sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
3817f8e566723de2868a2c207fb9e1205eae36606904c8c21822c08979a0a1fe | Python | 2,221 | 58 | from os import path
from setuptools import find_packages, setup
_dir = path.dirname(__file__)
with open(path.join(_dir, "stardist_napari", "_version.py"), encoding="utf-8") as f:
exec(f.read())
with open(path.join(_dir, "README.md"), encoding="utf-8") as f:
long_description = f.read()
setup(
name="sta... |
702338a6dbec3874424672797e3dc8cd74c1db6cc2d0b6c7a2a7e65a85e6eaab | Python | 2,221 | 60 | # LICENSE
#
# _This file is Copyright 2018 by the Image Processing and Analysis Group (BioImage Suite Team). Dept. of Radiology & Biomedical Imaging, Yale School of Medicine._
#
# BioImage Suite Web is licensed under the Apache License, Version 2.0 (the "License");
#
# - you may not use this software except in compl... |
28e72a2632e168715b5918ec6884ed9dc32a0693b77c76ed31d54118fb692818 | Python | 2,222 | 65 | import os
from tqdm import tqdm
import json
import logging
from os.path import join
from dict_hash import sha256
"""Handles utilities for saving/caching.
This file probably does not need to be edited.
"""
def save_json(args={}, save_dir='results', fname='params.json', r={}):
os.makedirs(save_dir, exist_ok=True)
... |
591f46352691b54b89ea07e0ba20472be6fad6c95bb75225f44af811eb7224ec | Python | 2,222 | 77 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Marker(_BaseTraceHierarchyType):
_parent_path_str = "choroplethmap.selected"
... |
10fa1d2411d889c5ee9e67b5fe0540487a94d583d396ddb8ae01f924a4560697 | Python | 2,223 | 91 | import pandas as pd
from anndata import AnnData
def stack_3d_plot(
adata: AnnData,
slides,
height,
width,
cmap="viridis",
slide_col="sample_id",
use_label=None,
gene_symbol=None,
) -> None:
"""\
Clustering plot for spatial transcriptomics data. Also, it has a function to
di... |
a8ecdc0992daf08ed3f27cfb9ea62b049189bde03cf6de9aecbeaa4523420ae0 | Python | 2,223 | 77 | """
Launchers of the diverse available simulation modes
"""
from __future__ import annotations
from typing import Any
__displayname__ = "Simulation"
__all__: list[str] = [
"ABModel",
"BaseRun",
"ReplayRun",
"ExpRun",
"Exec",
"BatchRun",
"OptimizationOps",
"GAlauncher",
"EvalRun",... |
2e0bf66690107422718d692b08763aeb2c7b91ad4fb8be46f4a5f6de3c536245 | Python | 2,224 | 88 | # %% [markdown]
# # Write labels
# (basic:labels)=
#
# Storing labels data alongside image data is a key application and feature of the ome-zarr file standard.
# First, let's create some image data:
# %%
import numpy as np
from skimage.data import binary_blobs
from ome_zarr import OMEZarrImage, OMEZarrLabels, OMEZarr... |
5dbcefd55eaadaf0f16cd60fdf9218d6cd074f3c998831676f227bda39be8d89 | Python | 2,226 | 67 | """Python Buffer Protocol for R arrays."""
import typing
from rpy2.rinterface_lib import openrlib
def getrank(cdata) -> int:
"""Get the rank (number of dimensions) of an R array.
The R NULL will return a rank of 1.
:param cdata: C data from cffi
:return: The rank"""
dim_cdata = openrlib.rlib.Rf_g... |
7feeb42c06bdf8422643f463514a949b1b29dc908c5c0e3df2425e55755206c3 | Python | 2,226 | 87 | import numpy as np
import torch
def all_seqs(n, *, amount=4):
"""
Generates all sequences of length n, with the given amount of nucleotides.
"""
if n == 0:
yield []
return
for s in all_seqs(n - 1, amount=amount):
for i in np.eye(amount):
yield [i] + s
def pack... |
2ee38b8ae985fbd286069754c46c1e14a830ca35401578e6ceeacdd272a85362 | Python | 2,227 | 62 | """
This module define loss logger
"""
import numpy as np
import logging
class LossLogger:
"""
This class keep track of the loss during the training process
We have two function in order to add train loss, the first one is add_train_loss_tmp() that is executed at each epoch and
calc_mean_train_loss() ... |
3d09c17983ab1254916cb93b9410d10d523a01c25b412503694a3b9811d8893a | Python | 2,227 | 55 | import sys
from tqdm import tqdm
# Define file names from command line arguments
gtf_file = sys.argv[1] # GTF file
hits_file = sys.argv[2] # Hits file
annotation_table_file = sys.argv[3] # Transcriptome annotation table file
output_file = sys.argv[4] # Output GTF file with annotations
# Function to append blastx ... |
37a9ba7e1cc92b02ee527a924575f5962e820b773fd6f322cea53a0edb75c380 | Python | 2,228 | 80 | '''
Load K-folding models from groups and evaluate performance
author : obanmarcos
'''
import os, sys
from config import *
sys.path.append(where_am_i())
import lightning as pl
import argparse
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from utilities import dataloading_utilities as dlutil... |
8f70b1de776f8268c0fb3751a16e2504f74df59ca9ef11890d575f897c8ce5b9 | Python | 2,229 | 69 |
from typing import Dict
import torch
@torch.jit.script
def sample_hiddens(
chains : Dict[str, torch.Tensor],
params : Dict[str, torch.Tensor],
beta : float=1.
