sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
59dfc3f027dec9244e6a0e6a744653005d29de458b6351fa5dabb732643872b2 | Python | 4,201 | 121 | # coding=utf-8
# Copyright 2023 HuggingFace Inc.
#
# 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 ag... |
b8630a426704c34fa607eff362b01b875024d143fb74b8c88a1fe04f98ad5c64 | Python | 4,202 | 130 | # -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
"""Defines an analog matrix"""
from typing import Any, Union, Tuple
from scipy.sparse.linalg import LinearOperator
from numpy import ndarray, dtype
# Imports ... |
efc35e67a3f6a76c5334a6b091ce6984cd922a60c535d361375204cc1fb5ea05 | Python | 4,204 | 130 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
"""
"""
import argparse
import os
import firecloud.api as fapi
from firecloud import fccore
from google.cloud import storage
fcconfig = fccore.config_parse()
def get_bucket_name(namespace, workspace):
response = fapi.get_workspace(namespace, workspace)
fapi... |
06c9b42414d8fe4688a252ca13a741a4b2aea2b110906bc4440f5884341fe15a | Python | 4,205 | 105 | import requests
from .__config import base_url
from .__aux_funcs import process_response
def get_all_genes(alias=None, direction="ASC", keyword=None, pageNumber=0, pageSize=10000000, projection="SUMMARY", sortBy="hugoGeneSymbol"):
"""
Get all genes based on filter criteria (alias or keyword). \n
:param ali... |
364a53c458cbab3d88e1b2537d2d3431a648e1b3c0d47282de3bfc28121074fc | Python | 4,205 | 83 | # Copyright 2021 Division of Medical Image Computing, German Cancer Research Center (DKFZ)
# and Applied Computer Vision Lab, Helmholtz Imaging Platform
#
# 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 L... |
5a0fadec6092078007c14bb1ed3282eac3c4869fc29b9b6d908d4f9769b9068b | Python | 4,205 | 123 | import argparse
import pandas as pd
import pickle
import time
from queue import PriorityQueue
from collections import defaultdict
def read_pickle(f):
with open(f, 'rb') as inFile:
return pickle.load(inFile)
def tuple2interval(t):
return f'{t[0]}:{t[1]}-{t[2]}'
def split_interval(iv):
chrom = iv.... |
65da5df5a07841900401464ce128af9f8dbf8580c6053cc2782e989d7e11dd12 | Python | 4,205 | 105 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
321feded5aa4c9ae783cd1cda0f7b26d0560d9d6d7a6eb7ec459259bb3634b5a | Python | 4,206 | 94 | import torch
from math import sqrt
class GnTredo(object):
"""
Generate-and-Test algorithm for feed forward neural networks, based on ReDo
"""
def __init__(
self,
net,
hidden_activation,
threshold=0.01,
init='kaiming',
device="cpu"... |
6559d9d247612ec824c12ba4cd3bbde1802c006873073809648a7964b3952b68 | Python | 4,210 | 84 | # 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 numpy as np
from .datareader import MolDataReader
from .datascaler import TargetScaler
from ... |
a600490b518f26659aa4cac795e6901dd00e3de60eae7ee68bc5ea1e155bff34 | Python | 4,211 | 125 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If exte... |
2316a11540eed6444ecba18574b21b9c15677a60c5336b6fbf14eb6e3706d850 | Python | 4,212 | 119 | #!/usr/bin/env python
from __future__ import print_function
import argparse
import glob
import json
import sys
import numpy as np
import os
LEARNED_PARAM_KEY = "readErrorModel"
MIN_DIST_OFF = .00000001
def parse_args():
parser = argparse.ArgumentParser("Consolidates output learned parameters for chunked marginPha... |
16f70164f2ac13cf5c3f61d023073f5fcf50b6bdd55ac3470088b1ae0eb40efc | Python | 4,213 | 78 | from keras.layers import Dense, Flatten, Conv2D, MaxPool2D, Dropout
from common import SEED
from keras.models import Sequential
from keras.optimizers import Adam
from keras import initializers
def create_cnn_keras(lr=0.0004, image_shape=[64,64]):
model = Sequential()
initializer = initializers.he_normal(seed=... |
5d37136abd0a15d9139ef13dd82b0f4c7f2ce7907b9d2320c964c648fd7ed57a | Python | 4,213 | 113 | import torch
import esm
import numpy as np
import h5py, argparse
parser = argparse.ArgumentParser()
parser.add_argument("--PDB_coords_seq_hdf5", type=str, default="./", help="path for train hdf5 file for coordinates")
parser.add_argument("--gpu_esm", type=int, default=[3], nargs="+", help="the IDs of GPU to be used fo... |
e30e4ecc70aa389affbcf1941ddedb4d1ad71a0fa07e852919f08170200e4cf3 | Python | 4,213 | 106 | #CHM height module. Given a x,y location and a pool of CHM images, find the matching location and extract the crown level CHM measurement
import glob
import numpy as np
from src import neon_paths
import rasterstats
import geopandas as gpd
import pandas as pd
def non_zero_99_quantile(x):
"""Get height quantile of ... |
8e553548bcae8f4a25bda4050105b190bc057b0631133998286fb4ad28d7fbae | Python | 4,216 | 147 | import numpy as np
import sklearn.metrics
import torch
import math
def calc_binary_metrics(pred, target):
mat = sklearn.metrics.confusion_matrix(target, pred)
tn, fp, fn, tp = mat.ravel()
se = (tp) / (tp + fn)
sp = (tn) / (tn + fp)
ppv = tp / (tp + fp)
return se, sp, ppv
def prepare_roc_plot(... |
41cf7830017e1a827f89aaad81b898b0ec41ecb0d79103975e3bd62421a95ad8 | Python | 4,218 | 83 | """Compare an actual MATLAB-exported fixture with the imported PyTorch model."""
