x{0}".format(i): bilby.core.prior.Uniform(-5, 5, "x{0}".format(i)) for i in range(dim) } ) result = bilby.run_sampler( likelihood=likelihood, priors=priors, sampler="dynesty", outdir=outdir, label=label, check_point_plot=True, resume=True, ) result.plot_corner(parameters={"x{0}".format(i): mean[i] for i in range(dim)}) # The prior is constant and flat, and the likelihood is normalised such that the area under it is one. # The analytical evidence is then given as 1/(prior volume) log_prior_vol = np.sum( np.log([prior.maximum - prior.minimum for key, prior in priors.items()]) ) log_evidence = -log_prior_vol sampled_std = [ np.std(result.posterior[param]) for param in result.search_parameter_keys ] logger.info("Analytic log evidence: " + str(log_evidence)) logger.info( "Sampled log evidence: " + str(result.log_evidence) + " +/- " + str(result.log_evidence_err) ) for i, search_parameter_key in enumerate(result.search_parameter_keys): logger.info(search_parameter_key) logger.info("Expected posterior standard deviation: " + str(likelihood.sigma[i])) logger.info("Sampled posterior standard deviation: " + str(sampled_std[i])) # BIMODAL distribution label = "multidim_gaussian_bimodal" dim = len(cov[0]) mean_1 = 4 * np.sqrt(np.diag(cov)) mean_2 = -4 * np.sqrt(np.diag(cov)) likelihood = AnalyticalMultidimensionalBimodalCovariantGaussian(mean_1, mean_2, cov) priors = bilby.core.prior.PriorDict() priors.update( { "x{0}".format(i): bilby.core.prior.Uniform(-5, 5, "x{0}".format(i)) for i in range(dim) } ) result = bilby.run_sampler( likelihood=likelihood, priors=priors, sampler="dynesty", outdir=outdir, label=label, check_point_plot=True, resume=True, ) result.plot_corner( parameters={"x{0}".format(i): mean_1[i] for i in range(dim)}, filename=outdir + "/multidim_gaussian_bimodal_mode_1", ) result.plot_corner( parameters={"x{0}".format(i): mean_2[i] for i in range(dim)}, filename=outdir + "/multidim_gaussian_bimodal_mode_2", ) log_prior_vol = np.sum( np.log([prior.maximum - prior.minimum for key, prior in priors.items()]) ) log_evidence = -log_prior_vol sampled_std_1 = [] sampled_std_2 = [] for param in result.search_parameter_keys: samples = np.array(result.posterior[param]) samples_1 = samples[np.where(samples < 0)] samples_2 = samples[np.where(samples > 0)] sampled_std_1.append(np.std(samples_1)) sampled_std_2.append(np.std(samples_2)) logger.info("Analytic log evidence: " + str(log_evidence)) logger.info( "Sampled log evidence: " + str(result.log_evidence) + " +/- " + str(result.log_evidence_err) ) for i, search_parameter_key in enumerate(result.search_parameter_keys): logger.info(search_parameter_key) logger.info( "Expected posterior standard deviation both modes: " + str(likelihood.sigma[i]) ) logger.info( "Sampled posterior standard deviation first mode: " + str(sampled_std_1[i]) ) logger.info( "Sampled posterior standard deviation second mode: " + str(sampled_std_2[i]) )

27.75969

102

0.638648

import bilby import numpy as np from bilby.core.likelihood import ( AnalyticalMultidimensionalBimodalCovariantGaussian, AnalyticalMultidimensionalCovariantGaussian, ) logger = bilby.core.utils.logger cov = [ [ 0.045991865933182365, -0.005489748382557155, -0.01025067223674548, 0.0020087713726603213, -0.0032648855847982987, -0.0034218261781145264, -0.0037173401838545774, -0.007694897715679858, 0.005260905282822458, 0.0013607957548231718, 0.001970785895702776, 0.006708452591621081, -0.005107684668720825, 0.004402554308030673, -0.00334987648531921, ], [ -0.005489748382557152, 0.05478640427684032, -0.004786202916836846, -0.007930397407501268, -0.0005945107515129139, 0.004858466255616657, -0.011667819871670204, 0.003169780190169035, 0.006761345004654851, -0.0037599761532668475, 0.005571796842520162, -0.0071098291510566895, -0.004477773540640284, -0.011250694688474672, 0.007465228985669282, ], [ -0.01025067223674548, -0.004786202916836844, 0.044324704403674524, -0.0010572820723801645, -0.009885693540838514, -0.0048321205972943464, -0.004576186966267275, 0.0025107211483955676, -0.010126911913571181, 0.01153595152487264, 0.005773054728678472, 0.005286558230422045, -0.0055438798694137734, 0.0044772210361854765, -0.00620416958073918, ], [ 0.0020087713726603213, -0.007930397407501268, -0.0010572820723801636, 0.029861342087731065, -0.007803477134405363, -0.0011466944120756021, 0.009925736654597632, -0.0007664415942207051, -0.0057593957402320385, -0.00027248233573270216, 0.003885350572544307, 0.00022362281488693097, 0.006609741178005571, -0.003292722856107429, -0.005873218251875897, ], [ -0.0032648855847982987, -0.0005945107515129156, -0.009885693540838514, -0.007803477134405362, 0.0538403407841302, -0.007446654755103316, -0.0025216534232170153, 0.004499568241334517, 0.009591034277125177, 0.00008612746932654223, 0.003386296829505543, -0.002600737873367083, 0.000621148057330571, -0.006603857049454523, -0.009241221870695395, ], [ -0.0034218261781145264, 0.004858466255616657, -0.004832120597294347, -0.0011466944120756015, -0.007446654755103318, 0.043746559133865104, 0.008962713024625965, -0.011099652042761613, -0.0006620240117921668, -0.0012591530037708058, -0.006899982952117269, 0.0019732354732442878, -0.002445676747004324, -0.006454778807421816, 0.0033303577606412765, ], [ -0.00371734018385458, -0.011667819871670206, -0.004576186966267273, 0.009925736654597632, -0.0025216534232170153, 0.008962713024625965, 0.03664582756831382, -0.009470328827284009, -0.006213741694945105, 0.007118775954484294, -0.0006741237990418526, -0.006003374957986355, 0.005718636997353189, -0.0005191095254772077, -0.008466566781233205, ], [ -0.007694897715679857, 0.0031697801901690347, 0.002510721148395566, -0.0007664415942207059, 0.004499568241334515, -0.011099652042761617, -0.009470328827284016, 0.057734267068088, 0.005521731225009532, -0.017008048805405164, 0.006749693090695894, -0.006348460110898, -0.007879244727681924, -0.005321753837620446, 0.011126783289057604, ], [ 0.005260905282822458, 0.0067613450046548505, -0.010126911913571181, -0.00575939574023204, 0.009591034277125177, -0.0006620240117921668, -0.006213741694945106, 0.005521731225009532, 0.04610670018969681, -0.010427010812879566, -0.0009861561285861987, -0.008896020395949732, -0.0037627528719902485, 0.00033704453138913093, -0.003173552163182467, ], [ 0.0013607957548231744, -0.0037599761532668475, 0.01153595152487264, -0.0002724823357326985, 0.0000861274693265406, -0.0012591530037708062, 0.007118775954484294, -0.01700804880540517, -0.010427010812879568, 0.05909125052583998, 0.002192545816395299, -0.002057672237277737, -0.004801518314458135, -0.014065326026662672, -0.005619012077114913, ], [ 0.0019707858957027763, 0.005571796842520162, 0.005773054728678472, 0.003885350572544309, 0.003386296829505542, -0.006899982952117272, -0.0006741237990418522, 0.006749693090695893, -0.0009861561285862005, 0.0021925458163952988, 0.024417715762416557, -0.003037163447600162, -0.011173674374382736, -0.0008193127407211239, -0.007137012700864866, ], [ 0.006708452591621083, -0.0071098291510566895, 0.005286558230422046, 0.00022362281488693216, -0.0026007378733670806, 0.0019732354732442886, -0.006003374957986352, -0.006348460110897999, -0.008896020395949732, -0.002057672237277737, -0.003037163447600163, 0.04762367868805726, 0.0008818947598625008, -0.0007262691465810616, -0.006482422704208912, ], [ -0.005107684668720825, -0.0044777735406402895, -0.005543879869413772, 0.006609741178005571, 0.0006211480573305693, -0.002445676747004324, 0.0057186369973531905, -0.00787924472768192, -0.003762752871990247, -0.004801518314458137, -0.011173674374382736, 0.0008818947598624995, 0.042639958466440225, 0.0010194948614718209, 0.0033872675386130637, ], [ 0.004402554308030674, -0.011250694688474675, 0.004477221036185477, -0.003292722856107429, -0.006603857049454523, -0.006454778807421815, -0.0005191095254772072, -0.005321753837620446, 0.0003370445313891318, -0.014065326026662679, -0.0008193127407211239, -0.0007262691465810616, 0.0010194948614718226, 0.05244900188599414, -0.000256550861960499, ], [ -0.00334987648531921, 0.007465228985669282, -0.006204169580739178, -0.005873218251875899, -0.009241221870695395, 0.003330357760641278, -0.008466566781233205, 0.011126783289057604, -0.0031735521631824654, -0.005619012077114915, -0.007137012700864866, -0.006482422704208912, 0.0033872675386130632, -0.000256550861960499, 0.05380987317762257, ], ] dim = 15 mean = np.zeros(dim) label = "multidim_gaussian_unimodal" outdir = "outdir" likelihood = AnalyticalMultidimensionalCovariantGaussian(mean, cov) priors = bilby.core.prior.PriorDict() priors.update( { "x{0}".format(i): bilby.core.prior.Uniform(-5, 5, "x{0}".format(i)) for i in range(dim) } ) result = bilby.run_sampler( likelihood=likelihood, priors=priors, sampler="dynesty", outdir=outdir, label=label, check_point_plot=True, resume=True, ) result.plot_corner(parameters={"x{0}".format(i): mean[i] for i in range(dim)}) # The prior is constant and flat, and the likelihood is normalised such that the area under it is one. # The analytical evidence is then given as 1/(prior volume) log_prior_vol = np.sum( np.log([prior.maximum - prior.minimum for key, prior in priors.items()]) ) log_evidence = -log_prior_vol sampled_std = [ np.std(result.posterior[param]) for param in result.search_parameter_keys ] logger.info("Analytic log evidence: " + str(log_evidence)) logger.info( "Sampled log evidence: " + str(result.log_evidence) + " +/- " + str(result.log_evidence_err) ) for i, search_parameter_key in enumerate(result.search_parameter_keys): logger.info(search_parameter_key) logger.info("Expected posterior standard deviation: " + str(likelihood.sigma[i])) logger.info("Sampled posterior standard deviation: " + str(sampled_std[i])) # BIMODAL distribution label = "multidim_gaussian_bimodal" dim = len(cov[0]) mean_1 = 4 * np.sqrt(np.diag(cov)) mean_2 = -4 * np.sqrt(np.diag(cov)) likelihood = AnalyticalMultidimensionalBimodalCovariantGaussian(mean_1, mean_2, cov) priors = bilby.core.prior.PriorDict() priors.update( { "x{0}".format(i): bilby.core.prior.Uniform(-5, 5, "x{0}".format(i)) for i in range(dim) } ) result = bilby.run_sampler( likelihood=likelihood, priors=priors, sampler="dynesty", outdir=outdir, label=label, check_point_plot=True, resume=True, ) result.plot_corner( parameters={"x{0}".format(i): mean_1[i] for i in range(dim)}, filename=outdir + "/multidim_gaussian_bimodal_mode_1", ) result.plot_corner( parameters={"x{0}".format(i): mean_2[i] for i in range(dim)}, filename=outdir + "/multidim_gaussian_bimodal_mode_2", ) log_prior_vol = np.sum( np.log([prior.maximum - prior.minimum for key, prior in priors.items()]) ) log_evidence = -log_prior_vol sampled_std_1 = [] sampled_std_2 = [] for param in result.search_parameter_keys: samples = np.array(result.posterior[param]) samples_1 = samples[np.where(samples < 0)] samples_2 = samples[np.where(samples > 0)] sampled_std_1.append(np.std(samples_1)) sampled_std_2.append(np.std(samples_2)) logger.info("Analytic log evidence: " + str(log_evidence)) logger.info( "Sampled log evidence: " + str(result.log_evidence) + " +/- " + str(result.log_evidence_err) ) for i, search_parameter_key in enumerate(result.search_parameter_keys): logger.info(search_parameter_key) logger.info( "Expected posterior standard deviation both modes: " + str(likelihood.sigma[i]) ) logger.info( "Sampled posterior standard deviation first mode: " + str(sampled_std_1[i]) ) logger.info( "Sampled posterior standard deviation second mode: " + str(sampled_std_2[i]) )

0

d142eccada5f83c8232284acc025dd5dfbe3b8aa

1,272

py

Python

lib/descriptor.py

scott-zhou/pyjvm

56b22a0fee77d1586bb3fda301896231aded0170

[ "MIT" ]

12

2017-01-17T13:47:30.000Z

2022-02-10T07:01:55.000Z

lib/descriptor.py

scott-zhou/pyjvm

56b22a0fee77d1586bb3fda301896231aded0170

[ "MIT" ]

null

lib/descriptor.py

scott-zhou/pyjvm

56b22a0fee77d1586bb3fda301896231aded0170

[ "MIT" ]

2

2018-02-24T07:56:02.000Z

2018-07-11T03:49:35.000Z

import re

31.02439

81

0.568396

import re def parse_field_descriptor(field, void=False): base_type = [ ('B', 'byte'), ('C', 'char'), ('D', 'double'), ('F', 'float'), ('I', 'int'), ('J', 'long'), ('S', 'short'), ('Z', 'boolean'), ] if void: base_type.append(('V', 'void')) base_pattern = '[' + ''.join(t for t, _ in base_type) + ']' object_type = [ ('L.+?;', 'reference'), ] object_pattern = object_type[0][0] array_type = [ ('\[+' + base_pattern, 'base type array reference'), ('\[+' + object_pattern, 'object type array reference'), ] array_pattern = '|'.join(t for t, _ in array_type) field_pattern = '|'.join([base_pattern, object_pattern, array_pattern]) pattern = re.compile(field_pattern) fields = pattern.findall(field) return fields def parse_method_descriptor(method_d): pattern = re.compile('$.*?$|.+') parts = pattern.findall(method_d) assert len(parts) == 2, 'Invalid method descriptor {d}'.format(d=method_d) assert parts[0][0] == '(', 'Invalid method descriptor {d}'.format(d=method_d) parameters = parse_field_descriptor(parts[0][1:-1]) rt = parse_field_descriptor(parts[1], True) return parameters, rt

1,214

0

46

4ea48d247045e2133033239fb19305c97a5233b5

3,646

py

Python

custom_components/promql/sensor.py

Adi146/home-assistant-promql

f4c302da407b816b0cc4bf3cc69c55552e0207f2

[ "MIT" ]

null

custom_components/promql/sensor.py

Adi146/home-assistant-promql

f4c302da407b816b0cc4bf3cc69c55552e0207f2

[ "MIT" ]

null

custom_components/promql/sensor.py

Adi146/home-assistant-promql

f4c302da407b816b0cc4bf3cc69c55552e0207f2

[ "MIT" ]

null

from datetime import timedelta import logging from homeassistant.core import callback from homeassistant.components.sensor import SensorEntity from homeassistant.helpers.entity import DeviceInfo from homeassistant.helpers.update_coordinator import ( DataUpdateCoordinator, ) from homeassistant.const import ( CONF_NAME, CONF_UNIT_OF_MEASUREMENT, ) from .const import ( DOMAIN, PROMETHEUS_METRIC_KEY, PROMETHEUS_VALUE_KEY, PROMETHEUS_JOB_KEY, PROMETHEUS_INSTANCE_KEY, ) from . import requestData _LOGGER = logging.getLogger(__name__)

26.808824

87

0.651947

from datetime import timedelta import logging from homeassistant.core import callback from homeassistant.components.sensor import SensorEntity from homeassistant.helpers.entity import DeviceInfo from homeassistant.helpers.update_coordinator import ( DataUpdateCoordinator, ) from homeassistant.const import ( CONF_NAME, CONF_UNIT_OF_MEASUREMENT, ) from .const import ( DOMAIN, PROMETHEUS_METRIC_KEY, PROMETHEUS_VALUE_KEY, PROMETHEUS_JOB_KEY, PROMETHEUS_INSTANCE_KEY, ) from . import requestData _LOGGER = logging.getLogger(__name__) async def async_setup_entry(hass, entry, async_add_entities): async def async_update_data(): result = await hass.async_add_executor_job( requestData, entry.data, ) return result["data"]["result"] coordinator = DataUpdateCoordinator( hass, _LOGGER, name="sensor", update_method=async_update_data, update_interval=timedelta(seconds=15), ) sensors = {} @callback def async_data_updated(): updated_sensors = [] for data in coordinator.data: unique_id = generate_unique_id(entry.entry_id, data[PROMETHEUS_METRIC_KEY]) if unique_id in sensors: sensors[unique_id].setData(data) else: newSensor = PromQLSensor(entry, unique_id, data) sensors[unique_id] = newSensor async_add_entities([newSensor]) updated_sensors.append(sensors[unique_id]) for sensor in sensors.values(): if sensor not in updated_sensors: sensor.setData(None) coordinator.async_add_listener(async_data_updated) await coordinator.async_config_entry_first_refresh() def generate_unique_id(entry_id, metric): return f"{entry_id}_{'_'.join(metric.values())}" class PromQLSensor(SensorEntity): def __init__(self, entry, unique_id, data): self._entry_id = entry.entry_id self._name = entry.data[CONF_NAME] self._attr_unit_of_measurement = entry.data.get(CONF_UNIT_OF_MEASUREMENT) self._attr_unique_id = unique_id self._data = data @property def name(self) -> str: if self._getData() is None or self._getInstanceHost() is None: return self._name return f"{self._getInstanceHost()} {self._name}" @property def state(self) -> str: return self._getValue()[1] @property def extra_state_attributes(self) -> dict: return self._getMetric() @property def device_info(self) -> DeviceInfo: if self._getInstance() is None: return None return DeviceInfo( identifiers={(DOMAIN, self._getInstance())}, name=self._getInstanceHost(), ) @property def should_poll(self) -> bool: return False def _getData(self) -> dict: return self._data def setData(self, data): if data is not None: self._data = data self._attr_available = data is not None self.async_write_ha_state() def _getMetric(self) -> dict: return self._getData()[PROMETHEUS_METRIC_KEY] def _getValue(self) -> str: return self._getData()[PROMETHEUS_VALUE_KEY] def _getJob(self) -> str: return self._getMetric().get(PROMETHEUS_JOB_KEY) def _getInstance(self) -> str: return self._getMetric().get(PROMETHEUS_INSTANCE_KEY) def _getInstanceHost(self) -> str: if self._getInstance() is None: return None return self._getInstance().split(":")[0]

2,574

432

69

d89fafd2c0a2db24b2fef7f82022eb82d78c0982

451

py

Python

spacy/tests/lang/da/test_exceptions.py

DEVESHTARASIA/spaCy

4c5d2c80d5e273cdc2ed7be6eb378bb7fb3c0c31

[ "MIT" ]

2

2019-07-08T17:09:22.000Z

2021-01-09T17:36:04.000Z

spacy/tests/lang/da/test_exceptions.py

DEVESHTARASIA/spaCy

4c5d2c80d5e273cdc2ed7be6eb378bb7fb3c0c31

[ "MIT" ]

null

spacy/tests/lang/da/test_exceptions.py

DEVESHTARASIA/spaCy

4c5d2c80d5e273cdc2ed7be6eb378bb7fb3c0c31

[ "MIT" ]

null

# coding: utf-8 from __future__ import unicode_literals import pytest @pytest.mark.parametrize('text', ["ca.", "m.a.o.", "Jan.", "Dec."])

28.1875

67

0.698448

# coding: utf-8 from __future__ import unicode_literals import pytest @pytest.mark.parametrize('text', ["ca.", "m.a.o.", "Jan.", "Dec."]) def test_da_tokenizer_handles_abbr(da_tokenizer, text): tokens = da_tokenizer(text) assert len(tokens) == 1 def test_da_tokenizer_handles_exc_in_text(da_tokenizer): text = "Det er bl.a. ikke meningen" tokens = da_tokenizer(text) assert len(tokens) == 5 assert tokens[2].text == "bl.a."

266

0

45

fb9754315cd56c3ee0852233f95ab43b0772c530

642

py

Python

11 Object Oriented Programming/product.py

Himanshu44626748/Learn-Python

f3a4d997f2d29b146e5f7434f4801ae94bc3483f

[ "MIT" ]

2

2020-03-16T14:57:44.000Z

2020-11-29T07:45:54.000Z

11 Object Oriented Programming/product.py

Himanshu44626748/Learn-Python

f3a4d997f2d29b146e5f7434f4801ae94bc3483f

[ "MIT" ]

null

11 Object Oriented Programming/product.py

Himanshu44626748/Learn-Python

f3a4d997f2d29b146e5f7434f4801ae94bc3483f

[ "MIT" ]

1

2020-08-13T07:59:02.000Z

'''This is my first class in python''' p1 = Product() p1.display() # print(p1.name) # print(p1.description) # print(p1.price) p2 = Product() p2.display() # print(p2.name) # print(p2.description) # print(p2.price)

24.692308

167

0.629283

'''This is my first class in python''' class Product: def __init__(self): self.name = 'Dell Inspiron' self.description = 'Laptop, i7, 8th Gen, 8 GB RAM, 512 GB SSD' self.price = 91000 def display(self): # Added an Instance function to print, so that we don't need to print each and every entity for every object separately print(self.name) print(self.description) print(self.price) p1 = Product() p1.display() # print(p1.name) # print(p1.description) # print(p1.price) p2 = Product() p2.display() # print(p2.name) # print(p2.description) # print(p2.price)

357

-7

76

5e8ac64fbe70fe326a2767fef3d9300d1b292115

2,049

py

Python

class_4/dungeon.py

goosemanjack/python_intro_class

ca4b2390f2b0bb037d94ed4516d98848b7cf97d6

[ "MIT" ]

null

class_4/dungeon.py

goosemanjack/python_intro_class

ca4b2390f2b0bb037d94ed4516d98848b7cf97d6

[ "MIT" ]

null

class_4/dungeon.py

goosemanjack/python_intro_class

ca4b2390f2b0bb037d94ed4516d98848b7cf97d6

[ "MIT" ]

null

# Dungeon Crawler import asciiart import level1 import level2 import time # timer import hero #def test(): # print(asciiart.baby_dragon()) # print(asciiart.big_skull()) # print(asciiart.dragon()) # print(asciiart.samurai()) # print(asciiart.skull_cross()) # print(asciiart.warrior()) # print(asciiart.chicken()) global my_hero = hero.Hero("Bob") start_dungeon()

19.893204

79

0.570522

# Dungeon Crawler import asciiart import level1 import level2 import time # timer import hero #def test(): # print(asciiart.baby_dragon()) # print(asciiart.big_skull()) # print(asciiart.dragon()) # print(asciiart.samurai()) # print(asciiart.skull_cross()) # print(asciiart.warrior()) # print(asciiart.chicken()) global my_hero = hero.Hero("Bob") def start_dungeon(): global my_hero result = level1.first_room() if result == 1: print(asciiart.chicken()) print("Have fun baking pies in safety, you baby.") return else: print("You are a brave soul!") print("") time.sleep(0.75) result = level1.second_room() if(result == 1): print(asciiart.skull_cross()) print("You are dead. It should have been obvious not to open the box.") return elif(result == 3): return start_dungeon() print("") result = level1.next_level() if(result == 1): result = level1.second_room() #... return elif(result == 2): return run_second_room() def run_second_room(): print("") result = level2.nest() if result == 1: print(asciiart.baby_dragon()) time.sleep(0.75) print("You have birthed a baby!") return elif result == 2: print(asciiart.dragon()) print("Oh no! Momma dragon is here and she isn't happy!") time.sleep(1.25) print(asciiart.big_skull()) print("You are dead") return print("") result = level2.dragon_lair() if result == 1: print(asciiart.samurai()) time.sleep(1.1) print(asciiart.dragon()) time.sleep(1.25) print("....") time.sleep(0.25) print("You are VICTORIOUS!!!") return else: print(asciiart.dragon()) print("The dragon awakens! Prepare for battle.") time.sleep(0.75) print(asciiart.big_skull()) print("You are dead") start_dungeon()

1,600

0

46

935cbb30e7c351867221dc569f3fce1527a04ae9

214

py

Python

setup.py

tzelleke/floodfill

ba11c990e9b2844fba1e5ec367c80571600d106c

[ "MIT" ]

5

2016-10-08T02:46:30.000Z

2021-08-30T12:43:53.000Z

setup.py

tzelleke/mepfinder

ba11c990e9b2844fba1e5ec367c80571600d106c

[ "MIT" ]

null

setup.py

tzelleke/mepfinder

ba11c990e9b2844fba1e5ec367c80571600d106c

[ "MIT" ]

null

from distutils.core import setup setup( name='mepfinder', version='0.1', packages=['mepfinder'], url='', license='MIT', author='Theodros Zelleke', author_email='', description='' )

16.461538

32

0.602804

from distutils.core import setup setup( name='mepfinder', version='0.1', packages=['mepfinder'], url='', license='MIT', author='Theodros Zelleke', author_email='', description='' )

0

9fe1c1e0ce7af6f205e8ffd160b033bde2928be9

5,162

py

Python

pokemon_classifier.py

taritkandpal/Classifier-Comparison

c87b9a40ab5d296e667ac76510e23b0fbc48e4c4

[ "MIT" ]

null

pokemon_classifier.py

taritkandpal/Classifier-Comparison

c87b9a40ab5d296e667ac76510e23b0fbc48e4c4

[ "MIT" ]

null

pokemon_classifier.py

taritkandpal/Classifier-Comparison

c87b9a40ab5d296e667ac76510e23b0fbc48e4c4

[ "MIT" ]

null

# Importing the libraries import numpy as np import matplotlib.pyplot as plt import pandas as pd # Importing the dataset dataset = pd.read_csv('pokemonchg.csv') X = dataset.iloc[:, [19,20,21,22,23,25,28,35]].values y = dataset.iloc[:, 40].values # Splitting the dataset into the Training set and Test set from sklearn.model_selection import train_test_split X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.25, random_state = 0) # Feature Scaling from sklearn.preprocessing import StandardScaler sc = StandardScaler() X_train = sc.fit_transform(X_train) X_test = sc.transform(X_test) #accuracy from sklearn.metrics import accuracy_score # Fitting Random Forest Classification to the Training set from sklearn.ensemble import RandomForestClassifier classifier = RandomForestClassifier(n_estimators = 10, criterion = 'entropy', random_state = 0) classifier.fit(X_train, y_train) # Predicting the Test set results y_pred = classifier.predict(X_test) # Making the Confusion Matrix from sklearn.metrics import confusion_matrix cm_randomforest = confusion_matrix(y_test, y_pred) acc_randomforest=accuracy_score(y_test,y_pred)*100 # Fitting Kernel SVM to the Training set from sklearn.svm import SVC classifier = SVC(kernel = 'rbf', random_state = 0) classifier.fit(X_train, y_train) # Predicting the Test set results y_pred = classifier.predict(X_test) # Making the Confusion Matrix from sklearn.metrics import confusion_matrix cm_svmkernel = confusion_matrix(y_test, y_pred) acc_svmkernel=accuracy_score(y_test,y_pred)*100 # Fitting K-NN to the Training set from sklearn.neighbors import KNeighborsClassifier classifier = KNeighborsClassifier(n_neighbors = 5, metric = 'minkowski', p = 2) classifier.fit(X_train, y_train) # Predicting the Test set results y_pred = classifier.predict(X_test) # Making the Confusion Matrix from sklearn.metrics import confusion_matrix cm_knn = confusion_matrix(y_test, y_pred) acc_knn=accuracy_score(y_test,y_pred)*100 # Fitting Naive Bayes to the Training set from sklearn.naive_bayes import GaussianNB classifier = GaussianNB() classifier.fit(X_train, y_train) # Predicting the Test set results y_pred = classifier.predict(X_test) # Making the Confusion Matrix from sklearn.metrics import confusion_matrix cm_naivebayes = confusion_matrix(y_test, y_pred) acc_naivebayes=accuracy_score(y_test,y_pred)*100 # Fitting Decision Tree Classification to the Training set from sklearn.tree import DecisionTreeClassifier classifier = DecisionTreeClassifier(criterion = 'entropy', random_state = 0) classifier.fit(X_train, y_train) # Predicting the Test set results y_pred = classifier.predict(X_test) # Making the Confusion Matrix from sklearn.metrics import confusion_matrix cm_decisiontree = confusion_matrix(y_test, y_pred) acc_decisiontree=accuracy_score(y_test,y_pred)*100 # Fitting SVM to the Training set from sklearn.svm import SVC classifier = SVC(kernel = 'linear', random_state = 0) classifier.fit(X_train, y_train) # Predicting the Test set results y_pred = classifier.predict(X_test) # Making the Confusion Matrix from sklearn.metrics import confusion_matrix cm_svm = confusion_matrix(y_test, y_pred) acc_svm=accuracy_score(y_test,y_pred)*100 # Fitting Logistic Regression to the Training set from sklearn.linear_model import LogisticRegression classifier = LogisticRegression(random_state = 0) classifier.fit(X_train, y_train) # Predicting the Test set results y_pred = classifier.predict(X_test) # Making the Confusion Matrix from sklearn.metrics import confusion_matrix cm_logistic = confusion_matrix(y_test, y_pred) acc_logistic=accuracy_score(y_test,y_pred)*100 # Importing the Keras libraries and packages import keras from keras.models import Sequential from keras.layers import Dense from tensorflow.python.keras import backend as k # Initialising the ANN classifier = Sequential() # Adding the input layer and the first hidden layer classifier.add(Dense(output_dim = 5, init = 'uniform', activation = 'relu', input_dim = 8)) # Adding the second hidden layer classifier.add(Dense(output_dim = 5, init = 'uniform', activation = 'relu')) # Adding the third hidden layer classifier.add(Dense(output_dim = 5, init = 'uniform', activation = 'relu')) # Adding the fourth hidden layer classifier.add(Dense(output_dim = 5, init = 'uniform', activation = 'relu')) # Adding the output layer classifier.add(Dense(output_dim = 1, init = 'uniform', activation = 'sigmoid')) # Compiling the ANN classifier.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics = ['accuracy']) # Fitting the ANN to the Training set classifier.fit(X_train, y_train, batch_size = 10, nb_epoch = 100) # Part 3 - Making the predictions and evaluating the model # Predicting the Test set results y_pred = classifier.predict(X_test) y_pred = (y_pred > 0.5) # Making the Confusion Matrix from sklearn.metrics import confusion_matrix cm_ann = confusion_matrix(y_test, y_pred) acc_ann=accuracy_score(y_test,y_pred)*100

31.47561

96

0.770632

# Importing the libraries import numpy as np import matplotlib.pyplot as plt import pandas as pd # Importing the dataset dataset = pd.read_csv('pokemonchg.csv') X = dataset.iloc[:, [19,20,21,22,23,25,28,35]].values y = dataset.iloc[:, 40].values # Splitting the dataset into the Training set and Test set from sklearn.model_selection import train_test_split X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.25, random_state = 0) # Feature Scaling from sklearn.preprocessing import StandardScaler sc = StandardScaler() X_train = sc.fit_transform(X_train) X_test = sc.transform(X_test) #accuracy from sklearn.metrics import accuracy_score # Fitting Random Forest Classification to the Training set from sklearn.ensemble import RandomForestClassifier classifier = RandomForestClassifier(n_estimators = 10, criterion = 'entropy', random_state = 0) classifier.fit(X_train, y_train) # Predicting the Test set results y_pred = classifier.predict(X_test) # Making the Confusion Matrix from sklearn.metrics import confusion_matrix cm_randomforest = confusion_matrix(y_test, y_pred) acc_randomforest=accuracy_score(y_test,y_pred)*100 # Fitting Kernel SVM to the Training set from sklearn.svm import SVC classifier = SVC(kernel = 'rbf', random_state = 0) classifier.fit(X_train, y_train) # Predicting the Test set results y_pred = classifier.predict(X_test) # Making the Confusion Matrix from sklearn.metrics import confusion_matrix cm_svmkernel = confusion_matrix(y_test, y_pred) acc_svmkernel=accuracy_score(y_test,y_pred)*100 # Fitting K-NN to the Training set from sklearn.neighbors import KNeighborsClassifier classifier = KNeighborsClassifier(n_neighbors = 5, metric = 'minkowski', p = 2) classifier.fit(X_train, y_train) # Predicting the Test set results y_pred = classifier.predict(X_test) # Making the Confusion Matrix from sklearn.metrics import confusion_matrix cm_knn = confusion_matrix(y_test, y_pred) acc_knn=accuracy_score(y_test,y_pred)*100 # Fitting Naive Bayes to the Training set from sklearn.naive_bayes import GaussianNB classifier = GaussianNB() classifier.fit(X_train, y_train) # Predicting the Test set results y_pred = classifier.predict(X_test) # Making the Confusion Matrix from sklearn.metrics import confusion_matrix cm_naivebayes = confusion_matrix(y_test, y_pred) acc_naivebayes=accuracy_score(y_test,y_pred)*100 # Fitting Decision Tree Classification to the Training set from sklearn.tree import DecisionTreeClassifier classifier = DecisionTreeClassifier(criterion = 'entropy', random_state = 0) classifier.fit(X_train, y_train) # Predicting the Test set results y_pred = classifier.predict(X_test) # Making the Confusion Matrix from sklearn.metrics import confusion_matrix cm_decisiontree = confusion_matrix(y_test, y_pred) acc_decisiontree=accuracy_score(y_test,y_pred)*100 # Fitting SVM to the Training set from sklearn.svm import SVC classifier = SVC(kernel = 'linear', random_state = 0) classifier.fit(X_train, y_train) # Predicting the Test set results y_pred = classifier.predict(X_test) # Making the Confusion Matrix from sklearn.metrics import confusion_matrix cm_svm = confusion_matrix(y_test, y_pred) acc_svm=accuracy_score(y_test,y_pred)*100 # Fitting Logistic Regression to the Training set from sklearn.linear_model import LogisticRegression classifier = LogisticRegression(random_state = 0) classifier.fit(X_train, y_train) # Predicting the Test set results y_pred = classifier.predict(X_test) # Making the Confusion Matrix from sklearn.metrics import confusion_matrix cm_logistic = confusion_matrix(y_test, y_pred) acc_logistic=accuracy_score(y_test,y_pred)*100 # Importing the Keras libraries and packages import keras from keras.models import Sequential from keras.layers import Dense from tensorflow.python.keras import backend as k # Initialising the ANN classifier = Sequential() # Adding the input layer and the first hidden layer classifier.add(Dense(output_dim = 5, init = 'uniform', activation = 'relu', input_dim = 8)) # Adding the second hidden layer classifier.add(Dense(output_dim = 5, init = 'uniform', activation = 'relu')) # Adding the third hidden layer classifier.add(Dense(output_dim = 5, init = 'uniform', activation = 'relu')) # Adding the fourth hidden layer classifier.add(Dense(output_dim = 5, init = 'uniform', activation = 'relu')) # Adding the output layer classifier.add(Dense(output_dim = 1, init = 'uniform', activation = 'sigmoid')) # Compiling the ANN classifier.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics = ['accuracy']) # Fitting the ANN to the Training set classifier.fit(X_train, y_train, batch_size = 10, nb_epoch = 100) # Part 3 - Making the predictions and evaluating the model # Predicting the Test set results y_pred = classifier.predict(X_test) y_pred = (y_pred > 0.5) # Making the Confusion Matrix from sklearn.metrics import confusion_matrix cm_ann = confusion_matrix(y_test, y_pred) acc_ann=accuracy_score(y_test,y_pred)*100

0

fe3462cce33307011401ed3f20189c90a2576830

1,900

py

Python

__init__.py

shrught/Create_LoginPage

41f3b57bce558110754167fcc32d13b7c77bd1f6

[ "MIT" ]

25

2021-03-23T22:05:07.000Z

2022-03-30T22:06:31.000Z

__init__.py

shrught/Create_LoginPage

41f3b57bce558110754167fcc32d13b7c77bd1f6

[ "MIT" ]

6

2021-08-30T06:57:53.000Z

2021-11-16T23:25:33.000Z

__init__.py

shrught/Create_LoginPage

41f3b57bce558110754167fcc32d13b7c77bd1f6

[ "MIT" ]

32

2021-02-27T21:25:07.000Z

2022-03-26T12:43:56.000Z

######################################################################## ################# Importing packages ####################### ######################################################################## from flask import Flask from flask_sqlalchemy import SQLAlchemy from flask_login import LoginManager # init SQLAlchemy so we can use it later in our models db = SQLAlchemy()

57.575758

142

0.679474

######################################################################## ################# Importing packages ####################### ######################################################################## from flask import Flask from flask_sqlalchemy import SQLAlchemy from flask_login import LoginManager # init SQLAlchemy so we can use it later in our models db = SQLAlchemy() def create_app(): app = Flask(__name__) # creates the Flask instance, __name__ is the name of the current Python module app.config['SECRET_KEY'] = 'secret-key-goes-here' # it is used by Flask and extensions to keep data safe app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///db.sqlite' #it is the path where the SQLite database file will be saved app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False # deactivate Flask-SQLAlchemy track modifications db.init_app(app) # Initialiaze sqlite database # The login manager contains the code that lets your application and Flask-Login work together login_manager = LoginManager() # Create a Login Manager instance login_manager.login_view = 'auth.login' # define the redirection path when login required and we attempt to access without being logged in login_manager.init_app(app) # configure it for login from models import User @login_manager.user_loader def load_user(user_id): #reload user object from the user ID stored in the session # since the user_id is just the primary key of our user table, use it in the query for the user return User.query.get(int(user_id)) # blueprint for auth routes in our app # blueprint allow you to orgnize your flask app from auth import auth as auth_blueprint app.register_blueprint(auth_blueprint) # blueprint for non-auth parts of app from main import main as main_blueprint app.register_blueprint(main_blueprint) return app

1,484

0

22

92f3b0fb601c87aa8ac221a3e268cbca2e468dfa

1,449

py

Python

paddlenlp/ops/optimizer/__init__.py

holazzer/PaddleNLP

14b6f897b875408c70cfd51230b4de8123e253ed

[ "Apache-2.0" ]

1

2022-01-04T01:37:10.000Z

paddlenlp/ops/optimizer/__init__.py

holazzer/PaddleNLP

14b6f897b875408c70cfd51230b4de8123e253ed

[ "Apache-2.0" ]

null

paddlenlp/ops/optimizer/__init__.py

holazzer/PaddleNLP

14b6f897b875408c70cfd51230b4de8123e253ed

[ "Apache-2.0" ]

null

# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os from paddle.utils.cpp_extension import load from .adamw import AdamW from .AdamwOptimizer import AdamwOptimizer from .adamwdl import AdamWDL __all__ = [ '_jit_compile', 'AdamW', 'AdamwOptimizer', 'AdamWDL', ]

29.571429

147

0.637681

# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os from paddle.utils.cpp_extension import load from .adamw import AdamW from .AdamwOptimizer import AdamwOptimizer from .adamwdl import AdamWDL def _jit_compile(): try: load( name="custom_jit_ops", sources=[ os.path.join(os.path.dirname(__file__), x) for x in [ "adamw.cc", "adamw.cu", ] ]) return True except RuntimeError as e: import sys sys.stderr.write(str(e) + "\n\n") sys.stderr.write( '''Warning with compile custom ops: compile custom adamw op failed. \nIf you do not use custom ops, please ignore this warning! \n\n''' ) return False __all__ = [ '_jit_compile', 'AdamW', 'AdamwOptimizer', 'AdamWDL', ]

577

0

23

0c3c499b54f5bd21c0622b78c59f6bfffa5106dd

19,731

py

Python

triangulation/myutils.py

mattjr/structured

0cb4635af7602f2a243a9b739e5ed757424ab2a7

[ "Apache-2.0" ]

14

2015-01-11T02:53:04.000Z

2021-11-25T17:31:22.000Z

triangulation/myutils.py

skair39/structured

0cb4635af7602f2a243a9b739e5ed757424ab2a7

[ "Apache-2.0" ]

null

triangulation/myutils.py

skair39/structured

0cb4635af7602f2a243a9b739e5ed757424ab2a7

[ "Apache-2.0" ]

