= 1:","as nn from torch.autograd import Variable import functools from . import net_blocks as","decoder.append(up) self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder) return def forward(self, input): img_enc = self.encoder(input) img_dec",">= 3: x = self.resnet.layer3(x) if n_blocks >= 4: x = self.resnet.layer4(x) return","from absl import app from absl import flags import os import os.path as","flags import os import os.path as osp import numpy as np import torch","torch.autograd import Variable import functools from . import net_blocks as nb import pdb","nn from torch.autograd import Variable import functools from . import net_blocks as nb","ResNetConcatGenerator(nn.Module): def __init__(self, input_nc, output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder = ResnetEncoder(n_blocks=n_blocks) self.n_blocks","if n_blocks == 3: inner_nc = 256 nlayers = 4 elif n_blocks ==","= 5 for lx in range(nlayers): outnc = max(inner_nc // 2, 16) up","kernel_size=3, stride=1, padding=1, bias=True) decoder.append(up) self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder) return def forward(self, input):","elif n_blocks == 4: inner_nc = 512 nlayers = 5 for lx in","lx in range(nlayers): outnc = max(inner_nc // 2, 16) up = nb.upconv2d(inner_nc, outnc)","= 256 nlayers = 4 elif n_blocks == 4: inner_nc = 512 nlayers","ResnetEncoder(n_blocks=n_blocks) self.n_blocks = n_blocks decoder = [] if n_blocks == 3: inner_nc =","self.n_blocks = n_blocks def forward(self, x): n_blocks = self.n_blocks x = self.resnet.conv1(x) x","if n_blocks >= 2: x = self.resnet.layer2(x) if n_blocks >= 3: x =","max(inner_nc // 2, 16) up = nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc = outnc up","n_blocks decoder = [] if n_blocks == 3: inner_nc = 256 nlayers =","osp import numpy as np import torch import torchvision import torch.nn as nn","from __future__ import absolute_import from __future__ import division from __future__ import print_function from","decoder = [] if n_blocks == 3: inner_nc = 256 nlayers = 4","256 nlayers = 4 elif n_blocks == 4: inner_nc = 512 nlayers =","5 for lx in range(nlayers): outnc = max(inner_nc // 2, 16) up =","n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder = ResnetEncoder(n_blocks=n_blocks) self.n_blocks = n_blocks decoder = []","= self.resnet.conv1(x) x = self.resnet.bn1(x) x = self.resnet.relu(x) x = self.resnet.maxpool(x) if n_blocks","= [] if n_blocks == 3: inner_nc = 256 nlayers = 4 elif","torch import torchvision import torch.nn as nn from torch.autograd import Variable import functools",">= 1: x = self.resnet.layer1(x) if n_blocks >= 2: x = self.resnet.layer2(x) if","outnc) decoder.append(up) inner_nc = outnc up = nn.Conv2d( inner_nc, output_nc, kernel_size=3, stride=1, padding=1,","output_nc, kernel_size=3, stride=1, padding=1, bias=True) decoder.append(up) self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder) return def forward(self,","2, 16) up = nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc = outnc up = nn.Conv2d(","<filename>acsm/nnutils/resunet.py from __future__ import absolute_import from __future__ import division from __future__ import print_function","import Variable import functools from . import net_blocks as nb import pdb class",">= 2: x = self.resnet.layer2(x) if n_blocks >= 3: x = self.resnet.layer3(x) if","= 512 nlayers = 5 for lx in range(nlayers): outnc = max(inner_nc //","bias=True) decoder.append(up) self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder) return def forward(self, input): img_enc = self.encoder(input)","= nn.Sequential(*decoder) nb.net_init(self.decoder) return def forward(self, input): img_enc = self.encoder(input) img_dec = self.decoder(img_enc)","img_dec = self.decoder(img_enc) return img_dec def reinit_weights(self, ): self.encoder = ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class","in range(nlayers): outnc = max(inner_nc // 2, 16) up = nb.upconv2d(inner_nc, outnc) decoder.append(up)","= self.n_blocks x = self.resnet.conv1(x) x = self.resnet.bn1(x) x = self.resnet.relu(x) x =","def reinit_weights(self, ): self.encoder = ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class ResnetEncoder(nn.Module): def __init__(self, n_blocks): super(ResnetEncoder,","from __future__ import division from __future__ import print_function from absl import app from","import net_blocks as nb import pdb class ResNetConcatGenerator(nn.Module): def __init__(self, input_nc, output_nc, n_blocks=3,","if n_blocks >= 1: x = self.resnet.layer1(x) if n_blocks >= 2: x =","output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder = ResnetEncoder(n_blocks=n_blocks) self.n_blocks = n_blocks decoder =","absl import app from absl import flags import os import os.path as osp","numpy as np import torch import torchvision import torch.nn as nn from torch.autograd","nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc = outnc up = nn.Conv2d( inner_nc, output_nc, kernel_size=3, stride=1,","nb.net_init(self.decoder) class ResnetEncoder(nn.Module): def __init__(self, n_blocks): super(ResnetEncoder, self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks =","inner_nc = outnc up = nn.Conv2d( inner_nc, output_nc, kernel_size=3, stride=1, padding=1, bias=True) decoder.append(up)","= self.resnet.layer1(x) if n_blocks >= 2: x = self.resnet.layer2(x) if n_blocks >= 3:","def __init__(self, input_nc, output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder = ResnetEncoder(n_blocks=n_blocks) self.n_blocks =","import division from __future__ import print_function from absl import app from absl import","__init__(self, input_nc, output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder = ResnetEncoder(n_blocks=n_blocks) self.n_blocks = n_blocks","__future__ import absolute_import from __future__ import division from __future__ import print_function from absl","reinit_weights(self, ): self.encoder = ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class ResnetEncoder(nn.Module): def __init__(self, n_blocks): super(ResnetEncoder, self).__init__()","for lx in range(nlayers): outnc = max(inner_nc // 2, 16) up = nb.upconv2d(inner_nc,","torchvision import torch.nn as nn from torch.autograd import Variable import functools from .","print_function from absl import app from absl import flags import os import os.path","padding=1, bias=True) decoder.append(up) self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder) return def forward(self, input): img_enc =","from . import net_blocks as nb import pdb class ResNetConcatGenerator(nn.Module): def __init__(self, input_nc,","= self.resnet.bn1(x) x = self.resnet.relu(x) x = self.resnet.maxpool(x) if n_blocks >= 1: x","os import os.path as osp import numpy as np import torch import torchvision","2: x = self.resnet.layer2(x) if n_blocks >= 3: x = self.resnet.layer3(x) if n_blocks","self.n_blocks x = self.resnet.conv1(x) x = self.resnet.bn1(x) x = self.resnet.relu(x) x = self.resnet.maxpool(x)","if n_blocks >= 3: x = self.resnet.layer3(x) if n_blocks >= 4: x =","import app from absl import flags import os import os.path as osp import","x = self.resnet.relu(x) x = self.resnet.maxpool(x) if n_blocks >= 1: x = self.resnet.layer1(x)","= torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks def forward(self, x): n_blocks = self.n_blocks x =","n_blocks >= 3: x = self.resnet.layer3(x) if n_blocks >= 4: x = self.resnet.layer4(x)","as nb import pdb class ResNetConcatGenerator(nn.Module): def __init__(self, input_nc, output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator,","= nn.Conv2d( inner_nc, output_nc, kernel_size=3, stride=1, padding=1, bias=True) decoder.append(up) self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder)","import numpy as np import torch import torchvision import torch.nn as nn from","def __init__(self, n_blocks): super(ResnetEncoder, self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks def forward(self,","ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class ResnetEncoder(nn.Module): def __init__(self, n_blocks): super(ResnetEncoder, self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks","pdb class ResNetConcatGenerator(nn.Module): def __init__(self, input_nc, output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder =","input_nc, output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder = ResnetEncoder(n_blocks=n_blocks) self.n_blocks = n_blocks decoder","self.decoder(img_enc) return img_dec def reinit_weights(self, ): self.encoder = ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class ResnetEncoder(nn.Module): def","self.resnet.relu(x) x = self.resnet.maxpool(x) if n_blocks >= 1: x = self.resnet.layer1(x) if n_blocks","self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder) return def forward(self, input): img_enc = self.encoder(input) img_dec =","4: inner_nc = 512 nlayers = 5 for lx in range(nlayers): outnc =","nlayers = 5 for lx in range(nlayers): outnc = max(inner_nc // 2, 16)","x = self.resnet.conv1(x) x = self.resnet.bn1(x) x = self.resnet.relu(x) x = self.resnet.maxpool(x) if","= 4 elif n_blocks == 4: inner_nc = 512 nlayers = 5 for","__future__ import division from __future__ import print_function from absl import app from absl","as np import torch import torchvision import torch.nn as nn from torch.autograd import","self.encoder = ResnetEncoder(n_blocks=n_blocks) self.n_blocks = n_blocks decoder = [] if n_blocks == 3:","inner_nc, output_nc, kernel_size=3, stride=1, padding=1, bias=True) decoder.append(up) self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder) return def","self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks def forward(self, x): n_blocks = self.n_blocks","import torch import torchvision import torch.nn as nn from torch.autograd import Variable import","): self.encoder = ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class ResnetEncoder(nn.Module): def __init__(self, n_blocks): super(ResnetEncoder, self).__init__() self.resnet","self.encoder(input) img_dec = self.decoder(img_enc) return img_dec def reinit_weights(self, ): self.encoder = ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder)","inner_nc = 256 nlayers = 4 elif n_blocks == 4: inner_nc = 512","= outnc up = nn.Conv2d( inner_nc, output_nc, kernel_size=3, stride=1, padding=1, bias=True) decoder.append(up) self.decoder","torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks def forward(self, x): n_blocks = self.n_blocks x = self.resnet.conv1(x)","as osp import numpy as np import torch import torchvision import torch.nn as","super(ResnetEncoder, self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks def forward(self, x): n_blocks =","= self.resnet.relu(x) x = self.resnet.maxpool(x) if n_blocks >= 1: x = self.resnet.layer1(x) if","self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks def forward(self, x): n_blocks = self.n_blocks x","forward(self, input): img_enc = self.encoder(input) img_dec = self.decoder(img_enc) return img_dec def reinit_weights(self, ):","import functools from . import net_blocks as nb import pdb class ResNetConcatGenerator(nn.Module): def",". import net_blocks as nb import pdb class ResNetConcatGenerator(nn.Module): def __init__(self, input_nc, output_nc,","== 4: inner_nc = 512 nlayers = 5 for lx in range(nlayers): outnc","[] if n_blocks == 3: inner_nc = 256 nlayers = 4 elif n_blocks","x = self.resnet.layer2(x) if n_blocks >= 3: x = self.resnet.layer3(x) if n_blocks >=","import absolute_import from __future__ import division from __future__ import print_function from absl import","img_enc = self.encoder(input) img_dec = self.decoder(img_enc) return img_dec def reinit_weights(self, ): self.encoder =","= self.resnet.maxpool(x) if n_blocks >= 1: x = self.resnet.layer1(x) if n_blocks >= 2:","net_blocks as nb import pdb class ResNetConcatGenerator(nn.Module): def __init__(self, input_nc, output_nc, n_blocks=3, ngf=64,):","import os import os.path as osp import numpy as np import torch import","512 nlayers = 5 for lx in range(nlayers): outnc = max(inner_nc // 2,","= nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc = outnc up = nn.Conv2d( inner_nc, output_nc, kernel_size=3,","n_blocks >= 1: x = self.resnet.layer1(x) if n_blocks >= 2: x = self.resnet.layer2(x)","up = nn.Conv2d( inner_nc, output_nc, kernel_size=3, stride=1, padding=1, bias=True) decoder.append(up) self.decoder = nn.Sequential(*decoder)","self.resnet.conv1(x) x = self.resnet.bn1(x) x = self.resnet.relu(x) x = self.resnet.maxpool(x) if n_blocks >=","outnc = max(inner_nc // 2, 16) up = nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc =","decoder.append(up) inner_nc = outnc up = nn.Conv2d( inner_nc, output_nc, kernel_size=3, stride=1, padding=1, bias=True)","self.encoder = ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class ResnetEncoder(nn.Module): def __init__(self, n_blocks): super(ResnetEncoder, self).__init__() self.resnet =","= self.encoder(input) img_dec = self.decoder(img_enc) return img_dec def reinit_weights(self, ): self.encoder = ResnetEncoder(n_blocks=self.n_blocks)","class ResNetConcatGenerator(nn.Module): def __init__(self, input_nc, output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder = ResnetEncoder(n_blocks=n_blocks)","input): img_enc = self.encoder(input) img_dec = self.decoder(img_enc) return img_dec def reinit_weights(self, ): self.encoder","self.n_blocks = n_blocks decoder = [] if n_blocks == 3: inner_nc = 256","import flags import os import os.path as osp import numpy as np import","import pdb class ResNetConcatGenerator(nn.Module): def __init__(self, input_nc, output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder","16) up = nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc = outnc up = nn.Conv2d( inner_nc,","absl import flags import os import os.path as osp import numpy as np","img_dec def reinit_weights(self, ): self.encoder = ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class ResnetEncoder(nn.Module): def __init__(self, n_blocks):","n_blocks def forward(self, x): n_blocks = self.n_blocks x = self.resnet.conv1(x) x = self.resnet.bn1(x)","self.resnet.layer2(x) if n_blocks >= 3: x = self.resnet.layer3(x) if n_blocks >= 4: x","self).__init__() self.encoder = ResnetEncoder(n_blocks=n_blocks) self.n_blocks = n_blocks decoder = [] if n_blocks ==","n_blocks = self.n_blocks x = self.resnet.conv1(x) x = self.resnet.bn1(x) x = self.resnet.relu(x) x","range(nlayers): outnc = max(inner_nc // 2, 16) up = nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc","Variable import functools from . import net_blocks as nb import pdb class ResNetConcatGenerator(nn.Module):","nb import pdb class ResNetConcatGenerator(nn.Module): def __init__(self, input_nc, output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__()","= n_blocks def forward(self, x): n_blocks = self.n_blocks x = self.resnet.conv1(x) x =","division from __future__ import print_function from absl import app from absl import flags","__init__(self, n_blocks): super(ResnetEncoder, self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks def forward(self, x):","from torch.autograd import Variable import functools from . import net_blocks as nb import","stride=1, padding=1, bias=True) decoder.append(up) self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder) return def forward(self, input): img_enc","= n_blocks decoder = [] if n_blocks == 3: inner_nc = 256 nlayers","1: x = self.resnet.layer1(x) if n_blocks >= 2: x = self.resnet.layer2(x) if n_blocks","self.resnet.bn1(x) x = self.resnet.relu(x) x = self.resnet.maxpool(x) if n_blocks >= 1: x =","os.path as osp import numpy as np import torch import torchvision import torch.nn","4 elif n_blocks == 4: inner_nc = 512 nlayers = 5 for lx","import print_function from absl import app from absl import flags import os import","n_blocks == 3: inner_nc = 256 nlayers = 4 elif n_blocks == 4:","nb.net_init(self.decoder) return def forward(self, input): img_enc = self.encoder(input) img_dec = self.decoder(img_enc) return img_dec","3: x = self.resnet.layer3(x) if n_blocks >= 4: x = self.resnet.layer4(x) return x","x = self.resnet.layer1(x) if n_blocks >= 2: x = self.resnet.layer2(x) if n_blocks >=","self.resnet.layer1(x) if n_blocks >= 2: x = self.resnet.layer2(x) if n_blocks >= 3: x","nlayers = 4 elif n_blocks == 4: inner_nc = 512 nlayers = 5","= self.resnet.layer2(x) if n_blocks >= 3: x = self.resnet.layer3(x) if n_blocks >= 4:","np import torch import torchvision import torch.nn as nn from torch.autograd import Variable","= max(inner_nc // 2, 16) up = nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc = outnc","inner_nc = 512 nlayers = 5 for lx in range(nlayers): outnc = max(inner_nc","nn.Conv2d( inner_nc, output_nc, kernel_size=3, stride=1, padding=1, bias=True) decoder.append(up) self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder) return","def forward(self, x): n_blocks = self.n_blocks x = self.resnet.conv1(x) x = self.resnet.bn1(x) x","up = nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc = outnc up = nn.Conv2d( inner_nc, output_nc,","def forward(self, input): img_enc = self.encoder(input) img_dec = self.decoder(img_enc) return img_dec def reinit_weights(self,","import os.path as osp import numpy as np import torch import torchvision import","== 3: inner_nc = 256 nlayers = 4 elif n_blocks == 4: inner_nc","__future__ import print_function from absl import app from absl import flags import os","from absl import flags import os import os.path as osp import numpy as","nn.Sequential(*decoder) nb.net_init(self.decoder) return def forward(self, input): img_enc = self.encoder(input) img_dec = self.decoder(img_enc) return","ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder = ResnetEncoder(n_blocks=n_blocks) self.n_blocks = n_blocks decoder = [] if","= self.decoder(img_enc) return img_dec def reinit_weights(self, ): self.encoder = ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class ResnetEncoder(nn.Module):","x = self.resnet.maxpool(x) if n_blocks >= 1: x = self.resnet.layer1(x) if n_blocks >=","self.resnet.maxpool(x) if n_blocks >= 1: x = self.resnet.layer1(x) if n_blocks >= 2: x","n_blocks == 4: inner_nc = 512 nlayers = 5 for lx in range(nlayers):","ResnetEncoder(nn.Module): def __init__(self, n_blocks): super(ResnetEncoder, self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks def","x): n_blocks = self.n_blocks x = self.resnet.conv1(x) x = self.resnet.bn1(x) x = self.resnet.relu(x)","class ResnetEncoder(nn.Module): def __init__(self, n_blocks): super(ResnetEncoder, self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks","import torch.nn as nn from torch.autograd import Variable import functools from . import","= ResnetEncoder(n_blocks=n_blocks) self.n_blocks = n_blocks decoder = [] if n_blocks == 3: inner_nc","= ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class ResnetEncoder(nn.Module): def __init__(self, n_blocks): super(ResnetEncoder, self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True)","n_blocks >= 2: x = self.resnet.layer2(x) if n_blocks >= 3: x = self.resnet.layer3(x)","n_blocks): super(ResnetEncoder, self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks def forward(self, x): n_blocks","torch.nn as nn from torch.autograd import Variable import functools from . import net_blocks","return def forward(self, input): img_enc = self.encoder(input) img_dec = self.decoder(img_enc) return img_dec def"],"string":"[\n \"from __future__ import print_function from absl import app from absl import flags import\",\n \"// 2, 16) up = nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc = outnc up =\",\n \"absolute_import from __future__ import division from __future__ import print_function from absl import app\",\n \"import torchvision import torch.nn as nn from torch.autograd import Variable import functools from\",\n \"return img_dec def reinit_weights(self, ): self.encoder = ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class ResnetEncoder(nn.Module): def __init__(self,\",\n \"forward(self, x): n_blocks = self.n_blocks x = self.resnet.conv1(x) x = self.resnet.bn1(x) x =\",\n \"functools from . import net_blocks as nb import pdb class ResNetConcatGenerator(nn.Module): def __init__(self,\",\n \"outnc up = nn.Conv2d( inner_nc, output_nc, kernel_size=3, stride=1, padding=1, bias=True) decoder.append(up) self.decoder =\",\n \"app from absl import flags import os import os.path as osp import numpy\",\n \"super(ResNetConcatGenerator, self).__init__() self.encoder = ResnetEncoder(n_blocks=n_blocks) self.n_blocks = n_blocks decoder = [] if n_blocks\",\n \"3: inner_nc = 256 nlayers = 4 elif n_blocks == 4: inner_nc =\",\n \"x = self.resnet.bn1(x) x = self.resnet.relu(x) x = self.resnet.maxpool(x) if n_blocks >= 1:\",\n \"as nn from torch.autograd import Variable import functools from . import net_blocks as\",\n \"decoder.append(up) self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder) return def forward(self, input): img_enc = self.encoder(input) img_dec\",\n \">= 3: x = self.resnet.layer3(x) if n_blocks >= 4: x = self.resnet.layer4(x) return\",\n \"from absl import app from absl import flags import os import os.path as\",\n \"flags import os import os.path as osp import numpy as np import torch\",\n \"torch.autograd import Variable import functools from . import net_blocks as nb import pdb\",\n \"nn from torch.autograd import Variable import functools from . import net_blocks as nb\",\n \"ResNetConcatGenerator(nn.Module): def __init__(self, input_nc, output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder = ResnetEncoder(n_blocks=n_blocks) self.n_blocks\",\n \"if n_blocks == 3: inner_nc = 256 nlayers = 4 elif n_blocks ==\",\n \"= 5 for lx in range(nlayers): outnc = max(inner_nc // 2, 16) up\",\n \"kernel_size=3, stride=1, padding=1, bias=True) decoder.append(up) self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder) return def forward(self, input):\",\n \"elif n_blocks == 4: inner_nc = 512 nlayers = 5 for lx in\",\n \"lx in range(nlayers): outnc = max(inner_nc // 2, 16) up = nb.upconv2d(inner_nc, outnc)\",\n \"= 256 nlayers = 4 elif n_blocks == 4: inner_nc = 512 nlayers\",\n \"ResnetEncoder(n_blocks=n_blocks) self.n_blocks = n_blocks decoder = [] if n_blocks == 3: inner_nc =\",\n \"self.n_blocks = n_blocks def forward(self, x): n_blocks = self.n_blocks x = self.resnet.conv1(x) x\",\n \"if n_blocks >= 2: x = self.resnet.layer2(x) if n_blocks >= 3: x =\",\n \"max(inner_nc // 2, 16) up = nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc = outnc up\",\n \"n_blocks decoder = [] if n_blocks == 3: inner_nc = 256 nlayers =\",\n \"osp import numpy as np import torch import torchvision import torch.nn as nn\",\n \"from __future__ import absolute_import from __future__ import division from __future__ import print_function from\",\n \"decoder = [] if n_blocks == 3: inner_nc = 256 nlayers = 4\",\n \"256 nlayers = 4 elif n_blocks == 4: inner_nc = 512 nlayers =\",\n \"5 for lx in range(nlayers): outnc = max(inner_nc // 2, 16) up =\",\n \"n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder = ResnetEncoder(n_blocks=n_blocks) self.n_blocks = n_blocks decoder = []\",\n \"= self.resnet.conv1(x) x = self.resnet.bn1(x) x = self.resnet.relu(x) x = self.resnet.maxpool(x) if n_blocks\",\n \"= [] if n_blocks == 3: inner_nc = 256 nlayers = 4 elif\",\n \"torch import torchvision import torch.nn as nn from torch.autograd import Variable import functools\",\n \">= 1: x = self.resnet.layer1(x) if n_blocks >= 2: x = self.resnet.layer2(x) if\",\n \"outnc) decoder.append(up) inner_nc = outnc up = nn.Conv2d( inner_nc, output_nc, kernel_size=3, stride=1, padding=1,\",\n \"output_nc, kernel_size=3, stride=1, padding=1, bias=True) decoder.append(up) self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder) return def forward(self,\",\n \"2, 16) up = nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc = outnc up = nn.Conv2d(\",\n \"<filename>acsm/nnutils/resunet.py from __future__ import absolute_import from __future__ import division from __future__ import print_function\",\n \"import Variable import functools from . import net_blocks as nb import pdb class\",\n \">= 2: x = self.resnet.layer2(x) if n_blocks >= 3: x = self.resnet.layer3(x) if\",\n \"= 512 nlayers = 5 for lx in range(nlayers): outnc = max(inner_nc //\",\n \"bias=True) decoder.append(up) self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder) return def forward(self, input): img_enc = self.encoder(input)\",\n \"= nn.Sequential(*decoder) nb.net_init(self.decoder) return def forward(self, input): img_enc = self.encoder(input) img_dec = self.decoder(img_enc)\",\n \"img_dec = self.decoder(img_enc) return img_dec def reinit_weights(self, ): self.encoder = ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class\",\n \"in range(nlayers): outnc = max(inner_nc // 2, 16) up = nb.upconv2d(inner_nc, outnc) decoder.append(up)\",\n \"= self.n_blocks x = self.resnet.conv1(x) x = self.resnet.bn1(x) x = self.resnet.relu(x) x =\",\n \"def reinit_weights(self, ): self.encoder = ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class ResnetEncoder(nn.Module): def __init__(self, n_blocks): super(ResnetEncoder,\",\n \"from __future__ import division from __future__ import print_function from absl import app from\",\n \"import net_blocks as nb import pdb class ResNetConcatGenerator(nn.Module): def __init__(self, input_nc, output_nc, n_blocks=3,\",\n \"if n_blocks >= 1: x = self.resnet.layer1(x) if n_blocks >= 2: x =\",\n \"output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder = ResnetEncoder(n_blocks=n_blocks) self.n_blocks = n_blocks decoder =\",\n \"absl import app from absl import flags import os import os.path as osp\",\n \"numpy as np import torch import torchvision import torch.nn as nn from torch.autograd\",\n \"nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc = outnc up = nn.Conv2d( inner_nc, output_nc, kernel_size=3, stride=1,\",\n \"nb.net_init(self.decoder) class ResnetEncoder(nn.Module): def __init__(self, n_blocks): super(ResnetEncoder, self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks =\",\n \"inner_nc = outnc up = nn.Conv2d( inner_nc, output_nc, kernel_size=3, stride=1, padding=1, bias=True) decoder.append(up)\",\n \"= self.resnet.layer1(x) if n_blocks >= 2: x = self.resnet.layer2(x) if n_blocks >= 3:\",\n \"def __init__(self, input_nc, output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder = ResnetEncoder(n_blocks=n_blocks) self.n_blocks =\",\n \"import division from __future__ import print_function from absl import app from absl import\",\n \"__init__(self, input_nc, output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder = ResnetEncoder(n_blocks=n_blocks) self.n_blocks = n_blocks\",\n \"__future__ import absolute_import from __future__ import division from __future__ import print_function from absl\",\n \"reinit_weights(self, ): self.encoder = ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class ResnetEncoder(nn.Module): def __init__(self, n_blocks): super(ResnetEncoder, self).__init__()\",\n \"for lx in range(nlayers): outnc = max(inner_nc // 2, 16) up = nb.upconv2d(inner_nc,\",\n \"torchvision import torch.nn as nn from torch.autograd import Variable import functools from .\",\n \"print_function from absl import app from absl import flags import os import os.path\",\n \"padding=1, bias=True) decoder.append(up) self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder) return def forward(self, input): img_enc =\",\n \"from . import net_blocks as nb import pdb class ResNetConcatGenerator(nn.Module): def __init__(self, input_nc,\",\n \"= self.resnet.bn1(x) x = self.resnet.relu(x) x = self.resnet.maxpool(x) if n_blocks >= 1: x\",\n \"os import os.path as osp import numpy as np import torch import torchvision\",\n \"2: x = self.resnet.layer2(x) if n_blocks >= 3: x = self.resnet.layer3(x) if n_blocks\",\n \"self.n_blocks x = self.resnet.conv1(x) x = self.resnet.bn1(x) x = self.resnet.relu(x) x = self.resnet.maxpool(x)\",\n \"if n_blocks >= 3: x = self.resnet.layer3(x) if n_blocks >= 4: x =\",\n \"import app from absl import flags import os import os.path as osp import\",\n \"x = self.resnet.relu(x) x = self.resnet.maxpool(x) if n_blocks >= 1: x = self.resnet.layer1(x)\",\n \"= torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks def forward(self, x): n_blocks = self.n_blocks x =\",\n \"n_blocks >= 3: x = self.resnet.layer3(x) if n_blocks >= 4: x = self.resnet.layer4(x)\",\n \"as nb import pdb class ResNetConcatGenerator(nn.Module): def __init__(self, input_nc, output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator,\",\n \"= nn.Conv2d( inner_nc, output_nc, kernel_size=3, stride=1, padding=1, bias=True) decoder.append(up) self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder)\",\n \"import numpy as np import torch import torchvision import torch.nn as nn from\",\n \"def __init__(self, n_blocks): super(ResnetEncoder, self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks def forward(self,\",\n \"ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class ResnetEncoder(nn.Module): def __init__(self, n_blocks): super(ResnetEncoder, self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks\",\n \"pdb class ResNetConcatGenerator(nn.Module): def __init__(self, input_nc, output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder =\",\n \"input_nc, output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder = ResnetEncoder(n_blocks=n_blocks) self.n_blocks = n_blocks decoder\",\n \"self.decoder(img_enc) return img_dec def reinit_weights(self, ): self.encoder = ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class ResnetEncoder(nn.Module): def\",\n \"self.resnet.relu(x) x = self.resnet.maxpool(x) if n_blocks >= 1: x = self.resnet.layer1(x) if n_blocks\",\n \"self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder) return def forward(self, input): img_enc = self.encoder(input) img_dec =\",\n \"4: inner_nc = 512 nlayers = 5 for lx in range(nlayers): outnc =\",\n \"nlayers = 5 for lx in range(nlayers): outnc = max(inner_nc // 2, 16)\",\n \"x = self.resnet.conv1(x) x = self.resnet.bn1(x) x = self.resnet.relu(x) x = self.resnet.maxpool(x) if\",\n \"= 4 elif n_blocks == 4: inner_nc = 512 nlayers = 5 for\",\n \"__future__ import division from __future__ import print_function from absl import app from absl\",\n \"as np import torch import torchvision import torch.nn as nn from torch.autograd import\",\n \"self.encoder = ResnetEncoder(n_blocks=n_blocks) self.n_blocks = n_blocks decoder = [] if n_blocks == 3:\",\n \"inner_nc, output_nc, kernel_size=3, stride=1, padding=1, bias=True) decoder.append(up) self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder) return def\",\n \"self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks def forward(self, x): n_blocks = self.n_blocks\",\n \"import torch import torchvision import torch.nn as nn from torch.autograd import Variable import\",\n \"): self.encoder = ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class ResnetEncoder(nn.Module): def __init__(self, n_blocks): super(ResnetEncoder, self).__init__() self.resnet\",\n \"self.encoder(input) img_dec = self.decoder(img_enc) return img_dec def reinit_weights(self, ): self.encoder = ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder)\",\n \"inner_nc = 256 nlayers = 4 elif n_blocks == 4: inner_nc = 512\",\n \"= outnc up = nn.Conv2d( inner_nc, output_nc, kernel_size=3, stride=1, padding=1, bias=True) decoder.append(up) self.decoder\",\n \"torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks def forward(self, x): n_blocks = self.n_blocks x = self.resnet.conv1(x)\",\n \"as osp import numpy as np import torch import torchvision import torch.nn as\",\n \"super(ResnetEncoder, self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks def forward(self, x): n_blocks =\",\n \"= self.resnet.relu(x) x = self.resnet.maxpool(x) if n_blocks >= 1: x = self.resnet.layer1(x) if\",\n \"self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks def forward(self, x): n_blocks = self.n_blocks x\",\n \"forward(self, input): img_enc = self.encoder(input) img_dec = self.decoder(img_enc) return img_dec def reinit_weights(self, ):\",\n \"import functools from . import net_blocks as nb import pdb class ResNetConcatGenerator(nn.Module): def\",\n \". import net_blocks as nb import pdb class ResNetConcatGenerator(nn.Module): def __init__(self, input_nc, output_nc,\",\n \"== 4: inner_nc = 512 nlayers = 5 for lx in range(nlayers): outnc\",\n \"[] if n_blocks == 3: inner_nc = 256 nlayers = 4 elif n_blocks\",\n \"x = self.resnet.layer2(x) if n_blocks >= 3: x = self.resnet.layer3(x) if n_blocks >=\",\n \"import absolute_import from __future__ import division from __future__ import print_function from absl import\",\n \"img_enc = self.encoder(input) img_dec = self.decoder(img_enc) return img_dec def reinit_weights(self, ): self.encoder =\",\n \"= self.resnet.maxpool(x) if n_blocks >= 1: x = self.resnet.layer1(x) if n_blocks >= 2:\",\n \"net_blocks as nb import pdb class ResNetConcatGenerator(nn.Module): def __init__(self, input_nc, output_nc, n_blocks=3, ngf=64,):\",\n \"import os import os.path as osp import numpy as np import torch import\",\n \"512 nlayers = 5 for lx in range(nlayers): outnc = max(inner_nc // 2,\",\n \"= nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc = outnc up = nn.Conv2d( inner_nc, output_nc, kernel_size=3,\",\n \"n_blocks >= 1: x = self.resnet.layer1(x) if n_blocks >= 2: x = self.resnet.layer2(x)\",\n \"up = nn.Conv2d( inner_nc, output_nc, kernel_size=3, stride=1, padding=1, bias=True) decoder.append(up) self.decoder = nn.Sequential(*decoder)\",\n \"self.resnet.conv1(x) x = self.resnet.bn1(x) x = self.resnet.relu(x) x = self.resnet.maxpool(x) if n_blocks >=\",\n \"outnc = max(inner_nc // 2, 16) up = nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc =\",\n \"decoder.append(up) inner_nc = outnc up = nn.Conv2d( inner_nc, output_nc, kernel_size=3, stride=1, padding=1, bias=True)\",\n \"self.encoder = ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class ResnetEncoder(nn.Module): def __init__(self, n_blocks): super(ResnetEncoder, self).__init__() self.resnet =\",\n \"= self.encoder(input) img_dec = self.decoder(img_enc) return img_dec def reinit_weights(self, ): self.encoder = ResnetEncoder(n_blocks=self.n_blocks)\",\n \"class ResNetConcatGenerator(nn.Module): def __init__(self, input_nc, output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder = ResnetEncoder(n_blocks=n_blocks)\",\n \"input): img_enc = self.encoder(input) img_dec = self.decoder(img_enc) return img_dec def reinit_weights(self, ): self.encoder\",\n \"self.n_blocks = n_blocks decoder = [] if n_blocks == 3: inner_nc = 256\",\n \"import flags import os import os.path as osp import numpy as np import\",\n \"import pdb class ResNetConcatGenerator(nn.Module): def __init__(self, input_nc, output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder\",\n \"16) up = nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc = outnc up = nn.Conv2d( inner_nc,\",\n \"absl import flags import os import os.path as osp import numpy as np\",\n \"img_dec def reinit_weights(self, ): self.encoder = ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class ResnetEncoder(nn.Module): def __init__(self, n_blocks):\",\n \"n_blocks def forward(self, x): n_blocks = self.n_blocks x = self.resnet.conv1(x) x = self.resnet.bn1(x)\",\n \"self.resnet.layer2(x) if n_blocks >= 3: x = self.resnet.layer3(x) if n_blocks >= 4: x\",\n \"self).__init__() self.encoder = ResnetEncoder(n_blocks=n_blocks) self.n_blocks = n_blocks decoder = [] if n_blocks ==\",\n \"n_blocks = self.n_blocks x = self.resnet.conv1(x) x = self.resnet.bn1(x) x = self.resnet.relu(x) x\",\n \"range(nlayers): outnc = max(inner_nc // 2, 16) up = nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc\",\n \"Variable import functools from . import net_blocks as nb import pdb class ResNetConcatGenerator(nn.Module):\",\n \"nb import pdb class ResNetConcatGenerator(nn.Module): def __init__(self, input_nc, output_nc, n_blocks=3, ngf=64,): super(ResNetConcatGenerator, self).__init__()\",\n \"= n_blocks def forward(self, x): n_blocks = self.n_blocks x = self.resnet.conv1(x) x =\",\n \"division from __future__ import print_function from absl import app from absl import flags\",\n \"__init__(self, n_blocks): super(ResnetEncoder, self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks def forward(self, x):\",\n \"from torch.autograd import Variable import functools from . import net_blocks as nb import\",\n \"stride=1, padding=1, bias=True) decoder.append(up) self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder) return def forward(self, input): img_enc\",\n \"= n_blocks decoder = [] if n_blocks == 3: inner_nc = 256 nlayers\",\n \"1: x = self.resnet.layer1(x) if n_blocks >= 2: x = self.resnet.layer2(x) if n_blocks\",\n \"self.resnet.bn1(x) x = self.resnet.relu(x) x = self.resnet.maxpool(x) if n_blocks >= 1: x =\",\n \"os.path as osp import numpy as np import torch import torchvision import torch.nn\",\n \"4 elif n_blocks == 4: inner_nc = 512 nlayers = 5 for lx\",\n \"import print_function from absl import app from absl import flags import os import\",\n \"n_blocks == 3: inner_nc = 256 nlayers = 4 elif n_blocks == 4:\",\n \"nb.net_init(self.decoder) return def forward(self, input): img_enc = self.encoder(input) img_dec = self.decoder(img_enc) return img_dec\",\n \"3: x = self.resnet.layer3(x) if n_blocks >= 4: x = self.resnet.layer4(x) return x\",\n \"x = self.resnet.layer1(x) if n_blocks >= 2: x = self.resnet.layer2(x) if n_blocks >=\",\n \"self.resnet.layer1(x) if n_blocks >= 2: x = self.resnet.layer2(x) if n_blocks >= 3: x\",\n \"nlayers = 4 elif n_blocks == 4: inner_nc = 512 nlayers = 5\",\n \"= self.resnet.layer2(x) if n_blocks >= 3: x = self.resnet.layer3(x) if n_blocks >= 4:\",\n \"np import torch import torchvision import torch.nn as nn from torch.autograd import Variable\",\n \"= max(inner_nc // 2, 16) up = nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc = outnc\",\n \"inner_nc = 512 nlayers = 5 for lx in range(nlayers): outnc = max(inner_nc\",\n \"nn.Conv2d( inner_nc, output_nc, kernel_size=3, stride=1, padding=1, bias=True) decoder.append(up) self.decoder = nn.Sequential(*decoder) nb.net_init(self.decoder) return\",\n \"def forward(self, x): n_blocks = self.n_blocks x = self.resnet.conv1(x) x = self.resnet.bn1(x) x\",\n \"up = nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc = outnc up = nn.Conv2d( inner_nc, output_nc,\",\n \"def forward(self, input): img_enc = self.encoder(input) img_dec = self.decoder(img_enc) return img_dec def reinit_weights(self,\",\n \"import os.path as osp import numpy as np import torch import torchvision import\",\n \"== 3: inner_nc = 256 nlayers = 4 elif n_blocks == 4: inner_nc\",\n \"__future__ import print_function from absl import app from absl import flags import os\",\n \"from absl import flags import os import os.path as osp import numpy as\",\n \"nn.Sequential(*decoder) nb.net_init(self.decoder) return def forward(self, input): img_enc = self.encoder(input) img_dec = self.decoder(img_enc) return\",\n \"ngf=64,): super(ResNetConcatGenerator, self).__init__() self.encoder = ResnetEncoder(n_blocks=n_blocks) self.n_blocks = n_blocks decoder = [] if\",\n \"= self.decoder(img_enc) return img_dec def reinit_weights(self, ): self.encoder = ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class ResnetEncoder(nn.Module):\",\n \"x = self.resnet.maxpool(x) if n_blocks >= 1: x = self.resnet.layer1(x) if n_blocks >=\",\n \"self.resnet.maxpool(x) if n_blocks >= 1: x = self.resnet.layer1(x) if n_blocks >= 2: x\",\n \"n_blocks == 4: inner_nc = 512 nlayers = 5 for lx in range(nlayers):\",\n \"ResnetEncoder(nn.Module): def __init__(self, n_blocks): super(ResnetEncoder, self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks def\",\n \"x): n_blocks = self.n_blocks x = self.resnet.conv1(x) x = self.resnet.bn1(x) x = self.resnet.relu(x)\",\n \"class ResnetEncoder(nn.Module): def __init__(self, n_blocks): super(ResnetEncoder, self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks\",\n \"import torch.nn as nn from torch.autograd import Variable import functools from . import\",\n \"= ResnetEncoder(n_blocks=n_blocks) self.n_blocks = n_blocks decoder = [] if n_blocks == 3: inner_nc\",\n \"= ResnetEncoder(n_blocks=self.n_blocks) nb.net_init(self.decoder) class ResnetEncoder(nn.Module): def __init__(self, n_blocks): super(ResnetEncoder, self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True)\",\n \"n_blocks >= 2: x = self.resnet.layer2(x) if n_blocks >= 3: x = self.resnet.layer3(x)\",\n \"n_blocks): super(ResnetEncoder, self).