import argparse
import json
import sys
import numpy as np
from scipy import sparse
from scipy.io import loadmat
import torch
from palmnet import PalmPCAGabor
from palmnet.ops import ridge_orientation
def error_report(actual, expected, at... |
4a101f6bd48aafdeb6bcf6e156a8ed6e5cf41e1a8dc99998fb31c528ca2bb646 | Python | 4,220 | 101 | from enum import Enum
from typing import Callable, Dict, List
from ray._private.ray_constants import RAY_METRIC_CARDINALITY_LEVEL
from ray._private.telemetry.metric_types import MetricType
# Keep in sync with the WorkerIdKey in src/ray/stats/tag_defs.cc
WORKER_ID_TAG_KEY = "WorkerId"
# Keep in sync with the NameKey i... |
4b98cc3360812cf7b8ec1ad007f15dc69241e1e342d9ad3f76ac45a32b021ef7 | Python | 4,220 | 107 | from utils import *
if __name__ == "__main__":
SHOW = 0
# Declare the datadir and paramfile
datadir = "/cfs/klemming/scratch/n/nbrav/logs/test-mnist1k/"
# "/cfs/klemming/scratch/n/nbrav/logs/sparsespk-full/2024-04-21_14:40:38:083781"
paramfilename = "apps/hidassospk/hidassospk.par" #f"{datadi... |
9f596179ada8bd966ec430ce981b26bd561fdf3d028f12d24fbdfb40906201a5 | Python | 4,220 | 121 | # -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
"""Base class for an Experiment Runner."""
from typing import Any, Dict, List, Optional
from aihwkit.cloud.client.entities import CloudExperiment
from aihwkit.... |
e3595a588394ce6bc73f93c4d6e918853d462162d8118722c574632eaae18301 | Python | 4,220 | 140 | import logging
import tempfile
import numpy as np
import pytest
import torch
from torch import nn
import pfrl
from pfrl.envs.abc import ABC
from pfrl.experiments.evaluator import run_evaluation_episodes
from pfrl.policies import (
GaussianHeadWithStateIndependentCovariance,
SoftmaxCategoricalHead,
)
@pytest... |
ff1bf2574edd885b6636bd43fc430a8c3f7afaed8030660e37c8a85c08527b70 | Python | 4,220 | 119 | #
# CEBRA: Consistent EmBeddings of high-dimensional Recordings using Auxiliary variables
# © Mackenzie W. Mathis & Steffen Schneider (v0.4.0+)
# Source code:
# https://github.com/AdaptiveMotorControlLab/CEBRA
#
# Please see LICENSE.md for the full license document:
# https://github.com/AdaptiveMotorControlLab/CEBRA/bl... |
4469f53dc750b0e425366b60db1818b81c8761bdea41338b2ee4e95e0ccf3056 | Python | 4,221 | 97 | import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from Bio import SeqIO
from autogluon.text import TextPredictor
from sklearn.metrics import confusion_matrix
def plot_confusion_matrix(y_true, y_pred, classes,
normalize=False,
title=None... |
c16a6c3c0e5a88b220854588c300d14480c0a525bad03635735ca5d9c6b90b24 | Python | 4,221 | 102 | import pathlib
path = pathlib.Path.cwd()
if path.stem == 'tmb_survival':
cwd = path
else:
cwd = list(path.parents)[::-1][path.parts.index('tmb_survival')]
import sys
sys.path.append(str(cwd))
import numpy as np
from lifelines import CoxPHFitter
from lifelines.utils import concordance_index
import pandas as pd
i... |
8892065072f9480bc9097fdfd2993f61dab97f0e9549f7b5600ffaefa2e574e4 | Python | 4,222 | 92 | import json
from pathlib import Path
import keras
import sys
sys.path.insert(0,str(Path(__file__).resolve().parents[1]))
from mothra_runtime import CompatibleGRU, set_model_mode
#from keras.models import load_model
def prepare_data(smiles,all_smile):
all_smile_index=[]
for i in range(len(all_smile)):
... |
8a33c96011b9669532d46362a31a43940296cb3a0b4c90c82329479fb5bb6c79 | Python | 4,222 | 119 | from __future__ import annotations
"""
Build a new skill from a single link to cover functionality OmicVerse does not yet provide.
This scaffolds a SKILL.md and scrapes the provided URL (same-domain crawl)
to populate reference markdown files.
Security: validates output paths and sanitizes generated filenames.
