sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
c8afabb30b267c005cea7350fcc7c285c1079485848ed403ade9e7018dda1762 | Python | 11,076 | 251 | # -*- coding: utf-8 -*-
"""
Created on Wed Sep 20 16:48:57 2023
@author: Ed"""
import sys
import pandas as pd
import numpy as np
from scipy.optimize import curve_fit
import matplotlib.pyplot as plt
import cv2
import os
#Main function is here
def CalcWarpRemap(pointFile, remapfile, projx, projy, im... |
4913ae19eab682b6449a18657888ee2fc06c60e81edef39f55cf8431356f2868 | Python | 11,079 | 318 | """ Convert PASCAL VOC XML-type dataset to TFRecords for Tensorflow object_detection.
Example usage:
python convert_pascal_to_tfrecords.py \
--images_dir "./data/scales_data_sample/images/"\
--annotations_dir "./data/scales_data_sample/annotations/"\
--image_set_file "./data/scales_data_sample/image_s... |
a05e3275295522df168492d1c390a680081d36447172285e0388ee8d94b5092b | Python | 11,079 | 407 | from chreyesees import plot_utils
import seaborn as sns
import numpy as np
import proplot as pplt
from itertools import product
from chreyesees.palettes import CMAP_CELLS
from chreyesees.plot_tetrahedron import plot_tetrahedron
RADIUS = 0.1
WIGGLE = 1
TRANSFORM_FUNC = lambda x: x
POINT_SIZE = 3
POINT_OFFSET = 3.5
def... |
7b956d3bcc3581ee5ff369369d4ef2f1f45567d5ffda38c2735304b707ad1947 | Python | 11,085 | 192 | import os
import pytest
from perses.tests.utils import enter_temp_directory
@pytest.mark.gpu_needed
def test_RESTCapableHybridTopologyFactory_repex_neutral_mutation():
"""
Run ALA->THR and THR->ALA repex with the RESTCapableHybridTopologyFactory and make sure that the free energies are
equal and opposite.
... |
8c47b4950854709c412049f91cd44b2f2226e918c6499224e9f16ca9f5c9c8f6 | Python | 11,087 | 207 | """DDSurfer surface prediction for white-matter and pial cortical surfaces."""
from __future__ import annotations
import argparse
from contextlib import nullcontext
import logging
from pathlib import Path
import sys
import time
import nibabel as nib
import numpy as np
import torch
from inference.coordinates import G... |
e34247aced0043cb85a74dbffaf0fe3df9395909985d4fafbea92303d928f856 | Python | 11,090 | 252 | from typing import Sequence, Union, Any
from collections import OrderedDict
from numpy import inf, exp
import pandas as pd
from hbayesdm.base import TaskModel
from hbayesdm.preprocess_funcs import dbdm_preprocess_func
__all__ = ['dbdm_prob_weight']
class DbdmProbWeight(TaskModel):
def __init__(self, **kwargs):... |
01978b7dba644b77e9f4477a1ade29376a108a9c68a5ca3deb3eca44ac19fa0d | Python | 11,098 | 344 | import torch
import torch.nn as nn
from torchvision import models
import torch.nn.functional as F
from .resnet_model import *
class RefUnet(nn.Module):
def __init__(self,in_ch,inc_ch):
super(RefUnet, self).__init__()
self.conv0 = nn.Conv2d(in_ch,inc_ch,3,padding=1)
self.conv1 = nn.Conv2... |
324a05f257448d19b4f35043497750feb809a80fe07f5e004491ac0181560214 | Python | 11,098 | 258 | import argparse
import logging
import os
import random
import shutil
import sys
import time
import numpy as np
import torch
import torch.backends.cudnn as cudnn
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from tensorboardX import SummaryWriter
from torch.nn import B... |
14a6794c904b81a4f80f173101adce2022ba0cc137f4792e55b2b6c28b8bee90 | Python | 11,100 | 453 | from collections.abc import AsyncIterator, Iterator
from typing import Any
from langchain_core.messages import AIMessageChunk
from langchain_core.output_parsers.openai_functions import JsonOutputFunctionsParser
GOOD_JSON = """```json
{
"foo": "bar"
}
```"""
JSON_WITH_NEW_LINES = """
```json
{
"foo": "bar"
}... |
59de8f46324c2a72f39fbabbea0b7bd41dbad0458405f4b685e18dc121091739 | Python | 11,100 | 249 | import torch
from stable_baselines3.common.policies import BasePolicy
import torch as th
import gym
from gym import spaces
import math
import random
from stable_baselines3.common.preprocessing import get_action_dim, is_image_space, maybe_transpose, preprocess_obs
from stable_baselines3.common.type_aliases imp... |
2c7cefe8bc109338fb36714ad155d57013be74ec86f08de9b1df79943bc55a9e | Python | 11,102 | 251 | from typing import Sequence, Union, Any
from collections import OrderedDict
from numpy import inf, exp
import pandas as pd
from hbayesdm.base import TaskModel
from hbayesdm.preprocess_funcs import ts_preprocess_func
__all__ = ['ts_par7']
class TsPar7(TaskModel):
def __init__(self, **kwargs):
super().__... |
075bc5b60fb364f9d0eb55171c2248c172458852143ff97f678d77cc1e1ba499 | Python | 11,103 | 334 | #!/usr/bin/env python
# command line args
import argparse
PARSER = argparse.ArgumentParser()
PARSER.add_argument("data_file")
PARSER.add_argument("extras_file", nargs='?')