__init__() self.resnet = torchvision.models.resnet18(pretrained=True) self.n_blocks = n_blocks def forward(self, x): n_blocks\",\n \"torch.nn as nn from torch.autograd import Variable import functools from . import net_blocks\",\n \"return def forward(self, input): img_enc = self.encoder(input) img_dec = self.decoder(img_enc) return img_dec def\"\n]","isConversational":false}}},{"rowIdx":4395,"cells":{"ngram":{"kind":"list like","value":["and the following disclaimer in the documentation # and/or other materials provided with","# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR #","awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out class","EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES","AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL","ArrayMethods(Common): @property def unit(self): return self / self.mag @property def rho(self): out =","return self._scalar(operator.lshift, other, True) def __rshift__(self, other): return self._scalar(operator.rshift, other) def __rrshift__(self, other):","raise TypeError(\"spatial vectors have no natural ordering\") def __gt__(self, other): raise TypeError(\"spatial vectors","awkward.util.numpy.absolute(tmp.z) out = (tmp.x < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out","other, tolerance=1e-10): tmp = self + other return abs(tmp.x) < tolerance and abs(tmp.y)","return self._scalar(operator.rshift, other) def __rrshift__(self, other): return self._scalar(operator.rshift, other, True) def __and__(self, other):","def __ror__(self, other): return self._scalar(operator.or_, other, True) def __xor__(self, other): return self._scalar(operator.xor, other)","OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE","without # modification, are permitted provided that the following conditions are met: #","+ other return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and abs(tmp.z) <","in binary form must reproduce the above copyright notice, # this list of","math.atan2(self.y, self.x) def cosdelta(self, other): m1 = self.mag2 m2 = other.mag2 if m1","All rights reserved. # # Redistribution and use in source and binary forms,","software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY","return self.dot(self) @property def mag(self): return awkward.util.numpy.sqrt(self.mag2) @property def rho2(self): out = self.x*self.x","def __floordiv__(self, other): return self._scalar(operator.floordiv, other) def __rfloordiv__(self, other): return self._scalar(operator.floordiv, other, True)","# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE","other): return self._scalar(operator.and_, other, True) def __or__(self, other): return self._scalar(operator.or_, other) def __ror__(self,","__ror__(self, other): return self._scalar(operator.or_, other, True) def __xor__(self, other): return self._scalar(operator.xor, other) def","INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT","vectors have no natural ordering\") def __ge__(self, other): raise TypeError(\"spatial vectors have no","PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\" # AND ANY EXPRESS","# this software without specific prior written permission. # # THIS SOFTWARE IS","other): return self._scalar(operator.divmod, other) def __rdivmod__(self, other): return self._scalar(operator.divmod, other, True) def __pow__(self,","other, True) def __rshift__(self, other): return self._scalar(operator.rshift, other) def __rrshift__(self, other): return self._scalar(operator.rshift,","out = awkward.util.numpy.arccos(self.cosdelta(other)) if normal is not None: a = self.unit b =","% (2*math.pi) - math.pi def isparallel(self, other, tolerance=1e-10): return 1 - self.cosdelta(other) <","other) def __radd__(self, other): return self._vector(operator.add, other, True) def __sub__(self, other): return self._vector(operator.sub,","phi(self): return awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self, other): denom = self.mag2 * other.mag2 mask","AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE #","return out def isopposite(self, other, tolerance=1e-10): tmp = self + other return abs(tmp.x)","other == 2: return self.mag2 else: return self.mag2**(0.5*other) else: self._scalar(operator.pow, other) # no","have no natural ordering\") class ArrayMethods(Common): @property def unit(self): return self / self.mag","angle(self, other, normal=None, degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other)) if normal is not None: a","# no __rpow__ def __lshift__(self, other): return self._scalar(operator.lshift, other) def __rlshift__(self, other): return","out = math.acos(self.cosdelta(other)) if degrees: out = out * 180.0/math.pi return out def","return awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self, other): denom = self.mag2 * other.mag2 mask =","awkward.util.numpy.sqrt(self.mag2) @property def rho2(self): out = self.x*self.x out = out + self.y*self.y return","mask = (denom > 0) denom = denom[mask] denom[:] = awkward.util.numpy.sqrt(denom) out =","POSSIBILITY OF SUCH DAMAGE. import math import numbers import operator import awkward import","other.mag2 mask = (denom > 0) denom = denom[mask] denom[:] = awkward.util.numpy.sqrt(denom) out","180.0/awkward.util.numpy.pi) return out def isopposite(self, other, tolerance=1e-10): tmp = self + other tmp.x","code must retain the above copyright notice, this # list of conditions and","other, True) def __divmod__(self, other): return self._scalar(operator.divmod, other) def __rdivmod__(self, other): return self._scalar(operator.divmod,","other) def __rfloordiv__(self, other): return self._scalar(operator.floordiv, other, True) def __mod__(self, other): return self._scalar(operator.mod,","self.mag2**(0.5*other) else: self._scalar(operator.pow, other) # no __rpow__ def __lshift__(self, other): return self._scalar(operator.lshift, other)","and the following disclaimer. # # * Redistributions in binary form must reproduce","other): return self._scalar(operator.mod, other, True) def __divmod__(self, other): return self._scalar(operator.divmod, other) def __rdivmod__(self,","__rdiv__(self, other): return self._scalar(operator.div, other, True) def __truediv__(self, other): return self._scalar(operator.truediv, other) def","out = out + self.y*self.y return out def delta_phi(self, other): return (self.phi -","out def isopposite(self, other, tolerance=1e-10): tmp = self + other tmp.x = awkward.util.numpy.absolute(tmp.x)","awkward import awkward.util class Common(object): @property def mag2(self): return self.dot(self) @property def mag(self):","# # * Redistributions in binary form must reproduce the above copyright notice,","< tolerance def __add__(self, other): return self._vector(operator.add, other) def __radd__(self, other): return self._vector(operator.add,","awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self, other): denom = self.mag2 * other.mag2 mask = (denom","< tolerance) return out def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) tmp.x =","tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out = (tmp.x < tolerance) out =","# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING,","and abs(tmp.z) < tolerance def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) return abs(tmp.x)","LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR","awkward.util.numpy.sqrt(denom) out = self.dot(other) out[mask] /= denom mask = awkward.util.numpy.logical_not(mask) out[mask] = 1","True) def __truediv__(self, other): return self._scalar(operator.truediv, other) def __rtruediv__(self, other): return self._scalar(operator.truediv, other,","True) def __floordiv__(self, other): return self._scalar(operator.floordiv, other) def __rfloordiv__(self, other): return self._scalar(operator.floordiv, other,","= 1 return awkward.util.numpy.clip(out, -1, 1) def angle(self, other, normal=None, degrees=False): out =","self._vector(operator.sub, other) def __rsub__(self, other): return self._vector(operator.sub, other, True) def __mul__(self, other): return","* Redistributions in binary form must reproduce the above copyright notice, # this","other) def __rtruediv__(self, other): return self._scalar(operator.truediv, other, True) def __floordiv__(self, other): return self._scalar(operator.floordiv,","__rtruediv__(self, other): return self._scalar(operator.truediv, other, True) def __floordiv__(self, other): return self._scalar(operator.floordiv, other) def","return self._vector(operator.sub, other) def __rsub__(self, other): return self._vector(operator.sub, other, True) def __mul__(self, other):","this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED","r)) def angle(self, other, degrees=False): out = math.acos(self.cosdelta(other)) if degrees: out = out","< tolerance) return out class Methods(Common): @property def unit(self): return self / self.mag","def __rand__(self, other): return self._scalar(operator.and_, other, True) def __or__(self, other): return self._scalar(operator.or_, other)","# * Neither the name of the copyright holder nor the names of","CONTRIBUTORS \"AS IS\" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT","= out * 180.0/math.pi return out def isopposite(self, other, tolerance=1e-10): tmp = self","OF THE POSSIBILITY OF SUCH DAMAGE. import math import numbers import operator import","def __rxor__(self, other): return self._scalar(operator.xor, other, True) def __neg__(self): return self._unary(operator.neg) def __pos__(self):","return out def delta_phi(self, other): return (self.phi - other.phi + math.pi) % (2*math.pi)","__le__(self, other): raise TypeError(\"spatial vectors have no natural ordering\") def __ge__(self, other): raise","with or without # modification, are permitted provided that the following conditions are","b = other.unit out = out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out = awkward.util.numpy.multiply(out,","other): return self._scalar(operator.rshift, other, True) def __and__(self, other): return self._scalar(operator.and_, other) def __rand__(self,","__lshift__(self, other): return self._scalar(operator.lshift, other) def __rlshift__(self, other): return self._scalar(operator.lshift, other, True) def","other): return self._scalar(operator.lshift, other, True) def __rshift__(self, other): return self._scalar(operator.rshift, other) def __rrshift__(self,","vectors have no natural ordering\") class ArrayMethods(Common): @property def unit(self): return self /","out = awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return","other): return self._scalar(operator.truediv, other, True) def __floordiv__(self, other): return self._scalar(operator.floordiv, other) def __rfloordiv__(self,","__divmod__(self, other): return self._scalar(operator.divmod, other) def __rdivmod__(self, other): return self._scalar(operator.divmod, other, True) def","no __rpow__ def __lshift__(self, other): return self._scalar(operator.lshift, other) def __rlshift__(self, other): return self._scalar(operator.lshift,","numbers import operator import awkward import awkward.util class Common(object): @property def mag2(self): return","return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def","isopposite(self, other, tolerance=1e-10): tmp = self + other tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y =","def __mod__(self, other): return self._scalar(operator.mod, other) def __rmod__(self, other): return self._scalar(operator.mod, other, True)","self._scalar(operator.pow, other) # no __rpow__ def __lshift__(self, other): return self._scalar(operator.lshift, other) def __rlshift__(self,","__floordiv__(self, other): return self._scalar(operator.floordiv, other) def __rfloordiv__(self, other): return self._scalar(operator.floordiv, other, True) def","endorse or promote products derived from # this software without specific prior written","__truediv__(self, other): return self._scalar(operator.truediv, other) def __rtruediv__(self, other): return self._scalar(operator.truediv, other, True) def","def __rlshift__(self, other): return self._scalar(operator.lshift, other, True) def __rshift__(self, other): return self._scalar(operator.rshift, other)","ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import math import numbers import operator","other): return self._scalar(operator.or_, other, True) def __xor__(self, other): return self._scalar(operator.xor, other) def __rxor__(self,","# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF","LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND","normal is not None: a = self.unit b = other.unit out = out","and/or other materials provided with the distribution. # # * Neither the name","# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,","Redistributions of source code must retain the above copyright notice, this # list","= self + other return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and","tolerance and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def isperpendicular(self, other, tolerance=1e-10):","tolerance def isantiparallel(self, other, tolerance=1e-10): return self.cosdelta(other) - (-1) < tolerance def iscollinear(self,","self._scalar(operator.mul, other, True) def __div__(self, other): return self._scalar(operator.div, other) def __rdiv__(self, other): return","USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY","/ self.mag @property def rho(self): return math.sqrt(self.rho2) @property def phi(self): return math.atan2(self.y, self.x)","def __lshift__(self, other): return self._scalar(operator.lshift, other) def __rlshift__(self, other): return self._scalar(operator.lshift, other, True)","return self._scalar(operator.floordiv, other) def __rfloordiv__(self, other): return self._scalar(operator.floordiv, other, True) def __mod__(self, other):","tolerance and abs(tmp.z) < tolerance def __add__(self, other): return self._vector(operator.add, other) def __radd__(self,","NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A","import awkward.util class Common(object): @property def mag2(self): return self.dot(self) @property def mag(self): return","WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF","self.y*self.y return out def delta_phi(self, other): return (self.phi - other.phi + math.pi) %","math.pi def isparallel(self, other, tolerance=1e-10): return 1 - self.cosdelta(other) < tolerance def isantiparallel(self,","(self.phi - other.phi + math.pi) % (2*math.pi) - math.pi def isparallel(self, other, tolerance=1e-10):","if m1 == 0 or m2 == 0: return 1.0 r = self.dot(other)","return out def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y","rights reserved. # # Redistribution and use in source and binary forms, with","other.phi + math.pi) % (2*math.pi) - math.pi def isparallel(self, other, tolerance=1e-10): return 1","conditions and the following disclaimer. # # * Redistributions in binary form must","EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import math import numbers","max(-1.0, min(1.0, r)) def angle(self, other, degrees=False): out = math.acos(self.cosdelta(other)) if degrees: out","return awkward.util.numpy.sqrt(self.mag2) @property def rho2(self): out = self.x*self.x out = out + self.y*self.y","self._scalar(operator.div, other, True) def __truediv__(self, other): return self._scalar(operator.truediv, other) def __rtruediv__(self, other): return","1) def angle(self, other, normal=None, degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other)) if normal is not","- other.phi + math.pi) % (2*math.pi) - math.pi def isparallel(self, other, tolerance=1e-10): return","permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS","class ArrayMethods(Common): @property def unit(self): return self / self.mag @property def rho(self): out","the following conditions are met: # # * Redistributions of source code must","copyright holder nor the names of its # contributors may be used to","other, tolerance=1e-10): tmp = self + other tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y)","other): return self._vector(operator.sub, other, True) def __mul__(self, other): return self._scalar(operator.mul, other) def __rmul__(self,","if normal is not None: a = self.unit b = other.unit out =","other) def __rmul__(self, other): return self._scalar(operator.mul, other, True) def __div__(self, other): return self._scalar(operator.div,","OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE,","self.mag2 m2 = other.mag2 if m1 == 0 or m2 == 0: return","THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF","that the following conditions are met: # # * Redistributions of source code","natural ordering\") class ArrayMethods(Common): @property def unit(self): return self / self.mag @property def","reproduce the above copyright notice, # this list of conditions and the following","mask = awkward.util.numpy.logical_not(mask) out[mask] = 1 return awkward.util.numpy.clip(out, -1, 1) def angle(self, other,","other): m1 = self.mag2 m2 = other.mag2 if m1 == 0 or m2","def __rmul__(self, other): return self._scalar(operator.mul, other, True) def __div__(self, other): return self._scalar(operator.div, other)","other): return self._vector(operator.sub, other) def __rsub__(self, other): return self._vector(operator.sub, other, True) def __mul__(self,","@property def mag(self): return awkward.util.numpy.sqrt(self.mag2) @property def rho2(self): out = self.x*self.x out =","def __lt__(self, other): raise TypeError(\"spatial vectors have no natural ordering\") def __gt__(self, other):","self._scalar(operator.or_, other, True) def __xor__(self, other): return self._scalar(operator.xor, other) def __rxor__(self, other): return","out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out def isopposite(self, other, tolerance=1e-10): tmp = self","vectors have no natural ordering\") def __gt__(self, other): raise TypeError(\"spatial vectors have no","self._scalar(operator.divmod, other, True) def __pow__(self, other): if isinstance(other, (numbers.Number, awkward.util.numpy.number)): if other ==","2018, DIANA-HEP # All rights reserved. # # Redistribution and use in source","no natural ordering\") def __le__(self, other): raise TypeError(\"spatial vectors have no natural ordering\")","return self._scalar(operator.div, other) def __rdiv__(self, other): return self._scalar(operator.div, other, True) def __truediv__(self, other):","HOLDERS AND CONTRIBUTORS \"AS IS\" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,","the documentation # and/or other materials provided with the distribution. # # *","GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)","out[mask] = 1 return awkward.util.numpy.clip(out, -1, 1) def angle(self, other, normal=None, degrees=False): out","def __rshift__(self, other): return self._scalar(operator.rshift, other) def __rrshift__(self, other): return self._scalar(operator.rshift, other, True)","TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE","-1, 1) def angle(self, other, normal=None, degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other)) if normal is","def __rtruediv__(self, other): return self._scalar(operator.truediv, other, True) def __floordiv__(self, other): return self._scalar(operator.floordiv, other)","ordering\") def __le__(self, other): raise TypeError(\"spatial vectors have no natural ordering\") def __ge__(self,","tolerance) return out class Methods(Common): @property def unit(self): return self / self.mag @property","def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) return abs(tmp.x) < tolerance and abs(tmp.y)","awkward.util.numpy.logical_not(mask) out[mask] = 1 return awkward.util.numpy.clip(out, -1, 1) def angle(self, other, normal=None, degrees=False):","(2*math.pi) - math.pi def isparallel(self, other, tolerance=1e-10): return 1 - self.cosdelta(other) < tolerance","normal=None, degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other)) if normal is not None: a = self.unit","other) def __rlshift__(self, other): return self._scalar(operator.lshift, other, True) def __rshift__(self, other): return self._scalar(operator.rshift,","tolerance=1e-10): tmp = self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z)","other tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out = (tmp.x","IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\" # AND ANY","__rmul__(self, other): return self._scalar(operator.mul, other, True) def __div__(self, other): return self._scalar(operator.div, other) def","self._scalar(operator.and_, other) def __rand__(self, other): return self._scalar(operator.and_, other, True) def __or__(self, other): return","+ math.pi) % (2*math.pi) - math.pi def isparallel(self, other, tolerance=1e-10): return 1 -","def unit(self): return self / self.mag @property def rho(self): out = self.rho2 return","or without # modification, are permitted provided that the following conditions are met:","CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY","and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def __add__(self, other): return self._vector(operator.add,","without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE","awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out = (tmp.x < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.y","phi(self): return math.atan2(self.y, self.x) def cosdelta(self, other): m1 = self.mag2 m2 = other.mag2","other, True) def __sub__(self, other): return self._vector(operator.sub, other) def __rsub__(self, other): return self._vector(operator.sub,","= (tmp.x < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out,","2: return self.mag2 else: return self.mag2**(0.5*other) else: self._scalar(operator.pow, other) # no __rpow__ def","THE POSSIBILITY OF SUCH DAMAGE. import math import numbers import operator import awkward","- self.cosdelta(other) < tolerance def isantiparallel(self, other, tolerance=1e-10): return self.cosdelta(other) - (-1) <","def __radd__(self, other): return self._vector(operator.add, other, True) def __sub__(self, other): return self._vector(operator.sub, other)","(numbers.Number, awkward.util.numpy.number)): if other == 2: return self.mag2 else: return self.mag2**(0.5*other) else: self._scalar(operator.pow,","* m2) return max(-1.0, min(1.0, r)) def angle(self, other, degrees=False): out = math.acos(self.cosdelta(other))","copyright notice, # this list of conditions and the following disclaimer in the","awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out class Methods(Common): @property def unit(self): return self","or m2 == 0: return 1.0 r = self.dot(other) / math.sqrt(m1 * m2)","BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL #","THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL,","python # Copyright (c) 2018, DIANA-HEP # All rights reserved. # # Redistribution","self._scalar(operator.and_, other, True) def __or__(self, other): return self._scalar(operator.or_, other) def __ror__(self, other): return","__mul__(self, other): return self._scalar(operator.mul, other) def __rmul__(self, other): return self._scalar(operator.mul, other, True) def","other) def __rdiv__(self, other): return self._scalar(operator.div, other, True) def __truediv__(self, other): return self._scalar(operator.truediv,","TypeError(\"spatial vectors have no natural ordering\") def __le__(self, other): raise TypeError(\"spatial vectors have","def phi(self): return math.atan2(self.y, self.x) def cosdelta(self, other): m1 = self.mag2 m2 =","isopposite(self, other, tolerance=1e-10): tmp = self + other return abs(tmp.x) < tolerance and","notice, this # list of conditions and the following disclaimer. # # *","def mag2(self): return self.dot(self) @property def mag(self): return awkward.util.numpy.sqrt(self.mag2) @property def rho2(self): out","INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,","abs(tmp.z) < tolerance def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) return abs(tmp.x) <","documentation # and/or other materials provided with the distribution. # # * Neither","(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS","import awkward import awkward.util class Common(object): @property def mag2(self): return self.dot(self) @property def","other): raise TypeError(\"spatial vectors have no natural ordering\") def __ge__(self, other): raise TypeError(\"spatial","> 0) denom = denom[mask] denom[:] = awkward.util.numpy.sqrt(denom) out = self.dot(other) out[mask] /=","this list of conditions and the following disclaimer in the documentation # and/or","of conditions and the following disclaimer in the documentation # and/or other materials","awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other)","are permitted provided that the following conditions are met: # # * Redistributions","True) def __neg__(self): return self._unary(operator.neg) def __pos__(self): return self._unary(operator.pos) def __abs__(self): return self.mag","= awkward.util.numpy.arccos(self.cosdelta(other)) if normal is not None: a = self.unit b = other.unit","list of conditions and the following disclaimer. # # * Redistributions in binary","other, tolerance=1e-10): tmp = self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z =","list of conditions and the following disclaimer in the documentation # and/or other","def mag(self): return awkward.util.numpy.sqrt(self.mag2) @property def rho2(self): out = self.x*self.x out = out","awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out def","SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF","name of the copyright holder nor the names of its # contributors may","NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF","and use in source and binary forms, with or without # modification, are","FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT","< tolerance and abs(tmp.z) < tolerance def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other)","the distribution. # # * Neither the name of the copyright holder nor","# this list of conditions and the following disclaimer in the documentation #","provided that the following conditions are met: # # * Redistributions of source","DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED","iscollinear(self, other, tolerance=1e-10): return 1 - awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def __lt__(self, other): raise","tolerance=1e-10): tmp = self + other return abs(tmp.x) < tolerance and abs(tmp.y) <","m1 == 0 or m2 == 0: return 1.0 r = self.dot(other) /","awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out def isopposite(self, other, tolerance=1e-10): tmp = self + other","@property def mag2(self): return self.dot(self) @property def mag(self): return awkward.util.numpy.sqrt(self.mag2) @property def rho2(self):","other, True) def __pow__(self, other): if isinstance(other, (numbers.Number, awkward.util.numpy.number)): if other == 2:","other): return self._scalar(operator.or_, other) def __ror__(self, other): return self._scalar(operator.or_, other, True) def __xor__(self,","self.cosdelta(other) - (-1) < tolerance def iscollinear(self, other, tolerance=1e-10): return 1 - awkward.util.numpy.absolute(self.cosdelta(other))","__ge__(self, other): raise TypeError(\"spatial vectors have no natural ordering\") class ArrayMethods(Common): @property def","DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE #","Methods(Common): @property def unit(self): return self / self.mag @property def rho(self): return math.sqrt(self.rho2)","SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import math import","import math import numbers import operator import awkward import awkward.util class Common(object): @property","__and__(self, other): return self._scalar(operator.and_, other) def __rand__(self, other): return self._scalar(operator.and_, other, True) def","def isantiparallel(self, other, tolerance=1e-10): return self.cosdelta(other) - (-1) < tolerance def iscollinear(self, other,","return self._vector(operator.add, other) def __radd__(self, other): return self._vector(operator.add, other, True) def __sub__(self, other):","awkward.util.numpy.number)): if other == 2: return self.mag2 else: return self.mag2**(0.5*other) else: self._scalar(operator.pow, other)","self + other return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and abs(tmp.z)","# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE","denom mask = awkward.util.numpy.logical_not(mask) out[mask] = 1 return awkward.util.numpy.clip(out, -1, 1) def angle(self,","tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out def isperpendicular(self,","@property def phi(self): return math.atan2(self.y, self.x) def cosdelta(self, other): m1 = self.mag2 m2","of its # contributors may be used to endorse or promote products derived","its # contributors may be used to endorse or promote products derived from","return self._scalar(operator.floordiv, other, True) def __mod__(self, other): return self._scalar(operator.mod, other) def __rmod__(self, other):","self._scalar(operator.lshift, other, True) def __rshift__(self, other): return self._scalar(operator.rshift, other) def __rrshift__(self, other): return","not None: a = self.unit b = other.unit out = out * awkward.util.numpy.sign(normal.dot(a.cross(b)))","__sub__(self, other): return self._vector(operator.sub, other) def __rsub__(self, other): return self._vector(operator.sub, other, True) def","self._scalar(operator.divmod, other) def __rdivmod__(self, other): return self._scalar(operator.divmod, other, True) def __pow__(self, other): if","True) def __sub__(self, other): return self._vector(operator.sub, other) def __rsub__(self, other): return self._vector(operator.sub, other,","awkward.util.numpy.sqrt(out) @property def phi(self): return awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self, other): denom = self.mag2","< tolerance def isantiparallel(self, other, tolerance=1e-10): return self.cosdelta(other) - (-1) < tolerance def","def cosdelta(self, other): denom = self.mag2 * other.mag2 mask = (denom > 0)","OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER","WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING","__div__(self, other): return self._scalar(operator.div, other) def __rdiv__(self, other): return self._scalar(operator.div, other, True) def","OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE","OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS","IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR","def __rdivmod__(self, other): return self._scalar(operator.divmod, other, True) def __pow__(self, other): if isinstance(other, (numbers.Number,","self.unit b = other.unit out = out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out =","out = self.dot(other) out[mask] /= denom mask = awkward.util.numpy.logical_not(mask) out[mask] = 1 return","other): return self._scalar(operator.and_, other) def __rand__(self, other): return self._scalar(operator.and_, other, True) def __or__(self,","out class Methods(Common): @property def unit(self): return self / self.mag @property def rho(self):","__xor__(self, other): return self._scalar(operator.xor, other) def __rxor__(self, other): return self._scalar(operator.xor, other, True) def","contributors may be used to endorse or promote products derived from # this","< tolerance def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) return abs(tmp.x) < tolerance","return self._scalar(operator.or_, other) def __ror__(self, other): return self._scalar(operator.or_, other, True) def __xor__(self, other):","r = self.dot(other) / math.sqrt(m1 * m2) return max(-1.0, min(1.0, r)) def angle(self,","NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY","return self._scalar(operator.mod, other) def __rmod__(self, other): return self._scalar(operator.mod, other, True) def __divmod__(self, other):","Redistribution and use in source and binary forms, with or without # modification,","= other.mag2 if m1 == 0 or m2 == 0: return 1.0 r","other): return self._scalar(operator.lshift, other) def __rlshift__(self, other): return self._scalar(operator.lshift, other, True) def __rshift__(self,","source and binary forms, with or without # modification, are permitted provided that","BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR","out = (tmp.x < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out =","class Common(object): @property def mag2(self): return self.dot(self) @property def mag(self): return awkward.util.numpy.sqrt(self.mag2) @property","self / self.mag @property def rho(self): return math.sqrt(self.rho2) @property def phi(self): return math.atan2(self.y,","the name of the copyright holder nor the names of its # contributors","FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE","return self._vector(operator.add, other, True) def __sub__(self, other): return self._vector(operator.sub, other) def __rsub__(self, other):","angle(self, other, degrees=False): out = math.acos(self.cosdelta(other)) if degrees: out = out * 180.0/math.pi","= self.mag2 * other.mag2 mask = (denom > 0) denom = denom[mask] denom[:]","math.pi) % (2*math.pi) - math.pi def isparallel(self, other, tolerance=1e-10): return 1 - self.cosdelta(other)","of conditions and the following disclaimer. # # * Redistributions in binary form","= awkward.util.numpy.sqrt(denom) out = self.dot(other) out[mask] /= denom mask = awkward.util.numpy.logical_not(mask) out[mask] =","CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, #","other): return self._vector(operator.add, other) def __radd__(self, other): return self._vector(operator.add, other, True) def __sub__(self,","self._scalar(operator.mod, other) def __rmod__(self, other): return self._scalar(operator.mod, other, True) def __divmod__(self, other): return","math.sqrt(self.rho2) @property def phi(self): return math.atan2(self.y, self.x) def cosdelta(self, other): m1 = self.mag2","tmp = self + other return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance","above copyright notice, this # list of conditions and the following disclaimer. #","out = out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out","the following disclaimer. # # * Redistributions in binary form must reproduce the","derived from # this software without specific prior written permission. # # THIS","self._scalar(operator.xor, other, True) def __neg__(self): return self._unary(operator.neg) def __pos__(self): return self._unary(operator.pos) def __abs__(self):","HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT","min(1.0, r)) def angle(self, other, degrees=False): out = math.acos(self.cosdelta(other)) if degrees: out =","* other.mag2 mask = (denom > 0) denom = denom[mask] denom[:] = awkward.util.numpy.sqrt(denom)","= awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out def isopposite(self, other, tolerance=1e-10): tmp = self +","== 0 or m2 == 0: return 1.0 r = self.dot(other) / math.sqrt(m1","/ math.sqrt(m1 * m2) return max(-1.0, min(1.0, r)) def angle(self, other, degrees=False): out","self + other tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out","is not None: a = self.unit b = other.unit out = out *","< tolerance and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def __add__(self, other):","tolerance def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) return abs(tmp.x) < tolerance and","return out def isopposite(self, other, tolerance=1e-10): tmp = self + other tmp.x =","ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING","return self._vector(operator.sub, other, True) def __mul__(self, other): return self._scalar(operator.mul, other) def __rmul__(self, other):","rho(self): return math.sqrt(self.rho2) @property def phi(self): return math.atan2(self.y, self.x) def cosdelta(self, other): m1","# # * Neither the name of the copyright holder nor the names","__rand__(self, other): return self._scalar(operator.and_, other, True) def __or__(self, other): return self._scalar(operator.or_, other) def","rho(self): out = self.rho2 return awkward.util.numpy.sqrt(out) @property def phi(self): return awkward.util.numpy.arctan2(self.y, self.x) def","isantiparallel(self, other, tolerance=1e-10): return self.cosdelta(other) - (-1) < tolerance def iscollinear(self, other, tolerance=1e-10):","other): return (self.phi - other.phi + math.pi) % (2*math.pi) - math.pi def isparallel(self,","# contributors may be used to endorse or promote products derived from #","@property def rho(self): out = self.rho2 return awkward.util.numpy.sqrt(out) @property def phi(self): return awkward.util.numpy.arctan2(self.y,","permitted provided that the following conditions are met: # # * Redistributions of","self.mag @property def rho(self): return math.sqrt(self.rho2) @property def phi(self): return math.atan2(self.y, self.x) def","isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) return abs(tmp.x) < tolerance and abs(tmp.y) <","/= denom mask = awkward.util.numpy.logical_not(mask) out[mask] = 1 return awkward.util.numpy.clip(out, -1, 1) def","0 or m2 == 0: return 1.0 r = self.dot(other) / math.sqrt(m1 *","other, tolerance=1e-10): tmp = self.dot(other) return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance","__rmod__(self, other): return self._scalar(operator.mod, other, True) def __divmod__(self, other): return self._scalar(operator.divmod, other) def","m2 == 0: return 1.0 r = self.dot(other) / math.sqrt(m1 * m2) return","HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY,","other materials provided with the distribution. # # * Neither the name of","__or__(self, other): return self._scalar(operator.or_, other) def __ror__(self, other): return self._scalar(operator.or_, other, True) def","math.acos(self.cosdelta(other)) if degrees: out = out * 180.0/math.pi return out def isopposite(self, other,","COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\" # AND ANY EXPRESS OR IMPLIED WARRANTIES,","* 180.0/math.pi return out def isopposite(self, other, tolerance=1e-10): tmp = self + other","tolerance and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def __add__(self, other): return","degrees: out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out def isopposite(self, other, tolerance=1e-10): tmp =","return self._unary(operator.neg) def __pos__(self): return self._unary(operator.pos) def __abs__(self): return self.mag def __invert__(self): return","= self + other tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z)","__rsub__(self, other): return self._vector(operator.sub, other, True) def __mul__(self, other): return self._scalar(operator.mul, other) def","awkward.util class Common(object): @property def mag2(self): return self.dot(self) @property def mag(self): return awkward.util.numpy.sqrt(self.mag2)","self.dot(self) @property def mag(self): return awkward.util.numpy.sqrt(self.mag2) @property def rho2(self): out = self.x*self.x out","tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out def isperpendicular(self, other, tolerance=1e-10):","and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def isperpendicular(self, other, tolerance=1e-10): tmp","def __and__(self, other): return self._scalar(operator.and_, other) def __rand__(self, other): return self._scalar(operator.and_, other, True)","tmp = self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out","self.dot(other) out[mask] /= denom mask = awkward.util.numpy.logical_not(mask) out[mask] = 1 return awkward.util.numpy.clip(out, -1,","other): return self._scalar(operator.xor, other, True) def __neg__(self): return self._unary(operator.neg) def __pos__(self): return self._unary(operator.pos)","def isparallel(self, other, tolerance=1e-10): return 1 - self.cosdelta(other) < tolerance def isantiparallel(self, other,","OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO","= out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out def","tolerance def __lt__(self, other): raise TypeError(\"spatial vectors have no natural ordering\") def __gt__(self,","def __add__(self, other): return self._vector(operator.add, other) def __radd__(self, other): return self._vector(operator.add, other, True)","self._scalar(operator.truediv, other, True) def __floordiv__(self, other): return self._scalar(operator.floordiv, other) def __rfloordiv__(self, other): return","forms, with or without # modification, are permitted provided that the following conditions","ordering\") def __gt__(self, other): raise TypeError(\"spatial vectors have no natural ordering\") def __le__(self,","Copyright (c) 2018, DIANA-HEP # All rights reserved. # # Redistribution and use","# # * Redistributions of source code must retain the above copyright notice,","with the distribution. # # * Neither the name of the copyright holder","above copyright notice, # this list of conditions and the following disclaimer in","= other.unit out = out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi)","def unit(self): return self / self.mag @property def rho(self): return math.sqrt(self.rho2) @property def","tolerance=1e-10): tmp = self.dot(other) return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and","other, True) def __or__(self, other): return self._scalar(operator.or_, other) def __ror__(self, other): return self._scalar(operator.or_,","= awkward.util.numpy.absolute(tmp.z) out = (tmp.x < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.y < tolerance)","return self._scalar(operator.div, other, True) def __truediv__(self, other): return self._scalar(operator.truediv, other) def __rtruediv__(self, other):","other): return self._scalar(operator.rshift, other) def __rrshift__(self, other): return self._scalar(operator.rshift, other, True) def __and__(self,","other): return self._scalar(operator.xor, other) def __rxor__(self, other): return self._scalar(operator.xor, other, True) def __neg__(self):","in source and binary forms, with or without # modification, are permitted provided","tolerance def iscollinear(self, other, tolerance=1e-10): return 1 - awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def __lt__(self,","other, True) def __mod__(self, other): return self._scalar(operator.mod, other) def __rmod__(self, other): return self._scalar(operator.mod,","other): return self._scalar(operator.floordiv, other, True) def __mod__(self, other): return self._scalar(operator.mod, other) def __rmod__(self,","IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF","@property def unit(self): return self / self.mag @property def rho(self): out = self.rho2","the following disclaimer in the documentation # and/or other materials provided with the","PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY,","delta_phi(self, other): return (self.phi - other.phi + math.pi) % (2*math.pi) - math.pi def","cosdelta(self, other): m1 = self.mag2 m2 = other.mag2 if m1 == 0 or","# # Redistribution and use in source and binary forms, with or without","tolerance and abs(tmp.z) < tolerance def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) return","return self._scalar(operator.mul, other, True) def __div__(self, other): return self._scalar(operator.div, other) def __rdiv__(self, other):","out[mask] /= denom mask = awkward.util.numpy.logical_not(mask) out[mask] = 1 return awkward.util.numpy.clip(out, -1, 1)","ordering\") def __ge__(self, other): raise TypeError(\"spatial vectors have no natural ordering\") class ArrayMethods(Common):","tmp = self.dot(other) return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and abs(tmp.z)","__neg__(self): return self._unary(operator.neg) def __pos__(self): return self._unary(operator.pos) def __abs__(self): return self.mag def __invert__(self):","other) def __rsub__(self, other): return self._vector(operator.sub, other, True) def __mul__(self, other): return self._scalar(operator.mul,","= awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out","__rlshift__(self, other): return self._scalar(operator.lshift, other, True) def __rshift__(self, other): return self._scalar(operator.rshift, other) def","the above copyright notice, this # list of conditions and the following disclaimer.","TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE","used to endorse or promote products derived from # this software without specific","< tolerance and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def isperpendicular(self, other,","self.dot(other) return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance","awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out = (tmp.x < tolerance) out","__rxor__(self, other): return self._scalar(operator.xor, other, True) def __neg__(self): return self._unary(operator.neg) def __pos__(self): return","other) # no __rpow__ def __lshift__(self, other): return self._scalar(operator.lshift, other) def __rlshift__(self, other):","(-1) < tolerance def iscollinear(self, other, tolerance=1e-10): return 1 - awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance","math import numbers import operator import awkward import awkward.util class Common(object): @property def","= awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out = (tmp.x < tolerance)","< tolerance def __lt__(self, other): raise TypeError(\"spatial vectors have no natural ordering\") def","awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out def isopposite(self, other, tolerance=1e-10):","< tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out class Methods(Common): @property","have no natural ordering\") def __ge__(self, other): raise TypeError(\"spatial vectors have no natural","promote products derived from # this software without specific prior written permission. #","other): return self._scalar(operator.mul, other, True) def __div__(self, other): return self._scalar(operator.div, other) def __rdiv__(self,","prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS","return awkward.util.numpy.clip(out, -1, 1) def angle(self, other, normal=None, degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other)) if","self._scalar(operator.mod, other, True) def __divmod__(self, other): return self._scalar(operator.divmod, other) def __rdivmod__(self, other): return","tmp.z < tolerance) return out def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) tmp.x","class Methods(Common): @property def unit(self): return self / self.mag @property def rho(self): return","abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def isperpendicular(self,","return 1 - self.cosdelta(other) < tolerance def isantiparallel(self, other, tolerance=1e-10): return self.cosdelta(other) -","@property def phi(self): return awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self, other): denom = self.mag2 *","(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE #","self._vector(operator.add, other, True) def __sub__(self, other): return self._vector(operator.sub, other) def __rsub__(self, other): return","True) def __mod__(self, other): return self._scalar(operator.mod, other) def __rmod__(self, other): return self._scalar(operator.mod, other,","1 - awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def __lt__(self, other): raise TypeError(\"spatial vectors have no","True) def __div__(self, other): return self._scalar(operator.div, other) def __rdiv__(self, other): return self._scalar(operator.div, other,","== 2: return self.mag2 else: return self.mag2**(0.5*other) else: self._scalar(operator.pow, other) # no __rpow__","self._scalar(operator.rshift, other) def __rrshift__(self, other): return self._scalar(operator.rshift, other, True) def __and__(self, other): return","<gh_stars>0 #!