"""
... |
590097b4fa8c4df1d4919e57293905689be43e4c43000faaef97bb4be1b7ff40 | Python | 4,223 | 125 | import os
from urllib.request import urlretrieve
import tarfile
from dstoolbox.transformers import Padder2d
from dstoolbox.transformers import TextFeaturizer
import numpy as np
from sklearn.datasets import load_files
from sklearn.pipeline import Pipeline
from skorch import NeuralNetClassifier
import torch
from torch i... |
c92ba0a37dbb3494a27cfbeb6fcc0f888262a8973823c9f086288ec27e0f5aec | Python | 4,223 | 159 | from __future__ import print_function, unicode_literals, absolute_import, division
from six.moves import range, zip, map, reduce, filter
from six import string_types
import numpy as np
from .utils import normalize
def plot_history(history,*keys,**kwargs):
"""Plot (Keras) training history returned by :func:`CAR... |
9bed055e920444332c996be08541f5f4312127d1a00498c59fd494c9e84c9e9a | Python | 4,224 | 118 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#... |
778cec5a6bd8842ff8414196d549238ccbe73b11da813e8d68b144c2fe502114 | Python | 4,225 | 109 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Oct 3 14:23:29 2022
@author: S_Barnett
"""
from glob import glob
import os
import pandas as pd
from tkinter import filedialog as fd
from docx import Document
from docx.shared import Inches
def retrieve_settings(input_folder: str, settings_key: str) -... |
a9e1f30609e66429c1ec4f34d9adb1c32411f75c9dc0624208ea5026ccea42f1 | Python | 4,226 | 136 | """
Copy from scVI (https://github.com/scverse/scvi-tools/blob/main/scvi/data/_built_in_data/_synthetic.py)
"""
import logging
from typing import Optional
import numpy as np
import pandas as pd
import scipy
from anndata import AnnData
#from scanpy import read
import scanpy as sc
from .._anndata_compat import as_dtyp... |
b407b32bd4e9b1a3eb21fc0c40cf6f90708f19c0998942d16c4f9f1788c57806 | Python | 4,226 | 143 | from absl.testing import absltest
from absl.testing import flagsaver
from absl.testing import parameterized
import numpy as np
import pandas as pd
import xarray as xr
import xarray_beam
from . import compute_quantiles
class ComputeQuantileTest(parameterized.TestCase):
def _dict_to_str(self, a_dict):
return ',... |
c31eb77f5694d3484a57293ad2de96d7c120eb485e40eb54e622d8c10be8b11d | Python | 4,226 | 92 | ####################################################################################################
# Copyright (c) 2023, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is free softw... |
3a9ec663614feb1b0fa6c981504b8d0faf7e9ed335b634faa520282a12b2ef57 | Python | 4,228 | 124 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
from functools import reduce
import math
# Caches genotype carrier status for _is_non_ref()
_carrier_map = {}
def choose_best_genotype(sample, records):
"""
Return record where sample has best non-reference genotype, if available
Parameters
----------... |
ea4f9115ef2e80da60930675956c56c5b05ee722e6b4d633f54d9b8f56da46ca | Python | 4,228 | 140 | import pathlib
import zipfile
import numpy as np
import pytest
from stl import mesh
_RELS = """<?xml version="1.0" encoding="UTF-8"?>
<Relationships
xmlns="http://schemas.openxmlformats.org/package/2006/relationships">
<Relationship Target="/3D/3dmodel.model" Id="rel0"
Type="http://schemas.microsoft.com/3dmanufa... |
93487132c0400b23d95c9c480c229d9c94fca3638f9f267193cbf17c43d6213c | Python | 4,230 | 141 | from torch.nn import Linear, ReLU, Sequential, Conv2d, MaxPool2d, Module, Dropout
from torch import softmax
from torch.nn.init import kaiming_normal_
class CNN(Module):
def __init__(self, n_dim, linear_dim):
super(CNN, self).__init__()
self.n_dim = n_dim
self.linear_dim = linear_dim
... |
215aa94e89419729ad3f5b164a9c706c9ba57ac7f28bcea4b70cedd4c8447c5a | Python | 4,234 | 86 | import os
import numpy as np
import matplotlib.pyplot as plt
import ivim
root = '/path/to/root'
input_root = os.path.join(root,'data')
results_root = os.path.join(root,'results')
subs = [sub for sub in os.listdir(results_root) if sub.startswith('sub')]
runs = ['run-{}'.format(r+1) for r in range(2)]
scans = ['sIVIM'... |
be7be1ef7dd86852fb41c33c8669dbf9390903a80e2436699b22546084c91a35 | Python | 4,234 | 82 | #!/bin/python
import argparse
import logging
def process_bed_file(input_bed, n_per_split, bca=True, digits=9):
SVTYPE_FIELD = 5
END_FIELD = 2
START_FIELD = 1
# Conditions for each category of variants
condition_prefixes = {
'gt5kb': {'condition': lambda line: (line[SVTYPE_FIELD] == 'DEL' ... |
f38c076634e35f9ba4403e3301b41b926eb94403605eade1fefd94958467812c | Python | 4,236 | 147 | import struct
import numpy as np
import pytest
from stl import mesh
_STL_FILE = """
solid test.stl
facet normal -0.014565 0.073223 -0.002897
outer loop
vertex 0.399344 0.461940 1.044090
vertex 0.500000 0.500000 1.500000
vertex 0.576120 0.500000 1.117320
endloop
endfacet
endsolid test.stl
""".lstrip()... |
303518ee61fd153c0d5d79813358eccee054002b36c6901331270d0ed66d1886 | Python | 4,239 | 145 | '''infer the underlying context by using knn with prediction error '''
