sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
41fcecb95d34374e659af8c2d8ea249bf5b5a69dc9c328fb968618c540dbc584 | Python | 6,326 | 156 | from rl_games.algos_torch import torch_ext
import torch
import numpy as np
class AlgoObserver:
def __init__(self):
pass
def before_init(self, base_name, config, experiment_name):
pass
def after_init(self, algo):
pass
def process_infos(self, infos, done_indices):
pass... |
8b93ecbeb0822694c613cc9b4078ff8df8ceebf8dc654e7caac9d8fe1311ef37 | Python | 6,329 | 168 | from datetime import datetime
import numpy as np
from pandas.errors import Pandas4Warning
import pandas as pd
import pandas._testing as tm
class TestCombineFirst:
def test_combine_first_period_datetime(self):
# GH#3367
didx = pd.date_range(start="1950-01-31", end="1950-07-31", freq="ME")
... |
d9daa4488f53593b16080ec871b7b5f776f7309bd6380768313d5cc7feb0651d | Python | 6,329 | 201 | """Tests for thriveline utilities in velocity.py."""
from __future__ import annotations
import math
import warnings
import numpy as np
import pytest
import xarray as xr
from scipy.stats import norm
from pcntoolkit.math_functions.velocity import (
_resolve_reference_batch_effects,
compute_thriveline_z,
t... |
7bf4ea779acc8895fca85562e872972607e3795ddcdcd5aa6978f33182acdbfc | Python | 6,334 | 167 | import numpy as np, matplotlib.pyplot as plt, sys
import pumpprobe as pp, wormdatamodel as wormdm
from scipy.optimize import curve_fit
import matplotlib.ticker as ticker
plt.rc('axes',labelsize=12)
plt.rc('xtick',labelsize=14)
plt.rc('ytick',labelsize=14)
ds_list = "/projects/LEIFER/francesco/funatlas_list.txt"
ds_ta... |
d8b63cb01ea552eb21b4a38146dfd74c0b860ae05c8fccac78342b4b364733d9 | Python | 6,335 | 161 | import datetime
import glob
import os
import re
import numpy as np
from tqdm.auto import tqdm
from .session import Session, SessionCollection
_rx_dict = {
"StartDate": re.compile(r"^Start Date: (?P<StartDate>.*)\r\n"),
"EndDate": re.compile(r"^End Date: (?P<EndDate>.*)\r\n"),
"StartTime": re.compile(r"^... |
4693a0143356e2073e8c4016cf7f19207d6abbddf4dd95284e0ba88ecb7fc5b5 | Python | 6,337 | 231 | import numpy as np
import matplotlib.pyplot as plt
# increase the figure size
plt.rcParams["figure.figsize"] = [12, 10]
# remove the top and right spines from plot in the global plt setting
plt.rcParams["axes.spines.top"] = False
plt.rcParams["axes.spines.right"] = False
# change the linewidth of the axes and spines
... |
af0e2433a247b8f4f5fceba856e19d823ce62c32daa7951c09400ab5a9a6b9cf | Python | 6,338 | 189 | #
# hologram.py -- Michael Pun -- 28 January 2021
#
# This module contains the functions used to project point clouds
# characterized by arrays of spherical coordinates into spherical
# coefficients. The functions also allow for a channel dimensions
# to encode any information that is not spatial in the data.
#
# imp... |
ae47b01e473331c38d4130cf347a1dc42f9ea78c8c18fef72c621347973523f5 | Python | 6,339 | 159 | # Copyright (c) 2018-2023, NVIDIA Corporation
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this
# list of condit... |
f62afee30d4fb923bbfb5e26e56f1343ed06b94709a3afb1acd730fcac46b145 | Python | 6,339 | 182 | """
Pretrained models in test/resources/pretrained_* were produced by an actual training
run under PCNtoolkit 1.1.2 with a single response variable. They test
pcntoolkit/util/migration.py which was introduced in v1.1.2.
"""
from pathlib import Path
import pytest
from pcntoolkit.normative_model import NormativeModel
... |
9512d7ef50e4196622ba7b345f8b0d5c60a0313fbab88e496f5ef0420deefad9 | Python | 6,344 | 162 | # Copyright 2026 Xanadu Quantum Technologies 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 agre... |
c4a51b1e127d8d14bb691f4e78e3d1f36d77ecc3191a499676976e93de4361b8 | Python | 6,347 | 170 | import logging
import os
import pickle
from pathlib import Path
import click
import shutil
import matplotlib.pyplot as plt
import mlflow
import numpy as np
import pandas as pd
from dotenv import find_dotenv, load_dotenv
from sklearn.utils.class_weight import compute_sample_weight
from sklearn.metrics import (accuracy... |
17cfd9eae75fa404fb3ed80ffbdda6a2e1b279dfa5b60eaee7da67e659cf677a | Python | 6,356 | 193 | """
command-line app to update the necessary databases
Authors:
Benjamin Schubert
"""
import ftplib
import datetime
import os
import errno
import zlib
from functools import partial
from pathlib import Path
import click
from evcouplings.compare import SIFTS
from evcouplings.utils import Progressbar
UNIPROT_URL =... |
afa3b388a3213e0e4c2136c5e95db96476f863b37eeb121b4d27fb925996d354 | Python | 6,356 | 171 | """Tests for the v4 self-supervised pretraining feature.