/usr/bin/env python # Copyright (c) 2018, DIANA-HEP # All rights reserved. #","@property def unit(self): return self / self.mag @property def rho(self): return math.sqrt(self.rho2) @property","denom[mask] denom[:] = awkward.util.numpy.sqrt(denom) out = self.dot(other) out[mask] /= denom mask = awkward.util.numpy.logical_not(mask)","other, True) def __mul__(self, other): return self._scalar(operator.mul, other) def __rmul__(self, other): return self._scalar(operator.mul,","cosdelta(self, other): denom = self.mag2 * other.mag2 mask = (denom > 0) denom","self.mag2 else: return self.mag2**(0.5*other) else: self._scalar(operator.pow, other) # no __rpow__ def __lshift__(self, other):","True) def __xor__(self, other): return self._scalar(operator.xor, other) def __rxor__(self, other): return self._scalar(operator.xor, other,","if isinstance(other, (numbers.Number, awkward.util.numpy.number)): if other == 2: return self.mag2 else: return self.mag2**(0.5*other)","180.0/math.pi return out def isopposite(self, other, tolerance=1e-10): tmp = self + other return","= self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out =","rho2(self): out = self.x*self.x out = out + self.y*self.y return out def delta_phi(self,","m2) return max(-1.0, min(1.0, r)) def angle(self, other, degrees=False): out = math.acos(self.cosdelta(other)) if","= self.mag2 m2 = other.mag2 if m1 == 0 or m2 == 0:","use in source and binary forms, with or without # modification, are permitted","tmp = self + other tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z =","IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED.","self.x*self.x out = out + self.y*self.y return out def delta_phi(self, other): return (self.phi","THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\" #","unit(self): return self / self.mag @property def rho(self): out = self.rho2 return awkward.util.numpy.sqrt(out)","= self.dot(other) return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and abs(tmp.z) <","operator import awkward import awkward.util class Common(object): @property def mag2(self): return self.dot(self) @property","OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR","True) def __or__(self, other): return self._scalar(operator.or_, other) def __ror__(self, other): return self._scalar(operator.or_, other,","must reproduce the above copyright notice, # this list of conditions and the","other, tolerance=1e-10): return self.cosdelta(other) - (-1) < tolerance def iscollinear(self, other, tolerance=1e-10): return","return self._scalar(operator.xor, other) def __rxor__(self, other): return self._scalar(operator.xor, other, True) def __neg__(self): return","this # list of conditions and the following disclaimer. # # * Redistributions","# All rights reserved. # # Redistribution and use in source and binary","* awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out def isopposite(self, other,","following conditions are met: # # * Redistributions of source code must retain","self._scalar(operator.mul, other) def __rmul__(self, other): return self._scalar(operator.mul, other, True) def __div__(self, other): return","# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE #","def isopposite(self, other, tolerance=1e-10): tmp = self + other tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y","other): return self._scalar(operator.mul, other) def __rmul__(self, other): return self._scalar(operator.mul, other, True) def __div__(self,","disclaimer in the documentation # and/or other materials provided with the distribution. #","return math.sqrt(self.rho2) @property def phi(self): return math.atan2(self.y, self.x) def cosdelta(self, other): m1 =","to endorse or promote products derived from # this software without specific prior","if degrees: out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out def isopposite(self, other, tolerance=1e-10): tmp","True) def __and__(self, other): return self._scalar(operator.and_, other) def __rand__(self, other): return self._scalar(operator.and_, other,","OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER","Common(object): @property def mag2(self): return self.dot(self) @property def mag(self): return awkward.util.numpy.sqrt(self.mag2) @property def","return self._scalar(operator.mod, other, True) def __divmod__(self, other): return self._scalar(operator.divmod, other) def __rdivmod__(self, other):","return self._scalar(operator.divmod, other, True) def __pow__(self, other): if isinstance(other, (numbers.Number, awkward.util.numpy.number)): if other","- (-1) < tolerance def iscollinear(self, other, tolerance=1e-10): return 1 - awkward.util.numpy.absolute(self.cosdelta(other)) <","INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO,","__mod__(self, other): return self._scalar(operator.mod, other) def __rmod__(self, other): return self._scalar(operator.mod, other, True) def","abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def __add__(self, other): return self._vector(operator.add, other)","tolerance def __add__(self, other): return self._vector(operator.add, other) def __radd__(self, other): return self._vector(operator.add, other,","tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out class Methods(Common):","EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT,","self / self.mag @property def rho(self): out = self.rho2 return awkward.util.numpy.sqrt(out) @property def","a = self.unit b = other.unit out = out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees:","and abs(tmp.z) < tolerance def __add__(self, other): return self._vector(operator.add, other) def __radd__(self, other):","def rho(self): return math.sqrt(self.rho2) @property def phi(self): return math.atan2(self.y, self.x) def cosdelta(self, other):","isinstance(other, (numbers.Number, awkward.util.numpy.number)): if other == 2: return self.mag2 else: return self.mag2**(0.5*other) else:","def __rdiv__(self, other): return self._scalar(operator.div, other, True) def __truediv__(self, other): return self._scalar(operator.truediv, other)","LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)","distribution. # # * Neither the name of the copyright holder nor the","THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import math","in the documentation # and/or other materials provided with the distribution. # #","TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR","denom = denom[mask] denom[:] = awkward.util.numpy.sqrt(denom) out = self.dot(other) out[mask] /= denom mask","+ other tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out =","AND CONTRIBUTORS \"AS IS\" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT","# and/or other materials provided with the distribution. # # * Neither the","other, normal=None, degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other)) if normal is not None: a =","products derived from # this software without specific prior written permission. # #","SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS","# Copyright (c) 2018, DIANA-HEP # All rights reserved. # # Redistribution and","other): if isinstance(other, (numbers.Number, awkward.util.numpy.number)): if other == 2: return self.mag2 else: return","the above copyright notice, # this list of conditions and the following disclaimer","def __div__(self, other): return self._scalar(operator.div, other) def __rdiv__(self, other): return self._scalar(operator.div, other, True)","else: return self.mag2**(0.5*other) else: self._scalar(operator.pow, other) # no __rpow__ def __lshift__(self, other): return","(denom > 0) denom = denom[mask] denom[:] = awkward.util.numpy.sqrt(denom) out = self.dot(other) out[mask]","= awkward.util.numpy.logical_not(mask) out[mask] = 1 return awkward.util.numpy.clip(out, -1, 1) def angle(self, other, normal=None,","from # this software without specific prior written permission. # # THIS SOFTWARE","def __mul__(self, other): return self._scalar(operator.mul, other) def __rmul__(self, other): return self._scalar(operator.mul, other, True)","= (denom > 0) denom = denom[mask] denom[:] = awkward.util.numpy.sqrt(denom) out = self.dot(other)","return self._scalar(operator.mul, other) def __rmul__(self, other): return self._scalar(operator.mul, other, True) def __div__(self, other):","out def isopposite(self, other, tolerance=1e-10): tmp = self + other return abs(tmp.x) <","__rpow__ def __lshift__(self, other): return self._scalar(operator.lshift, other) def __rlshift__(self, other): return self._scalar(operator.lshift, other,","raise TypeError(\"spatial vectors have no natural ordering\") class ArrayMethods(Common): @property def unit(self): return","other) def __ror__(self, other): return self._scalar(operator.or_, other, True) def __xor__(self, other): return self._scalar(operator.xor,","other) def __rxor__(self, other): return self._scalar(operator.xor, other, True) def __neg__(self): return self._unary(operator.neg) def","be used to endorse or promote products derived from # this software without","OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF","self._scalar(operator.or_, other) def __ror__(self, other): return self._scalar(operator.or_, other, True) def __xor__(self, other): return","IS\" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,","* Neither the name of the copyright holder nor the names of its","return self._scalar(operator.xor, other, True) def __neg__(self): return self._unary(operator.neg) def __pos__(self): return self._unary(operator.pos) def","OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON","self._scalar(operator.floordiv, other, True) def __mod__(self, other): return self._scalar(operator.mod, other) def __rmod__(self, other): return","IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY","other): return self._scalar(operator.floordiv, other) def __rfloordiv__(self, other): return self._scalar(operator.floordiv, other, True) def __mod__(self,","@property def rho2(self): out = self.x*self.x out = out + self.y*self.y return out","1.0 r = self.dot(other) / math.sqrt(m1 * m2) return max(-1.0, min(1.0, r)) def","BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN","FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT","other): return self._scalar(operator.div, other, True) def __truediv__(self, other): return self._scalar(operator.truediv, other) def __rtruediv__(self,","return self._scalar(operator.rshift, other, True) def __and__(self, other): return self._scalar(operator.and_, other) def __rand__(self, other):","USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH","def isopposite(self, other, tolerance=1e-10): tmp = self + other return abs(tmp.x) < tolerance","out = self.rho2 return awkward.util.numpy.sqrt(out) @property def phi(self): return awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self,","materials provided with the distribution. # # * Neither the name of the","tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance)","m2 = other.mag2 if m1 == 0 or m2 == 0: return 1.0","EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE","natural ordering\") def __ge__(self, other): raise TypeError(\"spatial vectors have no natural ordering\") class","PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR","self.dot(other) / math.sqrt(m1 * m2) return max(-1.0, min(1.0, r)) def angle(self, other, degrees=False):","__rfloordiv__(self, other): return self._scalar(operator.floordiv, other, True) def __mod__(self, other): return self._scalar(operator.mod, other) def","mag(self): return awkward.util.numpy.sqrt(self.mag2) @property def rho2(self): out = self.x*self.x out = out +","0) denom = denom[mask] denom[:] = awkward.util.numpy.sqrt(denom) out = self.dot(other) out[mask] /= denom","IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN","and binary forms, with or without # modification, are permitted provided that the","conditions and the following disclaimer in the documentation # and/or other materials provided","SUCH DAMAGE. import math import numbers import operator import awkward import awkward.util class","raise TypeError(\"spatial vectors have no natural ordering\") def __ge__(self, other): raise TypeError(\"spatial vectors","degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other)) if normal is not None: a = self.unit b","self.x) def cosdelta(self, other): m1 = self.mag2 m2 = other.mag2 if m1 ==","names of its # contributors may be used to endorse or promote products","copyright notice, this # list of conditions and the following disclaimer. # #","SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\" # AND","other, True) def __neg__(self): return self._unary(operator.neg) def __pos__(self): return self._unary(operator.pos) def __abs__(self): return","self._scalar(operator.xor, other) def __rxor__(self, other): return self._scalar(operator.xor, other, True) def __neg__(self): return self._unary(operator.neg)","other): raise TypeError(\"spatial vectors have no natural ordering\") def __gt__(self, other): raise TypeError(\"spatial","have no natural ordering\") def __le__(self, other): raise TypeError(\"spatial vectors have no natural","return max(-1.0, min(1.0, r)) def angle(self, other, degrees=False): out = math.acos(self.cosdelta(other)) if degrees:","return self._scalar(operator.truediv, other, True) def __floordiv__(self, other): return self._scalar(operator.floordiv, other) def __rfloordiv__(self, other):","disclaimer. # # * Redistributions in binary form must reproduce the above copyright","ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED","other): return self._vector(operator.add, other, True) def __sub__(self, other): return self._vector(operator.sub, other) def __rsub__(self,","out def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y =","out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out def isopposite(self,","other): return self._scalar(operator.mod, other) def __rmod__(self, other): return self._scalar(operator.mod, other, True) def __divmod__(self,","= awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out = (tmp.x < tolerance) out = awkward.util.numpy.bitwise_and(out,","= denom[mask] denom[:] = awkward.util.numpy.sqrt(denom) out = self.dot(other) out[mask] /= denom mask =","awkward.util.numpy.clip(out, -1, 1) def angle(self, other, normal=None, degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other)) if normal","return self._scalar(operator.or_, other, True) def __xor__(self, other): return self._scalar(operator.xor, other) def __rxor__(self, other):","WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND","other, tolerance=1e-10): return 1 - awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def __lt__(self, other): raise TypeError(\"spatial","return self / self.mag @property def rho(self): out = self.rho2 return awkward.util.numpy.sqrt(out) @property","provided with the distribution. # # * Neither the name of the copyright","out = out * 180.0/math.pi return out def isopposite(self, other, tolerance=1e-10): tmp =","def iscollinear(self, other, tolerance=1e-10): return 1 - awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def __lt__(self, other):","(c) 2018, DIANA-HEP # All rights reserved. # # Redistribution and use in","A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER","self.mag2 * other.mag2 mask = (denom > 0) denom = denom[mask] denom[:] =","self._scalar(operator.lshift, other) def __rlshift__(self, other): return self._scalar(operator.lshift, other, True) def __rshift__(self, other): return","modification, are permitted provided that the following conditions are met: # # *","def __rfloordiv__(self, other): return self._scalar(operator.floordiv, other, True) def __mod__(self, other): return self._scalar(operator.mod, other)","= math.acos(self.cosdelta(other)) if degrees: out = out * 180.0/math.pi return out def isopposite(self,","def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y)","must retain the above copyright notice, this # list of conditions and the","are met: # # * Redistributions of source code must retain the above","True) def __mul__(self, other): return self._scalar(operator.mul, other) def __rmul__(self, other): return self._scalar(operator.mul, other,","True) def __pow__(self, other): if isinstance(other, (numbers.Number, awkward.util.numpy.number)): if other == 2: return","out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out def isperpendicular(self, other, tolerance=1e-10): tmp","CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR","self.cosdelta(other) < tolerance def isantiparallel(self, other, tolerance=1e-10): return self.cosdelta(other) - (-1) < tolerance","self._scalar(operator.floordiv, other) def __rfloordiv__(self, other): return self._scalar(operator.floordiv, other, True) def __mod__(self, other): return","return self / self.mag @property def rho(self): return math.sqrt(self.rho2) @property def phi(self): return","degrees: out = out * 180.0/math.pi return out def isopposite(self, other, tolerance=1e-10): tmp","def __le__(self, other): raise TypeError(\"spatial vectors have no natural ordering\") def __ge__(self, other):","other.mag2 if m1 == 0 or m2 == 0: return 1.0 r =","return self._scalar(operator.truediv, other) def __rtruediv__(self, other): return self._scalar(operator.truediv, other, True) def __floordiv__(self, other):","True) def __divmod__(self, other): return self._scalar(operator.divmod, other) def __rdivmod__(self, other): return self._scalar(operator.divmod, other,","__pow__(self, other): if isinstance(other, (numbers.Number, awkward.util.numpy.number)): if other == 2: return self.mag2 else:","OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS","def cosdelta(self, other): m1 = self.mag2 m2 = other.mag2 if m1 == 0","< tolerance def iscollinear(self, other, tolerance=1e-10): return 1 - awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def","other): raise TypeError(\"spatial vectors have no natural ordering\") class ArrayMethods(Common): @property def unit(self):","return self.cosdelta(other) - (-1) < tolerance def iscollinear(self, other, tolerance=1e-10): return 1 -","(tmp.x < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z","self.mag @property def rho(self): out = self.rho2 return awkward.util.numpy.sqrt(out) @property def phi(self): return","__lt__(self, other): raise TypeError(\"spatial vectors have no natural ordering\") def __gt__(self, other): raise","ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED","__radd__(self, other): return self._vector(operator.add, other, True) def __sub__(self, other): return self._vector(operator.sub, other) def","the copyright holder nor the names of its # contributors may be used","ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN","tolerance=1e-10): return 1 - awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def __lt__(self, other): raise TypeError(\"spatial vectors","tmp.z < tolerance) return out class Methods(Common): @property def unit(self): return self /","out + self.y*self.y return out def delta_phi(self, other): return (self.phi - other.phi +","other): denom = self.mag2 * other.mag2 mask = (denom > 0) denom =","@property def rho(self): return math.sqrt(self.rho2) @property def phi(self): return math.atan2(self.y, self.x) def cosdelta(self,","mag2(self): return self.dot(self) @property def mag(self): return awkward.util.numpy.sqrt(self.mag2) @property def rho2(self): out =","def __rrshift__(self, other): return self._scalar(operator.rshift, other, True) def __and__(self, other): return self._scalar(operator.and_, other)","raise TypeError(\"spatial vectors have no natural ordering\") def __le__(self, other): raise TypeError(\"spatial vectors","def __sub__(self, other): return self._vector(operator.sub, other) def __rsub__(self, other): return self._vector(operator.sub, other, True)","PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS;","tolerance) return out def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x)","COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,","return self.mag2**(0.5*other) else: self._scalar(operator.pow, other) # no __rpow__ def __lshift__(self, other): return self._scalar(operator.lshift,","SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT,","def __xor__(self, other): return self._scalar(operator.xor, other) def __rxor__(self, other): return self._scalar(operator.xor, other, True)","def __neg__(self): return self._unary(operator.neg) def __pos__(self): return self._unary(operator.pos) def __abs__(self): return self.mag def","DIANA-HEP # All rights reserved. # # Redistribution and use in source and","# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER #","out * 180.0/math.pi return out def isopposite(self, other, tolerance=1e-10): tmp = self +","= self.unit b = other.unit out = out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out","self.rho2 return awkward.util.numpy.sqrt(out) @property def phi(self): return awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self, other): denom","def rho(self): out = self.rho2 return awkward.util.numpy.sqrt(out) @property def phi(self): return awkward.util.numpy.arctan2(self.y, self.x)","other) def __rrshift__(self, other): return self._scalar(operator.rshift, other, True) def __and__(self, other): return self._scalar(operator.and_,","no natural ordering\") def __ge__(self, other): raise TypeError(\"spatial vectors have no natural ordering\")","met: # # * Redistributions of source code must retain the above copyright","= out + self.y*self.y return out def delta_phi(self, other): return (self.phi - other.phi","other) def __rdivmod__(self, other): return self._scalar(operator.divmod, other, True) def __pow__(self, other): if isinstance(other,","= awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out def isperpendicular(self, other, tolerance=1e-10): tmp =","DAMAGE. import math import numbers import operator import awkward import awkward.util class Common(object):","tmp.z = awkward.util.numpy.absolute(tmp.z) out = (tmp.x < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.y <","def __or__(self, other): return self._scalar(operator.or_, other) def __ror__(self, other): return self._scalar(operator.or_, other, True)","DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY","def __truediv__(self, other): return self._scalar(operator.truediv, other) def __rtruediv__(self, other): return self._scalar(operator.truediv, other, True)","other): return self._scalar(operator.divmod, other, True) def __pow__(self, other): if isinstance(other, (numbers.Number, awkward.util.numpy.number)): if","OF SUCH DAMAGE. import math import numbers import operator import awkward import awkward.util","= self.dot(other) out[mask] /= denom mask = awkward.util.numpy.logical_not(mask) out[mask] = 1 return awkward.util.numpy.clip(out,","self._vector(operator.add, other) def __radd__(self, other): return self._vector(operator.add, other, True) def __sub__(self, other): return","Redistributions in binary form must reproduce the above copyright notice, # this list","ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE","/ self.mag @property def rho(self): out = self.rho2 return awkward.util.numpy.sqrt(out) @property def phi(self):","ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT","have no natural ordering\") def __gt__(self, other): raise TypeError(\"spatial vectors have no natural","return out class Methods(Common): @property def unit(self): return self / self.mag @property def","CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL","LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA,","degrees=False): out = math.acos(self.cosdelta(other)) if degrees: out = out * 180.0/math.pi return out","TypeError(\"spatial vectors have no natural ordering\") class ArrayMethods(Common): @property def unit(self): return self","isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z","other, degrees=False): out = math.acos(self.cosdelta(other)) if degrees: out = out * 180.0/math.pi return","LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT","OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import","other): raise TypeError(\"spatial vectors have no natural ordering\") def __le__(self, other): raise TypeError(\"spatial","of the copyright holder nor the names of its # contributors may be","other, True) def __floordiv__(self, other): return self._scalar(operator.floordiv, other) def __rfloordiv__(self, other): return self._scalar(operator.floordiv,","# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"","of source code must retain the above copyright notice, this # list of","- math.pi def isparallel(self, other, tolerance=1e-10): return 1 - self.cosdelta(other) < tolerance def","1 return awkward.util.numpy.clip(out, -1, 1) def angle(self, other, normal=None, degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other))","ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT","= self.x*self.x out = out + self.y*self.y return out def delta_phi(self, other): return","TypeError(\"spatial vectors have no natural ordering\") def __ge__(self, other): raise TypeError(\"spatial vectors have","def rho2(self): out = self.x*self.x out = out + self.y*self.y return out def","self._scalar(operator.rshift, other, True) def __and__(self, other): return self._scalar(operator.and_, other) def __rand__(self, other): return","other): return self._scalar(operator.truediv, other) def __rtruediv__(self, other): return self._scalar(operator.truediv, other, True) def __floordiv__(self,","notice, # this list of conditions and the following disclaimer in the documentation","self._scalar(operator.truediv, other) def __rtruediv__(self, other): return self._scalar(operator.truediv, other, True) def __floordiv__(self, other): return","self._unary(operator.neg) def __pos__(self): return self._unary(operator.pos) def __abs__(self): return self.mag def __invert__(self): return self._unary(operator.invert)","< tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z <","+ self.y*self.y return out def delta_phi(self, other): return (self.phi - other.phi + math.pi)","THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE","MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT","THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\" # AND ANY EXPRESS OR IMPLIED","vectors have no natural ordering\") def __le__(self, other): raise TypeError(\"spatial vectors have no","= self.dot(other) / math.sqrt(m1 * m2) return max(-1.0, min(1.0, r)) def angle(self, other,","return self._scalar(operator.lshift, other) def __rlshift__(self, other): return self._scalar(operator.lshift, other, True) def __rshift__(self, other):","the names of its # contributors may be used to endorse or promote","def __rmod__(self, other): return self._scalar(operator.mod, other, True) def __divmod__(self, other): return self._scalar(operator.divmod, other)","def phi(self): return awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self, other): denom = self.mag2 * other.mag2","DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES;","natural ordering\") def __le__(self, other): raise TypeError(\"spatial vectors have no natural ordering\") def","out def delta_phi(self, other): return (self.phi - other.phi + math.pi) % (2*math.pi) -","def angle(self, other, normal=None, degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other)) if normal is not None:","= awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out class Methods(Common): @property def unit(self): return","tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out class Methods(Common): @property def","abs(tmp.z) < tolerance def __add__(self, other): return self._vector(operator.add, other) def __radd__(self, other): return","return math.atan2(self.y, self.x) def cosdelta(self, other): m1 = self.mag2 m2 = other.mag2 if","self._vector(operator.sub, other, True) def __mul__(self, other): return self._scalar(operator.mul, other) def __rmul__(self, other): return","def __gt__(self, other): raise TypeError(\"spatial vectors have no natural ordering\") def __le__(self, other):","abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def isperpendicular(self, other, tolerance=1e-10): tmp =","return self._scalar(operator.and_, other) def __rand__(self, other): return self._scalar(operator.and_, other, True) def __or__(self, other):","None: a = self.unit b = other.unit out = out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if","other): return self._scalar(operator.div, other) def __rdiv__(self, other): return self._scalar(operator.div, other, True) def __truediv__(self,","= self.rho2 return awkward.util.numpy.sqrt(out) @property def phi(self): return awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self, other):","reserved. # # Redistribution and use in source and binary forms, with or","import numbers import operator import awkward import awkward.util class Common(object): @property def mag2(self):","def __divmod__(self, other): return self._scalar(operator.divmod, other) def __rdivmod__(self, other): return self._scalar(operator.divmod, other, True)","\"AS IS\" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED","if other == 2: return self.mag2 else: return self.mag2**(0.5*other) else: self._scalar(operator.pow, other) #","# Redistribution and use in source and binary forms, with or without #","INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS","self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out = (tmp.x","other, True) def __and__(self, other): return self._scalar(operator.and_, other) def __rand__(self, other): return self._scalar(operator.and_,","< tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out def isperpendicular(self, other,","__rdivmod__(self, other): return self._scalar(operator.divmod, other, True) def __pow__(self, other): if isinstance(other, (numbers.Number, awkward.util.numpy.number)):","def __rsub__(self, other): return self._vector(operator.sub, other, True) def __mul__(self, other): return self._scalar(operator.mul, other)","nor the names of its # contributors may be used to endorse or","< tolerance and abs(tmp.z) < tolerance def __add__(self, other): return self._vector(operator.add, other) def","other, True) def __div__(self, other): return self._scalar(operator.div, other) def __rdiv__(self, other): return self._scalar(operator.div,","source code must retain the above copyright notice, this # list of conditions","conditions are met: # # * Redistributions of source code must retain the","return awkward.util.numpy.sqrt(out) @property def phi(self): return awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self, other): denom =","retain the above copyright notice, this # list of conditions and the following","holder nor the names of its # contributors may be used to endorse","out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out class Methods(Common): @property def unit(self):","BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\" # AND ANY EXPRESS OR","tolerance=1e-10): return 1 - self.cosdelta(other) < tolerance def isantiparallel(self, other, tolerance=1e-10): return self.cosdelta(other)","- awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def __lt__(self, other): raise TypeError(\"spatial vectors have no natural","return (self.phi - other.phi + math.pi) % (2*math.pi) - math.pi def isparallel(self, other,","BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF","tolerance=1e-10): tmp = self + other tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z","tolerance=1e-10): return self.cosdelta(other) - (-1) < tolerance def iscollinear(self, other, tolerance=1e-10): return 1","IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import math import numbers import","STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY","isparallel(self, other, tolerance=1e-10): return 1 - self.cosdelta(other) < tolerance def isantiparallel(self, other, tolerance=1e-10):","tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out = (tmp.x <","return 1.0 r = self.dot(other) / math.sqrt(m1 * m2) return max(-1.0, min(1.0, r))","binary forms, with or without # modification, are permitted provided that the following","other) def __rmod__(self, other): return self._scalar(operator.mod, other, True) def __divmod__(self, other): return self._scalar(operator.divmod,","math.sqrt(m1 * m2) return max(-1.0, min(1.0, r)) def angle(self, other, degrees=False): out =","def __pow__(self, other): if isinstance(other, (numbers.Number, awkward.util.numpy.number)): if other == 2: return self.mag2","awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def __lt__(self, other): raise TypeError(\"spatial vectors have no natural ordering\")","no natural ordering\") class ArrayMethods(Common): @property def unit(self): return self / self.mag @property","ordering\") class ArrayMethods(Common): @property def unit(self): return self / self.mag @property def rho(self):","unit(self): return self / self.mag @property def rho(self): return math.sqrt(self.rho2) @property def phi(self):","other, True) def __truediv__(self, other): return self._scalar(operator.truediv, other) def __rtruediv__(self, other): return self._scalar(operator.truediv,","may be used to endorse or promote products derived from # this software","out = self.x*self.x out = out + self.y*self.y return out def delta_phi(self, other):","denom = self.mag2 * other.mag2 mask = (denom > 0) denom = denom[mask]","THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE","#!/usr/bin/env python # Copyright (c) 2018, DIANA-HEP # All rights reserved. # #","# # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS","True) def __rshift__(self, other): return self._scalar(operator.rshift, other) def __rrshift__(self, other): return self._scalar(operator.rshift, other,","binary form must reproduce the above copyright notice, # this list of conditions","other.unit out = out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return","return 1 - awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def __lt__(self, other): raise TypeError(\"spatial vectors have","following disclaimer in the documentation # and/or other materials provided with the distribution.","other, tolerance=1e-10): return 1 - self.cosdelta(other) < tolerance def isantiparallel(self, other, tolerance=1e-10): return","self.x) def cosdelta(self, other): denom = self.mag2 * other.mag2 mask = (denom >","abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def __add__(self,","else: self._scalar(operator.pow, other) # no __rpow__ def __lshift__(self, other): return self._scalar(operator.lshift, other) def","NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE,","other return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance","form must reproduce the above copyright notice, # this list of conditions and","other, True) def __xor__(self, other): return self._scalar(operator.xor, other) def __rxor__(self, other): return self._scalar(operator.xor,","LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES","# list of conditions and the following disclaimer. # # * Redistributions in","if degrees: out = out * 180.0/math.pi return out def isopposite(self, other, tolerance=1e-10):","__add__(self, other): return self._vector(operator.add, other) def __radd__(self, other): return self._vector(operator.add, other, True) def","self._scalar(operator.div, other) def __rdiv__(self, other): return self._scalar(operator.div, other, True) def __truediv__(self, other): return","return self._scalar(operator.divmod, other) def __rdivmod__(self, other): return self._scalar(operator.divmod, other, True) def __pow__(self, other):","Neither the name of the copyright holder nor the names of its #","def __ge__(self, other): raise TypeError(\"spatial vectors have no natural ordering\") class ArrayMethods(Common): @property","PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS","TypeError(\"spatial vectors have no natural ordering\") def __gt__(self, other): raise TypeError(\"spatial vectors have","OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY","WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN","return self._scalar(operator.and_, other, True) def __or__(self, other): return self._scalar(operator.or_, other) def __ror__(self, other):","denom[:] = awkward.util.numpy.sqrt(denom) out = self.dot(other) out[mask] /= denom mask = awkward.util.numpy.logical_not(mask) out[mask]","awkward.util.numpy.arccos(self.cosdelta(other)) if normal is not None: a = self.unit b = other.unit out","m1 = self.mag2 m2 = other.mag2 if m1 == 0 or m2 ==","SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED","OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR","__rrshift__(self, other): return self._scalar(operator.rshift, other, True) def __and__(self, other): return self._scalar(operator.and_, other) def","OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR","# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.","__gt__(self, other): raise TypeError(\"spatial vectors have no natural ordering\") def __le__(self, other): raise","# * Redistributions of source code must retain the above copyright notice, this","# modification, are permitted provided that the following conditions are met: # #","written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND","# * Redistributions in binary form must reproduce the above copyright notice, #","return self.mag2 else: return self.mag2**(0.5*other) else: self._scalar(operator.pow, other) # no __rpow__ def __lshift__(self,","def angle(self, other, degrees=False): out = math.acos(self.cosdelta(other)) if degrees: out = out *","AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR","== 0: return 1.0 r = self.dot(other) / math.sqrt(m1 * m2) return max(-1.0,","0: return 1.0 r = self.dot(other) / math.sqrt(m1 * m2) return max(-1.0, min(1.0,","1 - self.cosdelta(other) < tolerance def isantiparallel(self, other, tolerance=1e-10): return self.cosdelta(other) - (-1)","no natural ordering\") def __gt__(self, other): raise TypeError(\"spatial vectors have no natural ordering\")","def delta_phi(self, other): return (self.phi - other.phi + math.pi) % (2*math.pi) - math.pi","natural ordering\") def __gt__(self, other): raise TypeError(\"spatial vectors have no natural ordering\") def","__rshift__(self, other): return self._scalar(operator.rshift, other) def __rrshift__(self, other): return self._scalar(operator.rshift, other, True) def","import operator import awkward import awkward.util class Common(object): @property def mag2(self): return self.dot(self)","OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF","or promote products derived from # this software without specific prior written permission.","other) def __rand__(self, other): return self._scalar(operator.and_, other, True) def __or__(self, other): return self._scalar(operator.or_,","specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT","* Redistributions of source code must retain the above copyright notice, this #","following disclaimer. # # * Redistributions in binary form must reproduce the above"],"string":"[\n \"and the following disclaimer in the documentation # and/or other materials provided with\",\n \"# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR #\",\n \"awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out class\",\n \"EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES\",\n \"AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL\",\n \"ArrayMethods(Common): @property def unit(self): return self / self.mag @property def rho(self): out =\",\n \"return self._scalar(operator.lshift, other, True) def __rshift__(self, other): return self._scalar(operator.rshift, other) def __rrshift__(self, other):\",\n \"raise TypeError(\\\"spatial vectors have no natural ordering\\\") def __gt__(self, other): raise TypeError(\\\"spatial vectors\",\n \"awkward.util.numpy.absolute(tmp.z) out = (tmp.x < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out\",\n \"other, tolerance=1e-10): tmp = self + other return abs(tmp.x) < tolerance and abs(tmp.y)\",\n \"return self._scalar(operator.rshift, other) def __rrshift__(self, other): return self._scalar(operator.rshift, other, True) def __and__(self, other):\",\n \"def __ror__(self, other): return self._scalar(operator.or_, other, True) def __xor__(self, other): return self._scalar(operator.xor, other)\",\n \"OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE\",\n \"without # modification, are permitted provided that the following conditions are met: #\",\n \"+ other return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and abs(tmp.z) <\",\n \"in binary form must reproduce the above copyright notice, # this list of\",\n \"math.atan2(self.y, self.x) def cosdelta(self, other): m1 = self.mag2 m2 = other.mag2 if m1\",\n \"All rights reserved. # # Redistribution and use in source and binary forms,\",\n \"software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY\",\n \"return self.dot(self) @property def mag(self): return awkward.util.numpy.sqrt(self.mag2) @property def rho2(self): out = self.x*self.x\",\n \"def __floordiv__(self, other): return self._scalar(operator.floordiv, other) def __rfloordiv__(self, other): return self._scalar(operator.floordiv, other, True)\",\n \"# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\",\n \"other): return self._scalar(operator.and_, other, True) def __or__(self, other): return self._scalar(operator.or_, other) def __ror__(self,\",\n \"__ror__(self, other): return self._scalar(operator.or_, other, True) def __xor__(self, other): return self._scalar(operator.xor, other) def\",\n \"INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT\",\n \"vectors have no natural ordering\\\") def __ge__(self, other): raise TypeError(\\\"spatial vectors have no\",\n \"PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \\\"AS IS\\\" # AND ANY EXPRESS\",\n \"# this software without specific prior written permission. # # THIS SOFTWARE IS\",\n \"other): return self._scalar(operator.divmod, other) def __rdivmod__(self, other): return self._scalar(operator.divmod, other, True) def __pow__(self,\",\n \"other, True) def __rshift__(self, other): return self._scalar(operator.rshift, other) def __rrshift__(self, other): return self._scalar(operator.rshift,\",\n \"out = awkward.util.numpy.arccos(self.cosdelta(other)) if normal is not None: a = self.unit b =\",\n \"% (2*math.pi) - math.pi def isparallel(self, other, tolerance=1e-10): return 1 - self.cosdelta(other) <\",\n \"other) def __radd__(self, other): return self._vector(operator.add, other, True) def __sub__(self, other): return self._vector(operator.sub,\",\n \"phi(self): return awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self, other): denom = self.mag2 * other.mag2 mask\",\n \"AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE #\",\n \"return out def isopposite(self, other, tolerance=1e-10): tmp = self + other return abs(tmp.x)\",\n \"other == 2: return self.mag2 else: return self.mag2**(0.5*other) else: self._scalar(operator.pow, other) # no\",\n \"have no natural ordering\\\") class ArrayMethods(Common): @property def unit(self): return self / self.mag\",\n \"angle(self, other, normal=None, degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other)) if normal is not None: a\",\n \"# no __rpow__ def __lshift__(self, other): return self._scalar(operator.lshift, other) def __rlshift__(self, other): return\",\n \"out = math.acos(self.cosdelta(other)) if degrees: out = out * 180.0/math.pi return out def\",\n \"return awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self, other): denom = self.mag2 * other.mag2 mask =\",\n \"awkward.util.numpy.sqrt(self.mag2) @property def rho2(self): out = self.x*self.x out = out + self.y*self.y return\",\n \"mask = (denom > 0) denom = denom[mask] denom[:] = awkward.util.numpy.sqrt(denom) out =\",\n \"POSSIBILITY OF SUCH DAMAGE. import math import numbers import operator import awkward import\",\n \"other.mag2 mask = (denom > 0) denom = denom[mask] denom[:] = awkward.util.numpy.sqrt(denom) out\",\n \"180.0/awkward.util.numpy.pi) return out def isopposite(self, other, tolerance=1e-10): tmp = self + other tmp.x\",\n \"code must retain the above copyright notice, this # list of conditions and\",\n \"other, True) def __divmod__(self, other): return self._scalar(operator.divmod, other) def __rdivmod__(self, other): return self._scalar(operator.divmod,\",\n \"other) def __rfloordiv__(self, other): return self._scalar(operator.floordiv, other, True) def __mod__(self, other): return self._scalar(operator.mod,\",\n \"self.mag2**(0.5*other) else: self._scalar(operator.pow, other) # no __rpow__ def __lshift__(self, other): return self._scalar(operator.lshift, other)\",\n \"and the following disclaimer. # # * Redistributions in binary form must reproduce\",\n \"other): return self._scalar(operator.mod, other, True) def __divmod__(self, other): return self._scalar(operator.divmod, other) def __rdivmod__(self,\",\n \"__rdiv__(self, other): return self._scalar(operator.div, other, True) def __truediv__(self, other): return self._scalar(operator.truediv, other) def\",\n \"out = out + self.y*self.y return out def delta_phi(self, other): return (self.phi -\",\n \"out def isopposite(self, other, tolerance=1e-10): tmp = self + other tmp.x = awkward.util.numpy.absolute(tmp.x)\",\n \"awkward import awkward.util class Common(object): @property def mag2(self): return self.dot(self) @property def mag(self):\",\n \"# # * Redistributions in binary form must reproduce the above copyright notice,\",\n \"< tolerance def __add__(self, other): return self._vector(operator.add, other) def __radd__(self, other): return self._vector(operator.add,\",\n \"awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self, other): denom = self.mag2 * other.mag2 mask = (denom\",\n \"< tolerance) return out def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) tmp.x =\",\n \"tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out = (tmp.x < tolerance) out =\",\n \"# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING,\",\n \"and abs(tmp.z) < tolerance def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) return abs(tmp.x)\",\n \"LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR\",\n \"awkward.util.numpy.sqrt(denom) out = self.dot(other) out[mask] /= denom mask = awkward.util.numpy.logical_not(mask) out[mask] = 1\",\n \"True) def __truediv__(self, other): return self._scalar(operator.truediv, other) def __rtruediv__(self, other): return self._scalar(operator.truediv, other,\",\n \"True) def __floordiv__(self, other): return self._scalar(operator.floordiv, other) def __rfloordiv__(self, other): return self._scalar(operator.floordiv, other,\",\n \"= 1 return awkward.util.numpy.clip(out, -1, 1) def angle(self, other, normal=None, degrees=False): out =\",\n \"self._vector(operator.sub, other) def __rsub__(self, other): return self._vector(operator.sub, other, True) def __mul__(self, other): return\",\n \"* Redistributions in binary form must reproduce the above copyright notice, # this\",\n \"other) def __rtruediv__(self, other): return self._scalar(operator.truediv, other, True) def __floordiv__(self, other): return self._scalar(operator.floordiv,\",\n \"__rtruediv__(self, other): return self._scalar(operator.truediv, other, True) def __floordiv__(self, other): return self._scalar(operator.floordiv, other) def\",\n \"return self._vector(operator.sub, other) def __rsub__(self, other): return self._vector(operator.sub, other, True) def __mul__(self, other):\",\n \"this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED\",\n \"r)) def angle(self, other, degrees=False): out = math.acos(self.cosdelta(other)) if degrees: out = out\",\n \"< tolerance) return out class Methods(Common): @property def unit(self): return self / self.mag\",\n \"def __rand__(self, other): return self._scalar(operator.and_, other, True) def __or__(self, other): return self._scalar(operator.or_, other)\",\n \"# * Neither the name of the copyright holder nor the names of\",\n \"CONTRIBUTORS \\\"AS IS\\\" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT\",\n \"= out * 180.0/math.pi return out def isopposite(self, other, tolerance=1e-10): tmp = self\",\n \"OF THE POSSIBILITY OF SUCH DAMAGE. import math import numbers import operator import\",\n \"def __rxor__(self, other): return self._scalar(operator.xor, other, True) def __neg__(self): return self._unary(operator.neg) def __pos__(self):\",\n \"return out def delta_phi(self, other): return (self.phi - other.phi + math.pi) % (2*math.pi)\",\n \"__le__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") def __ge__(self, other): raise\",\n \"with or without # modification, are permitted provided that the following conditions are\",\n \"b = other.unit out = out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out = awkward.util.numpy.multiply(out,\",\n \"other): return self._scalar(operator.rshift, other, True) def __and__(self, other): return self._scalar(operator.and_, other) def __rand__(self,\",\n \"__lshift__(self, other): return self._scalar(operator.lshift, other) def __rlshift__(self, other): return self._scalar(operator.lshift, other, True) def\",\n \"other): return self._scalar(operator.lshift, other, True) def __rshift__(self, other): return self._scalar(operator.rshift, other) def __rrshift__(self,\",\n \"vectors have no natural ordering\\\") class ArrayMethods(Common): @property def unit(self): return self /\",\n \"out = awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return\",\n \"other): return self._scalar(operator.truediv, other, True) def __floordiv__(self, other): return self._scalar(operator.floordiv, other) def __rfloordiv__(self,\",\n \"__divmod__(self, other): return self._scalar(operator.divmod, other) def __rdivmod__(self, other): return self._scalar(operator.divmod, other, True) def\",\n \"no __rpow__ def __lshift__(self, other): return self._scalar(operator.lshift, other) def __rlshift__(self, other): return self._scalar(operator.lshift,\",\n \"numbers import operator import awkward import awkward.util class Common(object): @property def mag2(self): return\",\n \"return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def\",\n \"isopposite(self, other, tolerance=1e-10): tmp = self + other tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y =\",\n \"def __mod__(self, other): return self._scalar(operator.mod, other) def __rmod__(self, other): return self._scalar(operator.mod, other, True)\",\n \"self._scalar(operator.pow, other) # no __rpow__ def __lshift__(self, other): return self._scalar(operator.lshift, other) def __rlshift__(self,\",\n \"__floordiv__(self, other): return self._scalar(operator.floordiv, other) def __rfloordiv__(self, other): return self._scalar(operator.floordiv, other, True) def\",\n \"endorse or promote products derived from # this software without specific prior written\",\n \"__truediv__(self, other): return self._scalar(operator.truediv, other) def __rtruediv__(self, other): return self._scalar(operator.truediv, other, True) def\",\n \"def __rlshift__(self, other): return self._scalar(operator.lshift, other, True) def __rshift__(self, other): return self._scalar(operator.rshift, other)\",\n \"ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import math import numbers import operator\",\n \"other): return self._scalar(operator.or_, other, True) def __xor__(self, other): return self._scalar(operator.xor, other) def __rxor__(self,\",\n \"# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF\",\n \"LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND\",\n \"normal is not None: a = self.unit b = other.unit out = out\",\n \"and/or other materials provided with the distribution. # # * Neither the name\",\n \"# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,\",\n \"Redistributions of source code must retain the above copyright notice, this # list\",\n \"= self + other return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and\",\n \"tolerance and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def isperpendicular(self, other, tolerance=1e-10):\",\n \"tolerance def isantiparallel(self, other, tolerance=1e-10): return self.cosdelta(other) - (-1) < tolerance def iscollinear(self,\",\n \"self._scalar(operator.mul, other, True) def __div__(self, other): return self._scalar(operator.div, other) def __rdiv__(self, other): return\",\n \"USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY\",\n \"/ self.mag @property def rho(self): return math.sqrt(self.rho2) @property def phi(self): return math.atan2(self.y, self.x)\",\n \"def __lshift__(self, other): return self._scalar(operator.lshift, other) def __rlshift__(self, other): return self._scalar(operator.lshift, other, True)\",\n \"return self._scalar(operator.floordiv, other) def __rfloordiv__(self, other): return self._scalar(operator.floordiv, other, True) def __mod__(self, other):\",\n \"tolerance and abs(tmp.z) < tolerance def __add__(self, other): return self._vector(operator.add, other) def __radd__(self,\",\n \"NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A\",\n \"import awkward.util class Common(object): @property def mag2(self): return self.dot(self) @property def mag(self): return\",\n \"WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF\",\n \"self.y*self.y return out def delta_phi(self, other): return (self.phi - other.phi + math.pi) %\",\n \"math.pi def isparallel(self, other, tolerance=1e-10): return 1 - self.cosdelta(other) < tolerance def isantiparallel(self,\",\n \"(self.phi - other.phi + math.pi) % (2*math.pi) - math.pi def isparallel(self, other, tolerance=1e-10):\",\n \"if m1 == 0 or m2 == 0: return 1.0 r = self.dot(other)\",\n \"return out def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y\",\n \"rights reserved. # # Redistribution and use in source and binary forms, with\",\n \"other.phi + math.pi) % (2*math.pi) - math.pi def isparallel(self, other, tolerance=1e-10): return 1\",\n \"conditions and the following disclaimer. # # * Redistributions in binary form must\",\n \"EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import math import numbers\",\n \"max(-1.0, min(1.0, r)) def angle(self, other, degrees=False): out = math.acos(self.cosdelta(other)) if degrees: out\",\n \"return awkward.util.numpy.sqrt(self.mag2) @property def rho2(self): out = self.x*self.x out = out + self.y*self.y\",\n \"self._scalar(operator.div, other, True) def __truediv__(self, other): return self._scalar(operator.truediv, other) def __rtruediv__(self, other): return\",\n \"1) def angle(self, other, normal=None, degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other)) if normal is not\",\n \"- other.phi + math.pi) % (2*math.pi) - math.pi def isparallel(self, other, tolerance=1e-10): return\",\n \"permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS\",\n \"class ArrayMethods(Common): @property def unit(self): return self / self.mag @property def rho(self): out\",\n \"the following conditions are met: # # * Redistributions of source code must\",\n \"copyright holder nor the names of its # contributors may be used to\",\n \"other, tolerance=1e-10): tmp = self + other tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y)\",\n \"other): return self._vector(operator.sub, other, True) def __mul__(self, other): return self._scalar(operator.mul, other) def __rmul__(self,\",\n \"if normal is not None: a = self.unit b = other.unit out =\",\n \"other) def __rmul__(self, other): return self._scalar(operator.mul, other, True) def __div__(self, other): return self._scalar(operator.div,\",\n \"OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE,\",\n \"self.mag2 m2 = other.mag2 if m1 == 0 or m2 == 0: return\",\n \"THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF\",\n \"that the following conditions are met: # # * Redistributions of source code\",\n \"natural ordering\\\") class ArrayMethods(Common): @property def unit(self): return self / self.mag @property def\",\n \"reproduce the above copyright notice, # this list of conditions and the following\",\n \"mask = awkward.util.numpy.logical_not(mask) out[mask] = 1 return awkward.util.numpy.clip(out, -1, 1) def angle(self, other,\",\n \"other): m1 = self.mag2 m2 = other.mag2 if m1 == 0 or m2\",\n \"def __rmul__(self, other): return self._scalar(operator.mul, other, True) def __div__(self, other): return self._scalar(operator.div, other)\",\n \"other): return self._vector(operator.sub, other) def __rsub__(self, other): return self._vector(operator.sub, other, True) def __mul__(self,\",\n \"@property def mag(self): return awkward.util.numpy.sqrt(self.mag2) @property def rho2(self): out = self.x*self.x out =\",\n \"def __lt__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") def __gt__(self, other):\",\n \"self._scalar(operator.or_, other, True) def __xor__(self, other): return self._scalar(operator.xor, other) def __rxor__(self, other): return\",\n \"out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out def isopposite(self, other, tolerance=1e-10): tmp = self\",\n \"vectors have no natural ordering\\\") def __gt__(self, other): raise TypeError(\\\"spatial vectors have no\",\n \"self._scalar(operator.divmod, other, True) def __pow__(self, other): if isinstance(other, (numbers.Number, awkward.util.numpy.number)): if other ==\",\n \"2018, DIANA-HEP # All rights reserved. # # Redistribution and use in source\",\n \"no natural ordering\\\") def __le__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\")\",\n \"return self._scalar(operator.div, other) def __rdiv__(self, other): return self._scalar(operator.div, other, True) def __truediv__(self, other):\",\n \"HOLDERS AND CONTRIBUTORS \\\"AS IS\\\" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,\",\n \"the documentation # and/or other materials provided with the distribution. # # *\",\n \"GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)\",\n \"out[mask] = 1 return awkward.util.numpy.clip(out, -1, 1) def angle(self, other, normal=None, degrees=False): out\",\n \"def __rshift__(self, other): return self._scalar(operator.rshift, other) def __rrshift__(self, other): return self._scalar(operator.rshift, other, True)\",\n \"TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\",\n \"-1, 1) def angle(self, other, normal=None, degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other)) if normal is\",\n \"def __rtruediv__(self, other): return self._scalar(operator.truediv, other, True) def __floordiv__(self, other): return self._scalar(operator.floordiv, other)\",\n \"ordering\\\") def __le__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") def __ge__(self,\",\n \"tolerance) return out class Methods(Common): @property def unit(self): return self / self.mag @property\",\n \"def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) return abs(tmp.x) < tolerance and abs(tmp.y)\",\n \"awkward.util.numpy.logical_not(mask) out[mask] = 1 return awkward.util.numpy.clip(out, -1, 1) def angle(self, other, normal=None, degrees=False):\",\n \"(2*math.pi) - math.pi def isparallel(self, other, tolerance=1e-10): return 1 - self.cosdelta(other) < tolerance\",\n \"normal=None, degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other)) if normal is not None: a = self.unit\",\n \"other) def __rlshift__(self, other): return self._scalar(operator.lshift, other, True) def __rshift__(self, other): return self._scalar(operator.rshift,\",\n \"tolerance=1e-10): tmp = self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z)\",\n \"other tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out = (tmp.x\",\n \"IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \\\"AS IS\\\" # AND ANY\",\n \"__rmul__(self, other): return self._scalar(operator.mul, other, True) def __div__(self, other): return self._scalar(operator.div, other) def\",\n \"self._scalar(operator.and_, other) def __rand__(self, other): return self._scalar(operator.and_, other, True) def __or__(self, other): return\",\n \"+ math.pi) % (2*math.pi) - math.pi def isparallel(self, other, tolerance=1e-10): return 1 -\",\n \"def unit(self): return self / self.mag @property def rho(self): out = self.rho2 return\",\n \"or without # modification, are permitted provided that the following conditions are met:\",\n \"CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY\",\n \"and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def __add__(self, other): return self._vector(operator.add,\",\n \"without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE\",\n \"awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out = (tmp.x < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.y\",\n \"phi(self): return math.atan2(self.y, self.x) def cosdelta(self, other): m1 = self.mag2 m2 = other.mag2\",\n \"other, True) def __sub__(self, other): return self._vector(operator.sub, other) def __rsub__(self, other): return self._vector(operator.sub,\",\n \"= (tmp.x < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out,\",\n \"2: return self.mag2 else: return self.mag2**(0.5*other) else: self._scalar(operator.pow, other) # no __rpow__ def\",\n \"THE POSSIBILITY OF SUCH DAMAGE. import math import numbers import operator import awkward\",\n \"- self.cosdelta(other) < tolerance def isantiparallel(self, other, tolerance=1e-10): return self.cosdelta(other) - (-1) <\",\n \"def __radd__(self, other): return self._vector(operator.add, other, True) def __sub__(self, other): return self._vector(operator.sub, other)\",\n \"(numbers.Number, awkward.util.numpy.number)): if other == 2: return self.mag2 else: return self.mag2**(0.5*other) else: self._scalar(operator.pow,\",\n \"* m2) return max(-1.0, min(1.0, r)) def angle(self, other, degrees=False): out = math.acos(self.cosdelta(other))\",\n \"copyright notice, # this list of conditions and the following disclaimer in the\",\n \"awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out class Methods(Common): @property def unit(self): return self\",\n \"or m2 == 0: return 1.0 r = self.dot(other) / math.sqrt(m1 * m2)\",\n \"BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL #\",\n \"THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL,\",\n \"python # Copyright (c) 2018, DIANA-HEP # All rights reserved. # # Redistribution\",\n \"self._scalar(operator.and_, other, True) def __or__(self, other): return self._scalar(operator.or_, other) def __ror__(self, other): return\",\n \"__mul__(self, other): return self._scalar(operator.mul, other) def __rmul__(self, other): return self._scalar(operator.mul, other, True) def\",\n \"other) def __rdiv__(self, other): return self._scalar(operator.div, other, True) def __truediv__(self, other): return self._scalar(operator.truediv,\",\n \"TypeError(\\\"spatial vectors have no natural ordering\\\") def __le__(self, other): raise TypeError(\\\"spatial vectors have\",\n \"def phi(self): return math.atan2(self.y, self.x) def cosdelta(self, other): m1 = self.mag2 m2 =\",\n \"isopposite(self, other, tolerance=1e-10): tmp = self + other return abs(tmp.x) < tolerance and\",\n \"notice, this # list of conditions and the following disclaimer. # # *\",\n \"def mag2(self): return self.dot(self) @property def mag(self): return awkward.util.numpy.sqrt(self.mag2) @property def rho2(self): out\",\n \"INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,\",\n \"abs(tmp.z) < tolerance def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) return abs(tmp.x) <\",\n \"documentation # and/or other materials provided with the distribution. # # * Neither\",\n \"(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS\",\n \"import awkward import awkward.util class Common(object): @property def mag2(self): return self.dot(self) @property def\",\n \"other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") def __ge__(self, other): raise TypeError(\\\"spatial\",\n \"> 0) denom = denom[mask] denom[:] = awkward.util.numpy.sqrt(denom) out = self.dot(other) out[mask] /=\",\n \"this list of conditions and the following disclaimer in the documentation # and/or\",\n \"of conditions and the following disclaimer in the documentation # and/or other materials\",\n \"awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other)\",\n \"are permitted provided that the following conditions are met: # # * Redistributions\",\n \"True) def __neg__(self): return self._unary(operator.neg) def __pos__(self): return self._unary(operator.pos) def __abs__(self): return self.mag\",\n \"= awkward.util.numpy.arccos(self.cosdelta(other)) if normal is not None: a = self.unit b = other.unit\",\n \"list of conditions and the following disclaimer. # # * Redistributions in binary\",\n \"other, tolerance=1e-10): tmp = self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z =\",\n \"list of conditions and the following disclaimer in the documentation # and/or other\",\n \"def mag(self): return awkward.util.numpy.sqrt(self.mag2) @property def rho2(self): out = self.x*self.x out = out\",\n \"awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out def\",\n \"SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF\",\n \"name of the copyright holder nor the names of its # contributors may\",\n \"NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF\",\n \"and use in source and binary forms, with or without # modification, are\",\n \"FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT\",\n \"< tolerance and abs(tmp.z) < tolerance def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other)\",\n \"the distribution. # # * Neither the name of the copyright holder nor\",\n \"# this list of conditions and the following disclaimer in the documentation #\",\n \"provided that the following conditions are met: # # * Redistributions of source\",\n \"DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED\",\n \"iscollinear(self, other, tolerance=1e-10): return 1 - awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def __lt__(self, other): raise\",\n \"tolerance=1e-10): tmp = self + other return abs(tmp.x) < tolerance and abs(tmp.y) <\",\n \"m1 == 0 or m2 == 0: return 1.0 r = self.dot(other) /\",\n \"awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out def isopposite(self, other, tolerance=1e-10): tmp = self + other\",\n \"@property def mag2(self): return self.dot(self) @property def mag(self): return awkward.util.numpy.sqrt(self.mag2) @property def rho2(self):\",\n \"other, True) def __pow__(self, other): if isinstance(other, (numbers.Number, awkward.util.numpy.number)): if other == 2:\",\n \"other): return self._scalar(operator.or_, other) def __ror__(self, other): return self._scalar(operator.or_, other, True) def __xor__(self,\",\n \"self.cosdelta(other) - (-1) < tolerance def iscollinear(self, other, tolerance=1e-10): return 1 - awkward.util.numpy.absolute(self.cosdelta(other))\",\n \"__ge__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") class ArrayMethods(Common): @property def\",\n \"DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE #\",\n \"Methods(Common): @property def unit(self): return self / self.mag @property def rho(self): return math.sqrt(self.rho2)\",\n \"SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import math import\",\n \"import math import numbers import operator import awkward import awkward.util class Common(object): @property\",\n \"__and__(self, other): return self._scalar(operator.and_, other) def __rand__(self, other): return self._scalar(operator.and_, other, True) def\",\n \"def isantiparallel(self, other, tolerance=1e-10): return self.cosdelta(other) - (-1) < tolerance def iscollinear(self, other,\",\n \"return self._vector(operator.add, other) def __radd__(self, other): return self._vector(operator.add, other, True) def __sub__(self, other):\",\n \"awkward.util.numpy.number)): if other == 2: return self.mag2 else: return self.mag2**(0.5*other) else: self._scalar(operator.pow, other)\",\n \"self + other return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and abs(tmp.z)\",\n \"# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE\",\n \"denom mask = awkward.util.numpy.logical_not(mask) out[mask] = 1 return awkward.util.numpy.clip(out, -1, 1) def angle(self,\",\n \"tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out def isperpendicular(self,\",\n \"@property def phi(self): return math.atan2(self.y, self.x) def cosdelta(self, other): m1 = self.mag2 m2\",\n \"of its # contributors may be used to endorse or promote products derived\",\n \"its # contributors may be used to endorse or promote products derived from\",\n \"return self._scalar(operator.floordiv, other, True) def __mod__(self, other): return self._scalar(operator.mod, other) def __rmod__(self, other):\",\n \"self._scalar(operator.lshift, other, True) def __rshift__(self, other): return self._scalar(operator.rshift, other) def __rrshift__(self, other): return\",\n \"not None: a = self.unit b = other.unit out = out * awkward.util.numpy.sign(normal.dot(a.cross(b)))\",\n \"__sub__(self, other): return self._vector(operator.sub, other) def __rsub__(self, other): return self._vector(operator.sub, other, True) def\",\n \"self._scalar(operator.divmod, other) def __rdivmod__(self, other): return self._scalar(operator.divmod, other, True) def __pow__(self, other): if\",\n \"True) def __sub__(self, other): return self._vector(operator.sub, other) def __rsub__(self, other): return self._vector(operator.sub, other,\",\n \"awkward.util.numpy.sqrt(out) @property def phi(self): return awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self, other): denom = self.mag2\",\n \"< tolerance def isantiparallel(self, other, tolerance=1e-10): return self.cosdelta(other) - (-1) < tolerance def\",\n \"def cosdelta(self, other): denom = self.mag2 * other.mag2 mask = (denom > 0)\",\n \"OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER\",\n \"WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING\",\n \"__div__(self, other): return self._scalar(operator.div, other) def __rdiv__(self, other): return self._scalar(operator.div, other, True) def\",\n \"OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE\",\n \"OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS\",\n \"IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR\",\n \"def __rdivmod__(self, other): return self._scalar(operator.divmod, other, True) def __pow__(self, other): if isinstance(other, (numbers.Number,\",\n \"self.unit b = other.unit out = out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out =\",\n \"out = self.dot(other) out[mask] /= denom mask = awkward.util.numpy.logical_not(mask) out[mask] = 1 return\",\n \"other): return self._scalar(operator.and_, other) def __rand__(self, other): return self._scalar(operator.and_, other, True) def __or__(self,\",\n \"out class Methods(Common): @property def unit(self): return self / self.mag @property def rho(self):\",\n \"__xor__(self, other): return self._scalar(operator.xor, other) def __rxor__(self, other): return self._scalar(operator.xor, other, True) def\",\n \"contributors may be used to endorse or promote products derived from # this\",\n \"< tolerance def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) return abs(tmp.x) < tolerance\",\n \"return self._scalar(operator.or_, other) def __ror__(self, other): return self._scalar(operator.or_, other, True) def __xor__(self, other):\",\n \"r = self.dot(other) / math.sqrt(m1 * m2) return max(-1.0, min(1.0, r)) def angle(self,\",\n \"NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY\",\n \"return self._scalar(operator.mod, other) def __rmod__(self, other): return self._scalar(operator.mod, other, True) def __divmod__(self, other):\",\n \"Redistribution and use in source and binary forms, with or without # modification,\",\n \"= other.mag2 if m1 == 0 or m2 == 0: return 1.0 r\",\n \"other): return self._scalar(operator.lshift, other) def __rlshift__(self, other): return self._scalar(operator.lshift, other, True) def __rshift__(self,\",\n \"source and binary forms, with or without # modification, are permitted provided that\",\n \"BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR\",\n \"out = (tmp.x < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out =\",\n \"class Common(object): @property def mag2(self): return self.dot(self) @property def mag(self): return awkward.util.numpy.sqrt(self.mag2) @property\",\n \"self / self.mag @property def rho(self): return math.sqrt(self.rho2) @property def phi(self): return math.atan2(self.y,\",\n \"the name of the copyright holder nor the names of its # contributors\",\n \"FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE\",\n \"return self._vector(operator.add, other, True) def __sub__(self, other): return self._vector(operator.sub, other) def __rsub__(self, other):\",\n \"angle(self, other, degrees=False): out = math.acos(self.cosdelta(other)) if degrees: out = out * 180.0/math.pi\",\n \"= self.mag2 * other.mag2 mask = (denom > 0) denom = denom[mask] denom[:]\",\n \"math.pi) % (2*math.pi) - math.pi def isparallel(self, other, tolerance=1e-10): return 1 - self.cosdelta(other)\",\n \"of conditions and the following disclaimer. # # * Redistributions in binary form\",\n \"= awkward.util.numpy.sqrt(denom) out = self.dot(other) out[mask] /= denom mask = awkward.util.numpy.logical_not(mask) out[mask] =\",\n \"CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, #\",\n \"other): return self._vector(operator.add, other) def __radd__(self, other): return self._vector(operator.add, other, True) def __sub__(self,\",\n \"self._scalar(operator.mod, other) def __rmod__(self, other): return self._scalar(operator.mod, other, True) def __divmod__(self, other): return\",\n \"math.sqrt(self.rho2) @property def phi(self): return math.atan2(self.y, self.x) def cosdelta(self, other): m1 = self.mag2\",\n \"tmp = self + other return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance\",\n \"above copyright notice, this # list of conditions and the following disclaimer. #\",\n \"out = out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out\",\n \"the following disclaimer. # # * Redistributions in binary form must reproduce the\",\n \"derived from # this software without specific prior written permission. # # THIS\",\n \"self._scalar(operator.xor, other, True) def __neg__(self): return self._unary(operator.neg) def __pos__(self): return self._unary(operator.pos) def __abs__(self):\",\n \"HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT\",\n \"min(1.0, r)) def angle(self, other, degrees=False): out = math.acos(self.cosdelta(other)) if degrees: out =\",\n \"* other.mag2 mask = (denom > 0) denom = denom[mask] denom[:] = awkward.util.numpy.sqrt(denom)\",\n \"= awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out def isopposite(self, other, tolerance=1e-10): tmp = self +\",\n \"== 0 or m2 == 0: return 1.0 r = self.dot(other) / math.sqrt(m1\",\n \"/ math.sqrt(m1 * m2) return max(-1.0, min(1.0, r)) def angle(self, other, degrees=False): out\",\n \"self + other tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out\",\n \"is not None: a = self.unit b = other.unit out = out *\",\n \"< tolerance and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def __add__(self, other):\",\n \"tolerance def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) return abs(tmp.x) < tolerance and\",\n \"return out def isopposite(self, other, tolerance=1e-10): tmp = self + other tmp.x =\",\n \"ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING\",\n \"return self._vector(operator.sub, other, True) def __mul__(self, other): return self._scalar(operator.mul, other) def __rmul__(self, other):\",\n \"rho(self): return math.sqrt(self.rho2) @property def phi(self): return math.atan2(self.y, self.x) def cosdelta(self, other): m1\",\n \"# # * Neither the name of the copyright holder nor the names\",\n \"__rand__(self, other): return self._scalar(operator.and_, other, True) def __or__(self, other): return self._scalar(operator.or_, other) def\",\n \"rho(self): out = self.rho2 return awkward.util.numpy.sqrt(out) @property def phi(self): return awkward.util.numpy.arctan2(self.y, self.x) def\",\n \"isantiparallel(self, other, tolerance=1e-10): return self.cosdelta(other) - (-1) < tolerance def iscollinear(self, other, tolerance=1e-10):\",\n \"other): return (self.phi - other.phi + math.pi) % (2*math.pi) - math.pi def isparallel(self,\",\n \"# contributors may be used to endorse or promote products derived from #\",\n \"@property def rho(self): out = self.rho2 return awkward.util.numpy.sqrt(out) @property def phi(self): return awkward.util.numpy.arctan2(self.y,\",\n \"permitted provided that the following conditions are met: # # * Redistributions of\",\n \"self.mag @property def rho(self): return math.sqrt(self.rho2) @property def phi(self): return math.atan2(self.y, self.x) def\",\n \"isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) return abs(tmp.x) < tolerance and abs(tmp.y) <\",\n \"/= denom mask = awkward.util.numpy.logical_not(mask) out[mask] = 1 return awkward.util.numpy.clip(out, -1, 1) def\",\n \"0 or m2 == 0: return 1.0 r = self.dot(other) / math.sqrt(m1 *\",\n \"other, tolerance=1e-10): tmp = self.dot(other) return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance\",\n \"__rmod__(self, other): return self._scalar(operator.mod, other, True) def __divmod__(self, other): return self._scalar(operator.divmod, other) def\",\n \"m2 == 0: return 1.0 r = self.dot(other) / math.sqrt(m1 * m2) return\",\n \"HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY,\",\n \"other materials provided with the distribution. # # * Neither the name of\",\n \"__or__(self, other): return self._scalar(operator.or_, other) def __ror__(self, other): return self._scalar(operator.or_, other, True) def\",\n \"math.acos(self.cosdelta(other)) if degrees: out = out * 180.0/math.pi return out def isopposite(self, other,\",\n \"COPYRIGHT HOLDERS AND CONTRIBUTORS \\\"AS IS\\\" # AND ANY EXPRESS OR IMPLIED WARRANTIES,\",\n \"* 180.0/math.pi return out def isopposite(self, other, tolerance=1e-10): tmp = self + other\",\n \"tolerance and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def __add__(self, other): return\",\n \"degrees: out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out def isopposite(self, other, tolerance=1e-10): tmp =\",\n \"return self._unary(operator.neg) def __pos__(self): return self._unary(operator.pos) def __abs__(self): return self.mag def __invert__(self): return\",\n \"= self + other tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z)\",\n \"__rsub__(self, other): return self._vector(operator.sub, other, True) def __mul__(self, other): return self._scalar(operator.mul, other) def\",\n \"awkward.util class Common(object): @property def mag2(self): return self.dot(self) @property def mag(self): return awkward.util.numpy.sqrt(self.mag2)\",\n \"self.dot(self) @property def mag(self): return awkward.util.numpy.sqrt(self.mag2) @property def rho2(self): out = self.x*self.x out\",\n \"tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out def isperpendicular(self, other, tolerance=1e-10):\",\n \"and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def isperpendicular(self, other, tolerance=1e-10): tmp\",\n \"def __and__(self, other): return self._scalar(operator.and_, other) def __rand__(self, other): return self._scalar(operator.and_, other, True)\",\n \"tmp = self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out\",\n \"self.dot(other) out[mask] /= denom mask = awkward.util.numpy.logical_not(mask) out[mask] = 1 return awkward.util.numpy.clip(out, -1,\",\n \"other): return self._scalar(operator.xor, other, True) def __neg__(self): return self._unary(operator.neg) def __pos__(self): return self._unary(operator.pos)\",\n \"def isparallel(self, other, tolerance=1e-10): return 1 - self.cosdelta(other) < tolerance def isantiparallel(self, other,\",\n \"OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO\",\n \"= out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out def\",\n \"tolerance def __lt__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") def __gt__(self,\",\n \"def __add__(self, other): return self._vector(operator.add, other) def __radd__(self, other): return self._vector(operator.add, other, True)\",\n \"self._scalar(operator.truediv, other, True) def __floordiv__(self, other): return self._scalar(operator.floordiv, other) def __rfloordiv__(self, other): return\",\n \"forms, with or without # modification, are permitted provided that the following conditions\",\n \"ordering\\\") def __gt__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") def __le__(self,\",\n \"Copyright (c) 2018, DIANA-HEP # All rights reserved. # # Redistribution and use\",\n \"# # * Redistributions of source code must retain the above copyright notice,\",\n \"with the distribution. # # * Neither the name of the copyright holder\",\n \"above copyright notice, # this list of conditions and the following disclaimer in\",\n \"= other.unit out = out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi)\",\n \"def unit(self): return self / self.mag @property def rho(self): return math.sqrt(self.rho2) @property def\",\n \"tolerance=1e-10): tmp = self.dot(other) return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and\",\n \"other, True) def __or__(self, other): return self._scalar(operator.or_, other) def __ror__(self, other): return self._scalar(operator.or_,\",\n \"= awkward.util.numpy.absolute(tmp.z) out = (tmp.x < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.y < tolerance)\",\n \"return self._scalar(operator.div, other, True) def __truediv__(self, other): return self._scalar(operator.truediv, other) def __rtruediv__(self, other):\",\n \"other): return self._scalar(operator.rshift, other) def __rrshift__(self, other): return self._scalar(operator.rshift, other, True) def __and__(self,\",\n \"other): return self._scalar(operator.xor, other) def __rxor__(self, other): return self._scalar(operator.xor, other, True) def __neg__(self):\",\n \"in source and binary forms, with or without # modification, are permitted provided\",\n \"tolerance def iscollinear(self, other, tolerance=1e-10): return 1 - awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def __lt__(self,\",\n \"other, True) def __mod__(self, other): return self._scalar(operator.mod, other) def __rmod__(self, other): return self._scalar(operator.mod,\",\n \"other): return self._scalar(operator.floordiv, other, True) def __mod__(self, other): return self._scalar(operator.mod, other) def __rmod__(self,\",\n \"IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF\",\n \"@property def unit(self): return self / self.mag @property def rho(self): out = self.rho2\",\n \"the following disclaimer in the documentation # and/or other materials provided with the\",\n \"PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY,\",\n \"delta_phi(self, other): return (self.phi - other.phi + math.pi) % (2*math.pi) - math.pi def\",\n \"cosdelta(self, other): m1 = self.mag2 m2 = other.mag2 if m1 == 0 or\",\n \"# # Redistribution and use in source and binary forms, with or without\",\n \"tolerance and abs(tmp.z) < tolerance def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) return\",\n \"return self._scalar(operator.mul, other, True) def __div__(self, other): return self._scalar(operator.div, other) def __rdiv__(self, other):\",\n \"out[mask] /= denom mask = awkward.util.numpy.logical_not(mask) out[mask] = 1 return awkward.util.numpy.clip(out, -1, 1)\",\n \"ordering\\\") def __ge__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") class ArrayMethods(Common):\",\n \"tmp = self.dot(other) return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and abs(tmp.z)\",\n \"__neg__(self): return self._unary(operator.neg) def __pos__(self): return self._unary(operator.pos) def __abs__(self): return self.mag def __invert__(self):\",\n \"other) def __rsub__(self, other): return self._vector(operator.sub, other, True) def __mul__(self, other): return self._scalar(operator.mul,\",\n \"= awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out\",\n \"__rlshift__(self, other): return self._scalar(operator.lshift, other, True) def __rshift__(self, other): return self._scalar(operator.rshift, other) def\",\n \"the above copyright notice, this # list of conditions and the following disclaimer.\",\n \"TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\",\n \"used to endorse or promote products derived from # this software without specific\",\n \"< tolerance and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def isperpendicular(self, other,\",\n \"self.dot(other) return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance\",\n \"awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out = (tmp.x < tolerance) out\",\n \"__rxor__(self, other): return self._scalar(operator.xor, other, True) def __neg__(self): return self._unary(operator.neg) def __pos__(self): return\",\n \"other) # no __rpow__ def __lshift__(self, other): return self._scalar(operator.lshift, other) def __rlshift__(self, other):\",\n \"(-1) < tolerance def iscollinear(self, other, tolerance=1e-10): return 1 - awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance\",\n \"math import numbers import operator import awkward import awkward.util class Common(object): @property def\",\n \"= awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out = (tmp.x < tolerance)\",\n \"< tolerance def __lt__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") def\",\n \"awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out def isopposite(self, other, tolerance=1e-10):\",\n \"< tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out class Methods(Common): @property\",\n \"have no natural ordering\\\") def __ge__(self, other): raise TypeError(\\\"spatial vectors have no natural\",\n \"promote products derived from # this software without specific prior written permission. #\",\n \"other): return self._scalar(operator.mul, other, True) def __div__(self, other): return self._scalar(operator.div, other) def __rdiv__(self,\",\n \"prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS\",\n \"return awkward.util.numpy.clip(out, -1, 1) def angle(self, other, normal=None, degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other)) if\",\n \"self._scalar(operator.mod, other, True) def __divmod__(self, other): return self._scalar(operator.divmod, other) def __rdivmod__(self, other): return\",\n \"tmp.z < tolerance) return out def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) tmp.x\",\n \"class Methods(Common): @property def unit(self): return self / self.mag @property def rho(self): return\",\n \"abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def isperpendicular(self,\",\n \"return 1 - self.cosdelta(other) < tolerance def isantiparallel(self, other, tolerance=1e-10): return self.cosdelta(other) -\",\n \"@property def phi(self): return awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self, other): denom = self.mag2 *\",\n \"(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE #\",\n \"self._vector(operator.add, other, True) def __sub__(self, other): return self._vector(operator.sub, other) def __rsub__(self, other): return\",\n \"True) def __mod__(self, other): return self._scalar(operator.mod, other) def __rmod__(self, other): return self._scalar(operator.mod, other,\",\n \"1 - awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def __lt__(self, other): raise TypeError(\\\"spatial vectors have no\",\n \"True) def __div__(self, other): return self._scalar(operator.div, other) def __rdiv__(self, other): return self._scalar(operator.div, other,\",\n \"== 2: return self.mag2 else: return self.mag2**(0.5*other) else: self._scalar(operator.pow, other) # no __rpow__\",\n \"self._scalar(operator.rshift, other) def __rrshift__(self, other): return self._scalar(operator.rshift, other, True) def __and__(self, other): return\",\n \"<gh_stars>0 #!/usr/bin/env python # Copyright (c) 2018, DIANA-HEP # All rights reserved. #\",\n \"@property def unit(self): return self / self.mag @property def rho(self): return math.sqrt(self.rho2) @property\",\n \"denom[mask] denom[:] = awkward.util.numpy.sqrt(denom) out = self.dot(other) out[mask] /= denom mask = awkward.util.numpy.logical_not(mask)\",\n \"other, True) def __mul__(self, other): return self._scalar(operator.mul, other) def __rmul__(self, other): return self._scalar(operator.mul,\",\n \"cosdelta(self, other): denom = self.mag2 * other.mag2 mask = (denom > 0) denom\",\n \"self.mag2 else: return self.mag2**(0.5*other) else: self._scalar(operator.pow, other) # no __rpow__ def __lshift__(self, other):\",\n \"True) def __xor__(self, other): return self._scalar(operator.xor, other) def __rxor__(self, other): return self._scalar(operator.xor, other,\",\n \"if isinstance(other, (numbers.Number, awkward.util.numpy.number)): if other == 2: return self.mag2 else: return self.mag2**(0.5*other)\",\n \"180.0/math.pi return out def isopposite(self, other, tolerance=1e-10): tmp = self + other return\",\n \"= self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out =\",\n \"rho2(self): out = self.x*self.x out = out + self.y*self.y return out def delta_phi(self,\",\n \"m2) return max(-1.0, min(1.0, r)) def angle(self, other, degrees=False): out = math.acos(self.cosdelta(other)) if\",\n \"= self.mag2 m2 = other.mag2 if m1 == 0 or m2 == 0:\",\n \"use in source and binary forms, with or without # modification, are permitted\",\n \"tmp = self + other tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z =\",\n \"IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED.\",\n \"self.x*self.x out = out + self.y*self.y return out def delta_phi(self, other): return (self.phi\",\n \"THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \\\"AS IS\\\" #\",\n \"unit(self): return self / self.mag @property def rho(self): out = self.rho2 return awkward.util.numpy.sqrt(out)\",\n \"= self.dot(other) return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and abs(tmp.z) <\",\n \"operator import awkward import awkward.util class Common(object): @property def mag2(self): return self.dot(self) @property\",\n \"OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR\",\n \"True) def __or__(self, other): return self._scalar(operator.or_, other) def __ror__(self, other): return self._scalar(operator.or_, other,\",\n \"must reproduce the above copyright notice, # this list of conditions and the\",\n \"other, tolerance=1e-10): return self.cosdelta(other) - (-1) < tolerance def iscollinear(self, other, tolerance=1e-10): return\",\n \"return self._scalar(operator.xor, other) def __rxor__(self, other): return self._scalar(operator.xor, other, True) def __neg__(self): return\",\n \"this # list of conditions and the following disclaimer. # # * Redistributions\",\n \"# All rights reserved. # # Redistribution and use in source and binary\",\n \"* awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out def isopposite(self, other,\",\n \"following conditions are met: # # * Redistributions of source code must retain\",\n \"self._scalar(operator.mul, other) def __rmul__(self, other): return self._scalar(operator.mul, other, True) def __div__(self, other): return\",\n \"# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE #\",\n \"def isopposite(self, other, tolerance=1e-10): tmp = self + other tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y\",\n \"other): return self._scalar(operator.mul, other) def __rmul__(self, other): return self._scalar(operator.mul, other, True) def __div__(self,\",\n \"disclaimer in the documentation # and/or other materials provided with the distribution. #\",\n \"return math.sqrt(self.rho2) @property def phi(self): return math.atan2(self.y, self.x) def cosdelta(self, other): m1 =\",\n \"to endorse or promote products derived from # this software without specific prior\",\n \"if degrees: out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out def isopposite(self, other, tolerance=1e-10): tmp\",\n \"True) def __and__(self, other): return self._scalar(operator.and_, other) def __rand__(self, other): return self._scalar(operator.and_, other,\",\n \"OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER\",\n \"Common(object): @property def mag2(self): return self.dot(self) @property def mag(self): return awkward.util.numpy.sqrt(self.mag2) @property def\",\n \"return self._scalar(operator.mod, other, True) def __divmod__(self, other): return self._scalar(operator.divmod, other) def __rdivmod__(self, other):\",\n \"return self._scalar(operator.divmod, other, True) def __pow__(self, other): if isinstance(other, (numbers.Number, awkward.util.numpy.number)): if other\",\n \"- (-1) < tolerance def iscollinear(self, other, tolerance=1e-10): return 1 - awkward.util.numpy.absolute(self.cosdelta(other)) <\",\n \"INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO,\",\n \"__mod__(self, other): return self._scalar(operator.mod, other) def __rmod__(self, other): return self._scalar(operator.mod, other, True) def\",\n \"abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def __add__(self, other): return self._vector(operator.add, other)\",\n \"tolerance def __add__(self, other): return self._vector(operator.add, other) def __radd__(self, other): return self._vector(operator.add, other,\",\n \"tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out class Methods(Common):\",\n \"EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT,\",\n \"self / self.mag @property def rho(self): out = self.rho2 return awkward.util.numpy.sqrt(out) @property def\",\n \"a = self.unit b = other.unit out = out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees:\",\n \"and abs(tmp.z) < tolerance def __add__(self, other): return self._vector(operator.add, other) def __radd__(self, other):\",\n \"def rho(self): return math.sqrt(self.rho2) @property def phi(self): return math.atan2(self.y, self.x) def cosdelta(self, other):\",\n \"isinstance(other, (numbers.Number, awkward.util.numpy.number)): if other == 2: return self.mag2 else: return self.mag2**(0.5*other) else:\",\n \"def __rdiv__(self, other): return self._scalar(operator.div, other, True) def __truediv__(self, other): return self._scalar(operator.truediv, other)\",\n \"LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)\",\n \"distribution. # # * Neither the name of the copyright holder nor the\",\n \"THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import math\",\n \"in the documentation # and/or other materials provided with the distribution. # #\",\n \"TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR\",\n \"denom = denom[mask] denom[:] = awkward.util.numpy.sqrt(denom) out = self.dot(other) out[mask] /= denom mask\",\n \"+ other tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out =\",\n \"AND CONTRIBUTORS \\\"AS IS\\\" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT\",\n \"# and/or other materials provided with the distribution. # # * Neither the\",\n \"other, normal=None, degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other)) if normal is not None: a =\",\n \"products derived from # this software without specific prior written permission. # #\",\n \"SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS\",\n \"# Copyright (c) 2018, DIANA-HEP # All rights reserved. # # Redistribution and\",\n \"other): if isinstance(other, (numbers.Number, awkward.util.numpy.number)): if other == 2: return self.mag2 else: return\",\n \"the above copyright notice, # this list of conditions and the following disclaimer\",\n \"def __div__(self, other): return self._scalar(operator.div, other) def __rdiv__(self, other): return self._scalar(operator.div, other, True)\",\n \"else: return self.mag2**(0.5*other) else: self._scalar(operator.pow, other) # no __rpow__ def __lshift__(self, other): return\",\n \"(denom > 0) denom = denom[mask] denom[:] = awkward.util.numpy.sqrt(denom) out = self.dot(other) out[mask]\",\n \"= awkward.util.numpy.logical_not(mask) out[mask] = 1 return awkward.util.numpy.clip(out, -1, 1) def angle(self, other, normal=None,\",\n \"from # this software without specific prior written permission. # # THIS SOFTWARE\",\n \"def __mul__(self, other): return self._scalar(operator.mul, other) def __rmul__(self, other): return self._scalar(operator.mul, other, True)\",\n \"= (denom > 0) denom = denom[mask] denom[:] = awkward.util.numpy.sqrt(denom) out = self.dot(other)\",\n \"return self._scalar(operator.mul, other) def __rmul__(self, other): return self._scalar(operator.mul, other, True) def __div__(self, other):\",\n \"out def isopposite(self, other, tolerance=1e-10): tmp = self + other return abs(tmp.x) <\",\n \"__rpow__ def __lshift__(self, other): return self._scalar(operator.lshift, other) def __rlshift__(self, other): return self._scalar(operator.lshift, other,\",\n \"raise TypeError(\\\"spatial vectors have no natural ordering\\\") class ArrayMethods(Common): @property def unit(self): return\",\n \"other) def __ror__(self, other): return self._scalar(operator.or_, other, True) def __xor__(self, other): return self._scalar(operator.xor,\",\n \"other) def __rxor__(self, other): return self._scalar(operator.xor, other, True) def __neg__(self): return self._unary(operator.neg) def\",\n \"be used to endorse or promote products derived from # this software without\",\n \"OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF\",\n \"self._scalar(operator.or_, other) def __ror__(self, other): return self._scalar(operator.or_, other, True) def __xor__(self, other): return\",\n \"IS\\\" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,\",\n \"* Neither the name of the copyright holder nor the names of its\",\n \"return self._scalar(operator.xor, other, True) def __neg__(self): return self._unary(operator.neg) def __pos__(self): return self._unary(operator.pos) def\",\n \"OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON\",\n \"self._scalar(operator.floordiv, other, True) def __mod__(self, other): return self._scalar(operator.mod, other) def __rmod__(self, other): return\",\n \"IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY\",\n \"other): return self._scalar(operator.floordiv, other) def __rfloordiv__(self, other): return self._scalar(operator.floordiv, other, True) def __mod__(self,\",\n \"@property def rho2(self): out = self.x*self.x out = out + self.y*self.y return out\",\n \"1.0 r = self.dot(other) / math.sqrt(m1 * m2) return max(-1.0, min(1.0, r)) def\",\n \"BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN\",\n \"FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT\",\n \"other): return self._scalar(operator.div, other, True) def __truediv__(self, other): return self._scalar(operator.truediv, other) def __rtruediv__(self,\",\n \"return self._scalar(operator.rshift, other, True) def __and__(self, other): return self._scalar(operator.and_, other) def __rand__(self, other):\",\n \"USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH\",\n \"def isopposite(self, other, tolerance=1e-10): tmp = self + other return abs(tmp.x) < tolerance\",\n \"out = self.rho2 return awkward.util.numpy.sqrt(out) @property def phi(self): return awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self,\",\n \"materials provided with the distribution. # # * Neither the name of the\",\n \"tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance)\",\n \"m2 = other.mag2 if m1 == 0 or m2 == 0: return 1.0\",\n \"EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE\",\n \"natural ordering\\\") def __ge__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") class\",\n \"PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR\",\n \"self.dot(other) / math.sqrt(m1 * m2) return max(-1.0, min(1.0, r)) def angle(self, other, degrees=False):\",\n \"__rfloordiv__(self, other): return self._scalar(operator.floordiv, other, True) def __mod__(self, other): return self._scalar(operator.mod, other) def\",\n \"mag(self): return awkward.util.numpy.sqrt(self.mag2) @property def rho2(self): out = self.x*self.x out = out +\",\n \"0) denom = denom[mask] denom[:] = awkward.util.numpy.sqrt(denom) out = self.dot(other) out[mask] /= denom\",\n \"IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN\",\n \"and binary forms, with or without # modification, are permitted provided that the\",\n \"conditions and the following disclaimer in the documentation # and/or other materials provided\",\n \"SUCH DAMAGE. import math import numbers import operator import awkward import awkward.util class\",\n \"raise TypeError(\\\"spatial vectors have no natural ordering\\\") def __ge__(self, other): raise TypeError(\\\"spatial vectors\",\n \"degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other)) if normal is not None: a = self.unit b\",\n \"self.x) def cosdelta(self, other): m1 = self.mag2 m2 = other.mag2 if m1 ==\",\n \"names of its # contributors may be used to endorse or promote products\",\n \"copyright notice, this # list of conditions and the following disclaimer. # #\",\n \"SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \\\"AS IS\\\" # AND\",\n \"other, True) def __neg__(self): return self._unary(operator.neg) def __pos__(self): return self._unary(operator.pos) def __abs__(self): return\",\n \"self._scalar(operator.xor, other) def __rxor__(self, other): return self._scalar(operator.xor, other, True) def __neg__(self): return self._unary(operator.neg)\",\n \"other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") def __gt__(self, other): raise TypeError(\\\"spatial\",\n \"have no natural ordering\\\") def __le__(self, other): raise TypeError(\\\"spatial vectors have no natural\",\n \"return max(-1.0, min(1.0, r)) def angle(self, other, degrees=False): out = math.acos(self.cosdelta(other)) if degrees:\",\n \"return self._scalar(operator.truediv, other, True) def __floordiv__(self, other): return self._scalar(operator.floordiv, other) def __rfloordiv__(self, other):\",\n \"disclaimer. # # * Redistributions