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
from task import CSW
from utils import compute_smth_mean, to_sqnp
from sklearn.decomposition import PCA
from scipy.spatial import distance_matrix
sns.set(style='white', palet... |
378499552e536a0b5bd05a7bb38f6478b1a226fec510bb73974e5b245fa59889 | Python | 4,239 | 121 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon May 27 15:36:17 2019
@author: gary
"""
import numpy as np
import skvideo.io
def intensityTimeseries(vidName, nFrames, ROI, channel=0):
intense=[]
videogen = skvideo.io.vreader(vidName)
for i, frame in enumerate(videogen):
if i%100... |
104eb8f4c373b9cfe2a5285f0e691ab7bdf14a2cc311b8705dbc6d898831fb9b | Python | 4,240 | 133 | import time
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
from config import args
from models import GNN, Discriminator
from torch_geometric.data import DataLoader
from torch_geometric.nn import global_mean_pool
from util import cycle_index
from datasets import MoleculeDataset
de... |
62119539ee69fae4ed91ac31566124bc77d7dc611da1c265a4be1ca680d127cc | Python | 4,240 | 141 | import json
import numpy as np
import matplotlib.pyplot as plt
from spinnaker2 import snn, hardware
from spinnaker2.neuron_models.spikes_from_array_latency_code import SpikesFromArrayLatencyCodeApplication
from spinnaker2.helpers import read_log
SpikesFromArrayLatencyCodeApplication.profiling = True
rng = np.random.de... |
123e6d58304b2c45c4d35c6e581913c5380064727a9324f564dc64d49faf5e05 | Python | 4,242 | 104 | import os
import pandas as pd
import numpy as np
from src.commons.process_dataframe import keep_valid_columns, change_col_value_type, insert_new_col_from_two_cols, \
get_sub_df_according2col_value, get_std, get_mean
from src.commons.process_number import get_percent_change, get_deviation
from src.constants.ms2_mi... |
827ae3f2884bede82763864152ce0b19f9ac876bbbb2af0c96f1e94bda663c37 | Python | 4,242 | 141 | import numpy as np
from constants import CA_C_DIST, N_CA_DIST, N_CA_C_ANGLE
def rotation_matrix(angle, axis):
"""
Args:
angle: (n,)
axis: 0=x, 1=y, 2=z
Returns:
(n, 3, 3)
"""
n = len(angle)
R = np.eye(3)[None, :, :].repeat(n, axis=0)
axis = 2 - axis
start = ax... |
8ddb36669321cb9b281b3aa9e2d5c69be30da964c992840d62fffee194a5df7f | Python | 4,243 | 109 | """
Created on: 03/18/2014
Updated on: 05/19/2017
@author: Dorjee Gyaltsen
@brief: antibody epitope prediction - the main class
"""
import os
import sys
import pickle
from collections import OrderedDict,namedtuple
from .method_calculation import MethodScores
from .util import get_sequence
SequenceInfo = namedtuple(... |
317e46201fda034383507bb3bb47245c30427061ea314dd6878696e7b0ee7d8f | Python | 4,246 | 100 | import pathlib
path = pathlib.Path.cwd()
if path.stem == 'tmb_survival':
cwd = path
else:
cwd = list(path.parents)[::-1][path.parts.index('tmb_survival')]
import sys
sys.path.append(str(cwd))
import pickle
import pandas as pd
import numpy as np
from model.model import Encoders, NN
from model.layers import Losse... |
b9a14cf4d9c9dbdaf4b6267e774ad54427536d691e3d3f5fe7d5f5e7692e9503 | Python | 4,246 | 125 | # Copyright (c) 2017-present, Facebook, Inc.
#
# 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... |
f462b9159488eccdb8e213c1da199ecf114ea8143f9a328189c3b144492dc37f | Python | 4,246 | 192 | # flake8: noqa
# fmt: off
# __dag_tasks_begin__
import ray
ray.init()
@ray.remote
def func(src, inc=1):
return src + inc
a_ref = func.bind(1, inc=2)
assert ray.get(a_ref.execute()) == 3 # 1 + 2 = 3
b_ref = func.bind(a_ref, inc=3)
assert ray.get(b_ref.execute()) == 6 # (1 + 2) + 3 = 6
c_ref = func.bind(b_ref, in... |
33847a06ee0e08753e55c8023deed06c1229cf34ffc95f3cfab26cf7ecc49c5d | Python | 4,247 | 108 | from typing import List
from lqit.edit.models.base_models import BaseGenerator
from lqit.edit.structures import BatchPixelData
from lqit.registry import MODELS
from lqit.utils import ConfigType, OptConfigType, OptMultiConfig
@MODELS.register_module()
class TIENetGenerator(BaseGenerator):
"""The generator of TIEN... |
ba3a94acf9db63cac19f446cd9199cb41da8f902e9c6cf0f445c74fd0795b804 | Python | 4,248 | 128 | # -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
"""Tests for quant conversion."""
import torch
from pytest import mark
from torch.nn import Linear, Sequential
from aihwkit.nn.low_precision_conversion import ... |
44f28067f4473276bf6d56917c3090350084b8a5d832acdce84c3d8df2fc66c8 | Python | 4,249 | 119 | import unittest
from math import isclose
import torch
from rising.transforms.functional import (
add_noise,
add_value,
gamma_correction,
norm_mean_std,
norm_min_max,
norm_range,
norm_zero_mean_unit_std,
scale_by_value,
)
class TestIntensityFunctional(unittest.TestCase):
def setUp... |
1bea31a31a6f12b4f3e7eca27c15e8cbb095879bd7cc321d99e16f47e082bdf3 | Python | 4,250 | 121 | # -*- coding: utf-8 -*-
"""
Created on Mon Sep 21 15:14:00 2020
@author: ju-bar
Linear search function.