) -> Dict[str, torch.Tensor]:
"""Samples the hidden layer conditioned on the state of the visible layer.
Args:
chains (Dict[s... |
c37ee95c8513402f4b6315113c0287266b4a7fbe0dc5ff04320bb51a9b00feb0 | Python | 2,229 | 55 | from typing import List, Optional, Tuple
import numpy as np
from anndata import AnnData
from ...logging import logger_manager as lm
def get_X_Y_grid(
adata: Optional[AnnData] = None,
genes: Optional[List] = None,
X: Optional[np.ndarray] = None,
Y: Optional[np.ndarray] = None,
grid_num: List = [5... |
cbd708367c44ff8a8d12daceb7ad4e18fa88f79d706304a58cc665f3faf34423 | Python | 2,229 | 66 | """Helper functions for dealing with logging
By default, mne's logger has a highly verbose stream handler logging to the
screen. Here this screen handler is set to a higher level (WARNING), but only
if Eelbrain is the primary import (i.e., it is imported before mne) and if the
user has not stored another configuration... |
85cd94d3b25f22c4c55303aca094111a81eadb01a684256cd3e1d3e6132c5901 | Python | 2,230 | 72 | """Save, load, and execute a sparse runnable ``.tlspec`` artifact."""
from __future__ import annotations
import tempfile
from pathlib import Path
import torch
from torch import nn
import torchlens as tl
from torchlens.options import CaptureOptions
class TinyClassifier(nn.Module):
"""Small deterministic model ... |
ecb5542c89620318b72a4fd067cae17751d3cdb742bb1b6d37a558bc3a4030e7 | Python | 2,231 | 55 | #!/usr/bin/env python
#
# Copyright 2019 Google LLC. All Rights Reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list o... |
34afbdff16c58c5502a5ea9d6537178842a61bcc5267b0fc02fd5fa9aca6ba87 | Python | 2,232 | 70 | from keras.src import backend
from keras.src.api_export import keras_export
from keras.src.layers.merging.base_merge import Merge
@keras_export("keras.layers.Average")
class Average(Merge):
"""Averages a list of inputs element-wise..
It takes as input a list of tensors, all of the same shape,
and returns... |
ca5ceb6fb5149b03b33559d4e79a3e9e90d7f008e69c8d7f661d4441d7aa4184 | Python | 2,232 | 55 | '''Power ROI functions'''
import numpy as np
ours2orig = [12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27,
28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 254, 41, 42, 43, 44, 45,
46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64,
65, 66, 67, 68, 69, 70, 71, 72, 73, 74, ... |
9da3b7875ccecd5e745c287c77e6033eda1b0ccc20fec657ab2e9c621eed3477 | Python | 2,233 | 54 | import torch
import torch.nn as nn
import numpy as np
import torch.distributed as dist
def Optimize(Epoch,print_epoch,ema_nbatch,weight_scheduler,scheduler,print_info,data_train,data_val,get_loss,swa_model,optim):
rank=dist.get_rank()
lr=optim.param_groups[0]["lr"]
intime_weight=weight_scheduler(lr)
... |
7da384d1e7b3fcddee99cac522927ffa599dd7a81ca36ccc507cc350803119f8 | Python | 2,234 | 93 | from dataclasses import dataclass
from enum import Enum
from fastapi import HTTPException
class EmptyResultException(Exception):
"""
The request return an empty result.
"""
class AuthenticationError(HTTPException):
"""
Raised when a session cookie or bearer token cannot be verified
(bad/abs... |
c90887e68aaa07653386becaca41162bd9437754bc74446f10680bf1359e8ee4 | Python | 2,234 | 61 | from copy import deepcopy
import numpy as np
from sklearn.metrics import accuracy_score
from sklearn.utils import resample
from tqdm import tqdm
class BaggingEstimatorText:
def __init__(self, estimator, n_estimators=10, max_samples=1.0,
bootstrap=True, random_state=None):
"""Use this class because skl... |
ce7a0195e87917c85fc7c04dd3eca6e6ebb5f3b9290049c26a55b4679d4f89d9 | Python | 2,234 | 82 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Fit peptides for degradation constant and half-life.
Project: SILAM
Step #2
Goals: (1) Filter for peptides with R^2 passed the threshold;
(2) Scale the value for each peptide from 0 to 1 based on the max value.
Input data: (1) Peptide mass spec readout, normalized... |
36c9af185868c693aaecc95b41d5ab5626a8904bee509bbf959cfa90adb6ccea | Python | 2,235 | 76 | #
# MarkovModels setuptools script
#
import os
from setuptools import find_packages, setup
# Load text for description
with open('README.md') as f:
readme = f.read()
# Load version number
#with open(os.path.join('MarkovModels', 'version.txt'), 'r') as f:
# version = f.read()
version = "0"
# Go!
setup(
... |
9aae1ea8fdf29dc3b7fb11a07478a0be90f20b27783f84054447995cc3b903f5 | Python | 2,236 | 61 | """Regression tests for r18bauto.
Item 2 (landed): ``tl.record`` must enforce the same unsupported-tensor-variant guard that
``tl.trace`` enforces (meta / sparse / symbolic-shape inputs). Before this fix ``record`` skipped
the guard and crashed deep in the capture pipeline with an opaque torch error instead of raising... |
35eb40bd8352fad47ea61e3e66e523a969e6e6538f6df6c9f3f7c7ae5f5e48ea | Python | 2,237 | 61 | """
Create PCA images.
"""
import argparse
import os.path
import pathlib
import numpy
import numpy.random
from sklearn import decomposition
import skimage.io
def parseargs():
"""
Parses arguments.