in binary form must reproduce the above copyright\",\n \"ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED\",\n \"other): return self._vector(operator.add, other, True) def __sub__(self, other): return self._vector(operator.sub, other) def __rsub__(self,\",\n \"out def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y =\",\n \"out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return out def isopposite(self,\",\n \"other): return self._scalar(operator.mod, other) def __rmod__(self, other): return self._scalar(operator.mod, other, True) def __divmod__(self,\",\n \"= awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out = (tmp.x < tolerance) out = awkward.util.numpy.bitwise_and(out,\",\n \"= denom[mask] denom[:] = awkward.util.numpy.sqrt(denom) out = self.dot(other) out[mask] /= denom mask =\",\n \"awkward.util.numpy.clip(out, -1, 1) def angle(self, other, normal=None, degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other)) if normal\",\n \"return self._scalar(operator.or_, other, True) def __xor__(self, other): return self._scalar(operator.xor, other) def __rxor__(self, other):\",\n \"WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND\",\n \"other, tolerance=1e-10): return 1 - awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def __lt__(self, other): raise TypeError(\\\"spatial\",\n \"return self / self.mag @property def rho(self): out = self.rho2 return awkward.util.numpy.sqrt(out) @property\",\n \"provided with the distribution. # # * Neither the name of the copyright\",\n \"out = out * 180.0/math.pi return out def isopposite(self, other, tolerance=1e-10): tmp =\",\n \"def iscollinear(self, other, tolerance=1e-10): return 1 - awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def __lt__(self, other):\",\n \"(c) 2018, DIANA-HEP # All rights reserved. # # Redistribution and use in\",\n \"A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER\",\n \"self.mag2 * other.mag2 mask = (denom > 0) denom = denom[mask] denom[:] =\",\n \"self._scalar(operator.lshift, other) def __rlshift__(self, other): return self._scalar(operator.lshift, other, True) def __rshift__(self, other): return\",\n \"modification, are permitted provided that the following conditions are met: # # *\",\n \"def __rfloordiv__(self, other): return self._scalar(operator.floordiv, other, True) def __mod__(self, other): return self._scalar(operator.mod, other)\",\n \"= math.acos(self.cosdelta(other)) if degrees: out = out * 180.0/math.pi return out def isopposite(self,\",\n \"def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y)\",\n \"must retain the above copyright notice, this # list of conditions and the\",\n \"are met: # # * Redistributions of source code must retain the above\",\n \"True) def __mul__(self, other): return self._scalar(operator.mul, other) def __rmul__(self, other): return self._scalar(operator.mul, other,\",\n \"True) def __pow__(self, other): if isinstance(other, (numbers.Number, awkward.util.numpy.number)): if other == 2: return\",\n \"out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out def isperpendicular(self, other, tolerance=1e-10): tmp\",\n \"CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR\",\n \"self.cosdelta(other) < tolerance def isantiparallel(self, other, tolerance=1e-10): return self.cosdelta(other) - (-1) < tolerance\",\n \"self._scalar(operator.floordiv, other) def __rfloordiv__(self, other): return self._scalar(operator.floordiv, other, True) def __mod__(self, other): return\",\n \"return self / self.mag @property def rho(self): return math.sqrt(self.rho2) @property def phi(self): return\",\n \"degrees: out = out * 180.0/math.pi return out def isopposite(self, other, tolerance=1e-10): tmp\",\n \"def __le__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") def __ge__(self, other):\",\n \"other.mag2 if m1 == 0 or m2 == 0: return 1.0 r =\",\n \"return self._scalar(operator.truediv, other) def __rtruediv__(self, other): return self._scalar(operator.truediv, other, True) def __floordiv__(self, other):\",\n \"True) def __divmod__(self, other): return self._scalar(operator.divmod, other) def __rdivmod__(self, other): return self._scalar(operator.divmod, other,\",\n \"__pow__(self, other): if isinstance(other, (numbers.Number, awkward.util.numpy.number)): if other == 2: return self.mag2 else:\",\n \"OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS\",\n \"def cosdelta(self, other): m1 = self.mag2 m2 = other.mag2 if m1 == 0\",\n \"< tolerance def iscollinear(self, other, tolerance=1e-10): return 1 - awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def\",\n \"other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") class ArrayMethods(Common): @property def unit(self):\",\n \"return self.cosdelta(other) - (-1) < tolerance def iscollinear(self, other, tolerance=1e-10): return 1 -\",\n \"(tmp.x < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z\",\n \"self.mag @property def rho(self): out = self.rho2 return awkward.util.numpy.sqrt(out) @property def phi(self): return\",\n \"__lt__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") def __gt__(self, other): raise\",\n \"ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED\",\n \"__radd__(self, other): return self._vector(operator.add, other, True) def __sub__(self, other): return self._vector(operator.sub, other) def\",\n \"the copyright holder nor the names of its # contributors may be used\",\n \"ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN\",\n \"tolerance=1e-10): return 1 - awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def __lt__(self, other): raise TypeError(\\\"spatial vectors\",\n \"tmp.z < tolerance) return out class Methods(Common): @property def unit(self): return self /\",\n \"out + self.y*self.y return out def delta_phi(self, other): return (self.phi - other.phi +\",\n \"other): denom = self.mag2 * other.mag2 mask = (denom > 0) denom =\",\n \"@property def rho(self): return math.sqrt(self.rho2) @property def phi(self): return math.atan2(self.y, self.x) def cosdelta(self,\",\n \"mag2(self): return self.dot(self) @property def mag(self): return awkward.util.numpy.sqrt(self.mag2) @property def rho2(self): out =\",\n \"def __rrshift__(self, other): return self._scalar(operator.rshift, other, True) def __and__(self, other): return self._scalar(operator.and_, other)\",\n \"raise TypeError(\\\"spatial vectors have no natural ordering\\\") def __le__(self, other): raise TypeError(\\\"spatial vectors\",\n \"def __sub__(self, other): return self._vector(operator.sub, other) def __rsub__(self, other): return self._vector(operator.sub, other, True)\",\n \"PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS;\",\n \"tolerance) return out def isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x)\",\n \"COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\",\n \"return self.mag2**(0.5*other) else: self._scalar(operator.pow, other) # no __rpow__ def __lshift__(self, other): return self._scalar(operator.lshift,\",\n \"SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT,\",\n \"def __xor__(self, other): return self._scalar(operator.xor, other) def __rxor__(self, other): return self._scalar(operator.xor, other, True)\",\n \"def __neg__(self): return self._unary(operator.neg) def __pos__(self): return self._unary(operator.pos) def __abs__(self): return self.mag def\",\n \"DIANA-HEP # All rights reserved. # # Redistribution and use in source and\",\n \"# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER #\",\n \"out * 180.0/math.pi return out def isopposite(self, other, tolerance=1e-10): tmp = self +\",\n \"= self.unit b = other.unit out = out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out\",\n \"self.rho2 return awkward.util.numpy.sqrt(out) @property def phi(self): return awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self, other): denom\",\n \"def rho(self): out = self.rho2 return awkward.util.numpy.sqrt(out) @property def phi(self): return awkward.util.numpy.arctan2(self.y, self.x)\",\n \"other) def __rrshift__(self, other): return self._scalar(operator.rshift, other, True) def __and__(self, other): return self._scalar(operator.and_,\",\n \"no natural ordering\\\") def __ge__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\")\",\n \"met: # # * Redistributions of source code must retain the above copyright\",\n \"= out + self.y*self.y return out def delta_phi(self, other): return (self.phi - other.phi\",\n \"other) def __rdivmod__(self, other): return self._scalar(operator.divmod, other, True) def __pow__(self, other): if isinstance(other,\",\n \"= awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out def isperpendicular(self, other, tolerance=1e-10): tmp =\",\n \"DAMAGE. import math import numbers import operator import awkward import awkward.util class Common(object):\",\n \"tmp.z = awkward.util.numpy.absolute(tmp.z) out = (tmp.x < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.y <\",\n \"def __or__(self, other): return self._scalar(operator.or_, other) def __ror__(self, other): return self._scalar(operator.or_, other, True)\",\n \"DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY\",\n \"def __truediv__(self, other): return self._scalar(operator.truediv, other) def __rtruediv__(self, other): return self._scalar(operator.truediv, other, True)\",\n \"other): return self._scalar(operator.divmod, other, True) def __pow__(self, other): if isinstance(other, (numbers.Number, awkward.util.numpy.number)): if\",\n \"OF SUCH DAMAGE. import math import numbers import operator import awkward import awkward.util\",\n \"= self.dot(other) out[mask] /= denom mask = awkward.util.numpy.logical_not(mask) out[mask] = 1 return awkward.util.numpy.clip(out,\",\n \"self._vector(operator.add, other) def __radd__(self, other): return self._vector(operator.add, other, True) def __sub__(self, other): return\",\n \"Redistributions in binary form must reproduce the above copyright notice, # this list\",\n \"ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE\",\n \"/ self.mag @property def rho(self): out = self.rho2 return awkward.util.numpy.sqrt(out) @property def phi(self):\",\n \"ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT\",\n \"have no natural ordering\\\") def __gt__(self, other): raise TypeError(\\\"spatial vectors have no natural\",\n \"return out class Methods(Common): @property def unit(self): return self / self.mag @property def\",\n \"CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL\",\n \"LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA,\",\n \"degrees=False): out = math.acos(self.cosdelta(other)) if degrees: out = out * 180.0/math.pi return out\",\n \"TypeError(\\\"spatial vectors have no natural ordering\\\") class ArrayMethods(Common): @property def unit(self): return self\",\n \"isperpendicular(self, other, tolerance=1e-10): tmp = self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z\",\n \"other, degrees=False): out = math.acos(self.cosdelta(other)) if degrees: out = out * 180.0/math.pi return\",\n \"LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT\",\n \"OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import\",\n \"other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") def __le__(self, other): raise TypeError(\\\"spatial\",\n \"of the copyright holder nor the names of its # contributors may be\",\n \"other, True) def __floordiv__(self, other): return self._scalar(operator.floordiv, other) def __rfloordiv__(self, other): return self._scalar(operator.floordiv,\",\n \"# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \\\"AS IS\\\"\",\n \"of source code must retain the above copyright notice, this # list of\",\n \"- math.pi def isparallel(self, other, tolerance=1e-10): return 1 - self.cosdelta(other) < tolerance def\",\n \"1 return awkward.util.numpy.clip(out, -1, 1) def angle(self, other, normal=None, degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other))\",\n \"ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT\",\n \"= self.x*self.x out = out + self.y*self.y return out def delta_phi(self, other): return\",\n \"TypeError(\\\"spatial vectors have no natural ordering\\\") def __ge__(self, other): raise TypeError(\\\"spatial vectors have\",\n \"def rho2(self): out = self.x*self.x out = out + self.y*self.y return out def\",\n \"self._scalar(operator.rshift, other, True) def __and__(self, other): return self._scalar(operator.and_, other) def __rand__(self, other): return\",\n \"other): return self._scalar(operator.truediv, other) def __rtruediv__(self, other): return self._scalar(operator.truediv, other, True) def __floordiv__(self,\",\n \"notice, # this list of conditions and the following disclaimer in the documentation\",\n \"self._scalar(operator.truediv, other) def __rtruediv__(self, other): return self._scalar(operator.truediv, other, True) def __floordiv__(self, other): return\",\n \"self._unary(operator.neg) def __pos__(self): return self._unary(operator.pos) def __abs__(self): return self.mag def __invert__(self): return self._unary(operator.invert)\",\n \"< tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z <\",\n \"+ self.y*self.y return out def delta_phi(self, other): return (self.phi - other.phi + math.pi)\",\n \"THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\",\n \"MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT\",\n \"THE COPYRIGHT HOLDERS AND CONTRIBUTORS \\\"AS IS\\\" # AND ANY EXPRESS OR IMPLIED\",\n \"vectors have no natural ordering\\\") def __le__(self, other): raise TypeError(\\\"spatial vectors have no\",\n \"= self.dot(other) / math.sqrt(m1 * m2) return max(-1.0, min(1.0, r)) def angle(self, other,\",\n \"return self._scalar(operator.lshift, other) def __rlshift__(self, other): return self._scalar(operator.lshift, other, True) def __rshift__(self, other):\",\n \"the names of its # contributors may be used to endorse or promote\",\n \"def __rmod__(self, other): return self._scalar(operator.mod, other, True) def __divmod__(self, other): return self._scalar(operator.divmod, other)\",\n \"def phi(self): return awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self, other): denom = self.mag2 * other.mag2\",\n \"DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES;\",\n \"natural ordering\\\") def __le__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") def\",\n \"out def delta_phi(self, other): return (self.phi - other.phi + math.pi) % (2*math.pi) -\",\n \"def angle(self, other, normal=None, degrees=False): out = awkward.util.numpy.arccos(self.cosdelta(other)) if normal is not None:\",\n \"= awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out class Methods(Common): @property def unit(self): return\",\n \"tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out class Methods(Common): @property def\",\n \"abs(tmp.z) < tolerance def __add__(self, other): return self._vector(operator.add, other) def __radd__(self, other): return\",\n \"return math.atan2(self.y, self.x) def cosdelta(self, other): m1 = self.mag2 m2 = other.mag2 if\",\n \"self._vector(operator.sub, other, True) def __mul__(self, other): return self._scalar(operator.mul, other) def __rmul__(self, other): return\",\n \"def __gt__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") def __le__(self, other):\",\n \"abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def isperpendicular(self, other, tolerance=1e-10): tmp =\",\n \"return self._scalar(operator.and_, other) def __rand__(self, other): return self._scalar(operator.and_, other, True) def __or__(self, other):\",\n \"None: a = self.unit b = other.unit out = out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if\",\n \"other): return self._scalar(operator.div, other) def __rdiv__(self, other): return self._scalar(operator.div, other, True) def __truediv__(self,\",\n \"= self.rho2 return awkward.util.numpy.sqrt(out) @property def phi(self): return awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self, other):\",\n \"reserved. # # Redistribution and use in source and binary forms, with or\",\n \"import numbers import operator import awkward import awkward.util class Common(object): @property def mag2(self):\",\n \"def __divmod__(self, other): return self._scalar(operator.divmod, other) def __rdivmod__(self, other): return self._scalar(operator.divmod, other, True)\",\n \"\\\"AS IS\\\" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED\",\n \"if other == 2: return self.mag2 else: return self.mag2**(0.5*other) else: self._scalar(operator.pow, other) #\",\n \"# Redistribution and use in source and binary forms, with or without #\",\n \"INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS\",\n \"self.dot(other) tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out = (tmp.x\",\n \"other, True) def __and__(self, other): return self._scalar(operator.and_, other) def __rand__(self, other): return self._scalar(operator.and_,\",\n \"< tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out def isperpendicular(self, other,\",\n \"__rdivmod__(self, other): return self._scalar(operator.divmod, other, True) def __pow__(self, other): if isinstance(other, (numbers.Number, awkward.util.numpy.number)):\",\n \"def __rsub__(self, other): return self._vector(operator.sub, other, True) def __mul__(self, other): return self._scalar(operator.mul, other)\",\n \"nor the names of its # contributors may be used to endorse or\",\n \"< tolerance and abs(tmp.z) < tolerance def __add__(self, other): return self._vector(operator.add, other) def\",\n \"other, True) def __div__(self, other): return self._scalar(operator.div, other) def __rdiv__(self, other): return self._scalar(operator.div,\",\n \"source code must retain the above copyright notice, this # list of conditions\",\n \"conditions are met: # # * Redistributions of source code must retain the\",\n \"return awkward.util.numpy.sqrt(out) @property def phi(self): return awkward.util.numpy.arctan2(self.y, self.x) def cosdelta(self, other): denom =\",\n \"retain the above copyright notice, this # list of conditions and the following\",\n \"holder nor the names of its # contributors may be used to endorse\",\n \"out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out class Methods(Common): @property def unit(self):\",\n \"BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \\\"AS IS\\\" # AND ANY EXPRESS OR\",\n \"tolerance=1e-10): return 1 - self.cosdelta(other) < tolerance def isantiparallel(self, other, tolerance=1e-10): return self.cosdelta(other)\",\n \"- awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def __lt__(self, other): raise TypeError(\\\"spatial vectors have no natural\",\n \"return (self.phi - other.phi + math.pi) % (2*math.pi) - math.pi def isparallel(self, other,\",\n \"BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF\",\n \"tolerance=1e-10): tmp = self + other tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z\",\n \"tolerance=1e-10): return self.cosdelta(other) - (-1) < tolerance def iscollinear(self, other, tolerance=1e-10): return 1\",\n \"IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import math import numbers import\",\n \"STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY\",\n \"isparallel(self, other, tolerance=1e-10): return 1 - self.cosdelta(other) < tolerance def isantiparallel(self, other, tolerance=1e-10):\",\n \"tmp.x = awkward.util.numpy.absolute(tmp.x) tmp.y = awkward.util.numpy.absolute(tmp.y) tmp.z = awkward.util.numpy.absolute(tmp.z) out = (tmp.x <\",\n \"return 1.0 r = self.dot(other) / math.sqrt(m1 * m2) return max(-1.0, min(1.0, r))\",\n \"binary forms, with or without # modification, are permitted provided that the following\",\n \"other) def __rmod__(self, other): return self._scalar(operator.mod, other, True) def __divmod__(self, other): return self._scalar(operator.divmod,\",\n \"math.sqrt(m1 * m2) return max(-1.0, min(1.0, r)) def angle(self, other, degrees=False): out =\",\n \"def __pow__(self, other): if isinstance(other, (numbers.Number, awkward.util.numpy.number)): if other == 2: return self.mag2\",\n \"awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def __lt__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\")\",\n \"no natural ordering\\\") class ArrayMethods(Common): @property def unit(self): return self / self.mag @property\",\n \"ordering\\\") class ArrayMethods(Common): @property def unit(self): return self / self.mag @property def rho(self):\",\n \"unit(self): return self / self.mag @property def rho(self): return math.sqrt(self.rho2) @property def phi(self):\",\n \"other, True) def __truediv__(self, other): return self._scalar(operator.truediv, other) def __rtruediv__(self, other): return self._scalar(operator.truediv,\",\n \"may be used to endorse or promote products derived from # this software\",\n \"out = self.x*self.x out = out + self.y*self.y return out def delta_phi(self, other):\",\n \"denom = self.mag2 * other.mag2 mask = (denom > 0) denom = denom[mask]\",\n \"THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE\",\n \"#!/usr/bin/env python # Copyright (c) 2018, DIANA-HEP # All rights reserved. # #\",\n \"# # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \\\"AS\",\n \"True) def __rshift__(self, other): return self._scalar(operator.rshift, other) def __rrshift__(self, other): return self._scalar(operator.rshift, other,\",\n \"binary form must reproduce the above copyright notice, # this list of conditions\",\n \"other.unit out = out * awkward.util.numpy.sign(normal.dot(a.cross(b))) if degrees: out = awkward.util.numpy.multiply(out, 180.0/awkward.util.numpy.pi) return\",\n \"return 1 - awkward.util.numpy.absolute(self.cosdelta(other)) < tolerance def __lt__(self, other): raise TypeError(\\\"spatial vectors have\",\n \"following disclaimer in the documentation # and/or other materials provided with the distribution.\",\n \"other, tolerance=1e-10): return 1 - self.cosdelta(other) < tolerance def isantiparallel(self, other, tolerance=1e-10): return\",\n \"self.x) def cosdelta(self, other): denom = self.mag2 * other.mag2 mask = (denom >\",\n \"abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance def __add__(self,\",\n \"else: self._scalar(operator.pow, other) # no __rpow__ def __lshift__(self, other): return self._scalar(operator.lshift, other) def\",\n \"NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE,\",\n \"other return abs(tmp.x) < tolerance and abs(tmp.y) < tolerance and abs(tmp.z) < tolerance\",\n \"form must reproduce the above copyright notice, # this list of conditions and\",\n \"other, True) def __xor__(self, other): return self._scalar(operator.xor, other) def __rxor__(self, other): return self._scalar(operator.xor,\",\n \"LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES\",\n \"# list of conditions and the following disclaimer. # # * Redistributions in\",\n \"if degrees: out = out * 180.0/math.pi return out def isopposite(self, other, tolerance=1e-10):\",\n \"__add__(self, other): return self._vector(operator.add, other) def __radd__(self, other): return self._vector(operator.add, other, True) def\",\n \"self._scalar(operator.div, other) def __rdiv__(self, other): return self._scalar(operator.div, other, True) def __truediv__(self, other): return\",\n \"return self._scalar(operator.divmod, other) def __rdivmod__(self, other): return self._scalar(operator.divmod, other, True) def __pow__(self, other):\",\n \"Neither the name of the copyright holder nor the names of its #\",\n \"def __ge__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") class ArrayMethods(Common): @property\",\n \"PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS\",\n \"TypeError(\\\"spatial vectors have no natural ordering\\\") def __gt__(self, other): raise TypeError(\\\"spatial vectors have\",\n \"OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY\",\n \"WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN\",\n \"return self._scalar(operator.and_, other, True) def __or__(self, other): return self._scalar(operator.or_, other) def __ror__(self, other):\",\n \"denom[:] = awkward.util.numpy.sqrt(denom) out = self.dot(other) out[mask] /= denom mask = awkward.util.numpy.logical_not(mask) out[mask]\",\n \"awkward.util.numpy.arccos(self.cosdelta(other)) if normal is not None: a = self.unit b = other.unit out\",\n \"m1 = self.mag2 m2 = other.mag2 if m1 == 0 or m2 ==\",\n \"SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED\",\n \"OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR\",\n \"__rrshift__(self, other): return self._scalar(operator.rshift, other, True) def __and__(self, other): return self._scalar(operator.and_, other) def\",\n \"OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR\",\n \"# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\",\n \"__gt__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") def __le__(self, other): raise\",\n \"# * Redistributions of source code must retain the above copyright notice, this\",\n \"# modification, are permitted provided that the following conditions are met: # #\",\n \"written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND\",\n \"# * Redistributions in binary form must reproduce the above copyright notice, #\",\n \"return self.mag2 else: return self.mag2**(0.5*other) else: self._scalar(operator.pow, other) # no __rpow__ def __lshift__(self,\",\n \"def angle(self, other, degrees=False): out = math.acos(self.cosdelta(other)) if degrees: out = out *\",\n \"AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR\",\n \"== 0: return 1.0 r = self.dot(other) / math.sqrt(m1 * m2) return max(-1.0,\",\n \"0: return 1.0 r = self.dot(other) / math.sqrt(m1 * m2) return max(-1.0, min(1.0,\",\n \"1 - self.cosdelta(other) < tolerance def isantiparallel(self, other, tolerance=1e-10): return self.cosdelta(other) - (-1)\",\n \"no natural ordering\\\") def __gt__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\")\",\n \"def delta_phi(self, other): return (self.phi - other.phi + math.pi) % (2*math.pi) - math.pi\",\n \"natural ordering\\\") def __gt__(self, other): raise TypeError(\\\"spatial vectors have no natural ordering\\\") def\",\n \"__rshift__(self, other): return self._scalar(operator.rshift, other) def __rrshift__(self, other): return self._scalar(operator.rshift, other, True) def\",\n \"import operator import awkward import awkward.util class Common(object): @property def mag2(self): return self.dot(self)\",\n \"OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF\",\n \"or promote products derived from # this software without specific prior written permission.\",\n \"other) def __rand__(self, other): return self._scalar(operator.and_, other, True) def __or__(self, other): return self._scalar(operator.or_,\",\n \"specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT\",\n \"* Redistributions of source code must retain the above copyright notice, this #\",\n \"following disclaimer. # # * Redistributions in binary form must reproduce the above\"\n]","isConversational":false}}},{"rowIdx":4396,"cells":{"ngram":{"kind":"list like","value":["\"\"\" Implements a non interactive controller to controt non-interactive visualizers. (i.e. those that","self.vis.visualize(page.next_line(), eop) if eop: break def close(self): \"\"\" Todo: ApiDoc. :return: \"\"\" self.vis.close()","input: :param output: :param visualizer_class: \"\"\" super(ConversionController, self).__init__() parser = FileParser(input_file) self.pages =","into another format) \"\"\" from tpp.FileParser import FileParser from tpp.controller.TPPController import TPPController class","from tpp.controller.TPPController import TPPController class ConversionController(TPPController): \"\"\" Implements a non interactive controller to","a non interactive controller to run non-interactive visualizers. (i.e. those that are used","super(ConversionController, self).__init__() parser = FileParser(input_file) self.pages = parser.get_pages() self.vis = visualizer_class(output) def run(self):","eop = page.is_eop() self.vis.visualize(page.next_line(), eop) if eop: break def close(self): \"\"\" Todo: ApiDoc.","self.pages = parser.get_pages() self.vis = visualizer_class(output) def run(self): \"\"\" Todo: ApiDoc. :return: \"\"\"","to controt non-interactive visualizers. (i.e. those that are used for converting TPP souce","ConversionController(TPPController): \"\"\" Implements a non interactive controller to run non-interactive visualizers. (i.e. those",":param output: :param visualizer_class: \"\"\" super(ConversionController, self).__init__() parser = FileParser(input_file) self.pages = parser.get_pages()","non interactive controller to controt non-interactive visualizers. (i.e. those that are used for","non-interactive visualizers. (i.e. those that are used for converting TPP source code into",":param visualizer_class: \"\"\" super(ConversionController, self).__init__() parser = FileParser(input_file) self.pages = parser.get_pages() self.vis =","self.vis = visualizer_class(output) def run(self): \"\"\" Todo: ApiDoc. :return: \"\"\" for page in","\"\"\" Implements a non interactive controller to run non-interactive visualizers. (i.e. those that","that are used for converting TPP souce code into another format) \"\"\" from","controt non-interactive visualizers. (i.e. those that are used for converting TPP souce code","non interactive controller to run non-interactive visualizers. (i.e. those that are used for","self).__init__() parser = FileParser(input_file) self.pages = parser.get_pages() self.vis = visualizer_class(output) def run(self): \"\"\"",":rtype: :param input: :param output: :param visualizer_class: \"\"\" super(ConversionController, self).__init__() parser = FileParser(input_file)","in self.pages: while True: eop = page.is_eop() self.vis.visualize(page.next_line(), eop) if eop: break def","Todo: ApiDoc. :return: \"\"\" for page in self.pages: while True: eop = page.is_eop()","converting TPP source code into another format) \"\"\" def __init__(self, input_file, output, visualizer_class):","while True: eop = page.is_eop() self.vis.visualize(page.next_line(), eop) if eop: break def close(self): \"\"\"","source code into another format) \"\"\" def __init__(self, input_file, output, visualizer_class): \"\"\" Todo:","= parser.get_pages() self.vis = visualizer_class(output) def run(self): \"\"\" Todo: ApiDoc. :return: \"\"\" for","def __init__(self, input_file, output, visualizer_class): \"\"\" Todo: ApiDoc. :rtype: :param input: :param output:","import TPPController class ConversionController(TPPController): \"\"\" Implements a non interactive controller to run non-interactive","converting TPP souce code into another format) \"\"\" from tpp.FileParser import FileParser from","to run non-interactive visualizers. (i.e. those that are used for converting TPP source","import FileParser from tpp.controller.TPPController import TPPController class ConversionController(TPPController): \"\"\" Implements a non interactive","used for converting TPP souce code into another format) \"\"\" from tpp.FileParser import","Todo: ApiDoc. :rtype: :param input: :param output: :param visualizer_class: \"\"\" super(ConversionController, self).__init__() parser","visualizers. (i.e. those that are used for converting TPP souce code into another","format) \"\"\" from tpp.FileParser import FileParser from tpp.controller.TPPController import TPPController class ConversionController(TPPController): \"\"\"","visualizer_class): \"\"\" Todo: ApiDoc. :rtype: :param input: :param output: :param visualizer_class: \"\"\" super(ConversionController,","FileParser from tpp.controller.TPPController import TPPController class ConversionController(TPPController): \"\"\" Implements a non interactive controller","for converting TPP source code into another format) \"\"\" def __init__(self, input_file, output,","Implements a non interactive controller to run non-interactive visualizers. (i.e. those that are","are used for converting TPP source code into another format) \"\"\" def __init__(self,","output, visualizer_class): \"\"\" Todo: ApiDoc. :rtype: :param input: :param output: :param visualizer_class: \"\"\"","True: eop = page.is_eop() self.vis.visualize(page.next_line(), eop) if eop: break def close(self): \"\"\" Todo:",":param input: :param output: :param visualizer_class: \"\"\" super(ConversionController, self).__init__() parser = FileParser(input_file) self.pages","run(self): \"\"\" Todo: ApiDoc. :return: \"\"\" for page in self.pages: while True: eop","interactive controller to run non-interactive visualizers. (i.e. those that are used for converting","class ConversionController(TPPController): \"\"\" Implements a non interactive controller to run non-interactive visualizers. (i.e.","visualizer_class: \"\"\" super(ConversionController, self).__init__() parser = FileParser(input_file) self.pages = parser.get_pages() self.vis = visualizer_class(output)","are used for converting TPP souce code into another format) \"\"\" from tpp.FileParser","def run(self): \"\"\" Todo: ApiDoc. :return: \"\"\" for page in self.pages: while True:","\"\"\" Todo: ApiDoc. :rtype: :param input: :param output: :param visualizer_class: \"\"\" super(ConversionController, self).__init__()","\"\"\" super(ConversionController, self).__init__() parser = FileParser(input_file) self.pages = parser.get_pages() self.vis = visualizer_class(output) def","\"\"\" Todo: ApiDoc. :return: \"\"\" for page in self.pages: while True: eop =","TPP source code into another format) \"\"\" def __init__(self, input_file, output, visualizer_class): \"\"\"","for converting TPP souce code into another format) \"\"\" from tpp.FileParser import FileParser","code into another format) \"\"\" def __init__(self, input_file, output, visualizer_class): \"\"\" Todo: ApiDoc.","= FileParser(input_file) self.pages = parser.get_pages() self.vis = visualizer_class(output) def run(self): \"\"\" Todo: ApiDoc.","\"\"\" from tpp.FileParser import FileParser from tpp.controller.TPPController import TPPController class ConversionController(TPPController): \"\"\" Implements","code into another format) \"\"\" from tpp.FileParser import FileParser from tpp.controller.TPPController import TPPController","\"\"\" for page in self.pages: while True: eop = page.is_eop() self.vis.visualize(page.next_line(), eop) if","parser.get_pages() self.vis = visualizer_class(output) def run(self): \"\"\" Todo: ApiDoc. :return: \"\"\" for page","souce code into another format) \"\"\" from tpp.FileParser import FileParser from tpp.controller.TPPController import","tpp.FileParser import FileParser from tpp.controller.TPPController import TPPController class ConversionController(TPPController): \"\"\" Implements a non","TPP souce code into another format) \"\"\" from tpp.FileParser import FileParser from tpp.controller.TPPController","(i.e. those that are used for converting TPP source code into another format)","ApiDoc. :return: \"\"\" for page in self.pages: while True: eop = page.is_eop() self.vis.visualize(page.next_line(),","self.pages: while True: eop = page.is_eop() self.vis.visualize(page.next_line(), eop) if eop: break def close(self):","= visualizer_class(output) def run(self): \"\"\" Todo: ApiDoc. :return: \"\"\" for page in self.pages:","page in self.pages: while True: eop = page.is_eop() self.vis.visualize(page.next_line(), eop) if eop: break","used for converting TPP source code into another format) \"\"\" def __init__(self, input_file,","TPPController class ConversionController(TPPController): \"\"\" Implements a non interactive controller to run non-interactive visualizers.","those that are used for converting TPP source code into another format) \"\"\"","another format) \"\"\" from tpp.FileParser import FileParser from tpp.controller.TPPController import TPPController class ConversionController(TPPController):","run non-interactive visualizers. (i.e. those that are used for converting TPP source code","output: :param visualizer_class: \"\"\" super(ConversionController, self).__init__() parser = FileParser(input_file) self.pages = parser.get_pages() self.vis","non-interactive visualizers. (i.e. those that are used for converting TPP souce code into","controller to run non-interactive visualizers. (i.e. those that are used for converting TPP","that are used for converting TPP source code into another format) \"\"\" def","FileParser(input_file) self.pages = parser.get_pages() self.vis = visualizer_class(output) def run(self): \"\"\" Todo: ApiDoc. :return:","parser = FileParser(input_file) self.pages = parser.get_pages() self.vis = visualizer_class(output) def run(self): \"\"\" Todo:","visualizer_class(output) def run(self): \"\"\" Todo: ApiDoc. :return: \"\"\" for page in self.pages: while","those that are used for converting TPP souce code into another format) \"\"\"","format) \"\"\" def __init__(self, input_file, output, visualizer_class): \"\"\" Todo: ApiDoc. :rtype: :param input:","a non interactive controller to controt non-interactive visualizers. (i.e. those that are used","interactive controller to controt non-interactive visualizers. (i.e. those that are used for converting","Implements a non interactive controller to controt non-interactive visualizers. (i.e. those that are","visualizers. (i.e. those that are used for converting TPP source code into another","ApiDoc. :rtype: :param input: :param output: :param visualizer_class: \"\"\" super(ConversionController, self).__init__() parser =","(i.e. those that are used for converting TPP souce code into another format)","from tpp.FileParser import FileParser from tpp.controller.TPPController import TPPController class ConversionController(TPPController): \"\"\" Implements a","tpp.controller.TPPController import TPPController class ConversionController(TPPController): \"\"\" Implements a non interactive controller to run","__init__(self, input_file, output, visualizer_class): \"\"\" Todo: ApiDoc. :rtype: :param input: :param output: :param","controller to controt non-interactive visualizers. (i.e. those that are used for converting TPP","into another format) \"\"\" def __init__(self, input_file, output, visualizer_class): \"\"\" Todo: ApiDoc. :rtype:",":return: \"\"\" for page in self.pages: while True: eop = page.is_eop() self.vis.visualize(page.next_line(), eop)","page.is_eop() self.vis.visualize(page.next_line(), eop) if eop: break def close(self): \"\"\" Todo: ApiDoc. :return: \"\"\"","= page.is_eop() self.vis.visualize(page.next_line(), eop) if eop: break def close(self): \"\"\" Todo: ApiDoc. :return:","\"\"\" def __init__(self, input_file, output, visualizer_class): \"\"\" Todo: ApiDoc. :rtype: :param input: :param","another format) \"\"\" def __init__(self, input_file, output, visualizer_class): \"\"\" Todo: ApiDoc. :rtype: :param","for page in self.pages: while True: eop = page.is_eop() self.vis.visualize(page.next_line(), eop) if eop:","input_file, output, visualizer_class): \"\"\" Todo: ApiDoc. :rtype: :param input: :param output: :param visualizer_class:"],"string":"[\n \"\\\"\\\"\\\" Implements a non interactive controller to controt non-interactive visualizers. (i.e. those that\",\n \"self.vis.visualize(page.next_line(), eop) if eop: break def close(self): \\\"\\\"\\\" Todo: ApiDoc. :return: \\\"\\\"\\\" self.vis.close()\",\n \"input: :param output: :param visualizer_class: \\\"\\\"\\\" super(ConversionController, self).__init__() parser = FileParser(input_file) self.pages =\",\n \"into another format) \\\"\\\"\\\" from tpp.FileParser import FileParser from tpp.controller.TPPController import TPPController class\",\n \"from tpp.controller.TPPController import TPPController class ConversionController(TPPController): \\\"\\\"\\\" Implements a non interactive controller to\",\n \"a non interactive controller to run non-interactive visualizers. (i.e. those that are used\",\n \"super(ConversionController, self).__init__() parser = FileParser(input_file) self.pages = parser.get_pages() self.vis = visualizer_class(output) def run(self):\",\n \"eop = page.is_eop() self.vis.visualize(page.next_line(), eop) if eop: break def close(self): \\\"\\\"\\\" Todo: ApiDoc.\",\n \"self.pages = parser.get_pages() self.vis = visualizer_class(output) def run(self): \\\"\\\"\\\" Todo: ApiDoc. :return: \\\"\\\"\\\"\",\n \"to controt non-interactive visualizers. (i.e. those that are used for converting TPP souce\",\n \"ConversionController(TPPController): \\\"\\\"\\\" Implements a non interactive controller to run non-interactive visualizers. (i.e. those\",\n \":param output: :param visualizer_class: \\\"\\\"\\\" super(ConversionController, self).__init__() parser = FileParser(input_file) self.pages = parser.get_pages()\",\n \"non interactive controller to controt non-interactive visualizers. (i.e. those that are used for\",\n \"non-interactive visualizers. (i.e. those that are used for converting TPP source code into\",\n \":param visualizer_class: \\\"\\\"\\\" super(ConversionController, self).__init__() parser = FileParser(input_file) self.pages = parser.get_pages() self.vis =\",\n \"self.vis = visualizer_class(output) def run(self): \\\"\\\"\\\" Todo: ApiDoc. :return: \\\"\\\"\\\" for page in\",\n \"\\\"\\\"\\\" Implements a non interactive controller to run non-interactive visualizers. (i.e. those that\",\n \"that are used for converting TPP souce code into another format) \\\"\\\"\\\" from\",\n \"controt non-interactive visualizers. (i.e. those that are used for converting TPP souce code\",\n \"non interactive controller to run non-interactive visualizers. (i.e. those that are used for\",\n \"self).__init__() parser = FileParser(input_file) self.pages = parser.get_pages() self.vis = visualizer_class(output) def run(self): \\\"\\\"\\\"\",\n \":rtype: :param input: :param output: :param visualizer_class: \\\"\\\"\\\" super(ConversionController, self).__init__() parser = FileParser(input_file)\",\n \"in self.pages: while True: eop = page.is_eop() self.vis.visualize(page.next_line(), eop) if eop: break def\",\n \"Todo: ApiDoc. :return: \\\"\\\"\\\" for page in self.pages: while True: eop = page.is_eop()\",\n \"converting TPP source code into another format) \\\"\\\"\\\" def __init__(self, input_file, output, visualizer_class):\",\n \"while True: eop = page.is_eop() self.vis.visualize(page.next_line(), eop) if eop: break def close(self): \\\"\\\"\\\"\",\n \"source code into another format) \\\"\\\"\\\" def __init__(self, input_file, output, visualizer_class): \\\"\\\"\\\" Todo:\",\n \"= parser.get_pages() self.vis = visualizer_class(output) def run(self): \\\"\\\"\\\" Todo: ApiDoc. :return: \\\"\\\"\\\" for\",\n \"def __init__(self, input_file, output, visualizer_class): \\\"\\\"\\\" Todo: ApiDoc. :rtype: :param input: :param output:\",\n \"import TPPController class ConversionController(TPPController): \\\"\\\"\\\" Implements a non interactive controller to run non-interactive\",\n \"converting TPP souce code into another format) \\\"\\\"\\\" from tpp.FileParser import FileParser from\",\n \"to run non-interactive visualizers. (i.e. those that are used for converting TPP source\",\n \"import FileParser from tpp.controller.TPPController import TPPController class ConversionController(TPPController): \\\"\\\"\\\" Implements a non interactive\",\n \"used for converting TPP souce code into another format) \\\"\\\"\\\" from tpp.FileParser import\",\n \"Todo: ApiDoc. :rtype: :param input: :param output: :param visualizer_class: \\\"\\\"\\\" super(ConversionController, self).__init__() parser\",\n \"visualizers. (i.e. those that are used for converting TPP souce code into another\",\n \"format) \\\"\\\"\\\" from tpp.FileParser import FileParser from tpp.controller.TPPController import TPPController class ConversionController(TPPController): \\\"\\\"\\\"\",\n \"visualizer_class): \\\"\\\"\\\" Todo: ApiDoc. :rtype: :param input: :param output: :param visualizer_class: \\\"\\\"\\\" super(ConversionController,\",\n \"FileParser from tpp.controller.TPPController import TPPController class ConversionController(TPPController): \\\"\\\"\\\" Implements a non interactive controller\",\n \"for converting TPP source code into another format) \\\"\\\"\\\" def __init__(self, input_file, output,\",\n \"Implements a non interactive controller to run non-interactive visualizers. (i.e. those that are\",\n \"are used for converting TPP source code into another format) \\\"\\\"\\\" def __init__(self,\",\n \"output, visualizer_class): \\\"\\\"\\\" Todo: ApiDoc. :rtype: :param input: :param output: :param visualizer_class: \\\"\\\"\\\"\",\n \"True: eop = page.is_eop() self.vis.visualize(page.next_line(), eop) if eop: break def close(self): \\\"\\\"\\\" Todo:\",\n \":param input: :param output: :param visualizer_class: \\\"\\\"\\\" super(ConversionController, self).__init__() parser = FileParser(input_file) self.pages\",\n \"run(self): \\\"\\\"\\\" Todo: ApiDoc. :return: \\\"\\\"\\\" for page in self.pages: while True: eop\",\n \"interactive controller to run non-interactive visualizers. (i.e. those that are used for converting\",\n \"class ConversionController(TPPController): \\\"\\\"\\\" Implements a non interactive controller to run non-interactive visualizers. (i.e.\",\n \"visualizer_class: \\\"\\\"\\\" super(ConversionController, self).__init__() parser = FileParser(input_file) self.pages = parser.get_pages() self.vis = visualizer_class(output)\",\n \"are used for converting TPP souce code into another format) \\\"\\\"\\\" from tpp.FileParser\",\n \"def run(self): \\\"\\\"\\\" Todo: ApiDoc. :return: \\\"\\\"\\\" for page in self.pages: while True:\",\n \"\\\"\\\"\\\" Todo: ApiDoc. :rtype: :param input: :param output: :param visualizer_class: \\\"\\\"\\\" super(ConversionController, self).__init__()\",\n \"\\\"\\\"\\\" super(ConversionController, self).__init__() parser = FileParser(input_file) self.pages = parser.get_pages() self.vis = visualizer_class(output) def\",\n \"\\\"\\\"\\\" Todo: ApiDoc. :return: \\\"\\\"\\\" for page in self.pages: while True: eop =\",\n \"TPP source code into another format) \\\"\\\"\\\" def __init__(self, input_file, output, visualizer_class): \\\"\\\"\\\"\",\n \"for converting TPP souce code into another format) \\\"\\\"\\\" from tpp.FileParser import FileParser\",\n \"code into another format) \\\"\\\"\\\" def __init__(self, input_file, output, visualizer_class): \\\"\\\"\\\" Todo: ApiDoc.\",\n \"= FileParser(input_file) self.pages = parser.get_pages() self.vis = visualizer_class(output) def run(self): \\\"\\\"\\\" Todo: ApiDoc.\",\n \"\\\"\\\"\\\" from tpp.FileParser import FileParser from tpp.controller.TPPController import TPPController class ConversionController(TPPController): \\\"\\\"\\\" Implements\",\n \"code into another format) \\\"\\\"\\\" from tpp.FileParser import FileParser from tpp.controller.TPPController import TPPController\",\n \"\\\"\\\"\\\" for page in self.pages: while True: eop = page.is_eop() self.vis.visualize(page.next_line(), eop) if\",\n \"parser.get_pages() self.vis = visualizer_class(output) def run(self): \\\"\\\"\\\" Todo: ApiDoc. :return: \\\"\\\"\\\" for page\",\n \"souce code into another format) \\\"\\\"\\\" from tpp.FileParser import FileParser from tpp.controller.TPPController import\",\n \"tpp.FileParser import FileParser from tpp.controller.TPPController import TPPController class ConversionController(TPPController): \\\"\\\"\\\" Implements a non\",\n \"TPP souce code into another format) \\\"\\\"\\\" from tpp.FileParser import FileParser from tpp.controller.TPPController\",\n \"(i.e. those that are used for converting TPP source code into another format)\",\n \"ApiDoc. :return: \\\"\\\"\\\" for page in self.pages: while True: eop = page.is_eop() self.vis.visualize(page.next_line(),\",\n \"self.pages: while True: eop = page.is_eop() self.vis.visualize(page.next_line(), eop) if eop: break def close(self):\",\n \"= visualizer_class(output) def run(self): \\\"\\\"\\\" Todo: ApiDoc. :return: \\\"\\\"\\\" for page in self.pages:\",\n \"page in self.pages: while True: eop = page.is_eop() self.vis.visualize(page.next_line(), eop) if eop: break\",\n \"used for converting TPP source code into another format) \\\"\\\"\\\" def __init__(self, input_file,\",\n \"TPPController class ConversionController(TPPController): \\\"\\\"\\\" Implements a non interactive controller to run non-interactive visualizers.