This code is part of the 'emilys' repository
https://github.com/ju-bar/emilys
published under the GNU General Publishing License, version 3
"""
import numpy as np
def linsrch_minloc1(data, subpix = True):
'''... |
f202aba982c1a06e18df85e15d69ef66ca1d919e26b3486ae81784f8fbcf76b4 | Python | 4,250 | 111 | # Copyright (c) 2017-present, Facebook, Inc.
#
# 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... |
22e0c633d9392d39b775984c2c0f791b56532baf321008173db9b004e21c94b7 | Python | 4,252 | 161 | from os.path import exists, isdir, join, dirname
import os
import pkg_resources
import argparse
import sys
import yaml
import ngs_mapper
# Raised when invalid config is loaded
class InvalidConfigError(Exception): pass
class Config(object):
'''
Wrapper around config yaml that raises better exception messages... |
e9653e9ae041d2b4eb1f3942e29c6b13a4f0347666a481af37dd8d439bc5511c | Python | 4,253 | 95 | import torch
from torch.nn import Parameter
# https://github.com/mourga/variational-lstm/blob/master/weight_drop.py
class WeightDrop(torch.nn.Module):
def __init__(self, module, weights, dropout=0, variational=True):
"""
Dropout class that is paired with a torch module to make sure that the SAME m... |
2bdeea24f3ce7a15b4f2fc035226c1e6ba37614b3dd9cdb6f697b9cc875a2fb7 | Python | 4,257 | 90 | import os
import h5py
import logging
import argparse
import traceback
from collections import Counter
from ml4h.defines import TENSOR_EXT, HD5_GROUP_CHAR
"""
This script copies all the hd5 datasets from all hd5 files within the 'sources'
directories to the same-named files within the 'destination' directory.
If the ... |
97e4c2dfaa9613161e8e8340157562072e8c31bad562058cf61eb0687e29e8ad | Python | 4,257 | 166 | import pdb
import numpy as np
import matplotlib.pyplot as plt
import ray
from data_assimilation.particle_filter.base import BaseForwardModel
from data_assimilation.test_cases.single_phase_pipeflow_with_leak.PDE_model import PipeflowEquations
def compute_forward_model_PDE(
forward_model,
state: np.ndarray,
... |
08c520e282f8becfb8990734a7a76ddc0fb502bd777a9ad2813beb53103f701d | Python | 4,259 | 150 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
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 annotations
import numpy as np
from scipy.optimize import curve_fit
def get_she(voltage):
u_she, u_rhe = fullc... |
4118e2583081689164e09ed144c824b4c68b0b237ac445c02af0bd06efcf2025 | Python | 4,259 | 142 | from typing import Callable, Optional
import torch
def lif_forward_single(
input_data: torch.Tensor,
alpha_mem: float,
alpha_syn: float,
state: dict,
spike_threshold: float,
spike_fn: Callable,
reset_fn: Callable,
surrogate_grad_fn: Callable,
min_v_mem: Optional[float],
norm_i... |
59c6918697a4baed90272a1a9acf85ac772d5f9efbea6022c835e072a0e3363c | Python | 4,259 | 98 | import numpy as np
import pytest
import torch
from lqit.utils import AvoidOOM
from lqit.utils.memory import cast_tensor_type
def test_avoidoom():
tensor = torch.from_numpy(np.random.random((20, 20)))
if torch.cuda.is_available():
tensor = tensor.cuda()
# get default result
default_res... |
0a39a560ef9637a6ea9b98f286c120846ea1c3f3faf466ea848929e6ca213fc4 | Python | 4,260 | 148 | import numpy as np
import tonic
import torch
import torch.nn as nn
from sinabs import from_model, layers, set_batch_size
from sinabs.backend.dynapcnn import DynapcnnNetwork
from sinabs.nir import from_nir, to_nir
import nir
ann = nn.Sequential(
nn.Conv2d(
2, 16, kernel_size=(5, 5), stride=(2, 2), padding=... |
4e83252dc59606bd47620c5ec4b49e364b27adc543fd60bd4a0c58bf96ab715b | Python | 4,261 | 145 | import ipywidgets
import exputils as eu
#TODO: Feature - events for change of values
class TextSelectionAccordionWidget(ipywidgets.Accordion):
@staticmethod
def default_config():
dc = eu.AttrDict()
dc.title = '<selection>'
dc.main_accordion = eu.AttrDict(
#layout=eu.Attr... |
5e6faf74169535dac89bceb61b7e5f6ed6fd93e7fb3f101aa5ffc97d842136d6 | Python | 4,261 | 128 | import numpy as np
from utils import random_ortho_mat
class SimpleContext():
def __init__(self, context_dim, concentration, loss_q_size=10, pseudo_count=10, stickiness=10):
self.context_dim = context_dim
self.loss_q_size = loss_q_size
self.pseudo_count = pseudo_count