PARSER.add_argument("--color_map", dest='color_map', default='seismic',
help="Name of a matplotlib color map.")
PARSER.add_argument("--mult... |
7c2a49f72776f10a2603247304c0d38e7e9e465d1e0e6d210918ff59edbdfcda | Python | 11,104 | 266 | #!/usr/bin/env python
# coding: utf-8
"""
Original Author: Anthony Juliano, acjulian@uvm.edu
Wrapper Author: Greg Conan, gconan@umn.edu
Wrapper Created: 2021-06-22
Wrapper Updated: 2021-11-12
"""
# Import standard libraries
from glob import glob
import os
import pandas as pd
import shutil
import subprocess
import sys... |
8d234c4dc80b22a4a511247155c168ed21df6612c794dbcac344c84291e16bfc | Python | 11,109 | 261 | import sys
import argparse
import pyBigWig
import pyfaidx
import subprocess
import pandas as pd
import numpy as np
import itertools
import warnings
from termcolor import colored
import os
from modisco.visualization import viz_sequence
import chrombpnet.training.utils.one_hot as one_hot
from chrombpnet.data import Defau... |
e2f62fca764eaad85d727320877d005e0898cf602c26ec281190426698a6a311 | Python | 11,112 | 152 | """FINAL confirmatory CPU run (5 seeds). Produces:
results/final_point.csv Ridge / GBDT (abs, anchored) x P1-P4 x fold x seed x test dataset (MAPE, RMSE, MAE)
results/final_conformal.csv GBDT-anchored intervals under P3 and P4: split / mondrian(dataset) / cqr / weighted / shift-matched
... |
a3484442b658981b21d02d1eea8014cf03852ca817669971cd78ded5477723e8 | Python | 11,118 | 301 | """Output parser for XML format."""
import contextlib
import re
import xml
import xml.etree.ElementTree as ET
from collections.abc import AsyncIterator, Iterator
from typing import Any, Literal
from xml.etree.ElementTree import TreeBuilder
from typing_extensions import override
from langchain_core.exceptions import ... |
dc226fbe8c15feab60ef6ffdc051a872c05509becac8c044b5b8ce81dc235272 | Python | 11,122 | 249 | import torch
from stable_baselines3.common.policies import BasePolicy
import torch as th
import gym
from gym import spaces
import math
import random
from stable_baselines3.common.preprocessing import get_action_dim, is_image_space, maybe_transpose, preprocess_obs
from stable_baselines3.common.type_aliases imp... |
c4eef37f2c19ff3c583b9d663838e23e9581db3a61a8110b2adb2558903640fa | Python | 11,123 | 294 | import torch
import numpy as np
import torch.nn as nn
from timm.models.layers import trunc_normal_
from pdearena.models.transolver.model.Embedding import timestep_embedding
from pdearena.models.transolver.model.Physics_Attention import Physics_Attention_Structured_Mesh_2D
from pdearena.configs.config import CFDConfig
f... |
87d1f9c2ab965a948adee4416ea3f44477aa9c79cccd27f63926d7bbc2a0a78e | Python | 11,128 | 249 | import torch
from stable_baselines3.common.policies import BasePolicy
import torch as th
import gym
from gym import spaces
import math
import random
from stable_baselines3.common.preprocessing import get_action_dim, is_image_space, maybe_transpose, preprocess_obs
from stable_baselines3.common.type_aliases imp... |
e5f0b9ddfcfcebca23b7c98ace5ffff93801db4189ea12573c4225a1498f024a | Python | 11,134 | 297 | import torch
from torch.distributions.categorical import Categorical
import numpy as np
from egnn.models import EGNN_dynamics_QM9, EGNN_encoder_QM9, EGNN_decoder_QM9
from equivariant_diffusion.en_diffusion import EnVariationalDiffusion, EnHierarchicalVAE, EnLatentDiffusion
import pickle
from os.path import join
def... |
558c2900ad853545632d120b91dddc17cd57cb9101dceb8dbed3abdb5dce4892 | Python | 11,139 | 324 | """Parsers for OpenAI functions output."""
import copy
import json
from typing import Any
import jsonpatch # type: ignore[import-untyped]
from pydantic import BaseModel, model_validator
from pydantic.v1 import BaseModel as BaseModelV1
from typing_extensions import override
from langchain_core.exceptions import Outp... |
7e2e42ef05ebf6e8b659e98cbb627916884f0f081d837afc06990a7d8f0c2ce1 | Python | 11,147 | 392 | # Copyright 2021 AlQuraishi Laboratory
# Copyright 2021 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# U... |
3cbf77d15b6def4548d4f89140ba1e69fd4f08ce733732def5053c991c5f4e32 | Python | 11,151 | 269 | """Test all ConvNet capabilities."""
import pytest
import numpy as np
import copy
import logging
import os
import shutil
import torch
import torch.nn as nn
from torch.utils.data import DataLoader, Subset, TensorDataset
import vulcanai
from vulcanai.models import BaseNetwork
from vulcanai.models.cnn import ConvNet, Co... |
18898029d76f283b073b1600df3a50908346e3ba558110e5104000d93acc797b | Python | 11,154 | 338 | #!/usr/bin/python
#############################################################################
#Package: stamp
#Updated by Yiqin Wang
#Usage:
#summarize read coverage for whole-genome sequencing data
#
##############################################################################
import os, sys
import time
... |
41d89515bd238459f43f0b7e857db0321ea25464faa8d17d358e8c1095fe5865 | Python | 11,154 | 347 | """Base classes for media and documents.