The pretrainer was non-functional dead code in scsims 3.x; v4 rewrites
it as a real LightningModule wrapping pytorch_tabnet's TabNetPretraining
plus a `transfer_pretrained_weights` helper. These tests pin the
behavior we promised in the v4 release notes.
"""
fr... |
130a0ea8ac0d0516aac7d89c79e89152cb69c95e9b41b3a837fe18d5c256bb5f | Python | 6,360 | 165 | #%%
# -*- coding: utf-8 -*-
import numpy as np
from pydrake.all import MathematicalProgram, Solve
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon as matplotlib_polygon
import matplotlib
import math
from pydrake.math import sin, cos, sqrt
import pickle as pkl
from scipy.interpo... |
eb4396a1b8cb8581276d9e669024793587af1acc7ef277ea57c095cad6ec36fc | Python | 6,366 | 200 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# Shape-Out 2 documentation build configuration file, created by
# sphinx-quickstart on Tue Sep 26 17:55:31 2017.
#
# 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
... |
53e0f291f2f474727f2d0ad737c3bd15abe1d891a09758e7deb66c208c709406 | Python | 6,368 | 231 | from __future__ import annotations
import numpy as np
import pytest
from pandas._libs import lib
from pandas.compat import (
pa_version_under19p0,
)
from pandas.core.dtypes.dtypes import (
ArrowDtype,
CategoricalDtypeType,
)
import pandas as pd
import pandas._testing as tm
from pandas.api.types import (... |
16230e7d2067573ea5f3db2dc34d93a33dc3f9aeb2c55cd62de8676ea6dd5b26 | Python | 6,372 | 157 | #!/usr/bin/env python3
"""
Description:
This module performs the SPIT-Test. The test randomly splits the control group in half, and identifies the most significant difference in isoform fractions between the two halves. The observations from this process can then be used to compare candidate DTU events in terms of... |
d6b0549e0f177c6735ba56d43eb0bb2c9ea0b89151595b25e1ab1cf94da6ed1f | Python | 6,372 | 192 | """
Benchmarks in this file depend mostly on code in _libs/
We have to created masked arrays to test the masked engine though. The
array is unpacked on the Cython level.
If a PR does not edit anything in _libs, it is very unlikely that benchmarks
in this file will be affected.
"""
import numpy as np
from pandas._li... |
6177ee4a781ff9e69b4c10b8a1de1e07bc3cbc13ab93637eb18d6b74dfbb99b9 | Python | 6,374 | 166 | from keras.models import Sequential, Model
from keras.layers import LSTM, Dense, Dropout, TimeDistributed, Conv2D, MaxPooling2D, Flatten, concatenate
from keras.optimizers import Adam
from sklearn.model_selection import StratifiedKFold
import numpy as np
from keras import backend as K
from keras.utils import Sequence
i... |
9ca8041e592d6487d39620a00d44368f03b3186f9e72fedc1c6fda964188f5f0 | Python | 6,376 | 157 | # emacs: -*- mode: python-mode; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-
# ex: set sts=4 ts=4 sw=4 et:
"""
.. _metas_subtraction:
=================================
Subtraction and conjunction CBMAs
=================================
The (coordinate-based) ALE subtraction method tests at which voxe... |
9fc9eff6f5671f1e653eba2b2c93d502f63e197b31ba69f522aea8aeb75fa410 | Python | 6,376 | 135 | # Copyright (c) 2018-2023, NVIDIA Corporation
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this
# list of condit... |
64b164c721223674e55fcc897e7d562265b9bb72c7b48a99c38c3f15c94493a0 | Python | 6,380 | 201 | # Copyright 2018-2024 Xanadu Quantum Technologies 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... |
6f8060e27b1d0c37a5234de159da7ad9e6d649520e8298817294b22aa66a04fa | Python | 6,380 | 193 | import numpy as np
import pytest
from pandas.core.dtypes.cast import can_hold_element
import pandas as pd
def test_can_hold_element_range(any_int_numpy_dtype):
# GH#44261
dtype = np.dtype(any_int_numpy_dtype)
arr = np.array([], dtype=dtype)
rng = range(2, 127)
assert can_hold_element(arr, rng)
... |
126512d6b666d7f7195d092d0c846e7e990ea91ccf2d623e6e2b144c9c7f5ad9 | Python | 6,381 | 189 | #!/usr/bin/env python3
import fire, json, os
import tensorflow as tf
import encoder, surprisal, model
BATCH_SIZE = 1
DELIMITER = '!ARTICLE'
def get_delimited_texts(lineitems_fn):
'''Returns the texts in the delim.linetimes file. Each text
is preceded by a line with a special delimiter token. Output is a
... |
cccb6eb6372b465641bfb23565ce483da8349d538c2c4ad589dc1b8a35534645 | Python | 6,381 | 177 | """In-process deployment registry.