self.stickin... |
61a5868cb8fa69a0f3eb846dfa1b6d6fcf6fd10750c4bb00f3a7928d9d6bee09 | Python | 4,261 | 166 | import pdb
import numpy as np
import matplotlib.pyplot as plt
import ray
from data_assimilation.particle_filter.base import BaseForwardModel
from data_assimilation.test_cases.multi_phase_pipeflow_with_leak.PDE_model import PipeflowEquations
def compute_forward_model_PDE(
forward_model,
state: np.ndarray,
... |
875dbc0396210d42bb7891a53928fca710705c492b83042ae15656fc7a0e682a | Python | 4,261 | 136 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
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 annotations
import numpy as np
import pytest
from ase import build
from ase.calculators.singlepoint import SinglePo... |
0058a223b7d36028a21022d97a07d5c0a4abd903199615fe54d3851d73c8fd09 | Python | 4,262 | 89 | __author__ = "Simon Andermatt"
__copyright__ = "Copyright (C) 2017 Simon Andermatt"
from copy import copy, deepcopy
import torch as th
from mdgru.helper import compile_arguments, harmonize_filter_size, generate_defaults_info
from ..crnn.cgru import CGRUCell
class MDRNN(th.nn.Module):
"""MDRNN class originally ... |
0d60b2c7b97ebfab7d9c13336d67cc917f893dbdfa1e586192e3eefb17dbc99c | Python | 4,262 | 123 | import torch
from diffusers import KDPM2AncestralDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class KDPM2AncestralDiscreteSchedulerTest(SchedulerCommonTest):
scheduler_classes = (KDPM2AncestralDiscreteScheduler,)
num_inference_steps = 10
de... |
f8278ac6ded108b6a8ebf804d77448527043e227dedc157294f35ce7d08d1417 | Python | 4,262 | 106 | import numpy as np
import torch
from torch.utils.data import TensorDataset
from torch.utils.data import DataLoader
class EAVDataSplit:
def __init__(self, x, y, batch_size=32):
self.x = np.array(x)
self.y = np.array(y)
self.batch_size = batch_size
def _split_features_labels(self):
... |
02053cacd35ce56e47f97a4740a56122c096619b955121b3a2a45b6a3ff72d4d | Python | 4,263 | 125 | # Modified from https://github.com/open-mmlab/mmediting/tree/1.x/
import functools
from typing import Optional
import torch.nn.functional as F
from torch import Tensor
def reduce_loss(loss: Tensor, reduction: str) -> Tensor:
"""Reduce loss as specified.
Args:
loss (Tensor): Elementwise loss tensor.
... |
3c0530b3058c2fcca17f544a051c6f598af7899bdbe5946d3a29790a62c66ef3 | Python | 4,264 | 75 | proj_dir = "/path/to/main_project_folder/" # edit this line
import numpy as np
import pandas as pd
import xarray as xr
import dask.array as da
import glob as glob
from functools import partial
import os
import sys
sys.path.append(proj_dir)
from project_fxns import load_region
from project_fxns import fxns
import impor... |
5a7398a873e3983cc1864936e02c2416bb72d46173259ba6b5f75b18dbb7c786 | Python | 4,265 | 124 | # Copyright 2023 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
ad014c433521f84bd3e28186d39516f17612f177000f271db4b6f40f86362df1 | Python | 4,265 | 73 | import numpy as np
# #significant social
# lypd1 = np.array([4,8,17]) # pro neutral anti 13.7 % 27.5% 58.8%
# etv1 = np.array([40,10,17]) # 59.7% 15% 25.3
# rspo2 = np.array([9,16,11]) #25 44.4 30.6
# ##significant food
# lypd1 = np.array([29,7,6]) # pro neutral anti 69.1 16.7 14.2 23.8 19.0
... |
441922348a2d8926cdce1b763f3f60b423df1882ea76799eb175d1ef5b435190 | Python | 4,266 | 119 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
0d86eeec67dfd602d44a97e8c8fada733242ce725417e4d7b965ae735c0d314b | Python | 4,270 | 117 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#... |
8eafa32c4c58ab0c104bb465f60b683e6fde280b09775ecbc69043683d5ccc46 | Python | 4,270 | 124 | # built-in dependencies
import sqlite3
# 3rd party dependencies
import numpy as np
import pytest
# project dependencies
from deepface.modules import datastore
from deepface.modules.database.sqlite import SqliteClient
from deepface.modules.exceptions import DuplicateEntryError
def _record(seed: int, model_name: str ... |
59f8d5e962ae9fc05df54c62eff962a4692f0ee9671371e57fd2800fc083b98c | Python | 4,271 | 111 | """Base class for building internal Ray events.
This module provides the base class for creating event builders that can
emit events to dashboard-agents aggregator agent service.
