sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
c101454136be8b68aefdbf2d235fb67f8c5d22815ed09ed8f014990fc9b79e07 | Python | 7,865 | 227 | from ChipseqReport import *
##########################################################################
##########################################################################
##########################################################################
##
###############################################################... |
1ccdbef9a73105e9fea567b82fa7266f7f8fca9138eac4b5ef6424b37f35c250 | Python | 7,871 | 247 | import logging
import os
import socket
import sys
import matplotlib.pyplot as plt
import pandas as pd
import ptitprince as pt
import seaborn as sns
from configs.configs import get_config_dict
from helpers.figures import get_palette
def _plot_bar_graph_scores(config_dict: dict) -> None:
plt.figure(figsize=config... |
f4b9596912d7a0f6a726578a03cc51b6fa0515172010614beb29d95597103778 | Python | 7,872 | 233 | import copy
import filecmp
import os
import random
import tempfile
import time
from pathlib import Path
from unittest import TestCase
import numpy as np
import pandas
import pytest
import requests
import chroma
from chroma.data.system import System
BASE_PATH = str(Path(chroma.__file__).parent.parent)
CIF_TRAJECTORY ... |
af0f75d9816d863af4f80989ff0f37bc57cd0e798add59ecdff8ad6281a81b6c | Python | 7,873 | 198 | import argparse
from typing import List
import math
import numpy as np
import pylsl
import pyqtgraph as pg
from pyqtgraph.Qt import QtCore, QtGui
class Inlet:
"""Base class to represent a plottable inlet"""
def __init__(self, info: pylsl.StreamInfo, plot_duration: int):
# create an inlet and connect ... |
9de440f183a4846713513beb319bd3af09d7da3eb46c6c064488eb740d62cd23 | Python | 7,882 | 194 | from pathlib import Path
from collections import Counter, OrderedDict, defaultdict
import logging
from hashlib import md5
from clldutils.misc import slug
from clldutils.path import git_describe, read_text, write_text
from pycldf import StructureDataset
from csvw.dsv import reader
from csvw import ForeignKey
from pyglo... |
c98098fe2bd6bccf3e1213481d78935f72e6c4b65ce00d0013dcbef1225b511d | Python | 7,885 | 175 | # Copyright (c) DP Technology.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import absolute_import, division, print_function
import os
import pandas as pd
import numpy as np
from tqdm import tqdm
from rdkit import Chem
from... |
570a7541885ef50bc3026d7c4b45a41064c79aa0797d58f7480a58e39bcbce55 | Python | 7,893 | 249 | """
@author: Nick Anthony
"""
from __future__ import annotations
import abc
import json
import typing
from dataclasses import dataclass
import numpy as np
class _HookReg:
"""Stores deserialization hooks and combines them into `getHook`"""
def __init__(self):
self._hooks = []
def addHook(self, f... |
6c0ae3cd6cc470d2a53ac740774c00adc3ba62a628e41753950126b6218fdfeb | Python | 7,893 | 231 | """
This script summarized DE results.
"""
import numpy as np
import pandas as pd
import session_info
from pyhere import here
from functools import lru_cache
from scipy.stats import mannwhitneyu
@lru_cache()
def get_annotation(feature, tissue):
"""
Get the annotation file based on feature and tissue.
"""
... |
eca181de184a897840f270fc66893bd47ec90ab31b8e74be207cd96f10e19800 | Python | 7,895 | 155 | #!/usr/bin/env python3
import sys
import random
import numpy as np
import pandas as pd
import seaborn as sns
from scipy import stats
import matplotlib.pyplot as plt
plt.switch_backend('agg')
from itertools import islice, cycle
from plottify import autosize
sns.set_context("paper", font_scale=1.4)
sns.set_style("white... |
f5bbe4d30d69f76c6bda3540f33a0b00ad27230b93ba903bca9feaede7dbbe65 | Python | 7,896 | 185 | import glob
import os
import SimpleITK as sitk
import numpy as np
import argparse
from medpy.metric import binary
import GeodisTK
from scipy import ndimage
def dice(pred, label):
if (pred.sum() + label.sum()) == 0:
return 1
else:
return 2. * np.logical_and(pred, label).sum() / (pred.sum() + la... |
f9befa3b522d88daaf2228e43c4f253b38460c62a7e2e803ad66adb99c1ec075 | Python | 7,896 | 211 | """Tiny MCP servers the examples share, so each example stays about one idea.
Nothing here is specific to LangChain — these are plain FastMCP servers. The
`run_*` functions exist because a server reached over stdio or HTTP has to be
started as its own process, and that entry point cannot be a lambda.