"""
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('-i',
... |
ab0c7ee31da81cfffda09aea239ac6c4b184fb28e09eb0b89446b04ca0673f0f | Python | 2,237 | 83 | """Tests for specparam.plts.templates."""
import numpy as np
from specparam.modutils.dependencies import safe_import
from specparam.tests.tutils import plot_test
from specparam.plts.templates import *
mpl = safe_import('matplotlib')
#################################################################################... |
c70a158dca63ed22421b96c890eae55f4afb86ad1bf3ca3ffe99e86a68a0a973 | Python | 2,237 | 54 | """R23-3: ParamRef construction pairs each RAW parent-param with ITS barcode.
``_param_barcodes`` is the DEDUPED key list of ``parent_param_ops`` (a dict)
while ``parent_params`` is the raw occurrence list, so the old
``zip(barcodes, params)`` misaligned every pairing after a repeated param
(weight-tied einsum / hyper... |
cf9985674153fb8965765563328e58b0df5641418b7f1a82d250218de82e9c7b | Python | 2,237 | 65 | # LICENSE
#
# _This file is Copyright 2018 by the Image Processing and Analysis Group (BioImage Suite Team). Dept. of Radiology & Biomedical Imaging, Yale School of Medicine._
#
# BioImage Suite Web is licensed under the Apache License, Version 2.0 (the "License");
#
# - you may not use this software except in compl... |
4915ad227f882c333b185e4db73dd9cd899335788c6918574b1f8832dbfc1f89 | Python | 2,238 | 72 | # coding=utf-8
# Copyright 2024 The Google Research Authors.
#
# 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 applicab... |
1a91256e56db3456d95829e190c9194babb2c4c0f48aa11930e16189484ead2e | Python | 2,239 | 78 | """Prepare Cityscapes dataset.
========================
`Cityscapes <http://sceneparsing.csail.mit.edu/>`_ focuses on semantic understanding of
urban street scenes. This tutorial help you to download Cityscapes and set it up for later experiments.
.. image:: https://www.cityscapes-dataset.com/wordpress/wp-content/up... |
c338943926cb792a566a20a488f5db0a0a9fd880f306840e1e3852ed90520245 | Python | 2,239 | 85 | #!/usr/bin/python
# USAGE: ./manhattan_filt.py <filedir>
import sys
import os
#import json
import pandas as pd
import numpy as np
import math
import re
filedir = sys.argv[1]
if re.match(".+\/$", filedir) is None:
filedir += '/'
GWAS = pd.read_csv(filedir+"input.snps", delim_whitespace=True, usecols=["chr", "bp", "p... |
f6ded044e31e3f8de5f394a186511757aec174a8c6af31f7d1487d7edcf52c0d | Python | 2,239 | 80 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Diagonal(_BaseTraceHierarchyType):
_parent_path_str = "splom"
_path_str =... |
51f2de71b48598a0f46f019ca65be0788cea828003a8b4c71be77af614b3721e | Python | 2,240 | 78 | from pathlib import Path
from typing import Annotated
import typer
def main(
n_seqs: int,
seq_length: int,
output: Path,
max_memory: Annotated[int, typer.Argument(help="Max memory in mebibytes.")],
):
import logging
import sys
from time import perf_counter
import numcodecs as ncds
... |
fb2785d33ef8aca1de8551650c52ce95d44d9411d6cc21cd5ad0dbdd26e5e15c | Python | 2,240 | 82 | '''
compile_test.py - check pyximport functionality with pysam
==========================================================
test script for checking if compilation against
pysam and tabix works.
'''
# clean up previous compilation
import os
import platform
import pytest
import pysam
from TestUtils import make_data_file... |
04ebd9f4bf97ee4c949d0827f8486c330ef00c96bd81f14e535c2878ab8e335b | Python | 2,241 | 62 | # content of conftest.py
import pytest
import torch.multiprocessing as mp
# Distributed (DDP) test pool, see #1982. The flag and gloo setup live in
# tests/ddp_helpers.py so they can be typed and shared with the test modules;
# the session hooks below only start/stop the pool.
from tests.ddp_helpers import NUM_PROCES... |
29f0c7d65e54f988aa957635a3a15e20c6c912c80df0d54ffe22830a93156c89 | Python | 2,241 | 69 | # Deprecated
# Now we use sa2.merge.rmdlt.py to get a complete bmat snap file.
# then do subset on it directly.
import os
import sys
import traceback
from pathlib import Path
import logging
from typing import Dict, List
import shutil
from numba.core.errors import NumbaDeprecationWarning
from numba.core.errors import... |
92aeab5a52f8288fc64c8dab84bf969160c966bc31410d49f62da43bc092b7f3 | Python | 2,241 | 83 |
from flask_login import current_user
from mongoengine import *
import imantics as im
class CategoryModel(DynamicDocument):
COCO_PROPERTIES = ["id", "name", "supercategory", "color", "metadata",\
"keypoint_edges", "keypoint_labels", "keypoint_colors"]
id = SequenceField(primary_key=T... |
d07038c616f5cef2773b18262d16ae55dc04f02134286e0c4b4941b253fd3fb2 | Python | 2,241 | 67 | import sys
from robustness import datasets
from robustness.attacker import AttackerModel
from robustness.model_utils import make_and_restore_model
from model_analysis_folders.all_model_info import IMAGENET_PATH, MODEL_BASE_PATH
import os
def build_net(ds_kwargs={}, return_metamer_layers=False):
# We need to build... |
0fed94350966e46e36a1f89b98c1f73228316ffa463db378e81444422d211a5a | Python | 2,242 | 50 | """The CPU Float8 allocation guard, importable from an unambiguous dotted path.
