sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
1c0adad25bbc1c70e1427a5b2c8a1a13cb1dff270ceaa6e335160a60d823cd0a | Python | 5,694 | 153 | import torch
from .. import ModelWrapper
import numpy as np
import warnings
class STGCNModelWrapper(ModelWrapper):
def __init__(self, model, optimizer_cfg, **args):
super(STGCNModelWrapper, self).__init__()
self.model = model
self.optimizer_cfg = optimizer_cfg
self.edge_index = tor... |
13ef49fa401a527efa58c6783e9cca5313380b7ca363b9a8a4ea5b3c8cb70eca | Python | 5,700 | 156 | """The match_hostname() function from Python 3.3.3, essential when using SSL."""
# Note: This file is under the PSF license as the code comes from the python
# stdlib. http://docs.python.org/3/license.html
import re
import sys
# ipaddress has been backported to 2.6+ in pypi. If it is installed on the
# system, us... |
1f62cbfe898989c3d1dbba35139591750fd59b26b4b81d8d0a5651106da87618 | Python | 5,707 | 137 | # Copyright (c) MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, so... |
977aaf1f0bbf3d006fa9f6d2ff40777ac98145cafab51d4708a00932003dd893 | Python | 5,707 | 145 | """
Advanced example: querying the literature with brain maps
=========================================================
In this example, instead of providing a text query to find related brain
regions, we provide a brain map and discover which terms or studies in the
literature are associated with similar activation p... |
ec443bb97f349b4dcec40adee339470ff9353eca6aa05d7f69f01513f3cb15c3 | Python | 5,708 | 123 | import unittest, os, sys, numpy as np, h5py, importlib
sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
from bsb.core import Scaffold
from bsb.models import Layer, CellType
from test_setup import get_test_network
def relative_to_tests_folder(path):
return os.path.join(os.path.dirname(__file__), ... |
dbc04b2b39e97229563d21900d9dcaccd43af477895ec056266e0c4f0bb274ba | Python | 5,713 | 178 | from __future__ import annotations
from collections.abc import Mapping, Sequence
from types import MappingProxyType
from typing import TYPE_CHECKING, Any, Literal
import pandas as pd
from anndata import AnnData
from scanpy import logging as logg
from squidpy._compat import old_positionals
from squidpy._docs import d... |
e5f444f89498fe1a002e139165360e096d273db0962e80e72b6614e5cbaf2d11 | Python | 5,716 | 200 | from typing import Union, Callable
import numpy as np
import warnings
import torch
import torch.nn as nn
from sklearn.metrics import f1_score
def setup_evaluator(metric: Union[str, Callable]):
if isinstance(metric, str):
metric = metric.lower()
if metric == "acc" or metric == "accuracy":
... |
d059b71f2d9a180cbd98a5fc740c7d2035514246347a7bedb23136b7d188582e | Python | 5,719 | 205 | """
#########################################################################################################
Author: Álvaro Fernández García
Date: 4 - Junio - 2019
Description: Entrenamiento y validación de modelos entrenados en imagenet
y aplicados a la detección de las Glándulas.
###################################... |
f99152f77da7e9afd46b00eb59c90f07ecfb4c02b289543721049ff439aa1420 | Python | 5,723 | 145 | """
Copyright © 2025 Howard Hughes Medical Institute, Authored by Carsen Stringer , Michael Rariden and Marius Pachitariu.
"""
from qtpy.QtWidgets import QAction
from . import io
def mainmenu(parent):
main_menu = parent.menuBar()
file_menu = main_menu.addMenu("&File")
# load processed data
loadImg = Q... |
7bd90116f4ce8ad82a47b2e3d007746793fe366c5ceb3763719379a64e9097aa | Python | 5,724 | 135 | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
from __future__ import print_function
"""
python {} study.file population.file gene-association.file
This program returns P-values for functional enrichment in a cluster of study
genes using Fisher's exact test, and corrected for multiple testing (including
Bonferroni, Ho... |
60682eb2f17f4ae08d0fb87b3f5f9c6f62bc5cd2b1219420fb07d8ead21adb2f | Python | 5,725 | 155 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Postprocessing functions, used for interpretation of fitted models
Created on Wed May 19 10:03:53 2021
@author: townesf
"""
import numpy as np
from copy import deepcopy
from pandas import DataFrame
from utils.misc import t2np,nan_to_zero
from utils.nnfu import norma... |
ab339a25812c38636ac5a985fcc61ec900f88b78cfed17aad9c24e202ee9170a | Python | 5,726 | 155 | from collections.abc import Sequence
import numpy as np
from pydantic import BaseModel, ConfigDict, field_validator
from .util import NPArray
class LanguageModelConfig(BaseModel):
"""Protein language model integration parameters."""