"""
from __futur... |
5942e803bce01709e5f18c2263942168cf63f9c0aa6343691dafcdb4d85fcd67 | Python | 7,904 | 221 | """
Authors: {
Orestis D. Papagiannopoulos : orepap_a@hotmail.com
Vasileios Pezoulas : bpezoulas@gmail.com
Costas Papaloukas : papalouk@uoi.gr
Dimitrios I. Fotiadis : fotiadis@uoi.gr
}
Institution ... |
e33cef9d5ec43cbc757253c23fdba90f34cba2b0a24c90b10e1563127933dd92 | Python | 7,905 | 237 | import pandas as pd
import numpy as np
import random
import operator
import itertools
import sys
from pathlib import Path
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
import warnings
warnings.filterwarnings("ignore", message="numpy.dtype size changed")
warnings.filterwarnings("ignore", message="numpy.u... |
13d527d6cbb04bfdc6037d555d9374451d7e1137265aa49f7e4a0a4b9f1174ef | Python | 7,914 | 202 | #!/usr/bin/env python3
import os
import torch
import hydra
import logging
import shutil
from models import get_model
from torchvision.transforms import Compose
from torch_geometric.loader import DataLoader
from ori_dataset import MD17_DFT, random_split, get_mask
from torch_ema import ExponentialMovingAverage
from tra... |
f9a39ac7ee38d71c9c6f5e5b7be781abcca993bae10db1d72f9e26e678076349 | Python | 7,915 | 183 | """
Make a summary table to check data sanity and quality for an individual subject.
"""
import argparse
import data_analysis_utils as dana
import json
import matplotlib.pyplot as plt
import numpy as np
import os.path as op
import plot_utils as plut
SUMMARY_TABLE_WIDTH = 3.5
SUMMARY_TABLE_ROW_HEIGHT = 0.3
SUMMARY_TAB... |
35f85e35e3c75232b60c8208cb9a1896f3a348b8e7a32d600d1473bce117f49f | Python | 7,918 | 227 | import torch
import torch.nn as nn
from h3xsemble.model.structure_module import AngleResnet, AngleResnet_backbone
from h3xsemble.utils.residue_constants import (
restype_rigid_group_default_frame,
restype_atom14_to_rigid_group,
restype_atom14_mask,
restype_atom14_rigid_group_positions,
)
import h3xsembl... |
6232a04804a950df718e532a4639446a6b137061510bde74f216190d92a4b932 | Python | 7,921 | 180 | import os
import numpy as np
import brokenaxes
import torch
torch.set_printoptions(precision=4, sci_mode=False, threshold=5000)
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
plt.rc('savefig', format='pdf', bbox='tight')
plt.rc('font', size=8)
#plt.rc('legend', fontsize=8)
from... |
bf6b1dad16980434c9b5b923a421773dca8e2aa6d6b51b57e2d679975d29578c | Python | 7,922 | 249 | # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
# -*- coding: utf-8 -*-
#
# Rallpack1 model
# Author Iain Hepburn
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
import numpy as np
import numpy.linalg as la
import sys
import os
from mpi4py import MPI
import... |
aae874e68ea490fc7ed29b2e07e156f49b98dec83e384430f2e8ed7785483dbc | Python | 7,924 | 199 | # Copyright (c) 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, so... |
cbeead86c3e6aaaaf5b23fdb0c223c8c091dd5986052353c9bfd75cf2c27ccad | Python | 7,927 | 189 | "evaluate multi class tagger"
import pyrootutils
root = pyrootutils.setup_root(search_from=__file__, pythonpath=True)
import copy
import numpy as np
import matplotlib.pyplot as plt
from sklearn import metrics
import torch as T
from tqdm import tqdm
import src.pipeline as pl
import src.eval_utils as eval_utils
import... |
9a65f492d68d14db1dd1bae01d98224fab157038672f3da3a7fb7747711dd0d0 | Python | 7,929 | 193 | import re
import cv2
import numpy as np
from scipy.spatial.distance import cdist, pdist, squareform
import math
def intersection(start1, end1, start2, end2):
x1, y1, x2, y2, x3, y3, x4, y4 = *start1, *end1, *start2, *end2
d = np.linalg.det(np.array([[x1 - x2, x4 - x3], [y1 - y2, y4 - y3]]))
p = np.linalg... |
a5a570f903adf0901aa2d724a33b7ab320082166c200160977be8261095ee378 | Python | 7,929 | 255 | from pprint import pprint
import numpy as np
import cv2
import albumentations as A
from albumentations.pytorch import ToTensorV2
from albumentations import ImageOnlyTransform
import torch
from torch.utils.data import Dataset
import com_image as ci
import com_plot as cp
class FixPatchBrightness(ImageOnlyTransform... |
895fcfc518acc721d6340287fc2c66c0ee09ee0e7e779db3a054a80fad6638d1 | Python | 7,930 | 221 | import torch
import torch.nn as nn
import torch.nn.functional as F
from networks.attention import *
from networks.efficient_encoder import get_encoder
def initialize_decoder(module):
for m in module.modules():
if isinstance(m, nn.Conv2d):
nn.init.kaiming_uniform_(m.weight, mode="fan_in", non... |
3d885aed8996b41bcf553f906e1f5d2036948bc3dfcd2db41b06d1f758619e44 | Python | 7,934 | 166 | import random
from feature_test import Compound
from label import FaceLabel
from itertools import combinations
from OCC.Core.BRepAlgoAPI import BRepAlgoAPI_Cut, BRepAlgoAPI_Fuse
from OCC.Display.SimpleGui import init_display
from OCC.Core.TopLoc import TopLoc_Location
from OCC.Core.STEPControl import STEPControl_Writer... |
678db11b042b92f4076a8feb73f854e918354f9dead6394997b04771e4512a2e | Python | 7,934 | 212 | """Data loaders for the de novo sequencing task."""