``tests/conftest.py`` and ``tests/backends/conftest.py`` are two DIFFERENT
files that both resolve to the bare top-level module name ``conftest`` under
pytest's default ``prepend`` import mode (neither ``tests/`` nor
``tests/backends/`` is... |
a8a4ddf453038d04f3ce157d168f3020ff0ab96e5b2ce3928166a1dd83645082 | Python | 2,242 | 62 | """
Backs up and restores a settings file to Dropbox.
This is an example app for API v2.
"""
import sys
import os
import dropbox
from dropbox.files import WriteMode
from dropbox.exceptions import ApiError, AuthError
# Add OAuth2 access token here.
# You can generate one for yourself in the App Console.
# See <https:/... |
c43d89eb95a77290e4fae3accc1b67c454ceed32cdbbbe1fa3cad4950592fec4 | Python | 2,242 | 79 | """
Collection of standalone methods, custom classes and other tools, all of them
independent of the larvaworld registry.
This file used to eagerly star-import many submodules, which made importing
`larvaworld` heavier and obscured the public surface. We now lazily import the
same symbols on first access to preserve b... |
641dc5d543d4e9220c6621728beb4ab917e53856a516457af8b819fffee8693e | Python | 2,243 | 76 | import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule
from mmcv.runner import BaseModule
from ..builder import NECKS
@NECKS.register_module()
class FPN(BaseModule):
def __init__(self,
in_channels,
out_channels,
conv_cfg=None,
... |
e561debf4f9de674ce83a004cc86720a659289e4cedd834b34eda407a4536161 | Python | 2,243 | 62 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""tests for pagerank.py"""
import unittest
import numpy as np
from sknetwork.data.models import cyclic_digraph
from sknetwork.data.test_graphs import test_graph, test_digraph, test_bigraph
from sknetwork.ranking.pagerank import PageRank
class TestPageRank(unittest.Te... |
337a283cd580e0ad59e7deec83aecd3e618373c7f0072670ad6ee103991b64d4 | Python | 2,244 | 72 | # -*- coding: utf-8 -*-
# @Author: gviejo
# @Date: 2022-11-30 09:29:21
# @Last Modified by: gviejo
# @Last Modified time: 2024-02-26 13:14:41
"""Tests of time units for `pynapple` package."""
# from pynapple.core.time_units import format_timestamps, return_timestamps, sort_timestamps
# from pynapple.core.time_inde... |
4c92b1da02ee18b16b4487281f53ba78f531d6a3f86be519164f3cd8267086a6 | Python | 2,245 | 64 | import os
import h5py
import numpy as np
import scanpy as sc
from ica import ica1
from scbig.utils import read_data, setup_seed, louvain, calculate_metric
def preprocess(adata, scale=True):
sc.pp.filter_genes(adata, min_cells=3)
sc.pp.filter_cells(adata, min_genes=200)
sc.pp.normalize_total(adata, targe... |
c52bf3fc86f13677a2f08ac4cac20e8bc6295ff6ba79dc55138d60fe54b1d669 | Python | 2,245 | 63 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Tests for format.py"""
import unittest
from sknetwork.data.test_graphs import *
from sknetwork.utils.format import *
class TestFormats(unittest.TestCase):
def setUp(self):
"""Basic biadjacency for tests."""
self.biadjacency = test_bigraph()
... |
2643a1933a10e6daa40a7d84adb6c29db1e54740f6d0d7a7ab42fd622064e9af | Python | 2,246 | 70 | # -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: bream/experiment_estimated_end.proto
"""Generated protocol buffer code."""
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflect... |
2b5e19bd2507ae0e0df704b94826ede34b39f7c585678f615b9b5cd5edf593e1 | Python | 2,246 | 67 | #!/usr/bin/env python
# coding: utf-8
# In[1]:
import tensorflow as tf
import tensorflow.keras as keras
from tensorflow.keras.layers import Reshape, Input, Flatten, concatenate, Dense, BatchNormalization ,Conv1D,Conv2D,Conv3D,MaxPool1D, MaxPool2D,MaxPool3D, GlobalMaxPool2D, Dropout
from tensorflow.keras.optimizers i... |
82ff045b06126152a650981ded61536bce73f6ada6e6f280d7ef1361209cdf6b | Python | 2,246 | 60 | from typing import Tuple
import torch
from torch import Tensor
from torch.distributions import Uniform
from torch.distributions.bernoulli import Bernoulli
class PhaseShiftTransform:
"""Implementation of phase shifting transformation.
Applies a random phase shift `theta` (positive or negative) t... |
9df4b2524885c55ce90efb09c504b532cdc2e5f0918bb013c5897566c340f9b9 | Python | 2,247 | 73 | # %%
'''
Downsamples fmriprep cifti data into parcellation
Assumes you have access to connectome workbench command line
'''
import numpy as np
import subprocess
import sys
sys.path.append("..")