This module contains core abstractions for **data retrieval and processing workflows**:
- `BaseMedia`: Base class providing `id` and `metadata` fields
- `Blob`: Raw data loading (files, binary data) - used by document loaders
- `Document`: Text content for retrieval (RAG, vect... |
da6130e7c5f140d165c8c7382b54aa3bbd26b19ee358ade58e6da76ef38f3565 | Python | 11,166 | 256 | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
thresh = None # neuronal threshold
decay = None # decay constants
num_classes = None
batch_size = None
learning_rate = None
lr_decay = None
num_epochs... |
8f8b3b3578c90f2a480cbc8eb50a728db7f130eea8cbffb20794a47bb0fa4a49 | Python | 11,169 | 402 | import scipy.stats as ss
from SMdRQA.RQA_functions import entropy
from SMdRQA.RQA_functions import average
from SMdRQA.RQA_functions import maxi
from SMdRQA.RQA_functions import mode
from SMdRQA.RQA_functions import percentmorethan
from SMdRQA.RQA_functions import diaghist
from SMdRQA.RQA_functions import onedhist
from... |
640891adff1c045bed111a4d461ce23b9ec815067cef447a9d04b3e64239f0dd | Python | 11,170 | 316 | import torch
import torch.nn as nn
import torch.nn.functional as F
from time import time
import numpy as np
def timeit(tag, t):
print("{}: {}s".format(tag, time() - t))
return time()
def pc_normalize(pc):
l = pc.shape[0]
centroid = np.mean(pc, axis=0)
pc = pc - centroid
m = np.max(np.sqrt(np.s... |
ae70a0b4b4a979d8e777fa04514b229f1ce9868891eaaabe39a2dd1126d02958 | Python | 11,171 | 246 | """
Analyze relationship between the subject's learning rate
and model variable (cpp, uncertainty) at the group level.
"""
import argparse
import data_analysis_utils as dana
import itertools
import matplotlib.pyplot as plt
import matplotlib.ticker
import model_learner as model
import numpy as np
import os.path as op
i... |
19e2ae45b5a5777d83f4b457d93179dec4183b27994810c56f2757e983b82222 | Python | 11,177 | 328 | """**Retriever** class returns `Document` objects given a text **query**.
It is more general than a vector store. A retriever does not need to be able to
store documents, only to return (or retrieve) it. Vector stores can be used as
the backbone of a retriever, but there are other types of retrievers as well.
"""
fro... |
094ef0fed8474969c9bdcd97a1c679f3afff0afa242519152a2a61d6ad94c890 | Python | 11,181 | 318 | """SSRF protection policy with IP validation and DNS-aware URL checking."""
import asyncio
import dataclasses
import ipaddress
import os
import socket
import urllib.parse
from langchain_core._security._exceptions import SSRFBlockedError
# ---------------------------------------------------------------------------
# ... |
3e2644a68f69df6b7d0eacec31b3e02124b9bc3eb10ec73db6fc24c480c8083d | Python | 11,182 | 418 | import warnings
import numpy as np
import numpy.testing as np_test
import pytest
from skbase.utils.dependencies import _check_soft_dependencies
from pgmpy import config
from pgmpy.example_models import load_model
from pgmpy.factors.discrete import TabularCPD
from pgmpy.models import DiscreteBayesianNetwork
from pgmpy... |
43956a5507f05a72ae80a8a33a1841e35d0927a6df106d6a085bb941246588a1 | Python | 11,184 | 303 | # MIT License
# Copyright (c) 2021 Yuyang Wang
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, pu... |
71cddc47a87306326ab44babcf3b873ba22ec4a31f0dd207f30d0d2c697cadbe | Python | 11,185 | 299 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
ae_head_predictor.py
====================
Drop-in leaderboard-compatible wrapper that:
1. Trains a BERNN AE encoder (using TrainAEClassifierHoldout).
2. Freezes the encoder and extracts train / test embeddings.
3. Sweeps all classification heads (XGBoost, RF, SVC... |
a6eebad898e7ddcc4888428dbd87c3d87b3001964473193cea527bdb0cb5f100 | Python | 11,188 | 272 | """Test all DenseNet capabilities."""
import pytest
import numpy as np
import copy
import logging
import os
import shutil
import torch
import torch.nn as nn
from torch.utils.data import DataLoader, Subset, TensorDataset
import vulcanai
from vulcanai.models import BaseNetwork
from vulcanai.models.dnn import DenseNet, ... |
ade9054a8231c3e01cf24dba0a82ba849cbdf498eaf80cd6a2b8ad64cc95e8f0 | Python | 11,195 | 254 | import torch
import numpy as np
import copy
from ._base import register_transform, _get_CB_positions
from rde.utils.transforms.select_atom import chi_atom15_index_map,atom15to37_index_map
from rde.utils.protein.dihedral_chi import atom37_to_torsion_angles, AA_TO_INDEX, ALL_ATOMS, ALL_ATOM_POSNS,ONE_TO_THREE, CHI_PI_P... |
204bad1c59e3bd3b8378b4c708d7d00945eb0412a28f4225b8216acac772af1a | Python | 11,203 | 258 | # this script runs image segmentation of AMF dataset based by transfer learning
# Mask-RCNN on detectron2:
import argparse
import os
import random
import shutil
import time
import warnings
import pickle
import numpy as np
import math
import sys
import copy
import re
import pandas as pd
import matplotlib.pyplot as plt
i... |
42ffb98a31f0b7898d22bbd57d5dbcaa83eb916bb9759963873a4a7d9dd0adc1 | Python | 11,211 | 409 | # Flask server to provide read access to image volumes and read/write access