model_config = ConfigDict(arbitrary_types_allowed=True)
use_language_... |
9ced880667cfede73586f82658c50807f422aa1c801d9199ed20d1a3214eeb77 | Python | 5,730 | 104 | '''
CUDA_VISIBLE_DEVICES=2 python Train_Test_Examples.py --model_name GraphSAGE \
--data_path ../dataset/BBBP/BBBP.csv \
--dataset_name BBBP \
--smiles_col smile... |
02c657fdbe6321668489c244b17bf05ccca58910861a37df1f10caedc65fcfe6 | Python | 5,731 | 169 | from __future__ import print_function, unicode_literals, absolute_import, division
import numpy as np
import warnings
from skimage.measure import regionprops
from skimage.draw import polygon
from csbdeep.utils import _raise
from ..utils import path_absolute, _is_power_of_2, _normalize_grid
from ..matching import _che... |
8f1d5aa93a1844f90103239683d697851ff075f658fad5165243bbb4e68c02f9 | Python | 5,735 | 165 | """Dataset setting and data loader for MNIST-M.
Modified from
https://github.com/pytorch/vision/blob/master/torchvision/datasets/mnist.py
CREDIT: https://github.com/corenel
"""
from __future__ import print_function
import errno
import os
import torch
import torch.utils.data as data
from PIL import Image
class MN... |
55d7d1aa283165c4c78047d44cb07b7aeb4701a0c50a6cb597bfc1da25c4d630 | Python | 5,736 | 167 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... |
624d44aa760bbd14227caa062f06bc89b0f9e01151b7cca9350c6fae5ca6dc9b | Python | 5,736 | 238 | import math
from functools import partial
from typing import Optional
import torch
from ..autograd import _higher_order_grad, _save_for_higher_order
from ..layout import _fake_empty_like
from ..validation import _check_gradients, _check_inputs
def _check(
x: torch.Tensor,
v: torch.Tensor,
w: torch.Tenso... |
c0181c070bfd6c97a36b2a776b631a67b9ce56833fb91002292fcd05b61e8f1b | Python | 5,738 | 132 | # -*- coding: utf-8 -*-
from figureflow import figure
import seaborn as sb
import numpy as np
import os
import importlib
importlib.reload(figure)
Figure = figure.Figure
# get the path to the data of the respective figure or movie
# the data is in the data folder in a folder with the same
# name as the folder that t... |
c38653c3a4199bfc55edd10025f596624d7e10a1477b00e2c365860b855048f8 | Python | 5,739 | 123 | import os
import numpy as np
import pandas as pd
from src.utils import get_parcelwise_average_surface
import wget
import nibabel as nib
from src.utils import load_schaefer_parc, load_glasser_parc
from sklearn.metrics import pairwise_distances
class BrainMapLoader:
def __init__(self, computer='macbook', parc='schae... |
7aa868e8eeab2c668b60eabc8ae5682da8fad9d27c6cd4431054e5cccef1c32d | Python | 5,741 | 135 | #!/usr/bin/env python
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "L... |
93400c43d1996bc333df29239083677f2cd0557b3d5db26f5a5c2ff39fea8804 | Python | 5,741 | 197 | # -*- coding: utf-8 -*-
"""
MultipleComparisonCorrection
============================
Correction methods for multiple comparison tests.
"""
__author__ = 'Christoph Kirst <christoph.kirst.ck@gmail.com>'
__license__ = 'GPLv3 - GNU General Pulic License v3 (see LICENSE.txt)'
__copyright__ = 'Copyright © 2020 by Chri... |
fffd6a5d84b1cf246a695b4388510b1e6acf555c7ec9ab57d6551d3ec0d85434 | Python | 5,744 | 118 | #!/usr/bin/env python