\",\n \"those that are used for converting TPP source code into another format) \\\"\\\"\\\"\",\n \"another format) \\\"\\\"\\\" from tpp.FileParser import FileParser from tpp.controller.TPPController import TPPController class ConversionController(TPPController):\",\n \"run non-interactive visualizers. (i.e. those that are used for converting TPP source code\",\n \"output: :param visualizer_class: \\\"\\\"\\\" super(ConversionController, self).__init__() parser = FileParser(input_file) self.pages = parser.get_pages() self.vis\",\n \"non-interactive visualizers. (i.e. those that are used for converting TPP souce code into\",\n \"controller to run non-interactive visualizers. (i.e. those that are used for converting TPP\",\n \"that are used for converting TPP source code into another format) \\\"\\\"\\\" def\",\n \"FileParser(input_file) self.pages = parser.get_pages() self.vis = visualizer_class(output) def run(self): \\\"\\\"\\\" Todo: ApiDoc. :return:\",\n \"parser = FileParser(input_file) self.pages = parser.get_pages() self.vis = visualizer_class(output) def run(self): \\\"\\\"\\\" Todo:\",\n \"visualizer_class(output) def run(self): \\\"\\\"\\\" Todo: ApiDoc. :return: \\\"\\\"\\\" for page in self.pages: while\",\n \"those that are used for converting TPP souce code into another format) \\\"\\\"\\\"\",\n \"format) \\\"\\\"\\\" def __init__(self, input_file, output, visualizer_class): \\\"\\\"\\\" Todo: ApiDoc. :rtype: :param input:\",\n \"a non interactive controller to controt non-interactive visualizers. (i.e. those that are used\",\n \"interactive controller to controt non-interactive visualizers. (i.e. those that are used for converting\",\n \"Implements a non interactive controller to controt non-interactive visualizers. (i.e. those that are\",\n \"visualizers. (i.e. those that are used for converting TPP source code into another\",\n \"ApiDoc. :rtype: :param input: :param output: :param visualizer_class: \\\"\\\"\\\" super(ConversionController, self).__init__() parser =\",\n \"(i.e. those that are used for converting TPP souce code into another format)\",\n \"from tpp.FileParser import FileParser from tpp.controller.TPPController import TPPController class ConversionController(TPPController): \\\"\\\"\\\" Implements a\",\n \"tpp.controller.TPPController import TPPController class ConversionController(TPPController): \\\"\\\"\\\" Implements a non interactive controller to run\",\n \"__init__(self, input_file, output, visualizer_class): \\\"\\\"\\\" Todo: ApiDoc. :rtype: :param input: :param output: :param\",\n \"controller to controt non-interactive visualizers. (i.e. those that are used for converting TPP\",\n \"into another format) \\\"\\\"\\\" def __init__(self, input_file, output, visualizer_class): \\\"\\\"\\\" Todo: ApiDoc. :rtype:\",\n \":return: \\\"\\\"\\\" for page in self.pages: while True: eop = page.is_eop() self.vis.visualize(page.next_line(), eop)\",\n \"page.is_eop() self.vis.visualize(page.next_line(), eop) if eop: break def close(self): \\\"\\\"\\\" Todo: ApiDoc. :return: \\\"\\\"\\\"\",\n \"= page.is_eop() self.vis.visualize(page.next_line(), eop) if eop: break def close(self): \\\"\\\"\\\" Todo: ApiDoc. :return:\",\n \"\\\"\\\"\\\" def __init__(self, input_file, output, visualizer_class): \\\"\\\"\\\" Todo: ApiDoc. :rtype: :param input: :param\",\n \"another format) \\\"\\\"\\\" def __init__(self, input_file, output, visualizer_class): \\\"\\\"\\\" Todo: ApiDoc. :rtype: :param\",\n \"for page in self.pages: while True: eop = page.is_eop() self.vis.visualize(page.next_line(), eop) if eop:\",\n \"input_file, output, visualizer_class): \\\"\\\"\\\" Todo: ApiDoc. :rtype: :param input: :param output: :param visualizer_class:\"\n]","isConversational":false}}},{"rowIdx":4397,"cells":{"ngram":{"kind":"list like","value":["data=sum_data) return [response.json(), response_sum.json()] if __name__ == '__main__': cs = CovidScraper() results =","BeautifulSoup(page.content, 'html.parser') return soup def scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content, 'html.parser')","self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data and self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data( self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data)","soup def get_daily_data(self, soup): covid_data = [] daily_covidgr_html_content = soup.find('li', class_='news_li') get_daily_covidgr_text =","self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data and self.covid_data: post_daily_and_sum_covid_data","= self.call_api_put_data( self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data = self.get_tests_per_day(soup_test_page) if tests_data[0]:","self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data = self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0],","= BeautifulSoup(page.content, 'html.parser') return soup def scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content,","regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data = summary_data def get_tests_per_day(self, tree): html_content = tree.find('tr',","self.summary_data= [] def scrape_data(self): data = [] self.today = str(date.today()) soup = self.scrape_page_content()","self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data = self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data(","def __init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url =","soup = BeautifulSoup(page.content, 'html.parser') return soup def scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url) soup =","return [response.json(), response_sum.json()] if __name__ == '__main__': cs = CovidScraper() results = cs.scrape_data()","get_daily_covidgr_text = daily_covidgr_html_content.text for elem in get_daily_covidgr_text.split(): regex = '\\d*(.|)\\d+' match = re.findall(regex,","re.findall(regex, elem) if match: covid_data.append(elem) self.covid_data = covid_data def get_summary_data(self, soup): summary_data =","html_content[3].text if country_code.text == 'GRC': today_tests = html_content[10].text total_tests = html_content[8].text return [date_test,","= json.dumps( {\"date\": today, \"cases\": covid_data[0], \"deaths\": covid_data[1]}) sum_data = json.dumps( {\"sum_cases\": summary_data[0],","[] self.summary_data= [] def scrape_data(self): data = [] self.today = str(date.today()) soup =","response_tests.json() def call_api_put_data(self, today, covid_data, summary_data): headers = { 'Content-type': 'application/json', } data","total_tests = html_content[8].text return [date_test, today_tests] def call_api_post_tested_covid_data(self, today, tests): headers = {","html_content = tree.find('tr', id='LC34').find_all('td') country_code = html_content[1] date_test = html_content[3].text if country_code.text ==","today, \"daily_test\": tests}) response_tests = requests.post( self.api_test_url, headers=headers, data=data) return response_tests.json() def call_api_put_data(self,","tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return data def scrape_page_content(self): page =","def get_tests_per_day(self, tree): html_content = tree.find('tr', id='LC34').find_all('td') country_code = html_content[1] date_test = html_content[3].text","\"cases\": covid_data[0], \"deaths\": covid_data[1]}) sum_data = json.dumps( {\"sum_cases\": summary_data[0], \"sum_deaths\": summary_data[1], \"sum_recovered\": summary_data[2]})","today, \"cases\": covid_data[0], \"deaths\": covid_data[1]}) sum_data = json.dumps( {\"sum_cases\": summary_data[0], \"sum_deaths\": summary_data[1], \"sum_recovered\":","import requests import re import json class CovidScraper: def __init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr'","if soup_test_page: tests_data = self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data)","self.today = '' self.covid_data = [] self.summary_data= [] def scrape_data(self): data = []","def call_api_post_tested_covid_data(self, today, tests): headers = { 'Content-type': 'application/json', } data = json.dumps({\"date\":","post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return data def scrape_page_content(self): page = requests.get(self.scrape_url)","CovidScraper: def __init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url","data.append(post_daily_tests_covid_data) return data def scrape_page_content(self): page = requests.get(self.scrape_url) soup = BeautifulSoup(page.content, 'html.parser') return","'GRC': today_tests = html_content[10].text total_tests = html_content[8].text return [date_test, today_tests] def call_api_post_tested_covid_data(self, today,","\"sum_deaths\": summary_data[1], \"sum_recovered\": summary_data[2]}) response = requests.post(self.api_url, headers=headers, data=data) response_sum = requests.put( self.api_sum_url,","soup): summary_data = [] all_cases_covidgr_html_content = soup.find_all( 'div', class_='maincounter-number') for item in range(len(all_cases_covidgr_html_content)):","html import requests import re import json class CovidScraper: def __init__(self): self.api_url =","return soup def get_daily_data(self, soup): covid_data = [] daily_covidgr_html_content = soup.find('li', class_='news_li') get_daily_covidgr_text","match: covid_data.append(elem) self.covid_data = covid_data def get_summary_data(self, soup): summary_data = [] all_cases_covidgr_html_content =","'html.parser') return soup def scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content, 'html.parser') return","json class CovidScraper: def __init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url =","get_daily_covidgr_text.split(): regex = '\\d*(.|)\\d+' match = re.findall(regex, elem) if match: covid_data.append(elem) self.covid_data =","self.covid_data = [] self.summary_data= [] def scrape_data(self): data = [] self.today = str(date.today())","soup.find('li', class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text for elem in get_daily_covidgr_text.split(): regex = '\\d*(.|)\\d+' match","self.summary_data and self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data( self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data","import json class CovidScraper: def __init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url","= requests.get(self.scrape_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url)","today_tests = html_content[10].text total_tests = html_content[8].text return [date_test, today_tests] def call_api_post_tested_covid_data(self, today, tests):","summary_data[2]}) response = requests.post(self.api_url, headers=headers, data=data) response_sum = requests.put( self.api_sum_url, headers=headers, data=sum_data) return","soup: self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data and self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data( self.today, self.covid_data, self.summary_data)","'' self.covid_data = [] self.summary_data= [] def scrape_data(self): data = [] self.today =","= requests.put( self.api_sum_url, headers=headers, data=sum_data) return [response.json(), response_sum.json()] if __name__ == '__main__': cs","[] def scrape_data(self): data = [] self.today = str(date.today()) soup = self.scrape_page_content() soup_test_page","= str(date.today()) soup = self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup) self.get_summary_data(soup) if","} data = json.dumps( {\"date\": today, \"cases\": covid_data[0], \"deaths\": covid_data[1]}) sum_data = json.dumps(","lxml import html import requests import re import json class CovidScraper: def __init__(self):","= tree.find('tr', id='LC34').find_all('td') country_code = html_content[1] date_test = html_content[3].text if country_code.text == 'GRC':","regex = r'(\\n)|\\s' all_cases_data = re.sub( regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data = summary_data","daily_covidgr_html_content = soup.find('li', class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text for elem in get_daily_covidgr_text.split(): regex =","today_tests] def call_api_post_tested_covid_data(self, today, tests): headers = { 'Content-type': 'application/json', } data =","= re.findall(regex, elem) if match: covid_data.append(elem) self.covid_data = covid_data def get_summary_data(self, soup): summary_data","= summary_data def get_tests_per_day(self, tree): html_content = tree.find('tr', id='LC34').find_all('td') country_code = html_content[1] date_test","date from lxml import html import requests import re import json class CovidScraper:","import date from lxml import html import requests import re import json class","import BeautifulSoup from datetime import date from lxml import html import requests import","= json.dumps({\"date\": today, \"daily_test\": tests}) response_tests = requests.post( self.api_test_url, headers=headers, data=data) return response_tests.json()","self.covid_data = covid_data def get_summary_data(self, soup): summary_data = [] all_cases_covidgr_html_content = soup.find_all( 'div',","self.get_summary_data(soup) if self.summary_data and self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data( self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if","covid_data.append(elem) self.covid_data = covid_data def get_summary_data(self, soup): summary_data = [] all_cases_covidgr_html_content = soup.find_all(","if match: covid_data.append(elem) self.covid_data = covid_data def get_summary_data(self, soup): summary_data = [] all_cases_covidgr_html_content","summary_data[0], \"sum_deaths\": summary_data[1], \"sum_recovered\": summary_data[2]}) response = requests.post(self.api_url, headers=headers, data=data) response_sum = requests.put(","data def scrape_page_content(self): page = requests.get(self.scrape_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def","self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url","headers = { 'Content-type': 'application/json', } data = json.dumps({\"date\": today, \"daily_test\": tests}) response_tests","self.call_api_put_data( self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data = self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data","soup_test_page: tests_data = self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return","if soup: self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data and self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data( self.today, self.covid_data,","re import json class CovidScraper: def __init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr'","self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = '' self.covid_data = [] self.summary_data= [] def scrape_data(self):","def scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def get_daily_data(self,","self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return data def scrape_page_content(self):","def get_daily_data(self, soup): covid_data = [] daily_covidgr_html_content = soup.find('li', class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text","data = json.dumps({\"date\": today, \"daily_test\": tests}) response_tests = requests.post( self.api_test_url, headers=headers, data=data) return","[] self.today = str(date.today()) soup = self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup)","and self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data( self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data =","= 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today =","return soup def scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content, 'html.parser') return soup","get_summary_data(self, soup): summary_data = [] all_cases_covidgr_html_content = soup.find_all( 'div', class_='maincounter-number') for item in","summary_data): headers = { 'Content-type': 'application/json', } data = json.dumps( {\"date\": today, \"cases\":","datetime import date from lxml import html import requests import re import json","'div', class_='maincounter-number') for item in range(len(all_cases_covidgr_html_content)): regex = r'(\\n)|\\s' all_cases_data = re.sub( regex,","daily_covidgr_html_content.text for elem in get_daily_covidgr_text.split(): regex = '\\d*(.|)\\d+' match = re.findall(regex, elem) if","requests import re import json class CovidScraper: def __init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url","json.dumps({\"date\": today, \"daily_test\": tests}) response_tests = requests.post( self.api_test_url, headers=headers, data=data) return response_tests.json() def","'application/json', } data = json.dumps( {\"date\": today, \"cases\": covid_data[0], \"deaths\": covid_data[1]}) sum_data =","if self.summary_data and self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data( self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page:","{\"date\": today, \"cases\": covid_data[0], \"deaths\": covid_data[1]}) sum_data = json.dumps( {\"sum_cases\": summary_data[0], \"sum_deaths\": summary_data[1],","= self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data and self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data(","= '\\d*(.|)\\d+' match = re.findall(regex, elem) if match: covid_data.append(elem) self.covid_data = covid_data def","'\\d*(.|)\\d+' match = re.findall(regex, elem) if match: covid_data.append(elem) self.covid_data = covid_data def get_summary_data(self,","def call_api_put_data(self, today, covid_data, summary_data): headers = { 'Content-type': 'application/json', } data =","BeautifulSoup(page.content, 'html.parser') return soup def get_daily_data(self, soup): covid_data = [] daily_covidgr_html_content = soup.find('li',","= daily_covidgr_html_content.text for elem in get_daily_covidgr_text.split(): regex = '\\d*(.|)\\d+' match = re.findall(regex, elem)","'Content-type': 'application/json', } data = json.dumps({\"date\": today, \"daily_test\": tests}) response_tests = requests.post( self.api_test_url,","self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data and self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data( self.today,","{\"sum_cases\": summary_data[0], \"sum_deaths\": summary_data[1], \"sum_recovered\": summary_data[2]}) response = requests.post(self.api_url, headers=headers, data=data) response_sum =","page = requests.get(self.scrape_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def scrape_page_content_contains_tests(self): page =","json.dumps( {\"sum_cases\": summary_data[0], \"sum_deaths\": summary_data[1], \"sum_recovered\": summary_data[2]}) response = requests.post(self.api_url, headers=headers, data=data) response_sum","html_content[1] date_test = html_content[3].text if country_code.text == 'GRC': today_tests = html_content[10].text total_tests =","tree.find('tr', id='LC34').find_all('td') country_code = html_content[1] date_test = html_content[3].text if country_code.text == 'GRC': today_tests","def get_summary_data(self, soup): summary_data = [] all_cases_covidgr_html_content = soup.find_all( 'div', class_='maincounter-number') for item","soup): covid_data = [] daily_covidgr_html_content = soup.find('li', class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text for elem","\"sum_recovered\": summary_data[2]}) response = requests.post(self.api_url, headers=headers, data=data) response_sum = requests.put( self.api_sum_url, headers=headers, data=sum_data)","'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = '' self.covid_data = []","= re.sub( regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data = summary_data def get_tests_per_day(self, tree): html_content","[] daily_covidgr_html_content = soup.find('li', class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text for elem in get_daily_covidgr_text.split(): regex","[] all_cases_covidgr_html_content = soup.find_all( 'div', class_='maincounter-number') for item in range(len(all_cases_covidgr_html_content)): regex = r'(\\n)|\\s'","re.sub( regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data = summary_data def get_tests_per_day(self, tree): html_content =","post_daily_and_sum_covid_data = self.call_api_put_data( self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data = self.get_tests_per_day(soup_test_page) if","data = json.dumps( {\"date\": today, \"cases\": covid_data[0], \"deaths\": covid_data[1]}) sum_data = json.dumps( {\"sum_cases\":","headers=headers, data=sum_data) return [response.json(), response_sum.json()] if __name__ == '__main__': cs = CovidScraper() results","country_code.text == 'GRC': today_tests = html_content[10].text total_tests = html_content[8].text return [date_test, today_tests] def","summary_data.append(all_cases_data) self.summary_data = summary_data def get_tests_per_day(self, tree): html_content = tree.find('tr', id='LC34').find_all('td') country_code =","tests_data[1]) data.append(post_daily_tests_covid_data) return data def scrape_page_content(self): page = requests.get(self.scrape_url) soup = BeautifulSoup(page.content, 'html.parser')","= [] self.summary_data= [] def scrape_data(self): data = [] self.today = str(date.today()) soup","= html_content[8].text return [date_test, today_tests] def call_api_post_tested_covid_data(self, today, tests): headers = { 'Content-type':","requests.post( self.api_test_url, headers=headers, data=data) return response_tests.json() def call_api_put_data(self, today, covid_data, summary_data): headers =","'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = '' self.covid_data = [] self.summary_data= [] def scrape_data(self): data =","call_api_post_tested_covid_data(self, today, tests): headers = { 'Content-type': 'application/json', } data = json.dumps({\"date\": today,","= { 'Content-type': 'application/json', } data = json.dumps( {\"date\": today, \"cases\": covid_data[0], \"deaths\":","} data = json.dumps({\"date\": today, \"daily_test\": tests}) response_tests = requests.post( self.api_test_url, headers=headers, data=data)","= '' self.covid_data = [] self.summary_data= [] def scrape_data(self): data = [] self.today","= r'(\\n)|\\s' all_cases_data = re.sub( regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data = summary_data def","bs4 import BeautifulSoup from datetime import date from lxml import html import requests","soup.find_all( 'div', class_='maincounter-number') for item in range(len(all_cases_covidgr_html_content)): regex = r'(\\n)|\\s' all_cases_data = re.sub(","\"deaths\": covid_data[1]}) sum_data = json.dumps( {\"sum_cases\": summary_data[0], \"sum_deaths\": summary_data[1], \"sum_recovered\": summary_data[2]}) response =","tree): html_content = tree.find('tr', id='LC34').find_all('td') country_code = html_content[1] date_test = html_content[3].text if country_code.text","= soup.find('li', class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text for elem in get_daily_covidgr_text.split(): regex = '\\d*(.|)\\d+'","html_content[10].text total_tests = html_content[8].text return [date_test, today_tests] def call_api_post_tested_covid_data(self, today, tests): headers =","self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today","from lxml import html import requests import re import json class CovidScraper: def","= 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = '' self.covid_data = [] self.summary_data= []","in range(len(all_cases_covidgr_html_content)): regex = r'(\\n)|\\s' all_cases_data = re.sub( regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data","== 'GRC': today_tests = html_content[10].text total_tests = html_content[8].text return [date_test, today_tests] def call_api_post_tested_covid_data(self,","tests_data = self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return data","requests.post(self.api_url, headers=headers, data=data) response_sum = requests.put( self.api_sum_url, headers=headers, data=sum_data) return [response.json(), response_sum.json()] if","[response.json(), response_sum.json()] if __name__ == '__main__': cs = CovidScraper() results = cs.scrape_data() print(results)","tests}) response_tests = requests.post( self.api_test_url, headers=headers, data=data) return response_tests.json() def call_api_put_data(self, today, covid_data,","scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def get_daily_data(self, soup):","covid_data = [] daily_covidgr_html_content = soup.find('li', class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text for elem in","data = [] self.today = str(date.today()) soup = self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests() if","all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data = summary_data def get_tests_per_day(self, tree): html_content = tree.find('tr', id='LC34').find_all('td') country_code","today, covid_data, summary_data): headers = { 'Content-type': 'application/json', } data = json.dumps( {\"date\":","= requests.post( self.api_test_url, headers=headers, data=data) return response_tests.json() def call_api_put_data(self, today, covid_data, summary_data): headers","covid_data, summary_data): headers = { 'Content-type': 'application/json', } data = json.dumps( {\"date\": today,","range(len(all_cases_covidgr_html_content)): regex = r'(\\n)|\\s' all_cases_data = re.sub( regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data =","class CovidScraper: def __init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests'","covid_data[0], \"deaths\": covid_data[1]}) sum_data = json.dumps( {\"sum_cases\": summary_data[0], \"sum_deaths\": summary_data[1], \"sum_recovered\": summary_data[2]}) response","__init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/'","'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = '' self.covid_data = [] self.summary_data= [] def","= html_content[10].text total_tests = html_content[8].text return [date_test, today_tests] def call_api_post_tested_covid_data(self, today, tests): headers","self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = '' self.covid_data","json.dumps( {\"date\": today, \"cases\": covid_data[0], \"deaths\": covid_data[1]}) sum_data = json.dumps( {\"sum_cases\": summary_data[0], \"sum_deaths\":","= covid_data def get_summary_data(self, soup): summary_data = [] all_cases_covidgr_html_content = soup.find_all( 'div', class_='maincounter-number')","response_tests = requests.post( self.api_test_url, headers=headers, data=data) return response_tests.json() def call_api_put_data(self, today, covid_data, summary_data):","import re import json class CovidScraper: def __init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url =","data=data) return response_tests.json() def call_api_put_data(self, today, covid_data, summary_data): headers = { 'Content-type': 'application/json',","self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = '' self.covid_data = [] self.summary_data=","today, tests): headers = { 'Content-type': 'application/json', } data = json.dumps({\"date\": today, \"daily_test\":","all_cases_data = re.sub( regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data = summary_data def get_tests_per_day(self, tree):","{ 'Content-type': 'application/json', } data = json.dumps( {\"date\": today, \"cases\": covid_data[0], \"deaths\": covid_data[1]})","in get_daily_covidgr_text.split(): regex = '\\d*(.|)\\d+' match = re.findall(regex, elem) if match: covid_data.append(elem) self.covid_data","= BeautifulSoup(page.content, 'html.parser') return soup def get_daily_data(self, soup): covid_data = [] daily_covidgr_html_content =","self.api_sum_url, headers=headers, data=sum_data) return [response.json(), response_sum.json()] if __name__ == '__main__': cs = CovidScraper()","self.today = str(date.today()) soup = self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup) self.get_summary_data(soup)","tests): headers = { 'Content-type': 'application/json', } data = json.dumps({\"date\": today, \"daily_test\": tests})","= self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data and self.covid_data:","if tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return data def scrape_page_content(self): page","self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return data def scrape_page_content(self): page = requests.get(self.scrape_url) soup =","str(date.today()) soup = self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data","elem in get_daily_covidgr_text.split(): regex = '\\d*(.|)\\d+' match = re.findall(regex, elem) if match: covid_data.append(elem)","covid_data def get_summary_data(self, soup): summary_data = [] all_cases_covidgr_html_content = soup.find_all( 'div', class_='maincounter-number') for","[date_test, today_tests] def call_api_post_tested_covid_data(self, today, tests): headers = { 'Content-type': 'application/json', } data","tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return data def scrape_page_content(self): page = requests.get(self.scrape_url) soup = BeautifulSoup(page.content,","r'(\\n)|\\s' all_cases_data = re.sub( regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data = summary_data def get_tests_per_day(self,","from datetime import date from lxml import html import requests import re import","= self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return data def","= soup.find_all( 'div', class_='maincounter-number') for item in range(len(all_cases_covidgr_html_content)): regex = r'(\\n)|\\s' all_cases_data =","= 'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url =","'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = ''","item in range(len(all_cases_covidgr_html_content)): regex = r'(\\n)|\\s' all_cases_data = re.sub( regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data)","return data def scrape_page_content(self): page = requests.get(self.scrape_url) soup = BeautifulSoup(page.content, 'html.parser') return soup","country_code = html_content[1] date_test = html_content[3].text if country_code.text == 'GRC': today_tests = html_content[10].text","if country_code.text == 'GRC': today_tests = html_content[10].text total_tests = html_content[8].text return [date_test, today_tests]","headers=headers, data=data) response_sum = requests.put( self.api_sum_url, headers=headers, data=sum_data) return [response.json(), response_sum.json()] if __name__","html_content[8].text return [date_test, today_tests] def call_api_post_tested_covid_data(self, today, tests): headers = { 'Content-type': 'application/json',","date_test = html_content[3].text if country_code.text == 'GRC': today_tests = html_content[10].text total_tests = html_content[8].text","scrape_page_content(self): page = requests.get(self.scrape_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def scrape_page_content_contains_tests(self): page","import html import requests import re import json class CovidScraper: def __init__(self): self.api_url","summary_data = [] all_cases_covidgr_html_content = soup.find_all( 'div', class_='maincounter-number') for item in range(len(all_cases_covidgr_html_content)): regex","self.api_test_url, headers=headers, data=data) return response_tests.json() def call_api_put_data(self, today, covid_data, summary_data): headers = {","self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data( self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data = self.get_tests_per_day(soup_test_page)","soup = BeautifulSoup(page.content, 'html.parser') return soup def get_daily_data(self, soup): covid_data = [] daily_covidgr_html_content","requests.get(self.scrape_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url) soup","= self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return data def scrape_page_content(self): page = requests.get(self.scrape_url) soup","elem) if match: covid_data.append(elem) self.covid_data = covid_data def get_summary_data(self, soup): summary_data = []","all_cases_covidgr_html_content = soup.find_all( 'div', class_='maincounter-number') for item in range(len(all_cases_covidgr_html_content)): regex = r'(\\n)|\\s' all_cases_data","soup = self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data and","get_tests_per_day(self, tree): html_content = tree.find('tr', id='LC34').find_all('td') country_code = html_content[1] date_test = html_content[3].text if","'Content-type': 'application/json', } data = json.dumps( {\"date\": today, \"cases\": covid_data[0], \"deaths\": covid_data[1]}) sum_data","match = re.findall(regex, elem) if match: covid_data.append(elem) self.covid_data = covid_data def get_summary_data(self, soup):","= [] all_cases_covidgr_html_content = soup.find_all( 'div', class_='maincounter-number') for item in range(len(all_cases_covidgr_html_content)): regex =","headers = { 'Content-type': 'application/json', } data = json.dumps( {\"date\": today, \"cases\": covid_data[0],","self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data = self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data =","{ 'Content-type': 'application/json', } data = json.dumps({\"date\": today, \"daily_test\": tests}) response_tests = requests.post(","'application/json', } data = json.dumps({\"date\": today, \"daily_test\": tests}) response_tests = requests.post( self.api_test_url, headers=headers,","= json.dumps( {\"sum_cases\": summary_data[0], \"sum_deaths\": summary_data[1], \"sum_recovered\": summary_data[2]}) response = requests.post(self.api_url, headers=headers, data=data)","regex = '\\d*(.|)\\d+' match = re.findall(regex, elem) if match: covid_data.append(elem) self.covid_data = covid_data","self.summary_data = summary_data def get_tests_per_day(self, tree): html_content = tree.find('tr', id='LC34').find_all('td') country_code = html_content[1]","= html_content[3].text if country_code.text == 'GRC': today_tests = html_content[10].text total_tests = html_content[8].text return","= [] self.today = str(date.today()) soup = self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests() if soup:","= [] daily_covidgr_html_content = soup.find('li', class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text for elem in get_daily_covidgr_text.split():","covid_data[1]}) sum_data = json.dumps( {\"sum_cases\": summary_data[0], \"sum_deaths\": summary_data[1], \"sum_recovered\": summary_data[2]}) response = requests.post(self.api_url,","summary_data[1], \"sum_recovered\": summary_data[2]}) response = requests.post(self.api_url, headers=headers, data=data) response_sum = requests.put( self.api_sum_url, headers=headers,","class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text for elem in get_daily_covidgr_text.split(): regex = '\\d*(.|)\\d+' match =","\"daily_test\": tests}) response_tests = requests.post( self.api_test_url, headers=headers, data=data) return response_tests.json() def call_api_put_data(self, today,","requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def get_daily_data(self, soup): covid_data = []","soup def scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def","class_='maincounter-number') for item in range(len(all_cases_covidgr_html_content)): regex = r'(\\n)|\\s' all_cases_data = re.sub( regex, '',","response_sum = requests.put( self.api_sum_url, headers=headers, data=sum_data) return [response.json(), response_sum.json()] if __name__ == '__main__':","call_api_put_data(self, today, covid_data, summary_data): headers = { 'Content-type': 'application/json', } data = json.dumps(","headers=headers, data=data) return response_tests.json() def call_api_put_data(self, today, covid_data, summary_data): headers = { 'Content-type':","soup_test_page = self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data and self.covid_data: post_daily_and_sum_covid_data =","requests.put( self.api_sum_url, headers=headers, data=sum_data) return [response.json(), response_sum.json()] if __name__ == '__main__': cs =","scrape_data(self): data = [] self.today = str(date.today()) soup = self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests()","= html_content[1] date_test = html_content[3].text if country_code.text == 'GRC': today_tests = html_content[10].text total_tests","return response_tests.json() def call_api_put_data(self, today, covid_data, summary_data): headers = { 'Content-type': 'application/json', }","def scrape_page_content(self): page = requests.get(self.scrape_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def scrape_page_content_contains_tests(self):","'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv'","'', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data = summary_data def get_tests_per_day(self, tree): html_content = tree.find('tr', id='LC34').find_all('td')","page = requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def get_daily_data(self, soup): covid_data","data=data) response_sum = requests.put( self.api_sum_url, headers=headers, data=sum_data) return [response.json(), response_sum.json()] if __name__ ==","for item in range(len(all_cases_covidgr_html_content)): regex = r'(\\n)|\\s' all_cases_data = re.sub( regex, '', all_cases_covidgr_html_content[item].text)","= 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = '' self.covid_data =","BeautifulSoup from datetime import date from lxml import html import requests import re","response = requests.post(self.api_url, headers=headers, data=data) response_sum = requests.put( self.api_sum_url, headers=headers, data=sum_data) return [response.json(),","'html.parser') return soup def get_daily_data(self, soup): covid_data = [] daily_covidgr_html_content = soup.find('li', class_='news_li')","for elem in get_daily_covidgr_text.split(): regex = '\\d*(.|)\\d+' match = re.findall(regex, elem) if match:","return [date_test, today_tests] def call_api_post_tested_covid_data(self, today, tests): headers = { 'Content-type': 'application/json', }","from bs4 import BeautifulSoup from datetime import date from lxml import html import","= requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def get_daily_data(self, soup): covid_data =","get_daily_data(self, soup): covid_data = [] daily_covidgr_html_content = soup.find('li', class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text for","id='LC34').find_all('td') country_code = html_content[1] date_test = html_content[3].text if country_code.text == 'GRC': today_tests =","= { 'Content-type': 'application/json', } data = json.dumps({\"date\": today, \"daily_test\": tests}) response_tests =","def scrape_data(self): data = [] self.today = str(date.today()) soup = self.scrape_page_content() soup_test_page =","= requests.post(self.api_url, headers=headers, data=data) response_sum = requests.put( self.api_sum_url, headers=headers, data=sum_data) return [response.json(), response_sum.json()]","= 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = '' self.covid_data = [] self.summary_data= [] def scrape_data(self): data","data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data = self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0], tests_data[1])","sum_data = json.dumps( {\"sum_cases\": summary_data[0], \"sum_deaths\": summary_data[1], \"sum_recovered\": summary_data[2]}) response = requests.post(self.api_url, headers=headers,","summary_data def get_tests_per_day(self, tree): html_content = tree.find('tr', id='LC34').find_all('td') country_code = html_content[1] date_test ="],"string":"[\n \"data=sum_data) return [response.json(), response_sum.json()] if __name__ == '__main__': cs = CovidScraper() results =\",\n \"BeautifulSoup(page.content, 'html.parser') return soup def scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content, 'html.parser')\",\n \"self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data and self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data( self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data)\",\n \"soup def get_daily_data(self, soup): covid_data = [] daily_covidgr_html_content = soup.find('li', class_='news_li') get_daily_covidgr_text =\",\n \"self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data and self.covid_data: post_daily_and_sum_covid_data\",\n \"= self.call_api_put_data( self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data = self.get_tests_per_day(soup_test_page) if tests_data[0]:\",\n \"self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data = self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0],\",\n \"= BeautifulSoup(page.content, 'html.parser') return soup def scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content,\",\n \"regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data = summary_data def get_tests_per_day(self, tree): html_content = tree.find('tr',\",\n \"self.summary_data= [] def scrape_data(self): data = [] self.today = str(date.today()) soup = self.scrape_page_content()\",\n \"self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data = self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data(\",\n \"def __init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url =\",\n \"soup = BeautifulSoup(page.content, 'html.parser') return soup def scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url) soup =\",\n \"return [response.json(), response_sum.json()] if __name__ == '__main__': cs = CovidScraper() results = cs.scrape_data()\",\n \"get_daily_covidgr_text = daily_covidgr_html_content.text for elem in get_daily_covidgr_text.split(): regex = '\\\\d*(.|)\\\\d+' match = re.findall(regex,\",\n \"re.findall(regex, elem) if match: covid_data.append(elem) self.covid_data = covid_data def get_summary_data(self, soup): summary_data =\",\n \"html_content[3].text if country_code.text == 'GRC': today_tests = html_content[10].text total_tests = html_content[8].text return [date_test,\",\n \"= json.dumps( {\\\"date\\\": today, \\\"cases\\\": covid_data[0], \\\"deaths\\\": covid_data[1]}) sum_data = json.dumps( {\\\"sum_cases\\\": summary_data[0],\",\n \"[] self.summary_data= [] def scrape_data(self): data = [] self.today = str(date.today()) soup =\",\n \"response_tests.json() def call_api_put_data(self, today, covid_data, summary_data): headers = { 'Content-type': 'application/json', } data\",\n \"total_tests = html_content[8].text return [date_test, today_tests] def call_api_post_tested_covid_data(self, today, tests): headers = {\",\n \"html_content = tree.find('tr', id='LC34').find_all('td') country_code = html_content[1] date_test = html_content[3].text if country_code.text ==\",\n \"today, \\\"daily_test\\\": tests}) response_tests = requests.post( self.api_test_url, headers=headers, data=data) return response_tests.json() def call_api_put_data(self,\",\n \"tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return data def scrape_page_content(self): page =\",\n \"def get_tests_per_day(self, tree): html_content = tree.find('tr', id='LC34').find_all('td') country_code = html_content[1] date_test = html_content[3].text\",\n \"\\\"cases\\\": covid_data[0], \\\"deaths\\\": covid_data[1]}) sum_data = json.dumps( {\\\"sum_cases\\\": summary_data[0], \\\"sum_deaths\\\": summary_data[1], \\\"sum_recovered\\\": summary_data[2]})\",\n \"today, \\\"cases\\\": covid_data[0], \\\"deaths\\\": covid_data[1]}) sum_data = json.dumps( {\\\"sum_cases\\\": summary_data[0], \\\"sum_deaths\\\": summary_data[1], \\\"sum_recovered\\\":\",\n \"import requests import re import json class CovidScraper: def __init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr'\",\n \"if soup_test_page: tests_data = self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data)\",\n \"self.today = '' self.covid_data = [] self.summary_data= [] def scrape_data(self): data = []\",\n \"def call_api_post_tested_covid_data(self, today, tests): headers = { 'Content-type': 'application/json', } data = json.dumps({\\\"date\\\":\",\n \"post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return data def scrape_page_content(self): page = requests.get(self.scrape_url)\",\n \"CovidScraper: def __init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url\",\n \"data.append(post_daily_tests_covid_data) return data def scrape_page_content(self): page = requests.get(self.scrape_url) soup = BeautifulSoup(page.content, 'html.parser') return\",\n \"'GRC': today_tests = html_content[10].text total_tests = html_content[8].text return [date_test, today_tests] def call_api_post_tested_covid_data(self, today,\",\n \"\\\"sum_deaths\\\": summary_data[1], \\\"sum_recovered\\\": summary_data[2]}) response = requests.post(self.api_url, headers=headers, data=data) response_sum = requests.put( self.api_sum_url,\",\n \"soup): summary_data = [] all_cases_covidgr_html_content = soup.find_all( 'div', class_='maincounter-number') for item in range(len(all_cases_covidgr_html_content)):\",\n \"html import requests import re import json class CovidScraper: def __init__(self): self.api_url =\",\n \"return soup def get_daily_data(self, soup): covid_data = [] daily_covidgr_html_content = soup.find('li', class_='news_li') get_daily_covidgr_text\",\n \"match: covid_data.append(elem) self.covid_data = covid_data def get_summary_data(self, soup): summary_data = [] all_cases_covidgr_html_content =\",\n \"'html.parser') return soup def scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content, 'html.parser') return\",\n \"json class CovidScraper: def __init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url =\",\n \"get_daily_covidgr_text.split(): regex = '\\\\d*(.|)\\\\d+' match = re.findall(regex, elem) if match: covid_data.append(elem) self.covid_data =\",\n \"self.covid_data = [] self.summary_data= [] def scrape_data(self): data = [] self.today = str(date.today())\",\n \"soup.find('li', class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text for elem in get_daily_covidgr_text.split(): regex = '\\\\d*(.