import functools
import os
from typing import List, Optional, Tuple
import lightning.pytorch as pl
import numpy as np
import torch
from depthcharge.data import AnnotatedSpectrumIndex
from ..data.datasets import AnnotatedSpectrumDataset, SpectrumDataset
class DeNov... |
5e46e05c466c129a17796b74addee9558a8f8c4021a7538b8e37551d2a0aa841 | Python | 7,936 | 249 | from typing import Tuple, List, Optional, Dict, Union, Iterable
from rdkit import Chem
from rdkit.Chem import Descriptors, Mol, MolFromSmiles
import numpy as np
from rdkit import RDLogger
def molar_wt_fromSmiles(smiles: str) -> float:
return Descriptors.MolWt(polymol_fom_smiles(smiles))
def calc_polymer_shares(... |
949da1ce11342137f76738d4633d57bebfd9b226003da94f74c670926c0ad26c | Python | 7,940 | 147 | from typing import TYPE_CHECKING, Any
import numpy as np
import pandas as pd
from pandas.api.types import is_string_dtype
from skbase.utils.dependencies import _safe_import
from sklearn.base import clone
from pgmpy.parameterization._base import BaseParameter, _is_numeric, _plain
from pgmpy.parameterization.adapters.s... |
30ba6c7c5ba8ad9abeabb9740e472da04a67e01bd9ed18e7b2f3fd40db1199f6 | Python | 7,944 | 227 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import sys
if '../../../embeddings' not in sys.path:
sys.path.append('../../../embeddings')
from seq2tensor import s2t
import keras
from keras.models import Sequential, Model
from keras.layers import Den... |
712432f84c98507d92a78dc3772e95f4b4a8ddc3f36dfe077afc52d25fd145d5 | Python | 7,948 | 153 | ####################################################################################
#
# STEPS - STochastic Engine for Pathway Simulation
# Copyright (C) 2007-2023 Okinawa Institute of Science and Technology, Japan.
# Copyright (C) 2003-2006 University of Antwerp, Belgium.
#
# See the file AUTHORS for d... |
cfb4d71ad60e96f6bf3f44f21926c53ce6716d6a9ea8867b192603decaf8e64c | Python | 7,964 | 246 | # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
# -*- coding: utf-8 -*-
#
# Rallpack1 model
# Author Iain Hepburn
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
import steps.quiet
from steps.geom import UNKNOWN_TET
import steps.model as smodel
import steps... |
d48a09fd25d56df6ef84f5049641d5dee8f9cf7a226e2b01eb8ff322f2a67609 | Python | 7,968 | 174 | ## main module for parsing, processing and interacting with cellsdata/files of 1p-stim protocols (i.e. matlab .dat files that are used in PackIO)
## - 1pstim module - just copied straight from allopticalseizure version so far..
import os
from datetime import time
import numpy as np
from matplotlib import pyplot as plt... |
3ee34e4c8243d129c20dbfd385d87b5ed101d3486981e41bbce622c055144cfa | Python | 7,975 | 267 | # 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... |
3a777713431cfe50c69a352819a08121d72758cbd33d997517941e433a7cf2e1 | Python | 7,977 | 222 | """
Tests for the SMdRQA UI support modules.
The ScriptRecorder and window_size_sensitivity tests run without any UI
dependency; the app import smoke test is skipped unless streamlit and
plotly are installed.
"""
import numpy as np
import pytest
from SMdRQA.RQA2 import RQA2
from SMdRQA.ui import ScriptRecorder, wind... |
829a973fbc71d9cb7499d3378deb21a11dda4b9238cfb52776c1f94eb104f335 | Python | 7,977 | 163 | import sys
import warnings
from time import time
import torch
from monai.data import set_track_meta
from sklearn.metrics import confusion_matrix, roc_auc_score
warnings.filterwarnings("ignore")
from train_functions.metric_functions import calc_metrics
def train_loop(outcome_label_name, max_epochs, train_loader, mod... |
9602617ccf5219222bd75778525a0eea2acf0a2b11a35784ae4326645adcc4e1 | Python | 7,977 | 228 | # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
"""Processing phase-difference (aka :abbr:`GRE (gradient-recalled echo)`) fieldmaps.
.. _gre-fieldmaps:
Workflows for processing :abbr:`GRE (gradient recalled echo)` fieldmaps
~~~~~~~~~~~~~~~~~~~~~~~~~~~~... |
a184cad760a49a8b87e6f49e95a1016aa3de9bdff53dcf17c643b9f974cb6ea7 | Python | 7,982 | 147 | import os
from tqdm import tqdm
import torch
import torch.nn as nn
import numpy as np
import random
import time
import argparse
import math
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
def main():
torch.autograd.set_detect_anomaly(True)
# parse arguments
parser = argparse.Argume... |
d3b16d6bbaf7cf8b79ae044784cecb862a79526142564b12edd309992114227a | Python | 7,982 | 279 | from tensorflow.keras import Model
from tensorflow.keras.layers import (BatchNormalization, Conv3D, Dense,
GlobalAveragePooling3D,
GlobalMaxPooling3D, MaxPooling3D, Input)
from explainability import LRP, LRPStrategy
from explainability.layers im... |
13468eeef84838aa428c3cc4c67078cba4762ca8cbfe33941cffc168650bf2e7 | Python | 7,983 | 198 | #!/usr/bin/env python
# =============================================================================
# MODULE DOCSTRING
# =============================================================================
"""
Test force factories in forcefactories.py.