A thin LRU-style cache that loads a fitted pipeline from disk on first
prediction and keeps it in memory until the deployment is deleted or the
process recycles. No out-of-process worker, no remote protocol — the whole
point of 4.0's serving story is "the same FastAPI process answers... |
0367012be384be50ea183864626d15a746eb82ed65f0ed5f2856173a66480cec | Python | 6,386 | 204 | from datetime import (
UTC,
datetime,
)
import numpy as np
import pytest
from pandas._libs.tslibs import (
OutOfBoundsDatetime,
OutOfBoundsTimedelta,
astype_overflowsafe,
conversion,
iNaT,
timezones,
tz_convert_from_utc,
tzconversion,
)
import pandas as pd
import pandas._testi... |
075eb1662aab302e02136646b857887f01aca93dfcbd15a79d5fccf467495862 | Python | 6,386 | 162 | # Copyright 2026 Xanadu Quantum Technologies 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 agre... |
217ff010763d3e184ec35b80388eba7b27c235dcb49121e08aebdfe7f22ef90f | Python | 6,386 | 188 | #
# -*- coding: utf-8 -*-
#
# gvar documentation build configuration file, created by
# sphinx-quickstart on Sat Dec 26 13:11:17 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 ... |
b0adba8683636710cc031b9938f68800c405cb8aee1950e8328fa3030fc8bc13 | Python | 6,386 | 145 | import torch
from torch.nn import Sequential, Linear, ELU, Tanh, Module
from pathlib import Path
from typing import Iterable, Tuple
import numpy as np
class APEmulator(Module):
nr_conds : int #No. max. conductances
max_conds_names : Iterable[str]
max_conds_ranges : Tuple[np.ndarray, np.ndarray]
vm_ampl... |
8732772e10b42b2f160d7670670d075bc6c5ac77277dc6c82fe34d6ab111f439 | Python | 6,387 | 194 | import torch
import torch.nn as nn
from torch.nn.utils.parametrizations import spectral_norm
from torch.utils.data import DataLoader
import pytorch_lightning as pl
class Generator(nn.Module):
def __init__(self, z_dim, x_dim, n_hidden_layers=8, n_hidden_nodes=100):
super().__init__()
self.z_dim = ... |
8e1878a9982c4b6436c077e9ee8fe1d0af77bc72b4f9b12d892dd676bf3f1d1c | Python | 6,387 | 170 | import dclab
class FilterRay(object):
def __init__(self, slot):
"""Manages filter-based dataset hierarchies
Filter rays are used to cache RTDCBase filter-hierarchy
children.
"""
#: identifier of the ray (matches the slot)
self.identifier = slot.identifier
#... |
bc00abc17adf68ca0e50ec951fbaee4516c99ccf8027c3bcf50a9ec40bc627f6 | Python | 6,387 | 170 | import numpy as np
import matplotlib.pyplot as plt, matplotlib.gridspec as gridspec
import matplotlib.ticker
c_in_wt = "C0"
c_not_in_wt = "C1"
c_wt = "C2"
c_unc31 = "C9"
def make_alphacolorbar(cax,vmin,vmax,tickstep,
alphamin,alphamax,nalphaticks,
cmap="viridis",bg_gray=0... |
d2eeb129a44ea5066293933595dafc31bdff9f23606c4bd7f1477b86e9038c78 | Python | 6,387 | 188 | ''' Create and display commands needed to populate DynamoDB
'''
import argparse
from glob import glob
import json
import os
from os.path import exists
import re
import sys
import colorlog
import requests
from simple_term_menu import TerminalMenu
from tqdm import tqdm
# pylint: disable=no-member
# Configuration
CONFIG... |
d5899c9fe96a571db24ddb03dba5b1641d28e968a15b55cbff80ff8bf1ffb223 | Python | 6,389 | 157 | #!/usr/bin/env python3
"""
The purpose of this script is to update the the 'scpca-meta.json' checkpoint files of already processed libraries to be up to date with changes in `scpca-nf`.
This includes addition of the following missing fields in the mapping checkpoints:
- 'ref_mito'
- 'ref_fasta_index'
- 'assay_ontolog... |
cdb01f7138a755b96a9330227d968b58ca35ca745554f369b55391a562ee4a6b | Python | 6,390 | 169 | # Module: containers.metrics.anomaly
# Author: Antoni Baum (Yard1) <antoni.baum@protonmail.com>
# License: MIT
# The purpose of this module is to serve as a central repository of anomaly metrics. The `anomaly` module will
# call `get_all_metrics_containers()`, which will return instances of all classes in this module ... |
32c9f101c62ec3c49dbb96cca0f6123e3cb98067cb05a62df36f617cea2c5a55 | Python | 6,391 | 145 | import os
import pickle
import numpy as np
from sklearn.model_selection import KFold
from datetime import datetime
import Load as Load
import Models
import Processing
import Statistics
startTime = datetime.now()
# Define Parameters
tmin, tmax = -0.3, 0.3
sr = 128
n_folds = 5
delays = - np.arange(n... |
af88143bebaacf5e7ba487c48f4cfcab44a33340a34296bdaff5a0f01ad32933 | Python | 6,392 | 171 | #!/usr/bin/env python
# coding: utf-8
import sys
import numpy as np
import pandas as pd
import pickle
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import StandardScaler
from sklearn.feature_selection import SelectKBest, f_classif
from sklearn.linear_model import LogisticRegression
from skl... |
1e8ebc8c28f60cc58d912718e6fead3d6fd284517525c7b872bb1eaa8f12cb80 | Python | 6,394 | 192 | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
# Created by Roberto Preste
from concurrent.futures import ThreadPoolExecutor
import apybiomart as apy
from mtoolnote.classes import Field, Variant, Parser, Annotator
from mtoolnote.constants import NONHUMAN_HEADERS, SPECIES
# TODO: these two can be deleted, only keepin... |
68d096fe6985bec0d103c55f04477ebd0e4d69e284ff047218c5ad228a50efc4 | Python | 6,395 | 168 | """
.. _metas_subtraction:
============================
Two-sample ALE meta-analysis
============================
Meta-analytic projects often involve a number of common steps comparing two or more samples.