14

2015-07-21T04:47:52.000Z

2020-03-12T12:31:25.000Z

################################################## # Copyright (c) INRIA (France) 2011, 2012, 2013 # # This file is part of inria-mvs. You can redistribute it and/or # modify it under the terms of the GNU General Public License. # # This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE # WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. # # Author: Jean-Paul CHIEZE <[email protected]> # ################################################## import sys, os, re, string from scipy import weave import numpy as np class MyException(Exception): """Bad parameter or file. The execution cannot continue """ def draw_point(buf,ix,iy,size,color,cross = False): """ draw a colored square around point (ix,iy) """ code = """ struct pts { int y; int nbx; int x[5]; }; struct pts rpoints[] = { {-1,3,-1,0,1}, {0,2,-1,1,0}, {1,3,-1,0,1}, }; struct pts cpoints[] = { {-2,1,0}, {-1,1,0}, {0,5,-2,-1,0,1,2}, {1,1,0}, {2,1,0}, }; #define NBLR sizeof(rpoints) / sizeof(struct pts) #define NBLC sizeof(cpoints) / sizeof(struct pts) #include <stdio.h> int nbl; struct pts *points; if(cross == 0) { nbl = NBLR; points = rpoints; } else { nbl = NBLC; points = cpoints; } int i, j, k, ky, kx, k0; int rdimx = 3 * dimx; for(j=0;j<nbl;j++) { ky = points[j].y + iy; if(ky < 0 || ky >= dimy) continue; k0 = ky * rdimx; for(i=0;i<points[j].nbx;i++) { kx = points[j].x[i] + ix; //printf("i,j = %d,%d, kx= %d, k0 = %d\\n",i,j,kx,k0); if(kx < 0 || kx >= dimx) continue; k = k0 + 3 * kx; *(buf+k++) = color[0]; *(buf+k++) = color[1]; *(buf+k) = color[2]; } } """ (dimx,dimy) = (size[0],size[1]) weave.inline(code,['buf' ,'ix','iy','dimx','dimy','color','cross']) def draw_color_rect(buf,ix,iy,size,wrect,color): """ draw a square centerd on x,y filled with color """ code = """ int nd = %d; int x, y, i, j; int ny = 1 + 2 * nd; int nx = ny; y = iy - nd; if (y < 0) { ny += y; y = 0; } else if ((y + ny) > dimy) ny -= y + ny - dimy; x = ix - nd; if (x < 0) { nx += x; x = 0; } else if ((x + nx) > dimx) nx -= x + nx - dimx; int k = y * dimx * 3 + 3 * x; int deltak = 3 * (dimx - nx); for (i = 0;i < ny;i++) { for (j = 0;j < nx;j++) { #if 1 *(buf+k++) = color[0]; *(buf+k++) = color[1]; *(buf+k++) = color[2]; #else *(buf+k) = (*(buf+k) / 2) + (color[0] / 2); k++; *(buf+k) = (*(buf+k) / 2) + (color[1] / 2); k++; *(buf+k) = (*(buf+k) / 2) + (color[2] / 2); k++; #endif } k += deltak; } """ %wrect (dimx,dimy) = (size[0],size[1]) #ll lqprint "XX %d %d" %(ix,iy) if(ix < 0 or iy < 0 or ix >= dimx or iy >= dimy): return() weave.inline(code,['buf' ,'ix','iy','dimx','dimy','color']) def c_projection(matr,pts3d,pts2d): """ fills pts2d (2xn array) with projection of pts3d (3xn array) """ code = """ int jj = 0; int i; float X[3]; float x; int ki, kj; for( i =0;i < npts;i++) { double *mat = matr; for(ki = 0;ki < 3; ki++) { x = 0; for(kj = 0;kj < 3;kj++) x += *(mat+kj) * *(pts3d + jj + kj); x += *(mat + 3); X[ki] = x; mat += 4; } x = X[2]; *(pts2d + jj) = X[0] / x; *(pts2d + jj + 1) = X[1] / x; *(pts2d + jj + 2) = x; jj += 3; } """ npts = pts3d.shape[1] weave.inline(code,['matr','pts3d','pts2d','npts']) def decode_line(s,l,func = float): """ split a string and convert each token with <func> and append the result to list <l> """ x = s.split() for v in x: l.append(func(v)) return(l) def get_bundle_header(bundler_file,num = None): """ reads header of <dir>/pmvs/bundle.rd.out output : file handle (pointing to the 1st point), nb of points + if num is given >= 0 : focal length and 3x4 Rotation-translation matrix of camera if num < 0 : array of focals and array of matrices for all cameras """ matPs = [] focals = [] f = open(bundler_file,'r') s = f.readline() s = f.readline() s = s.strip() l = s.split() if len(l) != 2: raise Exception, "Bad 1st line <%s> in bundle file" %s nbcam = int(l[0]) nbpts = int(l[1]) if num != None and num >= nbcam: raise Exception, "Only %d cameras" %nbcam for i in xrange(0,nbcam): (f,focal,m) = get_bundle_cam(f) if num < 0 or i == num: focals.append(focal) matPs.append(m) if num < 0: return(f,nbpts,focals,matPs) else: return(f,nbpts,focals[0],matPs[0]) def read_projmatrx(file,return_coef = False,return_pairs = False): """ return the 3x4 projection matrix read from the given pmvs .txt file """ mat = [] with open(file,'r') as f: lines = f.readlines() s = lines[0].strip() if (s != 'CONTOUR'): raise Exception, "Bad format <%s> for projection file" %s for i in range(1,4): s = lines[i].strip() l = s.split() for j in range(0,4): mat.append(float(l[j])) if return_coef or return_pairs: coef = None pairs = [] if(len(lines) >= 6): if(lines[4].strip() == 'COEF'): coef = float(lines[5].strip()) if return_pairs: if (len(lines) >= 10) and (lines[8].strip() == 'PAIRS'): nbp = int(lines[9].strip()) if (len(lines) >= (10 + nbp)): for i in xrange(0,nbp): xl = map(lambda x : int(x) ,lines[10 + i].strip().split()) pairs.append(xl) return(np.array(mat).reshape(3,4),coef,pairs) return(np.array(mat).reshape(3,4),coef) else: return(np.array(mat).reshape(3,4)) def get_bundle_points(f,nbpts,numcam): """ input : filehandle to bundle file (ready to read 1st point) nb of points, and num of picture output (lists): - 3d coordinates of all points (numcam == None) of points matched in camera numcam - corresponding 2d coordinates if numcam is specified (origine au centre de l'image) - colors of returned points """ pts3d = [] pts2d = [] ptscol = [] for k in xrange(0,nbpts): l = [] s = (f.readline()).strip() decode_line(s,l) l.append(1.) X = np.array(l) s = (f.readline()).strip() cols = [] decode_line(s,cols,int) if (numcam == None): pts3d.append(X) ptscol.append(np.array(cols)) f.readline() else: keys = [] s = (f.readline()).strip() decode_line(s,keys) n = int(keys[0]) i = 1 for j in xrange(0,n): if(int(keys[i]) != numcam): i += 4 continue rx = keys[i+2] ry = keys[i+3] i += 4 pts2d.append((rx,ry)) pts3d.append(X) ptscol.append(np.array(cols)) break return(pts3d,pts2d,ptscol) def get_ply_array(ptsfile): """ read the ply file and return the points coord as a 3xn array """ nbpts = 0 with open(ptsfile,'r') as f: s = f.readline() if s.strip() != 'ply': raise Exception, "Not a ply file!" while True: s = f.readline().strip() l = s.split() if (len(l) == 3 and l[0] == 'element' and l[1] == 'vertex'): nbpts = int(l[2]) continue if(s.strip() == 'end_header'): break if (s == ''): break # start with points kk = 0 pts3d = np.empty((3,nbpts),dtype=np.float,order="F") while True: s = (f.readline()).strip() if (s == ''): break l = s.split() n = len(l) if(n < 3): continue ln = [float(l[i]) for i in range(0,n)] pts3d[0,kk] = ln[0] pts3d[1,kk] = ln[1] pts3d[2,kk] = ln[2] kk += 1 return pts3d def get_ply_points(ptsfile,return_normals = False): """ read the ply file and return the lists of points and colors """ pts3d = [] ptscol = [] ptsnorm = [] with open(ptsfile,'r') as f: s = f.readline() if s.strip() != 'ply': raise Exception, "Not a ply file!" while True: s = f.readline() if(s.strip() == 'end_header'): break if (s == ''): break # start with points while True: s = (f.readline()).strip() if (s == ''): break l = s.split() n = len(l) if(n < 3): continue ln = [float(l[i]) for i in range(0,n)] pts3d.append(np.array([ln[0],ln[1],ln[2],1.])) if (n > 3): ptscol.append(np.array([ln[n-3],ln[n-2],ln[n-1]])) if (n > 6 and return_normals): ptsnorm.append(np.array([ln[3],ln[4],ln[5]])) if return_normals: return(pts3d,ptscol,ptsnorm) else: return(pts3d,ptscol) def projection(matrx,pts3d): """ returns the list of projections of <pts3d> points (origin at the image center). <matrx> is the projection matrix of camera and <size> the image width and height """ ptsxy = [] n = len(pts3d) ## print "MATR %s" %str(matrx) for i in xrange(0,n): X = pts3d[i] Y = np.dot(matrx,X) x = int(0.5 + Y[0] / Y[2]) y = int(0.5 + Y[1] / Y[2]) ptsxy.append((x,y)) return(ptsxy) color = np.array([0,255,0]) color2 = np.array([255,0,0]) color3 = np.array([255,255,0]) def draw_projection(ptsxy,refpts,ptscol,obuf,size,wrect,cross = False): """ input : 2d projections list (ptsxy), original 2d points (refpts) colors of points (ptscol), image buffer (obuf), image size drawing options (wrect,cross) Points are in image coordinates (0,0 = top left corner) writes 2d points (ptsxy) in the image buffer <obuf>; if wrect is None : a litle green square (cross = False) or cross (cross = True) is drawn centered on each point and if refpts is non empty, a red square or croos is drawn on these points If refpts[i] == ptsxy[i] : draw in yellow if wrect is given : at each point, fill a square of (2*wrect +1) size with the point color """ (nx,ny) = size ## nx2 = 0.5 + (float(nx) / 2) ## ny2 = .5 + (float(ny) / 2) n2d = len(refpts) ncol = len(ptscol) n = len(ptsxy) for i in xrange(0,n): (x,y) = ptsxy[i] if(wrect != None): draw_color_rect(obuf,x,y,size,wrect,ptscol[i]) else: draw_point(obuf,x,y,size,color) if n2d > 0: (rx,ry) = refpts[i] ## rx = int(rx + nx2) ## ry = ny - int(ny2 + ry) #print "XXX %d %d (%d %d)" %(x,y,rx,ry) if (rx == x and ry == y): col2 = color3 else: col2 = color2 draw_point(obuf,rx,ry,size,col2,cross) def calc_camparams(m,tzsign,verb=False): """ calculate intrinsics and extrinsics parameter of camera from 3x4 projection matrix m NB : tzsign is ignored and will be removed in a next release """ a1 = m[0,0:3] a2 = m[1,0:3] a3 = m[2,0:3] b = np.array([[m[0,3]],[m[1,3]],[m[2,3]]]) eps = 1 rho=eps / np.linalg.norm(a3) r3 = rho * a3 x0 = rho * rho * np.dot(a1.T, a3) y0 = rho * rho * np.dot(a2.T,a3) b1 = np.cross(a1,a3) b2 = np.cross(a2,a3); theta = np.arccos(- np.dot(b1.T,b2) / (np.linalg.norm(b1)*np.linalg.norm(b2))) # The magnifications are assumed to be positive.. alpha = rho * rho * np.linalg.norm(b1) * np.sin(theta) beta = rho * rho * np.linalg.norm(b2) * np.sin(theta) b23 = np.cross(a2,a3) r1 = (1. / np.linalg.norm(b23)) * b23 r2 = np.cross(r3,r1) K = np.array([[alpha, -alpha * np.cos(theta) / np.sin(theta), x0], [ 0, beta/np.sin(theta), y0], [0, 0, 1]]) t = rho * np.linalg.solve(K,b) # The sign of the solution is unknow : the last element in # original and recalculated projection matrices must be the same R = np.array([r1.T, r2.T, r3.T]) M = m M2 = np.dot(K,np.concatenate((R,t),1)) tzsign = M[0,0] * M2[0,0] * M[2,3] * M2[2,3] if tzsign < 0: r3 = -r3 r2 = -r2 t = -t R = np.array([r1.T, r2.T, r3.T]) M2 = np.dot(K,np.concatenate((R,t),1)) rho =M[0,0] / M2[0,0] M2 = rho * M2 intrins = np.array([alpha,beta,180 * theta / np.pi]) if verb: print "\nrho %f\nM= %s\nM2= %s" %(rho,str(M),str(M2)) print "R= %s\nt= %s\nintrinsic= %s" %(str(R),str(t),str(intrins)) print "x0,y0 %s %s" %(x0,y0) X = np.array([[0.,0.,0.,1.],[t[0,0],t[1,0],-1.,1.]]) pts = projection(m,X) pts2 = projection(M2,X) (x,y) = pts[0];(x1,y1) = pts2[0] print "Proj de 0 : %.3f %.3f, %.3f %.3f" %(x,y,x1,y1) (x,y) = pts[1];(x1,y1) = pts2[1] print "Proj de C : %.3f %.3f, %.3f %.3f\n" %(x,y,x1,y1) return (K,R,t,M2) def calc_transform(pts3d1,pts3d2,cmn_pts): """ renvoie la matrice de transformation pour passer du repere 1 au repere 2 input : pts3d1 pts3d2, liste d'arrays de dim 4 cmn_pts : liste de couples d'indices dans pts3d1 pts3d2 """ nb = len(cmn_pts) if (nb < 6): print "Not enough (%d) common points!" %nb return None # if(nb > 25): # nb = 25 print "-- %d common projections" %nb A = np.zeros((3*nb,12)) zer = np.zeros((4,)) b = np.zeros((3*nb,)) for i in xrange(0,nb): (i1,i2) = cmn_pts[i] A[3 * i,:] = np.concatenate((pts3d1[i1],zer,zer)) A[3 * i + 1,:] = np.concatenate((zer,pts3d1[i1],zer)) A[3 * i + 2,:] = np.concatenate((zer,zer,pts3d1[i1])) b[3*i:3*(i+1)] = pts3d2[i2][0:3] x = np.linalg.lstsq(A,b)[0] x = np.concatenate((x,np.array([0.,0.,0.,1.]))) matr = x.reshape((4,4)) ## print "M= %s" %str(matr) emoy = 0. emax = 0. for i in xrange(0,nb): (i1,i2) = cmn_pts[i] p1 = pts3d1[i1] p2 = pts3d2[i2] y = np.dot(matr,p1) e = np.linalg.norm(y - p2) if e > emax: emax = e emoy += e emoy /= nb print "ERR max %f, moy %f" %(emax,emoy) return matr def print_matrix(M,file= None): """ print matrix m*n as m lines of n floats """ (m,n) = M.shape for i in xrange(0,m): l = map(lambda x : str(x),M[i,:]) s = ' '.join(l) if file == None: print s else: print >>file, s def mk_KRt(mat,focal,w,h): """ makes matrix in pmvs2 format from bundler camera data """ K = np.array([[-focal,0, 0.5 * w - 0.5], [0,focal,0.5 * h - 0.5], [0,0,1]]) M = np.dot(K,mat) return ( - np.concatenate((M,np.array([0,0,0,1],ndmin=2)),0)) def read_metis_graph(file): """ reads the metis graph (1st line = nb-img 2*nb-edges, other lines : neighbours of each image Output : list of lists (list[i] = neighbours of i) """ graph = [] try: f = open(file,'r') s = f.readline().strip() l = s.split() with_weights = False if len(l) == 3: with_weights = True while True: s = f.readline() if s == '': break l = [] if with_weights: x = s.strip().split() for i in xrange(0,len(x),2): l.append(int(x[i]) - 1) else: l = map(lambda x : int(x) - 1,s.strip().split()) graph.append(l) f.close() except Exception: raise MyException("%s open error" %file) return graph def read_adj_matrix(file): """ reads the adjacency matrix (values = nb of matched points) Output : list of lists (list[i] = list of (j, nb-match) where j is a neighbour of i) list[i] is ordered according to nb-match """ adj = [] try: f = open(file,'r') lines = f.readlines() f.close() except Exception: raise MyException("%s open error" %file) for s in lines: l = [] decode_line(s.strip(),l,func = int) neighbours = [] for i in xrange(0,len(l)): if l[i] != 0: neighbours.append((i,l[i])) neighbours = sorted(neighbours,cmp = lambda (i1,nb1),(i2,nb2) : nb1 - nb2) adj.append(neighbours) return adj

29.016176

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0.482743

################################################## # Copyright (c) INRIA (France) 2011, 2012, 2013 # # This file is part of inria-mvs. You can redistribute it and/or # modify it under the terms of the GNU General Public License. # # This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE # WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. # # Author: Jean-Paul CHIEZE <[email protected]> # ################################################## import sys, os, re, string from scipy import weave import numpy as np class MyException(Exception): """Bad parameter or file. The execution cannot continue """ def draw_point(buf,ix,iy,size,color,cross = False): """ draw a colored square around point (ix,iy) """ code = """ struct pts { int y; int nbx; int x[5]; }; struct pts rpoints[] = { {-1,3,-1,0,1}, {0,2,-1,1,0}, {1,3,-1,0,1}, }; struct pts cpoints[] = { {-2,1,0}, {-1,1,0}, {0,5,-2,-1,0,1,2}, {1,1,0}, {2,1,0}, }; #define NBLR sizeof(rpoints) / sizeof(struct pts) #define NBLC sizeof(cpoints) / sizeof(struct pts) #include <stdio.h> int nbl; struct pts *points; if(cross == 0) { nbl = NBLR; points = rpoints; } else { nbl = NBLC; points = cpoints; } int i, j, k, ky, kx, k0; int rdimx = 3 * dimx; for(j=0;j<nbl;j++) { ky = points[j].y + iy; if(ky < 0 || ky >= dimy) continue; k0 = ky * rdimx; for(i=0;i<points[j].nbx;i++) { kx = points[j].x[i] + ix; //printf("i,j = %d,%d, kx= %d, k0 = %d\\n",i,j,kx,k0); if(kx < 0 || kx >= dimx) continue; k = k0 + 3 * kx; *(buf+k++) = color[0]; *(buf+k++) = color[1]; *(buf+k) = color[2]; } } """ (dimx,dimy) = (size[0],size[1]) weave.inline(code,['buf' ,'ix','iy','dimx','dimy','color','cross']) def draw_color_rect(buf,ix,iy,size,wrect,color): """ draw a square centerd on x,y filled with color """ code = """ int nd = %d; int x, y, i, j; int ny = 1 + 2 * nd; int nx = ny; y = iy - nd; if (y < 0) { ny += y; y = 0; } else if ((y + ny) > dimy) ny -= y + ny - dimy; x = ix - nd; if (x < 0) { nx += x; x = 0; } else if ((x + nx) > dimx) nx -= x + nx - dimx; int k = y * dimx * 3 + 3 * x; int deltak = 3 * (dimx - nx); for (i = 0;i < ny;i++) { for (j = 0;j < nx;j++) { #if 1 *(buf+k++) = color[0]; *(buf+k++) = color[1]; *(buf+k++) = color[2]; #else *(buf+k) = (*(buf+k) / 2) + (color[0] / 2); k++; *(buf+k) = (*(buf+k) / 2) + (color[1] / 2); k++; *(buf+k) = (*(buf+k) / 2) + (color[2] / 2); k++; #endif } k += deltak; } """ %wrect (dimx,dimy) = (size[0],size[1]) #ll lqprint "XX %d %d" %(ix,iy) if(ix < 0 or iy < 0 or ix >= dimx or iy >= dimy): return() weave.inline(code,['buf' ,'ix','iy','dimx','dimy','color']) def c_projection(matr,pts3d,pts2d): """ fills pts2d (2xn array) with projection of pts3d (3xn array) """ code = """ int jj = 0; int i; float X[3]; float x; int ki, kj; for( i =0;i < npts;i++) { double *mat = matr; for(ki = 0;ki < 3; ki++) { x = 0; for(kj = 0;kj < 3;kj++) x += *(mat+kj) * *(pts3d + jj + kj); x += *(mat + 3); X[ki] = x; mat += 4; } x = X[2]; *(pts2d + jj) = X[0] / x; *(pts2d + jj + 1) = X[1] / x; *(pts2d + jj + 2) = x; jj += 3; } """ npts = pts3d.shape[1] weave.inline(code,['matr','pts3d','pts2d','npts']) def c_find_common_points(pts1,pts2,npts,nx,ny): code_mark = """ int j, i; int npt = 0, ndbl = 0; float *zpts = (float *)malloc(nx * ny *sizeof(float)); for (i = 0;i < npts;i++) { int x = (int) (pts[3 * i] + 0.5); int y = (int) (pts[3 * i + 1] + 0.5); float z = pts[3 * i + 2]; if(x < 0 || y < 0 || x >= nx || y >= ny) continue; j = x * ny + y; npt++; if (buf[j] == 0) { buf[j] = i + 1; zpts[j] = z; #if 1 } else if(zpts[j] > z) { buf[j] = i + 1; zpts[j] = z; #else } else { buf[j] = -1; #endif ndbl++; } } printf("XX (%d) %d pts, %d dbl\\n",npts,npt,ndbl); """ code_cmn = """ int i, nb; int k = 0; for (i = 0;i < nx * ny;i++) { if(buf1[i] > 0 && buf2 [i] > 0) { cmnpts[k++] = buf1[i] - 1; cmnpts[k++] = buf2[i] - 1; nb++; } } return_val = nb; """ buf1 = np.zeros((ny*nx),dtype = np.int) buf2 = np.zeros((ny*nx),dtype = np.int) pts = pts1 buf = buf1 weave.inline(code_mark,['buf','pts','npts','nx','ny']) pts = pts2 buf = buf2 weave.inline(code_mark,['buf','pts','npts','nx','ny']) cmnpts = np.empty((2,npts),dtype=np.int,order="F") nb = weave.inline(code_cmn,['buf1','buf2','cmnpts','nx','ny']) print "XX CMN %s %s" %(str(cmnpts[:,0]),str(cmnpts[:,1])) return (nb,cmnpts) def decode_line(s,l,func = float): """ split a string and convert each token with <func> and append the result to list <l> """ x = s.split() for v in x: l.append(func(v)) return(l) def get_bundle_cam(f): l = [] for i in range(0,5): s = (f.readline()).strip() decode_line(s,l) matP = np.array([[l[3],l[4],l[5],l[12]], [l[6],l[7],l[8],l[13]], [l[9],l[10],l[11],l[14]]]) focal = l[0] return (f,focal,matP) def get_bundle_header(bundler_file,num = None): """ reads header of <dir>/pmvs/bundle.rd.out output : file handle (pointing to the 1st point), nb of points + if num is given >= 0 : focal length and 3x4 Rotation-translation matrix of camera if num < 0 : array of focals and array of matrices for all cameras """ matPs = [] focals = [] f = open(bundler_file,'r') s = f.readline() s = f.readline() s = s.strip() l = s.split() if len(l) != 2: raise Exception, "Bad 1st line <%s> in bundle file" %s nbcam = int(l[0]) nbpts = int(l[1]) if num != None and num >= nbcam: raise Exception, "Only %d cameras" %nbcam for i in xrange(0,nbcam): (f,focal,m) = get_bundle_cam(f) if num < 0 or i == num: focals.append(focal) matPs.append(m) if num < 0: return(f,nbpts,focals,matPs) else: return(f,nbpts,focals[0],matPs[0]) def read_projmatrx(file,return_coef = False,return_pairs = False): """ return the 3x4 projection matrix read from the given pmvs .txt file """ mat = [] with open(file,'r') as f: lines = f.readlines() s = lines[0].strip() if (s != 'CONTOUR'): raise Exception, "Bad format <%s> for projection file" %s for i in range(1,4): s = lines[i].strip() l = s.split() for j in range(0,4): mat.append(float(l[j])) if return_coef or return_pairs: coef = None pairs = [] if(len(lines) >= 6): if(lines[4].strip() == 'COEF'): coef = float(lines[5].strip()) if return_pairs: if (len(lines) >= 10) and (lines[8].strip() == 'PAIRS'): nbp = int(lines[9].strip()) if (len(lines) >= (10 + nbp)): for i in xrange(0,nbp): xl = map(lambda x : int(x) ,lines[10 + i].strip().split()) pairs.append(xl) return(np.array(mat).reshape(3,4),coef,pairs) return(np.array(mat).reshape(3,4),coef) else: return(np.array(mat).reshape(3,4)) def get_bundle_points(f,nbpts,numcam): """ input : filehandle to bundle file (ready to read 1st point) nb of points, and num of picture output (lists): - 3d coordinates of all points (numcam == None) of points matched in camera numcam - corresponding 2d coordinates if numcam is specified (origine au centre de l'image) - colors of returned points """ pts3d = [] pts2d = [] ptscol = [] for k in xrange(0,nbpts): l = [] s = (f.readline()).strip() decode_line(s,l) l.append(1.) X = np.array(l) s = (f.readline()).strip() cols = [] decode_line(s,cols,int) if (numcam == None): pts3d.append(X) ptscol.append(np.array(cols)) f.readline() else: keys = [] s = (f.readline()).strip() decode_line(s,keys) n = int(keys[0]) i = 1 for j in xrange(0,n): if(int(keys[i]) != numcam): i += 4 continue rx = keys[i+2] ry = keys[i+3] i += 4 pts2d.append((rx,ry)) pts3d.append(X) ptscol.append(np.array(cols)) break return(pts3d,pts2d,ptscol) def get_ply_array(ptsfile): """ read the ply file and return the points coord as a 3xn array """ nbpts = 0 with open(ptsfile,'r') as f: s = f.readline() if s.strip() != 'ply': raise Exception, "Not a ply file!" while True: s = f.readline().strip() l = s.split() if (len(l) == 3 and l[0] == 'element' and l[1] == 'vertex'): nbpts = int(l[2]) continue if(s.strip() == 'end_header'): break if (s == ''): break # start with points kk = 0 pts3d = np.empty((3,nbpts),dtype=np.float,order="F") while True: s = (f.readline()).strip() if (s == ''): break l = s.split() n = len(l) if(n < 3): continue ln = [float(l[i]) for i in range(0,n)] pts3d[0,kk] = ln[0] pts3d[1,kk] = ln[1] pts3d[2,kk] = ln[2] kk += 1 return pts3d def get_ply_points(ptsfile,return_normals = False): """ read the ply file and return the lists of points and colors """ pts3d = [] ptscol = [] ptsnorm = [] with open(ptsfile,'r') as f: s = f.readline() if s.strip() != 'ply': raise Exception, "Not a ply file!" while True: s = f.readline() if(s.strip() == 'end_header'): break if (s == ''): break # start with points while True: s = (f.readline()).strip() if (s == ''): break l = s.split() n = len(l) if(n < 3): continue ln = [float(l[i]) for i in range(0,n)] pts3d.append(np.array([ln[0],ln[1],ln[2],1.])) if (n > 3): ptscol.append(np.array([ln[n-3],ln[n-2],ln[n-1]])) if (n > 6 and return_normals): ptsnorm.append(np.array([ln[3],ln[4],ln[5]])) if return_normals: return(pts3d,ptscol,ptsnorm) else: return(pts3d,ptscol) def projection(matrx,pts3d): """ returns the list of projections of <pts3d> points (origin at the image center). <matrx> is the projection matrix of camera and <size> the image width and height """ ptsxy = [] n = len(pts3d) ## print "MATR %s" %str(matrx) for i in xrange(0,n): X = pts3d[i] Y = np.dot(matrx,X) x = int(0.5 + Y[0] / Y[2]) y = int(0.5 + Y[1] / Y[2]) ptsxy.append((x,y)) return(ptsxy) def norm_coord(pts,size): (nx,ny) = size nx2 = 0.5 + (float(nx) / 2) ny2 = 0.5 + (float(ny) / 2) n = len(pts); npts = [] for i in xrange(0,len(pts)): (rx,ry) = pts[i] rx = int(rx + nx2) ry = ny - int(ny2 + ry) npts.append((rx,ry)) return npts color = np.array([0,255,0]) color2 = np.array([255,0,0]) color3 = np.array([255,255,0]) def draw_projection(ptsxy,refpts,ptscol,obuf,size,wrect,cross = False): """ input : 2d projections list (ptsxy), original 2d points (refpts) colors of points (ptscol), image buffer (obuf), image size drawing options (wrect,cross) Points are in image coordinates (0,0 = top left corner) writes 2d points (ptsxy) in the image buffer <obuf>; if wrect is None : a litle green square (cross = False) or cross (cross = True) is drawn centered on each point and if refpts is non empty, a red square or croos is drawn on these points If refpts[i] == ptsxy[i] : draw in yellow if wrect is given : at each point, fill a square of (2*wrect +1) size with the point color """ (nx,ny) = size ## nx2 = 0.5 + (float(nx) / 2) ## ny2 = .5 + (float(ny) / 2) n2d = len(refpts) ncol = len(ptscol) n = len(ptsxy) for i in xrange(0,n): (x,y) = ptsxy[i] if(wrect != None): draw_color_rect(obuf,x,y,size,wrect,ptscol[i]) else: draw_point(obuf,x,y,size,color) if n2d > 0: (rx,ry) = refpts[i] ## rx = int(rx + nx2) ## ry = ny - int(ny2 + ry) #print "XXX %d %d (%d %d)" %(x,y,rx,ry) if (rx == x and ry == y): col2 = color3 else: col2 = color2 draw_point(obuf,rx,ry,size,col2,cross) def calc_camparams(m,tzsign,verb=False): """ calculate intrinsics and extrinsics parameter of camera from 3x4 projection matrix m NB : tzsign is ignored and will be removed in a next release """ a1 = m[0,0:3] a2 = m[1,0:3] a3 = m[2,0:3] b = np.array([[m[0,3]],[m[1,3]],[m[2,3]]]) eps = 1 rho=eps / np.linalg.norm(a3) r3 = rho * a3 x0 = rho * rho * np.dot(a1.T, a3) y0 = rho * rho * np.dot(a2.T,a3) b1 = np.cross(a1,a3) b2 = np.cross(a2,a3); theta = np.arccos(- np.dot(b1.T,b2) / (np.linalg.norm(b1)*np.linalg.norm(b2))) # The magnifications are assumed to be positive.. alpha = rho * rho * np.linalg.norm(b1) * np.sin(theta) beta = rho * rho * np.linalg.norm(b2) * np.sin(theta) b23 = np.cross(a2,a3) r1 = (1. / np.linalg.norm(b23)) * b23 r2 = np.cross(r3,r1) K = np.array([[alpha, -alpha * np.cos(theta) / np.sin(theta), x0], [ 0, beta/np.sin(theta), y0], [0, 0, 1]]) t = rho * np.linalg.solve(K,b) # The sign of the solution is unknow : the last element in # original and recalculated projection matrices must be the same R = np.array([r1.T, r2.T, r3.T]) M = m M2 = np.dot(K,np.concatenate((R,t),1)) tzsign = M[0,0] * M2[0,0] * M[2,3] * M2[2,3] if tzsign < 0: r3 = -r3 r2 = -r2 t = -t R = np.array([r1.T, r2.T, r3.T]) M2 = np.dot(K,np.concatenate((R,t),1)) rho =M[0,0] / M2[0,0] M2 = rho * M2 intrins = np.array([alpha,beta,180 * theta / np.pi]) if verb: print "\nrho %f\nM= %s\nM2= %s" %(rho,str(M),str(M2)) print "R= %s\nt= %s\nintrinsic= %s" %(str(R),str(t),str(intrins)) print "x0,y0 %s %s" %(x0,y0) X = np.array([[0.,0.,0.,1.],[t[0,0],t[1,0],-1.,1.]]) pts = projection(m,X) pts2 = projection(M2,X) (x,y) = pts[0];(x1,y1) = pts2[0] print "Proj de 0 : %.3f %.3f, %.3f %.3f" %(x,y,x1,y1) (x,y) = pts[1];(x1,y1) = pts2[1] print "Proj de C : %.3f %.3f, %.3f %.3f\n" %(x,y,x1,y1) return (K,R,t,M2) def calc_transform(pts3d1,pts3d2,cmn_pts): """ renvoie la matrice de transformation pour passer du repere 1 au repere 2 input : pts3d1 pts3d2, liste d'arrays de dim 4 cmn_pts : liste de couples d'indices dans pts3d1 pts3d2 """ nb = len(cmn_pts) if (nb < 6): print "Not enough (%d) common points!" %nb return None # if(nb > 25): # nb = 25 print "-- %d common projections" %nb A = np.zeros((3*nb,12)) zer = np.zeros((4,)) b = np.zeros((3*nb,)) for i in xrange(0,nb): (i1,i2) = cmn_pts[i] A[3 * i,:] = np.concatenate((pts3d1[i1],zer,zer)) A[3 * i + 1,:] = np.concatenate((zer,pts3d1[i1],zer)) A[3 * i + 2,:] = np.concatenate((zer,zer,pts3d1[i1])) b[3*i:3*(i+1)] = pts3d2[i2][0:3] x = np.linalg.lstsq(A,b)[0] x = np.concatenate((x,np.array([0.,0.,0.,1.]))) matr = x.reshape((4,4)) ## print "M= %s" %str(matr) emoy = 0. emax = 0. for i in xrange(0,nb): (i1,i2) = cmn_pts[i] p1 = pts3d1[i1] p2 = pts3d2[i2] y = np.dot(matr,p1) e = np.linalg.norm(y - p2) if e > emax: emax = e emoy += e emoy /= nb print "ERR max %f, moy %f" %(emax,emoy) return matr def print_matrix(M,file= None): """ print matrix m*n as m lines of n floats """ (m,n) = M.shape for i in xrange(0,m): l = map(lambda x : str(x),M[i,:]) s = ' '.join(l) if file == None: print s else: print >>file, s def mk_KRt(mat,focal,w,h): """ makes matrix in pmvs2 format from bundler camera data """ K = np.array([[-focal,0, 0.5 * w - 0.5], [0,focal,0.5 * h - 0.5], [0,0,1]]) M = np.dot(K,mat) return ( - np.concatenate((M,np.array([0,0,0,1],ndmin=2)),0)) def read_metis_graph(file): """ reads the metis graph (1st line = nb-img 2*nb-edges, other lines : neighbours of each image Output : list of lists (list[i] = neighbours of i) """ graph = [] try: f = open(file,'r') s = f.readline().strip() l = s.split() with_weights = False if len(l) == 3: with_weights = True while True: s = f.readline() if s == '': break l = [] if with_weights: x = s.strip().split() for i in xrange(0,len(x),2): l.append(int(x[i]) - 1) else: l = map(lambda x : int(x) - 1,s.strip().split()) graph.append(l) f.close() except Exception: raise MyException("%s open error" %file) return graph def read_adj_matrix(file): """ reads the adjacency matrix (values = nb of matched points) Output : list of lists (list[i] = list of (j, nb-match) where j is a neighbour of i) list[i] is ordered according to nb-match """ adj = [] try: f = open(file,'r') lines = f.readlines() f.close() except Exception: raise MyException("%s open error" %file) for s in lines: l = [] decode_line(s.strip(),l,func = int) neighbours = [] for i in xrange(0,len(l)): if l[i] != 0: neighbours.append((i,l[i])) neighbours = sorted(neighbours,cmp = lambda (i1,nb1),(i2,nb2) : nb1 - nb2) adj.append(neighbours) return adj def calc_cam_positions(cams,focals,R = None, t = None): poscams = [] for i in xrange(0,len(cams)): if focals[i] == 0: poscams.append(None) continue m = cams[i] R0 = m[:,0:3] t0 = -m[:,3] # Rinv = np.linalg.inv(R0) X = np.dot(R0.T,t0) ## print "XX %s, i= %d, t0 %s\nR0 %s\nR%s\nX %s" %(bundlefile,i,str(t0),str(R0),str(Rinv),str(X));quit() if R != None: X = np.dot(R,X) + t poscams.append((X[0],X[1],X[2])) return poscams

2,485

0

92

ebf94db1c4c91316cd7dab7c874067fd95792a17

48

py

Python

src/meltano/__init__.py

Bjenhamin4Alfredolvchenki/meltano

b8d1d812f4051b6334986fc6b447d23c4d0d5043

[ "MIT" ]

8

2020-06-16T22:29:54.000Z

2021-06-04T11:57:57.000Z

src/meltano/__init__.py

aroder/meltano

b8d1d812f4051b6334986fc6b447d23c4d0d5043

[ "MIT" ]

13

2021-03-10T19:44:58.000Z

2022-02-27T05:31:12.000Z

src/meltano/__init__.py

aroder/meltano

b8d1d812f4051b6334986fc6b447d23c4d0d5043

[ "MIT" ]

2

2020-06-16T22:29:59.000Z

2020-11-04T05:47:50.000Z

# Managed by bumpversion __version__ = "1.33.0"

16

24

0.729167

# Managed by bumpversion __version__ = "1.33.0"

0

b0200b1d4f3beb0be0474deb39c5f85e8f743623

393

py

Python

Chapter 2 - first neurons/layer-neurons-batch-data.py

benricok/pyNeural

5fc5710359e3a8d16d9bbb83679854bb07a817ad

[ "MIT" ]

null

Chapter 2 - first neurons/layer-neurons-batch-data.py

benricok/pyNeural

5fc5710359e3a8d16d9bbb83679854bb07a817ad

[ "MIT" ]

null

Chapter 2 - first neurons/layer-neurons-batch-data.py

benricok/pyNeural

5fc5710359e3a8d16d9bbb83679854bb07a817ad

[ "MIT" ]

null

import numpy as np inputs = [[1.0, 2.0, 3.0, 2.5], [2.0, 5.0, -1.0, 2.0], [-1.5, 2.7, 3.3, -0.8]] weights = [[0.2, 0.8, -0.5, 1.0], [0.5, -0.91, 0.26, -0.5], [-0.26, -0.27, 0.17, 0.87]] biases = [2.0, 3.0, 0.5] outputs = np.dot(inputs, np.array(weights).T) + biases print(outputs) # https://nnfs.io/crq # https://nnfs.io/gjw # https://nnfs.io/ch2

21.833333

54

0.475827

import numpy as np inputs = [[1.0, 2.0, 3.0, 2.5], [2.0, 5.0, -1.0, 2.0], [-1.5, 2.7, 3.3, -0.8]] weights = [[0.2, 0.8, -0.5, 1.0], [0.5, -0.91, 0.26, -0.5], [-0.26, -0.27, 0.17, 0.87]] biases = [2.0, 3.0, 0.5] outputs = np.dot(inputs, np.array(weights).T) + biases print(outputs) # https://nnfs.io/crq # https://nnfs.io/gjw # https://nnfs.io/ch2

0

6af2299e1cc21e04f6a15f4f77aa7af789e5fa58

10,794

py

Python

src/pipelinex/extras/ops/ignite/handlers/flexible_checkpoint.py

MarchRaBBiT/pipelinex

ea8def32a71752b667f9f3522acba3fd79102fe1

[ "Apache-2.0" ]

null

src/pipelinex/extras/ops/ignite/handlers/flexible_checkpoint.py

MarchRaBBiT/pipelinex

ea8def32a71752b667f9f3522acba3fd79102fe1

[ "Apache-2.0" ]

null

src/pipelinex/extras/ops/ignite/handlers/flexible_checkpoint.py

MarchRaBBiT/pipelinex

ea8def32a71752b667f9f3522acba3fd79102fe1

[ "Apache-2.0" ]

null

from datetime import datetime, timedelta import os import tempfile import torch import logging log = logging.getLogger(__name__) __all__ = ["FlexibleModelCheckpoint"] """ Copied from https://github.com/pytorch/ignite/blob/v0.2.1/ignite/handlers/checkpoint.py due to the change in ignite v0.3.0 """ class ModelCheckpoint(object): """ ModelCheckpoint handler can be used to periodically save objects to disk. This handler expects two arguments: - an :class:`~ignite.engine.Engine` object - a `dict` mapping names (`str`) to objects that should be saved to disk. See Notes and Examples for further details. Args: dirname (str): Directory path where objects will be saved. filename_prefix (str): Prefix for the filenames to which objects will be saved. See Notes for more details. save_interval (int, optional): if not None, objects will be saved to disk every `save_interval` calls to the handler. Exactly one of (`save_interval`, `score_function`) arguments must be provided. score_function (callable, optional): if not None, it should be a function taking a single argument, an :class:`~ignite.engine.Engine` object, and return a score (`float`). Objects with highest scores will be retained. Exactly one of (`save_interval`, `score_function`) arguments must be provided. score_name (str, optional): if `score_function` not None, it is possible to store its absolute value using `score_name`. See Notes for more details. n_saved (int, optional): Number of objects that should be kept on disk. Older files will be removed. atomic (bool, optional): If True, objects are serialized to a temporary file, and then moved to final destination, so that files are guaranteed to not be damaged (for example if exception occures during saving). require_empty (bool, optional): If True, will raise exception if there are any files starting with `filename_prefix` in the directory 'dirname'. create_dir (bool, optional): If True, will create directory 'dirname' if it doesnt exist. save_as_state_dict (bool, optional): If True, will save only the `state_dict` of the objects specified, otherwise the whole object will be saved. Note: This handler expects two arguments: an :class:`~ignite.engine.Engine` object and a `dict` mapping names to objects that should be saved. These names are used to specify filenames for saved objects. Each filename has the following structure: `{filename_prefix}_{name}_{step_number}.pth`. Here, `filename_prefix` is the argument passed to the constructor, `name` is the key in the aforementioned `dict`, and `step_number` is incremented by `1` with every call to the handler. If `score_function` is provided, user can store its absolute value using `score_name` in the filename. Each filename can have the following structure: `{filename_prefix}_{name}_{step_number}_{score_name}={abs(score_function_result)}.pth`. For example, `score_name="val_loss"` and `score_function` that returns `-loss` (as objects with highest scores will be retained), then saved models filenames will be `model_resnet_10_val_loss=0.1234.pth`. Examples: >>> import os >>> from ignite.engine import Engine, Events >>> from ignite.handlers import ModelCheckpoint >>> from torch import nn >>> trainer = Engine(lambda batch: None) >>> handler = ModelCheckpoint('/tmp/models', 'myprefix', save_interval=2, n_saved=2, create_dir=True) >>> model = nn.Linear(3, 3) >>> trainer.add_event_handler(Events.EPOCH_COMPLETED, handler, {'mymodel': model}) >>> trainer.run([0], max_epochs=6) >>> os.listdir('/tmp/models') ['myprefix_mymodel_4.pth', 'myprefix_mymodel_6.pth'] """

38.007042

120

0.593756

from datetime import datetime, timedelta import os import tempfile import torch import logging log = logging.getLogger(__name__) __all__ = ["FlexibleModelCheckpoint"] """ Copied from https://github.com/pytorch/ignite/blob/v0.2.1/ignite/handlers/checkpoint.py due to the change in ignite v0.3.0 """ class ModelCheckpoint(object): """ ModelCheckpoint handler can be used to periodically save objects to disk. This handler expects two arguments: - an :class:`~ignite.engine.Engine` object - a `dict` mapping names (`str`) to objects that should be saved to disk. See Notes and Examples for further details. Args: dirname (str): Directory path where objects will be saved. filename_prefix (str): Prefix for the filenames to which objects will be saved. See Notes for more details. save_interval (int, optional): if not None, objects will be saved to disk every `save_interval` calls to the handler. Exactly one of (`save_interval`, `score_function`) arguments must be provided. score_function (callable, optional): if not None, it should be a function taking a single argument, an :class:`~ignite.engine.Engine` object, and return a score (`float`). Objects with highest scores will be retained. Exactly one of (`save_interval`, `score_function`) arguments must be provided. score_name (str, optional): if `score_function` not None, it is possible to store its absolute value using `score_name`. See Notes for more details. n_saved (int, optional): Number of objects that should be kept on disk. Older files will be removed. atomic (bool, optional): If True, objects are serialized to a temporary file, and then moved to final destination, so that files are guaranteed to not be damaged (for example if exception occures during saving). require_empty (bool, optional): If True, will raise exception if there are any files starting with `filename_prefix` in the directory 'dirname'. create_dir (bool, optional): If True, will create directory 'dirname' if it doesnt exist. save_as_state_dict (bool, optional): If True, will save only the `state_dict` of the objects specified, otherwise the whole object will be saved. Note: This handler expects two arguments: an :class:`~ignite.engine.Engine` object and a `dict` mapping names to objects that should be saved. These names are used to specify filenames for saved objects. Each filename has the following structure: `{filename_prefix}_{name}_{step_number}.pth`. Here, `filename_prefix` is the argument passed to the constructor, `name` is the key in the aforementioned `dict`, and `step_number` is incremented by `1` with every call to the handler. If `score_function` is provided, user can store its absolute value using `score_name` in the filename. Each filename can have the following structure: `{filename_prefix}_{name}_{step_number}_{score_name}={abs(score_function_result)}.pth`. For example, `score_name="val_loss"` and `score_function` that returns `-loss` (as objects with highest scores will be retained), then saved models filenames will be `model_resnet_10_val_loss=0.1234.pth`. Examples: >>> import os >>> from ignite.engine import Engine, Events >>> from ignite.handlers import ModelCheckpoint >>> from torch import nn >>> trainer = Engine(lambda batch: None) >>> handler = ModelCheckpoint('/tmp/models', 'myprefix', save_interval=2, n_saved=2, create_dir=True) >>> model = nn.Linear(3, 3) >>> trainer.add_event_handler(Events.EPOCH_COMPLETED, handler, {'mymodel': model}) >>> trainer.run([0], max_epochs=6) >>> os.listdir('/tmp/models') ['myprefix_mymodel_4.pth', 'myprefix_mymodel_6.pth'] """ def __init__( self, dirname, filename_prefix, save_interval=None, score_function=None, score_name=None, n_saved=1, atomic=True, require_empty=True, create_dir=True, save_as_state_dict=True, ): self._dirname = os.path.expanduser(dirname) self._fname_prefix = filename_prefix self._n_saved = n_saved self._save_interval = save_interval self._score_function = score_function self._score_name = score_name self._atomic = atomic self._saved = [] # list of tuples (priority, saved_objects) self._iteration = 0 self._save_as_state_dict = save_as_state_dict if not (save_interval is None) ^ (score_function is None): raise ValueError( "Exactly one of `save_interval`, or `score_function` " "arguments must be provided." ) if score_function is None and score_name is not None: raise ValueError( "If `score_name` is provided, then `score_function` " "should be also provided." ) if create_dir: if not os.path.exists(dirname): os.makedirs(dirname) # Ensure that dirname exists if not os.path.exists(dirname): raise ValueError("Directory path '{}' is not found.".format(dirname)) if require_empty: matched = [ fname for fname in os.listdir(dirname) if fname.startswith(self._fname_prefix) ] if len(matched) > 0: raise ValueError( "Files prefixed with {} are already present " "in the directory {}. If you want to use this " "directory anyway, pass `require_empty=False`." "".format(filename_prefix, dirname) ) def _save(self, obj, path): if not self._atomic: self._internal_save(obj, path) else: tmp = tempfile.NamedTemporaryFile(delete=False, dir=self._dirname) try: self._internal_save(obj, tmp.file) except BaseException: tmp.close() os.remove(tmp.name) raise else: tmp.close() os.rename(tmp.name, path) def _internal_save(self, obj, path): if not self._save_as_state_dict: torch.save(obj, path) else: if not hasattr(obj, "state_dict") or not callable(obj.state_dict): raise ValueError("Object should have `state_dict` method.") torch.save(obj.state_dict(), path) def __call__(self, engine, to_save): if len(to_save) == 0: raise RuntimeError("No objects to checkpoint found.") self._iteration += 1 if self._score_function is not None: priority = self._score_function(engine) else: priority = self._iteration if (self._iteration % self._save_interval) != 0: return if (len(self._saved) < self._n_saved) or (self._saved[0][0] < priority): saved_objs = [] suffix = "" if self._score_name is not None: suffix = "_{}={:.7}".format(self._score_name, abs(priority)) for name, obj in to_save.items(): fname = "{}_{}_{}{}.pth".format( self._fname_prefix, name, self._iteration, suffix ) path = os.path.join(self._dirname, fname) self._save(obj=obj, path=path) saved_objs.append(path) self._saved.append((priority, saved_objs)) self._saved.sort(key=lambda item: item[0]) if len(self._saved) > self._n_saved: _, paths = self._saved.pop(0) for p in paths: os.remove(p) class FlexibleModelCheckpoint(ModelCheckpoint): def __init__( self, dirname, filename_prefix, offset_hours=0, filename_format=None, suffix_format=None, *args, **kwargs ): if "%" in filename_prefix: filename_prefix = get_timestamp( fmt=filename_prefix, offset_hours=offset_hours ) super().__init__(dirname, filename_prefix, *args, **kwargs) if not callable(filename_format): if isinstance(filename_format, str): format_str = filename_format else: format_str = "{}_{}_{:06d}{}.pth" def filename_format(filename_prefix, name, step_number, suffix): return format_str.format(filename_prefix, name, step_number, suffix) self._filename_format = filename_format if not callable(suffix_format): if isinstance(suffix_format, str): suffix_str = suffix_format else: suffix_str = "_{}_{:.7}" def suffix_format(score_name, abs_priority): return suffix_str.format(score_name, abs_priority) self._suffix_format = suffix_format def __call__(self, engine, to_save): if len(to_save) == 0: raise RuntimeError("No objects to checkpoint found.") self._iteration += 1 if self._score_function is not None: priority = self._score_function(engine) else: priority = self._iteration if (self._iteration % self._save_interval) != 0: return if (len(self._saved) < self._n_saved) or (self._saved[0][0] < priority): saved_objs = [] suffix = "" if self._score_name is not None: suffix = self._suffix_format(self._score_name, abs(priority)) for name, obj in to_save.items(): fname = self._filename_format( self._fname_prefix, name, self._iteration, suffix ) path = os.path.join(self._dirname, fname) self._save(obj=obj, path=path) saved_objs.append(path) self._saved.append((priority, saved_objs)) self._saved.sort(key=lambda item: item[0]) if len(self._saved) > self._n_saved: _, paths = self._saved.pop(0) for p in paths: os.remove(p) def get_timestamp(fmt="%Y-%m-%dT%H:%M:%S", offset_hours=0): return (datetime.now() + timedelta(hours=offset_hours)).strftime(fmt)