"""
# ==============================================================... |
805feaa19d8e110afeb2ffadbd8b234c062ae099eddf7d6b9f488c154d84a48c | Python | 7,984 | 233 | from mimic3models import metrics
from mimic3models import common_utils
import threading
import os
import numpy as np
import random
def preprocess_chunk(data, ts, discretizer, normalizer=None):
data = [discretizer.transform(X, end=t)[0] for (X, t) in zip(data, ts)]
if normalizer is not None:
data = [no... |
595ab14f3b43bd6ca4a27b3d98f38cf3178e78eb9959bf720c2f23140846f3b1 | Python | 7,986 | 252 | import warnings
import tempfile
import torch
import numpy as np
from rdkit import Chem
from rdkit.Chem.rdForceFieldHelpers import UFFOptimizeMolecule, UFFHasAllMoleculeParams
import openbabel
import utils
from constants import bonds1, bonds2, bonds3, margin1, margin2, margin3, \
bond_dict
def get_bond_order(ato... |
7905fddf573e85645e7731767a7ca93e92ff4f4d824ce03ec0ec49c338cd887b | Python | 7,988 | 231 | """
Create heatmaps for OMTscoring model across the WSI.
Usage:
create_heatmaps.py [options] [--help] [<args>...]
create_heatmaps.py --version
create_heatmaps.py (-h | --help)
Options:
-h --help Show this string.
--version Show version.
--input_dir=<string> Pa... |
4fc710f6f96788fb59cb19fab8d64873d3d16e9e182f12a544d451c74c548cc7 | Python | 7,989 | 175 | import torch.nn as nn
import torch
from einops import rearrange, repeat
class Physics_Attention_Irregular_Mesh(nn.Module):
## for irregular meshes in 1D, 2D or 3D space
def __init__(self, dim, heads=8, dim_head=64, dropout=0., slice_num=64):
super().__init__()
inner_dim = dim_head * heads
... |
c58f4525acc95b8f39ad52bd5c5d2679e37ef60e5c667bad3bc8189c79b19114 | Python | 7,989 | 168 | import torch.nn.functional as F
import torch
import pandas as pd
import numpy as np
import argparse
# from utils.data_processing import load_data
from node_embed.featurization import load_data_adv
from torch_geometric.loader import DataLoader
from sklearn.metrics import roc_auc_score, accuracy_score, f1_score... |
5cbf227b9014918053e9ece365da1d71239eaceb41cc3aaee6defea1e397c3f5 | Python | 7,995 | 195 | """
Read the phenotype-specific summary statistics (generally PLINK).
Standard LDSC-like format (.sumstat) works.
Required columns:
- SNP ID: one of [ID, id, snp, SNP]
- Sample size: one of [N, n]
- Z-score: one of [Z, z]
Reference: https://github.com/sriramlab/SUMRHE/blob/main/src/sumstats.py
"""
import... |
243a47f220fffde209b10d49b01ea7b3cfc50e803bf9bf859e17b261ecc8d4d4 | Python | 7,998 | 212 | from animalai.envs.raycastparser import RayCastParser
import uuid
from typing import NamedTuple, Dict, Optional, List
from mlagents_envs.environment import UnityEnvironment
from mlagents_envs.rpc_communicator import UnityTimeOutException
from mlagents_envs.side_channel.raw_bytes_channel import RawBytesChannel
from mlag... |
ac09dc9fdd8bc7a0059bbcaac98fedb67be946fc6d9ed5239fca7018ff5836a8 | Python | 7,998 | 194 | #!/usr/bin/env python3
#$ -cwd
#$ -V
#$ -N SFlex
#$ -e /cluster/uz_lab/cmives/TRP_channels/MDS/permeation_analysis/sf_flexibility/SFlex.err
#$ -o /cluster/uz_lab/cmives/TRP_channels/MDS/permeation_analysis/sf_flexibility/SFlex.out
#$ -pe smp 12
#$ -jc short
import os
import sys
import itertools
import numpy as np
impo... |
b9691b364d250d81778ac16960b43db85ef6db1c68b980d59c5c85b86ee3134a | Python | 8,000 | 211 | """Will test visualization functions."""
import pytest
import numpy as np
import pandas as pd
import torch
from torch.utils.data import TensorDataset, DataLoader
from vulcanai.datasets import tabular_data_utils
import os
from copy import deepcopy
from sklearn.datasets import load_digits
from sklearn.metrics import con... |
c2a40f0bec57f22af5d007170fa0eb068d60f1faa8f7f4a0bd62380dbcf139df | Python | 8,000 | 297 | import numpy as np
import pytest
from skbase.utils.dependencies import _check_soft_dependencies
from pgmpy import config
from pgmpy.factors.discrete import DiscreteFactor, TabularCPD
from pgmpy.models import DiscreteBayesianNetwork, DiscreteMarkovNetwork
from pgmpy.readwrite import UAIReader, UAIWriter
@pytest.fixtu... |
5209b29b48a9a128e7e65e61ee46ccaf328de6d06600a931f671d742384b8972 | Python | 8,001 | 163 | import bisect
import torch
from .misc import _scaled_dot_product, _select_initial_step, _handle_unused_kwargs