In this example, we replicate the ALE-based analyses from :footcite:t:`enge2021meta`.
A common project workf... |
5ae73fc460191934fa3e3e975592d8bd4a40315876c6230d8ce3acd13f55c893 | Python | 6,400 | 228 | import json
import tempfile
from pathlib import Path
import numpy as np
from kilosort import io
def test_probe_io():
# Create one-column probe with 5 contacts, spaced 1um apart.
json_probe = {
'chanMap': np.arange(5),
'xc': np.ones(5),
'yc': np.arange(5),
'kcoords': np.zeros(... |
99919cdef3cc02c96e082fe72aac14df8df1c0028174ebca397f9a02d97f75a7 | Python | 6,406 | 234 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
def test_data_frame_value_counts_unsorted():
df = pd.DataFrame(
{"num_legs": [2, 4, 4, 6], "num_wings": [2, 0, 0, 0]},
index=["falcon", "dog", "cat", "ant"],
)
result = df.value_counts(sort=False)
expec... |
e36acff5fb9bfa3003d811de426aa7ad33f390282d8a8c3ab96c6dfe8a0edcd9 | Python | 6,407 | 145 | #
# Pythonla module to implement equivariant neural network
# based on Clebsch-Gordan networks. This module uses linearity.py
# and nonlinearity.py to implement the linear and nonlinear operations
# of CG networks. Then it implements a dense layer at the end to
# classify the scalar output of every layer in the CG net... |
18937abda81b10ac27f60ca4ace22ba508570cc7d796e3d984baacffe1d1278b | Python | 6,408 | 191 | import os
from sklearn.model_selection import KFold
import os
import numpy as np
from PIL import Image
from torch.utils import data
from utils import image_helpers
class_colors = {
"BG": [255, 255, 255],
"REF": [66, 146, 197],
"INS": [251, 246, 180],
"DEL": [253, 229, 217],
"INV": [127, 106, 187],... |
65637ff5ad5677d20ffc749d650505421c7b648ee9ed405e6028d9eda882885f | Python | 6,410 | 179 | import torch
import wandb
import numpy as np
from tqdm import tqdm
from matplotlib import pyplot as plt
from typing import Optional
from opacus.utils.batch_memory_manager import BatchMemoryManager
from twoandahalfdimensions.utils.config import DataViewAxis, Config
def train_step(data, label, model, opt, loss_fn, set... |
f41115cfe2459296bb037355dde0720aa4eedfbb6a430d47c8947cf5e461788d | Python | 6,411 | 199 | #!/usr/bin/env python3
# JN 2015-05-05
# put out clustering data in old spikes/times format for response plots
"""
convert groups to old style spikes/times files for response plotting
"""
from __future__ import division, print_function, absolute_import
import os
import csv
# pylint: disable=E1101
import numpy as np
... |
bfbd7c30ba919a1e2878840bf457c76e7b62ce67198d2b79db6d37bb0aef3749 | Python | 6,413 | 204 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# EVcouplings documentation build configuration file, created by
# sphinx-quickstart on Thu Aug 17 09:30:42 2017.
#
# 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
... |
de6a9d60560013d26463a10e8a2de0024d96e81bcbd86440e6b60950a7eb56a6 | Python | 6,413 | 176 | import tensorflow as tf
import subprocess
import sys
import numpy as np
from halo import Halo
from const import SIZE
from dataset import load_all_datasets
def model(img, mask, dims):
init = tf.contrib.layers.xavier_initializer()
training = tf.placeholder_with_default(True, shape=[], name="training")
i... |
cc79aa06399122d168a33c30d8035c62581c8b520f434453e98a1b947e827002 | Python | 6,414 | 153 | # -*- coding: utf-8 -*-
"""
Unit tests for the kCSD methods
This was written by :
Chaitanya Chintaluri,
Laboratory of Neuroinformatics,
Nencki Institute of Exprimental Biology, Warsaw.
:license: Modified BSD, see LICENSE.txt for details.