6,426

26

207

7a844f619e3efa74efdbb5c73abfff44bb6d9063

300

py

Python

Python/Syntax/Exception.py

piovezan/SOpt

a5ec90796b7bdf98f0675457fc4bb99c8695bc40

[ "MIT" ]

148

2017-08-03T01:49:27.000Z

2022-03-26T10:39:30.000Z

Python/Syntax/Exception.py

piovezan/SOpt

a5ec90796b7bdf98f0675457fc4bb99c8695bc40

[ "MIT" ]

3

2017-11-23T19:52:05.000Z

2020-04-01T00:44:40.000Z

Python/Syntax/Exception.py

piovezan/SOpt

a5ec90796b7bdf98f0675457fc4bb99c8695bc40

[ "MIT" ]

59

2017-08-03T01:49:19.000Z

2022-03-31T23:24:38.000Z

lista = [1, 2, 3] try: numero = int(input(f'Digite um número entre 0 e {len(lista)-1}: ')) print(lista[numero]) except ValueError: print('Não foi digitado um número') except IndexError: print('O número digitado está fora da faixa aceita') #https://pt.stackoverflow.com/q/451936/101

27.272727

71

0.683333

lista = [1, 2, 3] try: numero = int(input(f'Digite um número entre 0 e {len(lista)-1}: ')) print(lista[numero]) except ValueError: print('Não foi digitado um número') except IndexError: print('O número digitado está fora da faixa aceita') #https://pt.stackoverflow.com/q/451936/101

0

ab0fe4af8c61239d35e953e82d97e659ca3bf28c

2,164

py

Python

mysite/teproj/middlewares/ip_middleware.py

talhamasood0000/django_ipcheck

f4d68e9c3575f02d6d2a29e7904ba3f162dfb451

[ "Apache-2.0" ]

null

mysite/teproj/middlewares/ip_middleware.py

talhamasood0000/django_ipcheck

f4d68e9c3575f02d6d2a29e7904ba3f162dfb451

[ "Apache-2.0" ]

null

mysite/teproj/middlewares/ip_middleware.py

talhamasood0000/django_ipcheck

f4d68e9c3575f02d6d2a29e7904ba3f162dfb451

[ "Apache-2.0" ]

null

from urllib import response from django.http import HttpResponse,HttpResponseForbidden, HttpResponseRedirect from teproj.models import TestModel from django.urls import reverse from django.conf import settings from django.core.cache import cache from django.contrib.auth.models import Group

36.677966

106

0.589649

from urllib import response from django.http import HttpResponse,HttpResponseForbidden, HttpResponseRedirect from teproj.models import TestModel from django.urls import reverse from django.conf import settings from django.core.cache import cache from django.contrib.auth.models import Group class CustomMiddleware: def __init__(self, get_response): self.get_response = get_response def __call__(self, request): response = self.get_response(request) return response def process_view(self,request, view_func, view_args, view_kwargs): if request.path.startswith(reverse('api')): x_forwarded_for = request.META.get('HTTP_X_FORWARDED_FOR') if x_forwarded_for: ip = x_forwarded_for.split(',')[0] else: ip=request.META.get('REMOTE_ADDR') ip_cache_key = "teproj:ip_rate" + ip this_ip_hits = cache.get(ip_cache_key) if not this_ip_hits: this_ip_hits = 1 cache.set(ip_cache_key, this_ip_hits) else: this_ip_hits += 1 cache.set(ip_cache_key, this_ip_hits) if request.user.is_authenticated: query_set = Group.objects.filter(user = request.user) if query_set[0].name == 'Bronze': max_allowed_hits = settings.IP_BRONZE elif query_set[0].name == 'Silver': max_allowed_hits = settings.IP_SILVER elif query_set[0].name == 'Gold': max_allowed_hits = settings.IP_GOLD value=TestModel(name=request.user,ip_address=ip) value.save() else: max_allowed_hits = settings.IP_UNAUTHORIZED value=TestModel(name=None,ip_address=ip) value.save() print(this_ip_hits, ip, max_allowed_hits) if this_ip_hits > max_allowed_hits: return HttpResponseForbidden("<h4>Wait for 1 min to access again. Limit Reached</h4>")

1,748

2

107

9113a67adedf08f6968ed8efa95fec64627823e4

6,395

py

Python

dynastyscraper.py

vizs/dynastyscraper

7f5c5933aa7e8b467db58cc7afbe51e40e324cd3

[ "BSD-2-Clause" ]

1

2022-01-31T05:09:43.000Z

dynastyscraper.py

vizs/dynastyscraper

7f5c5933aa7e8b467db58cc7afbe51e40e324cd3

[ "BSD-2-Clause" ]

null

dynastyscraper.py

vizs/dynastyscraper

7f5c5933aa7e8b467db58cc7afbe51e40e324cd3

[ "BSD-2-Clause" ]

null

#!/usr/bin/env python3 # # Licensed under BSD 2-Clause License. # # This is a really crude script. This spits out shell-escaped wget # commands to download the images of the chapters. # # Each image is downloaded into "VOLUME_CHAPTER/XXX.png" where VOLUME # and CHAPTER are the volume and chapter names respectively. If DRY # environmental variable is not empty, then this script does not # create the needed directories beforehand. # # Chapter or series URL may be given as arguments to the script. # # To read the chapter in zathura(1), use the following command # # zip CHAPTER.zip CHAPTER_IMAGES/* import json from os import mkdir, getenv from os.path import splitext, basename from os.path import exists as file_exists_p from shlex import quote as shell_quote from sys import argv import re import urllib.request as req import bs4 DYNASTY_IMAGE_RE = re.compile(r"//<!\[CDATA\[") BATOTO_IMAGE_RE_1 = re.compile(r"(?:const|var) images = \[") BATOTO_IMAGE_RE_2 = re.compile(r"(?:const|var) imgHttpLis = \[") JS_CTXT = None UA = { "User-Agent": "Chrome/96.0.4664.110" } MKDIRP = not getenv("DRY") def request(url): """Request URL.""" return req.urlopen(req.Request(url, headers=UA)) def dynasty_get_chapter_list(url): """Get the list of chapters in URL. Returned value is a dictionary { VOLUME: CHAPTERS } where VOLUME is the name of the volume and CHAPTERS is a tuple (NAME, URL) where NAME is the name of the chapter and URL is the link to the chapter. If the manga is not divided by volumes, then VOLUME is an empty string. """ soup = bs4.BeautifulSoup(request(url), "html.parser") ret = {} vol = "" chs = [] chp = soup.find("dl", class_="chapter-list") for i in chp: if not isinstance(i, bs4.element.Tag): continue if i.name == "dt": if chs: ret[vol] = chs vol = i.string chs = [] elif i.name == "dd": chs.append((i.a.string, "https://dynasty-scans.com" + i.a["href"])) if chs: ret[vol] = chs return ret def dynasty_get_images(ch): """Get list of image URLs for the chapter with URL CH.""" soup = bs4.BeautifulSoup(request(ch), "html.parser") if r := re.search(r"var pages = (\[.*\])", soup.find("script", string=DYNASTY_IMAGE_RE).string): return [ "https://dynasty-scans.com" + i["image"] for i in json.loads(r.group(1)) ] return [] def batoto_get_chapter_list(url): """Get the list of chapters in URL. Returned value is a list of (NAME, URL) where NAME is the name of chapter and URL is the link to the chapter. """ chs = [] # User-Agent is need to be set otherwise cloudfare pops up. soup = bs4.BeautifulSoup(request(url), "html.parser") for i in soup.find_all("a", class_="visited chapt"): # The name of the chapter is surrounded by newlines for some # reason. chs.append((i.text.strip(), "https://bato.to" + i["href"])) chs.reverse() return chs def batoto_get_images(ch): """Get list of image URLs for the chapter CH. I came to know of duktape thanks to the Tachiyomi bato.to extension. """ def js_eval(string): """Evalulate JavaScript code in the string STRING.""" import pyduktape global JS_CTXT if not JS_CTXT: JS_CTXT = pyduktape.DuktapeContext() if not file_exists_p("./crypto.js"): # The same URL tachiyomi uses. cryptojs = request("https://cdnjs.cloudflare.com/ajax/libs/crypto-js/4.0.0/crypto-js.min.js") with open("./crypto.js", "w") as f: f.write(cryptojs.read().decode("utf-8")) JS_CTXT.eval_js_file("./crypto.js") return JS_CTXT.eval_js(string) soup = bs4.BeautifulSoup(request(ch), "html.parser") if js := soup.find("script", text=BATOTO_IMAGE_RE_1): # Most of this magic can be figured out by reading the JavaScript # sources in a chapter page. Alternatively, refer to # https://github.com/tachiyomiorg/tachiyomi-extensions/blob/master/src/all/batoto/src/eu/kanade/tachiyomi/extension/all/batoto/BatoTo.kt js = js.string server = re.search(r"(?:const|var) server = ([^;]+);", js).group(1) batojs = re.search(r"(?:const|var) batojs = ([^;]+);", js).group(1) base = js_eval(f"CryptoJS.AES.decrypt({server} ,{batojs}).toString(CryptoJS.enc.Utf8);").strip("\"") return [ base + i for i in json.loads(re.search(r"(?:const|var) images = (\[.*\]);", js).group(1)) ] elif js := soup.find("script", text=BATOTO_IMAGE_RE_2): # Again, thanks to tachiyomi for showing the light. It is # also easy enough to figure out if you read the JS files. js = js.string img = re.search(r"(?:const|var) imgHttpLis = ([^;]+);", js).group(1) img = json.loads(img) batoword = re.search(r"(?:const|var) batoWord = ([^;]+);", js).group(1) batopass = re.search(r"(?:const|var) batoPass = ([^;]+);", js).group(1) passwd = json.loads(js_eval(f"CryptoJS.AES.decrypt({batoword}, {batopass}).toString(CryptoJS.enc.Utf8);")) if len(passwd) != len(img): return [ ] return [ i + "?" + passwd[n] for n, i in enumerate(img) ] return [] if __name__ == "__main__": for i in argv[1:]: do(i)

37.397661

144

0.606099

#!/usr/bin/env python3 # # Licensed under BSD 2-Clause License. # # This is a really crude script. This spits out shell-escaped wget # commands to download the images of the chapters. # # Each image is downloaded into "VOLUME_CHAPTER/XXX.png" where VOLUME # and CHAPTER are the volume and chapter names respectively. If DRY # environmental variable is not empty, then this script does not # create the needed directories beforehand. # # Chapter or series URL may be given as arguments to the script. # # To read the chapter in zathura(1), use the following command # # zip CHAPTER.zip CHAPTER_IMAGES/* import json from os import mkdir, getenv from os.path import splitext, basename from os.path import exists as file_exists_p from shlex import quote as shell_quote from sys import argv import re import urllib.request as req import bs4 DYNASTY_IMAGE_RE = re.compile(r"//<!\[CDATA\[") BATOTO_IMAGE_RE_1 = re.compile(r"(?:const|var) images = \[") BATOTO_IMAGE_RE_2 = re.compile(r"(?:const|var) imgHttpLis = \[") JS_CTXT = None UA = { "User-Agent": "Chrome/96.0.4664.110" } MKDIRP = not getenv("DRY") def request(url): """Request URL.""" return req.urlopen(req.Request(url, headers=UA)) def dynasty_get_chapter_list(url): """Get the list of chapters in URL. Returned value is a dictionary { VOLUME: CHAPTERS } where VOLUME is the name of the volume and CHAPTERS is a tuple (NAME, URL) where NAME is the name of the chapter and URL is the link to the chapter. If the manga is not divided by volumes, then VOLUME is an empty string. """ soup = bs4.BeautifulSoup(request(url), "html.parser") ret = {} vol = "" chs = [] chp = soup.find("dl", class_="chapter-list") for i in chp: if not isinstance(i, bs4.element.Tag): continue if i.name == "dt": if chs: ret[vol] = chs vol = i.string chs = [] elif i.name == "dd": chs.append((i.a.string, "https://dynasty-scans.com" + i.a["href"])) if chs: ret[vol] = chs return ret def dynasty_get_images(ch): """Get list of image URLs for the chapter with URL CH.""" soup = bs4.BeautifulSoup(request(ch), "html.parser") if r := re.search(r"var pages = (\[.*\])", soup.find("script", string=DYNASTY_IMAGE_RE).string): return [ "https://dynasty-scans.com" + i["image"] for i in json.loads(r.group(1)) ] return [] def batoto_get_chapter_list(url): """Get the list of chapters in URL. Returned value is a list of (NAME, URL) where NAME is the name of chapter and URL is the link to the chapter. """ chs = [] # User-Agent is need to be set otherwise cloudfare pops up. soup = bs4.BeautifulSoup(request(url), "html.parser") for i in soup.find_all("a", class_="visited chapt"): # The name of the chapter is surrounded by newlines for some # reason. chs.append((i.text.strip(), "https://bato.to" + i["href"])) chs.reverse() return chs def batoto_get_images(ch): """Get list of image URLs for the chapter CH. I came to know of duktape thanks to the Tachiyomi bato.to extension. """ def js_eval(string): """Evalulate JavaScript code in the string STRING.""" import pyduktape global JS_CTXT if not JS_CTXT: JS_CTXT = pyduktape.DuktapeContext() if not file_exists_p("./crypto.js"): # The same URL tachiyomi uses. cryptojs = request("https://cdnjs.cloudflare.com/ajax/libs/crypto-js/4.0.0/crypto-js.min.js") with open("./crypto.js", "w") as f: f.write(cryptojs.read().decode("utf-8")) JS_CTXT.eval_js_file("./crypto.js") return JS_CTXT.eval_js(string) soup = bs4.BeautifulSoup(request(ch), "html.parser") if js := soup.find("script", text=BATOTO_IMAGE_RE_1): # Most of this magic can be figured out by reading the JavaScript # sources in a chapter page. Alternatively, refer to # https://github.com/tachiyomiorg/tachiyomi-extensions/blob/master/src/all/batoto/src/eu/kanade/tachiyomi/extension/all/batoto/BatoTo.kt js = js.string server = re.search(r"(?:const|var) server = ([^;]+);", js).group(1) batojs = re.search(r"(?:const|var) batojs = ([^;]+);", js).group(1) base = js_eval(f"CryptoJS.AES.decrypt({server} ,{batojs}).toString(CryptoJS.enc.Utf8);").strip("\"") return [ base + i for i in json.loads(re.search(r"(?:const|var) images = (\[.*\]);", js).group(1)) ] elif js := soup.find("script", text=BATOTO_IMAGE_RE_2): # Again, thanks to tachiyomi for showing the light. It is # also easy enough to figure out if you read the JS files. js = js.string img = re.search(r"(?:const|var) imgHttpLis = ([^;]+);", js).group(1) img = json.loads(img) batoword = re.search(r"(?:const|var) batoWord = ([^;]+);", js).group(1) batopass = re.search(r"(?:const|var) batoPass = ([^;]+);", js).group(1) passwd = json.loads(js_eval(f"CryptoJS.AES.decrypt({batoword}, {batopass}).toString(CryptoJS.enc.Utf8);")) if len(passwd) != len(img): return [ ] return [ i + "?" + passwd[n] for n, i in enumerate(img) ] return [] def do1(images, dirname): if MKDIRP: mkdir(dirname) for n, i in enumerate(images): _, ext = splitext(i) if "?" in ext: ext, _, _ = ext.partition("?") print("wget {} -O {}".format(shell_quote(i), shell_quote(f"{dirname}/{n+1:03}{ext}"))) def do(url): if "dynasty-scans.com" in url: if "chapters" in url: do1(dynasty_get_images(url), basename(url)) else: chp = dynasty_get_chapter_list(url) for vol, ch in chp.items(): for prefix, url in ch: do1(dynasty_get_images(url), (vol+"_" if vol else "")+prefix) elif "bato.to" in url: if "chapter" in url: do1(batoto_get_images(url), basename(url)) else: chp = batoto_get_chapter_list(url) for name, ch in chp: do1(batoto_get_images(ch), name.replace("\n", "", True)) if __name__ == "__main__": for i in argv[1:]: do(i)

872

0

46

35344fdb50ad0e73db9563e4847d6313d8dfbe83

290

py

Python

catalog/bindings/gmd/abstract_operation.py

NIVANorge/s-enda-playground

56ae0a8978f0ba8a5546330786c882c31e17757a

[ "Apache-2.0" ]

null

catalog/bindings/gmd/abstract_operation.py

NIVANorge/s-enda-playground

56ae0a8978f0ba8a5546330786c882c31e17757a

[ "Apache-2.0" ]

null

catalog/bindings/gmd/abstract_operation.py

NIVANorge/s-enda-playground

56ae0a8978f0ba8a5546330786c882c31e17757a

[ "Apache-2.0" ]

null

from dataclasses import dataclass from bindings.gmd.abstract_crstype import AbstractCoordinateOperationType __NAMESPACE__ = "http://www.opengis.net/gml" @dataclass

26.363636

73

0.796552

from dataclasses import dataclass from bindings.gmd.abstract_crstype import AbstractCoordinateOperationType __NAMESPACE__ = "http://www.opengis.net/gml" @dataclass class AbstractOperation(AbstractCoordinateOperationType): class Meta: namespace = "http://www.opengis.net/gml"

0

101

22

1cc6c164dd77cefd83f6adae1de30b1677c4f0ec

26

py

Python

bassin/__init__.py

lionel42/bassin

45258ac11ce6ec62075c88f6445eddad3d945585

[ "MIT" ]

null

bassin/__init__.py

lionel42/bassin

45258ac11ce6ec62075c88f6445eddad3d945585

[ "MIT" ]

null

bassin/__init__.py

lionel42/bassin

45258ac11ce6ec62075c88f6445eddad3d945585

[ "MIT" ]

null

from .Bassin import Bassin

26

0.846154

from .Bassin import Bassin

0

5a2267304bf02066ad57cb523a22e659defb90d7

117

py

Python

sqlalchemy_solr/solrdbapi/api_globals.py

anjackson/sqlalchemy-solr

56d46f90fdc522ad9113d8efde592d6a9868bd10

[ "MIT" ]

null

sqlalchemy_solr/solrdbapi/api_globals.py

anjackson/sqlalchemy-solr

56d46f90fdc522ad9113d8efde592d6a9868bd10

[ "MIT" ]

null

sqlalchemy_solr/solrdbapi/api_globals.py

anjackson/sqlalchemy-solr

56d46f90fdc522ad9113d8efde592d6a9868bd10

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Global variables _HEADER = {"Content-Type": "application/json"} _PAYLOAD = {"stmt": None}

19.5

46

0.632479

# -*- coding: utf-8 -*- # Global variables _HEADER = {"Content-Type": "application/json"} _PAYLOAD = {"stmt": None}

0

fa5bda6b980c9d6262d78c458162ba7b19e4ef12

3,762

py

Python

zero_ilumi_agenda/zero_ilumi_agenda_core/views.py

ZeroILumi/Zero_ILumi_Agenda_Django

1a34c12e92e233b0e3d96f34b78d235f88fc7124

[ "MIT" ]

null

zero_ilumi_agenda/zero_ilumi_agenda_core/views.py

ZeroILumi/Zero_ILumi_Agenda_Django

1a34c12e92e233b0e3d96f34b78d235f88fc7124

[ "MIT" ]

null

zero_ilumi_agenda/zero_ilumi_agenda_core/views.py

ZeroILumi/Zero_ILumi_Agenda_Django

1a34c12e92e233b0e3d96f34b78d235f88fc7124

[ "MIT" ]

null

from django.contrib.auth.models import User from django.shortcuts import render, redirect from zero_ilumi_agenda_core.models import Evento_Agendado from django.contrib.auth.decorators import login_required from django.contrib.auth import authenticate, login, logout from django.contrib import messages from datetime import datetime, timedelta from django.http.response import Http404, JsonResponse # Create your views here. # def index(request): # return redirect('/agenda/') @login_required(login_url='/login/') @login_required(login_url='/login/') @login_required(login_url='/login/') @login_required(login_url='/login/') @login_required(login_url='/login/')

37.247525

105

0.661085

from django.contrib.auth.models import User from django.shortcuts import render, redirect from zero_ilumi_agenda_core.models import Evento_Agendado from django.contrib.auth.decorators import login_required from django.contrib.auth import authenticate, login, logout from django.contrib import messages from datetime import datetime, timedelta from django.http.response import Http404, JsonResponse # Create your views here. # def index(request): # return redirect('/agenda/') def login_user(request): return render(request, 'login.html') def submit_login(request): if request.POST: username = request.POST.get('nome_de_usuario') password = request.POST.get('senha_do_usuario') usuario = authenticate(username=username, password=password) if usuario is not None: login(request, usuario) else: messages.error(request, "Usuário ou Senha Inválidos") return redirect('/') @login_required(login_url='/login/') def listar_eventos_agendados(request): usuario = request.user data_atual = datetime.now() - timedelta(hours=1) eventos_do_usuario = Evento_Agendado.objects.filter(usuario=usuario) dados = {'eventos': eventos_do_usuario} return render(request, 'zero_ilumi_agenda.html', dados) @login_required(login_url='/login/') def logout_user(request): logout(request) return redirect('/') @login_required(login_url='/login/') def evento(request): id_evento = request.GET.get('id') dados = {} if id_evento: dados['evento'] = Evento_Agendado.objects.get(id=id_evento) return render(request, 'evento.html', dados) @login_required(login_url='/login/') def submit_evento(request): if request.POST: usuario = request.user titulo = request.POST.get('titulo_agendamento_novo') descricao = request.POST.get('input_descricao_agendamento_novo') data_do_evento = request.POST.get('data_do_evento_agendamento_novo') local_do_evento = request.POST.get('local_do_evento_agendamento_novo') id_evento = request.POST.get('id_evento') if id_evento: evento = Evento_Agendado.objects.get(id=id_evento) if usuario == evento.usuario: evento.titulo_do_evento_agendado = titulo evento.data_do_evento_agendado = data_do_evento evento.decricao_do_evento_agendado = descricao evento.save() # Evento_Agendado.objects.filter(id=id_evento).update(titulo_do_evento_agendado=titulo, # data_do_evento_agendado=data_do_evento, # decricao_do_evento_agendado=descricao) else: Evento_Agendado.objects.create(usuario=usuario, titulo_do_evento_agendado=titulo, decricao_do_evento_agendado=descricao, data_do_evento_agendado=data_do_evento, local_do_evento_agenda=local_do_evento) return redirect('/') @login_required(login_url='/login/') def delete_evento(request, id_evento): usuario = request.user try: evento = Evento_Agendado.objects.get(id=id_evento) except Exception: raise Http404() if usuario == evento.usuario: evento.delete() else: raise Http404() return redirect('/') def json_lista_evento(request, id_usuario): usuario = User.objects.get(id=id_usuario) evento = Evento_Agendado.objects.filter(usuario=usuario).values('id', 'titulo_do_evento_agendado') return JsonResponse(list(evento), safe=False)

2,906

0

179

7f5e0625c5594db764254be083cba073e7fbc7a6

4,616

py

Python

AutomatedTesting/Gem/PythonTests/largeworlds/landscape_canvas/test_GradientModifierNodes.py

aaarsene/o3de

37e3b0226958974defd14dd6d808e8557dcd7345

[ "Apache-2.0", "MIT" ]

1

2021-09-13T00:01:12.000Z

AutomatedTesting/Gem/PythonTests/largeworlds/landscape_canvas/test_GradientModifierNodes.py

aaarsene/o3de

37e3b0226958974defd14dd6d808e8557dcd7345

[ "Apache-2.0", "MIT" ]

null

AutomatedTesting/Gem/PythonTests/largeworlds/landscape_canvas/test_GradientModifierNodes.py

aaarsene/o3de

37e3b0226958974defd14dd6d808e8557dcd7345

[ "Apache-2.0", "MIT" ]

1

2021-07-20T11:07:25.000Z

""" Copyright (c) Contributors to the Open 3D Engine Project. For complete copyright and license terms please see the LICENSE at the root of this distribution. SPDX-License-Identifier: Apache-2.0 OR MIT """ """ C13767841 - All Gradient Modifier nodes can be added to a graph C18055051 - All Gradient Modifier nodes can be removed from a graph """ import os import pytest # Bail on the test if ly_test_tools doesn't exist. pytest.importorskip('ly_test_tools') import ly_test_tools.environment.file_system as file_system import editor_python_test_tools.hydra_test_utils as hydra test_directory = os.path.join(os.path.dirname(__file__), 'EditorScripts') @pytest.mark.parametrize('project', ['AutomatedTesting']) @pytest.mark.parametrize('level', ['tmp_level']) @pytest.mark.usefixtures("automatic_process_killer") @pytest.mark.parametrize("launcher_platform", ['windows_editor'])

50.173913

155

0.684575

""" Copyright (c) Contributors to the Open 3D Engine Project. For complete copyright and license terms please see the LICENSE at the root of this distribution. SPDX-License-Identifier: Apache-2.0 OR MIT """ """ C13767841 - All Gradient Modifier nodes can be added to a graph C18055051 - All Gradient Modifier nodes can be removed from a graph """ import os import pytest # Bail on the test if ly_test_tools doesn't exist. pytest.importorskip('ly_test_tools') import ly_test_tools.environment.file_system as file_system import editor_python_test_tools.hydra_test_utils as hydra test_directory = os.path.join(os.path.dirname(__file__), 'EditorScripts') @pytest.mark.parametrize('project', ['AutomatedTesting']) @pytest.mark.parametrize('level', ['tmp_level']) @pytest.mark.usefixtures("automatic_process_killer") @pytest.mark.parametrize("launcher_platform", ['windows_editor']) class TestGradientModifierNodes(object): @pytest.fixture(autouse=True) def setup_teardown(self, request, workspace, project, level): def teardown(): file_system.delete([os.path.join(workspace.paths.engine_root(), project, "Levels", level)], True, True) request.addfinalizer(teardown) file_system.delete([os.path.join(workspace.paths.engine_root(), project, "Levels", level)], True, True) @pytest.mark.test_case_id('C13767841') @pytest.mark.SUITE_periodic def test_LandscapeCanvas_GradientModifierNodes_EntityCreatedOnNodeAdd(self, request, editor, level, launcher_platform): """ Verifies all Gradient Modifier nodes can be successfully added to a Landscape Canvas graph, and the proper entity creation occurs. """ cfg_args = [level] expected_lines = [ "Landscape Canvas pane is open", "New graph created", "Graph registered with Landscape Canvas", "DitherGradientModifierNode created new Entity with Dither Gradient Modifier Component", "GradientMixerNode created new Entity with Gradient Mixer Component", "InvertGradientModifierNode created new Entity with Invert Gradient Modifier Component", "LevelsGradientModifierNode created new Entity with Levels Gradient Modifier Component", "PosterizeGradientModifierNode created new Entity with Posterize Gradient Modifier Component", "SmoothStepGradientModifierNode created new Entity with Smooth-Step Gradient Modifier Component", "ThresholdGradientModifierNode created new Entity with Threshold Gradient Modifier Component", "GradientModifierNodeEntityCreate: result=SUCCESS" ] hydra.launch_and_validate_results(request, test_directory, editor, 'GradientModifierNodes_EntityCreatedOnNodeAdd.py', expected_lines, cfg_args=cfg_args) @pytest.mark.test_case_id('C18055051') @pytest.mark.SUITE_periodic def test_LandscapeCanvas_GradientModifierNodes_EntityRemovedOnNodeDelete(self, request, editor, level, launcher_platform): """ Verifies all Gradient Modifier nodes can be successfully removed from a Landscape Canvas graph, and the proper entity cleanup occurs. """ cfg_args = [level] expected_lines = [ "Landscape Canvas pane is open", "New graph created", "Graph registered with Landscape Canvas", "DitherGradientModifierNode corresponding Entity was deleted when node is removed", "GradientMixerNode corresponding Entity was deleted when node is removed", "InvertGradientModifierNode corresponding Entity was deleted when node is removed", "LevelsGradientModifierNode corresponding Entity was deleted when node is removed", "PosterizeGradientModifierNode corresponding Entity was deleted when node is removed", "SmoothStepGradientModifierNode corresponding Entity was deleted when node is removed", "ThresholdGradientModifierNode corresponding Entity was deleted when node is removed", "GradientModifierNodeEntityDelete: result=SUCCESS" ] hydra.launch_and_validate_results(request, test_directory, editor, 'GradientModifierNodes_EntityRemovedOnNodeDelete.py', expected_lines, cfg_args=cfg_args)

332

3,378

22

5b926d450579990c8f09b93cbc5ae4c06128ef8d

802

py

Python

models/stylegan2/op/setup.py

Norod/encoder4editing

362ef1722f5082fda5f53aaa2c9562fbaedd5fd6

[ "MIT" ]

53

2021-01-22T08:52:02.000Z

2022-03-30T13:58:57.000Z

GAN2Shape/stylegan2/stylegan2-pytorch/op/setup.py

alessioGalatolo/GAN-2D-to-3D

088bd2c438c2419192733ddf6c322dff8db8e513

[ "MIT" ]

null

GAN2Shape/stylegan2/stylegan2-pytorch/op/setup.py

alessioGalatolo/GAN-2D-to-3D

088bd2c438c2419192733ddf6c322dff8db8e513

[ "MIT" ]

12

2021-02-03T09:04:02.000Z

2022-02-10T12:34:40.000Z

from setuptools import setup from torch.utils.cpp_extension import CUDAExtension, BuildExtension from pathlib import Path # Usage: # python setup.py install (or python setup.py bdist_wheel) # NB: Windows: run from VS2017 x64 Native Tool Command Prompt rootdir = (Path(__file__).parent / '..' / 'op').resolve() setup( name='upfirdn2d', ext_modules=[ CUDAExtension('upfirdn2d_op', [str(rootdir / 'upfirdn2d.cpp'), str(rootdir / 'upfirdn2d_kernel.cu')], ) ], cmdclass={ 'build_ext': BuildExtension } ) setup( name='fused', ext_modules=[ CUDAExtension('fused', [str(rootdir / 'fused_bias_act.cpp'), str(rootdir / 'fused_bias_act_kernel.cu')], ) ], cmdclass={ 'build_ext': BuildExtension } )

24.30303

93

0.633416

from setuptools import setup from torch.utils.cpp_extension import CUDAExtension, BuildExtension from pathlib import Path # Usage: # python setup.py install (or python setup.py bdist_wheel) # NB: Windows: run from VS2017 x64 Native Tool Command Prompt rootdir = (Path(__file__).parent / '..' / 'op').resolve() setup( name='upfirdn2d', ext_modules=[ CUDAExtension('upfirdn2d_op', [str(rootdir / 'upfirdn2d.cpp'), str(rootdir / 'upfirdn2d_kernel.cu')], ) ], cmdclass={ 'build_ext': BuildExtension } ) setup( name='fused', ext_modules=[ CUDAExtension('fused', [str(rootdir / 'fused_bias_act.cpp'), str(rootdir / 'fused_bias_act_kernel.cu')], ) ], cmdclass={ 'build_ext': BuildExtension } )

0

87c61571e70cdd66700ebb85bc4a82a19bc6aaf4

2,405

py

Python

LoadGames.py

SeppPenner/LoadGamesFromPcGamesDownloadCom

7dab270a1c1ff5db012bc26aacdafbd4cba1de74

[ "MIT" ]

6

2018-05-13T15:54:20.000Z

2021-12-12T22:30:38.000Z

LoadGames.py

SeppPenner/LoadGamesFromPcGamesDownloadCom

7dab270a1c1ff5db012bc26aacdafbd4cba1de74

[ "MIT" ]

null

LoadGames.py

SeppPenner/LoadGamesFromPcGamesDownloadCom

7dab270a1c1ff5db012bc26aacdafbd4cba1de74

[ "MIT" ]

3

2018-10-08T17:16:40.000Z

2021-12-12T22:30:41.000Z

import requests from bs4 import BeautifulSoup import sys import datetime mainPageUrl = 'https://pcgames-download.com/' mainFilePath = './loading/mainPage.html' pagePath = './loading/' def loadGameData(): "Loads computer games data" print ('Loading number of pages') response = requests.get(mainPageUrl) with open(mainFilePath, 'wb') as f: f.write(response.content) soup = BeautifulSoup(open(mainFilePath, encoding="utf8"), 'html.parser') for lastPage in soup.find_all(class_='last'): lastPageText = lastPage.get('href').strip() lastPageNumber = getLastPageNumber(lastPageText) print ('Last available page: ' + lastPageText) continue data = [] for currentPageNumber in range(1, lastPageNumber + 1): print('Loading page ' + str(currentPageNumber)) titleTexts, titleLinks = checkLoadPageData(currentPageNumber) for index in range(len(titleTexts)): data.append(str(titleTexts[index]) + '; ' + str(titleLinks[index]) + '\n') fileName = getCurrentDateTimeFormatted() + '.csv' print('Writing data to csv file: ' + fileName) with open('./savedData/' + fileName, 'w') as f: f.write(''.join(data)) print ("Done") def getLastPageNumber(lastPage): "Gets the last page number of the computer game website" #https://pcgames-download.com/page/271/ --> 271 lastPage = lastPage.replace(mainPageUrl + 'page/', "").replace("/", "") return int(lastPage) def checkLoadPageData(currentPage): "Loads the page data for the given page number" if currentPage == 1: print (mainPageUrl) return loadPageData(mainPageUrl, currentPage) else: pageUrl = mainPageUrl + 'page/' + str(currentPage) print (pageUrl) return loadPageData(pageUrl, currentPage) def loadPageData(pageUrl, currentPage): "Loads the page data for the given page url" response = requests.get(pageUrl) pageFile = pagePath + str(currentPage) + '.html' with open(pageFile, 'wb') as f: f.write(response.content) soup = BeautifulSoup(open(pageFile, encoding="utf8"), 'html.parser') titleTexts = [] titleLinks = [] for posts in soup.find_all(class_='post-title'): for post in posts: titleTexts.append(post.get('title')) titleLinks.append(post.get('href')) return (titleTexts, titleLinks) def getCurrentDateTimeFormatted(): "Returns a string for the json output file with the current date and time" return datetime.datetime.now().isoformat().replace(":", "-").replace(".", "-") loadGameData()

34.855072

79

0.722661

import requests from bs4 import BeautifulSoup import sys import datetime mainPageUrl = 'https://pcgames-download.com/' mainFilePath = './loading/mainPage.html' pagePath = './loading/' def loadGameData(): "Loads computer games data" print ('Loading number of pages') response = requests.get(mainPageUrl) with open(mainFilePath, 'wb') as f: f.write(response.content) soup = BeautifulSoup(open(mainFilePath, encoding="utf8"), 'html.parser') for lastPage in soup.find_all(class_='last'): lastPageText = lastPage.get('href').strip() lastPageNumber = getLastPageNumber(lastPageText) print ('Last available page: ' + lastPageText) continue data = [] for currentPageNumber in range(1, lastPageNumber + 1): print('Loading page ' + str(currentPageNumber)) titleTexts, titleLinks = checkLoadPageData(currentPageNumber) for index in range(len(titleTexts)): data.append(str(titleTexts[index]) + '; ' + str(titleLinks[index]) + '\n') fileName = getCurrentDateTimeFormatted() + '.csv' print('Writing data to csv file: ' + fileName) with open('./savedData/' + fileName, 'w') as f: f.write(''.join(data)) print ("Done") def getLastPageNumber(lastPage): "Gets the last page number of the computer game website" #https://pcgames-download.com/page/271/ --> 271 lastPage = lastPage.replace(mainPageUrl + 'page/', "").replace("/", "") return int(lastPage) def checkLoadPageData(currentPage): "Loads the page data for the given page number" if currentPage == 1: print (mainPageUrl) return loadPageData(mainPageUrl, currentPage) else: pageUrl = mainPageUrl + 'page/' + str(currentPage) print (pageUrl) return loadPageData(pageUrl, currentPage) def loadPageData(pageUrl, currentPage): "Loads the page data for the given page url" response = requests.get(pageUrl) pageFile = pagePath + str(currentPage) + '.html' with open(pageFile, 'wb') as f: f.write(response.content) soup = BeautifulSoup(open(pageFile, encoding="utf8"), 'html.parser') titleTexts = [] titleLinks = [] for posts in soup.find_all(class_='post-title'): for post in posts: titleTexts.append(post.get('title')) titleLinks.append(post.get('href')) return (titleTexts, titleLinks) def getCurrentDateTimeFormatted(): "Returns a string for the json output file with the current date and time" return datetime.datetime.now().isoformat().replace(":", "-").replace(".", "-") loadGameData()

0

1c20d53be87d3d3e6f7a2b8bd15d6a2ff185adbe

2,024

py

Python

test/student_t_repeated_measures.py

kozzion/tensealstat

93314a8721ec6b1a2bea466aaeadb06cbf5a4f63

[ "Apache-2.0" ]

6

2020-12-17T16:05:24.000Z

2021-12-28T13:26:31.000Z

test/student_t_repeated_measures.py

kozzion/tensealstat

93314a8721ec6b1a2bea466aaeadb06cbf5a4f63

[ "Apache-2.0" ]

null

test/student_t_repeated_measures.py

kozzion/tensealstat

93314a8721ec6b1a2bea466aaeadb06cbf5a4f63

[ "Apache-2.0" ]

null

import sys import os from scipy import stats import tenseal as ts import numpy as np from scipy.stats import t sys.path.append(os.path.abspath('../../tensealstat')) from tensealstat.tools_context import ToolsContext as tc from tensealstat.algebra.algebra_numpy import AlgebraNumpy from tensealstat.algebra.algebra_tenseal import AlgebraTenseal from tensealstat.statistic.student_t_repeated_measures import StudentTRepeatedMeasures statistic_generator = StudentTRepeatedMeasures() # # This test follows Larsen Marc 4Th edition P790 # # 1 done by the key holder context = tc.get_context_default() algebra_tenseal = AlgebraTenseal(context) algebra_numpy = AlgebraNumpy() # 2 done by the data holders sample_0 = np.array([14.6, 17.3, 10.9, 12.8, 16.6, 12.2, 11.2, 15.4, 14.8, 16.2]) sample_1 = np.array([13.8, 15.4, 11.3, 11.6, 16.4, 12.6, 11.8, 15.0, 14.4, 15.0]) list_sample = [sample_0, sample_1] list_sample_encrypted = [algebra_tenseal.encrypt_vector(sample) for sample in list_sample] # 3 done by the agregator statistic_encrypted = statistic_generator.encrypt_statistic(algebra_tenseal, list_sample_encrypted) # 4 done by the key holder t_statistic, degrees_of_freedom = statistic_generator.decrypt_statistic(algebra_tenseal, statistic_encrypted) p_value = t.cdf(t_statistic, degrees_of_freedom) # p value should be between about 0.94 and 0.95 print('via tensealstat') print('t_statistic: ' + str(t_statistic)) print('p_value: ' + str(p_value)) # Test version statistic_encrypted = statistic_generator.encrypt_statistic(algebra_numpy, list_sample) t_statistic, degrees_of_freedom = statistic_generator.decrypt_statistic(algebra_numpy, statistic_encrypted) p_value = t.cdf(t_statistic, degrees_of_freedom) print('') print('via tensealstattest') print('t_statistic: ' + str(t_statistic)) print('p_value: ' + str(p_value)) # Scipy version t_statistic, p_value = stats.ttest_rel(sample_0 ,sample_1) print('') print('via scipy') print('t_statistic: ' + str(t_statistic)) print('p_value: ' + str(1 - (p_value / 2)))

34.896552

109

0.784091

import sys import os from scipy import stats import tenseal as ts import numpy as np from scipy.stats import t sys.path.append(os.path.abspath('../../tensealstat')) from tensealstat.tools_context import ToolsContext as tc from tensealstat.algebra.algebra_numpy import AlgebraNumpy from tensealstat.algebra.algebra_tenseal import AlgebraTenseal from tensealstat.statistic.student_t_repeated_measures import StudentTRepeatedMeasures statistic_generator = StudentTRepeatedMeasures() # # This test follows Larsen Marc 4Th edition P790 # # 1 done by the key holder context = tc.get_context_default() algebra_tenseal = AlgebraTenseal(context) algebra_numpy = AlgebraNumpy() # 2 done by the data holders sample_0 = np.array([14.6, 17.3, 10.9, 12.8, 16.6, 12.2, 11.2, 15.4, 14.8, 16.2]) sample_1 = np.array([13.8, 15.4, 11.3, 11.6, 16.4, 12.6, 11.8, 15.0, 14.4, 15.0]) list_sample = [sample_0, sample_1] list_sample_encrypted = [algebra_tenseal.encrypt_vector(sample) for sample in list_sample] # 3 done by the agregator statistic_encrypted = statistic_generator.encrypt_statistic(algebra_tenseal, list_sample_encrypted) # 4 done by the key holder t_statistic, degrees_of_freedom = statistic_generator.decrypt_statistic(algebra_tenseal, statistic_encrypted) p_value = t.cdf(t_statistic, degrees_of_freedom) # p value should be between about 0.94 and 0.95 print('via tensealstat') print('t_statistic: ' + str(t_statistic)) print('p_value: ' + str(p_value)) # Test version statistic_encrypted = statistic_generator.encrypt_statistic(algebra_numpy, list_sample) t_statistic, degrees_of_freedom = statistic_generator.decrypt_statistic(algebra_numpy, statistic_encrypted) p_value = t.cdf(t_statistic, degrees_of_freedom) print('') print('via tensealstattest') print('t_statistic: ' + str(t_statistic)) print('p_value: ' + str(p_value)) # Scipy version t_statistic, p_value = stats.ttest_rel(sample_0 ,sample_1) print('') print('via scipy') print('t_statistic: ' + str(t_statistic)) print('p_value: ' + str(1 - (p_value / 2)))

0

7f2d97874d60745759c0eb8586e473b807a5fc32

1,883

py

Python

article/models.py

anush7/django-article-project

2de595309acdcf509491596483521c1c2fa31b46

[ "MIT" ]

null

article/models.py

anush7/django-article-project

2de595309acdcf509491596483521c1c2fa31b46

[ "MIT" ]

null

article/models.py

anush7/django-article-project

2de595309acdcf509491596483521c1c2fa31b46

[ "MIT" ]

null

import os from django.db import models from django.contrib.auth.models import User from easy_thumbnails.fields import ThumbnailerImageField import uuid