# to annotations stored in a provided path.
#
# This file can be run in two ways:
# 1. For development, use flask run annotator.py
# 2. For production, use annotator [OPTIONS]
"""
This provides a webpage to label key-points in a given datase... |
b928e8578779eb2ba7abf800d486a81977df9ef02853604293931fe64cd0a287 | Python | 11,212 | 316 | import torch
import torch.nn as nn
import torch.nn.functional as F
from time import time
import numpy as np
def timeit(tag, t):
print("{}: {}s".format(tag, time() - t))
return time()
def pc_normalize(pc):
l = pc.shape[0]
centroid = np.mean(pc, axis=0)
pc = pc - centroid
m = np.max(np.sqrt(np.s... |
790cefce3cff88a1e7d77fe4e41070eca64c8440f98a2c093a4644f1db3f8889 | Python | 11,213 | 216 | """TabFM / XGBoost vs DeepMapper head-to-head, classification metrics (exploration).
Adds two tabular classification METHODS alongside DeepMapper's differentiable
backbones and compares them on the four-way CD4 T-subtype task
(Helper / Treg / Naive / Memory):
- TabFM: the Google-Research tabular foundation model (in... |
f8c82432c057e0b8815036580d41db39aef283f617d0fe1218408e6add4562d1 | Python | 11,215 | 281 | """
2023.09.11
author: jonas.braun@epfl.ch
Plotting functions to analyse which behaviours and VNC projections are included in which cluster
"""
import os, sys
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib as mpl
import pickle
import tqdm
import params
linewidth = 2
mpl.rcPa... |
f5acb6b066c1eb20141ebf350512a959c039dc719b2b9d59e70ea7fbce8ab196 | Python | 11,220 | 302 | from collections import namedtuple
import h5py
import numpy as np
from scipy.signal import convolve2d
from torch.utils.data import Dataset
from ..transforms import DataTransform, Delay, MovieTransform, Subsequence
from ..utils import recursively_load_dict_contents_from_group
from .base import (
AttributeTransform... |
f6810f3961c19863d311526c9aa5f8c5b4e61caa33fe657d4e9691e53204efda | Python | 11,226 | 312 | import numpy as np
import torch
import torch.nn as nn
################################################################################
# Custom attention layers. #
################################################################################
class TransformerLay... |
479d72c880714df78551bacc78cd63d3b44cbe21973e7036ecb6fab7fad0419b | Python | 11,229 | 301 | # coding=utf-8
import torch
import torch.distributed as dist
from torch.utils.data import Dataset, DataLoader, Sampler, DistributedSampler
from typing import Iterator, List, Optional, Union
from collections import Counter
from operator import itemgetter
import numpy as np
class _InfiniteSampler(torch.utils.data.Sample... |
542ea107a7cd0c2d8a7f5f09c7ee83eab6e6ef2c9fe6b4405f145706cdc0be64 | Python | 11,240 | 348 | from copy import deepcopy
from typing import Dict, Optional, Sequence, Union
import numpy as np
import torch
import torch.nn as nn
from torch.nn.modules.utils import _pair
import bindsnet.network.nodes as nodes
import bindsnet.network.topology as topology
from bindsnet.conversion.nodes import PassThroughNodes, Subtra... |
c774c0ab822982844f51a05a71e6e6a45476d7a810aa0597a7ab4560b5e64ebc | Python | 11,242 | 259 | # this script runs image segmentation of dataset based by transfer learning
# Mask-RCNN on detectron2:
import argparse
import os
import random
import shutil
import time
import warnings
import pickle
import numpy as np
import math
import sys
import copy
import re
import pandas as pd
import matplotlib.pyplot as plt
impor... |
e9236fa8a01d6538efae077c05dcc7136d59b78158eaa6f60505d1bb87df76c5 | Python | 11,246 | 231 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
POCIF-BAT R2 — H-R2-1, transformation T2 : contrôle d'histoire identique.
MOTIF DE LA TRANSFORMATION, déclaré avant retest, fondé sur une mauvaise
spécification statistique de T1-b et non sur son résultat.