"""
import unittest
import numpy as np
from kcsd import ValidateKCSD1D, ValidateK... |
146138bc1cbe2eb0002a39671ca7c1c7c0b41a81fd6ca4788cfa0c1d90de0a5b | Python | 6,416 | 133 | from Environment import *
from Parameter import *
def volume_ratio(region_path, label_path, region_name, min_volume=Stats['min_volume'], max_volume=Stats['max_volume']):
'''volume ratio (computed as (total plaque volume in the region)/(region volume))'''
region = tifffile.imread(os.path.join(region_path, 'Reg... |
16676b648efae67949d2371d3c13f896020b3988b7554b755d4366d1fc69e908 | Python | 6,419 | 200 | from abc import ABC
from torch import Tensor, nn, stack, concatenate
from twoandahalfdimensions.utils.config import DataViewAxis
class Lambda(nn.Module):
def __init__(self, lambda_expr) -> None:
super().__init__()
self.lambda_expr = lambda_expr
def forward(self, x):
return self.lamb... |
6d177c429512092fdc241da0e59e74876075ce9395dccbd4e6a40221542d7855 | Python | 6,420 | 293 | """
Validate that the titles in the rst files follow the proper capitalization convention.
Print the titles that do not follow the convention.
Usage::
As pre-commit hook (recommended):
pre-commit run title-capitalization --all-files
From the command-line:
python scripts/validate_rst_title_capitalization.py ... |
3adff1a9a7ca3563dcfe9682b268f69e5907af9a9387e7eccbb83f934083a60e | Python | 6,421 | 130 | #!/usr/bin/python
from __future__ import print_function
import os
import sys
import numpy as np
import argparse
from stl import mesh
from string import Template
from scipy.optimize import newton
def grading_function(k, n, L, ds):
return L/ds - (np.power(k, n)-1)/(k-1)
def dgrading_function_dk(k, n, *args, **kwa... |
ab6974e6fddae0c5c2f6fcf8a70899e2f5ca0531014a624e429c542cc6029f19 | Python | 6,423 | 187 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
class TestTranspose:
def test_transpose_td64_intervals(self):
# GH#44917
tdi = pd.timedelta_range("0 Days", "3 Days")
ii = pd.IntervalIndex.from_breaks(tdi)
ii = ii.insert(-1, np.nan)
df = pd... |
4b2676db7909bd1ebbe5ca488b7ca3320ded57f68d178f1d1e4b7d61c74b1fdd | Python | 6,424 | 162 | """MD-CNN radial cardiac cine dataset."""
import concurrent.futures
import io
import re
import urllib.request
from collections.abc import Sequence
from os import PathLike
from pathlib import Path
import numpy as np
import platformdirs
import scipy.io
import torch
from einops import rearrange
from torch.utils.data imp... |
921b7e1f507a131e6d5221d38975b0bc8f6d673527914335f4c256934891c9de | Python | 6,426 | 171 | """Test metrics module."""
import numpy as np
import pandas as pd
from omegaconf import OmegaConf
from lightning_pose.metrics import (
compute_metrics_single,
pca_multiview_reprojection_error,
pca_singleview_reprojection_error,
pixel_error,
temporal_norm,
)
from lightning_pose.utils.pca import Key... |
eda2fa1f16497639b94028086989b8f7e9d55e71a6a2c1c21274d672dbf71136 | Python | 6,427 | 164 | # Copyright 2026 Xanadu Quantum Technologies 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 agre... |
49aea107560e106c242bd72fabe90611333c20b50d21b080aa12e6dcf76da9c4 | Python | 6,431 | 151 | # Copyright 2018-2021 Xanadu Quantum Technologies 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... |
3ad1df06340ef757a1790d66e796ca57abcfbbbc540672fda5ec65ce4e05e2b2 | Python | 6,433 | 176 | # Copyright 2018-2023 Xanadu Quantum Technologies 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... |
6a463b3c65de82f8c8b5964e93791311d8c79b11d1cf1d5be25c394550ff4c9e | Python | 6,434 | 149 | """PAOPAC parity against the original compiled Windows prediction interface."""