41.844444

95

0.765799

import os from django.db import models from django.contrib.auth.models import User from easy_thumbnails.fields import ThumbnailerImageField class Tag(models.Model): tag = models.CharField(max_length=150) def __unicode__(self): return self.tag class ArticleCategory(models.Model): name = models.CharField(max_length=150,unique=True) slug = models.CharField(max_length=200,null=True) created_on = models.DateTimeField(null=True, blank=True) def __unicode__(self): return self.name import uuid def get_photosgallery_path(instance, filename): ext = filename.split('.')[-1] filename = "%s.%s" % (uuid.uuid4(), ext) return os.path.join('photos/gallery', filename) class Article(models.Model): photo = ThumbnailerImageField(upload_to=get_photosgallery_path,null=True,blank=True) photo_url = models.CharField(max_length=255,null=True,blank=True) caption = models.CharField(max_length=200, default="",null=True,blank=True) title = models.CharField(max_length=200, default="") slug = models.CharField(max_length=250,null=True,blank=True) content = models.TextField(null=True,blank=True) category = models.ForeignKey("ArticleCategory",null=True,blank=True, related_name="articles") tags = models.ManyToManyField("Tag",blank=True) featured = models.BooleanField(default=False,blank=True) viewcount = models.PositiveIntegerField(default=0) published_on = models.DateTimeField(null=True,blank=True) created_on = models.DateTimeField(auto_now_add = True) modified_on = models.DateTimeField(auto_now = True) created_by = models.ForeignKey(User,related_name='%(class)s_createdby',null=True,blank=True) modified_by = models.ForeignKey(User,related_name='%(class)s_modifiedby',null=True,blank=True) is_active = models.BooleanField(default=True) status = models.CharField(max_length=1,default='D')# D -> Draft, P -> Published

199

1,436

91

d7e636d3d64063bcb97ad001385d2875f365c42a

1,419

py

Python

effective_python/metaclass_property/confirm_subclass.py

ftconan/python3

eb63ba33960072f792ecce6db809866b38c402f8

[ "MIT" ]

1

2018-12-19T22:07:56.000Z

effective_python/metaclass_property/confirm_subclass.py

ftconan/python3

eb63ba33960072f792ecce6db809866b38c402f8

[ "MIT" ]

12

2020-03-14T05:32:26.000Z

2022-03-12T00:08:49.000Z

effective_python/metaclass_property/confirm_subclass.py

ftconan/python3

eb63ba33960072f792ecce6db809866b38c402f8

[ "MIT" ]

1

2018-12-19T22:08:00.000Z

""" @author: magician @file: confirm_subclass.py @date: 2020/1/14 """ class Meta(type): """ Meta """ class MyClass(object, metaclass=Meta): """ MyClass """ stuff = 3 class ValidatePolygon(type): """ ValidatePolygon """ def __new__(meta, name, bases, class_dict): """ Don't validate the abstract Polygon class @param name: @param bases: @param class_dict: """ if bases != (object,): if class_dict['sides'] < 3: raise ValueError('Polygons need 3+ sides') return type.__new__(meta, name, bases, class_dict) class Polygon(object, metaclass=ValidatePolygon): """ Polygon """ # Specified by subclasses sides = None @classmethod class Triangle(Polygon): """ Triangle """ sides = 3 if __name__ == '__main__': print('Before Class') try: class Line(Polygon): """ Line """ print('Before sides') sides = 1 print('After sides') except Exception as e: print(e) print('After Class')

18.192308

58

0.538407

""" @author: magician @file: confirm_subclass.py @date: 2020/1/14 """ class Meta(type): """ Meta """ def __new__(meta, name, bases, class_dict): print(meta, name, bases, class_dict) return type.__new__(meta, name, bases, class_dict) class MyClass(object, metaclass=Meta): """ MyClass """ stuff = 3 def foo(self): pass class ValidatePolygon(type): """ ValidatePolygon """ def __new__(meta, name, bases, class_dict): """ Don't validate the abstract Polygon class @param name: @param bases: @param class_dict: """ if bases != (object,): if class_dict['sides'] < 3: raise ValueError('Polygons need 3+ sides') return type.__new__(meta, name, bases, class_dict) class Polygon(object, metaclass=ValidatePolygon): """ Polygon """ # Specified by subclasses sides = None @classmethod def interior_angles(cls): return (cls.sides - 2) * 180 class Triangle(Polygon): """ Triangle """ sides = 3 if __name__ == '__main__': print('Before Class') try: class Line(Polygon): """ Line """ print('Before sides') sides = 1 print('After sides') except Exception as e: print(e) print('After Class')

174

0

79

243cd76a122be32db8b6099cc8850f0875085453

2,309

py

Python

Geometry/ForwardCommonData/python/testForwardXML_cfi.py

PKUfudawei/cmssw

8fbb5ce74398269c8a32956d7c7943766770c093

[ "Apache-2.0" ]

1

2021-11-30T16:24:46.000Z

Geometry/ForwardCommonData/python/testForwardXML_cfi.py

PKUfudawei/cmssw

8fbb5ce74398269c8a32956d7c7943766770c093

[ "Apache-2.0" ]

4

2021-11-29T13:57:56.000Z

2022-03-29T06:28:36.000Z

Geometry/ForwardCommonData/python/testForwardXML_cfi.py

PKUfudawei/cmssw

8fbb5ce74398269c8a32956d7c7943766770c093

[ "Apache-2.0" ]

1

2022-02-27T06:12:26.000Z

import FWCore.ParameterSet.Config as cms XMLIdealGeometryESSource = cms.ESSource("XMLIdealGeometryESSource", geomXMLFiles = cms.vstring( 'Geometry/CMSCommonData/data/materials/2021/v3/materials.xml', 'Geometry/CMSCommonData/data/rotations.xml', 'Geometry/CMSCommonData/data/extend/v3/cmsextent.xml', 'Geometry/CMSCommonData/data/cavernData/2021/v1/cavernData.xml', 'Geometry/CMSCommonData/data/cms/2021/v3/cms.xml', 'Geometry/CMSCommonData/data/cmsMother.xml', 'Geometry/CMSCommonData/data/eta3/etaMax.xml', 'Geometry/TrackerCommonData/data/pixfwdCommon.xml', 'Geometry/ForwardCommonData/data/pixfwd/2021/v1/pixfwd.xml', 'Geometry/HcalCommonData/data/average/hcalforwardmaterial.xml', 'Geometry/ForwardCommonData/data/forward/2021/v1/forward.xml', 'Geometry/ForwardCommonData/data/totemt2/2021/v1/totemt2.xml', 'Geometry/ForwardCommonData/data/forwardshield/2021/v1/forwardshield.xml', 'Geometry/ForwardCommonData/data/bhm.xml', 'Geometry/ForwardCommonData/data/pltbcm/2021/v1/pltbcm.xml', 'Geometry/ForwardCommonData/data/bcm1f/2021/v1/bcm1f.xml', 'Geometry/ForwardCommonData/data/plt/2021/v1/plt.xml', 'Geometry/ForwardSimData/data/bcm1fsens.xml', 'Geometry/ForwardCommonData/data/zdcmaterials/2021/v1/zdcmaterials.xml', 'Geometry/ForwardCommonData/data/lumimaterials.xml', 'Geometry/ForwardCommonData/data/zdcrotations.xml', 'Geometry/ForwardCommonData/data/lumirotations.xml', 'Geometry/ForwardCommonData/data/zdc/2021/v1/zdc.xml', 'Geometry/ForwardCommonData/data/zdclumi/2021/v2/zdclumi.xml', 'Geometry/ForwardCommonData/data/cmszdc.xml', 'Geometry/ForwardSimData/data/pltsens.xml', 'Geometry/ForwardSimData/data/bcm1fsens.xml', 'Geometry/ForwardSimData/data/totemsensT2/2021/totemsensT2.xml', 'Geometry/ForwardSimData/data/zdcsens.xml', 'Geometry/ForwardSimData/data/bhmProdCuts/2021/v1/bhmProdCuts.xml', 'Geometry/ForwardSimData/data/zdcProdCuts/2021/v2/zdcProdCuts.xml', 'Geometry/ForwardSimData/data/ForwardShieldProdCuts.xml', 'Geometry/CMSCommonData/data/FieldParameters.xml', ), rootNodeName = cms.string('cms:OCMS') )

56.317073

82

0.728021

import FWCore.ParameterSet.Config as cms XMLIdealGeometryESSource = cms.ESSource("XMLIdealGeometryESSource", geomXMLFiles = cms.vstring( 'Geometry/CMSCommonData/data/materials/2021/v3/materials.xml', 'Geometry/CMSCommonData/data/rotations.xml', 'Geometry/CMSCommonData/data/extend/v3/cmsextent.xml', 'Geometry/CMSCommonData/data/cavernData/2021/v1/cavernData.xml', 'Geometry/CMSCommonData/data/cms/2021/v3/cms.xml', 'Geometry/CMSCommonData/data/cmsMother.xml', 'Geometry/CMSCommonData/data/eta3/etaMax.xml', 'Geometry/TrackerCommonData/data/pixfwdCommon.xml', 'Geometry/ForwardCommonData/data/pixfwd/2021/v1/pixfwd.xml', 'Geometry/HcalCommonData/data/average/hcalforwardmaterial.xml', 'Geometry/ForwardCommonData/data/forward/2021/v1/forward.xml', 'Geometry/ForwardCommonData/data/totemt2/2021/v1/totemt2.xml', 'Geometry/ForwardCommonData/data/forwardshield/2021/v1/forwardshield.xml', 'Geometry/ForwardCommonData/data/bhm.xml', 'Geometry/ForwardCommonData/data/pltbcm/2021/v1/pltbcm.xml', 'Geometry/ForwardCommonData/data/bcm1f/2021/v1/bcm1f.xml', 'Geometry/ForwardCommonData/data/plt/2021/v1/plt.xml', 'Geometry/ForwardSimData/data/bcm1fsens.xml', 'Geometry/ForwardCommonData/data/zdcmaterials/2021/v1/zdcmaterials.xml', 'Geometry/ForwardCommonData/data/lumimaterials.xml', 'Geometry/ForwardCommonData/data/zdcrotations.xml', 'Geometry/ForwardCommonData/data/lumirotations.xml', 'Geometry/ForwardCommonData/data/zdc/2021/v1/zdc.xml', 'Geometry/ForwardCommonData/data/zdclumi/2021/v2/zdclumi.xml', 'Geometry/ForwardCommonData/data/cmszdc.xml', 'Geometry/ForwardSimData/data/pltsens.xml', 'Geometry/ForwardSimData/data/bcm1fsens.xml', 'Geometry/ForwardSimData/data/totemsensT2/2021/totemsensT2.xml', 'Geometry/ForwardSimData/data/zdcsens.xml', 'Geometry/ForwardSimData/data/bhmProdCuts/2021/v1/bhmProdCuts.xml', 'Geometry/ForwardSimData/data/zdcProdCuts/2021/v2/zdcProdCuts.xml', 'Geometry/ForwardSimData/data/ForwardShieldProdCuts.xml', 'Geometry/CMSCommonData/data/FieldParameters.xml', ), rootNodeName = cms.string('cms:OCMS') )

0

dbeafa580c18ce1f9935d21c5c0dd724455a6ada

12,269

py

Python

wbb/utils/dbfunctions.py

sppidy/WilliamButcherBot

8cbd1593dd44a5384f7b1c4d630aa65271282e3e

[ "MIT" ]

null

wbb/utils/dbfunctions.py

sppidy/WilliamButcherBot

8cbd1593dd44a5384f7b1c4d630aa65271282e3e

[ "MIT" ]

null

wbb/utils/dbfunctions.py

sppidy/WilliamButcherBot

8cbd1593dd44a5384f7b1c4d630aa65271282e3e

[ "MIT" ]

null

""" MIT License Copyright (c) 2021 TheHamkerCat Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ from wbb import db from typing import Dict, List, Union notesdb = db.notes filtersdb = db.filters warnsdb = db.warns karmadb = db.karma chatsdb = db.chats gbansdb = db.gban coupledb = db.couple captchadb = db.captcha antiservicedb = db.antiservice pmpermitdb = db.pmpermit """ Notes functions """ """ Filters funcions """ """ Warn functions """ """ Karma functions """ """ Chats log functions """ """ Gban functions """ # Couple Chooser # Captcha """Anti Service System""" """ PM PERMIT """

24.735887

78

0.615291

""" MIT License Copyright (c) 2021 TheHamkerCat Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ from wbb import db from typing import Dict, List, Union notesdb = db.notes filtersdb = db.filters warnsdb = db.warns karmadb = db.karma chatsdb = db.chats gbansdb = db.gban coupledb = db.couple captchadb = db.captcha antiservicedb = db.antiservice pmpermitdb = db.pmpermit """ Notes functions """ async def get_notes_count() -> dict: chats = notesdb.find({"chat_id": {"$lt": 0}}) if not chats: return {} chats_count = 0 notes_count = 0 for chat in await chats.to_list(length=1000000000): notes_name = await get_note_names(chat['chat_id']) notes_count += len(notes_name) chats_count += 1 return { "chats_count": chats_count, "notes_count": notes_count } async def _get_notes(chat_id: int) -> Dict[str, int]: _notes = await notesdb.find_one({"chat_id": chat_id}) if _notes: _notes = _notes["notes"] else: _notes = {} return _notes async def get_note_names(chat_id: int) -> List[str]: _notes = [] for note in await _get_notes(chat_id): _notes.append(note) return _notes async def get_note(chat_id: int, name: str) -> Union[bool, dict]: name = name.lower().strip() _notes = await _get_notes(chat_id) if name in _notes: return _notes[name] else: return False async def save_note(chat_id: int, name: str, note: dict): name = name.lower().strip() _notes = await _get_notes(chat_id) _notes[name] = note await notesdb.update_one( {"chat_id": chat_id}, { "$set": { "notes": _notes } }, upsert=True ) async def delete_note(chat_id: int, name: str) -> bool: notesd = await _get_notes(chat_id) name = name.lower().strip() if name in notesd: del notesd[name] await notesdb.update_one( {"chat_id": chat_id}, { "$set": { "notes": notesd } }, upsert=True ) return True return False """ Filters funcions """ async def get_filters_count() -> dict: chats = filtersdb.find({"chat_id": {"$lt": 0}}) if not chats: return {} chats_count = 0 filters_count = 0 for chat in await chats.to_list(length=1000000000): filters_name = await get_filters_names(chat['chat_id']) filters_count += len(filters_name) chats_count += 1 return { "chats_count": chats_count, "filters_count": filters_count } async def _get_filters(chat_id: int) -> Dict[str, int]: _filters = await filtersdb.find_one({"chat_id": chat_id}) if _filters: _filters = _filters['filters'] else: _filters = {} return _filters async def get_filters_names(chat_id: int) -> List[str]: _filters = [] for _filter in await _get_filters(chat_id): _filters.append(_filter) return _filters async def get_filter(chat_id: int, name: str) -> Union[bool, dict]: name = name.lower().strip() _filters = await _get_filters(chat_id) if name in _filters: return _filters[name] else: return False async def save_filter(chat_id: int, name: str, _filter: dict): name = name.lower().strip() _filters = await _get_filters(chat_id) _filters[name] = _filter await filtersdb.update_one( {"chat_id": chat_id}, { "$set": { "filters": _filters } }, upsert=True ) async def delete_filter(chat_id: int, name: str) -> bool: filtersd = await _get_filters(chat_id) name = name.lower().strip() if name in filtersd: del filtersd[name] await filtersdb.update_one( {"chat_id": chat_id}, { "$set": { "filters": filtersd } }, upsert=True ) return True return False """ Warn functions """ async def int_to_alpha(user_id: int) -> str: alphabet = ["a", "b", "c", "d", "e", "f", "g", "h", "i", "j"] text = "" user_id = str(user_id) for i in user_id: text += alphabet[int(i)] return text async def alpha_to_int(user_id_alphabet: str) -> int: alphabet = ["a", "b", "c", "d", "e", "f", "g", "h", "i", "j"] user_id = "" for i in user_id_alphabet: index = alphabet.index(i) user_id += str(index) user_id = int(user_id) return user_id async def get_warns_count() -> dict: chats = warnsdb.find({"chat_id": {"$lt": 0}}) if not chats: return {} chats_count = 0 warns_count = 0 for chat in await chats.to_list(length=100000000): for user in chat['warns']: warns_count += chat['warns'][user]['warns'] chats_count += 1 return { "chats_count": chats_count, "warns_count": warns_count } async def get_warns(chat_id: int) -> Dict[str, int]: warns = await warnsdb.find_one({"chat_id": chat_id}) if warns: warns = warns['warns'] else: warns = {} return warns async def get_warn(chat_id: int, name: str) -> Union[bool, dict]: name = name.lower().strip() warns = await get_warns(chat_id) if name in warns: return warns[name] async def add_warn(chat_id: int, name: str, warn: dict): name = name.lower().strip() warns = await get_warns(chat_id) warns[name] = warn await warnsdb.update_one( {"chat_id": chat_id}, { "$set": { "warns": warns } }, upsert=True ) async def remove_warns(chat_id: int, name: str) -> bool: warnsd = await get_warns(chat_id) name = name.lower().strip() if name in warnsd: del warnsd[name] await warnsdb.update_one( {"chat_id": chat_id}, { "$set": { "warns": warnsd } }, upsert=True ) return True return False """ Karma functions """ async def get_karmas_count() -> dict: chats = karmadb.find({"chat_id": {"$lt": 0}}) if not chats: return {} chats_count = 0 karmas_count = 0 for chat in await chats.to_list(length=1000000): for i in chat['karma']: karmas_count += chat['karma'][i]['karma'] chats_count += 1 return { "chats_count": chats_count, "karmas_count": karmas_count } async def get_karmas(chat_id: int) -> Dict[str, int]: karma = await karmadb.find_one({"chat_id": chat_id}) if karma: karma = karma['karma'] else: karma = {} return karma async def get_karma(chat_id: int, name: str) -> Union[bool, dict]: name = name.lower().strip() karmas = await get_karmas(chat_id) if name in karmas: return karmas[name] async def update_karma(chat_id: int, name: str, karma: dict): name = name.lower().strip() karmas = await get_karmas(chat_id) karmas[name] = karma await karmadb.update_one( {"chat_id": chat_id}, { "$set": { "karma": karmas } }, upsert=True ) """ Chats log functions """ async def is_served_chat(chat_id: int) -> bool: chat = await chatsdb.find_one({"chat_id": chat_id}) if not chat: return False return True async def get_served_chats() -> list: chats = chatsdb.find({"chat_id": {'$lt': 0}}) if not chats: return [] chats_list = [] for chat in await chats.to_list(length=1000000000): chats_list.append(chat) return chats_list async def add_served_chat(chat_id: int): is_served = await is_served_chat(chat_id) if is_served: return return await chatsdb.insert_one({"chat_id": chat_id}) async def remove_served_chat(chat_id: int): is_served = await is_served_chat(chat_id) if not is_served: return return await chatsdb.delete_one({"chat_id": chat_id}) """ Gban functions """ async def get_gbans_count() -> int: users = gbansdb.find({"user_id": {"$gt": 0}}) users = await users.to_list(length=100000) return len(users) async def is_gbanned_user(user_id: int) -> bool: user = await gbansdb.find_one({"user_id": user_id}) if not user: return False return True async def add_gban_user(user_id: int): is_gbanned = await is_gbanned_user(user_id) if is_gbanned: return return await gbansdb.insert_one({"user_id": user_id}) async def remove_gban_user(user_id: int): is_gbanned = await is_gbanned_user(user_id) if not is_gbanned: return return await gbansdb.delete_one({"user_id": user_id}) # Couple Chooser async def _get_lovers(chat_id: int): lovers = await coupledb.find_one({"chat_id": chat_id}) if lovers: lovers = lovers["couple"] else: lovers = {} return lovers async def get_couple(chat_id: int, date: str): lovers = await _get_lovers(chat_id) if date in lovers: return lovers[date] else: return False async def save_couple(chat_id: int, date: str, couple: dict): lovers = await _get_lovers(chat_id) lovers[date] = couple await coupledb.update_one( {"chat_id": chat_id}, { "$set": { "couple": lovers } }, upsert=True ) # Captcha async def is_captcha_on(chat_id: int) -> bool: chat = await captchadb.find_one({"chat_id": chat_id}) if not chat: return True return False async def captcha_on(chat_id: int): is_captcha = await is_captcha_on(chat_id) if is_captcha: return return await captchadb.delete_one({"chat_id": chat_id}) async def captcha_off(chat_id: int): is_captcha = await is_captcha_on(chat_id) if not is_captcha: return return await captchadb.insert_one({"chat_id": chat_id}) """Anti Service System""" async def is_antiservice_on(chat_id: int) -> bool: chat = await antiservicedb.find_one({"chat_id": chat_id}) if not chat: return True return False async def antiservice_on(chat_id: int): is_antiservice = await is_antiservice_on(chat_id) if is_antiservice: return return await antiservicedb.delete_one({"chat_id": chat_id}) async def antiservice_off(chat_id: int): is_antiservice = await is_antiservice_on(chat_id) if not is_antiservice: return return await antiservicedb.insert_one({"chat_id": chat_id}) """ PM PERMIT """ async def is_pmpermit_approved(user_id: int) -> bool: user = await pmpermitdb.find_one({"user_id": user_id}) if not user: return False return True async def approve_pmpermit(user_id: int): is_pmpermit = await is_pmpermit_approved(user_id) if is_pmpermit: return return await pmpermitdb.insert_one({"user_id": user_id}) async def disapprove_pmpermit(user_id: int): is_pmpermit = await is_pmpermit_approved(user_id) if not is_pmpermit: return return await pmpermitdb.delete_one({"user_id": user_id})

9,652

0

989

49de79cb6c84fe14e0275dff4c478a1045fd3ede

1,308

py

Python

explicalib/calibration/evaluation/diagrams/discrete_diagrams.py

euranova/estimating_eces

9bfa81dd7a39ebe069c5b11b8e7a9bf9017e9350

[ "MIT" ]

2

2021-11-30T18:44:11.000Z

2021-11-30T18:44:19.000Z

explicalib/calibration/evaluation/diagrams/discrete_diagrams.py

euranova/estimating_eces

9bfa81dd7a39ebe069c5b11b8e7a9bf9017e9350

[ "MIT" ]

null

explicalib/calibration/evaluation/diagrams/discrete_diagrams.py

euranova/estimating_eces

9bfa81dd7a39ebe069c5b11b8e7a9bf9017e9350

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ @author: nicolas.posocco """ from sklearn.calibration import calibration_curve import numpy as np

39.636364

113

0.703364

# -*- coding: utf-8 -*- """ @author: nicolas.posocco """ from sklearn.calibration import calibration_curve import numpy as np def reliability_diagram(label_of_interest, scores, n_bins): # label_of_interest assert type(label_of_interest) is np.ndarray, \ "label_of_interest should be an np.ndarray, not a {}.".format(type(label_of_interest)) assert label_of_interest.ndim == 1, \ "label_of_interest should be a 1D array, not a {}D one.".format(label_of_interest.ndim) assert label_of_interest.shape[0] > 0, \ "label_of_interest can't be an empty array." # scores assert type(scores) is np.ndarray, \ "scores should be an np.ndarray, not a {}.".format(type(scores)) assert scores.ndim == 1, \ "scores should be a 1D array, not a {}D one.".format(scores.ndim) assert scores.shape == label_of_interest.shape, \ "scores and label_of_interest should share a common shape, here they are respectively {} and {}.".format( scores.shape, label_of_interest.shape) # Calculation via sklearn fraction_of_positives, mean_predicted_value = calibration_curve(label_of_interest, scores, n_bins=n_bins) return {"fraction_of_positives": fraction_of_positives, "mean_predicted_value": mean_predicted_value}

1,157

0

23

12561c7b297f03c8a4ed8c22313832ae6dd69b64

815

py

Python

src/aoikfiletypeasso/sac.py

AoiKuiyuyou/AoikWinFileTypeAsso

294570f729660b7f374ec6c128c9644b8f0eace0

[ "MIT" ]

3

2016-09-24T16:01:05.000Z

2020-06-16T07:40:14.000Z

src/aoikfiletypeasso/sac.py

AoiKuiyuyou/AoikFileTypeAsso

294570f729660b7f374ec6c128c9644b8f0eace0

[ "MIT" ]

null

src/aoikfiletypeasso/sac.py

AoiKuiyuyou/AoikFileTypeAsso

294570f729660b7f374ec6c128c9644b8f0eace0

[ "MIT" ]

null

# coding: utf-8 # # File name "sac" means "SHCNE_ASSOCCHANGED" used at 4xc5k9H. # from __future__ import absolute_import import sys #/ if __name__ == '__main__': sys.exit(main())

19.404762

89

0.650307

# coding: utf-8 # # File name "sac" means "SHCNE_ASSOCCHANGED" used at 4xc5k9H. # from __future__ import absolute_import import sys #/ def main(): #/ sys.stderr.write('#/ Send shell change notification, to make changes take effect.\n') try: import win32com.shell.shell as shell import win32com.shell.shellcon as shellcon except ImportError: sys.stderr.write(r"""Error: Importing |win32com| failed. Please install |pywin32|. Download is available at http://sourceforge.net/projects/pywin32/files/pywin32/ """) return 1 #/ 4xc5k9H shell.SHChangeNotify( shellcon.SHCNE_ASSOCCHANGED, shellcon.SHCNF_IDLIST, None, None, ) sys.stderr.write('OK\n') #/ return 0 if __name__ == '__main__': sys.exit(main())

606

0

22

ccf3e84481404af3c4b3cd4070a56149409c72b0

326

py

Python

ReadingGauges/ComputerSide/GrabberGaugesOutput_python3/ScriptRunGrabber.py

jerabaul29/PaddleAndUltrasonicGauges

5c6ba80ddfd44190eb21d5c61979ac802a54cb99

[ "MIT" ]

2

2021-02-03T12:55:57.000Z

2021-02-11T07:07:06.000Z

ReadingGauges/ComputerSide/GrabberGaugesOutput_python3/ScriptRunGrabber.py

jerabaul29/PaddleAndUltrasonicGauges

5c6ba80ddfd44190eb21d5c61979ac802a54cb99

[ "MIT" ]

null

ReadingGauges/ComputerSide/GrabberGaugesOutput_python3/ScriptRunGrabber.py

jerabaul29/PaddleAndUltrasonicGauges

5c6ba80ddfd44190eb21d5c61979ac802a54cb99

[ "MIT" ]

null

import Grabber gauge_grabber = Grabber.grabb_serial_values() gauge_grabber.init() gauge_grabber.grabb(10) gauge_grabber.convert_grabbed_to_numpy() gauge_grabber.plot_grabbed_data() gauge_grabber.clean_numpy_dict() gauge_grabber.save_cleaned_dict_numpy('test_saving') gauge_grabber.save_cleaned_dict_numpy_csv('test_saving')

27.166667

56

0.868098

import Grabber gauge_grabber = Grabber.grabb_serial_values() gauge_grabber.init() gauge_grabber.grabb(10) gauge_grabber.convert_grabbed_to_numpy() gauge_grabber.plot_grabbed_data() gauge_grabber.clean_numpy_dict() gauge_grabber.save_cleaned_dict_numpy('test_saving') gauge_grabber.save_cleaned_dict_numpy_csv('test_saving')

0

cc20e3149a11c3be4fc61095e2693ba607d9e501

5,488

py

Python

src/stdout.py

X-EcutiOnner/fileobj

7e4120759450bbdd1eee4ec26c8a757a8af48093

[ "BSD-2-Clause" ]

17

2015-05-23T11:09:46.000Z

2021-12-10T14:28:01.000Z

src/stdout.py

X-EcutiOnner/fileobj

7e4120759450bbdd1eee4ec26c8a757a8af48093

[ "BSD-2-Clause" ]

3

2015-03-23T04:35:25.000Z

2017-09-15T07:12:15.000Z

src/stdout.py

X-EcutiOnner/fileobj

7e4120759450bbdd1eee4ec26c8a757a8af48093

[ "BSD-2-Clause" ]

2

2016-01-07T00:38:13.000Z

2020-12-02T08:27:28.000Z

# Copyright (c) 2014, Tomohiro Kusumi # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # 1. Redistributions of source code must retain the above copyright notice, this # list of conditions and the following disclaimer. # 2. Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND # ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED # WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR # ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES # (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; # LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND # ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS # SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import sys from . import filebytes from . import ncurses from . import setting from . import terminal from . import util Error = Exception _count = 0 A_NONE = 0 A_BOLD = 1 A_REVERSE = 2 A_STANDOUT = 4 A_UNDERLINE = 8 A_COLOR_FB = 0 A_COLOR_CURRENT = 0 A_COLOR_ZERO = 0 A_COLOR_FF = 0 A_COLOR_PRINT = 0 A_COLOR_DEFAULT = 0 A_COLOR_VISUAL = 0 A_COLOR_OFFSET = 0 BUTTON1_CLICKED = 0 BUTTON1_PRESSED = 0 BUTTON1_RELEASED = 0 BUTTON1_DOUBLE_CLICKED = 0 BUTTON1_TRIPLE_CLICKED = 0 BUTTON2_CLICKED = 0 BUTTON2_PRESSED = 0 BUTTON2_RELEASED = 0 BUTTON2_DOUBLE_CLICKED = 0 BUTTON2_TRIPLE_CLICKED = 0 BUTTON3_CLICKED = 0 BUTTON3_PRESSED = 0 BUTTON3_RELEASED = 0 BUTTON3_DOUBLE_CLICKED = 0 BUTTON3_TRIPLE_CLICKED = 0 BUTTON4_CLICKED = 0 BUTTON4_PRESSED = 0 BUTTON4_RELEASED = 0 BUTTON4_DOUBLE_CLICKED = 0 BUTTON4_TRIPLE_CLICKED = 0 REPORT_MOUSE_POSITION = 0 # APIs must be compatible with # https://docs.python.org/3/library/curses.html

24.5

81

0.647959

# Copyright (c) 2014, Tomohiro Kusumi # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # 1. Redistributions of source code must retain the above copyright notice, this # list of conditions and the following disclaimer. # 2. Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND # ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED # WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR # ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES # (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; # LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND # ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS # SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import sys from . import filebytes from . import ncurses from . import setting from . import terminal from . import util Error = Exception _count = 0 A_NONE = 0 A_BOLD = 1 A_REVERSE = 2 A_STANDOUT = 4 A_UNDERLINE = 8 A_COLOR_FB = 0 A_COLOR_CURRENT = 0 A_COLOR_ZERO = 0 A_COLOR_FF = 0 A_COLOR_PRINT = 0 A_COLOR_DEFAULT = 0 A_COLOR_VISUAL = 0 A_COLOR_OFFSET = 0 BUTTON1_CLICKED = 0 BUTTON1_PRESSED = 0 BUTTON1_RELEASED = 0 BUTTON1_DOUBLE_CLICKED = 0 BUTTON1_TRIPLE_CLICKED = 0 BUTTON2_CLICKED = 0 BUTTON2_PRESSED = 0 BUTTON2_RELEASED = 0 BUTTON2_DOUBLE_CLICKED = 0 BUTTON2_TRIPLE_CLICKED = 0 BUTTON3_CLICKED = 0 BUTTON3_PRESSED = 0 BUTTON3_RELEASED = 0 BUTTON3_DOUBLE_CLICKED = 0 BUTTON3_TRIPLE_CLICKED = 0 BUTTON4_CLICKED = 0 BUTTON4_PRESSED = 0 BUTTON4_RELEASED = 0 BUTTON4_DOUBLE_CLICKED = 0 BUTTON4_TRIPLE_CLICKED = 0 REPORT_MOUSE_POSITION = 0 def init(): from . import screen return newwin(screen.get_size_y(), screen.get_size_x(), 0, 0), \ A_NONE, A_BOLD, A_REVERSE, A_STANDOUT, A_UNDERLINE, \ A_COLOR_FB, A_COLOR_CURRENT, A_COLOR_ZERO, A_COLOR_FF, A_COLOR_PRINT, \ A_COLOR_DEFAULT, A_COLOR_VISUAL, A_COLOR_OFFSET def cleanup(): ncurses.cleanup_windows() def doupdate(): return def flash(): return def newwin(leny, lenx, begy, begx, ref=None): scr = _window(leny, lenx, begy, begx, ref) scr.init() return scr def get_size(): return -1, -1 def is_resize_supported(): return False def has_chgat(): return True def has_color(): return False def can_change_color(): return False def set_color_attr(s): return -1 def use_color(): return False def use_mouse(): return False def iter_color_name(): yield "black" yield "white" def getmouse(): return -1, -1, -1, -1, 0 def get_mouse_event_name(bstate): return "" # APIs must be compatible with # https://docs.python.org/3/library/curses.html class _window (ncurses.SeqWindow): def __init__(self, leny, lenx, begy, begx, ref): self.__siz = util.Pair(leny, lenx) self.__pos = util.Pair(begy, begx) self.__ref = ref def init(self): global _count super(_window, self).init() if _count == 0: assert terminal.init_getch(sys.stdin) != -1 _count += 1 def cleanup(self): global _count super(_window, self).cleanup() _count -= 1 if _count == 0: assert terminal.cleanup_getch(sys.stdin) != -1 def __mkstr(self, y, x, s): return "{0} ({1:2}, {2:3}) {3}".format(repr(self.__ref), y, x, filebytes.str(s)) def keypad(self, yes): return def idlok(self, yes): return def scrollok(self, flag): return def bkgd(self, ch, attr=A_NONE): # attr must be optional return def addstr(self, y, x, s, attr=A_NONE): # attr must be optional if setting.stdout_verbose > 0: util.printf(self.__mkstr(y, x, s)) if setting.stdout_verbose > 2: for x in util.iter_traceback(): util.printf(x) def clrtoeol(self): return def erase(self): return def clear(self): return def noutrefresh(self): return def refresh(self): return def move(self, y, x): return def mvwin(self, y, x): self.__pos.set(y, x) def resize(self, y, x): self.__siz.set(y, x) def box(self): return def border(self, ls, rs, ts, bs, tl, tr, bl, br): return def chgat(self, y, x, num, attr): return def getmaxyx(self): return self.__siz.y, self.__siz.x def getbegyx(self): return self.__pos.y, self.__pos.x def _getch(self): return terminal.getch(sys.stdin) def preprocess(self, x, l): if setting.stdout_verbose > 1: if util.isprint(x): util.printf("{0} {1}".format(x, chr(x))) else: util.printf(x)

2,029

13

1,037

5f8e5d269900b982776e65a97bb854c3f10039cd

834

py

Python

User/set-namespace.py

rvock/Sublime-Text-Preferences

fbe408bc4740dee984d37336aa2888c8aaa0d74b

[ "MIT" ]

1

2015-05-18T15:52:47.000Z

User/set-namespace.py

rvock/Sublime-Text-Preferences

fbe408bc4740dee984d37336aa2888c8aaa0d74b

[ "MIT" ]

null

User/set-namespace.py

rvock/Sublime-Text-Preferences

fbe408bc4740dee984d37336aa2888c8aaa0d74b

[ "MIT" ]

null

import sublime, sublime_plugin import sys import re import os

26.0625

86

0.673861

import sublime, sublime_plugin import sys import re import os class SetNamespaceCommand(sublime_plugin.TextCommand): def run(self, edit): if self.view.settings().get('is_widget'): return namespace = os.path.dirname(self.view.file_name()) extensionName = re.sub(r'.*(?:typo3conf/ext|packages)/([^/]*)/.*', r'\1', namespace) if extensionName: extensionName = extensionName.title().replace('_', '') + '\\' # strip everything before Classes or src namespace = re.sub(r'.*(Classes|src)/', r'', namespace) # Change / to \ namespace = re.sub(r'/', r'\\', namespace) namespace = 'namespace Vierwd\\' + extensionName + namespace + ';' for region in self.view.sel(): s = self.view.substr(region) self.view.replace(edit, region, namespace) def is_enabled(self): return len(self.view.file_name()) > 0

669

33

70

02283df57f4319a703ace0e80322454df4dd0614

3,493

py

Python

software/permacam_processing/image_quality_process.py

lab11/Task2

3c3451599dd303cd1e2469e5b9e36e1b4ca49fa6

[ "Apache-2.0" ]

21

2018-08-29T18:58:26.000Z

2022-01-12T09:08:04.000Z

software/permacam_processing/image_quality_process.py

lab11/permamote

3c3451599dd303cd1e2469e5b9e36e1b4ca49fa6

[ "Apache-2.0" ]

9

2017-11-08T03:22:58.000Z

2020-05-02T18:23:12.000Z

software/permacam_processing/image_quality_process.py

lab11/Task2

3c3451599dd303cd1e2469e5b9e36e1b4ca49fa6

[ "Apache-2.0" ]

8

2018-10-28T23:44:23.000Z

2021-07-11T05:18:02.000Z

#!/usr/bin/env python3 import argparse from glob import glob from skimage import exposure from PIL import Image import colour import numpy as np import pandas as pd import os from colour_demosaicing import ( demosaicing_CFA_Bayer_bilinear, demosaicing_CFA_Bayer_Malvar2004, demosaicing_CFA_Bayer_Menon2007, mosaicing_CFA_Bayer) cctf_encoding = colour.cctf_encoding parser = argparse.ArgumentParser(description='Process quality series of Permacam images and generate error measurements') parser.add_argument('save_dir', help='Optional save detected images to file in dir') args = parser.parse_args() jpegs = glob(args.save_dir + '/image_mono*.jpeg') raws = glob(args.save_dir + '/image_raw*.npy') manifest_fname = args.save_dir + '/manifest.pkl' data = None if not os.path.isfile(manifest_fname) : print('Generating') data = {} data['filename'] = [] data['id'] = [] data['quality'] = [] data['size'] = [] data['raw'] = [] data['time'] = [] data['image_array'] = [] d = None fname = None for f in jpegs: data['filename'].append(f) i = int(f.split('_')[-1].split('.')[0]) data['id'].append(i) q = int(f.split('_')[2]) data['quality'].append(q) data['size'].append(os.path.getsize(f)) data['raw'].append(0) time_fname = args.save_dir + '/time_to_send_' + str(q) + '_' + str(i) + '.txt' time_to_send = 0 with open(time_fname, 'r') as tf: time_to_send = float(tf.read()); data['time'].append(time_to_send) jpeg = Image.open(f) d = np.array(jpeg.getdata()).reshape(jpeg.size[0], jpeg.size[1]) / 0xff d = cctf_encoding(demosaicing_CFA_Bayer_Menon2007(d, 'BGGR')) d = exposure.rescale_intensity(d, (0,1)) d = exposure.adjust_gamma(d, 1.5) #d = (d * 255).astype(np.uint8) fname = f.replace('mono', 'jpeg_demosaiced').replace('.jpeg', '.npy') np.save(fname, d) data['image_array'].append(fname) result = Image.fromarray((d * 255).astype(np.uint8)) result.save(fname.replace('npy','jpeg'), format='JPEG') for f in raws: data['filename'].append(f) i = int(f.split('_')[-1].split('.')[0]) data['id'].append(i) data['quality'].append(100) data['raw'].append(1) data['size'].append(d.shape[0] * d.shape[1]) time_fname = args.save_dir + '/time_to_send_0_' + str(i) + '.txt' time_to_send = 0 with open(time_fname, 'r') as tf: time_to_send = float(tf.read()); data['time'].append(time_to_send) d = np.load(f) / float(0xff) d = cctf_encoding(demosaicing_CFA_Bayer_Menon2007(d, 'BGGR')) d = exposure.rescale_intensity(d, (0,1)) d = exposure.adjust_gamma(d, 1.5) #d = (d * 255).astype(np.uint8) fname = f.replace('raw', 'demosaiced') np.save(fname, d) data['image_array'].append(fname) result = Image.fromarray((d * 255).astype(np.uint8)) result.save(fname.replace('npy','jpeg'), format='JPEG') data = pd.DataFrame(data) qualities = set(np.unique(data['quality']).flatten()) for i in data['id']: avail_qual = set(data[data['id'] == i]['quality']) if (avail_qual != qualities): data = data[data['id'] != i] data.to_pickle(manifest_fname) else: data = pd.read_pickle(manifest_fname) print(data) print(len(np.unique(data['id'])))

34.245098

121

0.604924

#!/usr/bin/env python3 import argparse from glob import glob from skimage import exposure from PIL import Image import colour import numpy as np import pandas as pd import os from colour_demosaicing import ( demosaicing_CFA_Bayer_bilinear, demosaicing_CFA_Bayer_Malvar2004, demosaicing_CFA_Bayer_Menon2007, mosaicing_CFA_Bayer) cctf_encoding = colour.cctf_encoding parser = argparse.ArgumentParser(description='Process quality series of Permacam images and generate error measurements') parser.add_argument('save_dir', help='Optional save detected images to file in dir') args = parser.parse_args() jpegs = glob(args.save_dir + '/image_mono*.jpeg') raws = glob(args.save_dir + '/image_raw*.npy') manifest_fname = args.save_dir + '/manifest.pkl' data = None if not os.path.isfile(manifest_fname) : print('Generating') data = {} data['filename'] = [] data['id'] = [] data['quality'] = [] data['size'] = [] data['raw'] = [] data['time'] = [] data['image_array'] = [] d = None fname = None for f in jpegs: data['filename'].append(f) i = int(f.split('_')[-1].split('.')[0]) data['id'].append(i) q = int(f.split('_')[2]) data['quality'].append(q) data['size'].append(os.path.getsize(f)) data['raw'].append(0) time_fname = args.save_dir + '/time_to_send_' + str(q) + '_' + str(i) + '.txt' time_to_send = 0 with open(time_fname, 'r') as tf: time_to_send = float(tf.read()); data['time'].append(time_to_send) jpeg = Image.open(f) d = np.array(jpeg.getdata()).reshape(jpeg.size[0], jpeg.size[1]) / 0xff d = cctf_encoding(demosaicing_CFA_Bayer_Menon2007(d, 'BGGR')) d = exposure.rescale_intensity(d, (0,1)) d = exposure.adjust_gamma(d, 1.5) #d = (d * 255).astype(np.uint8) fname = f.replace('mono', 'jpeg_demosaiced').replace('.jpeg', '.npy') np.save(fname, d) data['image_array'].append(fname) result = Image.fromarray((d * 255).astype(np.uint8)) result.save(fname.replace('npy','jpeg'), format='JPEG') for f in raws: data['filename'].append(f) i = int(f.split('_')[-1].split('.')[0]) data['id'].append(i) data['quality'].append(100) data['raw'].append(1) data['size'].append(d.shape[0] * d.shape[1]) time_fname = args.save_dir + '/time_to_send_0_' + str(i) + '.txt' time_to_send = 0 with open(time_fname, 'r') as tf: time_to_send = float(tf.read()); data['time'].append(time_to_send) d = np.load(f) / float(0xff) d = cctf_encoding(demosaicing_CFA_Bayer_Menon2007(d, 'BGGR')) d = exposure.rescale_intensity(d, (0,1)) d = exposure.adjust_gamma(d, 1.5) #d = (d * 255).astype(np.uint8) fname = f.replace('raw', 'demosaiced') np.save(fname, d) data['image_array'].append(fname) result = Image.fromarray((d * 255).astype(np.uint8)) result.save(fname.replace('npy','jpeg'), format='JPEG') data = pd.DataFrame(data) qualities = set(np.unique(data['quality']).flatten()) for i in data['id']: avail_qual = set(data[data['id'] == i]['quality']) if (avail_qual != qualities): data = data[data['id'] != i] data.to_pickle(manifest_fname) else: data = pd.read_pickle(manifest_fname) print(data) print(len(np.unique(data['id'])))

0

fd261e8c4a8691fb747969570204d7a92c2cb98d

2,307

py

Python

Code/packages/migrations/0001_initial.py

praktianerJones/LSD

8ca07bfcf53347dc466be0cae260387c90f0c2ed

[ "BSD-3-Clause" ]

2

2021-12-15T21:58:43.000Z

2021-12-15T22:17:26.000Z

Code/packages/migrations/0001_initial.py

praktianerJones/LSD

8ca07bfcf53347dc466be0cae260387c90f0c2ed

[ "BSD-3-Clause" ]

null

Code/packages/migrations/0001_initial.py

praktianerJones/LSD

8ca07bfcf53347dc466be0cae260387c90f0c2ed

[ "BSD-3-Clause" ]

1

2021-12-19T17:02:02.000Z

# Generated by Django 2.1.7 on 2020-10-22 12:55 from django.conf import settings from django.db import migrations, models import django.db.models.deletion import django.utils.timezone

31.60274

82

0.397486

# Generated by Django 2.1.7 on 2020-10-22 12:55 from django.conf import settings from django.db import migrations, models import django.db.models.deletion import django.utils.timezone class Migration(migrations.Migration): initial = True dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ("licenses", "0001_initial"), ] operations = [ migrations.CreateModel( name="Package", fields=[ ( "id", models.AutoField( auto_created=True, primary_key=True, serialize=False, verbose_name="ID", ), ), ("package_name", models.CharField(max_length=100)), ("package_version", models.CharField(max_length=50)), ("package_description", models.TextField(blank=True)), ( "usage", models.CharField( choices=[ ("d", "dynamic"), ("s", "static"), ("r", "rootfs"), ("u", "unknown"), ], default="u", max_length=1, ), ), ("date", models.DateTimeField(default=django.utils.timezone.now)), ( "license_list", models.ManyToManyField( related_name="linked_licenses", to="licenses.License" ), ), ( "license_used", models.ForeignKey( on_delete=django.db.models.deletion.PROTECT, to="licenses.License", ), ), ( "package_creator", models.ForeignKey( null=True, on_delete=django.db.models.deletion.PROTECT, to=settings.AUTH_USER_MODEL, ), ), ], ), ]