from functions.data_helpers import get_computer
# paths
computer, _ = get_computer()
if computer == 'lucky2':
prefix = '... |
b5f88a356ab4735c310b06ceddf950313216516b4f8586e4b64f76cd6bfd9a2f | Python | 2,247 | 81 | '''
Load K-folding models from groups and evaluate performance
author : obanmarcos
'''
import os, sys
from config import *
sys.path.append(where_am_i())
import pytorch_lightning as pl
import argparse
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from utilities import dataloading_utilities a... |
6397727f16d72f01454705d1ead4493b0861526250c2949e3a43c8cf1b9e53f4 | Python | 2,248 | 63 | from __future__ import annotations
import panel as pn
import pytest
from larvaworld.lib.reg.generators import ExpConf
from larvaworld.portal.config_widgets import build_sim_ops_widget
from larvaworld.portal.simulation.parameter_resolution import (
resolve_base_experiment_parameters,
)
def _find_widget_any(
... |
2f96e971151725a64796ba619e5bdd988879c22988ae0c31a84504ff3242fcde | Python | 2,249 | 55 | import numpy as np
from scipy.interpolate import PchipInterpolator, Akima1DInterpolator
from numba import jit
from typing import Tuple
# @jit(nopython=True)
# Define a function to generate a 2D Gaussian kernel using the shape and sigma as inputs
def matlab_style_gauss2D(
shape: Tuple[int, int], sigma: float = 1.0... |
be337feb715bf83579badfba8a0d8e5b4e4317c17a5afca5bfefcaf5fec83b83 | Python | 2,250 | 56 | electronic_states = {
"H": "1s1",
"He": "1s2",
"Li": "1s2 2s1",
"Be": "1s2 2s2",
"B": "1s2 2s2 2p1",
"C": "1s2 2s2 2p2",
"N": "1s2 2s2 2p3",
"O": "1s2 2s2 2p4",
"F": "1s2 2s2 2p5",
"Ne": "1s2 2s2 2p6",
"Na": "1s2 2s2 2p6 3s1",
"Mg": "1s2 2s2 2p6 3s2",
"Al": "1s2 2s2 2... |
090033855c7d5623eda8b354bc07aa9ca8f98967c511ca8cc794656568c9df47 | Python | 2,251 | 79 | """
Package containing all pip commands
"""
from __future__ import absolute_import
from pip._internal.commands.completion import CompletionCommand
from pip._internal.commands.configuration import ConfigurationCommand
from pip._internal.commands.download import DownloadCommand
from pip._internal.commands.freeze import ... |
878ffd47b52f9e67d82157ba8e22abc4de5fc53414d600df432982862fddd572 | Python | 2,251 | 62 | #!/usr/bin/env python
# =============================================================================
# MODULE DOCSTRING
# =============================================================================
"""
A script to convert AMBER's NetCDF trajectories to dcd format that CHARMM can read.
The script assumes that the ... |
daccbd241a3cee7f70f10685064934eb6f272d95a75f3ced5780d4b6d5000eb4 | Python | 2,252 | 96 | import pathlib
import numpy as np
from impose.structure import (
StructureComposite, StructureCompositeStack, StructureLayer)
from impose.geometry import shapes
data_path = pathlib.Path(__file__).parent / "data"
def make_sc(seed=42):
np.random.seed(seed)
sl1 = StructureLayer(
label="test layer"... |
45148097c83fbded3288b0ccc3333dd3bca51bb74c4000df2fb33fa090863842 | Python | 2,253 | 70 | import pytest
import tensorflow as tf
from psychrnn.backend.rnn import RNN
from pytest_mock import mocker
import sys
if sys.version_info[0] == 2:
from mock import patch
else:
from unittest.mock import patch
# clears tf graph after each test.
@pytest.fixture()
def tf_graph():
yield
tf.compat.v1.reset... |
7be0a3c404456f0484ab517a448b657de53a2d6c77f07d5219e8e0017497d0c6 | Python | 2,253 | 72 | import numpy as np
import torch
import tqdm.auto as tqdm
from permacache import permacache, stable_hash, drop_if_equal
from modular_splicing.evaluation.predict_splicing import predict_splicepoints_cached
from modular_splicing.models_for_testing.load_model_for_testing import (
achieved_target_acc,
)
from modular_s... |
ef1397afea52bae3aee77ce8739e346cf6ad25c8d4b981a57313a815b7ef6195 | Python | 2,253 | 44 | import tensorflow as tf
from tensorflow.keras.layers import MultiHeadAttention, LayerNormalization, Dropout, Layer
from tensorflow.keras.layers import Dense, Embedding
from tensorflow.keras.models import Sequential
class TransformerBlock(Layer):
def __init__(self, embed_dim, num_heads, ff_dim, rate=0.1):
... |
00883a5f4b7b1d00f00c800818ff392d7a9637cc12b6450035c934d4a0af2b0a | Python | 2,254 | 57 | import torch
from torchvision import datasets, transforms
import numpy as np
def rand_match_on_idx(l1, idx1, l2, idx2, max_d, dm):
"""
l*: sorted labels
idx*: indices of sorted labels in original list
"""
_idx1, _idx2 = [], []
for l in np.unique(l1): # assuming both have same idxs
l_i... |
0692cc03d90a98a927e9ab4880367c34a77d01e57b3a2d345463e0e6de4d8ca7 | Python | 2,254 | 66 | import numpy as np
from mudcod.community_detection import MuDCoD, StaticSpectralCoD
from mudcod.network_simulations import MuSDynamicDCBM
from sklearn.metrics.cluster import adjusted_rand_score
T = 4
S = 8
# Multi-subject Dynamic DCBM
model_dcbm = MuSDynamicDCBM(
n=200, # Total number of vertices
model_order... |
b933a8c05796d832a3df5cdb3488ab30d76c27f69b640b2998c5188668a9beb2 | Python | 2,254 | 55 | # LICENSE