import gzip
import hashlib
import importlib.util
import json
from pathlib import Path
import anndata
import numpy as np
import pandas as pd
import pytest
import torch
from pyaging.models._paopac import PAOPAC
FIXTURES = Path(__file__).r... |
cc4255fffe4776daf8438a0466fb935e91dca1e869d857020a0cc5e61000a405 | Python | 6,434 | 164 | from game_functions import Game
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm, use
from matplotlib import rc
from pylab import rcParams
import sys
from helper_compute_performance import compute_performance
from helper_history import history
from scipy.optimize import cur... |
c1d33d756d36e77d247af87d7a7eb327b1d1fbb553e60c575b5c29529bd5c0cf | Python | 6,435 | 206 | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import torch
from torch_scatter import scatter
from ocpmodels.modules.scaling import ScaleFactor
from ..initializers import he_orthogonal_i... |
0ff5b724b180f22203b8436c3acb5ef3ae2c6063cc25dc2463fe23521c61bad1 | Python | 6,437 | 178 | from datetime import timedelta
import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
from pandas.core.arrays import TimedeltaArray
class TestTimedeltaIndex:
def test_astype_object(self):
idx = pd.timedelta_range(start="1 days", periods=4, freq="D", name="idx")
expecte... |
ce9429c6251d883ec264286e89524b3cb3eb75684495364f6bdbffd69bf93061 | Python | 6,437 | 216 | """
Tests for the following offsets:
- BYearBegin
- BYearEnd
"""
from __future__ import annotations
from datetime import datetime
import pytest
from pandas.tests.tseries.offsets.common import (
assert_is_on_offset,
assert_offset_equal,
)
from pandas.tseries.offsets import (
BYearBegin,
BYearEnd,
)
... |
4971c010f732e16198995735776213ec30f1e230c5b608d9519e66ca31073343 | Python | 6,438 | 207 | __all__ = [
"PeptideRTData",
"PeptideRTDataBatch",
"PeptideRTDataConverter",
"PeptideRTDataset",
]
import os
from logging import Logger
from typing import (
Any,
Generic,
List,
Mapping,
NamedTuple,
Optional,
Protocol,
TypeVar,
Union,
overload,
)
import numpy as ... |
a015d325345a52f36551aa681ab602c51687df30ba05f9340fab5bd592b84a23 | Python | 6,444 | 141 | from rl_games.algos_torch import torch_ext
import torch
import torch.nn as nn
import numpy as np
from typing import Dict, Optional, Tuple
def _running_stats_dtype():
# MPS doesn't support float64. On a CUDA-less Mac the only accelerator
# is MPS, so default the running-stat buffers to float32 there. JIT
#... |
b137c24f135fb335c8ce4d0575f6bd3e67d5320320cb5780f2ab4674d09cab95 | Python | 6,445 | 180 | import medmnist
import torchio as tio
from numpy import float32
from typing import Any
from torch.utils.data import DataLoader
from monai.data.dataloader import DataLoader as MDTL
from monai import transforms as mtf
from twoandahalfdimensions.utils.config import Config, LoaderType, TransformLibrary
from twoandahalfdim... |
ff99a2ed71b7fe1c784feea36677a9b5949691160fdcb90257762358aa64593c | Python | 6,445 | 189 | """
A verbatim copy (vendored) of the spec tests.
Taken from https://github.com/data-apis/dataframe-api
"""
import ctypes
import math
import pytest
from pandas.errors import Pandas4Warning
import pandas as pd
import pandas._testing as tm
@pytest.fixture
def df_from_dict():
def maker(dct, is_categorical=False)... |
e73903ebea079bcd5af7985a61ece02d087059ede92cd9360a19a7646c0c4a3c | Python | 6,446 | 167 | # Copyright 2026 Xanadu Quantum Technologies 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 agree... |
0fc268b4ea80b8ae92ce708b2a9f3685a7db3e5423b2a52235a3814872b61f40 | Python | 6,448 | 206 | import random
import time
from typing import Any, Mapping
import torch
from deepglyco.chem.common.elements import ElementCollection
from deepglyco.chem.gpep.glycans import MonosaccharideCollection
from deepglyco.chem.pep.aminoacids import AminoAcidCollection
from deepglyco.chem.pep.mods import ModificationCollection,... |
ac81b59d4ab706df9779524638915149d4d87776a0d9ab15f3fb4d8aff3d3175 | Python | 6,450 | 192 | #
# This file computes the atomic spherical coordinates in a given set of
# neighborhoods and outputs a file with these coordinates.
#
# It takes as arguments:
# - The name of the ouput file
# - Name of central residue dataset
# - Number of threads
# - The neighborhood radius
# - "easy" flag to include central res... |
0aee5fc6d7d780c3626fb15eea7c6d22e8f09d8ec93829b686fca4414f4de6d1 | Python | 6,451 | 95 | #! /usr/bin/env python
##############################################################################
## DendroPy Phylogenetic Computing Library.
##
## Copyright 2010-2015 Jeet Sukumaran and Mark T. Holder.
## All rights reserved.
##
## See "LICENSE.rst" for terms and conditions of usage.
##
## If you use this wo... |
f2b4c1adb26ec8edc087cdc0c415aa3fd84a74eaa4415edbacdcd81c820a1f9c | Python | 6,456 | 206 | import re
import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
class TestDatetimeIndex:
def test_get_loc_naive_dti_aware_str_deprecated(self):
# GH#46903
ts = pd.Timestamp("20130101")._value
dti = pd.DatetimeIndex([ts + 50 + i for i in range(100)])
se... |
3ae3f3544fa65fc69cd56b64920062efe88e50b283bba45674f02f8610d76f7d | Python | 6,459 | 192 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
def test_get_values_for_csv():
index = pd.PeriodIndex(["2017-01-01", "2017-01-02", "2017-01-03"], freq="D")