T1-b comparait des η² entre facteurs comportant 4, 12 puis 24... |
64c3bed04bd29af0b9dd57a07085c6df8ce2483fbb377c01ce5ef9b38f6156b7 | Python | 11,247 | 310 | import MDAnalysis as mda
import numpy as np
from MDAnalysis.analysis import align
# -- Functions to preprocess trajectories --
def extract_coordinates(top, pdb, trj_list, out_name, sel_string, start_frame=0,
rename_segments=None, residues_offset=0):
"""
Extracts selected coordinates ... |
b69d05ed4c871165d47caf099e211488157f3892113c2a0c44d7e380e365a022 | Python | 11,252 | 337 | # -*- coding: utf-8 -*-
#
# Gpipe documentation build configuration file, created by
# sphinx-quickstart on Mon Jul 20 11:17:20 2009.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All... |
7c6f2f6058bc0d4c9901bedefc9fbc678549795c955a37b2fbe5756033af4222 | Python | 11,254 | 330 |
'''cgat_ruffus_profile.py - analyze ruffus logfile
==================================================
Purpose
-------
This script collects information about tasks that have completed or
are still running in a pipeline. It works by examining the logfile
:file:`pipeline.log` looking for the last active run. It will c... |
d1cdeb4d8118ec0ca9d0e8dede17b8efd644510f4755a4ce0d9cd959d2689bc9 | Python | 11,255 | 310 | import errno
import json
import random
import shutil
import tempfile
import zipfile
from collections import defaultdict
from pathlib import Path
import pydicom
from MRdataset.dicom_utils import is_bids_file
from MRdataset.tests.config import compl_data_xnat
from MRdataset.utils import convert2ascii
# from bids import... |
f20135882204c17ce0130ee94a39ea21578040a5c7709f1e9cf1f2dec7a813c2 | Python | 11,256 | 277 | import logging
from pathlib import Path
from functools import wraps, partialmethod
from typing import Tuple, List, Optional
import haiku
from alphafold.model import model, config, data
from alphafold.model.modules import AlphaFold
from alphafold.model.modules_multimer import AlphaFold as AlphaFoldMultimer
logger = log... |
6955c8c5108fdb946accb86bcc0a1ea638ba58d581f9827c30595fdba2741744 | Python | 11,259 | 406 | '''ucsc.py - Tasks for accessing UCSC data
==================================================
This module provides methods for accessing ucsc_ data via the public
UCSC relational database server and building UCSC track hubs.
The function :func:`connectToUCSC` establishes a connection.
Data import
-----------
The fu... |
e1500d879655533cfb9aadbeb7dafd088b68e78e0b7a86bebba81eee0006884d | Python | 11,259 | 373 | '''
This is a simple pipeline to demonstrate how ruffus is used to control
the flow of data through a series of functions.
There is a PowerPoint presentation with details of all the ruffus decorators
and which goes through the functions in this pipeline one by one at
https://www.cgat.org/downloads/public/training/cgat... |
b316f4b5dab307542835236f5bc2b4af29bbb24ea2dd082395a270ad43ede222 | Python | 11,264 | 288 | """Equations related to Navier Stokes Equations with coordinate transformation
"""
from sympy import Symbol, Function, Number
from modulus.eq.pde import PDE
from modulus.node import Node
from typing import Optional, Callable, List, Dict, Union, Tuple
from modulus.key import Key
class NavierStokes_CoordTr... |
c4d392243b90e9d678504e08751c83faaf430c99a8df6c640182fdc7260811ba | Python | 11,278 | 325 | # A collection of tools to remotely access a CATMAID server via its API
#
# Copyright (C) 2017 Philipp Schlegel
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of ... |
8647bd7cb7fe098696634f4875f04de301f9c792107add4a3b65b0d87cf3416a | Python | 11,283 | 221 | """Validate a pipeline run before starting expensive image processing."""
import hashlib
from importlib import metadata
import json
import os
from pathlib import Path
import shutil
from preprocessing.inputs import fingerprint, validate_diffusion_inputs, validate_mask
from utils.files import sha256_file
ROOT = Path(_... |
5d8c052643bb71c978f4b3a1a2d4efe4918b233531508b2f0434b7e512ee9a6f | Python | 11,294 | 313 | """
:AUTHOR: Jonas Scherer
:ORGANIZATION: Department of Neurobiology and Department of Cognitive Neuroscience, Bielefeld University, Germany
:CONTACT: jonas.scherer@uni-bielefeld.de
:SINCE: Mon Dec 12 11:08:00 2022
:VERSION: 0.1
This module contains helper functions.
"""
import numpy as np
import pandas as pd
import ... |
dc0cc33e5615158bea326278746a4c49197af0fcd5b5c95165fbc7bd814078b6 | Python | 11,313 | 288 | import math
from typing import Callable
import numpy as np
import torch
import torch.nn as nn
###############################################################################
# Adapted from diffusion transformer: https://github.com/facebookresearch/DiT #
##############################################################... |
5a2ad5713cdc7db3414735127a846732a3014b7caa31240cb6685aa5acb46f8a | Python | 11,322 | 269 | from typing import Optional, Any
import torch
from torch import Tensor
from torch.nn.parameter import Parameter, UninitializedParameter, UninitializedBuffer
from torch.nn import functional as F
from torch.nn import init
from torch.nn.modules._functions import SyncBatchNorm as sync_batch_norm
from torch.nn.modules.laz... |
160d99a5384258c8ff26de4e5fab9a6f0085924a155024a4709421f86123f12c | Python | 11,329 | 301 | """
Create Hypergraph (H: incidence matrix)
GeneHypergraph: return Hypergraph
SmileHypergraph: return Hypergraph, subgraph per smile
"""
import numpy as np
import pandas as pd
import networkx as nx
import pathlib
import pickle
import re
from rdkit import Chem as rdkChem
import sklearn.feature_extraction as skfet
imp... |
7a0c2efd54b33b713154d9801a0d5ba35dcf6b17a201cc8753f9a86f647e356c | Python | 11,335 | 252 | """Tests for motornet.skeleton — PointMass and TwoDofArm."""