|)\\\\d+' match\",\n \"self.summary_data and self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data( self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data\",\n \"import json class CovidScraper: def __init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url\",\n \"= requests.get(self.scrape_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url)\",\n \"today_tests = html_content[10].text total_tests = html_content[8].text return [date_test, today_tests] def call_api_post_tested_covid_data(self, today, tests):\",\n \"summary_data[2]}) response = requests.post(self.api_url, headers=headers, data=data) response_sum = requests.put( self.api_sum_url, headers=headers, data=sum_data) return\",\n \"soup: self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data and self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data( self.today, self.covid_data, self.summary_data)\",\n \"'' self.covid_data = [] self.summary_data= [] def scrape_data(self): data = [] self.today =\",\n \"= requests.put( self.api_sum_url, headers=headers, data=sum_data) return [response.json(), response_sum.json()] if __name__ == '__main__': cs\",\n \"[] def scrape_data(self): data = [] self.today = str(date.today()) soup = self.scrape_page_content() soup_test_page\",\n \"= str(date.today()) soup = self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup) self.get_summary_data(soup) if\",\n \"} data = json.dumps( {\\\"date\\\": today, \\\"cases\\\": covid_data[0], \\\"deaths\\\": covid_data[1]}) sum_data = json.dumps(\",\n \"lxml import html import requests import re import json class CovidScraper: def __init__(self):\",\n \"= tree.find('tr', id='LC34').find_all('td') country_code = html_content[1] date_test = html_content[3].text if country_code.text == 'GRC':\",\n \"regex = r'(\\\\n)|\\\\s' all_cases_data = re.sub( regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data = summary_data\",\n \"daily_covidgr_html_content = soup.find('li', class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text for elem in get_daily_covidgr_text.split(): regex =\",\n \"today_tests] def call_api_post_tested_covid_data(self, today, tests): headers = { 'Content-type': 'application/json', } data =\",\n \"= re.findall(regex, elem) if match: covid_data.append(elem) self.covid_data = covid_data def get_summary_data(self, soup): summary_data\",\n \"= summary_data def get_tests_per_day(self, tree): html_content = tree.find('tr', id='LC34').find_all('td') country_code = html_content[1] date_test\",\n \"date from lxml import html import requests import re import json class CovidScraper:\",\n \"import date from lxml import html import requests import re import json class\",\n \"import BeautifulSoup from datetime import date from lxml import html import requests import\",\n \"= json.dumps({\\\"date\\\": today, \\\"daily_test\\\": tests}) response_tests = requests.post( self.api_test_url, headers=headers, data=data) return response_tests.json()\",\n \"self.covid_data = covid_data def get_summary_data(self, soup): summary_data = [] all_cases_covidgr_html_content = soup.find_all( 'div',\",\n \"self.get_summary_data(soup) if self.summary_data and self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data( self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if\",\n \"covid_data.append(elem) self.covid_data = covid_data def get_summary_data(self, soup): summary_data = [] all_cases_covidgr_html_content = soup.find_all(\",\n \"if match: covid_data.append(elem) self.covid_data = covid_data def get_summary_data(self, soup): summary_data = [] all_cases_covidgr_html_content\",\n \"summary_data[0], \\\"sum_deaths\\\": summary_data[1], \\\"sum_recovered\\\": summary_data[2]}) response = requests.post(self.api_url, headers=headers, data=data) response_sum = requests.put(\",\n \"data def scrape_page_content(self): page = requests.get(self.scrape_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def\",\n \"self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url\",\n \"headers = { 'Content-type': 'application/json', } data = json.dumps({\\\"date\\\": today, \\\"daily_test\\\": tests}) response_tests\",\n \"self.call_api_put_data( self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data = self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data\",\n \"soup_test_page: tests_data = self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return\",\n \"if soup: self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data and self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data( self.today, self.covid_data,\",\n \"re import json class CovidScraper: def __init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr'\",\n \"self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = '' self.covid_data = [] self.summary_data= [] def scrape_data(self):\",\n \"def scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def get_daily_data(self,\",\n \"self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return data def scrape_page_content(self):\",\n \"def get_daily_data(self, soup): covid_data = [] daily_covidgr_html_content = soup.find('li', class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text\",\n \"data = json.dumps({\\\"date\\\": today, \\\"daily_test\\\": tests}) response_tests = requests.post( self.api_test_url, headers=headers, data=data) return\",\n \"[] self.today = str(date.today()) soup = self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup)\",\n \"and self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data( self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data =\",\n \"= 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today =\",\n \"return soup def scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content, 'html.parser') return soup\",\n \"get_summary_data(self, soup): summary_data = [] all_cases_covidgr_html_content = soup.find_all( 'div', class_='maincounter-number') for item in\",\n \"summary_data): headers = { 'Content-type': 'application/json', } data = json.dumps( {\\\"date\\\": today, \\\"cases\\\":\",\n \"datetime import date from lxml import html import requests import re import json\",\n \"'div', class_='maincounter-number') for item in range(len(all_cases_covidgr_html_content)): regex = r'(\\\\n)|\\\\s' all_cases_data = re.sub( regex,\",\n \"daily_covidgr_html_content.text for elem in get_daily_covidgr_text.split(): regex = '\\\\d*(.|)\\\\d+' match = re.findall(regex, elem) if\",\n \"requests import re import json class CovidScraper: def __init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url\",\n \"json.dumps({\\\"date\\\": today, \\\"daily_test\\\": tests}) response_tests = requests.post( self.api_test_url, headers=headers, data=data) return response_tests.json() def\",\n \"'application/json', } data = json.dumps( {\\\"date\\\": today, \\\"cases\\\": covid_data[0], \\\"deaths\\\": covid_data[1]}) sum_data =\",\n \"if self.summary_data and self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data( self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page:\",\n \"{\\\"date\\\": today, \\\"cases\\\": covid_data[0], \\\"deaths\\\": covid_data[1]}) sum_data = json.dumps( {\\\"sum_cases\\\": summary_data[0], \\\"sum_deaths\\\": summary_data[1],\",\n \"= self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data and self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data(\",\n \"= '\\\\d*(.|)\\\\d+' match = re.findall(regex, elem) if match: covid_data.append(elem) self.covid_data = covid_data def\",\n \"'\\\\d*(.|)\\\\d+' match = re.findall(regex, elem) if match: covid_data.append(elem) self.covid_data = covid_data def get_summary_data(self,\",\n \"def call_api_put_data(self, today, covid_data, summary_data): headers = { 'Content-type': 'application/json', } data =\",\n \"BeautifulSoup(page.content, 'html.parser') return soup def get_daily_data(self, soup): covid_data = [] daily_covidgr_html_content = soup.find('li',\",\n \"= daily_covidgr_html_content.text for elem in get_daily_covidgr_text.split(): regex = '\\\\d*(.|)\\\\d+' match = re.findall(regex, elem)\",\n \"'Content-type': 'application/json', } data = json.dumps({\\\"date\\\": today, \\\"daily_test\\\": tests}) response_tests = requests.post( self.api_test_url,\",\n \"self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data and self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data( self.today,\",\n \"{\\\"sum_cases\\\": summary_data[0], \\\"sum_deaths\\\": summary_data[1], \\\"sum_recovered\\\": summary_data[2]}) response = requests.post(self.api_url, headers=headers, data=data) response_sum =\",\n \"page = requests.get(self.scrape_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def scrape_page_content_contains_tests(self): page =\",\n \"json.dumps( {\\\"sum_cases\\\": summary_data[0], \\\"sum_deaths\\\": summary_data[1], \\\"sum_recovered\\\": summary_data[2]}) response = requests.post(self.api_url, headers=headers, data=data) response_sum\",\n \"html_content[1] date_test = html_content[3].text if country_code.text == 'GRC': today_tests = html_content[10].text total_tests =\",\n \"tree.find('tr', id='LC34').find_all('td') country_code = html_content[1] date_test = html_content[3].text if country_code.text == 'GRC': today_tests\",\n \"def get_summary_data(self, soup): summary_data = [] all_cases_covidgr_html_content = soup.find_all( 'div', class_='maincounter-number') for item\",\n \"soup): covid_data = [] daily_covidgr_html_content = soup.find('li', class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text for elem\",\n \"\\\"sum_recovered\\\": summary_data[2]}) response = requests.post(self.api_url, headers=headers, data=data) response_sum = requests.put( self.api_sum_url, headers=headers, data=sum_data)\",\n \"'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = '' self.covid_data = []\",\n \"= re.sub( regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data = summary_data def get_tests_per_day(self, tree): html_content\",\n \"[] daily_covidgr_html_content = soup.find('li', class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text for elem in get_daily_covidgr_text.split(): regex\",\n \"[] all_cases_covidgr_html_content = soup.find_all( 'div', class_='maincounter-number') for item in range(len(all_cases_covidgr_html_content)): regex = r'(\\\\n)|\\\\s'\",\n \"re.sub( regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data = summary_data def get_tests_per_day(self, tree): html_content =\",\n \"post_daily_and_sum_covid_data = self.call_api_put_data( self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data = self.get_tests_per_day(soup_test_page) if\",\n \"data = json.dumps( {\\\"date\\\": today, \\\"cases\\\": covid_data[0], \\\"deaths\\\": covid_data[1]}) sum_data = json.dumps( {\\\"sum_cases\\\":\",\n \"headers=headers, data=sum_data) return [response.json(), response_sum.json()] if __name__ == '__main__': cs = CovidScraper() results\",\n \"country_code.text == 'GRC': today_tests = html_content[10].text total_tests = html_content[8].text return [date_test, today_tests] def\",\n \"summary_data.append(all_cases_data) self.summary_data = summary_data def get_tests_per_day(self, tree): html_content = tree.find('tr', id='LC34').find_all('td') country_code =\",\n \"tests_data[1]) data.append(post_daily_tests_covid_data) return data def scrape_page_content(self): page = requests.get(self.scrape_url) soup = BeautifulSoup(page.content, 'html.parser')\",\n \"= [] self.summary_data= [] def scrape_data(self): data = [] self.today = str(date.today()) soup\",\n \"= html_content[8].text return [date_test, today_tests] def call_api_post_tested_covid_data(self, today, tests): headers = { 'Content-type':\",\n \"requests.post( self.api_test_url, headers=headers, data=data) return response_tests.json() def call_api_put_data(self, today, covid_data, summary_data): headers =\",\n \"'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = '' self.covid_data = [] self.summary_data= [] def scrape_data(self): data =\",\n \"call_api_post_tested_covid_data(self, today, tests): headers = { 'Content-type': 'application/json', } data = json.dumps({\\\"date\\\": today,\",\n \"= { 'Content-type': 'application/json', } data = json.dumps( {\\\"date\\\": today, \\\"cases\\\": covid_data[0], \\\"deaths\\\":\",\n \"} data = json.dumps({\\\"date\\\": today, \\\"daily_test\\\": tests}) response_tests = requests.post( self.api_test_url, headers=headers, data=data)\",\n \"= '' self.covid_data = [] self.summary_data= [] def scrape_data(self): data = [] self.today\",\n \"= r'(\\\\n)|\\\\s' all_cases_data = re.sub( regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data = summary_data def\",\n \"bs4 import BeautifulSoup from datetime import date from lxml import html import requests\",\n \"soup.find_all( 'div', class_='maincounter-number') for item in range(len(all_cases_covidgr_html_content)): regex = r'(\\\\n)|\\\\s' all_cases_data = re.sub(\",\n \"\\\"deaths\\\": covid_data[1]}) sum_data = json.dumps( {\\\"sum_cases\\\": summary_data[0], \\\"sum_deaths\\\": summary_data[1], \\\"sum_recovered\\\": summary_data[2]}) response =\",\n \"tree): html_content = tree.find('tr', id='LC34').find_all('td') country_code = html_content[1] date_test = html_content[3].text if country_code.text\",\n \"= soup.find('li', class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text for elem in get_daily_covidgr_text.split(): regex = '\\\\d*(.|)\\\\d+'\",\n \"html_content[10].text total_tests = html_content[8].text return [date_test, today_tests] def call_api_post_tested_covid_data(self, today, tests): headers =\",\n \"self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today\",\n \"from lxml import html import requests import re import json class CovidScraper: def\",\n \"= 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = '' self.covid_data = [] self.summary_data= []\",\n \"in range(len(all_cases_covidgr_html_content)): regex = r'(\\\\n)|\\\\s' all_cases_data = re.sub( regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data\",\n \"== 'GRC': today_tests = html_content[10].text total_tests = html_content[8].text return [date_test, today_tests] def call_api_post_tested_covid_data(self,\",\n \"tests_data = self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return data\",\n \"requests.post(self.api_url, headers=headers, data=data) response_sum = requests.put( self.api_sum_url, headers=headers, data=sum_data) return [response.json(), response_sum.json()] if\",\n \"[response.json(), response_sum.json()] if __name__ == '__main__': cs = CovidScraper() results = cs.scrape_data() print(results)\",\n \"tests}) response_tests = requests.post( self.api_test_url, headers=headers, data=data) return response_tests.json() def call_api_put_data(self, today, covid_data,\",\n \"scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def get_daily_data(self, soup):\",\n \"covid_data = [] daily_covidgr_html_content = soup.find('li', class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text for elem in\",\n \"data = [] self.today = str(date.today()) soup = self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests() if\",\n \"all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data = summary_data def get_tests_per_day(self, tree): html_content = tree.find('tr', id='LC34').find_all('td') country_code\",\n \"today, covid_data, summary_data): headers = { 'Content-type': 'application/json', } data = json.dumps( {\\\"date\\\":\",\n \"= requests.post( self.api_test_url, headers=headers, data=data) return response_tests.json() def call_api_put_data(self, today, covid_data, summary_data): headers\",\n \"covid_data, summary_data): headers = { 'Content-type': 'application/json', } data = json.dumps( {\\\"date\\\": today,\",\n \"range(len(all_cases_covidgr_html_content)): regex = r'(\\\\n)|\\\\s' all_cases_data = re.sub( regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data =\",\n \"class CovidScraper: def __init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests'\",\n \"covid_data[0], \\\"deaths\\\": covid_data[1]}) sum_data = json.dumps( {\\\"sum_cases\\\": summary_data[0], \\\"sum_deaths\\\": summary_data[1], \\\"sum_recovered\\\": summary_data[2]}) response\",\n \"__init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/'\",\n \"'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = '' self.covid_data = [] self.summary_data= [] def\",\n \"= html_content[10].text total_tests = html_content[8].text return [date_test, today_tests] def call_api_post_tested_covid_data(self, today, tests): headers\",\n \"self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = '' self.covid_data\",\n \"json.dumps( {\\\"date\\\": today, \\\"cases\\\": covid_data[0], \\\"deaths\\\": covid_data[1]}) sum_data = json.dumps( {\\\"sum_cases\\\": summary_data[0], \\\"sum_deaths\\\":\",\n \"= covid_data def get_summary_data(self, soup): summary_data = [] all_cases_covidgr_html_content = soup.find_all( 'div', class_='maincounter-number')\",\n \"response_tests = requests.post( self.api_test_url, headers=headers, data=data) return response_tests.json() def call_api_put_data(self, today, covid_data, summary_data):\",\n \"import re import json class CovidScraper: def __init__(self): self.api_url = 'http://127.0.0.1:5000/covidgr' self.api_sum_url =\",\n \"data=data) return response_tests.json() def call_api_put_data(self, today, covid_data, summary_data): headers = { 'Content-type': 'application/json',\",\n \"self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = '' self.covid_data = [] self.summary_data=\",\n \"today, tests): headers = { 'Content-type': 'application/json', } data = json.dumps({\\\"date\\\": today, \\\"daily_test\\\":\",\n \"all_cases_data = re.sub( regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data = summary_data def get_tests_per_day(self, tree):\",\n \"{ 'Content-type': 'application/json', } data = json.dumps( {\\\"date\\\": today, \\\"cases\\\": covid_data[0], \\\"deaths\\\": covid_data[1]})\",\n \"in get_daily_covidgr_text.split(): regex = '\\\\d*(.|)\\\\d+' match = re.findall(regex, elem) if match: covid_data.append(elem) self.covid_data\",\n \"= BeautifulSoup(page.content, 'html.parser') return soup def get_daily_data(self, soup): covid_data = [] daily_covidgr_html_content =\",\n \"self.api_sum_url, headers=headers, data=sum_data) return [response.json(), response_sum.json()] if __name__ == '__main__': cs = CovidScraper()\",\n \"self.today = str(date.today()) soup = self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup) self.get_summary_data(soup)\",\n \"tests): headers = { 'Content-type': 'application/json', } data = json.dumps({\\\"date\\\": today, \\\"daily_test\\\": tests})\",\n \"= self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data and self.covid_data:\",\n \"if tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return data def scrape_page_content(self): page\",\n \"self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return data def scrape_page_content(self): page = requests.get(self.scrape_url) soup =\",\n \"str(date.today()) soup = self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data\",\n \"elem in get_daily_covidgr_text.split(): regex = '\\\\d*(.|)\\\\d+' match = re.findall(regex, elem) if match: covid_data.append(elem)\",\n \"covid_data def get_summary_data(self, soup): summary_data = [] all_cases_covidgr_html_content = soup.find_all( 'div', class_='maincounter-number') for\",\n \"[date_test, today_tests] def call_api_post_tested_covid_data(self, today, tests): headers = { 'Content-type': 'application/json', } data\",\n \"tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return data def scrape_page_content(self): page = requests.get(self.scrape_url) soup = BeautifulSoup(page.content,\",\n \"r'(\\\\n)|\\\\s' all_cases_data = re.sub( regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data = summary_data def get_tests_per_day(self,\",\n \"from datetime import date from lxml import html import requests import re import\",\n \"= self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return data def\",\n \"= soup.find_all( 'div', class_='maincounter-number') for item in range(len(all_cases_covidgr_html_content)): regex = r'(\\\\n)|\\\\s' all_cases_data =\",\n \"= 'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url =\",\n \"'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = ''\",\n \"item in range(len(all_cases_covidgr_html_content)): regex = r'(\\\\n)|\\\\s' all_cases_data = re.sub( regex, '', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data)\",\n \"return data def scrape_page_content(self): page = requests.get(self.scrape_url) soup = BeautifulSoup(page.content, 'html.parser') return soup\",\n \"country_code = html_content[1] date_test = html_content[3].text if country_code.text == 'GRC': today_tests = html_content[10].text\",\n \"if country_code.text == 'GRC': today_tests = html_content[10].text total_tests = html_content[8].text return [date_test, today_tests]\",\n \"headers=headers, data=data) response_sum = requests.put( self.api_sum_url, headers=headers, data=sum_data) return [response.json(), response_sum.json()] if __name__\",\n \"html_content[8].text return [date_test, today_tests] def call_api_post_tested_covid_data(self, today, tests): headers = { 'Content-type': 'application/json',\",\n \"date_test = html_content[3].text if country_code.text == 'GRC': today_tests = html_content[10].text total_tests = html_content[8].text\",\n \"scrape_page_content(self): page = requests.get(self.scrape_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def scrape_page_content_contains_tests(self): page\",\n \"import html import requests import re import json class CovidScraper: def __init__(self): self.api_url\",\n \"summary_data = [] all_cases_covidgr_html_content = soup.find_all( 'div', class_='maincounter-number') for item in range(len(all_cases_covidgr_html_content)): regex\",\n \"self.api_test_url, headers=headers, data=data) return response_tests.json() def call_api_put_data(self, today, covid_data, summary_data): headers = {\",\n \"self.covid_data: post_daily_and_sum_covid_data = self.call_api_put_data( self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data = self.get_tests_per_day(soup_test_page)\",\n \"soup = BeautifulSoup(page.content, 'html.parser') return soup def get_daily_data(self, soup): covid_data = [] daily_covidgr_html_content\",\n \"requests.get(self.scrape_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url) soup\",\n \"= self.call_api_post_tested_covid_data( tests_data[0], tests_data[1]) data.append(post_daily_tests_covid_data) return data def scrape_page_content(self): page = requests.get(self.scrape_url) soup\",\n \"elem) if match: covid_data.append(elem) self.covid_data = covid_data def get_summary_data(self, soup): summary_data = []\",\n \"all_cases_covidgr_html_content = soup.find_all( 'div', class_='maincounter-number') for item in range(len(all_cases_covidgr_html_content)): regex = r'(\\\\n)|\\\\s' all_cases_data\",\n \"soup = self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data and\",\n \"get_tests_per_day(self, tree): html_content = tree.find('tr', id='LC34').find_all('td') country_code = html_content[1] date_test = html_content[3].text if\",\n \"'Content-type': 'application/json', } data = json.dumps( {\\\"date\\\": today, \\\"cases\\\": covid_data[0], \\\"deaths\\\": covid_data[1]}) sum_data\",\n \"match = re.findall(regex, elem) if match: covid_data.append(elem) self.covid_data = covid_data def get_summary_data(self, soup):\",\n \"= [] all_cases_covidgr_html_content = soup.find_all( 'div', class_='maincounter-number') for item in range(len(all_cases_covidgr_html_content)): regex =\",\n \"headers = { 'Content-type': 'application/json', } data = json.dumps( {\\\"date\\\": today, \\\"cases\\\": covid_data[0],\",\n \"self.today, self.covid_data, self.summary_data) data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data = self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data =\",\n \"{ 'Content-type': 'application/json', } data = json.dumps({\\\"date\\\": today, \\\"daily_test\\\": tests}) response_tests = requests.post(\",\n \"'application/json', } data = json.dumps({\\\"date\\\": today, \\\"daily_test\\\": tests}) response_tests = requests.post( self.api_test_url, headers=headers,\",\n \"= json.dumps( {\\\"sum_cases\\\": summary_data[0], \\\"sum_deaths\\\": summary_data[1], \\\"sum_recovered\\\": summary_data[2]}) response = requests.post(self.api_url, headers=headers, data=data)\",\n \"regex = '\\\\d*(.|)\\\\d+' match = re.findall(regex, elem) if match: covid_data.append(elem) self.covid_data = covid_data\",\n \"self.summary_data = summary_data def get_tests_per_day(self, tree): html_content = tree.find('tr', id='LC34').find_all('td') country_code = html_content[1]\",\n \"= html_content[3].text if country_code.text == 'GRC': today_tests = html_content[10].text total_tests = html_content[8].text return\",\n \"= [] self.today = str(date.today()) soup = self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests() if soup:\",\n \"= [] daily_covidgr_html_content = soup.find('li', class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text for elem in get_daily_covidgr_text.split():\",\n \"covid_data[1]}) sum_data = json.dumps( {\\\"sum_cases\\\": summary_data[0], \\\"sum_deaths\\\": summary_data[1], \\\"sum_recovered\\\": summary_data[2]}) response = requests.post(self.api_url,\",\n \"summary_data[1], \\\"sum_recovered\\\": summary_data[2]}) response = requests.post(self.api_url, headers=headers, data=data) response_sum = requests.put( self.api_sum_url, headers=headers,\",\n \"class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text for elem in get_daily_covidgr_text.split(): regex = '\\\\d*(.|)\\\\d+' match =\",\n \"\\\"daily_test\\\": tests}) response_tests = requests.post( self.api_test_url, headers=headers, data=data) return response_tests.json() def call_api_put_data(self, today,\",\n \"requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def get_daily_data(self, soup): covid_data = []\",\n \"soup def scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def\",\n \"class_='maincounter-number') for item in range(len(all_cases_covidgr_html_content)): regex = r'(\\\\n)|\\\\s' all_cases_data = re.sub( regex, '',\",\n \"response_sum = requests.put( self.api_sum_url, headers=headers, data=sum_data) return [response.json(), response_sum.json()] if __name__ == '__main__':\",\n \"call_api_put_data(self, today, covid_data, summary_data): headers = { 'Content-type': 'application/json', } data = json.dumps(\",\n \"headers=headers, data=data) return response_tests.json() def call_api_put_data(self, today, covid_data, summary_data): headers = { 'Content-type':\",\n \"soup_test_page = self.scrape_page_content_contains_tests() if soup: self.get_daily_data(soup) self.get_summary_data(soup) if self.summary_data and self.covid_data: post_daily_and_sum_covid_data =\",\n \"requests.put( self.api_sum_url, headers=headers, data=sum_data) return [response.json(), response_sum.json()] if __name__ == '__main__': cs =\",\n \"scrape_data(self): data = [] self.today = str(date.today()) soup = self.scrape_page_content() soup_test_page = self.scrape_page_content_contains_tests()\",\n \"= html_content[1] date_test = html_content[3].text if country_code.text == 'GRC': today_tests = html_content[10].text total_tests\",\n \"return response_tests.json() def call_api_put_data(self, today, covid_data, summary_data): headers = { 'Content-type': 'application/json', }\",\n \"def scrape_page_content(self): page = requests.get(self.scrape_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def scrape_page_content_contains_tests(self):\",\n \"'http://127.0.0.1:5000/covidgr' self.api_sum_url = 'http://127.0.0.1:5000/summary/covidgr' self.api_test_url = 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv'\",\n \"'', all_cases_covidgr_html_content[item].text) summary_data.append(all_cases_data) self.summary_data = summary_data def get_tests_per_day(self, tree): html_content = tree.find('tr', id='LC34').find_all('td')\",\n \"page = requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def get_daily_data(self, soup): covid_data\",\n \"data=data) response_sum = requests.put( self.api_sum_url, headers=headers, data=sum_data) return [response.json(), response_sum.json()] if __name__ ==\",\n \"for item in range(len(all_cases_covidgr_html_content)): regex = r'(\\\\n)|\\\\s' all_cases_data = re.sub( regex, '', all_cases_covidgr_html_content[item].text)\",\n \"= 'http://127.0.0.1:5000/covidgr/tests' self.scrape_url = 'https://www.worldometers.info/coronavirus/country/greece/' self.scrape_tests_url = 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = '' self.covid_data =\",\n \"BeautifulSoup from datetime import date from lxml import html import requests import re\",\n \"response = requests.post(self.api_url, headers=headers, data=data) response_sum = requests.put( self.api_sum_url, headers=headers, data=sum_data) return [response.json(),\",\n \"'html.parser') return soup def get_daily_data(self, soup): covid_data = [] daily_covidgr_html_content = soup.find('li', class_='news_li')\",\n \"for elem in get_daily_covidgr_text.split(): regex = '\\\\d*(.|)\\\\d+' match = re.findall(regex, elem) if match:\",\n \"return [date_test, today_tests] def call_api_post_tested_covid_data(self, today, tests): headers = { 'Content-type': 'application/json', }\",\n \"from bs4 import BeautifulSoup from datetime import date from lxml import html import\",\n \"= requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content, 'html.parser') return soup def get_daily_data(self, soup): covid_data =\",\n \"get_daily_data(self, soup): covid_data = [] daily_covidgr_html_content = soup.find('li', class_='news_li') get_daily_covidgr_text = daily_covidgr_html_content.text for\",\n \"id='LC34').find_all('td') country_code = html_content[1] date_test = html_content[3].text if country_code.text == 'GRC': today_tests =\",\n \"= { 'Content-type': 'application/json', } data = json.dumps({\\\"date\\\": today, \\\"daily_test\\\": tests}) response_tests =\",\n \"def scrape_data(self): data = [] self.today = str(date.today()) soup = self.scrape_page_content() soup_test_page =\",\n \"= requests.post(self.api_url, headers=headers, data=data) response_sum = requests.put( self.api_sum_url, headers=headers, data=sum_data) return [response.json(), response_sum.json()]\",\n \"= 'https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-latest-data-source-details.csv' self.today = '' self.covid_data = [] self.summary_data= [] def scrape_data(self): data\",\n \"data.append(post_daily_and_sum_covid_data) if soup_test_page: tests_data = self.get_tests_per_day(soup_test_page) if tests_data[0]: post_daily_tests_covid_data = self.call_api_post_tested_covid_data( tests_data[0], tests_data[1])\",\n \"sum_data = json.dumps( {\\\"sum_cases\\\": summary_data[0], \\\"sum_deaths\\\": summary_data[1], \\\"sum_recovered\\\": summary_data[2]}) response = requests.post(self.api_url, headers=headers,\",\n \"summary_data def get_tests_per_day(self, tree): html_content = tree.find('tr', id='LC34').find_all('td') country_code = html_content[1] date_test =\"\n]","isConversational":false}}},{"rowIdx":4398,"cells":{"ngram":{"kind":"list like","value":["os from PIL import Image DATEI_WEB_GROSSE = 700 def isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower()","float(img.size[1]) * float(wrel) ) splt = os.path.splitext(datei) newfilename = splt[0] + splt[1].lower() img","float(wrel) ) splt = os.path.splitext(datei) newfilename = splt[0] + splt[1].lower() img = img.resize((DATEI_WEB_GROSSE,","img.save(newfilename, quality=100, optimize=True, progressive=True) if newfilename != datei: os.rename(newfilename, datei) def main(): files","files) for f in files: print f bearbeiten(f) if __name__ == '__main__': main()","from PIL import Image DATEI_WEB_GROSSE = 700 def isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower() if","= DATEI_WEB_GROSSE / float(img.size[0]) habs = int( float(img.size[1]) * float(wrel) ) splt =","files = filter(isimg, files) for f in files: print f bearbeiten(f) if __name__","* float(wrel) ) splt = os.path.splitext(datei) newfilename = splt[0] + splt[1].lower() img =","if newfilename != datei: os.rename(newfilename, datei) def main(): files = os.listdir('.') files =","== \".jpg\" or ext == \".png\" or ext == \".gif\": return True return","os.listdir('.') files = filter(isimg, files) for f in files: print f bearbeiten(f) if","float(img.size[0]) habs = int( float(img.size[1]) * float(wrel) ) splt = os.path.splitext(datei) newfilename =","def main(): files = os.listdir('.') files = filter(isimg, files) for f in files:","\".gif\": return True return False def bearbeiten(datei): img = Image.open(datei) wrel = DATEI_WEB_GROSSE","def bearbeiten(datei): img = Image.open(datei) wrel = DATEI_WEB_GROSSE / float(img.size[0]) habs = int(","ext == \".jpg\" or ext == \".png\" or ext == \".gif\": return True","ext == \".png\" or ext == \".gif\": return True return False def bearbeiten(datei):","splt[1].lower() img = img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True, progressive=True) if newfilename !=","Image DATEI_WEB_GROSSE = 700 def isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower() if ext == \".jpg\"","if ext == \".jpg\" or ext == \".png\" or ext == \".gif\": return","splt = os.path.splitext(datei) newfilename = splt[0] + splt[1].lower() img = img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS)","DATEI_WEB_GROSSE / float(img.size[0]) habs = int( float(img.size[1]) * float(wrel) ) splt = os.path.splitext(datei)","/ float(img.size[0]) habs = int( float(img.size[1]) * float(wrel) ) splt = os.path.splitext(datei) newfilename","= os.path.splitext(isitimg)[1].lower() if ext == \".jpg\" or ext == \".png\" or ext ==",") splt = os.path.splitext(datei) newfilename = splt[0] + splt[1].lower() img = img.resize((DATEI_WEB_GROSSE, habs),","or ext == \".gif\": return True return False def bearbeiten(datei): img = Image.open(datei)","DATEI_WEB_GROSSE = 700 def isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower() if ext == \".jpg\" or","return True return False def bearbeiten(datei): img = Image.open(datei) wrel = DATEI_WEB_GROSSE /","= 700 def isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower() if ext == \".jpg\" or ext","datei) def main(): files = os.listdir('.') files = filter(isimg, files) for f in","os.rename(newfilename, datei) def main(): files = os.listdir('.') files = filter(isimg, files) for f","False def bearbeiten(datei): img = Image.open(datei) wrel = DATEI_WEB_GROSSE / float(img.size[0]) habs =","import Image DATEI_WEB_GROSSE = 700 def isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower() if ext ==","PIL import Image DATEI_WEB_GROSSE = 700 def isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower() if ext","+ splt[1].lower() img = img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True, progressive=True) if newfilename","or ext == \".png\" or ext == \".gif\": return True return False def","= Image.open(datei) wrel = DATEI_WEB_GROSSE / float(img.size[0]) habs = int( float(img.size[1]) * float(wrel)","filter(isimg, files) for f in files: print f bearbeiten(f) if __name__ == '__main__':","img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True, progressive=True) if newfilename != datei: os.rename(newfilename, datei)","ext = os.path.splitext(isitimg)[1].lower() if ext == \".jpg\" or ext == \".png\" or ext","img = Image.open(datei) wrel = DATEI_WEB_GROSSE / float(img.size[0]) habs = int( float(img.size[1]) *","Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True, progressive=True) if newfilename != datei: os.rename(newfilename, datei) def main():","splt[0] + splt[1].lower() img = img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True, progressive=True) if","Image.open(datei) wrel = DATEI_WEB_GROSSE / float(img.size[0]) habs = int( float(img.size[1]) * float(wrel) )","= img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True, progressive=True) if newfilename != datei: os.rename(newfilename,","= int( float(img.size[1]) * float(wrel) ) splt = os.path.splitext(datei) newfilename = splt[0] +","= os.path.splitext(datei) newfilename = splt[0] + splt[1].lower() img = img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename,","main(): files = os.listdir('.') files = filter(isimg, files) for f in files: print","newfilename != datei: os.rename(newfilename, datei) def main(): files = os.listdir('.') files = filter(isimg,","= os.listdir('.') files = filter(isimg, files) for f in files: print f bearbeiten(f)","optimize=True, progressive=True) if newfilename != datei: os.rename(newfilename, datei) def main(): files = os.listdir('.')","\".jpg\" or ext == \".png\" or ext == \".gif\": return True return False","os.path.splitext(isitimg)[1].lower() if ext == \".jpg\" or ext == \".png\" or ext == \".gif\":","quality=100, optimize=True, progressive=True) if newfilename != datei: os.rename(newfilename, datei) def main(): files =","!= datei: os.rename(newfilename, datei) def main(): files = os.listdir('.') files = filter(isimg, files)","isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower() if ext == \".jpg\" or ext == \".png\" or","700 def isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower() if ext == \".jpg\" or ext ==","img = img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True, progressive=True) if newfilename != datei:","= splt[0] + splt[1].lower() img = img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True, progressive=True)","ext == \".gif\": return True return False def bearbeiten(datei): img = Image.open(datei) wrel","os.path.splitext(datei) newfilename = splt[0] + splt[1].lower() img = img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename, quality=100,","datei: os.rename(newfilename, datei) def main(): files = os.listdir('.') files = filter(isimg, files) for","import os from PIL import Image DATEI_WEB_GROSSE = 700 def isimg(isitimg): ext =","= filter(isimg, files) for f in files: print f bearbeiten(f) if __name__ ==","int( float(img.size[1]) * float(wrel) ) splt = os.path.splitext(datei) newfilename = splt[0] + splt[1].lower()","#!/usr/bin/python2.7 import os from PIL import Image DATEI_WEB_GROSSE = 700 def isimg(isitimg): ext","True return False def bearbeiten(datei): img = Image.open(datei) wrel = DATEI_WEB_GROSSE / float(img.size[0])","habs), Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True, progressive=True) if newfilename != datei: os.rename(newfilename, datei) def","progressive=True) if newfilename != datei: os.rename(newfilename, datei) def main(): files = os.listdir('.') files","files = os.listdir('.') files = filter(isimg, files) for f in files: print f","newfilename = splt[0] + splt[1].lower() img = img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True,","habs = int( float(img.size[1]) * float(wrel) ) splt = os.path.splitext(datei) newfilename = splt[0]","\".png\" or ext == \".gif\": return True return False def bearbeiten(datei): img =","== \".gif\": return True return False def bearbeiten(datei): img = Image.open(datei) wrel =","bearbeiten(datei): img = Image.open(datei) wrel = DATEI_WEB_GROSSE / float(img.size[0]) habs = int( float(img.size[1])","def isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower() if ext == \".jpg\" or ext == \".png\"","== \".png\" or ext == \".gif\": return True return False def bearbeiten(datei): img","return False def bearbeiten(datei): img = Image.open(datei) wrel = DATEI_WEB_GROSSE / float(img.size[0]) habs","wrel = DATEI_WEB_GROSSE / float(img.size[0]) habs = int( float(img.size[1]) * float(wrel) ) splt"],"string":"[\n \"os from PIL import Image DATEI_WEB_GROSSE = 700 def isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower()\",\n \"float(img.size[1]) * float(wrel) ) splt = os.path.splitext(datei) newfilename = splt[0] + splt[1].lower() img\",\n \"float(wrel) ) splt = os.path.splitext(datei) newfilename = splt[0] + splt[1].lower() img = img.resize((DATEI_WEB_GROSSE,\",\n \"img.save(newfilename, quality=100, optimize=True, progressive=True) if newfilename != datei: os.rename(newfilename, datei) def main(): files\",\n \"files) for f in files: print f bearbeiten(f) if __name__ == '__main__': main()\",\n \"from PIL import Image DATEI_WEB_GROSSE = 700 def isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower() if\",\n \"= DATEI_WEB_GROSSE / float(img.size[0]) habs = int( float(img.size[1]) * float(wrel) ) splt =\",\n \"files = filter(isimg, files) for f in files: print f bearbeiten(f) if __name__\",\n \"* float(wrel) ) splt = os.path.splitext(datei) newfilename = splt[0] + splt[1].lower() img =\",\n \"if newfilename != datei: os.rename(newfilename, datei) def main(): files = os.listdir('.') files =\",\n \"== \\\".jpg\\\" or ext == \\\".png\\\" or ext == \\\".gif\\\": return True return\",\n \"os.listdir('.') files = filter(isimg, files) for f in files: print f bearbeiten(f) if\",\n \"float(img.size[0]) habs = int( float(img.size[1]) * float(wrel) ) splt = os.path.splitext(datei) newfilename =\",\n \"def main(): files = os.listdir('.') files = filter(isimg, files) for f in files:\",\n \"\\\".gif\\\": return True return False def bearbeiten(datei): img = Image.open(datei) wrel = DATEI_WEB_GROSSE\",\n \"def bearbeiten(datei): img = Image.open(datei) wrel = DATEI_WEB_GROSSE / float(img.size[0]) habs = int(\",\n \"ext == \\\".jpg\\\" or ext == \\\".png\\\" or ext == \\\".gif\\\": return True\",\n \"ext == \\\".png\\\" or ext == \\\".gif\\\": return True return False def bearbeiten(datei):\",\n \"splt[1].lower() img = img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True, progressive=True) if newfilename !=\",\n \"Image DATEI_WEB_GROSSE = 700 def isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower() if ext == \\\".jpg\\\"\",\n \"if ext == \\\".jpg\\\" or ext == \\\".png\\\" or ext == \\\".gif\\\": return\",\n \"splt = os.path.splitext(datei) newfilename = splt[0] + splt[1].lower() img = img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS)\",\n \"DATEI_WEB_GROSSE / float(img.size[0]) habs = int( float(img.size[1]) * float(wrel) ) splt = os.path.splitext(datei)\",\n \"/ float(img.size[0]) habs = int( float(img.size[1]) * float(wrel) ) splt = os.path.splitext(datei) newfilename\",\n \"= os.path.splitext(isitimg)[1].lower() if ext == \\\".jpg\\\" or ext == \\\".png\\\" or ext ==\",\n \") splt = os.path.splitext(datei) newfilename = splt[0] + splt[1].lower() img = img.resize((DATEI_WEB_GROSSE, habs),\",\n \"or ext == \\\".gif\\\": return True return False def bearbeiten(datei): img = Image.open(datei)\",\n \"DATEI_WEB_GROSSE = 700 def isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower() if ext == \\\".jpg\\\" or\",\n \"return True return False def bearbeiten(datei): img = Image.open(datei) wrel = DATEI_WEB_GROSSE /\",\n \"= 700 def isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower() if ext == \\\".jpg\\\" or ext\",\n \"datei) def main(): files = os.listdir('.') files = filter(isimg, files) for f in\",\n \"os.rename(newfilename, datei) def main(): files = os.listdir('.') files = filter(isimg, files) for f\",\n \"False def bearbeiten(datei): img = Image.open(datei) wrel = DATEI_WEB_GROSSE / float(img.size[0]) habs =\",\n \"import Image DATEI_WEB_GROSSE = 700 def isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower() if ext ==\",\n \"PIL import Image DATEI_WEB_GROSSE = 700 def isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower() if ext\",\n \"+ splt[1].lower() img = img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True, progressive=True) if newfilename\",\n \"or ext == \\\".png\\\" or ext == \\\".gif\\\": return True return False def\",\n \"= Image.open(datei) wrel = DATEI_WEB_GROSSE / float(img.size[0]) habs = int( float(img.size[1]) * float(wrel)\",\n \"filter(isimg, files) for f in files: print f bearbeiten(f) if __name__ == '__main__':\",\n \"img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True, progressive=True) if newfilename != datei: os.rename(newfilename, datei)\",\n \"ext = os.path.splitext(isitimg)[1].lower() if ext == \\\".jpg\\\" or ext == \\\".png\\\" or ext\",\n \"img = Image.open(datei) wrel = DATEI_WEB_GROSSE / float(img.size[0]) habs = int( float(img.size[1]) *\",\n \"Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True, progressive=True) if newfilename != datei: os.rename(newfilename, datei) def main():\",\n \"splt[0] + splt[1].lower() img = img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True, progressive=True) if\",\n \"Image.open(datei) wrel = DATEI_WEB_GROSSE / float(img.size[0]) habs = int( float(img.size[1]) * float(wrel) )\",\n \"= img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True, progressive=True) if newfilename != datei: os.rename(newfilename,\",\n \"= int( float(img.size[1]) * float(wrel) ) splt = os.path.splitext(datei) newfilename = splt[0] +\",\n \"= os.path.splitext(datei) newfilename = splt[0] + splt[1].lower() img = img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename,\",\n \"main(): files = os.listdir('.') files = filter(isimg, files) for f in files: print\",\n \"newfilename != datei: os.rename(newfilename, datei) def main(): files = os.listdir('.') files = filter(isimg,\",\n \"= os.listdir('.') files = filter(isimg, files) for f in files: print f bearbeiten(f)\",\n \"optimize=True, progressive=True) if newfilename != datei: os.rename(newfilename, datei) def main(): files = os.listdir('.')\",\n \"\\\".jpg\\\" or ext == \\\".png\\\" or ext == \\\".gif\\\": return True return False\",\n \"os.path.splitext(isitimg)[1].lower() if ext == \\\".jpg\\\" or ext == \\\".png\\\" or ext == \\\".gif\\\":\",\n \"quality=100, optimize=True, progressive=True) if newfilename != datei: os.rename(newfilename, datei) def main(): files =\",\n \"!= datei: os.rename(newfilename, datei) def main(): files = os.listdir('.') files = filter(isimg, files)\",\n \"isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower() if ext == \\\".jpg\\\" or ext == \\\".png\\\" or\",\n \"700 def isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower() if ext == \\\".jpg\\\" or ext ==\",\n \"img = img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True, progressive=True) if newfilename != datei:\",\n \"= splt[0] + splt[1].lower() img = img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True, progressive=True)\",\n \"ext == \\\".gif\\\": return True return False def bearbeiten(datei): img = Image.open(datei) wrel\",\n \"os.path.splitext(datei) newfilename = splt[0] + splt[1].lower() img = img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename, quality=100,\",\n \"datei: os.rename(newfilename, datei) def main(): files = os.listdir('.') files = filter(isimg, files) for\",\n \"import os from PIL import Image DATEI_WEB_GROSSE = 700 def isimg(isitimg): ext =\",\n \"= filter(isimg, files) for f in files: print f bearbeiten(f) if __name__ ==\",\n \"int( float(img.size[1]) * float(wrel) ) splt = os.path.splitext(datei) newfilename = splt[0] + splt[1].lower()\",\n \"#!/usr/bin/python2.7 import os from PIL import Image DATEI_WEB_GROSSE = 700 def isimg(isitimg): ext\",\n \"True return False def bearbeiten(datei): img = Image.open(datei) wrel = DATEI_WEB_GROSSE / float(img.size[0])\",\n \"habs), Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True, progressive=True) if newfilename != datei: os.rename(newfilename, datei) def\",\n \"progressive=True) if newfilename != datei: os.rename(newfilename, datei) def main(): files = os.listdir('.') files\",\n \"files = os.listdir('.') files = filter(isimg, files) for f in files: print f\",\n \"newfilename = splt[0] + splt[1].lower() img = img.resize((DATEI_WEB_GROSSE, habs), Image.ANTIALIAS) img.save(newfilename, quality=100, optimize=True,\",\n \"habs = int( float(img.size[1]) * float(wrel) ) splt = os.path.splitext(datei) newfilename = splt[0]\",\n \"\\\".png\\\" or ext == \\\".gif\\\": return True return False def bearbeiten(datei): img =\",\n \"== \\\".gif\\\": return True return False def bearbeiten(datei): img = Image.open(datei) wrel =\",\n \"bearbeiten(datei): img = Image.open(datei) wrel = DATEI_WEB_GROSSE / float(img.size[0]) habs = int( float(img.size[1])\",\n \"def isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower() if ext == \\\".jpg\\\" or ext == \\\".png\\\"\",\n \"== \\\".png\\\" or ext == \\\".gif\\\": return True return False def bearbeiten(datei): img\",\n \"return False def bearbeiten(datei): img = Image.open(datei) wrel = DATEI_WEB_GROSSE / float(img.size[0]) habs\",\n \"wrel = DATEI_WEB_GROSSE / float(img.size[0]) habs = int( float(img.size[1]) * float(wrel) ) splt\"\n]","isConversational":false}}},{"rowIdx":4399,"cells":{"ngram":{"kind":"list like","value":["flamewreath(self, ctx): \"\"\"I will not move when Flame Wreath is cast!