#
# _This file is Copyright 2018 by the Image Processing and Analysis Group (BioImage Suite Team). Dept. of Radiology & Biomedical Imaging, Yale School of Medicine._
#
# BioImage Suite Web is licensed under the Apache License, Version 2.0 (the "License");
#
# - you may not use this software except in compl... |
c9c1d768aaf36d9bf972b615c47f70b7e15f1fc566eb53ffa18d95555b644f00 | Python | 2,254 | 51 | from PCA.src.denoise import *
from PCA.src.utils import *
from Transform.src.noise import Noiser
from test_support_function.src.CEST import generate_Z_3D
# Function to generate synthetic CEST data with specified image shape, dynamic range, and noise level
def gen_data(img_shape: tuple, dyn: int, sigma: float):
# ... |
e78e469ebab9f6edec3f26a4e42138f60e83d1627a247cd0b522cbb7b2905e85 | Python | 2,254 | 70 | #############################################################
# Plot Figure 3F of the manuscript
#############################################################
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
coordFilename = '../SlideSeq2/spa.csv'
expFilename = '../SlideSeq2/count.csv'
coord=pd.... |
ec8b095045708e21257811094e8405aaec129569f8dfebe56499e627c775d8cd | Python | 2,254 | 70 | #############################################################
# Plot Figure 3G of the manuscript
#############################################################
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
coordFilename = '../SlideSeq2/spa.csv'
expFilename = '../SlideSeq2/count.csv'
coord=pd.... |
742d6c7d1b9aab31f0d3e41319d9a1c5aa929f5bd7ee97f294812e7f5717b072 | Python | 2,255 | 54 | import sys
# setting path
sys.path.append('../TM2_segmentation')
import os
import numpy as np
import nibabel as nib
import itk
import pandas as pd
import tarfile
from scripts.preprocess_utils import find_file_in_path, register_to_template
# load metadata file
input_annotation_file = 'data/csv_files/healthy_adults... |
ef3e04b35e3f55760b13aa5149b1c2334b7b7cb87c41ee183cd02275a3da778b | Python | 2,255 | 76 | import numpy as np
from bct import distance_wei_floyd, retrieve_shortest_path
from tqdm import tqdm
import itertools
def path_transitivity(W, transform = None):
"""
Computes the path transitivity, or density of one-step detours (triangles)
available along the shortest path between all pairs of nodes.
... |
0504898f40dc8a2b2d2d30cd15ac79a6b68f1f2cce9165b6dc276ba7935ca9e4 | Python | 2,256 | 74 | """Subprocess entry point for isolated capture-oracle characterization."""
from __future__ import annotations
import argparse
import json
import os
from collections.abc import Sequence
# Pin the CPU kernel paths BEFORE torch loads (ATen reads its capability and
# MKL its reproducibility branch at first use). The gol... |
2026073a2fc2e386a288914e4e2a27900b00115da880d96a72334dc46f5f11ed | Python | 2,256 | 62 | from enum import Enum
from pydantic import Field
from galaxy.managers.context import ProvidesUserContext
from galaxy.model.tags import GalaxyTagHandlerSession
from galaxy.schema.fields import DecodedDatabaseIdField
from galaxy.schema.schema import (
Model,
TagCollection,
)
class TaggableItemClass(Enum):
... |
a815bfb46f935f7d1740282677820052e597e6bc508215aa6db75cd4fcf2900a | Python | 2,256 | 67 | from __future__ import annotations
from typing import Optional
import numpy as np
import torch
from scipy.stats import spearmanr
def pearson_r(y_true: torch.Tensor, y_pred: torch.Tensor, dim: int = 0, eps: float = 1e-12) -> torch.Tensor:
x = y_true
y = y_pred
xm = x - torch.nanmean(x, dim=dim, keepdim=T... |
1e4a784479e6011937db70099eeea219eb0a7d13d2f770e5b45cad0764212254 | Python | 2,257 | 73 | from typing import Optional
from anndata import AnnData
import numpy as np
from scipy.sparse import csr_matrix
import pandas as pd
from ._weighting_matrix import (
calculate_weight_matrix,
impute_neighbour,
_WEIGHTING_MATRIX,
_PLATFORM,
)
def SME_normalize(
adata: AnnData,
use_data: str = "raw... |
592f72b4ee143ba346860d3e0f0f50ea836b774f6a6ee1d979db3a0760e7ed48 | Python | 2,257 | 71 | from sklearn.base import ClassifierMixin, ClusterMixin, TransformerMixin
class SpdTransfMixin(TransformerMixin):
"""TransformerMixin for SPD matrices"""
def fit_transform(self, X, y=None, sample_weight=None):
"""Fit and transform in a single function.
Parameters
----------
X ... |
675c57c302253ae8c67204be2b7bd930539c20960f949f6b444dca6f3a874817 | Python | 2,257 | 89 | # a/b will always return float
import numpy as np
from .constants import *
_maxshape=100e6
def memsafe_arr(shape, dtype=_dtype_):
import tempfile as tmpf
shape = tuple(shape)
N = np.prod(shape)
if N < _maxshape_:
return np.zeros(shape, dtype=dtype)
else:
print("Using memory-mapp... |
7e1ba4a242257ce907c6247a11be16050ed75bfd2919c613ccfbafd69347b6ee | Python | 2,257 | 70 | import numpy as np
from pylsl import StreamInlet, resolve_stream, local_clock
import pyqtgraph as pg
from pyqtgraph.Qt import QtCore, QtGui
import ipdb
plot_duration = 2.0
# first resolve an EEG stream on the lab network
print("looking for an EEG stream...")