import numpy as np
import pytest
import torch
from motornet.skeleton import PointMass, TwoDofArm
from motornet.effector import ReluPointMass24, RigidTendonArm26
from motornet.muscle import RigidTendonHillMuscleThelen
# ====================================... |
b9bb0257b6be5700fa2d3421ee7c540504220a330902656186004775d8c36fe1 | Python | 11,335 | 253 | from typing import Sequence, Union, Any
from collections import OrderedDict
from numpy import inf, exp
import pandas as pd
from hbayesdm.base import TaskModel
from hbayesdm.preprocess_funcs import cgt_preprocess_func
__all__ = ['cgt_cm']
class CgtCm(TaskModel):
def __init__(self, **kwargs):
super().__i... |
99085070bc0c997b1d71afb5928c9369d60ca5b9b8112acade5030036717a816 | Python | 11,339 | 309 | # Calibration methods including Histogram Binning and Temperature Scaling
import numpy as np
from scipy.optimize import minimize
from sklearn.metrics import log_loss
import pandas as pd
import time
from sklearn.metrics import log_loss, brier_score_loss
from keras.losses import categorical_crossentropy
from os.path im... |
7b96b7cb204ea470cb74c63432b4bd00c9db5ca2834089e3a527233e798b75ab | Python | 11,347 | 311 | import shap
import argparse
import os
import shutil
import numpy as np
import matplotlib.pyplot as plt
import torch
from torch.utils.data import DataLoader
import torch.nn.functional as F
from matplotlib.colors import LinearSegmentedColormap
import alg
from alg import alg, modelopera
from utils.util import set_random... |
d421f31cca676fbfa4342c97fc6bb012480851b4d5910cdb5e40b0f81edcd4e4 | Python | 11,350 | 307 | import os
import sys
import time
import warnings
import zipfile
from urllib.request import urlretrieve
import cv2
import numpy as np
from torch.utils.data import Dataset
from bindsnet.datasets.preprocess import (
BoundingBox,
Rescale,
bgr2rgb,
crop_sample,
cropPadImage,
)
warnings.filterwarnings(... |
87c1c3ae13a04ed84f1eaeeb04ffd49eeda4fb94487001f2f73660d3d689308c | Python | 11,351 | 277 | #!/usr/local/bin/env python
"""
Test iodrivers.py facility.
"""
# =============================================================================================
# GLOBAL IMPORTS
# =============================================================================================
import numpy as np
try:
from openmm imp... |
c86de8831e4d3d2f57bf9fac332b8f890abea3a939e905bb9fe04a779aebf1ba | Python | 11,354 | 296 |
import matplotlib.pyplot as plt
import numpy as np
import skvideo.io
import mediapipe as mp
import os
from tqdm import tqdm
import pkg_resources
from mediapipe.framework.formats import landmark_pb2
from mediapipe import solutions
from PoET.mediapipe_landmarks import prepare_empty_dataframe
def load_models(min... |
72f48031ccff0df76c81b0462436b5bc44290a2faae10f60c740d94ef1fa908a | Python | 11,358 | 300 | import logging
import time
import dask.distributed as distributed
# Instantiate logger
logging.basicConfig(level = logging.NOTSET)
_logger = logging.getLogger("parallelism")
_logger.setLevel(logging.INFO)
class Parallelism(object):
"""
This class maintains a running parallelism (with support for the paralleli... |
196b0dccc11b83324e474ffb479bbf9ca498d73564a9b394e3d097d3e62dd571 | Python | 11,359 | 413 | # -*- coding: utf-8 -*-
"""
Created on Mon May 24 15:13:58 2021
@author: xiao208
"""
# -*- coding: utf-8 -*-
"""
Created on Mon Nov 11 10:54:28 2019
@author: dalan
list of unit and default parameters:
time: ms
voltage: mV
current: uA/cm^2
capacitance: uf/cm^2
conducrance: mS/cm^2
Cm = 1 uF... |
35f7b1541a58a004900592cc3caa17eb7425ff3435a158d9b098d0601e9e6110 | Python | 11,367 | 315 | """Chain that interprets a prompt and executes python code to do math."""
from __future__ import annotations
import math
import re
import warnings
from typing import Any
from langchain_core._api import deprecated
from langchain_core.callbacks import (
AsyncCallbackManagerForChainRun,
CallbackManagerForChainR... |
2733bbd7cafba40f0450d7fe0d86a4baeed5ad49303e65773e0baf29fa23d706 | Python | 11,369 | 274 | import math
from e3nn import o3
from typing import Optional, Tuple, Union
import torch
import torch.nn.functional as F
from torch import Tensor
from torch_sparse import SparseTensor
import torch.nn as nn
from torch_geometric.nn.conv import MessagePassing
from torch_geometric.typing import Adj, OptTensor, PairTensor
f... |
7b6845ba31dac2cac43e08459367cb58d504bd4ae2368fd4a4730c880393ecd0 | Python | 11,371 | 230 | #! /bin/env python
#
# Michael Gibson 17 July 2015
# Modified Adrian Foy February 2021
# Modified jz103 Dec 20 2021
# Modified jz103 Feb 10 2022
import sys, struct, math, os, time
import numpy as np
from .intanutil.read_header import read_header
from .intanutil.get_bytes_per_data_block import get_bytes_per_data_block... |
6a4701e76da2f2882930fecf27f0144245cd4c490304db34ace222ab20eb0395 | Python | 11,374 | 244 | """entry point for the standalone exe.
runs the same FastAPI app as a local server and opens it in a native window
with pywebview. this file (plus a pyinstaller spec) is basically the entire
desktop-specific part of this project - everything else is shared with the
web version.
"""
import json
import os
import platfo... |
052d970762cebcc2a9c7beab358bfb3aeac9d3f681896c2912bb137b57b97f42 | Python | 11,379 | 239 | """
Plot the individual sequences (outcomes, estimates, and generative value)
for each session of the given subject data file.