\"\"\" await self._play(\"https://www.youtube.com/watch?v=gcA6y7sxKcA\",","url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async def flamewreath(self, ctx): \"\"\"I will not move when Flame","no_pm=True) async def flamewreath(self, ctx): \"\"\"I will not move when Flame Wreath is","in the Audio module\"\"\" audio = self.bot.get_cog('Audio') if not audio: await self.bot.say(\"Audio module","discord.ext import commands class WowCog: \"\"\"Custom Cog that had commands for WoW Memes\"\"\"","commands for WoW Memes\"\"\" def __init__(self, bot): self.bot = bot async def _play(self,","_play(self, url, ctx): \"\"\"Helper for aliasing Play in the Audio module\"\"\" audio =","class WowCog: \"\"\"Custom Cog that had commands for WoW Memes\"\"\" def __init__(self, bot):","not audio: await self.bot.say(\"Audio module required. Load with: {}load audio\".format(ctx.prefix)) return await ctx.invoke(audio.play,","return await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async def flamewreath(self, ctx): \"\"\"I will not","ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async def flamewreath(self, ctx): \"\"\"I will not move when","= bot async def _play(self, url, ctx): \"\"\"Helper for aliasing Play in the","WowCog: \"\"\"Custom Cog that had commands for WoW Memes\"\"\" def __init__(self, bot): self.bot","def __init__(self, bot): self.bot = bot async def _play(self, url, ctx): \"\"\"Helper for","bot): self.bot = bot async def _play(self, url, ctx): \"\"\"Helper for aliasing Play","{}load audio\".format(ctx.prefix)) return await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async def flamewreath(self, ctx): \"\"\"I","commands class WowCog: \"\"\"Custom Cog that had commands for WoW Memes\"\"\" def __init__(self,","import commands class WowCog: \"\"\"Custom Cog that had commands for WoW Memes\"\"\" def","Play in the Audio module\"\"\" audio = self.bot.get_cog('Audio') if not audio: await self.bot.say(\"Audio","discord from discord.ext import commands class WowCog: \"\"\"Custom Cog that had commands for","audio: await self.bot.say(\"Audio module required. Load with: {}load audio\".format(ctx.prefix)) return await ctx.invoke(audio.play, url_or_search_terms=url)","await self.bot.say(\"Audio module required. Load with: {}load audio\".format(ctx.prefix)) return await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True,","that had commands for WoW Memes\"\"\" def __init__(self, bot): self.bot = bot async","for aliasing Play in the Audio module\"\"\" audio = self.bot.get_cog('Audio') if not audio:","ctx): \"\"\"I will not move when Flame Wreath is cast!\"\"\" await self._play(\"https://www.youtube.com/watch?v=gcA6y7sxKcA\", ctx)","@commands.command(pass_context=True, no_pm=True) async def flamewreath(self, ctx): \"\"\"I will not move when Flame Wreath","await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async def flamewreath(self, ctx): \"\"\"I will not move","aliasing Play in the Audio module\"\"\" audio = self.bot.get_cog('Audio') if not audio: await","Memes\"\"\" def __init__(self, bot): self.bot = bot async def _play(self, url, ctx): \"\"\"Helper","Audio module\"\"\" audio = self.bot.get_cog('Audio') if not audio: await self.bot.say(\"Audio module required. Load","had commands for WoW Memes\"\"\" def __init__(self, bot): self.bot = bot async def","__init__(self, bot): self.bot = bot async def _play(self, url, ctx): \"\"\"Helper for aliasing","self.bot = bot async def _play(self, url, ctx): \"\"\"Helper for aliasing Play in","async def flamewreath(self, ctx): \"\"\"I will not move when Flame Wreath is cast!\"\"\"","will not move when Flame Wreath is cast!\"\"\" await self._play(\"https://www.youtube.com/watch?v=gcA6y7sxKcA\", ctx) def setup(bot):","from discord.ext import commands class WowCog: \"\"\"Custom Cog that had commands for WoW","for WoW Memes\"\"\" def __init__(self, bot): self.bot = bot async def _play(self, url,","WoW Memes\"\"\" def __init__(self, bot): self.bot = bot async def _play(self, url, ctx):","the Audio module\"\"\" audio = self.bot.get_cog('Audio') if not audio: await self.bot.say(\"Audio module required.","module\"\"\" audio = self.bot.get_cog('Audio') if not audio: await self.bot.say(\"Audio module required. Load with:","module required. Load with: {}load audio\".format(ctx.prefix)) return await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async","\"\"\"I will not move when Flame Wreath is cast!\"\"\" await self._play(\"https://www.youtube.com/watch?v=gcA6y7sxKcA\", ctx) def","self.bot.get_cog('Audio') if not audio: await self.bot.say(\"Audio module required. Load with: {}load audio\".format(ctx.prefix)) return","def flamewreath(self, ctx): \"\"\"I will not move when Flame Wreath is cast!\"\"\" await","audio\".format(ctx.prefix)) return await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async def flamewreath(self, ctx): \"\"\"I will","\"\"\"Helper for aliasing Play in the Audio module\"\"\" audio = self.bot.get_cog('Audio') if not","ctx): \"\"\"Helper for aliasing Play in the Audio module\"\"\" audio = self.bot.get_cog('Audio') if","audio = self.bot.get_cog('Audio') if not audio: await self.bot.say(\"Audio module required. Load with: {}load","not move when Flame Wreath is cast!\"\"\" await self._play(\"https://www.youtube.com/watch?v=gcA6y7sxKcA\", ctx) def setup(bot): bot.add_cog(WowCog(bot))","url, ctx): \"\"\"Helper for aliasing Play in the Audio module\"\"\" audio = self.bot.get_cog('Audio')","bot async def _play(self, url, ctx): \"\"\"Helper for aliasing Play in the Audio","async def _play(self, url, ctx): \"\"\"Helper for aliasing Play in the Audio module\"\"\"","if not audio: await self.bot.say(\"Audio module required. Load with: {}load audio\".format(ctx.prefix)) return await","Load with: {}load audio\".format(ctx.prefix)) return await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async def flamewreath(self,","def _play(self, url, ctx): \"\"\"Helper for aliasing Play in the Audio module\"\"\" audio","= self.bot.get_cog('Audio') if not audio: await self.bot.say(\"Audio module required. Load with: {}load audio\".format(ctx.prefix))","self.bot.say(\"Audio module required. Load with: {}load audio\".format(ctx.prefix)) return await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True)","\"\"\"Custom Cog that had commands for WoW Memes\"\"\" def __init__(self, bot): self.bot =","with: {}load audio\".format(ctx.prefix)) return await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async def flamewreath(self, ctx):","import discord from discord.ext import commands class WowCog: \"\"\"Custom Cog that had commands","required. Load with: {}load audio\".format(ctx.prefix)) return await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async def","Cog that had commands for WoW Memes\"\"\" def __init__(self, bot): self.bot = bot"],"string":"[\n \"flamewreath(self, ctx): \\\"\\\"\\\"I will not move when Flame Wreath is cast!\\\"\\\"\\\" await self._play(\\\"https://www.youtube.com/watch?v=gcA6y7sxKcA\\\",\",\n \"url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async def flamewreath(self, ctx): \\\"\\\"\\\"I will not move when Flame\",\n \"no_pm=True) async def flamewreath(self, ctx): \\\"\\\"\\\"I will not move when Flame Wreath is\",\n \"in the Audio module\\\"\\\"\\\" audio = self.bot.get_cog('Audio') if not audio: await self.bot.say(\\\"Audio module\",\n \"discord.ext import commands class WowCog: \\\"\\\"\\\"Custom Cog that had commands for WoW Memes\\\"\\\"\\\"\",\n \"commands for WoW Memes\\\"\\\"\\\" def __init__(self, bot): self.bot = bot async def _play(self,\",\n \"_play(self, url, ctx): \\\"\\\"\\\"Helper for aliasing Play in the Audio module\\\"\\\"\\\" audio =\",\n \"class WowCog: \\\"\\\"\\\"Custom Cog that had commands for WoW Memes\\\"\\\"\\\" def __init__(self, bot):\",\n \"not audio: await self.bot.say(\\\"Audio module required. Load with: {}load audio\\\".format(ctx.prefix)) return await ctx.invoke(audio.play,\",\n \"return await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async def flamewreath(self, ctx): \\\"\\\"\\\"I will not\",\n \"ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async def flamewreath(self, ctx): \\\"\\\"\\\"I will not move when\",\n \"= bot async def _play(self, url, ctx): \\\"\\\"\\\"Helper for aliasing Play in the\",\n \"WowCog: \\\"\\\"\\\"Custom Cog that had commands for WoW Memes\\\"\\\"\\\" def __init__(self, bot): self.bot\",\n \"def __init__(self, bot): self.bot = bot async def _play(self, url, ctx): \\\"\\\"\\\"Helper for\",\n \"bot): self.bot = bot async def _play(self, url, ctx): \\\"\\\"\\\"Helper for aliasing Play\",\n \"{}load audio\\\".format(ctx.prefix)) return await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async def flamewreath(self, ctx): \\\"\\\"\\\"I\",\n \"commands class WowCog: \\\"\\\"\\\"Custom Cog that had commands for WoW Memes\\\"\\\"\\\" def __init__(self,\",\n \"import commands class WowCog: \\\"\\\"\\\"Custom Cog that had commands for WoW Memes\\\"\\\"\\\" def\",\n \"Play in the Audio module\\\"\\\"\\\" audio = self.bot.get_cog('Audio') if not audio: await self.bot.say(\\\"Audio\",\n \"discord from discord.ext import commands class WowCog: \\\"\\\"\\\"Custom Cog that had commands for\",\n \"audio: await self.bot.say(\\\"Audio module required. Load with: {}load audio\\\".format(ctx.prefix)) return await ctx.invoke(audio.play, url_or_search_terms=url)\",\n \"await self.bot.say(\\\"Audio module required. Load with: {}load audio\\\".format(ctx.prefix)) return await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True,\",\n \"that had commands for WoW Memes\\\"\\\"\\\" def __init__(self, bot): self.bot = bot async\",\n \"for aliasing Play in the Audio module\\\"\\\"\\\" audio = self.bot.get_cog('Audio') if not audio:\",\n \"ctx): \\\"\\\"\\\"I will not move when Flame Wreath is cast!\\\"\\\"\\\" await self._play(\\\"https://www.youtube.com/watch?v=gcA6y7sxKcA\\\", ctx)\",\n \"@commands.command(pass_context=True, no_pm=True) async def flamewreath(self, ctx): \\\"\\\"\\\"I will not move when Flame Wreath\",\n \"await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async def flamewreath(self, ctx): \\\"\\\"\\\"I will not move\",\n \"aliasing Play in the Audio module\\\"\\\"\\\" audio = self.bot.get_cog('Audio') if not audio: await\",\n \"Memes\\\"\\\"\\\" def __init__(self, bot): self.bot = bot async def _play(self, url, ctx): \\\"\\\"\\\"Helper\",\n \"Audio module\\\"\\\"\\\" audio = self.bot.get_cog('Audio') if not audio: await self.bot.say(\\\"Audio module required. Load\",\n \"had commands for WoW Memes\\\"\\\"\\\" def __init__(self, bot): self.bot = bot async def\",\n \"__init__(self, bot): self.bot = bot async def _play(self, url, ctx): \\\"\\\"\\\"Helper for aliasing\",\n \"self.bot = bot async def _play(self, url, ctx): \\\"\\\"\\\"Helper for aliasing Play in\",\n \"async def flamewreath(self, ctx): \\\"\\\"\\\"I will not move when Flame Wreath is cast!\\\"\\\"\\\"\",\n \"will not move when Flame Wreath is cast!\\\"\\\"\\\" await self._play(\\\"https://www.youtube.com/watch?v=gcA6y7sxKcA\\\", ctx) def setup(bot):\",\n \"from discord.ext import commands class WowCog: \\\"\\\"\\\"Custom Cog that had commands for WoW\",\n \"for WoW Memes\\\"\\\"\\\" def __init__(self, bot): self.bot = bot async def _play(self, url,\",\n \"WoW Memes\\\"\\\"\\\" def __init__(self, bot): self.bot = bot async def _play(self, url, ctx):\",\n \"the Audio module\\\"\\\"\\\" audio = self.bot.get_cog('Audio') if not audio: await self.bot.say(\\\"Audio module required.\",\n \"module\\\"\\\"\\\" audio = self.bot.get_cog('Audio') if not audio: await self.bot.say(\\\"Audio module required. Load with:\",\n \"module required. Load with: {}load audio\\\".format(ctx.prefix)) return await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async\",\n \"\\\"\\\"\\\"I will not move when Flame Wreath is cast!\\\"\\\"\\\" await self._play(\\\"https://www.youtube.com/watch?v=gcA6y7sxKcA\\\", ctx) def\",\n \"self.bot.get_cog('Audio') if not audio: await self.bot.say(\\\"Audio module required. Load with: {}load audio\\\".format(ctx.prefix)) return\",\n \"def flamewreath(self, ctx): \\\"\\\"\\\"I will not move when Flame Wreath is cast!\\\"\\\"\\\" await\",\n \"audio\\\".format(ctx.prefix)) return await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async def flamewreath(self, ctx): \\\"\\\"\\\"I will\",\n \"\\\"\\\"\\\"Helper for aliasing Play in the Audio module\\\"\\\"\\\" audio = self.bot.get_cog('Audio') if not\",\n \"ctx): \\\"\\\"\\\"Helper for aliasing Play in the Audio module\\\"\\\"\\\" audio = self.bot.get_cog('Audio') if\",\n \"audio = self.bot.get_cog('Audio') if not audio: await self.bot.say(\\\"Audio module required. Load with: {}load\",\n \"not move when Flame Wreath is cast!\\\"\\\"\\\" await self._play(\\\"https://www.youtube.com/watch?v=gcA6y7sxKcA\\\", ctx) def setup(bot): bot.add_cog(WowCog(bot))\",\n \"url, ctx): \\\"\\\"\\\"Helper for aliasing Play in the Audio module\\\"\\\"\\\" audio = self.bot.get_cog('Audio')\",\n \"bot async def _play(self, url, ctx): \\\"\\\"\\\"Helper for aliasing Play in the Audio\",\n \"async def _play(self, url, ctx): \\\"\\\"\\\"Helper for aliasing Play in the Audio module\\\"\\\"\\\"\",\n \"if not audio: await self.bot.say(\\\"Audio module required. Load with: {}load audio\\\".format(ctx.prefix)) return await\",\n \"Load with: {}load audio\\\".format(ctx.prefix)) return await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async def flamewreath(self,\",\n \"def _play(self, url, ctx): \\\"\\\"\\\"Helper for aliasing Play in the Audio module\\\"\\\"\\\" audio\",\n \"= self.bot.get_cog('Audio') if not audio: await self.bot.say(\\\"Audio module required. Load with: {}load audio\\\".format(ctx.prefix))\",\n \"self.bot.say(\\\"Audio module required. Load with: {}load audio\\\".format(ctx.prefix)) return await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True)\",\n \"\\\"\\\"\\\"Custom Cog that had commands for WoW Memes\\\"\\\"\\\" def __init__(self, bot): self.bot =\",\n \"with: {}load audio\\\".format(ctx.prefix)) return await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async def flamewreath(self, ctx):\",\n \"import discord from discord.ext import commands class WowCog: \\\"\\\"\\\"Custom Cog that had commands\",\n \"required. Load with: {}load audio\\\".format(ctx.prefix)) return await ctx.invoke(audio.play, url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async def\",\n \"Cog that had commands for WoW Memes\\\"\\\"\\\" def __init__(self, bot): self.bot = bot\"\n]","isConversational":false}}}],"truncated":false,"partial":false},"paginationData":{"pageIndex":43,"numItemsPerPage":100,"numTotalItems":12866649,"offset":4300,"length":100}},"jwt":"eyJhbGciOiJFZERTQSIsImtpZCI6Im1sR1pFYktIVHRVSGRhX1RRdEczQ0N1S3k5ME9Qd25DNHY5elRjM3FVYzgifQ.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc4MzU5MTY2MSwianRpIjoiNGI0OTIxZGEtMmJlZC00ZmU1LTk2YTEtZTUyMzFjMDlhZmNlIiwic3ViIjoiL2RhdGFzZXRzL3RlcnJ5eXovc3RhcmNvZGVyZGF0YV9uZ3JhbV8xMyIsImV4cCI6MTc4MzU5NTI2MSwiaXNzIjoiaHR0cHM6Ly9odWdnaW5nZmFjZS5jbyJ9.YDQxWXZ_jYs5Y46hfDLcUxDXh_AJEf2QokgJhJ_SEqqoq6l3g1YUANDI077gm6FqW0670KaDnO0XkaPsB7KPDw","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":12866649,"numBytesParquet":149232926747}]},"discussionsStats":{"closed":0,"open":0,"total":0},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
ngram listlengths 0 67.8k |
|---|
[
"< (3, 6)) def tmphome(request, monkeypatch): \"\"\"Set up HOME in a temporary directory.",
"is _orig_trace orig_settrace = sys.settrace # Wrap sys.settrace to restore original tracing function",
"monkeypatch): \"\"\"Set up HOME in a temporary directory. This ignores any real ~/.pdbrc.py",
"else: m.setattr(\"... |
[
"amount to \"zoom\" into the image. E.g. 2.0 would cut out half of",
"to \"zoom\" into the image. E.g. 2.0 would cut out half of the",
"would cut out half of the width, half of the height, and only",
"relative_corners are floats between 0 and 1 designating where the corners of a",
"raw_width), int(rc[0][1] ... |
[
"self.assertEquals(result, True) def test_base_domain_matches_domain_with_explicit_port(self): result = self.isValidOrigin('http://example.com:80', ['example.com:80']) assert result is True def",
"def test_custom_protocol_with_domainish_match(self): result = self.isValidOrigin('sp://custom-thing.foobar/foo/bar', ... |
[
"date, feedgenerator, html, number, misc, text from markupsafe import Markup def bold(text): return",
"used in project.\"\"\" #from webhelpers import date, feedgenerator, html, number, misc, text from",
"<gh_stars>0 # -*- coding: utf-8 -*- \"\"\"WebHelpers used in project.\"\"\" #from webhelpers import",
"num... |
[
"else: remoteYcsbNodes = []; cluster = RiakCluster(NORMAL_BINDING, CONSISTENCY_BINDING, IPS_IN_CLUSTER); runLoadBenchmarkAsBatch(cluster, remoteYcsbNodes, pathToWorkloadFile, runtimeBenchmarkInMinutes,",
"ycsb nodes>]'; exit(); cluster = RiakCluster(NORMAL_BINDING, CONSISTENCY_BINDING, IPS_IN_CLUSTER); runLoadBen... |
[
"'<EMAIL>', 'cd', ) assert rr.get(self.mk_bug('P2::C2'), '2019-02-24') == ( '<EMAIL>', 'cd', ) assert rr.get(self.mk_bug('P3::C3'),",
"assert rr.get(self.mk_bug('P2::C2'), '2019-03-08') == ( '<EMAIL>', 'gh', ) assert rr.get(self.mk_bug('P3::C3'), '2019-03-08') == (",
"( '<EMAIL>', 'ef', ) assert rr.get(self.mk_... |
[
"function_code(self): from .ext_tools import indent decl_code = indent(self.arg_declaration_code(),4) cleanup_code = indent(self.arg_cleanup_code(),4) function_code =",
"= os.path.split(module_path) mod = inline_ext_module(module_name,compiler) # create the function. This relies on the",
"indent decl_code = ind... |
[
"in which they were applied. \"\"\" name_pattern = self._build_rev_name_pattern(group_name=group_name) return sorted(operating_system.list_files_in_directory( self._revision_dir, recursive=True,",
"an override is applied or removed a new configuration file is generated by",
"Unless required by applicable law or... |
[
"in content: if \"description\" in content[\"requestBody\"]: description_ = str(content[\"requestBody\"][\"description\"]) if description_[-1] != \".\":",
"{eg}</sub></i>' if isinstance(eg, str): eg = '\"' + eg + '\"' example_ =",
"description_[-1] != \".\": description_ += \".\" if \"enum\" in properties: type... |
[
"getHub(self, hub_id): url = self.api_url + '/project/v1/hubs/%s' % hub_id headers = { 'Authorization':",
"return get_request(url, headers) @authorized def getHub(self, hub_id): url = self.api_url + '/project/v1/hubs/%s' %",
"class Hubs: @authorized def getHubs(self): url = self.api_url + '/project/v1/hubs' hea... |
[
"# from .views import BaseIndexView urlpatterns = [ # url(r'^$', BaseIndexView.as_view(), name=\"index\"), ]",
"import url # from .views import BaseIndexView urlpatterns = [ # url(r'^$', BaseIndexView.as_view(),",
"url # from .views import BaseIndexView urlpatterns = [ # url(r'^$', BaseIndexView.as_view(), name... |
[
"subdirectories for {0}'.format(config_type)) return myconfigdir def create_context(config_var_file): # read the metafile to get",
"variables = oyaml.safe_load(var_metadata.read()) except IOError as ioe: print(f'Could not open metadata file {config_var_file}')",
"template.render(context) return rendered_templat... |
[
"clearer return \"ignore fail\", \"f\", \"IGNORE_FAIL\" @pytest.fixture() def pact_verifier(pytestconfig, request): interaction, consumer =",
"\"and will be removed in the 3.0.0 release.\", DeprecationWarning, ) if filter_consumer_name: pacts",
"provider_name: raise ValueError(\"--pact-broker-url requires the -... |
[
"is 10.' \"\"\" def wrapper(fget): return DocstringProperty(class_doc, fget) return wrapper class DocstringProperty(object): \"\"\"Property",
"for docstrings. Took from: https://gist.github.com/bfroehle/4041015 >>> class A(object): ... '''Main docstring''' ... def",
"the attribute is accessed from the main clas... |
[
"symmetry check is required. The ratio check is embedded on the cuda side",
"need to be remapped to the source_kps, # destin_kps indices. This is the",
"= pd.concat([pd.Series(source), pd.Series(matches.index), pd.Series(destination), matches.match, matches.score, matches.ambiguity], axis=1) df.columns = ['sour... |
[
"app.apis.hello import api as hello api = Api( title='api', version='1.0', description='', prefix='/api', doc='/api'",
"flask_restx import Api from app.apis.hello import api as hello api = Api( title='api',",
"api as hello api = Api( title='api', version='1.0', description='', prefix='/api', doc='/api' ) api.ad... |
[
"unittest from test.support import captured_stdout from brainfuck import BrainFuck class TestCore(unittest.TestCase): def test_hello_world(self):",
"as stdout: bf.run() self.assertEqual(stdout.getvalue(), \"Hello, world!\\n\") def test_fizzbuzz(self): bf = BrainFuck() bf.load_file(\"./tests/fizz_buzz.txt\") with"... |
[
"requests with cookies return get_page_data(request) if __name__ == \"__main__\": uvicorn.run(\"main:app\", host=\"127.0.0.1\", port=8050, log_level=\"info\")",
"StaticFiles(directory=\"static\"), name=\"static\") @app.get(\"/\", response_class=HTMLResponse) async def home(request: Request): # Expect requests wit... |
[
"KIND, either express or implied. # See the License for the specific language",
"Unless required by applicable law or agreed to in writing, software # distributed",
"to create a new static group # # _author_ = <NAME> <<EMAIL>> #",
"using OME API to create a new static group # # _author_ =",
"Script to creat... |
[
"limit_train_num_samples: Optional[int] = None, limit_val_num_samples: Optional[int] = None) -> Tuple[DataLoader, DataLoader, DataLoader]: train_ds",
"train_ds = get_train_dataset(root_path) val_ds = get_val_dataset(root_path) if with_sbd is not None: sbd_train_ds =",
"val_sampler = data_dist.DistributedSampler... |
[
"-> Optional[User]: user = User.objects.filter(email=payload[\"email\"], is_active=True).first() user_jwt_token = payload.get(\"token\") if not user_jwt_token or",
"import settings from django.core.handlers.wsgi import WSGIRequest from ..account.models import User from ..app.models import",
"token was generated... |
[
"if path.startswith('./') : path = path[1:] elif not path.startswith('/'): path = '/%s' %",
"MATCH.PATH. Each item is a path component, start from outer most item. \"\"\"",
"Exception as err: logger.info(err) self.config_data = json.load({}) return self.config_data def update_json_config(self, json_added, json_... |
[
"('data', '0022_discardaction'), ] operations = [ migrations.AddField( model_name='discardaction', name='answers', field=django.contrib.postgres.fields.jsonb.JSONField(blank=True, null=True), ), ]",
"import django.contrib.postgres.fields.jsonb from django.db import migrations class Migration(migrations.Migration)... |
[
"ComplexJsonEncoder(JSONEncoder): \"\"\"Basic JSON encoder for 'complex (nested)' Python objects.\"\"\" def default(self, o): if",
"method to be implemented by any class that wants to be serialized to",
"def __init__(self): self.id = \"\" self.name = \"\" self.time = int(round(time() * 1000))",
"time class Js... |
[
"\"\"\"Compute pi to a specific precision using multiple algorithms.\"\"\" @staticmethod def BBP(precision): \"\"\"Compute",
"<gh_stars>0 \"\"\"Compute pi.\"\"\" from decimal import Decimal, getcontext import argparse import itertools class",
"pi @staticmethod def arctan_euler(x, one=1000000): \"\"\"Calculate a... |
[
"# If we want an intializer function we can add # `initializer=box.store, 1`",
"{network.show_active()}\") data_types = DataTypes.deploy( {\"from\": account}, publish_source=config[\"networks\"][network.show_active()][\"verify\"], ) # Optional, deploy the ProxyAdmin",
"being the `store` function # with a `newVa... |
[
"class BidirectionalLSTM(nn.Module): # Module to extract BLSTM features from convolutional feature map def",
"nIn, nHidden, nOut): super(BidirectionalLSTM, self).__init__() self.rnn = nn.LSTM(nIn, nHidden, bidirectional=True) self.embedding = nn.Linear(nHidden",
"T, b, h = recurrent.size() t_rec = recurrent.vie... |
[
"self,v: None,lambda self: None) \"\"\"Gets the rectangle in which to paint. Get: ClipRectangle(self:",
"PaintEventArgs() def Dispose(self): \"\"\" Dispose(self: PaintEventArgs) Releases all resources used by the System.Windows.Forms.PaintEventArgs.",
"paint. Get: ClipRectangle(self: PaintEventArgs) -> Rectangl... |
[
"total training iteration') parser.add_argument('--batch_size', default=32, type=int, help='size of minibatch') parser.add_argument('--test_batch_size', default=32, type=int, help='size",
"training mode') os.environ['CUDA_VISIBLE_DEVICES'] = str(opt.gpu) opt.device = torch.device('cuda' if torch.cuda.is_available... |
[
"fileServers: - operation: \"all\" url: \"file://{work_dir}/scratch\" - type: \"localStorage\" path: \"{work_dir}/outputs\" fileServers: -",
"file for registration jobs with (TOP_DIR / \"replicas.yml\").open(\"w\") as f: rc.write(f) wf.add_transformation_catalog(tc) try:",
"\" + current_file.name + \".\", \"-da... |
[
"from ceem.opt_criteria import * from ceem.systems import LorenzAttractor from ceem.dynamics import * from",
"= 0.04 sys = LorenzAttractor(sigma, rho, beta, C, dt, method='midpoint') B = 1",
"Test BlockSparseGroupSOSCriterion crit = BlockSparseGroupSOSCriterion([obscrit, dyncrit]) xsm, metrics = NLSsmoother(tor... |
[
"import pulse from qiskit.providers import BaseBackend, BackendConfigurationError class DrawerBackendInfo(ABC): \"\"\"Backend information to be",
"of the backend. dt: System cycle time. channel_frequency_map: Mapping of channel and associated",
"complex(*u_lo_mapper.scale) chan_freqs[pulse.ControlChannel(qind)]... |
[
"messages from django.urls import reverse from django.http import HttpResponseRedirect from django_gotolong.lastrefd.models import Lastrefd,",
"model = Mfund def get_queryset(self): self.queryset = Mfund.objects.all().filter(mf_user_id=self.request.user.id). \\ values('mf_subcat').annotate(scheme_sum=Sum('mf_nav_... |
[
"re.sub(pattern,'{:0>3}'.format(r),lastTs,1) + \".ts\" req = urllib.request.Request(url=nextTs,headers=headers,method='GET') retry -= 1 isOk = False return",
"[urllib.parse.urljoin(m3u8_url, n.strip()) for n in str(body, encoding = \"utf8\").split('\\n') if n and not",
"file_name = self.succed.get(index, '') if... |
[
"= [ ('restaurants', '0001_initial'), ] operations = [ migrations.AddField( model_name='restaurant', name='description', field=models.CharField(default='Description', max_length=255,",
"<filename>buzzbox/restaurants/migrations/0002_restaurant_description.py # Generated by Django 3.2.9 on 2021-12-06 10:02 from dja... |
[
"**kwargs): layout = self._stack.pop() if self._stack: parent = self._stack[-1] if isinstance(layout, QtWidgets.QSplitter): parent.addWidget(layout)",
"settings: path = QtCore.QStandardPaths.writableLocation(QtCore.QStandardPaths.DocumentsLocation) sname = 'save_%s' % domain if settings.contains(sname): path =",
... |
[
"common_test_param: :return: \"\"\" try: test_plan = self.test_plan[self.test_module] for test_method_name in test_method_names: self.__prepare_test_vars(test_method_name, **common_test_param)",
"method_to_execute() except Exception as e: log_print(f'!!! Exception in {method_name} code !!!', color='red') log_prin... |
[
"return valid, cache_training_set_metadata, cached_training_set, cached_test_set, cached_validation_set def put(self, training_set, test_set, validation_set, training_set_metadata): logger.info(\"Writing",
"isinstance(dataset, str): # TODO(travis): could try hashing the in-memory dataset, but this is",
"alphanu... |
[
"test_calculator_base(failed_dict): mrms = [0, 0.3] pm = [None, [\"assembling-machine-2\", \"stone-furnace\", \"burner-mining-drill\"]] uk =",
"am = [1, 101.5] failed_dict['init_failed'] = {} failed_dict['method_failed'] = { 'change_machine_failed': { }",
"failed_dict['init_failed'] = {} failed_dict['method_fai... |
[
"16 UTF16 = 17 class TMessageType: CALL = 1 REPLY = 2 EXCEPTION",
"= 0 VOID = 1 BOOL = 2 BYTE = 3 I08 =",
"pass class TException(Exception): \"\"\"Base class for all thrift exceptions.\"\"\" def __init__(self, message=None): Exception.__init__(self,",
"iprot.readI32(); else: iprot.skip(ftype) else: iprot.skip... |
[
"engines import AudioRecognition, FeatureExtractor class Engines(Enum): POCKET_SPHINX = 'PocketSphinx' PORCUPINE = 'Porcupine' SNOWBOY",
"namedtuple from enum import Enum import numpy as np from pocketsphinx import get_model_path",
"KIND, either express or implied. # See the License for the specific language",
... |
[
"I haven't tested it. import weakref #https://docs.python.org/3/library/weakref.html class InsaneClass(object): _alive = [] def",
"__new__(cls): # there is a difference btw. cls and self, but i don't",
"instance = InsaneClass() instance.__enter__() instance.commit_suicide() #print(instance) print(InsaneClass) #... |
[
"epsilon, True) # find convexity hull and defects hull = cv2.convexHull(max_contour, returnPoints=False) defects",
"(contour, defects) = find_hull_defects(segment) # detect the number of fingers depending on the",
"imageheight frame center_half = 10 # half-width of 21 is 21/2-1 center =",
"# defects, then dra... |
[
"-*- coding: utf-8 -*- ''' // Copyright (c) 2015 Intel Corporation // //",
"\" panic_gbuffer=\" + str(self.args.gbuffer) self._kernel_module_parameters += \" exclude_userspace=\" + str(self.args.userspace) self._kernel_module_parameters += \"",
"not use this file except in compliance with the License. // You ma... |
[
"os from . import filesys MAIN_USAGE_MESSAGE = \"\"\" usage: xlab command ... Options:",
"Invalid arguments.\") exit() if args[0] == 'init': root = os.getcwd() dirs = filesys.Directories()",
"== 'init': root = os.getcwd() dirs = filesys.Directories() dirs.set_root(root) def main(): if len(sys.argv)",
"'init':... |
[
"Unless required by applicable law or agreed to in writing, software # distributed",
"make sure _create_param_lr() be called after # optimizer._create_global_learning_rate(). learning_rate = self._create_param_lr(param_and_grad) with block.program._optimized_guard(",
"the result will be reused. # NOTE(wangxi): ... |
[
"function test retrieving protein interactions for various species' genes. \"\"\" # Valid request",
"expected = { \"wasSuccessful\": False, \"error\": \"There are no data found for the",
"\"Num_species\": 1, \"Quality\": 1, \"pcc\": -0.116, }, ], } self.assertEqual(response.json, expected) # Invalid",
"def se... |
[
"#pathToCSV = '/Users/Michal/Downloads/dialogflow-java-client-master2/samples/clients/VirtualTradingAssistant/src/main/java/ai/api/examples/fileStore/file.csv' #pathToCSV = 'C:\\\\Users\\\\ojwoo\\\\Documents\\\\Warwick\\\\CS261\\\\Coursework\\\\dialogflow-java-client-master\\\\samples\\\\clients\\\\VirtualTradingAs... |
[
"= 1 parsed_length = 0 mtype = 0 msg_length = 0 while self.running:",
"Client class for hotbox serial connection \"\"\" parsers = { MSG_STATUS: OvenStatus, MSG_RUN_STATUS:",
"parsed_length < 3: # Abort if not a null byte if c[0]: parsed_length",
"*args, **kwargs): if self.state == \"connected\": try: fun(self... |
[
"b in random.sample(blocks, len(blocks)): node0conn.send_block(b) # The node should eventually, completely sync without",
"(potentially out of order) blocks exits initial block download (IBD; this occurs once",
"Bitcoin developers # Distributed under the MIT software license, see the accompanying #",
"send_he... |
[
"TimeStamedModel(models.Model): created_at = models.DateTimeField(auto_now_add=True) updated_at = models.DateTimeField(auto_now_add=True) # An option that makes this",
"image_likes = models.ManyToManyField(user_model.User, related_name='post_image_likes') class Comments(TimeStamedModel): author = models.ForeignKe... |
[
"object has been moved\"\"\" def __init__(self, object, workflow, action, comments): ObjectEvent.__init__(self, object) self.object",
"from guillotina.contrib.workflows.interfaces import IWorkflowChangedEvent from guillotina.events import ObjectEvent from zope.interface import implementer @implementer(IWorkflowCh... |
[
"imports from google.cloud.exceptions import GoogleCloudError LOGGER = logging.getLogger(__name__) SUPPRESSION_RULE_CONCEPT_TABLE = 'covid_vaccine_concepts' COVID_VACCINE_CONCEPT_QUERY =",
"table. if your class deletes a subset of rows in the tables you",
"the count of final final row counts + deleted rows shou... |
[
"the API endpoint data : Dict[str, Any] data to be processed to the",
"the server. Returns ------- Tuple[List[Any], str] The returned data is - a list",
"str url of the API endpoint. data : Dict[str, Any] data to be",
"if response.status_code != 201: # The returned status code indicates something went wrong",... |
[
"[] picked_winners = [\"picked team\"] with pytest.raises(ValueError, match=r\".*invalid winner\"): round_score(VALID_ROUND, all_teams, round_winners, picked_winners)",
"a seed # seed doesn't change, so maybe make that not passed around",
"match=r\".*range*\"): round_score(0) with pytest.raises(ValueError, matc... |
[
"remapped by PyOBO self.assertEqual({'pubmed', 'cas', 'beilstein', 'reaxys'}, { xref.prefix for xref in xrefs",
") from tests.constants import TEST_CHEBI_OBO_PATH class TestParseObonet(unittest.TestCase): \"\"\"\"\"\" @classmethod def setUpClass(cls) -> None:",
"\"\"\"Test getting synonyms from a node in a :mod... |
[
"[777], 'latitude': [lat], 'longitude': [lon]}) \"\"\" El proceso es muy pesado y no",
"import codecs from math import cos, asin, sqrt # + def read_csv_with_encoding(filename, delimiter=\"|\",",
"-*- coding: utf-8 -*- # + ## Utilidades comunes entre places y OSM.",
"distance(lat1, lon1, lat2, lon2): \"\"\" El... |
[
"= %s)' mycursor.execute(query_string, query_list) elif matchedGames[b][5] == team0OddsInfo[a][0]: query_list = [team0OddsInfo[a][1], team1OddsInfo[a][1], matchedGames[b][0]]",
"- from the dates for the URLs, then making the URLs. todayShort =",
"(str(allGames[c][0]),) mycursor.execute(query_string, gameID) if ... |
[
"in out main(args.format('--copy path/to/file.txt /tmp/file.txt').split()) out, _ = capsys.readouterr() assert 'COPY [\"path/to/file.txt\", \"/tmp/file.txt\"]'",
"main(args.split()) with pytest.raises(SystemExit): main() args = \"generate -b ubuntu -p apt --ants option=value\"",
"neurodocker.main\"\"\" # Author... |
[
"# -*- coding: utf-8 -*- # # Copyright (C) 2020 The Project U-Ray",
"On name: The primitives you listed have a control input to set the",
"{\"1'b0\": 0, \"1'b1\": 1}[s] print(\"Loading tags from design.txt\") with open(\"design.txt\", \"r\") as f:",
"LUT5 FF is2 = '2' in ff_name if used: segmk.add_site_tag(si... |
[
"self._jac_metric = value @jac_metric.deleter def jac_metric(self): del self._jac_metric @property def grad_logdet_metric(self): return self._grad_logdet_metric",
"in the Euclidean case. \"\"\" def __init__(self, position: np.ndarray, momentum: np.ndarray): super().__init__(position, momentum)",
"from typing im... |
[
"Foundation; either version 2 # of the License, or (at your option) any",
"___/ ___/ __ `/_ / / _ \\ # +------+ / /_/ /",
"either pressing Ctrl-C or by holding your hand above the Crazyflie. For the",
"# as published by the Free Software Foundation; either version 2 # of",
"Street, Fifth Floor, Boston, # MA... |
[
"ugettext_lazy as _ USER_TYPE_STAFF = 'STAFF' USER_TYPE_ADMIN = 'ADMIN' USER_TYPE_BARBER = 'BARBER' USER_TYPE_CHOICES",
"_ USER_TYPE_STAFF = 'STAFF' USER_TYPE_ADMIN = 'ADMIN' USER_TYPE_BARBER = 'BARBER' USER_TYPE_CHOICES = (",
"'STAFF' USER_TYPE_ADMIN = 'ADMIN' USER_TYPE_BARBER = 'BARBER' USER_TYPE_CHOICES = ( ... |
[
"HTML5TestStorySet(story.StorySet): \"\"\" Chrome proxy test page for traffic over https. \"\"\" def __init__(self):",
"# Use of this source code is governed by a BSD-style license that",
"2016 The Chromium Authors. All rights reserved. # Use of this source code",
"code is governed by a BSD-style license that... |
[
"user credentials database with: user_id & password logger showing connection logs, DB version,",
"FROM websites WHERE url = \\'{}\\';' # url, popularity, visitations = database.fetch(database.command.get_site.format('https://www.python.org'))[0] #",
"{}'.format(sqlite3.version)) if commands is None: commands =... |
[
"import re_path from projectx.consumers import UserWebSocketConsumer from .consumers import UserWebSocketConsumer websocket_urlpatterns = [",
"from django.urls import re_path from projectx.consumers import UserWebSocketConsumer from .consumers import UserWebSocketConsumer websocket_urlpatterns",
"<gh_stars>0 fr... |
[
"AldrynSearchApphook(CMSApp): name = _(\"aldryn search\") def get_urls(self, *args, **kwargs): return ['aldryn_search.urls'] if settings.ALDRYN_SEARCH_REGISTER_APPHOOK:",
"name = _(\"aldryn search\") def get_urls(self, *args, **kwargs): return ['aldryn_search.urls'] if settings.ALDRYN_SEARCH_REGISTER_APPHOOK: app... |
[
"<filename>BizPy/openpyxl/20200513/horizontal_chart.py import pandas as pd from openpyxl import Workbook from openpyxl.chart import BarChart,",
"chart.type = 'bar' chart.style = 11 chart.shape = 4 chart.title = '都道府県別の人口' chart.x_axis.title",
"import BarChart, Reference wb = Workbook() ws = wb.active df = pd.re... |
[
"LogSourceSerializer(Serializer): def serialize(self, instance, attrs): return { 'id': instance.id.hex, 'job': { 'id': instance.job_id.hex,",
"LogSource @register(LogSource) class LogSourceSerializer(Serializer): def serialize(self, instance, attrs): return { 'id': instance.id.hex, 'job':",
"serialize(self, ins... |
[
"# # Licensed under the Apache License, Version 2.0 (the \"License\"); # you",
"writing, software # distributed under the License is distributed on an \"AS IS\"",
"NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version",
"governing permissions and # limitations under the Licen... |
[
"document.', long_description=long_description, license='BSD', author='<NAME>', author_email='<EMAIL>', url='https://github.com/jszakmeister/rst2ctags', version=version, py_modules=['rst2ctags'], zip_safe=True, entry_points={ 'console_scripts': [ 'rst2ctags",
"version=version, py_modules=['rst2ctags'], zip_safe=T... |
[
"to workspace deployments' attach_camera_parser = subparsers.add_parser('attach-camera', description=attach_camera_commanddesc, help=attach_camera_commanddesc) attach_camera_parser.add_argument('camera', default=0, type=int, help=('on Linux,",
"help='print version number and exit.') help_parser = subparsers.add_p... |
[
"v*(10**i) if (2**31 - 1>= d >= -(2**31)): return d else: return 0",
"p[ind] = val for i, v in p.items(): d += v*(10**i) if (2**31",
"1>= d >= -(2**31)): return d else: return 0 if x>=0: return (solve(x))",
"<reponame>kkcookies99/UAST class Solution: def XXX(self, x: int) -> int: def solve(x): a =",
"list(m... |
[
"= [] for i in range(limit): line = response[i]['address']['line'] city = response[i]['address']['city'] state",
"querystring, headers = headers,) return response_for_rent.json()['properties'] @router.get('/for_rent_list/{property_id}') async def property_detail(property_id: str = \"O3599084026\"):",
"= {\"prop... |
[
"dateTime >= %(start)s);\" sql_stmt = SQL_TEMPLATE % interpolate_dict print(sql_stmt) # Get the number",
"StartTime , b.dateTime as EndTime , b.dateTime-a.dateTime as TimeChange , b.ch8_a_energy2-a.ch8_a_energy2 as ValueChange",
"MIN(dateTime) FROM archive WHERE dateTime >= %(start)s);\" sql_stmt = SQL_TEMPLATE... |
[
"}] } def test_post_orders8(): response = client.post('/orders/', json={ \"isin\": \"blablablabla\", \"limit_price\": 0.2, \"side\":",
"\"isin\": \"blablablablabla\", \"limit_price\": 0.2, \"side\": \"buy\", \"quantity\": 1, \"valid_until\": 1996950863 }) assert response.status_code",
"}) assert response.status... |
[
"oldformat = 0)] line = subprocess.check_output([PUC, \"-n\", r, p, v, n]) matches =",
"#!/bin/python2 import collections import re import subprocess import sys PUC = \"../pamu2fcfg/pamu2fcfg\" resident",
"free_block + end.format(devices = len(credentials)) print(code) # Single credentials print >> sys.stderr, ... |
[
"x_value): x_value = np.array(x_value) x = array_ops.placeholder(dtypes.float32, name=\"x\") return sess.run(fun(x), feed_dict={x: x_value}) for",
"run(bijector.inverse, x)) self.assertAllClose([0., 0.], run(bijector.inverse_log_det_jacobian, x)) def testTwoBatchScalarIdentityViaScale(self): with self.test_sessio... |
[
"Download and install algod. \"\"\" node_package_dir = file_util.ensure_folder(f\"/tmp/algod-pkg-{time_util.get_timestamp()}\") data_dir = file_util.ensure_folder(data_dir) bin_dir =",
"goal_args = [ 'node', 'stop', ] print(f\"Stopping node with:\\n\\tdata_dir: {data_dir}\\n\\tkmd_dir: {kmd_dir}\") goal(data_dir,... |
[
"use it where you want it to fill out a parent widget of",
"if needed. \"\"\" from pyjamas.ui.SimplePanel import SimplePanel from pyjamas.ui.ScrollPanel import ScrollPanel from pyjamas.ui.HTML",
"from pyjamas.ui.ScrollPanel import ScrollPanel from pyjamas.ui.HTML import HTML from pyjamas.ui.VerticalPanel import... |
[
"your weaknesses and share your strengths. # May you share freely, never taking",
"than you give. # May you find love and love everyone you find.",
"share freely, never taking more than you give. # May you find love",
"taking more than you give. # May you find love and love everyone",
"False: try: query = w... |
[
"''' def __init__(self, config): self.config = config self.CallGoTCList = [] def create_testcase_list(self): '''",
"self.config.test_case['call'][k][0], rx_node_addr = self.config.test_case['call'][k][1], msg_id = self.config.test_case['call'][k][2], msg_class = self.config.test_case['call'][k][3], hdr_len = self... |
[
"get_cart from cart.forms import SelectProductForm, SetQtyForm @require_POST def _cart_action_view(request, action_factory, form_class, message): form",
"cart.printable_total }) def add(request): return _cart_action_view( request, action_factory=lambda cart, data: cart.add(**data), form_class=SelectProductForm, m... |
[
"3 ROOK = 4 QUEEN = 5 KING = 6 FIGURE_NAME = [",
"\"#FFB87A\") } #----- move types -----# NORMAL_MOVE, CAPTURE, PROMOTION, DOUBLE_STEP, ENPASSANT_CAPTURE, CASTLING, KING_CAPTURE",
"(22, 2) #----- castling -----# CASTLING_LEFT = 0 CASTLING_RIGHT = 1 #----- player",
"B3, C3, D3, E3, F3, G3, H3, \\ A4, B4, C4, D... |
[
"= env.step(action) total_reward += reward total_steps += 1 print(\"Currently %d steps, total reward",
"<reponame>kapzlok2408/Pokemon-Showdown-Node-Bot<gh_stars>0 import gym import gym_pokemon import random if __name__ == \"__main__\": env =",
"random.randint(-1,8) obs, reward, done, _ = env.step(action) total_... |
[
"print('O {} é maior que {}'.format(num1, num2)) elif num1 < num2: print('O {}",
"')) if num1 > num2: print('O {} é maior que {}'.format(num1, num2)) elif",
"int(input('Digite o 1º número: ')) num2 = int(input('Digite o 2º número: ')) if",
"if num1 > num2: print('O {} é maior que {}'.format(num1, num2)) elif ... |
[
":: OS Independent', 'Development Status :: 4 - Beta', 'Intended Audience :: Developers',",
"Independent', 'Development Status :: 4 - Beta', 'Intended Audience :: Developers', ], install_requires=[",
"'Operating System :: OS Independent', 'Development Status :: 4 - Beta', 'Intended Audience",
"), long_descrip... |
[
"= app.MemorySuppressionSummary.all() monthly_timestamp = datetime.date.today().replace(day=1) query.filter('monthly_timestamp =', monthly_timestamp) query.order('monthly_timestamp') query.order('-%s' % sort) if",
"name, values): \"\"\" Wrapper for template.render that updates response and knows where to",
"lin... |
[
"= workspace.FetchBlob(\"out\") np.testing.assert_array_almost_equal(out, X * Y) self.assertDeviceChecks(dc, op, [X, Y], [0]) self.assertGradientChecks(gc, op,",
"array increased by one dim def powt_op_mixed(X, Y): return powt_op(X, Y[np.newaxis, :, :,",
"\"SumReduceLike\", [\"X\", \"Y\"], \"out\", broadcast=1,... |
[
"[ \"ansible/overcloud-host-image-workaround-resolv.yml\", \"ansible/seed-introspection-rules.yml\", \"ansible/dell-switch-bmp.yml\", ], ), ] self.assertEqual(expected_calls, mock_run.call_args_list) expected_calls = [ mock.call(",
"extra_vars={ \"ansible_python_interpreter\": \"/usr/bin/python\", \"ansible_user\... |
[
"tensor_shape] def dump_graph_into_tensorboard(tf_graph): # type: (_tf.Graph) -> None _tb_log_dir = os.environ.get('TB_LOG_DIR') if _tb_log_dir:",
"License. See License.txt in the project root for # license information. ############################################################################### import",
"pr... |
[
"\"\"\" # Needed for python2 / python3 print function compatibility from __future__ import",
"the # webserver 'http_method': 'GET', # 'http_method': 'PUT', # total duration, in nanoseconds.",
"PUT: Standard HTTP upload, the wireless endpoint will push data to the #",
"duration, in nanoseconds. # This is the d... |
[
"in doc.findall(\"kretsar/krets/startpoints/number\"): startnumbers[n.text] = True for p in doc.findall(\"points/point\"): number = p.find(\"number\").text if",
"None: print(\"** error: no distance: src: %s dst: %s\" % (src, dst)) properties",
"int(src) > MAXPOINT or int(dst) > MAXPOINT: continue if int(src) < ... |
[
"= {} self.filesystems = [] plugin_files = load_conf_list(plugin_config('files', default='[]')) self._load_from_files(plugin_files) self.plugin_files = plugin_files",
"rv._registry.get_file_system(uri, search_plugins=False) local_path = download_if_needed(uri, plugin_path, fs=fs) local_dir = os.path.dirname(local... |
[
"from __future__ import print_function from absl import app from absl import flags import",
"// 2, 16) up = nb.upconv2d(inner_nc, outnc) decoder.append(up) inner_nc = outnc up =",
"absolute_import from __future__ import division from __future__ import print_function from absl import app",
"import torchvision ... |
[
"and the following disclaimer in the documentation # and/or other materials provided with",
"# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR #",
"awkward.util.numpy.bitwise_and(out, tmp.y < tolerance) out = awkward.util.numpy.bitwise_and(out, tmp.z < tolerance) return out class",
... |
[
"\"\"\" Implements a non interactive controller to controt non-interactive visualizers. (i.e. those that",
"self.vis.visualize(page.next_line(), eop) if eop: break def close(self): \"\"\" Todo: ApiDoc. :return: \"\"\" self.vis.close()",
"input: :param output: :param visualizer_class: \"\"\" super(ConversionCont... |
[
"data=sum_data) return [response.json(), response_sum.json()] if __name__ == '__main__': cs = CovidScraper() results =",
"BeautifulSoup(page.content, 'html.parser') return soup def scrape_page_content_contains_tests(self): page = requests.get(self.scrape_tests_url) soup = BeautifulSoup(page.content, 'html.parser'... |
[
"os from PIL import Image DATEI_WEB_GROSSE = 700 def isimg(isitimg): ext = os.path.splitext(isitimg)[1].lower()",
"float(img.size[1]) * float(wrel) ) splt = os.path.splitext(datei) newfilename = splt[0] + splt[1].lower() img",
"float(wrel) ) splt = os.path.splitext(datei) newfilename = splt[0] + splt[1].lower()... |
[
"flamewreath(self, ctx): \"\"\"I will not move when Flame Wreath is cast!\"\"\" await self._play(\"https://www.youtube.com/watch?v=gcA6y7sxKcA\",",
"url_or_search_terms=url) @commands.command(pass_context=True, no_pm=True) async def flamewreath(self, ctx): \"\"\"I will not move when Flame",
"no_pm=True) async d... |