0

2,097

23

4765077027b875beb3bbe235bb22451c6aed58b9

2,655

py

Python

src/website/misc/mail.py

wooyek/secure-share

b3b1dd6a03dc278e881e866a5554254523d33a81

[ "MIT" ]

null

src/website/misc/mail.py

wooyek/secure-share

b3b1dd6a03dc278e881e866a5554254523d33a81

[ "MIT" ]

1

2020-05-01T10:53:25.000Z

src/website/misc/mail.py

wooyek/secure-share

b3b1dd6a03dc278e881e866a5554254523d33a81

[ "MIT" ]

null

# coding=utf-8 # Copyright 2015 Brave Labs sp. z o.o. # All rights reserved. # # This source code and all resulting intermediate files are CONFIDENTIAL and # PROPRIETY TRADE SECRETS of Brave Labs sp. z o.o. # Use is subject to license terms. See NOTICE file of this project for details. import json import logging from smtplib import SMTPAuthenticationError, SMTPServerDisconnected import html2text from django.conf import settings from django.core.mail import EmailMultiAlternatives from django.core.mail import send_mail as django_send_mail from django.template.exceptions import TemplateDoesNotExist from django.template.loader import render_to_string from sparkpost.exceptions import SparkPostAPIException def send_mail(template_path, ctx, to): """Simplifies message rendering""" ctx.setdefault('BASE_URL', settings.BASE_URL) message = render_to_string(template_path + '.jinja2', ctx) html_message = render_to_string(template_path + '.html', ctx) subject, message = message.split("\n", 1) if not isinstance(to, list): to = [to] django_send_mail( subject=subject, message=message, html_message=html_message, from_email=settings.DEFAULT_FROM_EMAIL, recipient_list=to ) def send_mail_template(template, ctx, subject, to=None, **kwargs): """Simplifies message rendering""" ctx.setdefault('BASE_URL', settings.BASE_URL) html_message = render_to_string(template, ctx) try: text_message = render_to_string(template.replace(".html", ".jinja2"), ctx) except TemplateDoesNotExist: text_message = html2text.html2text(html_message) if not isinstance(to, list): to = [to] kwargs.setdefault('from_email', settings.DEFAULT_FROM_EMAIL) kwargs.setdefault('reply_to', [settings.DEFAULT_REPLY_TO_EMAIL]) message = EmailMultiAlternatives(subject, body=text_message, to=to, **kwargs) if html_message: message.attach_alternative(html_message, 'text/html') logging.debug("to: %s", to) if 'unsubscribe' in ctx: message.extra_headers['List-Unsubscribe'] = "<{}>".format(ctx['unsubscribe']) message.extra_headers['X-MSYS-API'] = json.dumps({'options': {'transactional': True}}) try: return message.send() except SparkPostAPIException as ex: if ex.status == 1902 or not settings.FAIL_ON_EMAIL_SUPPRESSION: logging.error("Email suppression: %s", to, exc_info=ex) else: raise except (SMTPServerDisconnected, SMTPAuthenticationError) as ex: logging.error("", exc_info=ex) # Retry once return message.send()

34.480519

94

0.711864

# coding=utf-8 # Copyright 2015 Brave Labs sp. z o.o. # All rights reserved. # # This source code and all resulting intermediate files are CONFIDENTIAL and # PROPRIETY TRADE SECRETS of Brave Labs sp. z o.o. # Use is subject to license terms. See NOTICE file of this project for details. import json import logging from smtplib import SMTPAuthenticationError, SMTPServerDisconnected import html2text from django.conf import settings from django.core.mail import EmailMultiAlternatives from django.core.mail import send_mail as django_send_mail from django.template.exceptions import TemplateDoesNotExist from django.template.loader import render_to_string from sparkpost.exceptions import SparkPostAPIException def send_mail(template_path, ctx, to): """Simplifies message rendering""" ctx.setdefault('BASE_URL', settings.BASE_URL) message = render_to_string(template_path + '.jinja2', ctx) html_message = render_to_string(template_path + '.html', ctx) subject, message = message.split("\n", 1) if not isinstance(to, list): to = [to] django_send_mail( subject=subject, message=message, html_message=html_message, from_email=settings.DEFAULT_FROM_EMAIL, recipient_list=to ) def send_mail_template(template, ctx, subject, to=None, **kwargs): """Simplifies message rendering""" ctx.setdefault('BASE_URL', settings.BASE_URL) html_message = render_to_string(template, ctx) try: text_message = render_to_string(template.replace(".html", ".jinja2"), ctx) except TemplateDoesNotExist: text_message = html2text.html2text(html_message) if not isinstance(to, list): to = [to] kwargs.setdefault('from_email', settings.DEFAULT_FROM_EMAIL) kwargs.setdefault('reply_to', [settings.DEFAULT_REPLY_TO_EMAIL]) message = EmailMultiAlternatives(subject, body=text_message, to=to, **kwargs) if html_message: message.attach_alternative(html_message, 'text/html') logging.debug("to: %s", to) if 'unsubscribe' in ctx: message.extra_headers['List-Unsubscribe'] = "<{}>".format(ctx['unsubscribe']) message.extra_headers['X-MSYS-API'] = json.dumps({'options': {'transactional': True}}) try: return message.send() except SparkPostAPIException as ex: if ex.status == 1902 or not settings.FAIL_ON_EMAIL_SUPPRESSION: logging.error("Email suppression: %s", to, exc_info=ex) else: raise except (SMTPServerDisconnected, SMTPAuthenticationError) as ex: logging.error("", exc_info=ex) # Retry once return message.send()

0

e7588964b2c66c2e1a9c460176fbd519c621d0aa

1,256

py

Python

main.py

hiroyaiyori/MultiAgentQlearning

9e5161edad6b9e83995f3bb70bb159047e2dab79

[ "Apache-2.0" ]

null

main.py

hiroyaiyori/MultiAgentQlearning

9e5161edad6b9e83995f3bb70bb159047e2dab79

[ "Apache-2.0" ]

null

main.py

hiroyaiyori/MultiAgentQlearning

9e5161edad6b9e83995f3bb70bb159047e2dab79

[ "Apache-2.0" ]

null

import random import matplotlib.pyplot as plt from setting import * from field import Field from qvalue import Hunter if __name__ == "__main__": h0 = Hunter(0) h1 = Hunter(1) epi_itern_l = [] for i in range(EPISODE_N): f = Field() itern = 0 while True: fin = qlearn_step(f, h0, h1) itern += 1 if fin: break epi_itern_l.append(itern) print(i, itern) plt.plot(list(range(EPISODE_N)), epi_itern_l, linewidth=1) plt.xlabel("Number of Trials") plt.ylabel("Steps to Catch") plt.savefig("figure")

22.428571

62

0.610669

import random import matplotlib.pyplot as plt from setting import * from field import Field from qvalue import Hunter def qlearn_step(f: Field, h0: Hunter, h1: Hunter): # move hunter0 m0 = h0.decide_movement(f) pre_s0 = h0.h_recognize(f) f.move_agent(0, m0) # move hunter1 m1 = h1.decide_movement(f) pre_s1 = h1.h_recognize(f) f.move_agent(1, m1) # move target f.move_agent(2, random.randrange(0, 4)) # ask reward neighbor_hunter_n = f.catch_detection() if neighbor_hunter_n == 2: reward = CATCH_REWARD else: reward = MOVEMENT_REWARD # update q_value h0.update_qvalue(f, pre_s0, m0, reward) h1.update_qvalue(f, pre_s1, m1, reward) return neighbor_hunter_n == 2 if __name__ == "__main__": h0 = Hunter(0) h1 = Hunter(1) epi_itern_l = [] for i in range(EPISODE_N): f = Field() itern = 0 while True: fin = qlearn_step(f, h0, h1) itern += 1 if fin: break epi_itern_l.append(itern) print(i, itern) plt.plot(list(range(EPISODE_N)), epi_itern_l, linewidth=1) plt.xlabel("Number of Trials") plt.ylabel("Steps to Catch") plt.savefig("figure")

613

0

23

4dd52bce4b143c4fbffd44bc3c50266b8901f019

4,976

py

Python

rlpyt/runners/multigpu_sync.py

DilipA/rlpyt

edfd46484c56a47b4671006a16a642e6808da393

[ "MIT" ]

null

rlpyt/runners/multigpu_sync.py

DilipA/rlpyt

edfd46484c56a47b4671006a16a642e6808da393

[ "MIT" ]

null

rlpyt/runners/multigpu_sync.py

DilipA/rlpyt

edfd46484c56a47b4671006a16a642e6808da393

[ "MIT" ]

1

2020-06-23T14:13:40.000Z

import multiprocessing as mp import time import torch.distributed from rlpyt.runners.minibatch_rl import MinibatchRl from rlpyt.runners.minibatch_rl_eval import MinibatchRlEval from rlpyt.utils.seed import make_seed from rlpyt.utils.collections import AttrDict from rlpyt.utils.quick_args import save__init__args ############################################################################### # Master ############################################################################### ############################################################################### # Worker ############################################################################### # Helpers

28.434286

79

0.567725

import multiprocessing as mp import time import torch.distributed from rlpyt.runners.minibatch_rl import MinibatchRl from rlpyt.runners.minibatch_rl_eval import MinibatchRlEval from rlpyt.utils.seed import make_seed from rlpyt.utils.collections import AttrDict from rlpyt.utils.quick_args import save__init__args ############################################################################### # Master ############################################################################### class MultiGpuRlMixin(object): def startup(self): self.launch_workers() n_itr = super().startup() self.par.barrier.wait() self._start_time = self._last_time = time.time() # (Overwrite) return n_itr def launch_workers(self): self.affinities = self.affinity self.affinity = self.affinities[0] self.n_runners = n_runners = len(self.affinities) self.rank = rank = 0 self.par = par = self.build_par_objs(n_runners) if self.seed is None: self.seed = make_seed() port = find_port(offset=self.affinity.get("run_slot", 0)) workers_kwargs = [dict( algo=self.algo, agent=self.agent, sampler=self.sampler, n_steps=self.n_steps, seed=self.seed + 100 * rank, affinity=self.affinities[rank], log_interval_steps=self.log_interval_steps, rank=rank, n_runners=n_runners, port=port, par=par, ) for rank in range(1, n_runners)] workers = [self.WorkerCls(**w_kwargs) for w_kwargs in workers_kwargs] self.workers = [mp.Process(target=w.train, args=()) for w in workers] for w in self.workers: w.start() torch.distributed.init_process_group( backend="nccl", rank=rank, world_size=n_runners, init_method=f"tcp://127.0.0.1:{port}", ) def build_par_objs(self, n_runners): barrier = mp.Barrier(n_runners) traj_infos_queue = mp.Queue() mgr = mp.Manager() mgr_dict = mgr.dict() # For any other comms. par = AttrDict( barrier=barrier, traj_infos_queue=traj_infos_queue, dict=mgr_dict, ) return par class MultiGpuRl(MultiGpuRlMixin, MinibatchRl): @property def WorkerCls(self): return MultiGpuWorker def store_diagnostics(self, itr, traj_infos, opt_info): while self.par.traj_infos_queue.qsize(): traj_infos.append(self.par.traj_infos_queue.get()) super().store_diagnostics(itr, traj_infos, opt_info) class MultiGpuRlEval(MultiGpuRlMixin, MinibatchRlEval): @property def WorkerCls(self): return MultiGpuWorkerEval def log_diagnostics(self, *args, **kwargs): super().log_diagnostics(*args, **kwargs) self.par.barrier.wait() ############################################################################### # Worker ############################################################################### class MultiGpuWorkerMixin(object): def __init__( self, algo, agent, sampler, n_steps, seed, affinity, log_interval_steps, rank, n_runners, port, par, ): save__init__args(locals()) def startup(self): torch.distributed.init_process_group( backend="nccl", rank=self.rank, world_size=self.n_runners, init_method=f"tcp://127.0.0.1:{self.port}", ) n_itr = super().startup() self.par.barrier.wait() return n_itr def initialize_logging(self): pass # Don't log in workers. def shutdown(self): self.sampler.shutdown() class MultiGpuWorker(MultiGpuWorkerMixin, MinibatchRl): def store_diagnostics(self, itr, traj_infos, opt_info): for traj_info in traj_infos: self.par.traj_infos_queue.put(traj_info) # Leave worker opt_info un-recorded. def log_diagnostics(self, *args, **kwargs): pass class MultiGpuWorkerEval(MultiGpuWorkerMixin, MinibatchRlEval): def store_diagnostics(self, *args, **kwargs): pass def log_diagnostics(self, *args, **kwargs): self.par.barrier.wait() def evaluate_agent(self, *args, **kwargs): return None, None # Helpers def find_port(offset): # Find a unique open port, to stack multiple multi-GPU runs per machine. assert offset < 100 for port in range(29500 + offset, 65000, 100): try: store = torch.distributed.TCPStore("127.0.0.1", port, 1, True) break except RuntimeError: pass # Port taken. del store # Before fork (small time gap; could be re-taken, hence offset). return port

3,521

294

485

d85adc875950cf9304a2a13e89a8e00037af958b

8,324

py

Python

src/python/pants/backend/python/rules/python_test_runner.py

mpopenko-exos/pants

47d27037c8b13291fc9023e56ddd1b1defdf1b8e

[ "Apache-2.0" ]

null

src/python/pants/backend/python/rules/python_test_runner.py

mpopenko-exos/pants

47d27037c8b13291fc9023e56ddd1b1defdf1b8e

[ "Apache-2.0" ]

1

2018-09-04T17:37:34.000Z

2018-09-04T19:42:58.000Z

src/python/pants/backend/python/rules/python_test_runner.py

mpopenko-exos/pants

47d27037c8b13291fc9023e56ddd1b1defdf1b8e

[ "Apache-2.0" ]

null

# Copyright 2018 Pants project contributors (see CONTRIBUTORS.md). # Licensed under the Apache License, Version 2.0 (see LICENSE). import os from dataclasses import dataclass from textwrap import dedent from typing import Optional, Tuple from pants.backend.python.rules.pex import Pex from pants.backend.python.rules.pex_from_target_closure import CreatePexFromTargetClosure from pants.backend.python.rules.prepare_chrooted_python_sources import ChrootedPythonSources from pants.backend.python.subsystems.pytest import PyTest from pants.backend.python.subsystems.python_setup import PythonSetup from pants.backend.python.subsystems.subprocess_environment import SubprocessEncodingEnvironment from pants.build_graph.address import Address from pants.engine.addressable import BuildFileAddresses from pants.engine.fs import Digest, DirectoriesToMerge, FileContent, InputFilesContent from pants.engine.interactive_runner import InteractiveProcessRequest from pants.engine.isolated_process import ExecuteProcessRequest, FallibleExecuteProcessResult from pants.engine.legacy.graph import HydratedTargets, TransitiveHydratedTargets from pants.engine.legacy.structs import PythonTestsAdaptor from pants.engine.rules import UnionRule, rule, subsystem_rule from pants.engine.selectors import Get from pants.option.global_options import GlobalOptions from pants.rules.core.strip_source_root import SourceRootStrippedSources from pants.rules.core.test import TestDebugRequest, TestOptions, TestResult, TestTarget DEFAULT_COVERAGE_CONFIG = dedent(f""" [run] branch = True timid = False relative_files = True """) def calculate_timeout_seconds( *, timeouts_enabled: bool, target_timeout: Optional[int], timeout_default: Optional[int], timeout_maximum: Optional[int], ) -> Optional[int]: """Calculate the timeout for a test target. If a target has no timeout configured its timeout will be set to the default timeout. """ if not timeouts_enabled: return None if target_timeout is None: if timeout_default is None: return None target_timeout = timeout_default if timeout_maximum is not None: return min(target_timeout, timeout_maximum) return target_timeout @dataclass(frozen=True) @rule @rule(name="Run pytest") async def run_python_test( test_target: PythonTestsAdaptor, test_setup: TestTargetSetup, python_setup: PythonSetup, subprocess_encoding_environment: SubprocessEncodingEnvironment, global_options: GlobalOptions, test_options: TestOptions, ) -> TestResult: """Runs pytest for one target.""" colors = global_options.colors env = {"PYTEST_ADDOPTS": f"--color={'yes' if colors else 'no'}"} request = test_setup.requirements_pex.create_execute_request( python_setup=python_setup, subprocess_encoding_environment=subprocess_encoding_environment, pex_path=f'./{test_setup.requirements_pex.output_filename}', pex_args=test_setup.args, input_files=test_setup.input_files_digest, output_directories=('.coverage',) if test_options.values.run_coverage else None, description=f'Run Pytest for {test_target.address.reference()}', timeout_seconds=test_setup.timeout_seconds if test_setup.timeout_seconds is not None else 9999, env=env, ) result = await Get[FallibleExecuteProcessResult](ExecuteProcessRequest, request) return TestResult.from_fallible_execute_process_result(result) @rule(name="Run pytest in an interactive process")

38.359447

117

0.780995

# Copyright 2018 Pants project contributors (see CONTRIBUTORS.md). # Licensed under the Apache License, Version 2.0 (see LICENSE). import os from dataclasses import dataclass from textwrap import dedent from typing import Optional, Tuple from pants.backend.python.rules.pex import Pex from pants.backend.python.rules.pex_from_target_closure import CreatePexFromTargetClosure from pants.backend.python.rules.prepare_chrooted_python_sources import ChrootedPythonSources from pants.backend.python.subsystems.pytest import PyTest from pants.backend.python.subsystems.python_setup import PythonSetup from pants.backend.python.subsystems.subprocess_environment import SubprocessEncodingEnvironment from pants.build_graph.address import Address from pants.engine.addressable import BuildFileAddresses from pants.engine.fs import Digest, DirectoriesToMerge, FileContent, InputFilesContent from pants.engine.interactive_runner import InteractiveProcessRequest from pants.engine.isolated_process import ExecuteProcessRequest, FallibleExecuteProcessResult from pants.engine.legacy.graph import HydratedTargets, TransitiveHydratedTargets from pants.engine.legacy.structs import PythonTestsAdaptor from pants.engine.rules import UnionRule, rule, subsystem_rule from pants.engine.selectors import Get from pants.option.global_options import GlobalOptions from pants.rules.core.strip_source_root import SourceRootStrippedSources from pants.rules.core.test import TestDebugRequest, TestOptions, TestResult, TestTarget DEFAULT_COVERAGE_CONFIG = dedent(f""" [run] branch = True timid = False relative_files = True """) def get_coveragerc_input(coveragerc_content: str) -> InputFilesContent: return InputFilesContent( [ FileContent( path='.coveragerc', content=coveragerc_content.encode(), is_executable=False, ), ] ) def calculate_timeout_seconds( *, timeouts_enabled: bool, target_timeout: Optional[int], timeout_default: Optional[int], timeout_maximum: Optional[int], ) -> Optional[int]: """Calculate the timeout for a test target. If a target has no timeout configured its timeout will be set to the default timeout. """ if not timeouts_enabled: return None if target_timeout is None: if timeout_default is None: return None target_timeout = timeout_default if timeout_maximum is not None: return min(target_timeout, timeout_maximum) return target_timeout @dataclass(frozen=True) class TestTargetSetup: requirements_pex: Pex args: Tuple[str, ...] input_files_digest: Digest timeout_seconds: Optional[int] # Prevent this class from being detected by pytest as a test class. __test__ = False def get_packages_to_cover( test_target: PythonTestsAdaptor, source_root_stripped_file_paths: Tuple[str, ...], ) -> Tuple[str, ...]: if hasattr(test_target, 'coverage'): return tuple(sorted(set(test_target.coverage))) return tuple(sorted({ os.path.dirname(source_root_stripped_source_file_path).replace(os.sep, '.') # Turn file paths into package names. for source_root_stripped_source_file_path in source_root_stripped_file_paths })) @rule async def setup_pytest_for_target( test_target: PythonTestsAdaptor, pytest: PyTest, test_options: TestOptions, ) -> TestTargetSetup: # TODO: Rather than consuming the TestOptions subsystem, the TestRunner should pass on coverage # configuration via #7490. transitive_hydrated_targets = await Get[TransitiveHydratedTargets]( BuildFileAddresses((test_target.address,)) ) all_targets = transitive_hydrated_targets.closure resolved_requirements_pex = await Get[Pex]( CreatePexFromTargetClosure( build_file_addresses=BuildFileAddresses((test_target.address,)), output_filename='pytest-with-requirements.pex', entry_point="pytest:main", additional_requirements=pytest.get_requirement_strings(), # NB: We set `--not-zip-safe` because Pytest plugin discovery, which uses # `importlib_metadata` and thus `zipp`, does not play nicely when doing import magic directly # from zip files. `zipp` has pathologically bad behavior with large zipfiles. # TODO: this does have a performance cost as the pex must now be expanded to disk. Long term, # it would be better to fix Zipp (whose fix would then need to be used by importlib_metadata # and then by Pytest). See https://github.com/jaraco/zipp/pull/26. additional_args=("--not-zip-safe",), include_source_files=False, ) ) chrooted_sources = await Get[ChrootedPythonSources](HydratedTargets(all_targets)) directories_to_merge = [ chrooted_sources.digest, resolved_requirements_pex.directory_digest, ] # Get the file names for the test_target, adjusted for the source root. This allows us to # specify to Pytest which files to test and thus to avoid the test auto-discovery defined by # https://pytest.org/en/latest/goodpractices.html#test-discovery. In addition to a performance # optimization, this ensures that any transitive sources, such as a test project file named # test_fail.py, do not unintentionally end up being run as tests. source_root_stripped_test_target_sources = await Get[SourceRootStrippedSources]( Address, test_target.address.to_address() ) coverage_args = [] test_target_sources_file_names = source_root_stripped_test_target_sources.snapshot.files if test_options.values.run_coverage: coveragerc_digest = await Get[Digest](InputFilesContent, get_coveragerc_input(DEFAULT_COVERAGE_CONFIG)) directories_to_merge.append(coveragerc_digest) packages_to_cover = get_packages_to_cover( test_target, source_root_stripped_file_paths=test_target_sources_file_names, ) coverage_args = [ '--cov-report=', # To not generate any output. https://pytest-cov.readthedocs.io/en/latest/config.html ] for package in packages_to_cover: coverage_args.extend(['--cov', package]) merged_input_files = await Get[Digest](DirectoriesToMerge(directories=tuple(directories_to_merge))) timeout_seconds = calculate_timeout_seconds( timeouts_enabled=pytest.options.timeouts, target_timeout=getattr(test_target, 'timeout', None), timeout_default=pytest.options.timeout_default, timeout_maximum=pytest.options.timeout_maximum, ) return TestTargetSetup( requirements_pex=resolved_requirements_pex, args=(*pytest.options.args, *coverage_args, *sorted(test_target_sources_file_names)), input_files_digest=merged_input_files, timeout_seconds=timeout_seconds, ) @rule(name="Run pytest") async def run_python_test( test_target: PythonTestsAdaptor, test_setup: TestTargetSetup, python_setup: PythonSetup, subprocess_encoding_environment: SubprocessEncodingEnvironment, global_options: GlobalOptions, test_options: TestOptions, ) -> TestResult: """Runs pytest for one target.""" colors = global_options.colors env = {"PYTEST_ADDOPTS": f"--color={'yes' if colors else 'no'}"} request = test_setup.requirements_pex.create_execute_request( python_setup=python_setup, subprocess_encoding_environment=subprocess_encoding_environment, pex_path=f'./{test_setup.requirements_pex.output_filename}', pex_args=test_setup.args, input_files=test_setup.input_files_digest, output_directories=('.coverage',) if test_options.values.run_coverage else None, description=f'Run Pytest for {test_target.address.reference()}', timeout_seconds=test_setup.timeout_seconds if test_setup.timeout_seconds is not None else 9999, env=env, ) result = await Get[FallibleExecuteProcessResult](ExecuteProcessRequest, request) return TestResult.from_fallible_execute_process_result(result) @rule(name="Run pytest in an interactive process") async def debug_python_test(test_setup: TestTargetSetup) -> TestDebugRequest: run_request = InteractiveProcessRequest( argv=(test_setup.requirements_pex.output_filename, *test_setup.args), run_in_workspace=False, input_files=test_setup.input_files_digest ) return TestDebugRequest(run_request) def rules(): return [ run_python_test, debug_python_test, setup_pytest_for_target, UnionRule(TestTarget, PythonTestsAdaptor), subsystem_rule(PyTest), subsystem_rule(PythonSetup), ]

4,537

201

135

c133beede45af5e543c1fe1ec193fd97ed55895f

479

py

Python

tests/utils/string_test.py

medecau/sciencebeam-utils

0253139f17c4208ccacdedf6d2c4eb2b062b7721

[ "MIT" ]

2

2019-07-17T14:53:07.000Z

2021-09-15T04:47:47.000Z

tests/utils/string_test.py

medecau/sciencebeam-utils

0253139f17c4208ccacdedf6d2c4eb2b062b7721

[ "MIT" ]

108

2018-07-24T15:20:54.000Z

2022-03-28T16:57:39.000Z

tests/utils/string_test.py

medecau/sciencebeam-utils

0253139f17c4208ccacdedf6d2c4eb2b062b7721

[ "MIT" ]

2

2020-02-07T10:58:48.000Z

2021-09-01T10:15:32.000Z

from sciencebeam_utils.utils.string import ( parse_list )

26.611111

61

0.670146

from sciencebeam_utils.utils.string import ( parse_list ) class TestParseList: def test_should_return_empty_list_for_empty_string(self): assert parse_list('') == [] def test_should_return_single_item(self): assert parse_list('abc') == ['abc'] def test_should_return_multiple_items(self): assert parse_list('abc,def') == ['abc', 'def'] def test_should_ignore_space(self): assert parse_list(' abc , def ') == ['abc', 'def']

287

-1

130

ac0722f5355939a163b27b591dc7ab3e9e9bd82a

817

py

Python

blog_config.py

misalabs/misalabs.com

f2c95f124f01a718c5bf9331457d75bae0e892bd

[ "MIT" ]

null

blog_config.py

misalabs/misalabs.com

f2c95f124f01a718c5bf9331457d75bae0e892bd

[ "MIT" ]

null

blog_config.py

misalabs/misalabs.com

f2c95f124f01a718c5bf9331457d75bae0e892bd

[ "MIT" ]

null

# coding: utf-8 -*- # TITLE / SUBTITLE / AUTHOR # The title, subtitle, and author of the blog TITLE = "Misa Montes" SUBTITLE = "blog" AUTHOR = "Misa" METADATA_TAGS = ['title', 'author'] # POSTS_PER_PAGE # The number of posts that will appear on each page of index.html POSTS_PER_PAGE = 3 # SUMMARY_DELIMITOR # Used to specify a breaking point from the beginning of the document to the # end of the summary. SUMMARY_DELIMITER = "~~" # USE_HEROKU # Toggled as True/False if the system will or will not be deployed as a Heroku # app, respectively. USE_HEROKU = True # DISQUS_SHORTNAME # Disqus is a free system used to manage comments at the bottom of blog posts. # After signing up, you will be issued a shortname -- put it here. By default # developer mode of the script is enabled. DISQUS_SHORTNAME = "misalabs"

29.178571

78

0.740514

# coding: utf-8 -*- # TITLE / SUBTITLE / AUTHOR # The title, subtitle, and author of the blog TITLE = "Misa Montes" SUBTITLE = "blog" AUTHOR = "Misa" METADATA_TAGS = ['title', 'author'] # POSTS_PER_PAGE # The number of posts that will appear on each page of index.html POSTS_PER_PAGE = 3 # SUMMARY_DELIMITOR # Used to specify a breaking point from the beginning of the document to the # end of the summary. SUMMARY_DELIMITER = "~~" # USE_HEROKU # Toggled as True/False if the system will or will not be deployed as a Heroku # app, respectively. USE_HEROKU = True # DISQUS_SHORTNAME # Disqus is a free system used to manage comments at the bottom of blog posts. # After signing up, you will be issued a shortname -- put it here. By default # developer mode of the script is enabled. DISQUS_SHORTNAME = "misalabs"

0

ee0f794b0f5448c23e5ed4a42cf4a22fac9055fd

509

py

Python

tAPP/2/P2.py

ArvinZJC/UofG_PGT_PSD_Python

d90e9bb0b53b14c6b1d7e657c3c61e2792e0d9c4

[ "MIT" ]

null

tAPP/2/P2.py

ArvinZJC/UofG_PGT_PSD_Python

d90e9bb0b53b14c6b1d7e657c3c61e2792e0d9c4

[ "MIT" ]

null

tAPP/2/P2.py

ArvinZJC/UofG_PGT_PSD_Python

d90e9bb0b53b14c6b1d7e657c3c61e2792e0d9c4

[ "MIT" ]

null

''' Description: Problem 2 (rearrange the code) Version: 1.0.2.20210118 Author: Arvin Zhao Date: 2021-01-14 22:35:43 Last Editors: Arvin Zhao LastEditTime: 2021-01-18 18:11:03 ''' line = input('Enter a string: ') i = 0 is_palindrome = True while i < len(line) / 2 and is_palindrome: if line[i] != line[len(line) - i - 1]: is_palindrome = False else: is_palindrome = True i += 1 if is_palindrome: print(line, 'is a palindrome.') else: print(line, 'is not a palindrome.')

20.36

43

0.646365

''' Description: Problem 2 (rearrange the code) Version: 1.0.2.20210118 Author: Arvin Zhao Date: 2021-01-14 22:35:43 Last Editors: Arvin Zhao LastEditTime: 2021-01-18 18:11:03 ''' line = input('Enter a string: ') i = 0 is_palindrome = True while i < len(line) / 2 and is_palindrome: if line[i] != line[len(line) - i - 1]: is_palindrome = False else: is_palindrome = True i += 1 if is_palindrome: print(line, 'is a palindrome.') else: print(line, 'is not a palindrome.')

0

ed9616c041b5bba086b27dc907c55bb00c486b21

1,762

py

Python

classes/buildings.py

AlbatrosCZ/RP-bot

f605550ebb9009a9846048da645db91e385d4f35

[ "MIT" ]

null

classes/buildings.py

AlbatrosCZ/RP-bot

f605550ebb9009a9846048da645db91e385d4f35

[ "MIT" ]

null

classes/buildings.py

AlbatrosCZ/RP-bot

f605550ebb9009a9846048da645db91e385d4f35

[ "MIT" ]

null

""" name - jméno pozition - pozice (x, y) can_train - čísla pro trening jednotky (integer) - pokud je má jednotka alespoň jedno z těchto čísel může budova trénovat tuto jednotku (čím víc společných čísel tím kratší doba tréningu) defend_power - sílá obrany integer - 0 neučastní se obrany lifes - počet životů (integer, integer) - aktuálně, maximalně | 0 v maximalně zničení při zničení města, -1 v maximalně zničení při útoku na město, ostantí kladná čísla v maximalně zničení při dosažení 0 income - vydělá za čas (integer, integer, integer) - vydělá, za, posledně """ from time import time

46.368421

247

0.536322

""" name - jméno pozition - pozice (x, y) can_train - čísla pro trening jednotky (integer) - pokud je má jednotka alespoň jedno z těchto čísel může budova trénovat tuto jednotku (čím víc společných čísel tím kratší doba tréningu) defend_power - sílá obrany integer - 0 neučastní se obrany lifes - počet životů (integer, integer) - aktuálně, maximalně | 0 v maximalně zničení při zničení města, -1 v maximalně zničení při útoku na město, ostantí kladná čísla v maximalně zničení při dosažení 0 income - vydělá za čas (integer, integer, integer) - vydělá, za, posledně """ from time import time class building: def __init__(self, name, can_train, defend_power = 0, lifes = [0, 0], income = [0, 0, time()], pozition = "Tamplate"): self.name = name self.can_train = can_train self.defend_power = defend_power self.lifes = lifes self.income = income def get_income(self): if not self.income[0]: return 0 if time() - self.income[2] >= self.income[1]: self.income[2] = time() return self.income[0] return 0 def defend(self): if self.lifes == [-1, -1]: return "destroy" elif self.lifes == [0, 0]: if not self.defend_power: return "no_defend" else: return [self.defend_power, self.lifes] else: if not self.defend_power: return [0, self.lifes] else: return [self.defend_power, self.lifes]

852

-6

102

0dfa8249c34d3a763ad92b788a6d4f1a0321b4b8

1,870

py

Python

Labs/Lab10/lab10a.py

tonysulfaro/CSE-231

0e3ff5422fe42624a90a17d7f33174346662a6fc

[ "MIT" ]

2

2021-09-23T19:17:24.000Z

2021-11-29T09:03:56.000Z

Labs/Lab10/lab10a.py

tonysulfaro/CSE-231

0e3ff5422fe42624a90a17d7f33174346662a6fc

[ "MIT" ]

null

Labs/Lab10/lab10a.py

tonysulfaro/CSE-231

0e3ff5422fe42624a90a17d7f33174346662a6fc

[ "MIT" ]

1

2020-10-25T13:03:18.000Z

## ## Demonstrate some of the operations of the Deck and Card classes ## import cards # Seed the random number generator to a specific value so every execution # of the program uses the same sequence of random numbers (for testing). import random random.seed( 100 ) # Create a deck of cards my_deck = cards.Deck() # Shuffle the deck, then display it in 13 columns my_deck.shuffle() print( "===== shuffled deck =====" ) my_deck.display() # Deal five cards to each player (alternating) print( "Dealt five cards to each player (alternating)" ) print() player1_list=[] player2_list=[] for i in range( 5 ): player1_list.append( my_deck.deal() ) player2_list.append( my_deck.deal() ) # Display each player's cards and the cards still in the deck print( "===== player #1 =====" ) print() print( player1_list ) print() print( "===== player #2 =====" ) print() print( player2_list ) print() print( "===== remaining cards in deck =====" ) my_deck.display() hand(0,'First') hand(0,'Second') hand(-1,'Last')

24.285714

85

0.665775

## ## Demonstrate some of the operations of the Deck and Card classes ## import cards # Seed the random number generator to a specific value so every execution # of the program uses the same sequence of random numbers (for testing). import random random.seed( 100 ) # Create a deck of cards my_deck = cards.Deck() # Shuffle the deck, then display it in 13 columns my_deck.shuffle() print( "===== shuffled deck =====" ) my_deck.display() # Deal five cards to each player (alternating) print( "Dealt five cards to each player (alternating)" ) print() player1_list=[] player2_list=[] for i in range( 5 ): player1_list.append( my_deck.deal() ) player2_list.append( my_deck.deal() ) # Display each player's cards and the cards still in the deck print( "===== player #1 =====" ) print() print( player1_list ) print() print( "===== player #2 =====" ) print() print( player2_list ) print() print( "===== remaining cards in deck =====" ) my_deck.display() def hand(index, hand_name): # First card dealt to Player #1 print("\n") player1_card = player1_list.pop( index ) print(hand_name, " card dealt to player #1:", player1_card ) print("Player #1 hand", player1_list) # First card dealt to Player #2 print() player2_card = player2_list.pop( index ) print(hand_name, "card dealt to player #2:", player2_card ) print("Player #2 hand", player2_list) # Compare the ranks of the two cards print() if player1_card.rank() == player2_card.rank(): print( "Tie:", player1_card, "and", player2_card, "of equal rank" ) elif player1_card.rank() > player2_card.rank(): print( "Player #1 wins:", player1_card, "of higher rank than", player2_card ) else: print( "Player #2 wins:", player2_card, "of higher rank than", player1_card ) hand(0,'First') hand(0,'Second') hand(-1,'Last')

829

0

23

bb993e3d8ef9c6f08b033e56942c9442d4a223c0

4,886

py

Python

src/ur_online_control/ur_direct/structure.py

createchaos/ur_online_control_2

22b0ec6b7ffa2c74b55dd214e7b854bec9922ccb

[ "MIT" ]

null

src/ur_online_control/ur_direct/structure.py

createchaos/ur_online_control_2

22b0ec6b7ffa2c74b55dd214e7b854bec9922ccb

[ "MIT" ]

null

src/ur_online_control/ur_direct/structure.py

createchaos/ur_online_control_2

22b0ec6b7ffa2c74b55dd214e7b854bec9922ccb

[ "MIT" ]

null

from __future__ import absolute_import import os import socket from ur_online_control.ur_direct.mixins.airpick_mixins import AirpickMixins __all__ = [ 'URCommandScript' ] class URCommandScript(AirpickMixins): """Class containing commands for the UR Robot system""" def start(self): """To build the start of the script""" self.add_lines(["def program():", "\ttextmsg(\">> Entering program.\")", "\t# open line for airpick commands"]) def end(self, feedback=None): """To build the end of the script""" if feedback: self.socket_send_line('"Done"') self.add_lines(["\ttextmsg(\"<< Exiting program.\")", "end", "program()\n\n\n"]) def generate(self): """Translate the dictionary to a long string""" self.script = '\n'.join(self.commands_dict.values()) return self.script # Dictionary building def add_line(self, line, i=None): """Add a single line to the script""" if i is None: i = len(self.commands_dict) else: pass self.commands_dict[i] = line def add_lines(self, lines): """Add a multiple lines to the script""" i = len(self.commands_dict) [self.add_line(line, i+line_nr) for (line_nr, line) in zip(range(len(lines)), lines)] # Feedback functionality def get_current_pose_cartesian(self, send=False): """Get the current cartesian pose""" self.get_current_pose("cartesian", send) def get_current_pose_joints(self, send=False): """Get the current joints pose""" self.get_current_pose("joints", send) def get_current_pose(self, get_type, send): """Create get pose code""" pose_type = { "cartesian": "get_forward_kin()", "joints": "get_actual_joint_positions()" } self.add_lines(["\tcurrent_pose = {}".format(pose_type[get_type]), "\ttextmsg(current_pose)"]) if send: self.socket_send_line('current_pose') #self.add_line("\ttextmsg('sending done')") # Connectivity def is_available(self): """Ping the network, to check for availability""" system_call = "ping -r 1 -n 1 {}".format(self.ur_ip) response = os.system(system_call) if response == 0: return True else: return False # Geometric effects def set_tcp(self, tcp): """Set the tcp""" #tcp = [tcp[i]/1000 if i < 3 else tcp[i] for i in range(len(tcp))] tcp = [tcp[i] for i in range(len(tcp))] self.add_line("\tset_tcp(p{})".format(tcp)) def add_move_linear(self, move_command, feedback=None): """Add a move command to the script""" #move = [cmd / 1000 if c not in [3, 4, 5] else cmd for c, cmd in zip(range(len(move_command)), move_command)] move = [cmd for c, cmd in zip(range(len(move_command)), move_command)] [x, y, z, dx, dy, dz, v, r] = move self.add_line("\tmovel(p[{}, {}, {}, {}, {}, {}], v={}, r={})".format(x, y, z, dx, dy, dz, v, r)) if feedback == "Full": self.get_current_pose_cartesian(True) elif feedback == "UR_only": self.get_current_pose_cartesian(False) else: pass

35.926471

117

0.575931

from __future__ import absolute_import import os import socket from ur_online_control.ur_direct.mixins.airpick_mixins import AirpickMixins __all__ = [ 'URCommandScript' ] class URCommandScript(AirpickMixins): """Class containing commands for the UR Robot system""" def __init__(self, server_ip=None, server_port=None, ur_ip=None, ur_port=None): self.commands_dict = {} self.server_ip = server_ip self.server_port = server_port self.ur_ip = ur_ip self.ur_port = ur_port self.script = None self.exit_message = "Done" # Functionality def start(self): """To build the start of the script""" self.add_lines(["def program():", "\ttextmsg(\">> Entering program.\")", "\t# open line for airpick commands"]) def end(self, feedback=None): """To build the end of the script""" if feedback: self.socket_send_line('"Done"') self.add_lines(["\ttextmsg(\"<< Exiting program.\")", "end", "program()\n\n\n"]) def generate(self): """Translate the dictionary to a long string""" self.script = '\n'.join(self.commands_dict.values()) return self.script def socket_send_line(self, line): self.add_lines(['\tsocket_open("{}", {})'.format(self.server_ip, self.server_port), '\tsocket_send_line({})'.format(line), "\tsocket_close()"]) # Dictionary building def add_line(self, line, i=None): """Add a single line to the script""" if i is None: i = len(self.commands_dict) else: pass self.commands_dict[i] = line def add_lines(self, lines): """Add a multiple lines to the script""" i = len(self.commands_dict) [self.add_line(line, i+line_nr) for (line_nr, line) in zip(range(len(lines)), lines)] # Feedback functionality def get_current_pose_cartesian(self, send=False): """Get the current cartesian pose""" self.get_current_pose("cartesian", send) def get_current_pose_joints(self, send=False): """Get the current joints pose""" self.get_current_pose("joints", send) def get_current_pose(self, get_type, send): """Create get pose code""" pose_type = { "cartesian": "get_forward_kin()", "joints": "get_actual_joint_positions()" } self.add_lines(["\tcurrent_pose = {}".format(pose_type[get_type]), "\ttextmsg(current_pose)"]) if send: self.socket_send_line('current_pose') #self.add_line("\ttextmsg('sending done')") # Connectivity def is_available(self): """Ping the network, to check for availability""" system_call = "ping -r 1 -n 1 {}".format(self.ur_ip) response = os.system(system_call) if response == 0: return True else: return False def send_script(self): try: s = socket.create_connection((self.ur_ip, self.ur_port), timeout=2) except socket.timeout: print("UR with ip {} not available on port {}".format(self.ur_ip, self.ur_port)) raise finally: enc_script = self.script.encode('utf-8') # encoding allows use of python 3.7 s.send(enc_script) print("Script sent to {} on port {}".format(self.ur_ip, self.ur_port)) s.close() # Geometric effects def set_tcp(self, tcp): """Set the tcp""" #tcp = [tcp[i]/1000 if i < 3 else tcp[i] for i in range(len(tcp))] tcp = [tcp[i] for i in range(len(tcp))] self.add_line("\tset_tcp(p{})".format(tcp)) def add_move_linear(self, move_command, feedback=None): """Add a move command to the script""" #move = [cmd / 1000 if c not in [3, 4, 5] else cmd for c, cmd in zip(range(len(move_command)), move_command)] move = [cmd for c, cmd in zip(range(len(move_command)), move_command)] [x, y, z, dx, dy, dz, v, r] = move self.add_line("\tmovel(p[{}, {}, {}, {}, {}, {}], v={}, r={})".format(x, y, z, dx, dy, dz, v, r)) if feedback == "Full": self.get_current_pose_cartesian(True) elif feedback == "UR_only": self.get_current_pose_cartesian(False) else: pass def add_digital_out(self, number, value): self.add_line("\tset_digital_out({}, {})".format(number, value)) def add_areagrip_on(self, sleep = 1.): self.add_digital_out(7, True) self.add_line("\tsleep({})".format(sleep)) def add_areagrip_off(self, sleep = 0.1): self.add_digital_out(7, False) self.add_line("\tsleep({})".format(sleep))

1,308

0

161

728f3b3c609ce6bb2af3cd08ab99688368ec0879

1,168

py

Python

genemunge/data/cleanup.py

unlearnai/genemunge

a7dc07706ae2bf487a04fcda5623013c055030a3

[ "CC-BY-4.0" ]

21

2018-04-06T17:03:52.000Z

2020-06-29T12:56:43.000Z

genemunge/data/cleanup.py

unlearnai/genemunge

a7dc07706ae2bf487a04fcda5623013c055030a3

[ "CC-BY-4.0" ]

5

2018-04-10T19:32:33.000Z

2018-07-17T18:07:48.000Z

genemunge/data/cleanup.py

unlearnai/genemunge

a7dc07706ae2bf487a04fcda5623013c055030a3

[ "CC-BY-4.0" ]