"""
import argparse
import data_analysis_utils as dana
import matplotlib.pyplot as plt
import numpy as np
import os.path as op
import plot_utils as plut
FIGSIZE = (plut.A4_PAPER_CONTENT_WIDTH... |
d178c731cdf0444f9d596a4754bbd66aa980fc991d5b297436ab8e448d61aae8 | Python | 11,387 | 233 | """
Functions to generate plots to analyse the imaging of command neurons in intact and headless flies.
Author: jonas.braun@epfl.ch
"""
import os
import sys
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib as mpl
from matplotlib.backends.backend_pdf import PdfPages
import pickle... |
132d0260f9189396779113a9ec7ac6abfa1b438b576f73fb5c6b238824d42031 | Python | 11,388 | 249 | """
This module implements `tensorflow.keras.callbacks.Callback` subclasses.
For more information from the tensorflow package on what callbacks are and what they can achieve, feel free to refer to
the tensorflow documentation on callbacks at: https://www.tensorflow.org/api_docs/python/tf/keras/callbacks/Callback.
"""
... |
2bc368b3fc80721ab95dd6a3625283bf7a098a3786a2304feaa5a0ae7100ed00 | Python | 11,388 | 333 | import os
import sys
import re
import types
import itertools
import matplotlib.pyplot as plt
import numpy
import scipy.stats
import numpy.ma
import Stats
import Histogram
from cgatReport.Tracker import *
from cpgReport import *
##########################################################################
class Interva... |
94274fdab3f5a3ec172e78d184813c70cfc0c00458d36cd3ab66770fe215bb29 | Python | 11,389 | 234 | """
return processed data
1. drugcomb summary data
2. drugcomb drug data
3. drugcomb cell data
4. drug target data
"""
import argparse
import pathlib
import numpy as np
import pandas as pd
import pickle
import scipy.stats as scistat
import sklearn.preprocessing as skpre
import sklearn.feature_extraction as skfet
imp... |
336cdb6f3543b76591542995992d3252b5af29d39b0c92c5768f673d1eee88f4 | Python | 11,392 | 262 | import math
import matplotlib.pyplot as plt
from matplotlib import gridspec
from torch.utils.tensorboard import SummaryWriter
import torch
from data import generate_recog_data
from net_utils import load_from_file
from plotting import maxval, maxabs, plot_W, plot_B, ticks_off, plot_train_perf, plot_recog_gene... |
fbb8a30c18153f196a81d61cf01f5dd86ad104e67a1f013861c941f1c33fd86c | Python | 11,396 | 321 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
from typing import Callable
import torch
from torch import nn
from torch.nn import functional as F
from .activations import ACTIVATION_REGISTRY
# from .fourier import SpectralConv2d
#############################################################... |
3735317f2c2f6377a8a5b43f408bca3214a6cbea388ff04028775fc82481c4ed | Python | 11,400 | 255 | """
In this file the functions to evaluate the state, reward are defined and also the action is implemented
"""
import numpy as np
from DSS_Initialize import*
# To get the details of switches and their status
def switchInfo(DSSCktobj):
#Input: DSS Circuit Object
#Returns: A list of dictionaries which contain... |
e740e23808c8c25586e9744258635ad2e2233d7a693d679c00a71f0dc6965bb8 | Python | 11,407 | 265 | import argparse
import logging
import os
import random
import shutil
import sys
import time
import numpy as np
import torch
import torch.backends.cudnn as cudnn
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from tensorboardX import SummaryWriter
from torch.nn import B... |
295be44a595f339371cea8022d2d0fdefcc4430ba50830d5ffe95b8067d656d1 | Python | 11,411 | 352 | """Ensemble Retriever.
Ensemble retriever that ensemble the results of
multiple retrievers by using weighted Reciprocal Rank Fusion.
"""
import asyncio
from collections import defaultdict
from collections.abc import Callable, Hashable, Iterable, Iterator
from itertools import chain
from typing import (
Any,
... |
b100cde624f1f8cc74e6d311dcd165aee718f96b8ebd7ef05bc90748b56611c5 | Python | 11,415 | 273 | import copy
import logging
import os
import socket
import sys
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from configs.configs import get_config_dict
from helpers.hcp import get_human_connectome_project_subjects, rename_variables_for_plots
from helpers.figures import g... |
c834af6916d8525bf22b8d455e7f179af0ab4bd944822fd8d2b17a828688be43 | Python | 11,417 | 237 |
from copy import copy
import numpy as np
import pandas as pd
from statsmodels.stats.multitest import multipletests
def ttest(self, params):
"""Perform a T-test on the data
Args:
params (list): list containing control and experimental groups,
normalized dataframe and if the variables are dep... |
5bbcc59c7bcafd953c3be918abffdd04f7da30ab40fd1bad4f80dbd59decba42 | Python | 11,420 | 338 |
"""
A vanilla 3D resnet implementation.
Based on Raghavendra Kotikalapudi's 2D implementation
keras-resnet (See https://github.com/raghakot/keras-resnet.)