#
# Copyright (c) 2019 10x Genomics, Inc. All rights reserved.
#
import martian
import math
import os
import cellranger.analysis.constants as analysis_constants
import cellranger.matrix as cr_matrix
from constants import ALLOWED_FACTORIZATIONS, DEFAULT_FACTORIZATION
__MRO__ = """
stage ANALYZER_... |
8d3e263fbece6ac84feb4e736db237084d27a719493c639ffefd6cdf5b352447 | Python | 5,745 | 127 | import matplotlib.pyplot as plt
from matplotlib.pyplot import MultipleLocator
r"""lr vs coeff"""
plt.xlabel("lr")
plt.ylabel("coeff")
x = [1, 2, 3, 4, 5, 6, 7, 8]
x_index = ['0.00005', '0.0001', '0.0002', '0.0005', '0.001', '0.005', '0.01', '0.02']
# std V: [0.028, 0.008, 0.005, 0.013, 0.012, 0.005, 0.005, 0... |
f0eedd37bafdf2f5adeb15011f5a52c61e98e01b149457770f4be5c957882236 | Python | 5,747 | 142 | import os
import shutil
import tempfile
import unittest
import numpy as np
from bsb import MPI, Configuration, Scaffold, read_results
from bsb.simulation.results import iter_recordings
from bsb_test import (
NumpyTestCase,
RandomStorageFixture,
get_test_config,
get_test_config_tree,
)
def _population... |
8e6d794a9d1f1530f456bc181e22e321958b0c7ad93963de46b4df66c5f450bd | Python | 5,750 | 162 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
CellMap
=======
This script is the main pipeline to analyze immediate early gene expression
data from iDISCO+ cleared tissue [Renier2016]_.
See the :ref:`CellMap tutorial </CellMap.ipynb>` for a tutorial and usage.
.. image:: ../Static/cell_abstract_2016.jpg
:t... |
c3a6ae53387e163092c65ad029af1ed50949cfcb37c847da5f8ae266ae0fbbbb | Python | 5,755 | 151 |
"""
Copyright (c) 2019 10x Genomics, Inc. All rights reserved.
Perform normalization of libraries
"""
# Imports
import pickle
import json
import os
import pysam
from pybedtools import BedTool
from tools.io import merge_keyed_bed, subsample_fragments
from tools import ReferenceManager
import cellranger.io as cr_io
i... |
822e35236b923999b2358ec6bcfd38ea6d76d6a9b48f3ce12119244fb64fc9ea | Python | 5,756 | 189 | import sys
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from sklearn.mixture import GaussianMixture
from scipy import stats
def quantile_norm(X):
"""
Normalize the columns of X to each have the same distribution.
Given an expression matrix (microarray data, ... |
02c12112ef1913f4eb21db622dae63077768d802c6be75aac7d6dfce24152f00 | Python | 5,757 | 169 | import collections
from typing import AbstractSet
import problog.core
import problog.logic
import problog.program
import problog.sdd_formula
from nl_expr.expressions import Constant, FunctionApplication, Symbol
from ...relational_algebra import (
NamedRelationalAlgebraFrozenSet,
str2columnstr_constant,
)
from... |
b5e30082337dc94fc1cf81e34bb9f0d300b88fd7534d7e4afe563b805775681f | Python | 5,758 | 144 | import numpy as np
import random
import sys
import math
## Placing the bead in the brush
# System info
radius = 1
spacing = 4.5
charge = -1
T = 3
# Number of files out, etc.
Nconfigs = 100
Nplacements = 10
Nfiles = Nplacements
seed = 23
# Technicalities: Placement of bead
tol ... |
42c050890938bcc9d70f9bbc7db7fc7b191bca342dc43f7b8ecd68560a6b8b29 | Python | 5,759 | 171 | # Copyright 2020 DeepMind Technologies Limited.
#
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agre... |
3c0789ed8b7c914a9b0e0bc16b3fd97d415983ec3ebdfd603c2d073ba828fd32 | Python | 5,762 | 142 | """Time dependent algorithms."""
import networkx as nx
from networkx.utils import not_implemented_for
__all__ = ["cd_index"]
@not_implemented_for("undirected")
@not_implemented_for("multigraph")
@nx._dispatchable(node_attrs={"time": None, "weight": 1})
def cd_index(G, node, time_delta, *, time="time", weight=None):... |
5a49bc4599e814552a15d36fc863ac532cf6ef181de0a8abcc83c9ab8244ff29 | Python | 5,763 | 148 | import numpy as np
import nibabel as nb
import os
import h5py
def load_mgh(filename):
""" import mgh file using nibabel. returns flattened data array"""
mgh_file=nb.load(filename)
mmap_data=mgh_file.get_data()
array_data=np.ndarray.flatten(mmap_data)
return array_data;
def import_mgh(filename):
... |
f7ebb829f7dec4f3049b9dab4da22310ec6c0807760cc072c73bf91f9eba40bc | Python | 5,763 | 158 | """Build wheels/sdists by installing build deps to a temporary environment.