"""
from abc import ABC, abstractmethod
from typing import Optional
from ray._raylet import RayEvent
from ray.core.generated.events_base_e... |
6b53135f69fcf09fe7c544d6e425551f17158ae4cd3fbe1a867a762af2f21c44 | Python | 4,271 | 132 | #!/usr/bin/env python
"""
Useful utilities for intervals and interval trees.
"""
from intervaltree import IntervalTree, Interval
import svtest.utils.VCFUtils as vu
# Creates dictionary of trees[sv_type][contig] from iterable records of VariantRecords
def create_trees_from_records(records, variant_types, contigs):
... |
7425f6980ff43a3298f53f9841a3ec223cac78ac4418d367637a12735a8b9475 | Python | 4,271 | 93 | #
# CEBRA: Consistent EmBeddings of high-dimensional Recordings using Auxiliary variables
# © Mackenzie W. Mathis & Steffen Schneider (v0.4.0+)
# Source code:
# https://github.com/AdaptiveMotorControlLab/CEBRA
#
# Please see LICENSE.md for the full license document:
# https://github.com/AdaptiveMotorControlLab/CEBRA/bl... |
7a86bfdc6e54d2c45b8852611084cf8d2f115b3f821b56d94a4d61fb1f5b27d4 | Python | 4,272 | 131 | from dataclasses import dataclass
from typing import Tuple, Dict
import numpy as np
from denoise_inverse_alg.glm_inverse_alg import _compute_raw_coupling_indices
from lib.data_utils.matched_cells_struct import OrderedMatchedCellsStruct
from optimization_encoder.trial_glm import FittedGLMFamily, FittedFBOnlyGLMFamily
... |
10d035593d843d572182e2e268677dcfd55291fa4b7e3c5cf69cf21c9f0df4f0 | Python | 4,274 | 130 | #!/usr/bin/env python
from __future__ import print_function
# batteries
import re
import sys
import gzip
import argparse
import logging
from time import time
# 3rd party
from lxml import etree
# argparse
desc = 'Convert UniRef XML to taxonomy table'
epi = """DESCRIPTION:
A simple script to convert UniRef XML to table ... |
1c23024fcb5b57dd9e667f0d8ddb6623aac31421b36e09fa49b412cddf3de525 | Python | 4,274 | 129 | from typing import TYPE_CHECKING
import pandas as pd
if TYPE_CHECKING:
from .schemas import (
ClassificationTarget,
RegressionTarget,
TabularDatasetData,
)
__all__ = [
"generate_classification_target",
"generate_regression_target",
"merge_signals_from_multiple_cameras",
]
... |
f1bd893b602c5bb3df5e4c5a47c38cf3569ddfd53ffd464af9e02db824093200 | Python | 4,274 | 95 | ####################################################################################################
# Copyright (c) 2020 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
05c6f6f7c86f064461f1c9e483427f257f9b3b5db548be9a7aad53140cef1e36 | Python | 4,275 | 146 | import os
import json
from typing import Dict, Any, Union, Optional
import boto3
import xarray as xr
import numpy as np
from neuron_morphology.transforms.pia_wm_streamlines.calculate_pia_wm_streamlines import run_streamlines
from harness import step_fns_ecs_harness
s3 = boto3.client("s3")
DatasetLike = Union[xr.... |
64a24759ac5ab1d45ff742dbe5240fa4346e2808a711be623b4ca49a2cf620db | Python | 4,275 | 136 | '''
check if we can cluster the scene vectors
in particular, can we derive good clustering parameters from the training set
and generalize to the validation set
this is essential for the clustering based shortcut model to work
'''
import os
import pickle
import numpy as np
import pandas as pd
import seaborn as sns
imp... |
3eccbf648a7f2b32c4b511b1eaec4217fb0d5ab66e49a294fe6281978e9411e5 | Python | 4,276 | 139 | import logging
import numpy as np
import scipy.sparse as sp
from scipy.sparse import csr_matrix, issparse
def linear_embedding_velocity(V, PCs):
return V @ PCs
def _estimate_dt(X, V, nbrs_idx):
"""Estimates the time step (`dt`) based on local density for each cell.