# First, with no arguments.
expected = np.array(["2017-01-01", "2017-01-02", "2017-01-03"], dtype=object)
res... |
06a19d37d6f7e33fdd642735ed7a14b9a6faf3090a675de59775e867a7ac85d2 | Python | 6,461 | 208 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
@pytest.fixture
def df():
"""
base dataframe for testing
"""
return pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]})
def test_case_when_caselist_is_not_a_list(df):
"""
Raise ValueError if caselist is not a list.... |
f2209b0c453ef8fa78836f39282189081fef780345509b42ce33d2a0e6a00daf | Python | 6,461 | 168 | import numpy as np
import task_train_test as tk
import nn_analyses as nna
###### Fixed-point finding #################
def run_FPF_search(p, F, earliest_only = False):
# 1. Set Parms #
add_rand_seeds = True #True # (optional) get random trials for seeds
rand_numbatch = 5 # " " no. o... |
60723efb92a7abdadfb70ffe30bbbd3193d4177e5fee9ba68418d869cf553e02 | Python | 6,463 | 189 | from __future__ import absolute_import
from .tuplecloudsqlitedict import SqliteDict
import os, time
from ..utils import DelayedKeyboardInterrupt
from threading import ThreadError
import warnings
###################################################
# additional locking
##################################################... |
941ccd7a05d957837b8d2de12b904472d8a39bb4cc7b4dd57b57bba33a44d98d | Python | 6,463 | 167 | import os
import numpy as np
import pandas as pd
from deepglyco.specio.mzml import MzmlReader
from deepglyco.speclib.gpep.hdf import GlycoPeptideSpectralLibraryHdf
from deepglyco.util.log import get_logger
from deepglyco.util.progress import TqdmProgressFactory
def stat_speclib(speclib_file, logger, progres_factory... |
9a328a826600322176a4daa9f0b581fa494d48972a6f59abdd3a9e006d1e4c4d | Python | 6,465 | 170 | """
Implementation of DataFrame.select.
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
)
import numpy as np
from pandas.core.dtypes.common import is_list_like
from pandas.core.dtypes.generic import (
ABCDataFrame,
ABCSeries,
)
from pandas.core import common as com
f... |
4fa630c6af19fdf1e6598f08d56cac5bde791c4ca099225f26df0d9309d7b921 | Python | 6,470 | 192 | # Copyright 2018-2023 Xanadu Quantum Technologies 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... |
7f16a4341e2fde969fc17a4bb069538b9a192071c1b5620d93cab77d5ac61c1d | Python | 6,474 | 181 | import torch.nn as nn
import torch
def derive(input_tensor, deriv_axis, ds=1, terrain=None, no_nans=True):
'''
Computing the derivative of a scalar field in the specified axis direction.
Parameters
----------
input_tensor : torch.Tensor
Input tensor [samples, Z, Y, X]
deriv_axis : int... |
626d5d881529d4d5384d2cd8154e1f00233bceaf656736b513d335403e4fb91f | Python | 6,475 | 171 | # Copyright 2018-2024 Xanadu Quantum Technologies 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... |
ee5e1189cf6005f162163492e7dcab7829e8bb6c5b5a67c2f1759b31a84c123a | Python | 6,475 | 178 | __all__ = ["PeptideData", "PeptideDataConverter", "PeptideDataBatch"]
from typing import List, NamedTuple, Optional, Union
import torch
import torch.nn.functional as F
from torch.nn.utils.rnn import pad_sequence
from ....chem.pep.mods import ModifiedSequence, ModifiedSequenceParser
from ....util.config import Config... |
9df176026c64f8790e5e8a648a1f76614932b3cacb650ab71609d114e226d575 | Python | 6,476 | 159 | """
.. _metas_estimators:
===================
The Estimator class
===================
An introduction to the Estimator class.
The Estimator class is the base for all meta-analyses in NiMARE.
A general rule of thumb for Estimators is that they ingest Datasets and output
MetaResult objects.
"""
######################... |
2852bca7adb14b7bfc72abdba0259e45274f0518622248093f809f4559f684aa | Python | 6,477 | 175 | import re
import argparse
import numpy
import random
import math
import statistics
import multiprocessing as mp
import gzip
import os
from collections import Counter
def get_args():
parser = argparse.ArgumentParser(description="Find copy number of a feature in WGS data with pre-counted kmer multiplicitie... |
2da51dcb6b38b6baa554f91bb863d6f9028e517daca04c5f65479251909b3a5c | Python | 6,478 | 168 | #%%
from compute_sup_jux_segment import compute_segment
from driver import compute
from values import *
from defs import *
import os
import argparse
import multiprocessing
import output
import re
import pdb
import matplotlib.pyplot as plt
#%%
solute = ['Na','K','Cl','HCO3','H2CO3','CO2','HPO4','H2PO4','urea','NH3','... |
174ad7ab96b1e477608722ea72101e792a853edf443281799441d46ff069936f | Python | 6,479 | 182 | # Calculate structure searching performance
# Unpack training_coords first with `tar -xvf training_coords.tgz`
import progres as pg
import torch
from torch.utils.data import Dataset
from torch_geometric.loader import DataLoader
import numpy as np
from collections import defaultdict
dataset_dir = "dataset"
coord_dir =... |
896c609e85a01352ee4d9231501cc397dd305d45363dcc43bfc9f75461d87e06 | Python | 6,480 | 176 | """Prediction boundaries retain sample/feature identity and bounded batches."""