streams = resolve_stream('type', 'EEG')
ipdb.set_trace()
... |
85dfdded5c5514f4d827148993fbc5acd5c279247adbf48c936f87e84753cbb8 | Python | 2,257 | 65 | import pandas as pd
import tqdm
from tqdm import tqdm
from src.grid_search import *
from sklearn.linear_model import LogisticRegression
from statistics import mean, stdev
import pickle
def assign_target(input_df):
input_df = pd.read_csv(input_df, index_col=0)
input_df['animal'] = input_df.index.str[-1]
in... |
fe634fad75727af5b6a48b4ef63a13c855052cf0e9b6a6d85f5c0fdfebd229a7 | Python | 2,257 | 63 | from galaxy.files.sources.gitlab import (
GitLabFileSourceConfiguration,
GitLabFileSourceTemplateConfiguration,
GitLabFilesSource,
)
try:
from arcfs.fs import GitLabARCFileSystem
except ImportError:
GitLabARCFileSystem = None # type: ignore[assignment, misc, unused-ignore]
class ARCFileSourceTem... |
4fa999bc32e1ffe92fc5af6fec991c6e2bf98e6f8f805f98711495afa25d0799 | Python | 2,258 | 76 | #!/usr/bin/env python
import argparse
import sys
import readfile
txt_output = ["cids", "aids", "sids", "synonyms"]
csv_output = ["assaysummary", "property"]
check_for_id_type = ["cids", "aids", "sids"]
def main(args):
url = "http://pubchem.ncbi.nlm.nih.gov/rest/pug/" + args.type + "/"
if args.type == "assa... |
7b8ce356412ceac1a0e81c760d37bd628eb4aff5b1bcae017b06ed172f2e74b0 | Python | 2,259 | 76 | """``run(inputs=)`` on a fork carrying value-edits discloses their inertness.
D1 (2026-08-19): ``fork.do(sel, edit)`` then ``fork.run(inputs=new_x)`` is
COHERENT -- a do() edit rewrites saved values (path 1), while a new-input run
is a fresh execution (path 2) -- but the un-edited VERIFIED result tripped a
real user f... |
835f819f709d8ad5a4358b1a263c42404278d7c4b210ee9c1b77bb488d879fb5 | Python | 2,259 | 59 | """
Copyright (c) 2022 EPFL-BBP, All rights reserved.
THIS SOFTWARE IS PROVIDED BY THE BLUE BRAIN PROJECT ``AS IS''
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE BLUE BRAIN PROJE... |
a0bd9e069e22ba0d95cc80259092df679712739c4b47c106ef82fb2207702f9c | Python | 2,259 | 104 | import numpy as np
from neuron import gui, h
from neuron.units import ms
def simulate():
nseg = 100
s0 = h.Section()
s0.nseg = nseg
s0.L = 300000
s0.insert("hodhux")
ic = h.IClamp(s0(0.001))
ic.delay = 0
ic.dur = 1e9
ic.amp = 1000
s1 = h.Section()
s1.nseg = nseg
s1.L... |
c5617c6895ec64b5ee5d60b4241ab13c5b20f9972f13d93f4b39af131ad2701b | Python | 2,259 | 66 | from pl_bolts.utils import _PIL_AVAILABLE, _TORCHVISION_AVAILABLE, _TORCHVISION_LESS_THAN_0_9_1
from pl_bolts.utils.warnings import warn_missing_pkg
if _TORCHVISION_AVAILABLE:
from torchvision.datasets import MNIST
else: # pragma: no cover
warn_missing_pkg("torchvision")
MNIST = object
if _PIL_AVAILABLE:... |
229007eba0381237c7c698efcb4556a68e1402cb624891e715b674345176e03a | Python | 2,260 | 69 | #!/usr/bin/env python3
import argparse
import pandas as pd
from rdkit import Chem
def sdf_to_tab(vars):
mols = Chem.SDMolSupplier(vars.inp, sanitize=False)
df = pd.DataFrame() # for output
for n in range(len(mols)):
if mols[n]:
d = mols[n].GetPropsAsDict()
# filter dict ... |
5f4535935b8d2337ef529a25fa5a346fddcc9fb337e1f9869ca439e089bef2e3 | Python | 2,260 | 79 | from colorsys import hsv_to_rgb
import numpy as np
import matplotlib.pyplot as plt
def plot_text(x, ys, text, align, name):
for i in range(ys.shape[0]):
plt.text(x, ys[i], text[i], ha=align, va="center")
plt.text(x, 1 + ys.shape[0], name, ha=align, va="center")
def color(name, names):
names = s... |
61498698bc31402df6ee9f4d133b0c7092314dca21ff20d444a1c01d8226d8b1 | Python | 2,261 | 65 | """Code around assigning implicit list identifiers for collections."""