from .solvers import AdaptiveStepsizeODESolver
from .rk_common import _RungeKuttaState, _ButcherTableau, _runge_kutta_step
# Parameters from Tsitouras (2011).
_TSITOURAS_TABLEAU = _ButcherTableau(
alpha=[0... |
50d6a47b8681699c27fb2b571ad9318201fb68daafeb05cd38591db332b5d15b | Python | 8,006 | 192 | import torch
import torch.nn as nn
from egnn.egnn_new_SE3 import EGNN, GNN
# from egnn.egnn_new import EGNN, GNN
from equivariant_diffusion.utils import remove_mean, remove_mean_with_mask
import numpy as np
import math
class SinusoidalPosIdxEmb(torch.nn.Module):
def __init__(self, dim):
super().__init__()
... |
df7701740a2a1b2949984cac375437af98694b56d15d3bc6be62abe8cd4e4dab | Python | 8,006 | 251 | # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
# -*- coding: utf-8 -*-
#
# Rallpack1 model
# Author Iain Hepburn
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
import numpy as np
import numpy.linalg as la
import sys
import os
from mpi4py import MPI
import... |
4a28d3b4950533abbb7c7ea2991b958727bf3541bee7cfddeed85a29b242f226 | Python | 8,009 | 211 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import torch
import torch.nn.functional as F
from torch_geometric.utils import scatter
def lp_norm_weighted(input: torch.Tensor, weights: torch.Tensor, batch_idx: torch.Tensor, p: int):
if p == 2:
return scatter(src=input.sq... |
b281001089a5c27f85bc4855c8dae04eb3bfc440a7036ccb6b6d90c5d4705ae2 | Python | 8,009 | 173 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Nov 24 17:43:27 2020
@author: shni2598
"""
from brian2.only import *
import connection as cn
#%%
class two_areas:
def __init__(self):
self.neuron_model_e = cn.model_neu_syn_AD.neuron_e_AD
self.neuron_model_e_adapt_tv ... |
0b513988cdc406e9d7d7e6e863ae61fedf2e275bcc4e9b366d340dd502b5db3c | Python | 8,019 | 171 | # pylint: disable=E1101, E0401, E1102, W0621, W0221
import argparse
import numpy as np
import torch
import torch.optim as optim
from random import SystemRandom
import models
import utils
parser = argparse.ArgumentParser()
parser.add_argument('--niters', type=int, default=2000)
parser.add_argument('--lr', type=float, ... |
a60981b02f6a7d7b51cef9da9a661d09de3ccd31b3319a8d91dd61e2263c0123 | Python | 8,024 | 199 | """Training configuration dataclass for BERNN models."""
from dataclasses import dataclass
from typing import Optional, Any
@dataclass
class TrainingConfig:
"""Configuration contract for BERNN holdout trainers.
Core concepts
- Layer depth is controlled by ``n_layers``.
- ``layer1`` is the optional e... |
8c9cda3ceecc751b3830f8d89648acf6fcbf33a21c92b7fbd62f749fea834c27 | Python | 8,031 | 224 | import pytest
from pgmpy.base import MAG
# graph has been taken from the zhang 2008 paper (figure 1)
@pytest.fixture
def mag():
edges = [
("A", "B", "<>"),
("C", "D", "<>"),
("A", "C", "<>"),
("B", "D", "<>"),
("A", "D", "->"),
("B", "C", "->"),
]
roles = {... |
deeda0c947cd11bcba3e9742aa6ab367f783ce0d8dbf91a76759a72346465fff | Python | 8,036 | 259 | ####################################################################################
#
# STEPS - STochastic Engine for Pathway Simulation
# Copyright (C) 2007-2023 Okinawa Institute of Science and Technology, Japan.
# Copyright (C) 2003-2006 University of Antwerp, Belgium.
#
# See the file AUTHORS for d... |
671b6ca7a99e5e9ff2262f7ebcccd2e5b31d6bdf9de0aff23e50d60c9331cba8 | Python | 8,037 | 238 | import logging
import time
import json
import argparse
import contextlib
import numpy as np
from copy import deepcopy
from pathlib import Path
from tqdm.auto import tqdm
import omegaconf
import torch
from lightning.pytorch import seed_everything
from torch.utils.data import Subset
from scdp.common.pyg import DataLoad... |
8ac4e4c6cd7c002c0526b84d0da41e6a4703b98a7f43f86743ed5df77053fbfe | Python | 8,044 | 83 | from langchain_core.prompts.chat import (
ChatPromptTemplate,
HumanMessagePromptTemplate,
SystemMessagePromptTemplate,
)
from langchain_core.prompts.prompt import PromptTemplate
from langchain_classic.chains.prompt_selector import (
ConditionalPromptSelector,
is_chat_model,
)
question_prompt_templ... |
6eae4cfc94985529f431c4f87852a849241a4c23f5f41d21f957d401c85bb3fe | Python | 8,045 | 298 | """
Tests of the 'Configuration' step
"""
import random
from pathlib import Path
import pytest
from cwas.configuration import Configuration
from cwas.env import Env
import cwas.cli
import sys
@pytest.fixture(scope="module")
def vep_mock(cwas_workspace: Path):
return cwas_workspace / "vep"
@pytest.fixture(scope... |
f9f60792eb4c3521b9d5507b9ced3f0ea8e45f7210b33b82a890507071fa53ce | Python | 8,046 | 223 | import numpy as np
def polyphase_decimate_causal(in_sig, dec_filter_h, dec_rate, init_cond=None):
"""
A causal polyphase FIR decimator with continuous block boundaries.