"""
import os
import logging
from pip._vendor import pytoml
import shutil
from subprocess import check_call
import sys
from sysconfig import get_paths
from tempfile import mkdtemp
from .wrappers import Pep517HookCaller
log = logging.getLogge... |
2d98a187bd3ae50ddc5501446720e30ffd551f2222cee13a7f335fd1cd8dfe04 | Python | 5,764 | 230 | import os
import unittest
import numpy as np
import numpy.testing as npt
from parameterized import parameterized
from sklearn.datasets import make_blobs
import divik._matlab_legacy as ml
def no_threshold():
np.random.seed(0)
return np.random.randn(500)
def single_th_between_0_and_100():
np.random.seed... |
a595a7ddfe8d098fa51ad562290875d4d2790a7f9c5c12a1bda70cc9c837f38e | Python | 5,764 | 188 | import importlib
import importlib.util
import inspect
import os
import sys
import types
__all__ = ["attach", "_lazy_import"]
def attach(module_name, submodules=None, submod_attrs=None):
"""Attach lazily loaded submodules, and functions or other attributes.
Typically, modules import submodules and attributes... |
df88a30e0d00e7f0608c06f30012734eef46f69d3f79e29682aba613a0438df3 | Python | 5,764 | 165 | # -*- coding: utf-8 -*-
"""
GraphVisual
===========
Module providing Graph visuals for rendering graphs.
Note
----
This module is porviding vispy visuals only.
See :mod:`PlotGraph3d` module for plotting.
"""
__author__ = 'Christoph Kirst <ckirst@rockefeller.edu>'
__license__ = 'MIT License <http://www.opensourc... |
61e200f634757232be71dec596aa3032df92f7de7ca58ebd605b7b16d3b6626b | Python | 5,766 | 148 | # MIT License
#
# Copyright (c) 2019 Lucas K Wagner
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merg... |
5e79be61f40195d7649c47a7cee044a039b521bb7720b80f09973809be6c1eea | Python | 5,769 | 138 | import copy
import math
import os
import random
import allennlp
import torch
from typing import Iterator, Dict, List, Tuple
from allennlp.training import Trainer
from torch.utils.data import Subset, Dataset
from numpy.random.mtrand import RandomState
from allennlp.common import util as common_util
from allennlp.dat... |
b92063c23b343428e8e73407d2693876a76bf6252bec8d5cc5502491b43d39eb | Python | 5,769 | 155 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Postprocessing functions, used for interpretation of fitted models
Created on Wed May 19 10:03:53 2021
@author: townesf
"""
import numpy as np
from copy import deepcopy
from pandas import DataFrame
from spatial_factorization.utils.misc import t2np,nan_to_zero
from s... |
197965ca448921514e1aff350799e4e98e5972b5f16c3426e4a70aeadc6f1cd6 | Python | 5,772 | 145 | # -*- coding: utf-8 -*-
"""
Template to run the processing pipeline
"""
import os,numpy
#load the parameters:
runfile('/home/wirrbel/FriendlyClearmap/clearmap/docs/conf.py')
from ClearMap import *
parameter_filename = '/home/wirrbel/FriendlyClearmap/clearmap/ClearMap/Scripts/example_set/S1_57645/parameter_file.py'
e... |
2ccfefdc9c95af01fdf997e67914037a02dd6ad6166be817ad3c487756ecdfde | Python | 5,772 | 111 | # -*- coding: utf-8 -*-
from figureflow.figure import Figure
import seaborn as sb
import os
# get the path to the data of the respective figure or movie
# the data is in the data folder in a folder with the same
# name as the folder that the script is in
# the input_folder can also just be the folder in which the scr... |
774a5a8c551edaa03bd363acf051b5de343a734647876e0322fa23559118d48a | Python | 5,772 | 148 | """
Agent registry for managing available AI agents.