This function calculates an estimate ... |
a3f956bec505da63e1008e0e96747277b9bcf7023f012d6abf09b3fb8bb50584 | Python | 4,276 | 124 | import os
from deepinterpolation.generator_collection import SingleTifGenerator
from deepinterpolation.trainor_collection import core_trainer
from deepinterpolation.network_collection import unet_single_1024
import datetime
import pathlib
if __name__ == '__main__':
# This is used for record-keeping
now = datet... |
6d27cc44ddcb8a4600882fccd81fd44b40eb58940e17f9a7727ed82d716ef181 | Python | 4,277 | 118 | import logging
from ray._private.utils import get_num_cpus
logger = logging.getLogger(__name__)
CPU_USAGE_PATH = "/sys/fs/cgroup/cpuacct/cpuacct.usage"
CPU_USAGE_PATH_V2 = "/sys/fs/cgroup/cpu.stat"
PROC_STAT_PATH = "/proc/stat"
container_num_cpus = None
host_num_cpus = None
last_cpu_usage = None
last_system_usage ... |
51c006efffd63b0bc7d99e590e89d8c2c19e105c1afbec7de3685b3ad6d42d09 | Python | 4,278 | 123 | import os
import subprocess as sp
import unittest
import shutil
import tempfile
from neuron_morphology.morphology_builder import MorphologyBuilder
from neuron_morphology.swc_io import morphology_to_swc
from neuron_morphology.transforms.scale_correction.compute_scale_correction import (
estimate_scale_correction, r... |
84df45bbbda2b7b3e67e19846304deb81c0d6f3fb6198144f58676796a55b3de | Python | 4,279 | 119 | # -*- coding: utf-8 -*-
import pytest
from nilearn.image import concat_imgs, index_img, math_img
from nilearn.maskers import NiftiMasker
from numpy.testing import assert_array_almost_equal
from fmralign.template_alignment import TemplateAlignment, _rescaled_euclidean_mean
from fmralign.tests.utils import random_niimg,... |
e9514494702454b4ad94dad9d651cff0994f2eb30dddab8d3eab6b07f05affcc | Python | 4,279 | 143 | import functools
from typing import Callable, Dict
import numpy as np
import pandas as pd
from pandas.api import types as pdt
from visions.backends.pandas.series_utils import series_handle_nulls
from data_profiling.config import Settings
from data_profiling.utils.versions import is_pandas_1
def is_nulla... |
44502b0c92486d1d8123ae8627a01c21840fcc6a8ba3e3a49d5b48f253b7839b | Python | 4,280 | 172 | """
Script for tuning synfire chain parameters.
original parameters and model from Yexin:
V_rest = -70
V_reset = -70
threshold = -57
T_refract = 2
exp_TC = 0.904837
g_membrane = 29
I_offset = 0
V_rev_E = 0
V_rev_I = -75
exc_decay = 0.513417119
inh_decay = 0.367879441
exc_init = 0... |
6829b9edc0336ca3feac59482a372b809574d6b689314d2aa96945585d5da459 | Python | 4,280 | 139 | """
These are 'standard' batch correction methods to compare with.
"""
import scanpy as sc
import scvelo as scv
import numpy as np
import scipy as scp
import anndata as ad
def compute_scvi(adata_raw, counts_key = 'counts_spliced', batch_key = 'batch', n_latent=20, gene_likelihood='nb',
encode_covaria... |
a347259e30775d799e7ce3638fd3676c3df0bdcdd03633528aa9bb443f7a2ff7 | Python | 4,280 | 86 | # Copyright 2023 Kakao Brain and The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... |
39adc05743137474d783865bb15fba980c776e03f44762588414ecc2a9cc1d44 | Python | 4,282 | 148 | import os
import sys
import pytest
import ray
from ray._private.test_utils import request_with_auth_token
from ray.job_submission import JobSubmissionClient
from ray.tests.conftest import * # noqa
# For local testing on a Macbook, set `export TEST_ON_DARWIN=1`.
TEST_ON_DARWIN = os.environ.get("TEST_ON_DARWIN", "0")... |
fb3d0d207bc057f6c5463d405480c9ac4d8c769907eeecff838374392bca088c | Python | 4,282 | 117 | #!/usr/bin/env python3
"""Plot the enrichment of covariates on graphs."""
import logging
import numpy as np
import pandas as pd
# Plotting:
from matplotlib import pyplot as plt
import seaborn as sns
from .utils_enrichment import calc_df_enrichment, format_enrichment_matrices
def plot_df_enrichment(obj, graph_id, df... |
4593fe267d9018e61892b77bfc97e39eae11d5ad7ed0542caa47e10478999d20 | Python | 4,283 | 123 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
Script to generate gifs from traj
Note:
This is just a quick way to generate gifs and visualizations from traj, there are many parameters and ... |
9264287572b71522e43e19237dec723349df175d841c0b157904deb7e134779a | Python | 4,283 | 108 | from typing import Optional, Sequence
from mmeval.metrics import StructuralSimilarity as MMEVAL_SSIM
from lqit.registry import METRICS
@METRICS.register_module()
class StructuralSimilarity(MMEVAL_SSIM):
"""Calculate SSIM (structural similarity). A wrapper of :
class:`mmeval.SSIM`.
Ref:
Image quali... |
c4c752d1d56d13daeb014015f86a63060ced512138a95dd68cd1796e39659f3c | Python | 4,284 | 133 | #!/usr/bin/env python
# coding: utf-8
# In[5]:
import numpy as np
import tensorflow.keras as keras
import os
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import *
from tensorflow.keras import backend as K
import tensorflow as tf
import pdb
gpus = tf.config.experimental.list_phys... |
bcdc028da7b24f16c37bc69f7b99bd59f677a6c85c28ba7079d81d7fd48dce49 | Python | 4,285 | 112 | # --------------------------------------------------------
# SimMIM
# Copyright (c) 2021 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Zhenda Xie
# --------------------------------------------------------
import os
import torch.distributed as dist
from torch.utils.data import DataLo... |
40025f2f54ee7815f98d80aab133731c8a951a315d9306a605089904da067a50 | Python | 4,286 | 101 | import numpy as np
import matplotlib.pyplot as plt
import string
from itertools import cycle
def label_axes(fig, labels=None, loc=None, **kwargs):
"""
Walks through axes and labels each.
kwargs are collected and passed to `annotate`
Parameters
----------
fig : Figure
Figure object to... |
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