Parameters
----------
in_sig : array-like
Input signal (1D list or numpy array).
dec_filter_h : array-like
FI... |
284cc80d4625f5c744e21914eda855cec2517119dd71448b9e4e2e8431097bcf | Python | 8,048 | 216 | # This extension template provides instructions to add new metrics to pgmpy.
#
# Please follow the following steps:
# 1. Copy this file to `pgmpy/metrics` and rename the file as `your_metric_name.py` (e.g., `my_metric.py`).
# Note: Do NOT start the filename with an underscore `_`, otherwise it won't be discovered.
#... |
cf7773b7391772c2ad685aa5b7c80c089b64f13b0c29ea6f01c99dcfeee88fae | Python | 8,052 | 241 | # -*- coding: utf-8 -*-
"""
Created on Mon Aug 24 15:16:53 2020
@author: nishe
"""
import numpy as np
from scipy import signal
from scipy import stats
#%%
def find_MI_cfc(sigPhase, sigAmp, optionMethod=1, optionSur=2):
numSur = 200 ;
numPhase = np.shape(sigPhase)[0] ;
numAmp = np.shape(sigAmp)[0]... |
cf83353e2ca0ea5eaec6fb664f69e218532b31dc6009d7e31a6a68b4c24ed21b | Python | 8,056 | 161 | 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 tssInte... |
5c35481c4d05856c707e0c4aadf0e66277cf8fd4b392d8a0f5a0744a77f56fe6 | Python | 8,060 | 227 | import numpy as np
import torch
import logging
import os
import urllib
from os.path import join as join
import urllib.request
from qm9.data.prepare.process import process_xyz_files, process_xyz_gdb9
from qm9.data.prepare.utils import download_data, is_int, cleanup_file
def download_dataset_qm9(datadir, dataname, s... |
4e95cf3e4a28447774deae7dd2a13b98b27f9e57859df8c9c4045097f48605dd | Python | 8,063 | 197 | # Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this sof... |
441fc5d7da3a78e76c8d4744a6b4fae66aea7bebee9a800289140a6deccdf0e0 | Python | 8,065 | 215 | import torch
from torch_geometric.loader import DataLoader
import os
import pickle
from sklearn.model_selection import KFold
import numpy as np
import random
from torch_geometric.nn import global_mean_pool, GATConv
import torch.nn.functional as F
import torch.nn as nn
from torch import optim
import datetime
print("...... |
651fe5273580810328966ed4beb0d95aec33893c96ebc87d8e471b91d86182b1 | Python | 8,069 | 240 | # Copyright 2024 DeepMind Technologies Limited
#
# AlphaFold 3 source code is 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... |
cd725696fb433c84a4ae9a49bafbd1861c4fea5cf1aca8d4996f4e0632b0bb0f | Python | 8,072 | 215 | """Score network module."""
import torch
import math
from torch import nn
from torch.nn import functional as F
from data import utils as du
from data import all_atom
from model import ipa_pytorch
import functools as fn
Tensor = torch.Tensor
def get_index_embedding(indices, embed_size, max_len=2056):
"""Creates s... |
63ad76475513f346cc442d18a0d05693d67034754fd5dc24c15dc108cfd0c51f | Python | 8,073 | 191 | # Copyright (c) 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, so... |
065569527fd89dfefd04cf8ad9e5cbee26eb6f3d9938edcdbfb8effacecb03bc | Python | 8,076 | 261 | ####################################################################################