import os.path
from urllib.parse import urlparse
from pydantic import BaseModel
class FillIdentifiers(BaseModel):
fill_inner_list_identifiers: bool = False
deduplication_pattern: str = "_{#}"
deduplication_index_from: int = 1
def f... |
4c1f433194ba2d907e822f6c21fc604381a16153afb32444ccebf2ed744c124c | Python | 2,263 | 64 | import pytest
import torch
from pytest_mock import MockerFixture
from torch import distributed as dist
from lightly.loss.tico_loss import TiCoLoss
class TestTiCoLoss:
def test__gather_distributed(self, mocker: MockerFixture) -> None:
mock_is_available = mocker.patch.object(dist, "is_available", return_va... |
bc255f09b47ff3f3ab815265597e036fd64fa290e325582fd66794e8a66499b4 | Python | 2,263 | 83 | from typing import (
Any,
Dict,
Hashable,
Iterable,
Literal,
List,
Mapping,
MutableMapping,
Optional,
Tuple,
Union,
cast,
)
import pandas as pd
import xarray as xr
def concat_sdatas(
sdatas: Iterable[xr.Dataset],
keys: Optional[List] = None,
) -> xr.Dataset:
... |
663ecb624000e09ba43c5b53ebf1cde037f7111753f106e95b398755e9511657 | Python | 2,264 | 60 | import numpy as np
import scipy.interpolate as ip
def locextr(v, x=None, refine = True, output='full',
sort_values = True,
**kwargs):
"Finds local extrema "
if x is None: x = np.arange(len(v))
tck = ip.splrep(x,v, **kwargs) # spline representation
if refine:
... |
809ebbb7f60c6d61af25ade459aaa15b5e56c33a4c374de5be562557fa835ab1 | Python | 2,267 | 79 | import unittest
from numpy import log, mean
from spitfire.time.methods import *
from spitfire.time.nonlinear import *
from spitfire import odesolve
def direct_solve(fun):
def append_iteration_count_of_one_and_converged(x, *args, **kwargs):
output = fun(x, *args, **kwargs)
return output, 1, True
... |
8bbed619b84eda6279decbe317c4e6c7da79a1e91ab637fd02917f04a1a69edf | Python | 2,267 | 83 | """Tests for the public ``tl.sweep`` convenience constructor."""
from __future__ import annotations
import torch
from torch import nn
import torchlens as tl
class _ReluModel(nn.Module):
"""Small model with a sweepable ReLU site."""
def forward(self, x: torch.Tensor) -> torch.Tensor:
"""Run a simpl... |
06cc2e1cf99ad310b1af881592b91f3dd31a216ea0c3aca509de4c4ec7a8eedc | Python | 2,268 | 66 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""tests for values.py"""
import unittest
import numpy as np
from sknetwork.utils.values import get_values, stack_values, values2prob
class TestValues(unittest.TestCase):
def test_get_values(self):
n = 10
labels_array = -np.ones(n)
labels_... |
7458d783778b07c1bb1cbb91cc52baaa9aeaec12428b8945211149cc03e8a6f3 | Python | 2,268 | 77 | import pytest
import rpy2.rinterface as rinterface
try:
import numpy
has_numpy = True
except ImportError:
has_numpy = False
rinterface.initr()
def floatEqual(x, y, epsilon=0.00000001):
return abs(x - y) < epsilon
@pytest.mark.skipif(not has_numpy, reason='Package numpy is not installed.')
def test... |
0bed617ea9cca24d9d1bc1b88f1bd5652d4e56806b0d29403df2eafb6cfe8614 | Python | 2,269 | 59 | from unittest.mock import Mock, patch
from celery.apps.beat import Beat
class test_Beat_remote_control:
"""The remote-control knobs must survive the trip to the scheduler.
``Beat.__init__`` swallows unknown keyword arguments, so a flag that
isn't threaded through explicitly is silently dropped rather th... |
eeeaf5aa7f39ac49c5dbe7f9943e5dfd80ac7a866416fd527d1015633cbdc26d | Python | 2,269 | 57 | """Regression guard: a default-outpath draw() call must never write into the repo root.
xdist race (nightly fast tier, 2026-10-03): ``Trace.draw(vis_save_only=True)``
with no explicit ``vis_outpath=`` resolves the literal default basename
(``"modelgraph"``) against the process's current working directory. Several
xdis... |
4e5c399367f5df26a9e3bb71b4583d8c07977bcea9abbfcc7dd5c1ef77e01742 | Python | 2,270 | 76 | """Neutral machine identity for recorded benchmark artifacts.
Benchmark records are committed to a public repository, so they name the machine
with a neutral label instead of its hostname. Comparisons that need hardware
context read ``cpu_model`` and ``cpu_count``, which the writers record separately.
Absolute checkou... |
5bc55f8558d656253d5027814d0a079d031153ef69cdce28574e4d184fc4c7f8 | Python | 2,270 | 52 | #! /usr/bin/env python
import argparse
import sys
import os
import pandas as pd
#import subprocess
def create_sample_participant_lookup(data_dir):
sampleDS_fp = os.path.join(data_dir,
'GTEx_Analysis_v8_Annotations_SampleAttributesDS.txt')
subjectDS_fp = os.path.join(data_dir,
... |
6e0097e5c254ed228edd9717a01b6971d3f5dfe1e603b4ab80ae5dec3983b9ef | Python | 2,270 | 66 | from __future__ import annotations
from pathlib import Path
import pytest
from larvaworld.portal import notebook_workspace
from larvaworld.portal.workspace import (
WorkspaceError,
initialize_workspace,
set_active_workspace_path,
)
@pytest.fixture(autouse=True)
def workspace_config_dir(tmp_path: Path, ... |
9d80e1262cedfea5d072677a471587fd5d4c2e74b7b3241866fe1ce7fb9c7bd2 | Python | 2,270 | 81 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["splicepoint_model_spec"] = dict(
type="BothLSSIModels",
acceptor="model/splicepoint-model-acceptor-1",
donor="model/splicepoint-model-donor-1",
)
msp.architecture["motif_model_spec"]["motif_... |
dadbe38b767a8f442ac7acdabf8f37b4774c43301b12d62aebf6e862d96729a5 | Python | 2,270 | 86 | import os
import sys
os.environ["STARDIST_NAPARI_DEBUG"] = "1"
import napari
import numpy as np
from csbdeep.utils import normalize
from stardist.data import test_image_nuclei_2d, test_image_nuclei_3d
from stardist.models import StarDist2D, StarDist3D
from stardist_napari._dock_widget import surface_from_polys
def... |
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