5

2018-04-11T05:42:52.000Z

2019-04-02T03:43:52.000Z

import os import contextlib filepath = os.path.dirname(os.path.abspath(__file__)) def remove_installed_data_files(): """ Removes some of the files that are downloaded during install. Args: None Returns: None """ # remove the GO file with contextlib.suppress(FileNotFoundError): os.remove(os.path.join(filepath, 'go-basic.obo')) # remove the GO annotations with contextlib.suppress(FileNotFoundError): os.remove(os.path.join(filepath, 'goa_human.gaf.gz')) # remove the housekeeping genes file with contextlib.suppress(FileNotFoundError): os.remove(os.path.join(filepath, 'HK_genes.txt')) # remove the transcription factors genes file with contextlib.suppress(FileNotFoundError): os.remove(os.path.join(filepath, 'TFCheckpoint_download_180515.txt')) # remove the GTEx Rdata file with contextlib.suppress(FileNotFoundError): os.remove(os.path.join(filepath, 'gtex', 'rse_gene.Rdata')) # remove the GTEx expression file with contextlib.suppress(FileNotFoundError): os.remove(os.path.join(filepath, 'gtex', 'expression_data.csv'))

29.2

77

0.697774

import os import contextlib filepath = os.path.dirname(os.path.abspath(__file__)) def remove_installed_data_files(): """ Removes some of the files that are downloaded during install. Args: None Returns: None """ # remove the GO file with contextlib.suppress(FileNotFoundError): os.remove(os.path.join(filepath, 'go-basic.obo')) # remove the GO annotations with contextlib.suppress(FileNotFoundError): os.remove(os.path.join(filepath, 'goa_human.gaf.gz')) # remove the housekeeping genes file with contextlib.suppress(FileNotFoundError): os.remove(os.path.join(filepath, 'HK_genes.txt')) # remove the transcription factors genes file with contextlib.suppress(FileNotFoundError): os.remove(os.path.join(filepath, 'TFCheckpoint_download_180515.txt')) # remove the GTEx Rdata file with contextlib.suppress(FileNotFoundError): os.remove(os.path.join(filepath, 'gtex', 'rse_gene.Rdata')) # remove the GTEx expression file with contextlib.suppress(FileNotFoundError): os.remove(os.path.join(filepath, 'gtex', 'expression_data.csv'))

0

cbc363039e6a67e61d37d79f26466d4524013356

42

py

Python

test/integration/ElseIfStart/else if start.py

HighSchoolHacking/GLS-Draft

9e418b6290e7c8e3f2da87668784bdba1cde5a76

[ "MIT" ]

30

2019-10-29T12:47:50.000Z

2022-02-12T06:41:39.000Z

test/integration/ElseIfStart/else if start.py

HighSchoolHacking/GLS-Draft

9e418b6290e7c8e3f2da87668784bdba1cde5a76

[ "MIT" ]

247

2017-09-21T17:11:18.000Z

2019-10-08T12:59:07.000Z

test/integration/ElseIfStart/else if start.py

HighSchoolHacking/GLS-Draft

9e418b6290e7c8e3f2da87668784bdba1cde5a76

[ "MIT" ]

17

2017-10-01T16:53:20.000Z

2018-11-28T07:20:35.000Z

# if aaa: # ... elif bbb: # ... #

6

9

0.285714

# if aaa: # ... elif bbb: # ... #

0

8a6089511fc4904952eb4fa9eb272cd7236b50fa

6,550

py

Python

model/videoQA.py

MikeWangWZHL/StarterCode

e271c5dff2d9c4344c2fecd81bb0b5dfe2749cf2

[ "MIT" ]

63

2021-06-07T18:16:55.000Z

2022-03-29T09:41:05.000Z

model/videoQA.py

MikeWangWZHL/StarterCode

e271c5dff2d9c4344c2fecd81bb0b5dfe2749cf2

[ "MIT" ]

16

2021-07-08T07:42:28.000Z

2022-01-14T06:40:57.000Z

model/videoQA.py

MikeWangWZHL/StarterCode

e271c5dff2d9c4344c2fecd81bb0b5dfe2749cf2

[ "MIT" ]

5

2021-07-19T08:23:45.000Z

2022-02-02T02:49:48.000Z

""" Copyright (c) Microsoft Corporation. Licensed under the MIT license. HERO for Video Question Answering Tasks, shared by: 1. TVQA 2. How2QA 3. VLEP 4. VIOLIN copied/modified from HERO (https://github.com/linjieli222/HERO) """ from collections import defaultdict import copy import torch from torch import nn from torch.nn import functional as F from .model import HeroModel from .layers import MLPLayer from .modeling_utils import mask_logits

41.455696

81

0.563206

""" Copyright (c) Microsoft Corporation. Licensed under the MIT license. HERO for Video Question Answering Tasks, shared by: 1. TVQA 2. How2QA 3. VLEP 4. VIOLIN copied/modified from HERO (https://github.com/linjieli222/HERO) """ from collections import defaultdict import copy import torch from torch import nn from torch.nn import functional as F from .model import HeroModel from .layers import MLPLayer from .modeling_utils import mask_logits class HeroForVideoQA(HeroModel): def __init__(self, config, vfeat_dim, max_frm_seq_len): HeroModel.__init__( self, config, vfeat_dim, max_frm_seq_len) hsz = config.c_config.hidden_size self.qa_pool = nn.Linear( in_features=hsz, out_features=1, bias=False) self.qa_pred_head = MLPLayer(hsz, 1) # in tvqa/how2qa, we also have annotations for st and ed frame idx self.st_ed_pool = copy.deepcopy(self.qa_pool) self.st_ed_pred_head = MLPLayer(hsz, 2) def get_modularized_video( self, frame_embeddings, frame_mask, violin=False): """ Args: frame_embeddings: (Nv, Nq, L, D) frame_mask: (Nv, Nq, L) """ if not violin: st_ed_attn_scores = self.st_ed_pool( frame_embeddings) # (Nv, Nq, L, 1) qa_attn_scores = self.qa_pool(frame_embeddings) st_ed_attn_scores = F.softmax( mask_logits(st_ed_attn_scores, frame_mask.unsqueeze(-1)), dim=1) qa_attn_scores = F.softmax( mask_logits(qa_attn_scores, frame_mask.unsqueeze(-1)), dim=2) # TODO check whether it is the same st_ed_pooled_video = torch.einsum( "vqlm,vqld->vlmd", st_ed_attn_scores, frame_embeddings) # (Nv, L, 1, D) qa_pooled_video = torch.einsum( "vqlm,vqld->vqmd", qa_attn_scores, frame_embeddings) # (Nv, Nq, 1, D) return st_ed_pooled_video.squeeze(2), qa_pooled_video.squeeze(2) else: violin_attn_scores = self.qa_pool( frame_embeddings) # (Nv, L, 1) violin_attn_scores = F.softmax( mask_logits(violin_attn_scores, frame_mask.unsqueeze(-1)), dim=1) # TODO check whether it is the same violin_pooled_video = torch.einsum( "vlm,vld->vmd", violin_attn_scores, frame_embeddings) # (Nv, 1, D) return violin_pooled_video.squeeze(1) def forward(self, batch, task='videoQA', compute_loss=True): batch = defaultdict(lambda: None, batch) if task == "videoQA" or task == "violin": targets = batch['targets'].squeeze(-1) c_attn_masks = batch["c_attn_masks"] # (num_video * 5, num_frames, hid_size) v_encoder_output = self.v_encoder.forward_repr( batch, encode_clip=False) if isinstance(v_encoder_output, tuple): frame_embeddings, c_attn_masks = v_encoder_output else: frame_embeddings = v_encoder_output if self.v_encoder.c_encoder is not None: frame_embeddings = self.v_encoder.c_encoder.embeddings( frame_embeddings, position_ids=None) qa_embeddings = self.v_encoder.f_encoder._compute_txt_embeddings( batch["qa_input_ids"], batch["qa_pos_ids"], txt_type_ids=None) frame_qa_embeddings = torch.cat( (frame_embeddings, qa_embeddings), dim=1) frame_qa_attn_mask = torch.cat( (c_attn_masks, batch["qa_attn_masks"]), dim=1) fused_video_qa = self.v_encoder.c_encoder.forward_encoder( frame_qa_embeddings, frame_qa_attn_mask) num_frames = c_attn_masks.shape[1] video_embeddings = fused_video_qa[:, :num_frames, :] else: raise ValueError("c_encoder is None in v_encoder") if task == "videoQA": num_videos = len(targets) num_frames, hid_size = video_embeddings.shape[1:3] video_embeddings = video_embeddings.view( num_videos, -1, num_frames, hid_size) video_masks = c_attn_masks.view(num_videos, -1, num_frames) video_masks = video_masks.to(dtype=video_embeddings.dtype) (st_ed_pooled_video, qa_pooled_video ) = self.get_modularized_video( video_embeddings, video_masks) pred_st_ed = self.st_ed_pred_head(st_ed_pooled_video) st_prob = mask_logits(pred_st_ed[:, :, 0], video_masks[:, 0]) ed_prob = mask_logits(pred_st_ed[:, :, 1], video_masks[:, 0]) logits = self.qa_pred_head(qa_pooled_video).squeeze(-1) else: video_masks = c_attn_masks.to(dtype=video_embeddings.dtype) qa_pooled_video = self.get_modularized_video( video_embeddings, video_masks, violin=True) logits = self.qa_pred_head(qa_pooled_video) if compute_loss: if task == "videoQA": ts_targets = batch["ts_targets"] st_target, ed_target = ts_targets[:, 0], ts_targets[:, 1] st_loss = F.cross_entropy( st_prob, st_target, reduction="mean", ignore_index=-1) ed_loss = F.cross_entropy( ed_prob, ed_target, reduction="mean", ignore_index=-1) temporal_loss = (st_loss + ed_loss)/2. qa_loss = F.cross_entropy( logits, targets, reduction='mean', ignore_index=-1) return qa_loss, temporal_loss else: targets = batch['targets'] scores = torch.sigmoid(logits).squeeze(-1) targets = targets.squeeze(-1).to(dtype=scores.dtype) qa_loss = F.binary_cross_entropy( scores, targets, reduction='mean') return qa_loss else: return logits else: raise ValueError(f'Unrecognized task: {task}')

4,380

1,696

23

a41809e1c5cdadc95d16313cf867c2d8f5f87176

24,261

py

Python

cardgame_channels_app/tests.py

cyface/cardgame_channels

22f2bef190ee20999eae27e6aa9ce138a78ae47f

[ "MIT" ]

null

cardgame_channels_app/tests.py

cyface/cardgame_channels

22f2bef190ee20999eae27e6aa9ce138a78ae47f

[ "MIT" ]

null

cardgame_channels_app/tests.py

cyface/cardgame_channels

22f2bef190ee20999eae27e6aa9ce138a78ae47f

[ "MIT" ]

null

import logging from channels.test import ChannelTestCase, WSClient from .game_logic import add_player_to_game from .models import Player, Game, CardGamePlayer, Card LOGGER = logging.getLogger("cardgame_channels_app")

61.420253

228

0.676765

import logging from channels.test import ChannelTestCase, WSClient from .game_logic import add_player_to_game from .models import Player, Game, CardGamePlayer, Card LOGGER = logging.getLogger("cardgame_channels_app") class GameModelTests(ChannelTestCase): fixtures = ['test_card_data.json'] # 100 green and 100 red cards def setUp(self): self.game1 = Game.objects.create(pk=1, code='abcd') def test_cards(self): player = add_player_to_game(self.game1.code, 'tim') self.assertIsNotNone(str(player)) self.assertEqual(6, len(player.cardgameplayer_set.all())) # Pull by CGP cgps_in_hand = CardGamePlayer.objects.filter(player=player, game=player.game, status=CardGamePlayer.HAND) self.assertEqual(5, len(cgps_in_hand)) self.assertIsNotNone(str(cgps_in_hand[0])) # Pull by Card cards_in_hand = Card.objects.filter(cardgameplayer__player=player, cardgameplayer__game=player.game, cardgameplayer__status=CardGamePlayer.HAND) self.assertEqual(5, len(cards_in_hand)) self.assertIsNotNone(str(cards_in_hand[0])) def test_game(self): self.assertIsNotNone(str(self.game1)) class GameConsumerTests(ChannelTestCase): fixtures = ['test_card_data.json'] # 100 green and 100 red cards def setUp(self): self.game1 = Game.objects.create(pk=1, code='abcd') def test_create_game(self): client = WSClient() while client.receive(): pass # Grab connection success message from each consumer client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'create_game', 'payload': {}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel self.assertEqual(receive_reply.get('stream'), 'create_game') self.assertEqual(4, len(receive_reply.get('payload').get('data').get('game_code'))) disconnect_consumer = client.send_and_consume('websocket.disconnect', path='/game/') disconnect_consumer.close() def test_join_game_errors(self): client = WSClient() client.send_and_consume('websocket.connect', path='/game/') # Connect is forwarded to ALL multiplexed consumers under this demultiplexer while client.receive(): pass # Grab connection success message from each consumer # Test Player Name Too Long client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'join_game', 'payload': {'game_code': 'abcd', 'player_name': '1234567891011121314151617181920'}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertIn('most 10', receive_reply.get('payload').get('data').get('errors').get('player_name')[0]) # Test Game Code Missing client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'join_game', 'payload': {'game_code': '', 'player_name': '123456789'}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertIn('required', receive_reply.get('payload').get('data').get('errors').get('game_code')[0]) # Test Player Name Missing client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'join_game', 'payload': {'game_code': 'abcd', 'player_name': ''}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertIn('required', receive_reply.get('payload').get('data').get('errors').get('player_name')[0]) # Test Empty Submit client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'join_game', 'payload': {'game_code': '', 'player_name': ''}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertIn('required', receive_reply.get('payload').get('data').get('errors').get('game_code')[0]) self.assertIn('required', receive_reply.get('payload').get('data').get('errors').get('player_name')[0]) # Test Game Code Doesn't Exist client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'join_game', 'payload': {'game_code': '1234', 'player_name': '123456789'}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertIn('does not exist', receive_reply.get('payload').get('data').get('errors').get('game_code')[0]) # Test Player Name Taken add_player_to_game('abcd', 'my_player') client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'join_game', 'payload': {'game_code': 'abcd', 'player_name': 'my_player'}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertIn('already taken', receive_reply.get('payload').get('data').get('errors').get('player_name')[0]) Player.objects.get(name='my_player').delete() # Test HTML in Code/Player client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'join_game', 'payload': {'game_code': 'a<b>', 'player_name': '©<b>'}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) data = receive_reply.get('payload').get('data') self.assertIsNotNone(data.get('error')) disconnect_consumer = client.send_and_consume('websocket.disconnect', path='/game/') disconnect_consumer.close() def test_join_game(self): client = WSClient() client.send_and_consume('websocket.connect', path='/game/') # Connect is forwarded to ALL multiplexed consumers under this demultiplexer while client.receive(): pass # Grab connection success message from each consumer client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'join_game', 'payload': {'game_code': 'abcd', 'player_name': 'tim'}}) # Text arg is JSON as if it came from browser # Joined Event to Player receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertEqual('join_game', receive_reply.get('stream')) # Player Joined Group Event receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertEqual('player_joined_game', receive_reply.get('stream')) data = receive_reply.get('payload').get('data') self.assertEqual(1, len(data.get('players'))) self.assertEqual('judge', data.get('players')[0].get('status')) self.assertEqual('tim', data.get('player').get('name')) tim = Player.objects.get(name='tim') self.assertIsNotNone(Player.objects.get(name='tim', game__code='abcd')) self.assertEqual(6, len(tim.card_set.all())) # 5 red, one green disconnect_consumer = client.send_and_consume('websocket.disconnect', path='/game/') disconnect_consumer.close() def test_validate_game_code(self): client = WSClient() client.send_and_consume('websocket.connect', path='/game/') # Connect is forwarded to ALL multiplexed consumers under this demultiplexer while client.receive(): pass # Grab connection success message from each consumer # Valid Test client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'validate_game_code', 'payload': {'game_code': 'abcd'}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel self.assertEqual(receive_reply.get('stream'), 'validate_game_code') self.assertEqual('abcd', receive_reply.get('payload').get('data').get('game_code')) self.assertTrue(receive_reply.get('payload').get('data').get('valid')) # Invalid Test client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'validate_game_code', 'payload': {'game_code': '1234'}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel self.assertEqual(receive_reply.get('stream'), 'validate_game_code') self.assertEqual('1234', receive_reply.get('payload').get('data').get('game_code')) self.assertFalse(receive_reply.get('payload').get('data').get('valid')) disconnect_consumer = client.send_and_consume('websocket.disconnect', path='/game/') disconnect_consumer.close() def test_validate_player_name(self): client = WSClient() client.send_and_consume('websocket.connect', path='/game/') # Connect is forwarded to ALL multiplexed consumers under this demultiplexer while client.receive(): pass # Grab connection success message from each consumer # Available Test client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'validate_player_name', 'payload': {'game_code': 'abcd', 'player_name': 'tim'}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel self.assertEqual(receive_reply.get('stream'), 'validate_player_name') self.assertEqual('abcd', receive_reply.get('payload').get('data').get('game_code')) self.assertTrue(receive_reply.get('payload').get('data').get('valid')) # Invalid Test add_player_to_game(self.game1.code, 'tim') client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'validate_player_name', 'payload': {'game_code': 'abcd', 'player_name': 'tim'}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel self.assertEqual(receive_reply.get('stream'), 'validate_player_name') self.assertEqual('abcd', receive_reply.get('payload').get('data').get('game_code')) self.assertFalse(receive_reply.get('payload').get('data').get('valid')) disconnect_consumer = client.send_and_consume('websocket.disconnect', path='/game/') disconnect_consumer.close() def test_pick_card(self): client = WSClient() client.send_and_consume('websocket.connect', path='/game/') # Connect is forwarded to ALL multiplexed consumers under this demultiplexer while client.receive(): pass # Grab connection success message from each consumer # Invalid Test client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'pick_card', 'payload': {'game_code': '1234'}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel self.assertEqual(receive_reply.get('stream'), 'pick_card') self.assertFalse(receive_reply.get('payload').get('data').get('valid')) disconnect_consumer = client.send_and_consume('websocket.disconnect', path='/game/') disconnect_consumer.close() def test_submit_card(self): client = WSClient() client.send_and_consume('websocket.connect', path='/game/') # Connect is forwarded to ALL multiplexed consumers under this demultiplexer while client.receive(): pass # Grab connection success message from each consumer # Invalid Test client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'submit_card', 'payload': {'game_code': '1234'}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel self.assertEqual(receive_reply.get('stream'), 'submit_card') self.assertFalse(receive_reply.get('payload').get('data').get('valid')) disconnect_consumer = client.send_and_consume('websocket.disconnect', path='/game/') disconnect_consumer.close() def test_boot_player(self): client = WSClient() client.send_and_consume('websocket.connect', path='/game/') # Connect is forwarded to ALL multiplexed consumers under this demultiplexer while client.receive(): pass # Grab connection success message from each consumer # Add extra player for valid test add_player_to_game(self.game1.code, 'tim') # Join Game client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'join_game', 'payload': {'game_code': self.game1.code, 'player_name': 'bob'}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) bob_pk = receive_reply.get('payload').get('data').get('player').get('pk') self.assertEqual('join_game', receive_reply.get('stream')) # Join Game Broadcast receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) # Valid Test client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'boot_player', 'payload': {'game_code': self.game1.code, 'player_pk': bob_pk}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertEqual(receive_reply.get('stream'), 'boot_player') self.assertEqual(self.game1.code, receive_reply.get('payload').get('data').get('game_code')) self.assertEqual('bob', receive_reply.get('payload').get('data').get('player_name')) self.assertTrue(receive_reply.get('payload').get('data').get('valid')) self.assertFalse(Player.objects.filter(pk=bob_pk)) # Invalid Test client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'boot_player', 'payload': {'game_code': self.game1.code, 'player_pk': 99}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel self.assertEqual(receive_reply.get('stream'), 'boot_player') self.assertEqual(self.game1.code, receive_reply.get('payload').get('data').get('game_code')) self.assertFalse(receive_reply.get('payload').get('data').get('valid')) disconnect_consumer = client.send_and_consume('websocket.disconnect', path='/game/') disconnect_consumer.close() def test_whole_game(self): client = WSClient() client.send_and_consume('websocket.connect', path='/game/') # Connect is forwarded to ALL multiplexed consumers under this demultiplexer while client.receive(): pass # Grab connection success message from each consumer # Create a game client.send_and_consume('websocket.receive', path='/game/create/', text={'stream': 'create_game', 'payload': {}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel self.assertEqual('create_game', receive_reply.get('stream')) game_code = receive_reply.get('payload').get('data').get('game_code') # Join the game client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'join_game', 'payload': {'game_code': game_code, 'player_name': 'tim'}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertEqual('join_game', receive_reply.get('stream')) data = receive_reply.get('payload').get('data') self.assertEqual(5, len(data.get('player_cards'))) self.assertEqual('tim', data.get('judge').get('name')) self.assertIsNotNone(data.get('green_card').get('name')) # Player Join Event receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertEqual('player_joined_game', receive_reply.get('stream')) data = receive_reply.get('payload').get('data') self.assertEqual(1, len(data.get('players'))) self.assertEqual('judge', data.get('players')[0].get('status')) self.assertEqual('tim', data.get('player').get('name')) # Set up player 2 client2 = WSClient() client2.send_and_consume('websocket.connect', path='/game/') # Connect is forwarded to ALL multiplexed consumers under this demultiplexer while client2.receive(): pass # Grab connection success message from each consumer # Player 2: join the game client2.send_and_consume('websocket.receive', path='/game/', text={'stream': 'join_game', 'payload': {'game_code': game_code, 'player_name': 'bob'}}) # Text arg is JSON as if it came from browser receive_reply = client2.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertEqual('join_game', receive_reply.get('stream')) data = receive_reply.get('payload').get('data') submitted_card_pk = data.get('player_cards')[0].get('pk') self.assertEqual(5, len(data.get('player_cards'))) self.assertEqual('tim', data.get('judge').get('name')) self.assertIsNotNone(data.get('green_card').get('name')) # Player2 Join Event receive_reply = client2.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertEqual('player_joined_game', receive_reply.get('stream')) data = receive_reply.get('payload').get('data') self.assertEqual('bob', data.get('player').get('name')) self.assertEqual(2, len(data.get('players'))) self.assertEqual('bob', data.get('players')[0].get('name')) self.assertEqual('tim', data.get('players')[1].get('name')) self.assertEqual('waiting', data.get('players')[0].get('status')) self.assertEqual('judge', data.get('players')[1].get('status')) # Player2 Join Event - Seen by Player 1 receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel self.assertEqual('player_joined_game', receive_reply.get('stream')) LOGGER.debug(receive_reply) data = receive_reply.get('payload').get('data') self.assertEqual('bob', data.get('player').get('name')) # Player 2: Submit Card client2.send_and_consume('websocket.receive', path='/game/', text={'stream': 'submit_card', 'payload': {'game_code': game_code, 'card_pk': submitted_card_pk}}) # Text arg is JSON as if it came from browser receive_reply = client2.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertEqual('submit_card', receive_reply.get('stream')) data = receive_reply.get('payload').get('data') self.assertEqual(4, len(data.get('cards'))) # Player 2: Submit Card - Group Notification receive_reply = client2.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertEqual('card_was_submitted', receive_reply.get('stream')) data = receive_reply.get('payload').get('data') self.assertEqual('bob', data.get('submitting_player').get('name')) # Player 1: Submit Card - Group Notification receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertEqual('card_was_submitted', receive_reply.get('stream')) data = receive_reply.get('payload').get('data') self.assertEqual('bob', data.get('submitting_player').get('name')) # Player 1 Pick Card - Group notification client.send_and_consume('websocket.receive', path='/game/', text={'stream': 'pick_card', 'payload': {'game_code': game_code, 'card_pk': submitted_card_pk}}) # Text arg is JSON as if it came from browser receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertEqual('pick_card', receive_reply.get('stream')) data = receive_reply.get('payload').get('data') self.assertEqual('bob', data.get('picked_player').get('name')) self.assertEqual(1, data.get('players')[0].get('score')) # Point to bob self.assertEqual(0, data.get('players')[1].get('score')) # Tim's score should not have changed # Player 2: Pick Card - Group notification receive_reply = client2.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertEqual('pick_card', receive_reply.get('stream')) data = receive_reply.get('payload').get('data') self.assertEqual('bob', data.get('picked_player').get('name')) self.assertEqual(1, data.get('players')[0].get('score')) # Point to bob self.assertEqual(0, data.get('players')[1].get('score')) # Tim's score should not have changed # Player 1: Get New Cards Message receive_reply = client.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertIsNotNone(receive_reply) self.assertEqual('new_cards', receive_reply.get('stream')) data = receive_reply.get('payload').get('data') self.assertEqual(5, len(data.get('cards'))) self.assertEqual('bob', data.get('judge').get('name')) # Bob's card was picked so he should now be the judge self.assertIsNotNone(data.get('green_card').get('name')) # Player 2: Get New Cards Message receive_reply = client2.receive() # receive() grabs the content of the next message off of the client's reply_channel LOGGER.debug(receive_reply) self.assertIsNotNone(receive_reply) self.assertEqual('new_cards', receive_reply.get('stream')) data = receive_reply.get('payload').get('data') self.assertEqual(5, len(data.get('cards'))) self.assertEqual('bob', data.get('judge').get('name')) # Bob's card was picked so he should now be the judge self.assertIsNotNone(data.get('green_card').get('name')) disconnect_consumer = client.send_and_consume('websocket.disconnect', path='/game/') disconnect_consumer.close()

23,465

528

46

dce07b739ca43d0c08ddf16db1417665536ad16a

16,447

py

Python

pyt_utilities.py

realtechsupport/return_to_bali

6af3b8163ef583e9d9ad3fb5d381e62714ce8c6f

[ "CC-BY-4.0" ]

null

pyt_utilities.py

realtechsupport/return_to_bali

6af3b8163ef583e9d9ad3fb5d381e62714ce8c6f

[ "CC-BY-4.0" ]

null

pyt_utilities.py

realtechsupport/return_to_bali

6af3b8163ef583e9d9ad3fb5d381e62714ce8c6f

[ "CC-BY-4.0" ]

null

# pyt_utilities.py (python3) # utilities for CNN training with pytorch; data preparation, training, evaluation # added saving checkpoint # FEB 2020 / 21 # sources: # https://pytorch.org/tutorials/beginner/transfer_learning_tutorial.html#load-data # https://pytorch.org/tutorials/beginner/finetuning_torchvision_models_tutorial.html #updated normalization mean and std: #mean [0.4597244970012637, 0.4887084808460421, 0.46925360649661096] #std [0.20728858675971737, 0.2048932794469992, 0.21645177513430724] #------------------------------------------------------------------------------- import os, sys, time, random, itertools import torch, torchvision from torch.optim import lr_scheduler from torch.autograd import Variable from torchvision import models, datasets, transforms import torch.nn.functional as F from torch import utils import torch.optim as optim from PIL import Image import numpy import array import urllib, glob, shutil from shutil import copyfile, copy from copy import deepcopy import matplotlib.pyplot as plt from plot_helper import * from utilities import * bali26_class_names = ['aroid', 'bamboo', 'banana', 'cacao', 'cinnamon', 'coffeearabica', 'dragonfruit', 'durian', 'frangipani', 'guava', \ 'jackfruit', 'lychee', 'mango', 'mangosteen', 'nilam', 'papaya', 'passiflora', \ 'sawo', 'snakefruit', 'starfruit', 'sugarpalm', 'taro', 'vanilla', 'waterguava', 'whitepepper', 'zodia'] #files on pCloud bali26_alexnet = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/models/bali26_alexnet.pth' bali26_resnet152 = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/models/bali26_resnet152.pth' bali26_rexnext50 = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/models/bali26_resnext50.pth' bali26_samples_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/bali26samples.zip' bali3_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/bali-3.zip' bali3B_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/bali-3B.zip' bali3C_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/bali-3C.zip' bali3D_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/bali-3D.zip' tests_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/tests.zip' bali_mixedplants_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/bali_mixedplants.zip' #------------------------------------------------------------------------------- data_transforms = { 'train': transforms.Compose([ transforms.RandomResizedCrop(224), transforms.RandomHorizontalFlip(), transforms.ToTensor(), transforms.Normalize([0.4597, 0.4887, 0.4692], [0.2072, 0.2048, 0.2164]) #bali26 #transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]) ]), 'val': transforms.Compose([ transforms.Resize(256), transforms.CenterCrop(224), transforms.ToTensor(), transforms.Normalize([0.4597, 0.4887, 0.4692], [0.2072, 0.2048, 0.2164]) #bali26 #transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]) ]), } predict_transform = transforms.Compose([ transforms.CenterCrop(224), transforms.ToTensor(), transforms.Normalize([0.4597, 0.4887, 0.4692], [0.2072, 0.2048, 0.2164]) #bali26 #transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]) ]) #------------------------------------------------------------------------------- #simple three layer CNN for 224 x 224 input; reduced alexnet; untrained by default #https://github.com/pytorch/vision/blob/master/torchvision/models/alexnet.py #------------------------------------------------------------------------------- #------------------------------------------------------------------------------- #------------------------------------------------------------------------------- #def train_model(checkpointname, model, criterion, optimizer, scheduler, num_epochs, output): #------------------------------------------------------------------------------- #------------------------------------------------------------------------------- #------------------------------------------------------------------------------- #------------------------------------------------------------------------------- #------------------------------------------------------------------------------- #-------------------------------------------------------------------------------

42.830729

196

0.588436

# pyt_utilities.py (python3) # utilities for CNN training with pytorch; data preparation, training, evaluation # added saving checkpoint # FEB 2020 / 21 # sources: # https://pytorch.org/tutorials/beginner/transfer_learning_tutorial.html#load-data # https://pytorch.org/tutorials/beginner/finetuning_torchvision_models_tutorial.html #updated normalization mean and std: #mean [0.4597244970012637, 0.4887084808460421, 0.46925360649661096] #std [0.20728858675971737, 0.2048932794469992, 0.21645177513430724] #------------------------------------------------------------------------------- import os, sys, time, random, itertools import torch, torchvision from torch.optim import lr_scheduler from torch.autograd import Variable from torchvision import models, datasets, transforms import torch.nn.functional as F from torch import utils import torch.optim as optim from PIL import Image import numpy import array import urllib, glob, shutil from shutil import copyfile, copy from copy import deepcopy import matplotlib.pyplot as plt from plot_helper import * from utilities import * bali26_class_names = ['aroid', 'bamboo', 'banana', 'cacao', 'cinnamon', 'coffeearabica', 'dragonfruit', 'durian', 'frangipani', 'guava', \ 'jackfruit', 'lychee', 'mango', 'mangosteen', 'nilam', 'papaya', 'passiflora', \ 'sawo', 'snakefruit', 'starfruit', 'sugarpalm', 'taro', 'vanilla', 'waterguava', 'whitepepper', 'zodia'] #files on pCloud bali26_alexnet = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/models/bali26_alexnet.pth' bali26_resnet152 = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/models/bali26_resnet152.pth' bali26_rexnext50 = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/models/bali26_resnext50.pth' bali26_samples_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/bali26samples.zip' bali3_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/bali-3.zip' bali3B_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/bali-3B.zip' bali3C_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/bali-3C.zip' bali3D_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/bali-3D.zip' tests_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/tests.zip' bali_mixedplants_zip = 'https://filedn.com/lqzjnYhpY3yQ7BdfTulG1yY/bali_mixedplants.zip' #------------------------------------------------------------------------------- data_transforms = { 'train': transforms.Compose([ transforms.RandomResizedCrop(224), transforms.RandomHorizontalFlip(), transforms.ToTensor(), transforms.Normalize([0.4597, 0.4887, 0.4692], [0.2072, 0.2048, 0.2164]) #bali26 #transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]) ]), 'val': transforms.Compose([ transforms.Resize(256), transforms.CenterCrop(224), transforms.ToTensor(), transforms.Normalize([0.4597, 0.4887, 0.4692], [0.2072, 0.2048, 0.2164]) #bali26 #transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]) ]), } predict_transform = transforms.Compose([ transforms.CenterCrop(224), transforms.ToTensor(), transforms.Normalize([0.4597, 0.4887, 0.4692], [0.2072, 0.2048, 0.2164]) #bali26 #transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]) ]) #------------------------------------------------------------------------------- #simple three layer CNN for 224 x 224 input; reduced alexnet; untrained by default #https://github.com/pytorch/vision/blob/master/torchvision/models/alexnet.py class vanillanet(torch.nn.Module): def __init__(self, num_classes): super(vanillanet, self).__init__() self.cnn_layers = torch.nn.Sequential( torch.nn.Conv2d(3, 64, kernel_size=11, stride=4, padding=2), torch.nn.ReLU(inplace=True), torch.nn.MaxPool2d(kernel_size=3, stride=2), torch.nn.Conv2d(64, 192, kernel_size=5, padding=2), torch.nn.ReLU(inplace=True), torch.nn.MaxPool2d(kernel_size=3, stride=2), torch.nn.Conv2d(192, 256, kernel_size=3, padding=1), torch.nn.ReLU(inplace=True), torch.nn.MaxPool2d(kernel_size=3, stride=2), ) self.avgpool = torch.nn.AdaptiveAvgPool2d((6, 6)) self.classifier = torch.nn.Sequential( torch.nn.Dropout(), torch.nn.Linear(256 * 6 * 6, 4096), torch.nn.ReLU(inplace=True), torch.nn.Linear(4096, num_classes), ) def forward(self, x): x = self.cnn_layers(x) x = self.avgpool(x) x = torch.flatten(x, 1) x = self.classifier(x) return (x) #------------------------------------------------------------------------------- def prune_imageset(datapath, categories, limit, randomprune): for i in range(0, len(categories)): files = list(filter(os.path.isfile, glob.glob(datapath + categories[i] + '/' + "*"))) if(randomprune == True): #random.shuffle(files) shuffle(files) else: files.sort(key=lambda x: os.path.getmtime(x)) for i in range (0, len(files)): if(i < limit): pass else: print("random?, getting rid of: ", randomprune, files[i]) os.remove(files[i]) #------------------------------------------------------------------------------- def create_train_val_sets(datapath, categories, percentage): train = datapath + 'train/' val = datapath + 'val/' if not os.path.exists(train): os.mkdir(train) for k in categories: os.mkdir(train + k) if not os.path.exists(val): os.mkdir(val) for k in categories: os.mkdir(val + k) os.chdir(datapath) try: i = categories.index('train'); j = categories.index('val') p,d,f = next(os.walk(categories[i])) del categories[i]; del categories[j] except: pass print('here are the categories: ', categories) for i in range(0, len(categories)): files = list(filter(os.path.isfile, glob.glob(datapath + categories[i] + '/' + "*"))) files.sort(key=lambda x: os.path.getmtime(x)) traininglimit = int(percentage*len(files)) print('\ncategory: ', categories[i]) print('number files for training: ', traininglimit) print('number files for validation: ', (len(files) - traininglimit)) for j in range (0, len(files)): filename = files[j].split('/')[-1] filecatname = categories[i] + '/' + filename if(j < traininglimit): filecatnametrain = train + filecatname shutil.copy(files[j], filecatnametrain) else: filecatnameval = val + filecatname shutil.copy(files[j], filecatnameval) #------------------------------------------------------------------------------- #def train_model(checkpointname, model, criterion, optimizer, scheduler, num_epochs, output): def train_model(app, checkpointname, network, testcollection, model, categories, datapath, epochs, gamma, lr, momentum, max_images, training_percentage, pretrained, training_image, normalization): prune_imageset(datapath, categories, max_images, randomprune=True) #check if they esist, if so, delete and re-create create_train_val_sets(datapath, categories, training_percentage) device = ("cuda" if torch.cuda.is_available() else "cpu" ) image_datasets = {x: datasets.ImageFolder(os.path.join(datapath, x), data_transforms[x]) for x in ['train', 'val']} dataloaders = {x: torch.utils.data.DataLoader(image_datasets[x], batch_size=4,shuffle=True, num_workers=4) for x in ['train', 'val']} dataset_sizes = {x: len(image_datasets[x]) for x in ['train', 'val']} class_names = image_datasets['train'].classes model = model.to(device) criterion = torch.nn.CrossEntropyLoss() optimizer = torch.optim.SGD(model.parameters(), lr, momentum) step_size = 7 scheduler = lr_scheduler.StepLR(optimizer, step_size, gamma) #--------------------------------------------------------------------------- since = time.time() best_acc = 0.0 e_val_loss = []; e_train_loss = [] e_val_acc = []; e_train_acc = [] for epoch in range(epochs): print('Epoch {}/{}'.format(epoch, epochs - 1)) print('-' * 10) # Each epoch has a training and validation phase for phase in ['train', 'val']: if phase == 'train': print('training...') model.train() # Set model to training mode else: print('evaluating...') model.eval() # Set model to evaluate mode running_loss = 0.0; running_corrects = 0 for inputs, labels in dataloaders[phase]: inputs = inputs.to(device) labels = labels.to(device) # zero the parameter gradients optimizer.zero_grad() # forward; track history if only in train with torch.set_grad_enabled(phase == 'train'): outputs = model(inputs) _, preds = torch.max(outputs, 1) loss = criterion(outputs, labels) # backward + optimize only if in training phase if phase == 'train': loss.backward() optimizer.step() running_loss += loss.item() * inputs.size(0) running_corrects += torch.sum(preds == labels.data) if phase == 'train': scheduler.step() epoch_loss = running_loss / dataset_sizes[phase] epoch_acc = running_corrects.double() / dataset_sizes[phase] print('{} Loss: {:.4f} Acc: {:.4f}'.format(phase, epoch_loss, epoch_acc)) loss = float('{:.4f}'.format(epoch_loss)) acc = float('{:.4f}'.format(epoch_acc)) if(phase == 'train'): e_train_loss.append(loss) e_train_acc.append(acc) if(phase == 'val'): e_val_loss.append(loss) e_val_acc.append(acc) if (phase == 'val' and epoch_acc > best_acc): best_acc = epoch_acc best_model_wts = deepcopy(model.state_dict()) checkpoint = {'model': model,'state_dict': model.state_dict(), 'optimizer' : optimizer.state_dict()} print() time_elapsed = time.time() - since model.load_state_dict(best_model_wts) torch.save(checkpoint, checkpointname) print('Training complete in {:.0f}m {:.0f}s'.format(time_elapsed // 60, time_elapsed % 60)) print('Best val Acc: {:4f}'.format(best_acc)) print('\nPlotting results...') plot_training(e_val_loss, e_train_loss, e_val_acc, e_train_acc, training_image) toperrors_filename = os.path.join(app.config['RESULTS'], 'top_errors.csv') tk=3; processor=device; tpp=int(100 * training_percentage) get_toperrors(datapath, checkpointname, network, testcollection, predict_transform, tk, processor, toperrors_filename, pretrained, tpp, normalization, epochs, max_images) toperrors_image = os.path.join(app.config['RESULTS'], 'top_errors.jpg') ttp = int(100*training_percentage) plot_toperrors(datapath, testcollection, network, toperrors_filename, toperrors_image, pretrained, epochs, max_images, ttp) nwidth = 680; resize_image(training_image, nwidth) nwidth = 640; resize_image(toperrors_image, nwidth) return (training_image, toperrors_image) #------------------------------------------------------------------------------- def get_toperrors(datapath, checkpointname, network, testcollection, predict_transform, tk, processor, toperrors_filename, pretrained, tpp, normalization, epochs, max_images): print('\n> Getting top errors <') if(pretrained == True): if('bali' in normalization): comment_t = testcollection + ', ' + network + ', pretrainedyes' + ', ' + str(tpp) + ', ' + str(epochs) + ', ' + str(max_images) + ', ' + 'balinorms' else: comment_t = testcollection+ ', ' + network + ', pretrainedyes' + ', ' + str(tpp) + ', ' + str(epochs) + ', ' + str(max_images) + ', ' + '' else: if('bali' in normalization): comment_t = testcollection + ', ' + network + ', pretrainedNO' + ', ' + str(tpp) + ', ' + str(epochs) + ', ' + str(max_images) + ', ' + 'balinorms' else: comment_t = testcollection + ', ' + network + ', pretrainedNO' + ', ' + str(tpp) + ', ' + str(epochs) + ', ' + str(max_images) + ', ' + '' image_datasets = {x: datasets.ImageFolder(os.path.join(datapath, x), data_transforms[x]) for x in ['train', 'val']} class_names = image_datasets['train'].classes try: model = load_checkpoint(checkpointname, processor) except: print('That model does not exist... ') exit() for i in range (0, len(class_names)): fulldatapath = datapath + 'val/' + class_names[i] + '/' path, dirs, files = next(os.walk(fulldatapath)) limit = len(files) top1 = 0; topN = 0; tk = 3 for j in range (0, limit): image_path = next(itertools.islice(os.scandir(fulldatapath), j, None)).path predictions, percentage, outcategory = predict_image(image_path, model, predict_transform, class_names, tk, processor) topN_ind = predictions[1].tolist()[0] top1_ind = topN_ind[0] input = image_path.split('/')[-2], image_path.split('/')[-1] #check input[1] to find problematic images / categories of confusion #print('\ninput: ', input); print('output: ', outcategory, percentage) if(class_names[top1_ind] == input[0]): top1 = top1 + 1 #if(check_topN(class_names, topN_ind, tk, input[0]) == 1): # topN = topN + 1 top1_score = float(top1 / limit) top1_error = 100*float("%.3f" %(1.0 - top1_score)) #topN_score = float(topN / limit) #topN_error = 100*float("%.3f" %(1.0 - topN_score)) #comment = comment_t + ', ' + str(class_names[i]) + ', top1-error, ' + str(top1_error) + ', top' + str(tk) + '-error, ' + str(topN_error) comment = comment_t + ', ' + str(class_names[i]) + ', top1-error, ' + str(top1_error) print(comment) write2file(toperrors_filename, comment) #------------------------------------------------------------------------------- def predict_image(image_path, model, predict_transform, class_names, tk, processor): img = Image.open(image_path) img_t = predict_transform(img) if((processor == 'gpu') or (processor == 'cuda')): batch_t = torch.unsqueeze(img_t, 0).cuda() else: batch_t = torch.unsqueeze(img_t, 0).cpu() model.eval() output = model(batch_t) predictions = output.topk(tk,1,largest=True,sorted=True) _, index = torch.max(output, 1) t_percentage = torch.nn.functional.softmax(output, dim=1)[0] * 100 percentage = t_percentage[index[0]].item() percentage = '%.1f'%(percentage) category = class_names[index[0]] return(predictions, percentage, category) #------------------------------------------------------------------------------- def check_topN(class_names, topNlist, tk, input): topN = 0 for i in range (0, len(topNlist)): if(class_names[topNlist[i]] == input): topN = 1 break return(topN) #------------------------------------------------------------------------------- def load_checkpoint(filepath, processor): if(processor == 'gpu'): checkpoint = torch.load(filepath) else: checkpoint = torch.load(filepath, map_location=torch.device('cpu')) model = checkpoint['model'] model.load_state_dict(checkpoint['state_dict']) for parameter in model.parameters(): parameter.requires_grad = False model.eval() return (model) #------------------------------------------------------------------------------- def resize_image(inputimage, newwidth): img = Image.open(inputimage) wpercent = (newwidth/float(img.size[0])) hsize = int((float(img.size[1])*float(wpercent))) resized_image = img.resize((newwidth,hsize), Image.ANTIALIAS) resized_image.save(inputimage) #-------------------------------------------------------------------------------

11,897

13

251

ae1a7f1f3b28ebe4b6ed9d9b5a1557a03091f6d4

10,706

py

Python

data_preperation/cricsheet/load_data.py

vv-varun/IPL-DataAnalysis

936827aedcbc4f0a2204888210b3e20fcd46b0e6

[ "MIT" ]

null

data_preperation/cricsheet/load_data.py

vv-varun/IPL-DataAnalysis

936827aedcbc4f0a2204888210b3e20fcd46b0e6

[ "MIT" ]

null

data_preperation/cricsheet/load_data.py

vv-varun/IPL-DataAnalysis

936827aedcbc4f0a2204888210b3e20fcd46b0e6

[ "MIT" ]

null

import mysql.connector import yaml from os import path, listdir import shutil import datetime db_connection = mysql.connector.connect( host="localhost", port=3308, user="root", passwd="", database="ipldata" ) # Global Variable player_data = {} # Query Team details by name # Add new player to DB. # Get Player details by name # Read data from YAML file # Read files from folders # Upload data into MySQL DB # Parse Innings data ###### Main Program ###### # Read files to load from directory files = readFilesInFolder() # Read Data from the file. for file in files: print("Processing file: " + file) match_data = readDataFromFile(file) #print(match_data['info']) # Upload into DB parseAndUploadDataToDB(match_data) shutil.move(path.dirname(__file__) + "/to_load/" + file, path.dirname(__file__) + "/done/" + file) print("I'm done here !")