#
# STEPS - STochastic Engine for Pathway Simulation
# Copyright (C) 2007-2026 Okinawa Institute of Science and Technology, Japan.
# Copyright (C) 2003-2006 University of Antwerp, Belgium.
#
# See the file AUTHORS for detai... |
7810cb03d36b7bc716a26720fb41a1585a74bd7e5de1c3f15ea5281255fbdc32 | Python | 8,078 | 212 | import copy
from os.path import splitext
#from pdbx.reader import PdbxReader
from pdbx.writer import PdbxWriter
from pdbx.reader import *
from sys import argv
def parseOperationExpression(expression) :
operations = []
stops = [ "," , "-" , ")" ]
currentOp = ""
i = 1
# Iterate ov... |
cec54920ff7baaa22bc2e9e78a1db2c11054b8ec8022a56de9eca5893a4ff30c | Python | 8,081 | 187 | import argparse
import time
import json
import random
from collections import Counter
from dataset import Mol3DDataset, SimpleTokenizer
import argparse
from utils import set_seed
import numpy as np
import wandb
import os
import torch
import torch.nn as nn
from torch.utils.data import DataLoader
from torch.nn import fun... |
f44b7329a65cc7aae014d99d2a23a64f2de60e5d4750af266cef80189f5b9481 | Python | 8,081 | 210 | import re
from typing import Optional, Tuple
import torch
from torch import nn, Tensor
from torch_scatter import scatter
from torch_geometric.data import Data
from . import output_modules
import warnings
import numpy as np
import random
from .visnet_block import ViSNetBlock
def create_model(args):
model_args = dic... |
1293aca21b5175baae5b9008197a1c2f81ab50a7130e40d410cc34f4753426fe | Python | 8,082 | 191 | import logging
import os
import numpy as np
import pandas as pd
from sklearn.preprocessing import LabelEncoder
from helpers.data import normalize_array
def load_human_connectome_project_data(
data_file: str, scan_id: int, scan_length: int = 1200, verbose: bool = True
) -> (np.array, np.array):
"""
L... |
7cd2ff5cd666daf79983f7d9665365fada7f1057bcc3cfd1b0ee5bda1e15167d | Python | 8,082 | 205 | # this script inference based on trained models
# Mask-RCNN on detectron2:
# the folder structure should be:
# data/test (images)
# pretrained: the pretrained model model_best.pth
# Running:
# module load Detectron2/0.3-fosscuda-2019b-Python-3.7.4-PyTorch-1.6.0
#
import argparse
import os
import random
import shu... |
c2a20152ec5ee273dda9f35f836e4fdf7ed23742ff0c8a7ac88d4bfba2dcd40e | Python | 8,085 | 221 | from collections import OrderedDict
import torch.nn as nn
import torch.optim as optim
from tqdm.notebook import tqdm
from .build_pdists import get_all_pdists
from ..models.losses import *
from ..utils.utils import *
def get_optimization_trajectory(
frame_to_optimize,
parent,
reference,
container,
... |
46267f01ba377073f76630f921d81bd89097947cfb7f14060ff3f253bab95a2a | Python | 8,086 | 272 | # Import packages needs formatting
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from os import listdir
from os.path import isfile, join
from collections import defaultdict
import csv
from SMdRQA.RP_maker import RP_computer
from SMdRQA.Extract_from_RP import windowed_RP
from SMdRQA.Extract_from... |
0a9915e61fe2dc1f2b9942b8b5b8114f26b0da1f3fc5fda177f2b2e01e324043 | Python | 8,088 | 217 | #!/usr/bin/env python
#### Get command-line arguments
import argparse
arg_parser = argparse.ArgumentParser()
arg_parser.add_argument("data_file",
help="a list of data to perform inference on")
arg_parser.add_argument("data_dir",
help="directory containing the data files")
arg_parser.add... |
0f3d5b1ad44ff6715df685b5aeba9eed11f505ab57e17c564941248847be9ebe | Python | 8,089 | 176 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# 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://w... |
b3d80379d4a604ce582dfa98358969a532906f16053309b3fd7c97ee149734b5 | Python | 8,089 | 225 | """ Original Author: Haoqiang Fan """
import numpy as np
import ctypes as ct
import cv2
import sys
import os
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
showsz = 800
mousex, mousey = 0.5, 0.5
zoom = 1.0
changed = True
def onmouse(*args):
global mousex, mousey, changed
y = args[1]
x = args[2]
... |
b81466bf9b2435d5588e48ba824d5c1e84d673bc5f71e1aea074589f336f4a8b | Python | 8,095 | 274 | # 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... |
e5c8f7a44179daf36a1b0b85524a5326544d1d7c5215b974d350d595cd39315c | Python | 8,097 | 208 | """Chain for interacting with Elasticsearch Database."""
from __future__ import annotations
from typing import TYPE_CHECKING, Any
from langchain_core.callbacks import CallbackManagerForChainRun
from langchain_core.language_models import BaseLanguageModel
from langchain_core.output_parsers import BaseOutputParser, St... |
e27f2c3b58705c06f82b84957b06c83cbcf89db2d2104c7160607254a88ba8f8 | Python | 8,100 | 247 | """
Custom collections classes.
"""
__all__ = [
"ValidatedDict",
"ValidatedList",
]
from collections import abc
class ValidatedList(list):
"""A list that runs custom converter and validators when new elements are added.
Multiple converters and validators can be assigned to the list. These
are... |
4f4cd407f0466cd826be873f0b365163a901ea8a7bf8316bdaf58ef5303288c9 | Python | 8,109 | 258 | ###########################################################################################
# Utilities
# Authors: Ilyes Batatia, Gregor Simm and David Kovacs
# This program is distributed under the MIT License (see MIT.md)
###########################################################################################
imp... |
c3d5c373f2523a342cbbd23756023c72be5d2258e903d5154364512de4963b72 | Python | 8,109 | 222 | """Fake Chat Model wrapper for testing purposes."""
import re
from collections.abc import AsyncIterator, Iterator
from typing import Any, cast
from langchain_core.callbacks.manager import (
AsyncCallbackManagerForLLMRun,
CallbackManagerForLLMRun,
)
from langchain_core.language_models.chat_models import BaseCh... |
7f9711f2fdc8913175cf315bbf3c0228e5c449a9cb789a7cf44a45229a80e4e3 | Python | 8,111 | 167 | from scipy.integrate import solve_ivp
import numpy as np
import os
import h5py
from edNEGmodel.edNEGmodel_params import *
from functions.initial_values import *
from SALib.sample.saltelli import sample as ss
from SALib.analyze.sobol import analyze as sa
'''
Table 3: Factor Fixing analysis
'''
# Define the problem se... |
d369189f052aa740fa8d16b2b15496e6ad21eb2fb69ffe0428c91587717701bd | Python | 8,113 | 173 | #!/usr/bin/env python
# -*- encoding: utf-8 -*-
'''
@Description: :
@Date : 2022/06/15 00:35:33
@Author : Zilan Yu
@version : 1.0
'''
import pandas as pd
import os
clustered_root = "../clustered_datasets"
root_filter_datasets = "../filter_datasets"
filter_iedb_filepath = os.path.join(root_filter_da... |
ab05f499265925ba910fbce630cbf077774312dd23e998aebaf05af166388e28 | Python | 8,116 | 257 | '''
medip_merge_intervals.py - merge differentially methylated regions
==================================================================
:Tags: Python
Purpose
-------
This script takes the output of DESeq or EdgeR and merges
adjacent intervals that show a similar expression change.