from unittest.mock import Mock
import anndata
import numpy as np
import pandas as pd
import pytest
import torch
from scipy import sparse
import pyaging as pya
from pyaging.predict._pred_utils import check_features_in_adata, predict_ages_... |
df46ae89d24e883e1320c4d5b3b3a597753fefe3b03ee999bde6124feaf09c4c | Python | 6,480 | 154 | # -*- coding: utf-8 -*-
"""
classifiers
"""
from app.inout.inout import write_hist, write_map
from app.utils import end_execution
from pandas import read_csv
import numpy as np
import os
import logging
logger = logging.getLogger(__name__)
def call_model(data, p_model, p_scaling):
from sklearn.preprocessing impor... |
66ce2a91b9a508649e510b4613a215383d3cb94888bd807667d0a530c876798b | Python | 6,482 | 139 | # Copyright 2019 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... |
6f5d0e390c239f5833674af54ac6dc916dad388d862582ac11bb78e004f54266 | Python | 6,484 | 114 | import sys
sys.path.append('prepare_data')
import random
from create_cell_feat import *
from create_drug_feat import *
from create_drp_dict import *
from binarization_drp import *
from torch_geometric.data import Batch
from torch.utils.data import Dataset, DataLoader
GE_data = load_raw_GE()
drug_response_dict, drug_nam... |
75b8916226898ff2e3b5de0e98c7738bc56729df47c18c3101c5f19982cf607a | Python | 6,484 | 175 | """
Tests shared for DatetimeIndex/TimedeltaIndex/PeriodIndex
"""
from datetime import (
datetime,
timedelta,
)
import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
class EqualsTests:
def test_not_equals_numeric(self, index):
assert not index.equals(pd.Index(index.a... |
2c6079483658314249eaebfd02cc174f5bdd620107778a76d548d6182760fad8 | Python | 6,487 | 157 | #!/usr/bin/env python3
"""
The purpose of this script is to update the the 'scpca-meta.json' checkpoint files for cell typing of already processed libraries to contain reference file names with the following format:
<ref_name>_<source>_<version><ext>.
Specifically, we want to check that the version is present in the ... |
1781839a6b5e5ddc8e17dd1321088b68ba1e780205a5b3ded96463a01e2fac87 | Python | 6,490 | 227 | # coding: utf-8
# JN 2014-12-18
"""
This script plots extracted spikes
so one can decide if clustering
is worth it or not
"""
from __future__ import division, print_function, absolute_import
import logging
logger = logging.getLogger(__name__)
import os
import numpy as np
import tables
import matplotlib.pyplot as mp... |
ce3d0356ca32d175bbe3fe00babf24e905d78842167690ebec16e4adbf223830 | Python | 6,499 | 164 | import json
import numpy as np
import scipy.io as scio
import scipy.sparse
from scipy import sparse
# 该函数用于打标矩阵
# 先构造矩阵，行×列，其中行就是app应用程序的个数，列就是统计出的实体的个数
# 构造的矩阵应该是全0矩阵。
# 一个app一个app进行打标，读取一个app的实体信息后，若这个实体信息在总的矩阵里，就把第几个位置打标为1，
# 先把权限的做出来
# 提取信息，然后打标
def read_info(apkname,data2):
allindex = []
value... |
a4a70415cbf7fe4a5cf3c367b0d5cb56b428c4d3736523e2d1b2c86e00657358 | Python | 6,500 | 184 | """
Models for inducing predicate vectors and cued association transition model
Some code is adapted from the DGL implementation of RGCN link prediction:
https://github.com/dmlc/dgl/tree/master/examples/pytorch/rgcn
"""
import torch, dgl
import torch.nn as nn
import torch.nn.functional as F
import dgl.function as fn
... |
843ab0b5c559d47ab637bc083bd1545a0f084bc74e7040a07c24d7b8d64255fa | Python | 6,502 | 129 | import argparse
from base import loggingUtils
from base.surfaces import *
from base.kernelFunctions import *
from base.surfaceMultiPhase import *
def compute(args=None, noArgs=True):
if noArgs:
outputDir = '/Users/younes/Development/Results/multiShapes'
#outputDir = '/cis/home/younes/MorphingData/t... |
ecad2a23a72cad25e671b47e8ac09e3ace518911c8012003f6333d29c2786229 | Python | 6,502 | 202 | import requests
from PIL import Image
from neuronbridge.model import *
import logging
class Client:
def __init__(self, data_bucket="janelia-neuronbridge-data-prod", version="current"):
"""
Client constructor.
When the client is created, it retrieves the configuration for the speci... |
2ff5065f5cac3dc93065f8a3f36eb013e407972a80abcd4ee6b89a7138a0d5a6 | Python | 6,503 | 174 | import numpy as np
import tensorflow as tf
from tensorflow.contrib.training import HParams
def default_hparams():
return HParams(
n_vocab=0,
n_ctx=1024,
n_embd=768,
n_head=12,
n_layer=12,
)
def shape_list(x):
"""Deal with dynamic shape in tensorflow cleanly."""
... |
9f9f10bb08215f8d81b6119fe2aa1c079ee9a7e7b5391e48972c76fb834601ab | Python | 6,505 | 167 | # Copyright 2018-2021 Xanadu Quantum Technologies 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... |
d2dc6733d51893277db6f7e25efccf37084742f5eccba0e63bb6c835fd1f027a | Python | 6,505 | 209 | ## Works the best so far! Curve fits nicely and ymin/ymax don't have to be 0 and 1!
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from scipy.optimize import curve_fit
import sys
import matplotlib.ticker as ticker
import matplotlib.transforms as transforms
from pathlib import Path
from statisti... |
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