37.697183

153

0.621054

import mysql.connector import yaml from os import path, listdir import shutil import datetime db_connection = mysql.connector.connect( host="localhost", port=3308, user="root", passwd="", database="ipldata" ) # Global Variable player_data = {} # Query Team details by name def queryTeamDetailsByName(team_name): my_database = db_connection.cursor() sql_statement = "SELECT * FROM teams WHERE Team_Name = '" + team_name + "'" my_database.execute(sql_statement) result_set = my_database.fetchall() for team in result_set: team_details = {"id":team[1], "team_name": team[2]} return team_details # Add new player to DB. def addPlayer(player_name): # Here we assume that the player does not exist. # To keep it safe - lets add a unique index on Player name my_database = db_connection.cursor() sql_statement = "SELECT max(Player_Id) as C FROM players" my_database.execute(sql_statement) result_set = my_database.fetchall() id = result_set[0][0] + 1 # Now insert. sql_statement = "INSERT INTO players (PLAYER_SK, Player_Id, Player_Name) VALUES (%s, %s, %s)" values = (id,id,player_name) my_database.execute(sql_statement, values) db_connection.commit() return {"id":id, "player_name": player_name} # Get Player details by name def getPlayerDetailsByName(player_name): if player_name == '': return {"id":"","player_name":player_name} if player_name in player_data: return player_data[player_name] else: my_database = db_connection.cursor() sql_statement = "SELECT * FROM players WHERE Player_Name = '" + player_name + "'" my_database.execute(sql_statement) result_set = my_database.fetchall() if len(result_set) > 0: # We found entry for player in result_set: player_details = {"id":player[1], "player_name": player[2]} player_data[player_name] = player_details #print("Read " + player_name + " from DB") else: # This is a new player ! Create entry. player_details = addPlayer(player_name) player_data[player_name] = player_details return player_data[player_name] # Read data from YAML file def readDataFromFile(filename): # Get the filename without extension to extract the match id match_id = path.splitext(filename)[0] # Open YAML file and load data file = path.dirname(__file__) + '/to_load/' + filename with open(file, 'r') as stream: try: match_data = yaml.safe_load(stream) match_data['info']['match_id'] = match_id except yaml.YAMLError as exc: print(exc) return match_data # Read files from folders def readFilesInFolder(): return listdir(path.dirname(__file__) + "/to_load") # Upload data into MySQL DB def parseAndUploadDataToDB(match_data): # Prepare match info. match_info = {} ball_details = [] match_info['Match_SK'] = match_info['match_id'] = match_data['info']['match_id'] match_info['Team1'] = match_data['info']['teams'][0] match_info['Team2'] = match_data['info']['teams'][1] match_info['match_date_str'] = match_data['info']['dates'][0] match_info['match_date'] = datetime.datetime.strptime(match_data['info']['dates'][0], "%Y-%m-%d").date() match_info['Season_Year'] = match_info['match_date'].year match_info['Venue_Name'] = match_data['info']['venue'] match_info['City_Name'] = match_data['info'].get('city','') match_info['Country_Name'] = '' match_info['Toss_Winner'] = match_data['info']['toss']['winner'] match_info['Toss_Name'] = match_data['info']['toss']['decision'] if 'winner' in match_data['info']['outcome'].keys(): match_info['Outcome_Type'] = 'Result' match_info['match_winner'] = match_data['info']['outcome']['winner'] match_info['Win_Type'] = list(match_data['info']['outcome']['by'].keys())[0] match_info['Win_Margin'] = list(match_data['info']['outcome']['by'].values())[0] else: match_info['Outcome_Type'] = match_data['info']['outcome']['result'] match_info['match_winner'] = '' match_info['Win_Type'] = '' match_info['Win_Margin'] = '' if 'player_of_match' in match_data['info'].keys(): match_info['ManOfMach'] = match_data['info']['player_of_match'][0] else: match_info['ManOfMach'] = '' match_info['Country_id'] = '' #print(match_info) first_innings_data = match_data['innings'][0]['1st innings'] fi_team = queryTeamDetailsByName(first_innings_data['team']) second_innings_data = match_data['innings'][1]['2nd innings'] si_team = queryTeamDetailsByName(second_innings_data['team']) #Parse 1st innings first_innings = parseInningsData(first_innings_data) for bd in first_innings: bd['match_id'] = match_info['match_id'] bd['innings_no'] = 1 bd['Team_Batting'] = fi_team['id'] bd['Team_Bowling'] = si_team['id'] # Put all details in a list for Update ball_details.extend(first_innings) #Parse 2nd Innings second_innings = parseInningsData(second_innings_data) for bd in second_innings: bd['match_id'] = match_info['match_id'] bd['innings_no'] = 2 bd['Team_Batting'] = si_team['id'] bd['Team_Bowling'] = fi_team['id'] # Put all details in a list for Update ball_details.extend(second_innings) #May be there are super overs ! if len(match_data['innings']) > 2: # More than 2 innings ! - Super Over! so_first_innings_data = list(match_data['innings'][2].values())[0] so_fi_team = queryTeamDetailsByName(so_first_innings_data['team']) so_second_innings_data = list(match_data['innings'][3].values())[0] so_si_team = queryTeamDetailsByName(so_second_innings_data['team']) so_first_innings = parseInningsData(so_first_innings_data) for bd in so_first_innings: bd['match_id'] = match_info['match_id'] bd['innings_no'] = 3 bd['Team_Batting'] = so_fi_team['id'] bd['Team_Bowling'] = so_si_team['id'] ball_details.extend(so_first_innings) so_second_innings = parseInningsData(so_second_innings_data) for bd in so_second_innings: bd['match_id'] = match_info['match_id'] bd['innings_no'] = 4 bd['Team_Batting'] = si_team['id'] bd['Team_Bowling'] = fi_team['id'] ball_details.extend(so_first_innings) # Now update all in a transaction uploadDataToDB(match_info, ball_details) # Print Random for testing #print(first_innings[20]) #print(first_innings[12]) #print(second_innings[20]) #print(second_innings[7]) return # Parse Innings data def parseInningsData(innings_data): ball_data = [] bowler_wicket_list = ['caught','bowled','lbw','stumped','caught and bowled'] for delivery in innings_data['deliveries']: ball_no = str(list(delivery.keys())[0]) ball_details = list(delivery.values())[0] wicket = ball_details.get('wicket', {'player_out':'','kind':'Not Applicable'}) wicket_kind = wicket.get('kind','') if wicket_kind in bowler_wicket_list: wicket['Bowler_Wicket'] = 1 else: wicket['Bowler_Wicket'] = 0 extras = ball_details.get('extras', {}) if (len(extras) > 0): extra_type = list(extras.keys())[0] else: extra_type = '' wides = extras.get('wides',0) legbyes = extras.get('legbyes',0) noballs = extras.get('noballs',0) byes = extras.get('byes',0) bowler_extras = wides + noballs ball_data.append({ 'match_id': '', 'over_id': ball_no.split(".")[0], 'ball_id': ball_no.split(".")[1], 'innings_no': '', 'Team_Batting': '', 'Team_Bowling': '', 'Striker_Batting_Position': '', 'Extra_Type': extra_type, 'Runs_Scored': ball_details['runs']['batsman'], 'Extra_runs': ball_details['runs']['extras'], 'Wides': wides, 'Legbyes': legbyes, 'Byes': byes, 'Noballs': noballs, 'Penalty': '', 'Bowler_Extras': bowler_extras, 'Out_type': wicket['kind'], 'Caught': 1 if wicket_kind == 'caught' else 0, 'Bowled': 1 if wicket_kind == 'bowled' else 0, 'Run_out': 1 if wicket_kind == 'run out' else 0, 'LBW': 1 if wicket_kind == 'lbw' else 0, 'Retired_hurt': 1 if wicket_kind == 'retired hurt' else 0, 'Stumped': 1 if wicket_kind == 'stumped' else 0, 'caught_and_bowled': 1 if wicket_kind == 'caught and bowled' else 0, 'hit_wicket': 1 if wicket_kind == 'hit wicket' else 0, 'ObstructingFeild': 1 if wicket_kind == 'obstructing the field' else 0, 'Bowler_Wicket': wicket['Bowler_Wicket'], 'Striker': getPlayerDetailsByName(ball_details['batsman'])['id'], 'Non_Striker': getPlayerDetailsByName(ball_details['non_striker'])['id'], 'Bowler': getPlayerDetailsByName(ball_details['bowler'])['id'], 'Player_Out': getPlayerDetailsByName(wicket['player_out'])['id'], 'Fielders': '', 'Keeper_Catch': '' }) #print(ball_data) return ball_data def uploadDataToDB(match_info, ball_details): my_database = db_connection.cursor() db_connection.start_transaction() # Insert Match Info sql_statement = "INSERT INTO matches VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)" values = tuple(list(match_info.values())) my_database.execute(sql_statement, values) sql_statement = "INSERT INTO balldetails VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)" for bd in ball_details: values = tuple(list(bd.values())) my_database.execute(sql_statement, values) # Insert Ball Details db_connection.commit() ###### Main Program ###### # Read files to load from directory files = readFilesInFolder() # Read Data from the file. for file in files: print("Processing file: " + file) match_data = readDataFromFile(file) #print(match_data['info']) # Upload into DB parseAndUploadDataToDB(match_data) shutil.move(path.dirname(__file__) + "/to_load/" + file, path.dirname(__file__) + "/done/" + file) print("I'm done here !")

9,642

0

177

a258ffb0adf5980dfb80e491c805881a5b484263

5,868

py

Python

resources/mgltools_x86_64Linux2_1.5.6/MGLToolsPckgs/MolKit/groParser.py

J-E-J-S/aaRS-Pipeline

43f59f28ab06e4b16328c3bc405cdddc6e69ac44

[ "MIT" ]

8

2021-12-14T21:30:01.000Z

2022-02-14T11:30:03.000Z

resources/mgltools_x86_64Linux2_1.5.6/MGLToolsPckgs/MolKit/groParser.py

J-E-J-S/aaRS-Pipeline

43f59f28ab06e4b16328c3bc405cdddc6e69ac44

[ "MIT" ]

null

resources/mgltools_x86_64Linux2_1.5.6/MGLToolsPckgs/MolKit/groParser.py

J-E-J-S/aaRS-Pipeline

43f59f28ab06e4b16328c3bc405cdddc6e69ac44

[ "MIT" ]

1

2021-11-04T21:48:14.000Z

# # # # # # #$Id: groParser.py,v 1.11 2006/12/15 19:53:29 annao Exp $ # """ Module Gromacs Parser. """ import os,types from MolKit.moleculeParser import MoleculeParser from MolKit.protein import Protein, Chain, ChainSet, Residue, ResidueSet, ProteinSet from MolKit.molecule import Atom, AtomSet, Bond, BondSet, HydrogenBond from PyBabel.babelElements import babel_elements if __name__ == '__main__': parser = groParser( filename='/usr/share/gromacs/tutor/methanol/conf.gro' ) print "Reading molecule" mol = parser.parse()

36

179

0.512781

# # # # # # #$Id: groParser.py,v 1.11 2006/12/15 19:53:29 annao Exp $ # """ Module Gromacs Parser. """ import os,types from MolKit.moleculeParser import MoleculeParser from MolKit.protein import Protein, Chain, ChainSet, Residue, ResidueSet, ProteinSet from MolKit.molecule import Atom, AtomSet, Bond, BondSet, HydrogenBond from PyBabel.babelElements import babel_elements class groParser( MoleculeParser ): def __init__( self, filename=None, allLines=None ): """Constructor for groParser: adopted form PdbParser""" MoleculeParser.__init__( self, filename, allLines ) def parse( self, objClass=Protein ): if self.allLines is None and self.filename: self.readFile() if self.allLines is None or len(self.allLines)==0: return mol = Protein() self.mol = mol molList = mol.setClass() molList.append( mol ) current_residue_number = None current_chain = None current_residue = None number_of_atoms = int(self.allLines[1][:5]) self.configureProgressBar( init=1, mode='increment', authtext='parse atoms', max=number_of_atoms ) current_chain = Chain( id='GRO',) #FIX this: The existence of allAtoms attribute (and the fact that it is an empty set rather than all atoms in the chain) causes getNodesByMolecule() to return wrong values if hasattr(current_chain, "allAtoms"): del(current_chain.allAtoms) #current_chain = Chain( id='GRO',parent = mol) mol.adopt( current_chain, setChildrenTop=1 ) for index in range( 2,number_of_atoms+2 ): residue_number = int(self.allLines[index][:5]) if residue_number!=current_residue_number:# #current_chain should adopt the current residue if there is one #create new residue res_type = self.allLines[index][5:10] residue_type = res_type.split(' ')[0] current_residue = Residue( type=residue_type, number=residue_number ) current_residue_number = residue_number if current_residue is not None: #REMEMBER TO ADOPT THE LAST ONE!!! current_chain.adopt( current_residue, setChildrenTop=1 ) n = self.allLines[index][10:15] name = n.split(' ')[-1] element = name if element in babel_elements.keys(): element = element else: if residue_type == "System" or residue_type == "SOL": #if element[1] == 'W': # element = 'H' # group is treated as one particle #else: element = element[0] elif element[:2] == 'Me': element = 'C' else: element = element[0] #if len(element)>1: # if type(element[1]) == types.StringType: # # if element[1] == element[1].lower(): # element =element # else: # element = element[0] # # else: # element = element[0] atom = Atom( name, current_residue, element, top=mol ) c = self.allLines[index][15:20] cx = self.allLines[index][20:28] cy = self.allLines[index][28:36] cz = self.allLines[index][36:44] x = float(cx)*10 y = float(cy)*10 z = float(cz)*10 atom._coords = [[x, y, z]] atom._charges = [] atom.segID = mol.name atom.normalname = name atom.number = int(self.allLines[index][15:20]) atom.elementType = name[0] mol.atmNum[atom.number] = atom atom.altname = None atom.hetatm = 0 mol.name = os.path.split(os.path.splitext(self.filename)[0])[-1] mol.allAtoms = mol.chains.residues.atoms mol.parser = self mol.levels = [Protein, Chain, Residue, Atom] name = '' for n in molList.name: name = n + ',' name = name[:-1] molList.setStringRepr( name ) strRpr = name + ':::' molList.allAtoms.setStringRepr( strRpr ) for m in molList: mname = m.name strRpr = mname + ':::' m.allAtoms.setStringRepr( strRpr ) strRpr = mname + ':' m.chains.setStringRepr( strRpr ) for c in m.chains: cname = c.id strRpr = mname + ':' + cname + ':' c.residues.setStringRepr( strRpr ) for r in c.residues: rname = r.name strRpr = mname + ':' + cname + ':' + rname + ':' r.atoms.setStringRepr( strRpr ) return molList def getMoleculeInformation(self): """ Function to retrieve the general informations on the molecule. This information is used by the molecule chooser to provide informations on the molecule selected. """ molStr = '' return molStr def configureProgressBar( self, **kw ): # this method is to be implemented by the user from outside pass if __name__ == '__main__': parser = groParser( filename='/usr/share/gromacs/tutor/methanol/conf.gro' ) print "Reading molecule" mol = parser.parse()

4,734

559

23

cd271e097e85b39119ac5d57f5185c0f3eb0adae

3,675

py

Python

webiopi_0.7.1/python/webiopi/devices/bus.py

Masterkriz/rpi3-webiopi

3c627a2769394a9cd5687e32fe779e9280c17e9b

[ "Apache-2.0" ]

63

2016-09-01T13:10:59.000Z

2021-04-28T16:00:22.000Z

webiopi_0.7.1/python/webiopi/devices/bus.py

Masterkriz/rpi3-webiopi

3c627a2769394a9cd5687e32fe779e9280c17e9b

[ "Apache-2.0" ]

56

2016-09-08T21:59:25.000Z

2021-04-29T07:44:39.000Z

services/webiopi/src/python/webiopi/devices/bus.py

creative-workflow/pi-setup

d6d28cb8d34ef71b1e8ac95dd94099bfad08837a

[ "MIT" ]

24

2016-10-30T03:20:02.000Z

2021-04-28T15:03:07.000Z

# Copyright 2012-2013 Eric Ptak - trouch.com # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os import time import subprocess from webiopi.utils.logger import debug, info BUSLIST = { "I2C": {"enabled": False, "gpio": {0:"SDA", 1:"SCL", 2:"SDA", 3:"SCL"}, "modules": ["i2c-bcm2708", "i2c-dev"]}, "SPI": {"enabled": False, "gpio": {7:"CE1", 8:"CE0", 9:"MISO", 10:"MOSI", 11:"SCLK"}, "modules": ["spi-bcm2708", "spidev"]}, "UART": {"enabled": False, "gpio": {14:"TX", 15:"RX"}}, "ONEWIRE": {"enabled": False, "gpio": {4:"DATA"}, "modules": ["w1-gpio"], "wait": 2} }

31.144068

128

0.594558

# Copyright 2012-2013 Eric Ptak - trouch.com # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os import time import subprocess from webiopi.utils.logger import debug, info BUSLIST = { "I2C": {"enabled": False, "gpio": {0:"SDA", 1:"SCL", 2:"SDA", 3:"SCL"}, "modules": ["i2c-bcm2708", "i2c-dev"]}, "SPI": {"enabled": False, "gpio": {7:"CE1", 8:"CE0", 9:"MISO", 10:"MOSI", 11:"SCLK"}, "modules": ["spi-bcm2708", "spidev"]}, "UART": {"enabled": False, "gpio": {14:"TX", 15:"RX"}}, "ONEWIRE": {"enabled": False, "gpio": {4:"DATA"}, "modules": ["w1-gpio"], "wait": 2} } def loadModule(module): debug("Loading module : %s" % module) subprocess.call(["modprobe", module]) def unloadModule(module): subprocess.call(["modprobe", "-r", module]) def loadModules(bus): if BUSLIST[bus]["enabled"] == False and not modulesLoaded(bus): info("Loading %s modules" % bus) for module in BUSLIST[bus]["modules"]: loadModule(module) if "wait" in BUSLIST[bus]: info("Sleeping %ds to let %s modules load" % (BUSLIST[bus]["wait"], bus)) time.sleep(BUSLIST[bus]["wait"]) BUSLIST[bus]["enabled"] = True def unloadModules(bus): info("Unloading %s modules" % bus) for module in BUSLIST[bus]["modules"]: unloadModule(module) BUSLIST[bus]["enabled"] = False def __modulesLoaded__(modules, lines): if len(modules) == 0: return True for line in lines: if modules[0].replace("-", "_") == line.split(" ")[0]: return __modulesLoaded__(modules[1:], lines) return False def modulesLoaded(bus): if not bus in BUSLIST or not "modules" in BUSLIST[bus]: return True try: with open("/proc/modules") as f: c = f.read() f.close() lines = c.split("\n") return __modulesLoaded__(BUSLIST[bus]["modules"], lines) except: return False def checkAllBus(): for bus in BUSLIST: if modulesLoaded(bus): BUSLIST[bus]["enabled"] = True class Bus(): def __init__(self, busName, device, flag=os.O_RDWR): loadModules(busName) self.busName = busName self.device = device self.flag = flag self.fd = 0 self.open() def open(self): self.fd = os.open(self.device, self.flag) if self.fd < 0: raise Exception("Cannot open %s" % self.device) def close(self): if self.fd > 0: os.close(self.fd) def read(self, size=1): if self.fd > 0: return os.read(self.fd, size) raise Exception("Device %s not open" % self.device) def readBytes(self, size=1): return bytearray(self.read(size)) def readByte(self): return self.readBytes()[0] def write(self, string): if self.fd > 0: return os.write(self.fd, string) raise Exception("Device %s not open" % self.device) def writeBytes(self, data): return self.write(bytearray(data)) def writeByte(self, value): self.writeBytes([value])

2,102

-9

466

11ed4453dc35a54a0bce80fd61af7da083f6ed04

1,934

py

Python

clover/core/report.py

taoyanli0808/clover

54dc4000263ab9e8873f0d429a7fe48b11fb727a

[ "Apache-2.0" ]

18

2019-07-01T04:49:33.000Z

2022-03-11T03:15:09.000Z

clover/core/report.py

taoyanli0808/clover

54dc4000263ab9e8873f0d429a7fe48b11fb727a

[ "Apache-2.0" ]

64

2019-11-20T09:33:21.000Z

2021-11-16T06:34:32.000Z

clover/core/report.py

taoyanli0808/clover

54dc4000263ab9e8873f0d429a7fe48b11fb727a

[ "Apache-2.0" ]

9

2019-10-18T08:28:26.000Z

2020-05-25T15:38:12.000Z

import datetime from clover.common import get_system_info from clover.common import friendly_datetime from clover.report.service import ReportService

30.698413

98

0.520683

import datetime from clover.common import get_system_info from clover.common import friendly_datetime from clover.report.service import ReportService class Report(object): def __init__(self, suite, trigger): """ """ self.start = datetime.datetime.now() self.end = datetime.datetime.now() self.report = { 'suite_id': suite.id, 'suite_name': suite.name, 'team': suite.team, 'project': suite.project, 'type': 'interface', 'name': trigger.report, 'platform': get_system_info(), 'valid': trigger.trigger != 'clover', 'start': friendly_datetime(self.start), 'end': friendly_datetime(self.end), 'interface': { "error": 0, "total": 0, "failed": 0, "passed": 0, "skiped": 0, "verify": 0, "percent": 0.0, } } self.service = ReportService() self.id = self.service.create(self.report) def save(self, logid): """ :param suite: :param trigger: :param details: :param logger: """ self.end = datetime.datetime.now() self.report['end'] = friendly_datetime(self.end) self.report['duration'] = (self.end - self.start).total_seconds() self.report['interface']['total'] = sum(self.report['interface'].values()) try: percent = 100 * self.report['interface']['passed'] / self.report['interface']['total'] except ZeroDivisionError: percent = 0.0 self.report['interface']['percent'] = round(percent, 2) self.report.update({ 'id': self.id, 'logid': logid, }) print(self.report) result = self.service.update(self.report) return result

0

1,758

23

6e330a1ef95d54ec31a0638b0d3c9eb66886cac5

2,027

py

Python

server/asyncEvent.py

Orienfish/flsim

f87624dee904edd7830eb41f669574b4f6c81471

[ "Apache-2.0" ]

null

server/asyncEvent.py

Orienfish/flsim

f87624dee904edd7830eb41f669574b4f6c81471

[ "Apache-2.0" ]

null

server/asyncEvent.py

Orienfish/flsim

f87624dee904edd7830eb41f669574b4f6c81471

[ "Apache-2.0" ]

2

2021-10-21T03:43:50.000Z

2022-03-26T19:19:44.000Z

class asyncGwEvent(object): """Basic async event.""" class asyncClEvent(object): """Basic async event."""

36.196429

78

0.704489

class asyncGwEvent(object): """Basic async event.""" def __init__(self, clients, gateway, download_time): # Pick the clients that are associated with the given gateway object self.clients = [client for client in clients if client.client_id in gateway.clients_id] self.gateway = gateway self.download_time = download_time max_client_delay = max([client.est_delay for client in self.clients]) self.est_delay = max_client_delay + self.gateway.est_delay_gw_to_cloud self.est_aggregate_time = self.download_time + self.est_delay def __eq__(self, other): return self.est_aggregate_time == other.est_aggregate_time def __ne__(self, other): return self.est_aggregate_time != other.est_aggregate_time def __lt__(self, other): return self.est_aggregate_time < other.est_aggregate_time def __le__(self, other): return self.est_aggregate_time <= other.est_aggregate_time def __gt__(self, other): return self.est_aggregate_time > other.est_aggregate_time def __ge__(self, other): return self.est_aggregate_time >= other.est_aggregate_time class asyncClEvent(object): """Basic async event.""" def __init__(self, client, download_time): self.client = client self.download_time = download_time self.est_aggregate_time = self.download_time + self.client.est_delay def __eq__(self, other): return self.est_aggregate_time == other.est_aggregate_time def __ne__(self, other): return self.est_aggregate_time != other.est_aggregate_time def __lt__(self, other): return self.est_aggregate_time < other.est_aggregate_time def __le__(self, other): return self.est_aggregate_time <= other.est_aggregate_time def __gt__(self, other): return self.est_aggregate_time > other.est_aggregate_time def __ge__(self, other): return self.est_aggregate_time >= other.est_aggregate_time

1,535

0

376

0323291efc8d205fb0aa73cee0fb59b5fd6e516a

345,898

py

Python

3algo/homo/1_2_7datap.py

allengrr/deadlock_project

933878077c45a7df04daa087407bb2620c064617

[ "MIT" ]

null

3algo/homo/1_2_7datap.py

allengrr/deadlock_project

933878077c45a7df04daa087407bb2620c064617

[ "MIT" ]

null

3algo/homo/1_2_7datap.py

allengrr/deadlock_project

933878077c45a7df04daa087407bb2620c064617

[ "MIT" ]

1

2021-03-21T17:54:26.000Z

wt1_2_7 = {'192.168.122.112': [6.0527, 8.4551, 7.8479, 7.6681, 7.4932, 6.4745, 6.4198, 8.2644, 10.7811, 10.3783, 9.9412, 9.5791, 9.2604, 9.4337, 9.2044, 8.9888, 8.8576, 8.6938, 8.5687, 8.4276, 8.3159, 8.203, 8.3446, 8.2226, 8.127, 8.0167, 7.9279, 7.8576, 7.9614, 7.9092, 7.8796, 7.8118, 7.747, 7.8486, 7.7813, 7.8853, 7.8253, 7.7668, 7.8695, 7.8173, 7.7653, 7.7128, 7.6701, 7.7426, 7.811, 7.8762, 7.8196, 7.7081, 7.6705, 7.6261, 7.4933, 7.4535, 7.4443, 7.4345, 7.3984, 7.3828, 7.7321, 7.6903, 7.6519, 7.6141, 7.5784, 7.928, 7.9189, 7.9659, 7.944, 7.9437, 7.913, 7.8772, 7.85, 7.8308, 7.8185, 7.792, 7.7742, 7.7612, 7.7356, 7.766, 7.7373, 7.713, 7.6905, 7.6612, 7.6402, 7.6118, 7.6528, 7.6491, 7.6283, 7.6693, 7.6482, 7.6321, 7.6127, 7.6098, 7.591, 7.5769, 7.552, 7.5301, 7.599, 7.5916, 7.5948, 7.5769, 7.5614, 7.5986, 7.6272, 7.6068, 7.5859, 7.5649, 7.5449, 7.5254, 7.5584, 7.5457, 7.5256, 7.507, 7.4923, 7.4765, 7.4653, 7.4491, 7.4337, 7.4291, 7.4144, 7.3997, 7.3822, 7.367, 7.3764, 7.3622, 7.3563, 7.3879, 7.4147, 7.4086, 7.3983, 7.3818, 7.369, 7.3627, 7.3494, 7.336, 7.3291, 7.3555, 7.3425, 7.3289, 7.3256, 7.3134, 7.3019, 7.29, 7.2769, 7.28, 7.2784, 7.2705, 7.2624, 7.2586, 7.2533, 7.242, 7.2377, 7.226, 7.2145, 7.204, 7.196, 7.1857, 7.1782, 7.1677, 7.1569, 7.147, 7.1717, 7.1647, 7.1563, 7.1466, 7.1387, 7.1084, 7.0987, 7.1237, 7.1465, 7.1378, 7.1284, 7.1282, 7.1236, 7.1152, 7.1389, 7.1315, 7.1216, 7.1144, 7.1361, 7.1283, 7.1231, 7.1165, 7.1066, 7.0985, 7.0954, 7.0867, 7.0779, 7.0714, 7.1006, 7.0915, 7.0837, 7.0782, 7.0746, 7.0937, 7.0859, 7.0775, 7.0682, 7.0611, 7.0631, 7.081, 7.1014, 7.124, 7.1425, 7.1334, 7.1285, 7.1239, 7.1184, 7.114, 7.1419, 7.1632, 7.1568, 7.1517, 7.1455, 7.1398, 7.1347, 7.1295, 7.1227, 7.1424, 7.136, 7.1334, 7.1365, 7.1313, 7.1289, 7.1205, 7.1134, 7.1061, 7.0978, 7.0911, 7.0841, 7.1017, 7.0946, 7.1373, 7.1519, 7.2006, 7.1938, 7.1872, 7.18, 7.2445, 7.2365, 7.2297, 7.2465, 7.2423, 7.2577, 7.2533, 7.2483, 7.263, 7.256, 7.3058, 7.2987, 7.2907, 7.2849, 7.2795, 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1.1, 2.6, 2.6, 2.4, 2.4, 1.0, 2.0, 0.9, 4.9, 0.3, 3.9, 0.6, 0.8, 0.6, 2.1, 2.6, 1.4, 1.7, 1.6, 1.2, 0.9, 0.8, 1.0, 1.4, 0.7, 0.8, 0.9, 1.4, 0.1, 1.5, 0.1, 4.8, 1.6, 2.7, 0.4, 2.4, 2.3, 1.2, 1.0, 2.3, 1.4, 0.8, 0.2, 0.7, 0.3, 0.3, 0.1, 1.8, 5.2, 3.2, 2.8, 1.7, 0.2, 0.0, 1.6, 1.0, 1.6, 2.2, 1.8, 1.9, 0.3, 1.2, 0.0, 0.4, 0.3, 2.2, 1.3, 3.8, 3.5, 1.2, 2.3, 0.9, 1.0, 0.1, 1.5, 0.2, 1.4, 0.4, 0.3, 0.7, 0.9, 0.3, 4.0, 4.5, 0.0, 0.1, 5.9, 5.2, 1.7, 0.9, 0.4, 0.0, 1.3, 0.1, 0.5, 1.6, 0.4, 0.3] off_mec1_2_7 = 284 off_cloud1_2_7 = 392 inward_mec1_2_7 = 222 loc1_2_7 = 635 deadlock1_2_7 = [7] memory1_2_7 = [0.2175, 0.2178, 0.2179, 0.218, 0.2182, 0.2182, 0.2182, 0.2182, 0.2183, 0.2184, 0.2184, 0.2184, 0.2184, 0.2184, 0.2188, 0.2189, 0.2189, 0.219, 0.219, 0.219, 0.219, 0.219, 0.219, 0.2191, 0.2192, 0.2192, 0.2192, 0.2192, 0.2192, 0.2192, 0.2193, 0.2193, 0.2193, 0.2193, 0.2195, 0.2195, 0.2195, 0.2195, 0.2195, 0.2195, 0.2195, 0.2196, 0.2196, 0.2196, 0.2197, 0.2197, 0.2198, 0.2198, 0.2199, 0.2199, 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0.2267, 0.2268, 0.2268, 0.2269, 0.2269, 0.2269, 0.2272, 0.2272, 0.2272, 0.2272, 0.2272, 0.2272, 0.2272, 0.2272, 0.2273, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2276, 0.2277, 0.2277, 0.2277, 0.2277, 0.2277, 0.2277, 0.2277, 0.2278, 0.2278, 0.2278, 0.2279, 0.2279, 0.228, 0.228, 0.228, 0.228, 0.228, 0.228, 0.2283, 0.2283, 0.2283, 0.2283, 0.2284, 0.2284, 0.2284] task_received1_2_7 = 1311 sent_t1_2_7 = {'125': 375, '124': 449, '126': 487} cooperate1_2_7 = {'mec': 284, 'cloud': 392} task_record1_2_7 = {} outward_mec1_2_7 = 244 offload_check1_2_7 = [197, 42] timed_out_tasks1_2_7 = 0

20,346.941176

322,402

0.621296

wt1_2_7 = {'192.168.122.112': [6.0527, 8.4551, 7.8479, 7.6681, 7.4932, 6.4745, 6.4198, 8.2644, 10.7811, 10.3783, 9.9412, 9.5791, 9.2604, 9.4337, 9.2044, 8.9888, 8.8576, 8.6938, 8.5687, 8.4276, 8.3159, 8.203, 8.3446, 8.2226, 8.127, 8.0167, 7.9279, 7.8576, 7.9614, 7.9092, 7.8796, 7.8118, 7.747, 7.8486, 7.7813, 7.8853, 7.8253, 7.7668, 7.8695, 7.8173, 7.7653, 7.7128, 7.6701, 7.7426, 7.811, 7.8762, 7.8196, 7.7081, 7.6705, 7.6261, 7.4933, 7.4535, 7.4443, 7.4345, 7.3984, 7.3828, 7.7321, 7.6903, 7.6519, 7.6141, 7.5784, 7.928, 7.9189, 7.9659, 7.944, 7.9437, 7.913, 7.8772, 7.85, 7.8308, 7.8185, 7.792, 7.7742, 7.7612, 7.7356, 7.766, 7.7373, 7.713, 7.6905, 7.6612, 7.6402, 7.6118, 7.6528, 7.6491, 7.6283, 7.6693, 7.6482, 7.6321, 7.6127, 7.6098, 7.591, 7.5769, 7.552, 7.5301, 7.599, 7.5916, 7.5948, 7.5769, 7.5614, 7.5986, 7.6272, 7.6068, 7.5859, 7.5649, 7.5449, 7.5254, 7.5584, 7.5457, 7.5256, 7.507, 7.4923, 7.4765, 7.4653, 7.4491, 7.4337, 7.4291, 7.4144, 7.3997, 7.3822, 7.367, 7.3764, 7.3622, 7.3563, 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6.8619, 0.71, 5.3821, 5.4834, 19.5286, 5.4283, 5.893, 0.8774, 7.7083, 5.388, 0.8602, 6.7475, 12.1965, 5.3527, 11.5886, 5.4119, 5.5864, 5.671, 6.418, 10.8743, 5.5268, 5.9578, 6.7575, 6.3653, 5.6207, 11.0466, 10.8755, 11.6341, 11.4682, 6.2838, 6.6051, 6.0532, 7.2143, 6.4554, 5.6536, 6.7689, 5.842, 5.6367, 6.2401, 10.4873, 11.1978, 6.2242, 10.8969, 5.6725, 5.2683, 10.8359, 5.8007, 0.7579, 5.5573, 7.1144, 5.5046, 10.6452, 5.5692, 11.0986, 0.9634, 5.4519, 5.9872, 5.5604, 6.1219, 11.1403, 6.4495, 5.4703, 6.5126, 5.5857, 6.1297, 6.7737, 11.0033, 5.8131, 5.3322, 11.6692, 22.4624, 10.5932, 11.3494, 6.835, 5.4142, 6.5007]} cpu1_2_7 = [19.4, 29.2, 0.1, 2.2, 1.0, 0.3, 0.1, 1.7, 0.5, 0.5, 0.1, 1.8, 1.3, 0.6, 0.8, 2.2, 0.3, 2.0, 2.3, 1.6, 0.3, 1.1, 0.8, 0.1, 0.4, 1.1, 1.9, 0.4, 0.4, 0.4, 0.8, 0.3, 0.9, 0.7, 0.9, 0.2, 0.2, 0.2, 0.8, 0.7, 0.6, 0.7, 0.8, 0.5, 0.3, 3.3, 3.5, 1.2, 1.4, 0.6, 0.1, 0.3, 0.5, 0.4, 0.2, 0.3, 0.6, 0.2, 0.6, 0.3, 1.6, 1.4, 0.4, 1.7, 0.7, 0.5, 0.9, 0.7, 0.5, 1.1, 0.8, 6.3, 5.9, 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1.1, 2.6, 2.6, 2.4, 2.4, 1.0, 2.0, 0.9, 4.9, 0.3, 3.9, 0.6, 0.8, 0.6, 2.1, 2.6, 1.4, 1.7, 1.6, 1.2, 0.9, 0.8, 1.0, 1.4, 0.7, 0.8, 0.9, 1.4, 0.1, 1.5, 0.1, 4.8, 1.6, 2.7, 0.4, 2.4, 2.3, 1.2, 1.0, 2.3, 1.4, 0.8, 0.2, 0.7, 0.3, 0.3, 0.1, 1.8, 5.2, 3.2, 2.8, 1.7, 0.2, 0.0, 1.6, 1.0, 1.6, 2.2, 1.8, 1.9, 0.3, 1.2, 0.0, 0.4, 0.3, 2.2, 1.3, 3.8, 3.5, 1.2, 2.3, 0.9, 1.0, 0.1, 1.5, 0.2, 1.4, 0.4, 0.3, 0.7, 0.9, 0.3, 4.0, 4.5, 0.0, 0.1, 5.9, 5.2, 1.7, 0.9, 0.4, 0.0, 1.3, 0.1, 0.5, 1.6, 0.4, 0.3] off_mec1_2_7 = 284 off_cloud1_2_7 = 392 inward_mec1_2_7 = 222 loc1_2_7 = 635 deadlock1_2_7 = [7] memory1_2_7 = [0.2175, 0.2178, 0.2179, 0.218, 0.2182, 0.2182, 0.2182, 0.2182, 0.2183, 0.2184, 0.2184, 0.2184, 0.2184, 0.2184, 0.2188, 0.2189, 0.2189, 0.219, 0.219, 0.219, 0.219, 0.219, 0.219, 0.2191, 0.2192, 0.2192, 0.2192, 0.2192, 0.2192, 0.2192, 0.2193, 0.2193, 0.2193, 0.2193, 0.2195, 0.2195, 0.2195, 0.2195, 0.2195, 0.2195, 0.2195, 0.2196, 0.2196, 0.2196, 0.2197, 0.2197, 0.2198, 0.2198, 0.2199, 0.2199, 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0.2267, 0.2268, 0.2268, 0.2269, 0.2269, 0.2269, 0.2272, 0.2272, 0.2272, 0.2272, 0.2272, 0.2272, 0.2272, 0.2272, 0.2273, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2274, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2275, 0.2276, 0.2277, 0.2277, 0.2277, 0.2277, 0.2277, 0.2277, 0.2277, 0.2278, 0.2278, 0.2278, 0.2279, 0.2279, 0.228, 0.228, 0.228, 0.228, 0.228, 0.228, 0.2283, 0.2283, 0.2283, 0.2283, 0.2284, 0.2284, 0.2284] task_received1_2_7 = 1311 sent_t1_2_7 = {'125': 375, '124': 449, '126': 487} cooperate1_2_7 = {'mec': 284, 'cloud': 392} task_record1_2_7 = {} outward_mec1_2_7 = 244 offload_check1_2_7 = [197, 42] timed_out_tasks1_2_7 = 0

0

2903eba819ddcc9c757b78bfe5e2c4b7a2171307

7,963

py

Python

snc.py

hyungkwonko/steadiness-cohesiveness

a62b6796967f2b2e79c36fb2b103f7e4ee7aa0e8

[ "MIT" ]

13

2021-06-26T07:25:11.000Z

2021-07-20T06:58:04.000Z

snc.py

hyungkwonko/steadiness-cohesiveness

a62b6796967f2b2e79c36fb2b103f7e4ee7aa0e8

[ "MIT" ]

6

2020-09-24T17:49:41.000Z

2020-10-03T14:02:59.000Z

snc.py

jeonhyun97/fimif

7964474da15c688a90a8ce9b9e648543ce5114a0

[ "MIT" ]

1

2021-07-01T18:08:36.000Z

import numpy as np import random import json import hdbscan import numba import sys from sklearn.neighbors import KDTree from pyclustering.cluster.xmeans import xmeans from helpers import distance_matrix as dm from helpers import hparam_functions as hp from helpers import visualization as vis from concurrent.futures import ThreadPoolExecutor

37.384977

110

0.571142

import numpy as np import random import json import hdbscan import numba import sys from sklearn.neighbors import KDTree from pyclustering.cluster.xmeans import xmeans from helpers import distance_matrix as dm from helpers import hparam_functions as hp from helpers import visualization as vis from concurrent.futures import ThreadPoolExecutor class SNC: def __init__( self, raw, # raw data emb, # emb data iteration=200, # iteration number walk_num_ratio=0.4, # random walk number, dist_strategy="snn", # determines the way to compute distance dist_parameter={ # parameters used to compute distance "alpha": 0.1, "k": 100 }, dist_function=None, # inject predefined distance function cluster_strategy="dbscan" # determines the way to consider clusters ): self.raw = np.array(raw, dtype=np.float64) self.emb = np.array(emb, dtype=np.float64) self.N = len(raw) # number of points self.iter = iteration self.walk_num = int(self.N * walk_num_ratio) self.dist_strategy = dist_strategy self.dist_parameter = dist_parameter self.dist_function = dist_function self.cluster_strategy = cluster_strategy ## target score self.cohev_score = None self.stead_score = None ## Distortion log self.stead_log = [] for __ in range(self.N): new_dict = { } self.stead_log.append(new_dict) self.cohev_log = [] for __ in range(self.N): new_dict = { } self.cohev_log.append(new_dict) ## Check whether the log is recorded self.finished_stead = False self.finished_cohev = False def fit(self, record_vis_info=False): self.max_compress = None self.min_compress = None self.max_stretch = None self.min_stretch = None self.record = record_vis_info self.cstrat = hp.install_hparam( self.dist_strategy, self.dist_parameter, self.dist_function, self.cluster_strategy, self.raw, self.emb ) self.max_compress, self.min_compress, self.max_stretch, self.min_stretch = self.cstrat.preprocessing() def steadiness(self): self.stead_score = self.__measure("steadiness", self.max_compress, self.min_compress) self.finished_stead = True return self.stead_score def cohesiveness(self): self.cohev_score = self.__measure("cohesiveness", self.max_stretch, self.min_stretch) self.finished_cohev = True return self.cohev_score def vis_info(self, file_path=None, label=None, k=10): ## Exception handling if not self.record: raise Exception("The record_vis_info flag currently has 'False' value.") if not self.finished_stead: raise Exception("Please compute steadiness before extracting visualization infos") if not self.finished_cohev: raise Exception("Please compute cohesiveness before extracting visualization infos") for datum_log in self.stead_log: for key_idx in datum_log: datum_log[key_idx] = datum_log[key_idx][0] / datum_log[key_idx][1] for datum_log in self.cohev_log: for key_idx in datum_log: datum_log[key_idx] = datum_log[key_idx][0] / datum_log[key_idx][1] points, missing_log, edge_vis_infos = vis.generate_visualization_data( self.stead_log, self.cohev_log, self.stead_score, self.cohev_score, label, self.raw, self.emb, k ) if file_path == None: return points, missing_log, edge_vis_infos else: if file_path[-1] == "/": file_path += "info.json" elif not (file_path[-5:] == ".json"): file_path += ".json" with open(file_path, "w") as file: json.dump({ "points": points, "missing_info": missing_log, "edge_info": edge_vis_infos }, file) def record_result(self): if self.record: for datum_log in self.stead_log: for key_idx in datum_log: datum_log[key_idx] = datum_log[key_idx][0] / datum_log[key_idx][1] for datum_log in self.cohev_log: for key_idx in datum_log: datum_log[key_idx] = datum_log[key_idx][0] / datum_log[key_idx][1] return self.stead_log, self.cohev_log else: return None, None def __measure(self, mode, max_val, min_val): distortion_sum = 0 weight_sum = 0 for _ in range(self.iter): partial_distortion_sum, partial_weight_sum = self.__measure_single_iter(mode, max_val, min_val) distortion_sum += partial_distortion_sum weight_sum += partial_weight_sum score = 1 - distortion_sum / weight_sum return score def __measure_single_iter(self, mode, max_val, min_val): cluster_indices = self.cstrat.extract_cluster(mode, self.walk_num) clustering_result = self.cstrat.clustering(mode, cluster_indices) separated_clusters = self.__separate_cluster_labels(cluster_indices, clustering_result) partial_distortion_sum = 0 partial_weight_sum = 0 for i in range(len(separated_clusters)): for j in range(i): raw_dist, emb_dist = self.cstrat.compute_distance(mode, np.array(separated_clusters[i]), np.array(separated_clusters[j])) distance = None if mode == "steadiness": distance = raw_dist - emb_dist else: distance = emb_dist - raw_dist if(distance <= 0): continue distortion = (distance - min_val) / (max_val - min_val) weight = len(separated_clusters[i]) * len(separated_clusters[j]) partial_distortion_sum += distortion * weight partial_weight_sum += weight if self.record == True: self.__record_log(mode, distortion, weight, separated_clusters[i], separated_clusters[j]) return partial_distortion_sum, partial_weight_sum def __separate_cluster_labels(self, cluster_indices, clustering_result): cluster_num = np.max(clustering_result) + 1 clusters = [] for _ in range(cluster_num): clusters.append([]) for idx, cluster_idx in enumerate(clustering_result): if cluster_idx >= 0: clusters[cluster_idx].append(cluster_indices[idx]) else: clusters.append([cluster_indices[idx]]) return clusters def __record_log(self, mode, distortion, weight, cluster_a, cluster_b): log = None if mode == "steadiness": log = self.stead_log else: ## if cohesiveness log = self.cohev_log for i in cluster_a: for j in cluster_b: if j not in log[i]: log[i][j] = [distortion * weight, 1] else: log[i][j] = [log[i][j][0] + distortion * weight, log[i][j][1] + 1] if i not in log[j]: log[j][i] = [distortion * weight, 1] else: log[j][i] = [log[j][i][0] + distortion * weight, log[j][i][1] + 1]