"""
from __future__ import absolute_import, division, print_function, unicode_literals
import six
from math import ceil
from keras.models import Model
from keras.l... |
aa0fa3867b6a3816fda2bc61784b2b476b29603b7b27aa0e59cc6bc54a6d267c | Python | 11,422 | 315 | """Methods to evaluate peptide-spectrum predictions."""
import re
from typing import Dict, Iterable, List, Tuple
import numpy as np
from spectrum_utils.utils import mass_diff
def aa_match_prefix(
peptide1: List[str],
peptide2: List[str],
aa_dict: Dict[str, float],
cum_mass_threshold: float = 0.5,
... |
d12b54799271cace96dd6ac6f9e35fab70cba1ff66b3235f23ea8d3392fd1d37 | Python | 11,423 | 279 | # Copyright 2022 MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, s... |
12a3b51294e770d77f35bc63f340579bbb5ea68f8753328036add3e82e012fd3 | Python | 11,432 | 362 | import seaborn as sns
from SMdRQA.RQA_functions import entropy
from SMdRQA.RQA_functions import average
from SMdRQA.RQA_functions import maxi
from SMdRQA.RQA_functions import mode
from SMdRQA.RQA_functions import percentmorethan
from SMdRQA.RQA_functions import diaghist
from SMdRQA.RQA_functions import onedhist
from SM... |
75ea46673cc9011453861d99669816292500c27534f272b66479d1c3911002c9 | Python | 11,432 | 307 | import cv2
import torch
from skimage import measure
import numpy as np
from scipy.ndimage import binary_fill_holes
from utils.geometry import close_contour, find_recist_in_contour, recist2det
from visualizer.visualizers import vis_img, plt_show
from .bbox_operator import BBoxes
from functools import reduce
def read_m... |
2bd3cb0df4886aabccc89f4b1f96d9b73e1da6e0f01934d6b50b71992637c139 | Python | 11,439 | 347 | import argparse
import os
from time import time as t
import matplotlib.pyplot as plt
import numpy as np
import torch
from torchvision import transforms
from tqdm import tqdm
from bindsnet.analysis.plotting import (
plot_assignments,
plot_input,
plot_performance,
plot_spikes,
plot_voltages,
plo... |
0e8cf07eb1a37a1ad7d8139597e2ced1bd4dd1266a8e04a40f285dbccdb75695 | Python | 11,440 | 263 | """ This module contains the model class for DBMs.
:Implemented:
- DBM model
:Version:
1.0.0
:Date:
26.05.2019
:Author:
Jan Melchior
:Contact:
JanMelchior@gmx.de
:License:
Copyright (C) 2019 Jan Melchior
This file is part of the Pyt... |
572807a9e5ce441f5105bff3d833b3dc152dfd6cb675ab445dbe7dbcb50b540c | Python | 11,441 | 380 | """
gtfsubset.py - Tasks for GTF subsetting
===============================================
Reference
---------
"""
import os
import pysam
import cgatcore.experiment as E
import cgatcore.iotools as iotools
import cgat.GTF as GTF
import cgatcore.pipeline as P
import cgatcore.database as Database
class SubsetGTF():
... |
6efb713198a4ebed6c315baee480f0832913897f5b238e881978d1f393f237e0 | Python | 11,441 | 279 | from collections import deque
from collections.abc import Hashable
import networkx as nx
import pandas as pd
from sklearn.base import clone
from tqdm.auto import trange
from pgmpy import config
from pgmpy.base import DAG
from pgmpy.causal_discovery import ExpertKnowledge
from pgmpy.causal_discovery._base import BaseC... |
dbbbf0c99988c95c737d1ba80c8467dc215503c366c74714865cbe8543a51275 | Python | 11,444 | 308 | # Copyright (c) 2019 Mwiza Kunda
# Copyright (C) 2017 Sarah Parisot <s.parisot@imperial.ac.uk>, Sofia Ira Ktena <ira.ktena@imperial.ac.uk>
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, eithe... |
38c3d03cf9d81c286549a956a28574937ac5d75901d8a45af1d8c781649644fd | Python | 11,446 | 255 | """
In this file the functions to evaluate the state, reward are defined and also the action is implemented
"""
import numpy as np
from Environments.DSSdirect_34bus_loadandswitching.DSS_Initialize import*
# To get the details of switches and their status
def switchInfo(DSSCktobj):
#Input: DSS Circuit Object
... |
4fb5bad72dc63cf429e150a664b18ef8fc0f39ac3720c86d10d8245f465612aa | Python | 11,448 | 292 | import numpy as np
import scipy as sp
import scipy.stats
import scipy.spatial
import scipy.spatial.distance
import pyemma
from pyemma.util.contexts import settings
import MDAnalysis as mda
import matplotlib.pyplot as plt
import os
from pensa.features import *
def residue_visualization(names, data, ref_filename, pdf... |
b35bdf6d2e3f0452ed436ef8468f3c6d965e1e6865806d742706213cbf082fbc | Python | 11,448 | 189 | import pandas as pd
import numpy as np
import re
import argparse
def data_filter(rawdata_path,embedding_data_path,reference_path,sample_id_path,save_path,cancer):
# RNA
print('RNA')
data_mRNA=pd.read_csv(rawdata_path+cancer+'.mRNA.csv',sep=',')
sample_mRNA_data=pd.read_csv(sample_id_path+'/sample_mRNA... |
bb1b7c8d7f011ab7ec6dc5bec05aa8baff7ecc31cadd13797dc37cda54825f16 | Python | 11,461 | 292 | # Extension of MXNet Module
import logging
import mxnet as mx
import numpy as np
import mxnet.ndarray as nd
from collections import OrderedDict
from mxnet.module import Module
def nd_global_norm(t_list):
"""Computes the global norm of multiple tensors.
Given a tuple or list of tensors t_list, this operation ... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.