Input is data like this::
co... |
57eddc34d8d67aeb006da6f2c3f92da7f0f625cb1b72b672a4efc668c3df60ea | Python | 8,122 | 164 | #!/usr/bin/env python3
#$ -cwd
#$ -V
#$ -N m5_his_2c
#$ -e /cluster/uz_lab/cmives/TRP_channels/MDS/permeation_analysis/z_histogram/m5_his_ce.err
#$ -o /cluster/uz_lab/cmives/TRP_channels/MDS/permeation_analysis/z_histogram/m5_his_ce.out
#$ -pe smp 2
#$ -jc long
import os
import sys
import time
import numpy as np
impor... |
7268f6fd6e143f7f9334488b0a6b02e63f45654116e1d6fc5bd3ada1014d34b5 | Python | 8,122 | 211 | import re
from typing import Optional, Tuple
import torch
from torch import nn, Tensor
from torch_scatter import scatter
from torch_geometric.data import Data
from . import output_modules
import warnings
import numpy as np
import random
from .visnet_block import ViSNetBlock
def create_model(args):
model_args = dic... |
9c36335b5d9eff9700f2deb1d166a5e135f0e1f70967ebab91f469dc4a50efb1 | Python | 8,131 | 178 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Oct 24 09:04:04 2022
@author: baran
"""
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
from scipy import stats
impedances = pd.read_csv('rat1_impedances.csv')
phases = pd.read_csv('rat1_impedance_phases.csv')
impedances = i... |
b258a8b5d15d2406ee36da8c09a7b22c775f72861a6a7634afbd75c6f44b5dae | Python | 8,132 | 186 | from collections import Counter
import numpy as np
import pandas as pd
import scanpy as sc
from sklearn.preprocessing import MaxAbsScaler, maxabs_scale
from torch.utils.data import DataLoader, Dataset, WeightedRandomSampler
def batch_scale(adata, use_rep="X", chunk_size=20000):
for b in adata.obs["source"].uniqu... |
043fd26dfbc7bb522af534a4c287dfa43e4f8ffb796604cd09ee25e5ea023a67 | Python | 8,139 | 221 | 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... |
080d8203eb0cd6708c99d59d3292b6f1064acf5d2b32f99ea02fe491b2854304 | Python | 8,141 | 181 | import os, copy
import numpy as np
import matplotlib.pyplot as plt
import torch
import plotting
import networks
from net_utils import load_from_file
def compute_FLD_weights(net, R, neuronsMask=None, SCC=False, suppressOffDiagCov=False, multiRep=False, P=0.5, addNoise=False, **genDataKwargs):
Nh,d = ... |
47f10cc70a7c875435448f73efdaf4d66129793f3d7fce0044627f70ed5d7ac2 | Python | 8,141 | 173 | """This python script allows training `MotorNet` models in parallel on the CPU. This is particularly useful for CPUs
with a large amount of cores, and should significantly improve training speed over many model iterations.
This script should be called from a terminal console, and takes up to four parameter inputs.
Ar... |
89cac49acc573eb44b32bbbdbdd4eb758677c4c1c43a5f3459d7dc35e4576f91 | Python | 8,141 | 181 | # -*- coding: utf-8 -*-
"""
Created on Mon Aug 3 10:29:19 2020
@author: nishe
"""
import firing_rate_analysis
import numpy as np
import scipy.sparse as sparse
import pickle
#%%
class mydata(object):
'''
A user defined class used to save data hierarchically.
Input data musted be either in the format of dic... |
aa7c30c19dd123c56d26ee0d2a3c3a184bc5d3be8db90e12a0c707642f00ef47 | Python | 8,142 | 214 | import unittest
import torch
from EPI_MRI.utils import get_cell_centered_grid
from EPI_MRI.ImageModels import Interp1D
class TestImageModels(unittest.TestCase):
def setUp(self):
""" Initialize any common data or setup needed for the tests. """
torch.manual_seed(81) # reproducibility with randomne... |
77127a228d846ed5a44829608e3e9b3a2db5676f021d43721d0a66248a858781 | Python | 8,146 | 191 | #!/usr/bin/env python
# -*- encoding: utf-8 -*-
'''
@Description: :
@Date : 2022/06/16 13:50:29
@Author : Zilan Yu
@version : 1.0
'''
import os, sys
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
import tensorflow as tf
import keras_metrics as km
import numpy as np
import pandas as pd
import keras
from ke... |
67855e6d751439d9a45eb0ca71115398e70a58d8eb4ac8fb812f8733013e9cc0 | Python | 8,147 | 234 | """
***************************************************************
Author: LU
Date: Nov 2020
Utilities for thalamic nuclei segmentation
***************************************************************
"""
# import files
import numpy as np
import nibabel as nib
from scipy.ndimage import morphology
from skimage.expos... |
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