7,286

-11

299

fa8d31d66b14a0e8182646257c68eb38f41cd82f

3,517

py

Python

lib/turkish_nltk/trnltk/morphology/contextful/likelihoodmetrics/contextlessdistribution/contextlessdistributioncalculator.py

myasiny/wordembed

d4df516a4ac6eed71d1cc6e085638e895c525de6

[ "MIT" ]

null

lib/turkish_nltk/trnltk/morphology/contextful/likelihoodmetrics/contextlessdistribution/contextlessdistributioncalculator.py

myasiny/wordembed

d4df516a4ac6eed71d1cc6e085638e895c525de6

[ "MIT" ]

null

lib/turkish_nltk/trnltk/morphology/contextful/likelihoodmetrics/contextlessdistribution/contextlessdistributioncalculator.py

myasiny/wordembed

d4df516a4ac6eed71d1cc6e085638e895c525de6

[ "MIT" ]

null

""" Copyright 2012 Ali Ok (aliokATapacheDOTorg) Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ from __future__ import division from trnltk.morphology.contextful.likelihoodmetrics.hidden.querykeyappender import _word_parse_result_appender, _word_surface_appender

48.178082

147

0.76315

""" Copyright 2012 Ali Ok (aliokATapacheDOTorg) Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ from __future__ import division from trnltk.morphology.contextful.likelihoodmetrics.hidden.querykeyappender import _word_parse_result_appender, _word_surface_appender class ContextlessDistributionCalculator(object): def __init__(self, database_index_builder, target_form_given_context_counter, smoother): """ @type database_index_builder: DatabaseIndexBuilder @type target_form_given_context_counter: TargetFormGivenContextCounter @type smoother: ContextlessDistributionSmoother """ self._database_index_builder = database_index_builder self._target_form_given_context_counter = target_form_given_context_counter self._smoother = smoother def build_indexes(self): self._database_index_builder.create_indexes([(_word_parse_result_appender,)]) self._database_index_builder.create_indexes([(_word_surface_appender,)]) def calculate(self, target, calculation_context=None): """ Without considering context and wordforms, calculates (how many times given parse result occurs) / (how many times given parse result's surface occurs). Values are smoothed, so that we have an estimation for the parse results and surfaces that doesn't exist in the database @type target: WordFormContainer @rtype calculation_context: dict @rtype: float """ # since we ignore the syntactic category, it is better to call "surface without syn cat" "word" word_occurrence_count = self._target_form_given_context_counter._count_target_form_given_context(None, [target.get_surface()], False, None, _word_surface_appender) parse_result_occurrence_count = None if not word_occurrence_count: parse_result_occurrence_count = 0 else: parse_result_occurrence_count = self._target_form_given_context_counter._count_target_form_given_context(None, [target], False, None, _word_parse_result_appender) if calculation_context is not None: calculation_context['word_occurrence_count'] = word_occurrence_count calculation_context['parse_result_occurrence_count'] = parse_result_occurrence_count smooth_parse_result_occurrence_count = self._smoother.smooth_parse_result_occurrence_count(parse_result_occurrence_count) smooth_word_occurrence_count = self._smoother.smooth_word_occurrence_count(word_occurrence_count) smooth_likelihood = smooth_parse_result_occurrence_count / smooth_word_occurrence_count if calculation_context is not None: calculation_context['smooth_word_occurrence_count'] = smooth_word_occurrence_count calculation_context['smooth_parse_result_occurrence_count'] = smooth_parse_result_occurrence_count calculation_context['smooth_likelihood'] = smooth_likelihood return smooth_likelihood

170

2,579

23

fafae2dfa03776e286db1f07addd2a723945b066

248

py

Python

saf/nonlinear/flux.py

dmitry-kabanov/fickettmodel

255b1e9cae1cfb7a6b914ad61a17288d52215cc4

[ "MIT" ]

null

saf/nonlinear/flux.py

dmitry-kabanov/fickettmodel

255b1e9cae1cfb7a6b914ad61a17288d52215cc4

[ "MIT" ]

null

saf/nonlinear/flux.py

dmitry-kabanov/fickettmodel

255b1e9cae1cfb7a6b914ad61a17288d52215cc4

[ "MIT" ]

null

import numpy as np

19.076923

40

0.564516

import numpy as np class Flux(object): def __init__(self, npoints): """TODO: Docstring for __init__. :npoints: TODO :returns: TODO """ self.u = np.zeros(npoints) self.lamda = np.zeros(npoints)

0

206

23

6f99d3106f3bc1094a862c8c7aa78296741c8631

2,810

py

Python

jaqs/data/basic/position.py

WestXu/JAQS

3c9389afab518f188b8628af72297d750c07dfb1

[ "Apache-2.0" ]

602

2017-11-21T00:39:40.000Z

2022-03-16T06:13:08.000Z

jaqs/data/basic/position.py

WestXu/JAQS

3c9389afab518f188b8628af72297d750c07dfb1

[ "Apache-2.0" ]

63

2017-12-08T08:21:16.000Z

2020-03-07T13:57:35.000Z

jaqs/data/basic/position.py

WestXu/JAQS

3c9389afab518f188b8628af72297d750c07dfb1

[ "Apache-2.0" ]

365

2017-11-21T01:38:36.000Z

2022-03-30T15:55:30.000Z

# encoding:utf-8 class Position(object): """ Basic position class. Attributes ---------- symbol : str List of securities. side : str ("Long", "Short"). Positions of different sides will not be merged. cost_price : float Average cost price of current net position. close_pnl : float float_pnl : float trading_pnl : float holding_pnl : float init_size : int Position at the start of the day. enable_size : int Position that can be closed. frozen_size : int Positions to be closed. want_size : int Positions to be opened. pre_size : int Last day's position. today_size : int Today's position. current_size : int Current position. Methods ------- """ ''' __slots__ = ['symbol', 'side', 'cost_price', 'close_pnl', 'float_pnl', 'trading_pnl', 'holding_pnl', 'enable_size', 'frozen_size', 'want_size', 'today_size', 'pre_size', 'current_size', 'init_size', 'commission'] ''' @classmethod @classmethod class GoalPosition(object): """ Used in goal_portfolio function to generate orders. Attributes ---------- symbol : str ref_price : float Reference price, used by risk management, not by order. size : int Target position size. urgency : int The urgency to adjust position, used to determine trading algorithm. """

23.813559

79

0.552313

# encoding:utf-8 class Position(object): """ Basic position class. Attributes ---------- symbol : str List of securities. side : str ("Long", "Short"). Positions of different sides will not be merged. cost_price : float Average cost price of current net position. close_pnl : float float_pnl : float trading_pnl : float holding_pnl : float init_size : int Position at the start of the day. enable_size : int Position that can be closed. frozen_size : int Positions to be closed. want_size : int Positions to be opened. pre_size : int Last day's position. today_size : int Today's position. current_size : int Current position. Methods ------- """ ''' __slots__ = ['symbol', 'side', 'cost_price', 'close_pnl', 'float_pnl', 'trading_pnl', 'holding_pnl', 'enable_size', 'frozen_size', 'want_size', 'today_size', 'pre_size', 'current_size', 'init_size', 'commission'] ''' def __init__(self, symbol=""): self.symbol = symbol self.side = "" self.cost_price = 0.0 self.close_pnl = 0.0 self.float_pnl = 0.0 self.trading_pnl = 0.0 self.holding_pnl = 0.0 self.enable_size = 0 self.frozen_size = 0 self.want_size = 0 self.today_size = 0 self.pre_size = 0 self.current_size = 0 self.init_size = 0 self.commission = 0.0 def __repr__(self): return "{0.side:7s} {0.current_size:5d} of {0.symbol:10s}".format(self) def __str__(self): return self.__repr__() @classmethod def create_from_df(cls, df): bar_list = [] for _, row in df.iterrows(): dic = row.to_dict() bar = cls.create_from_dict(dic) bar_list.append(bar) return bar_list @classmethod def create_from_dict(cls, dic): bar = cls() bar.__dict__.update(dic) return bar class GoalPosition(object): """ Used in goal_portfolio function to generate orders. Attributes ---------- symbol : str ref_price : float Reference price, used by risk management, not by order. size : int Target position size. urgency : int The urgency to adjust position, used to determine trading algorithm. """ def __init__(self): self.symbol = "" self.ref_price = 0.0 self.size = 0 self.urgency = 0 def __repr__(self): return "{0.size:5d} of {0.symbol:10s}".format(self) def __str__(self): return self.__repr__()

1,054

0

226

7c155ca3ad86c8e2034ae70bd090f75f9ba1e72c

10,758

py

Python

conductor/conductor/controller/translator_svc.py

onap/optf-has

dd06e2675aedd7ae6344f2f51e70bbd468f36ce5

[ "Apache-2.0" ]

4

2019-02-14T19:18:09.000Z

2019-10-21T17:17:59.000Z

conductor/conductor/controller/translator_svc.py

onap/optf-has

dd06e2675aedd7ae6344f2f51e70bbd468f36ce5

[ "Apache-2.0" ]

null

conductor/conductor/controller/translator_svc.py

onap/optf-has

dd06e2675aedd7ae6344f2f51e70bbd468f36ce5

[ "Apache-2.0" ]

4

2019-05-09T07:05:54.000Z

2020-11-20T05:56:47.000Z

# # ------------------------------------------------------------------------- # Copyright (c) 2015-2017 AT&T Intellectual Property # Copyright (C) 2020 Wipro Limited. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # ------------------------------------------------------------------------- # import socket import time import cotyledon import futurist from oslo_config import cfg from oslo_log import log from conductor.common.config_loader import load_config_file from conductor.common import db_backend from conductor.common.music import messaging as music_messaging from conductor.common.utils import conductor_logging_util as log_util from conductor.controller.generic_objective_translator import GenericObjectiveTranslator from conductor.controller.translator import Translator from conductor.controller.translator_utils import TranslatorException from conductor.controller.translator_utils import VERSIONS from conductor.i18n import _LE from conductor.i18n import _LI from conductor import messaging LOG = log.getLogger(__name__) CONF = cfg.CONF CONTROLLER_OPTS = [ cfg.IntOpt('polling_interval', default=1, min=1, help='Time between checking for new plans. ' 'Default value is 1.'), cfg.IntOpt('max_translation_counter', default=1, min=1), cfg.StrOpt('opt_schema_file', default='opt_schema.json', help='json schema file which will be used to validate the ' 'optimization object for the new template version'), ] CONF.register_opts(CONTROLLER_OPTS, group='controller') class TranslatorService(cotyledon.Service): """Template Translator service. This service looks for untranslated templates and preps them for solving by the Solver service. """ # This will appear in 'ps xaf' name = "Template Translator" def __init__(self, worker_id, conf, **kwargs): """Initializer""" LOG.debug("{}".format(self.__class__.__name__)) super(TranslatorService, self).__init__(worker_id) self._init(conf, **kwargs) self.running = True def _gracefully_stop(self): """Gracefully stop working on things""" pass def millisec_to_sec(self, millisec): """Convert milliseconds to seconds""" return millisec / 1000 def _reset_template_status(self): """Reset plans being templated so they are translated again. Use this only when the translator service is not running concurrently. """ plans = self.Plan.query.get_plan_by_col("status", self.Plan.TRANSLATING) for the_plan in plans: the_plan.status = self.Plan.TEMPLATE # Use only in active-passive mode, so don't have to be atomic the_plan.update() def _restart(self): """Prepare to restart the service""" pass def current_time_seconds(self): """Current time in milliseconds.""" return int(round(time.time())) def setup_rpc(self, conf, topic): """Set up the RPC Client""" # TODO(jdandrea): Put this pattern inside music_messaging? transport = messaging.get_transport(conf=conf) target = music_messaging.Target(topic=topic) client = music_messaging.RPCClient(conf=conf, transport=transport, target=target) return client def translate(self, plan): """Translate the plan to a format the solver can use""" # Update the translation field and set status to TRANSLATED. try: LOG.info(_LI("Requesting plan {} translation").format( plan.id)) template_version = plan.template.get("homing_template_version") if template_version in VERSIONS['BASE']: trns = Translator(self.conf, plan.name, plan.id, plan.template) elif template_version in VERSIONS['GENERIC']: trns = GenericObjectiveTranslator(self.conf, plan.name, plan.id, plan.template, self.opt_schema) else: raise TranslatorException( "conductor_template_version must be one " "of: {}".format(', '.join([x for v in VERSIONS.values() for x in v]))) trns.translate() if trns.ok: plan.translation = trns.translation plan.status = self.Plan.TRANSLATED LOG.info(_LI( "Plan {} translated. Ready for solving").format( plan.id)) LOG.info(_LI( "Plan name: {}").format( plan.name)) else: plan.message = trns.error_message plan.status = self.Plan.ERROR LOG.error(_LE( "Plan {} translation error encountered").format( plan.id)) except Exception as ex: template = "An exception of type {0} occurred, arguments:\n{1!r}" plan.message = template.format(type(ex).__name__, ex.args) plan.status = self.Plan.ERROR _is_success = 'FAILURE' while 'FAILURE' in _is_success and (self.current_time_seconds() - self.millisec_to_sec(plan.updated)) \ <= self.conf.messaging_server.timeout: _is_success = plan.update(condition=self.translation_owner_condition) LOG.info(_LI("Changing the template status from translating to {}, " "atomic update response from MUSIC {}").format(plan.status, _is_success)) def __check_for_templates(self): """Wait for the polling interval, then do the real template check.""" # Wait for at least poll_interval sec polling_interval = self.conf.controller.polling_interval time.sleep(polling_interval) # Look for plans with the status set to TEMPLATE # Instead of using the query.all() method, now creating an index for 'status' # field in conductor.plans table, and query plans by status columns template_plans = self.Plan.query.get_plan_by_col("status", self.Plan.TEMPLATE) translating_plans = self.Plan.query.get_plan_by_col("status", self.Plan.TRANSLATING) # combine the plans with status = 'template' and 'translating' together plans = template_plans + translating_plans for plan in plans: # If there's a template to be translated, do it! if plan.status == self.Plan.TEMPLATE: if plan.translation_counter >= self.conf.controller.max_translation_counter: message = _LE("Tried {} times. Plan {} is unable to translate") \ .format(self.conf.controller.max_translation_counter, plan.id) plan.message = message plan.status = self.Plan.ERROR plan.update(condition=self.template_status_condition) LOG.error(message) break else: # change the plan status to "translating" and assign the current machine as translation owner plan.status = self.Plan.TRANSLATING plan.translation_counter += 1 plan.translation_owner = socket.gethostname() plan.translation_begin_timestamp = int(round(time.time() * 1000)) _is_updated = plan.update(condition=self.template_status_condition) log_util.setLoggerFilter(LOG, self.conf.keyspace, plan.id) LOG.info(_LE("Plan {} is trying to update the status from 'template' to 'translating'," " get {} response from MUSIC").format(plan.id, _is_updated)) if not _is_updated: break if _is_updated and 'SUCCESS' in _is_updated: self.translate(plan) break # TODO(larry): sychronized clock among Conducotr VMs, or use an offset elif plan.status == self.Plan.TRANSLATING and (self.current_time_seconds() - self.millisec_to_sec(plan.updated)) \ > self.conf.messaging_server.timeout: plan.status = self.Plan.TEMPLATE plan.update(condition=self.translating_status_condition) break elif plan.timedout: # TODO(jdandrea): How to tell all involved to stop working? # Not enough to just set status. continue def run(self): """Run""" LOG.debug("{}".format(self.__class__.__name__)) # Look for templates to translate from within a thread executor = futurist.ThreadPoolExecutor() while self.running: fut = executor.submit(self.__check_for_templates) fut.result() executor.shutdown() def terminate(self): """Terminate""" LOG.debug("{}".format(self.__class__.__name__)) self.running = False self._gracefully_stop() super(TranslatorService, self).terminate() def reload(self): """Reload""" LOG.debug("{}".format(self.__class__.__name__)) self._restart()

39.844444

113

0.604109

# # ------------------------------------------------------------------------- # Copyright (c) 2015-2017 AT&T Intellectual Property # Copyright (C) 2020 Wipro Limited. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # ------------------------------------------------------------------------- # import socket import time import cotyledon import futurist from oslo_config import cfg from oslo_log import log from conductor.common.config_loader import load_config_file from conductor.common import db_backend from conductor.common.music import messaging as music_messaging from conductor.common.utils import conductor_logging_util as log_util from conductor.controller.generic_objective_translator import GenericObjectiveTranslator from conductor.controller.translator import Translator from conductor.controller.translator_utils import TranslatorException from conductor.controller.translator_utils import VERSIONS from conductor.i18n import _LE from conductor.i18n import _LI from conductor import messaging LOG = log.getLogger(__name__) CONF = cfg.CONF CONTROLLER_OPTS = [ cfg.IntOpt('polling_interval', default=1, min=1, help='Time between checking for new plans. ' 'Default value is 1.'), cfg.IntOpt('max_translation_counter', default=1, min=1), cfg.StrOpt('opt_schema_file', default='opt_schema.json', help='json schema file which will be used to validate the ' 'optimization object for the new template version'), ] CONF.register_opts(CONTROLLER_OPTS, group='controller') class TranslatorService(cotyledon.Service): """Template Translator service. This service looks for untranslated templates and preps them for solving by the Solver service. """ # This will appear in 'ps xaf' name = "Template Translator" def __init__(self, worker_id, conf, **kwargs): """Initializer""" LOG.debug("{}".format(self.__class__.__name__)) super(TranslatorService, self).__init__(worker_id) self._init(conf, **kwargs) self.running = True def _init(self, conf, **kwargs): self.conf = conf self.Plan = kwargs.get('plan_class') self.kwargs = kwargs self.opt_schema = load_config_file(str(self.conf.controller.opt_schema_file)) # Set up the RPC service(s) we want to talk to. self.data_service = self.setup_rpc(conf, "data") # Set up Music access. self.music = db_backend.get_client() self.translation_owner_condition = { "translation_owner": socket.gethostname() } self.template_status_condition = { "status": self.Plan.TEMPLATE } self.translating_status_condition = { "status": self.Plan.TRANSLATING } if not self.conf.controller.concurrent: self._reset_template_status() def _gracefully_stop(self): """Gracefully stop working on things""" pass def millisec_to_sec(self, millisec): """Convert milliseconds to seconds""" return millisec / 1000 def _reset_template_status(self): """Reset plans being templated so they are translated again. Use this only when the translator service is not running concurrently. """ plans = self.Plan.query.get_plan_by_col("status", self.Plan.TRANSLATING) for the_plan in plans: the_plan.status = self.Plan.TEMPLATE # Use only in active-passive mode, so don't have to be atomic the_plan.update() def _restart(self): """Prepare to restart the service""" pass def current_time_seconds(self): """Current time in milliseconds.""" return int(round(time.time())) def setup_rpc(self, conf, topic): """Set up the RPC Client""" # TODO(jdandrea): Put this pattern inside music_messaging? transport = messaging.get_transport(conf=conf) target = music_messaging.Target(topic=topic) client = music_messaging.RPCClient(conf=conf, transport=transport, target=target) return client def translate(self, plan): """Translate the plan to a format the solver can use""" # Update the translation field and set status to TRANSLATED. try: LOG.info(_LI("Requesting plan {} translation").format( plan.id)) template_version = plan.template.get("homing_template_version") if template_version in VERSIONS['BASE']: trns = Translator(self.conf, plan.name, plan.id, plan.template) elif template_version in VERSIONS['GENERIC']: trns = GenericObjectiveTranslator(self.conf, plan.name, plan.id, plan.template, self.opt_schema) else: raise TranslatorException( "conductor_template_version must be one " "of: {}".format(', '.join([x for v in VERSIONS.values() for x in v]))) trns.translate() if trns.ok: plan.translation = trns.translation plan.status = self.Plan.TRANSLATED LOG.info(_LI( "Plan {} translated. Ready for solving").format( plan.id)) LOG.info(_LI( "Plan name: {}").format( plan.name)) else: plan.message = trns.error_message plan.status = self.Plan.ERROR LOG.error(_LE( "Plan {} translation error encountered").format( plan.id)) except Exception as ex: template = "An exception of type {0} occurred, arguments:\n{1!r}" plan.message = template.format(type(ex).__name__, ex.args) plan.status = self.Plan.ERROR _is_success = 'FAILURE' while 'FAILURE' in _is_success and (self.current_time_seconds() - self.millisec_to_sec(plan.updated)) \ <= self.conf.messaging_server.timeout: _is_success = plan.update(condition=self.translation_owner_condition) LOG.info(_LI("Changing the template status from translating to {}, " "atomic update response from MUSIC {}").format(plan.status, _is_success)) def __check_for_templates(self): """Wait for the polling interval, then do the real template check.""" # Wait for at least poll_interval sec polling_interval = self.conf.controller.polling_interval time.sleep(polling_interval) # Look for plans with the status set to TEMPLATE # Instead of using the query.all() method, now creating an index for 'status' # field in conductor.plans table, and query plans by status columns template_plans = self.Plan.query.get_plan_by_col("status", self.Plan.TEMPLATE) translating_plans = self.Plan.query.get_plan_by_col("status", self.Plan.TRANSLATING) # combine the plans with status = 'template' and 'translating' together plans = template_plans + translating_plans for plan in plans: # If there's a template to be translated, do it! if plan.status == self.Plan.TEMPLATE: if plan.translation_counter >= self.conf.controller.max_translation_counter: message = _LE("Tried {} times. Plan {} is unable to translate") \ .format(self.conf.controller.max_translation_counter, plan.id) plan.message = message plan.status = self.Plan.ERROR plan.update(condition=self.template_status_condition) LOG.error(message) break else: # change the plan status to "translating" and assign the current machine as translation owner plan.status = self.Plan.TRANSLATING plan.translation_counter += 1 plan.translation_owner = socket.gethostname() plan.translation_begin_timestamp = int(round(time.time() * 1000)) _is_updated = plan.update(condition=self.template_status_condition) log_util.setLoggerFilter(LOG, self.conf.keyspace, plan.id) LOG.info(_LE("Plan {} is trying to update the status from 'template' to 'translating'," " get {} response from MUSIC").format(plan.id, _is_updated)) if not _is_updated: break if _is_updated and 'SUCCESS' in _is_updated: self.translate(plan) break # TODO(larry): sychronized clock among Conducotr VMs, or use an offset elif plan.status == self.Plan.TRANSLATING and (self.current_time_seconds() - self.millisec_to_sec(plan.updated)) \ > self.conf.messaging_server.timeout: plan.status = self.Plan.TEMPLATE plan.update(condition=self.translating_status_condition) break elif plan.timedout: # TODO(jdandrea): How to tell all involved to stop working? # Not enough to just set status. continue def run(self): """Run""" LOG.debug("{}".format(self.__class__.__name__)) # Look for templates to translate from within a thread executor = futurist.ThreadPoolExecutor() while self.running: fut = executor.submit(self.__check_for_templates) fut.result() executor.shutdown() def terminate(self): """Terminate""" LOG.debug("{}".format(self.__class__.__name__)) self.running = False self._gracefully_stop() super(TranslatorService, self).terminate() def reload(self): """Reload""" LOG.debug("{}".format(self.__class__.__name__)) self._restart()

784

0

27

100224c5e87268947545ef064b470a911e6290c0

1,266

py

Python

src/findenum.py

WOWZON3/RoseOnline

ec17901400fedb1a4705a8a8bb69925910c5b0cd

[ "Apache-2.0" ]

1

2020-03-09T22:19:26.000Z

src/findenum.py

WOWZON3/RoseOnline

ec17901400fedb1a4705a8a8bb69925910c5b0cd

[ "Apache-2.0" ]

null

src/findenum.py

WOWZON3/RoseOnline

ec17901400fedb1a4705a8a8bb69925910c5b0cd

[ "Apache-2.0" ]

null

#!/bin/python3 enum = {} previousValue = None with open("rosecommon/include/epackettype.h", "r") as f: for i in range(46): f.readline() for line in f: if "};" in line: break name, value = parse(line) if value: enum[name] = value while True: value = input("Enter the hex value of the packet: ") for name, v in enum.items(): if int(value, 16) == v: if "PAKCS" in name: print("Sent by client :", name) else: print("Sent by server :", name)

25.32

56

0.50237

#!/bin/python3 enum = {} previousValue = None def parse(line): global previousValue line = line.strip() if len(line) == 0: return None, None id = line.find("//") if id != -1: line = line[:id] line = line.strip() line = line[:-1] line = line.split("=") line[0] = line[0].strip() if len(line[0]) == 0: return None, None if len(line) < 2: if previousValue is None: exit(-1) previousValue += 1 line.append("%x" % previousValue) else: line[1] = line[1].strip() try: previousValue = int(line[1], 16) except ValueError: return line[0], enum[line[1]] return line[0], int(line[1], 16) with open("rosecommon/include/epackettype.h", "r") as f: for i in range(46): f.readline() for line in f: if "};" in line: break name, value = parse(line) if value: enum[name] = value while True: value = input("Enter the hex value of the packet: ") for name, v in enum.items(): if int(value, 16) == v: if "PAKCS" in name: print("Sent by client :", name) else: print("Sent by server :", name)

668

0

23

07f45e7eb5d042bbd5cc5645219b308998496484

15,270

py

Python

addon_common/common/utils.py

senjacob/retopoflow

7817bb7d68f98e5ae2c7835f28eeafe76367789e

[ "OML" ]

null

addon_common/common/utils.py

senjacob/retopoflow

7817bb7d68f98e5ae2c7835f28eeafe76367789e

[ "OML" ]

null

addon_common/common/utils.py

senjacob/retopoflow

7817bb7d68f98e5ae2c7835f28eeafe76367789e

[ "OML" ]

null

''' Copyright (C) 2021 CG Cookie http://cgcookie.com [email protected] Created by Jonathan Denning, Jonathan Williamson This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see <http://www.gnu.org/licenses/>. ''' import os import re import sys import glob import inspect import operator import itertools import importlib import bpy from mathutils import Vector, Matrix from .blender import get_preferences from .profiler import profiler from .debug import dprint, debugger from .maths import ( Point, Direction, Normal, Frame, Point2D, Vec2D, Direction2D, Ray, XForm, BBox, Plane ) ################################################## # find functions of object that has key attribute # returns list of (attribute value, fn) ################################################## StructRNA = bpy.types.bpy_struct registered_objects = {} ################################################# ######################################################### ######################################################### ######################################################### ################################################# ################################################# def join(sep, iterable, preSep='', postSep='', toStr=str): ''' this function adds features on to sep.join(iterable) if iterable is not empty, preSep is prepended and postSep is appended also, all items of iterable are turned to strings using toStr, which can be customized ex: join(', ', [1,2,3]) => '1, 2, 3' ex: join('.', ['foo', 'bar'], preSep='.') => '.foo.bar' ''' s = sep.join(map(toStr, iterable)) if not s: return '' return f'{preSep}{s}{postSep}' def get_matrices(ob): ''' obtain blender object matrices ''' mx = ob.matrix_world imx = mx.inverted() return [mx, imx] class Dict(): ''' a fancy dictionary object '''

33.123644

97

0.576228

''' Copyright (C) 2021 CG Cookie http://cgcookie.com [email protected] Created by Jonathan Denning, Jonathan Williamson This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see <http://www.gnu.org/licenses/>. ''' import os import re import sys import glob import inspect import operator import itertools import importlib import bpy from mathutils import Vector, Matrix from .blender import get_preferences from .profiler import profiler from .debug import dprint, debugger from .maths import ( Point, Direction, Normal, Frame, Point2D, Vec2D, Direction2D, Ray, XForm, BBox, Plane ) ################################################## # find functions of object that has key attribute # returns list of (attribute value, fn) def find_fns(obj, key): cls = type(obj) fn_type = type(find_fns) members = [getattr(cls, k) for k in dir(cls)] methods = [member for member in members if type(member) == fn_type] return [ (getattr(method, key), method) for method in methods if hasattr(method, key) ] ################################################## StructRNA = bpy.types.bpy_struct def still_registered(self, oplist): if getattr(still_registered, 'is_broken', False): return False def is_registered(): cur = bpy.ops for n in oplist: if not hasattr(cur, n): return False cur = getattr(cur, n) try: StructRNA.path_resolve(self, "properties") except: print('no properties!') return False return True if is_registered(): return True still_registered.is_broken = True print('bpy.ops.%s is no longer registered!' % '.'.join(oplist)) return False registered_objects = {} def registered_object_add(self): global registered_objects opid = self.operator_id print('Registering bpy.ops.%s' % opid) registered_objects[opid] = (self, opid.split('.')) def registered_check(): global registered_objects return all(still_registered(s, o) for (s, o) in registered_objects.values()) ################################################# def find_and_import_all_subclasses(cls, root_path=None): here_path = os.path.realpath(os.path.dirname(__file__)) if root_path is None: root_path = os.path.realpath(os.path.join(here_path, '..')) touched_paths = set() found_subclasses = set() def search(root): nonlocal touched_paths, found_subclasses, here_path root = os.path.realpath(root) if root in touched_paths: return touched_paths.add(root) relpath = os.path.relpath(root, here_path) #print(' relpath: %s' % relpath) for path in glob.glob(os.path.join(root, '*')): if os.path.isdir(path): if not path.endswith('__pycache__'): search(path) continue if os.path.splitext(path)[1] != '.py': continue try: pyfile = os.path.splitext(os.path.basename(path))[0] if pyfile == '__init__': continue pyfile = os.path.join(relpath, pyfile) pyfile = re.sub(r'\\', '/', pyfile) if pyfile.startswith('./'): pyfile = pyfile[2:] level = pyfile.count('..') pyfile = re.sub(r'^(\.\./)*', '', pyfile) pyfile = re.sub('/', '.', pyfile) #print(' Searching: %s (%d, %s)' % (pyfile, level, path)) try: tmp = importlib.__import__(pyfile, globals(), locals(), [], level=level+1) except Exception as e: print('Caught exception while attempting to search for classes') print(' cls: %s' % str(cls)) print(' pyfile: %s' % pyfile) print(' %s' % str(e)) #print(' Could not import') continue for tk in dir(tmp): m = getattr(tmp, tk) if not inspect.ismodule(m): continue for k in dir(m): v = getattr(m, k) if not inspect.isclass(v): continue if v is cls: continue if not issubclass(v, cls): continue # v is a subclass of cls, so add it to the global namespace #print(' Found %s in %s' % (str(v), pyfile)) globals()[k] = v found_subclasses.add(v) except Exception as e: print('Exception occurred while searching %s' % path) debugger.print_exception() #print('Searching for class %s' % str(cls)) #print(' cwd: %s' % os.getcwd()) #print(' Root: %s' % root_path) search(root_path) return found_subclasses ######################################################### def delay_exec(action, f_globals=None, f_locals=None, ordered_parameters=None, precall=None): if f_globals is None or f_locals is None: frame = inspect.currentframe().f_back # get frame of calling function if f_globals is None: f_globals = frame.f_globals # get globals of calling function if f_locals is None: f_locals = frame.f_locals # get locals of calling function def run_it(*args, **kwargs): # args are ignored!? nf_locals = dict(f_locals) if ordered_parameters: for k,v in zip(ordered_parameters, args): nf_locals[k] = v nf_locals.update(kwargs) try: if precall: precall(nf_locals) return exec(action, f_globals, nf_locals) except Exception as e: print('Caught exception while trying to run a delay_exec') print(' action:', action) print(' except:', e) raise e return run_it ######################################################### def git_info(start_at_caller=True): if start_at_caller: path_root = os.path.abspath(inspect.stack()[1][1]) else: path_root = os.path.abspath(os.path.dirname(__file__)) try: path_git_head = None while path_root: path_test = os.path.join(path_root, '.git', 'HEAD') if os.path.exists(path_test): # found it! path_git_head = path_test break if os.path.split(path_root)[1] in {'addons', 'addons_contrib'}: break path_root = os.path.dirname(path_root) # try next level up if not path_git_head: # could not find .git folder return None path_git_ref = open(path_git_head).read().split()[1] if not path_git_ref.startswith('refs/heads/'): print('git detected, but HEAD uses unexpected format') return None path_git_ref = path_git_ref[len('refs/heads/'):] git_ref_fullpath = os.path.join(path_root, '.git', 'logs', 'refs', 'heads', path_git_ref) if not os.path.exists(git_ref_fullpath): print('git detected, but could not find ref file %s' % git_ref_fullpath) return None log = open(git_ref_fullpath).read().splitlines() commit = log[-1].split()[1] return ('%s %s' % (path_git_ref, commit)) except Exception as e: print('An exception occurred while checking git info') print(e) return None ######################################################### def kwargopts(kwargs, defvals=None, **mykwargs): opts = defvals.copy() if defvals else {} opts.update(mykwargs) opts.update(kwargs) if 'opts' in kwargs: opts.update(opts['opts']) def factory(): class Opts(): ''' pretend to be a dictionary, but also add . access fns ''' def __init__(self): self.touched = set() def __getattr__(self, opt): self.touched.add(opt) return opts[opt] def __getitem__(self, opt): self.touched.add(opt) return opts[opt] def __len__(self): return len(opts) def has_key(self, opt): return opt in opts def keys(self): return opts.keys() def values(self): return opts.values() def items(self): return opts.items() def __contains__(self, opt): return opt in opts def __iter__(self): return iter(opts) def print_untouched(self): print('untouched: %s' % str(set(opts.keys()) - self.touched)) def pass_through(self, *args): return {key:self[key] for key in args} return Opts() return factory() def kwargs_translate(key_from, key_to, kwargs): if key_from in kwargs: kwargs[key_to] = kwargs[key_from] del kwargs[key_from] def kwargs_splitter(keys, kwargs): if type(keys) is str: keys = [keys] kw = {k:v for (k,v) in kwargs.items() if k in keys} for k in keys: if k in kwargs: del kwargs[k] return kw def any_args(*args): return any(bool(a) for a in args) def get_and_discard(d, k, default=None): if k not in d: return default v = d[k] del d[k] return v ################################################# def abspath(*args, frame_depth=1, **kwargs): frame = inspect.currentframe() for i in range(frame_depth): frame = frame.f_back module = inspect.getmodule(frame) path = os.path.dirname(module.__file__) return os.path.abspath(os.path.join(path, *args, **kwargs)) ################################################# def strshort(s, l=50): s = str(s) return s[:l] + ('...' if len(s) > l else '') def join(sep, iterable, preSep='', postSep='', toStr=str): ''' this function adds features on to sep.join(iterable) if iterable is not empty, preSep is prepended and postSep is appended also, all items of iterable are turned to strings using toStr, which can be customized ex: join(', ', [1,2,3]) => '1, 2, 3' ex: join('.', ['foo', 'bar'], preSep='.') => '.foo.bar' ''' s = sep.join(map(toStr, iterable)) if not s: return '' return f'{preSep}{s}{postSep}' def accumulate_last(iterable, *args, **kwargs): # returns last result when accumulating # https://docs.python.org/3.7/library/itertools.html#itertools.accumulate final = None for step in itertools.accumulate(iterable, *args, **kwargs): final = step return final def selection_mouse(): select_type = get_preferences().inputs.select_mouse return ['%sMOUSE' % select_type, 'SHIFT+%sMOUSE' % select_type] def get_settings(): if not hasattr(get_settings, 'cache'): addons = get_preferences().addons folderpath = os.path.dirname(os.path.abspath(__file__)) while folderpath: folderpath,foldername = os.path.split(folderpath) if foldername in {'lib','addons', 'addons_contrib'}: continue if foldername in addons: break else: assert False, 'Could not find non-"lib" folder' if not addons[foldername].preferences: return None get_settings.cache = addons[foldername].preferences return get_settings.cache def get_dpi(): system_preferences = get_preferences().system factor = getattr(system_preferences, "pixel_size", 1) return int(system_preferences.dpi * factor) def get_dpi_factor(): return get_dpi() / 72 def blender_version(): major,minor,rev = bpy.app.version # '%03d.%03d.%03d' % (major, minor, rev) return '%d.%02d' % (major,minor) def iter_head(i, default=None): try: return next(iter(i)) except StopIteration: return default def iter_running_sum(lw): s = 0 for w in lw: s += w yield (w,s) def iter_pairs(items, wrap, repeat=False): if not items: return while True: for i0,i1 in zip(items[:-1],items[1:]): yield i0,i1 if wrap: yield items[-1],items[0] if not repeat: return def rotate_cycle(cycle, offset): l = len(cycle) return [cycle[(l + ((i - offset) % l)) % l] for i in range(l)] def max_index(vals, key=None): if not key: return max(enumerate(vals), key=lambda ival:ival[1])[0] return max(enumerate(vals), key=lambda ival:key(ival[1]))[0] def min_index(vals, key=None): if not key: return min(enumerate(vals), key=lambda ival:ival[1])[0] return min(enumerate(vals), key=lambda ival:key(ival[1]))[0] def shorten_floats(s): # reduces number of digits (for float) found in a string # useful for reducing noise of printing out a Vector, Buffer, Matrix, etc. s = re.sub(r'(?P<neg>-?)(?P<d0>\d)\.(?P<d1>\d)\d\d+e-02', r'\g<neg>0.0\g<d0>\g<d1>', s) s = re.sub(r'(?P<neg>-?)(?P<d0>\d)\.\d\d\d+e-03', r'\g<neg>0.00\g<d0>', s) s = re.sub(r'-?\d\.\d\d\d+e-0[4-9]', r'0.000', s) s = re.sub(r'-?\d\.\d\d\d+e-[1-9]\d', r'0.000', s) s = re.sub(r'(?P<digs>\d\.\d\d\d)\d+', r'\g<digs>', s) return s def get_matrices(ob): ''' obtain blender object matrices ''' mx = ob.matrix_world imx = mx.inverted() return [mx, imx] class AddonLocator(object): def __init__(self, f=None): self.fullInitPath = f if f else __file__ self.FolderPath = os.path.dirname(self.fullInitPath) self.FolderName = os.path.basename(self.FolderPath) def AppendPath(self): sys.path.append(self.FolderPath) print("Addon path has been registered into system path for this session") class UniqueCounter(): __counter = 0 @staticmethod def next(): UniqueCounter.__counter += 1 return UniqueCounter.__counter class Dict(): ''' a fancy dictionary object ''' def __init__(self, *args, **kwargs): self.__dict__['__d'] = {} self.set(*args, **kwargs) def __getitem__(self, k): return self.__dict__['__d'][k] def __setitem__(self, k, v): self.__dict__['__d'][k] = v return v def __delitem__(self, k): del self.__dict__['__d'][k] def __getattr__(self, k): return self.__dict__['__d'][k] def __setattr__(self, k, v): self.__dict__['__d'][k] = v return v def __delattr__(self, k): del self.__dict__['__d'][k] def set(self, d=None, **kwargs): if d: for k,v in d.items(): self[k] = v for k,v in kwargs.items(): self[k] = v def __str__(self): return str(self.__dict__['__d']) def __repr__(self): return repr(self.__dict__['__d'])

11,736

69

977

9751201d5d87e45e65a5fb9c8931abc18fb84269

1,575

py

Python

src/speech_distillation/custom_discriminator.py

AlonKellner/hifi-gan

e842836a0c879289c1848e922695ea1117715739

[ "MIT" ]

null

src/speech_distillation/custom_discriminator.py

AlonKellner/hifi-gan

e842836a0c879289c1848e922695ea1117715739

[ "MIT" ]

null

src/speech_distillation/custom_discriminator.py

AlonKellner/hifi-gan

e842836a0c879289c1848e922695ea1117715739

[ "MIT" ]

null

import torch import torch.nn as nn import torch.nn.functional as f

38.414634

105

0.645079

import torch import torch.nn as nn import torch.nn.functional as f class AllInOneDiscriminator(nn.Module): def __init__(self, pre_model, blocks, post_model): super(AllInOneDiscriminator, self).__init__() self.pre_model = pre_model self.blocks = blocks self.post_model = post_model def forward(self, raw): x = self.pre_model(raw) for block in self.blocks: x = block(x, raw) return self.post_model(x) class AllInOneBlock(nn.Module): def __init__(self, before_block, raw_blocks, after_block, padding_mode='constant', padding_value=0): super(AllInOneBlock, self).__init__() self.before_block = before_block self.raw_blocks = raw_blocks if raw_blocks is not None else [] self.after_block = after_block self.padding_mode = padding_mode self.padding_value = padding_value def forward(self, x, raw): x = self.before_block(x) processed_raw_results = [raw_block(raw) for raw_block in self.raw_blocks] all_results = [x, *processed_raw_results] lengths = [result.size()[2] for result in all_results] max_length = max(lengths) paddings = [max_length - length for length in lengths] padded_results = [f.pad(result, (0, padding), self.padding_mode, self.padding_value) for result, padding in zip(all_results, paddings)] concatted = torch.cat(padded_results, dim=1) x = self.after_block(concatted) return x

1,311

28

162

1946612015dd895b8e3ea0ba5a88d89c172ea93a

279

py

Python

hrsalespipes/system/templatetags/custom_tags.py

hanztura/hrsalespipes

77accf3132726ced05d84fa2a41891b841f310b8

[ "Apache-2.0" ]

3

2020-03-26T12:43:43.000Z

2021-05-10T14:35:51.000Z

hrsalespipes/system/templatetags/custom_tags.py

hanztura/hrsalespipes

77accf3132726ced05d84fa2a41891b841f310b8

[ "Apache-2.0" ]

5

2021-04-08T21:15:15.000Z

2022-02-10T11:03:12.000Z

hrsalespipes/system/templatetags/custom_tags.py

hanztura/hrsalespipes

77accf3132726ced05d84fa2a41891b841f310b8

[ "Apache-2.0" ]

1

2022-01-30T19:24:48.000Z

import json from django import template from django.utils.html import mark_safe register = template.Library() @register.simple_tag

21.461538

65

0.792115

import json from django import template from django.utils.html import mark_safe register = template.Library() @register.simple_tag def many_to_many_uuid_to_string(values): values_in_json = json.dumps([str(value) for value in values]) return mark_safe(values_in_json)

122

0

22

9f2b74ad866744c30cd1f3b15f739ae2f576a5f0

1,874

py

Python

organisations/factories.py

City-of-Helsinki/palvelutarjotin

4ad67cbf4062832aba8080cb96ac785bdbbe9aa8

[ "MIT" ]

2

2020-11-10T16:31:26.000Z

2021-02-19T10:33:27.000Z

organisations/factories.py

City-of-Helsinki/palvelutarjotin

4ad67cbf4062832aba8080cb96ac785bdbbe9aa8

[ "MIT" ]

239

2020-04-23T07:36:17.000Z

2022-03-15T08:38:38.000Z

organisations/factories.py

City-of-Helsinki/palvelutarjotin

4ad67cbf4062832aba8080cb96ac785bdbbe9aa8

[ "MIT" ]

null

import factory from django.contrib.auth import get_user_model from organisations.models import Organisation, OrganisationProposal, Person

28.830769

83

0.696905

import factory from django.contrib.auth import get_user_model from organisations.models import Organisation, OrganisationProposal, Person def fake_id_array(): from faker import Faker fake = Faker() return fake.pylist(3, True, "str") class UserFactory(factory.django.DjangoModelFactory): first_name = factory.Faker("first_name") last_name = factory.Faker("last_name") username = factory.Faker("user_name") email = factory.Faker("email") class Meta: model = get_user_model() class PersonFactory(factory.django.DjangoModelFactory): user = factory.SubFactory(UserFactory) name = factory.Faker("name") phone_number = factory.Faker("phone_number") email_address = factory.Faker("email") place_ids = factory.LazyFunction(fake_id_array) class Meta: model = Person @factory.post_generation def organisations(self, create, extracted, **kwargs): if not create: # Simple build, do nothing. return if extracted: # A list of organisations were passed in, use them for organisation in extracted: self.organisations.add(organisation) class OrganisationFactory(factory.django.DjangoModelFactory): name = factory.Faker("company") phone_number = factory.Faker("phone_number") type = factory.Faker( "random_element", elements=[t[0] for t in Organisation.ORGANISATION_TYPES], ) publisher_id = factory.Faker("pystr", max_chars=5) class Meta: model = Organisation class OrganisationProposalFactory(factory.django.DjangoModelFactory): name = factory.Faker("company") description = factory.Faker("text", max_nb_chars=255) phone_number = factory.Faker("phone_number") applicant = factory.SubFactory(PersonFactory) class Meta: model = OrganisationProposal

382

1,234

115