"""
import logging
from typing import (
Optional,
)
from .base import (
BaseGalaxyAgent,
GalaxyAgentDependencies,
)
log = logging.getLogger(__name__)
class AgentRegistry:
"""Registry for managing available AI agents."""
def __init__(self):
... |
53dcf5f4b7357aa7414289c1fc5c99526312010f55df9cbb8c73ab2ed5bc0f22 | Python | 5,774 | 174 | # Reference: https://wiseodd.github.io/techblog/2017/03/07/boundary-seeking-gan/
import argparse
import os
import numpy as np
import math
import torchvision.transforms as transforms
from torchvision.utils import save_image
from torch.utils.data import DataLoader
from torchvision import datasets
from torch.autograd i... |
cfe3a5d6263a2cdd532c3d54777f03c565e5e9b08a7f6d95c06f560d469280fc | Python | 5,774 | 150 | import logging
import numpy as np
from sklearn.base import BaseEstimator
import divik._matlab_legacy as ml
from divik.core import configurable
from ._stat_selector_mixin import StatSelectorMixin
@configurable
class GMMSelector(BaseEstimator, StatSelectorMixin):
"""Feature selector that removes low- or high- me... |
2c4cbc93632ba37a7ace3c0640d1febfb5efdf78c2742afa244e3a09b270b462 | Python | 5,776 | 167 | #!/bin/python3
# Utility functions for displaying and storing data
# Copyright 2021-2023 Jannik Luboeinski
# License: Apache-2.0 (http://www.apache.org/licenses/LICENSE-2.0)
# Contact: mail[at]jlubo.net
import time
from datetime import datetime
import os
import re
###################################################... |
f3ac5b8ed01d8c5d1b3c77ea3aeb909544920ce6e720650c38f0fda26f3b454b | Python | 5,776 | 156 | __doc__ = """
Independent Implementation of HCBS' Synaptic Partner Candidate Generation
See: https://github.com/paragt/EMSynConn/blob/master/vertebrate/candidate/generate_proposals.py
"""
import numpy as np
from scipy import spatial
from scipy.ndimage import distance_transform_edt
from ... import seg_utils
from .. i... |
cf152cb81b35fe0f208eeffaa2ab9e5e7c9c2816aee7d4ecaac0f2ed0ed922ba | Python | 5,780 | 166 | # -*- coding: utf-8 -*-
# Author: Florian Boudin
# Date: 09-10-2018
"""Kea supervised keyphrase extraction model.
Kea is a supervised model for keyphrase extraction that uses two features,
namely TF x IDF and first occurrence, to classify keyphrase candidates as
keyphrase or not. The model is described in:
* Ian Wit... |
05e5baa8cec5429814cbe3d84b09b0866ed85b4c3a8facbad477b703d079b8ae | Python | 5,782 | 165 | #!/usr/bin/env python3
#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "Li... |
075361bafcea7215eebf01f3096506586b7e21988810029059a562706a0cc4f4 | Python | 5,784 | 114 | import logging
from galaxy.tool_shed.tools.data_table_manager import (
BaseShedToolDataTableManager,
RequiredAppT,
)
from galaxy.tool_shed.util import (
basic_util,
hg_util,
)
from galaxy.tool_util.fetcher import ToolLocationFetcher
from galaxy.tool_util.parser import get_tool_source
from galaxy.tool_u... |
5d2de51b7e30c6bb2d1b53d2fa7f4ca9cc90224326b0e4639a9fa5b627675518 | Python | 5,786 | 108 | import tensorflow as tf
from .generic import *
class DataLoaderMidAir(DataLoaderGeneric):
"""Dataloader for the Mid-Air dataset
"""
def __init__(self, out_size=[384,384], crop=False):
super(DataLoaderMidAir, self).__init__('midair')
self.in_size = [1024, 1024]
self.depth_type = "ma... |
b31cd8d946273e4d591de86667e11c9e179a6af9d6b7b09c83747592f8748a55 | Python | 5,786 | 203 | """Tests for the attribute .X"""
from __future__ import annotations
import numpy as np
import pandas as pd
import pytest
from scipy import sparse
import anndata as ad
from anndata import AnnData
from anndata._warnings import ImplicitModificationWarning
from anndata.tests.helpers import (
GEN_ADATA_NO_XARRAY_ARGS... |
131916f470a3dd4ca8bcfe197eb4a008801198ede7218db7a3e8cf527d1465fc | Python | 5,787 | 126 | from __future__ import print_function
import tensorflow as tf
from keras import activations, initializers, constraints
from keras import regularizers
from tensorflow.keras.layers import Layer
import keras.backend as K
class GraphConvolution(Layer):
"""Basic graph convolution layer as in https://arxiv.org/abs/160... |
981aca00006f08f41558b603015c22464a90af82b088cf1c1849a146a240d7c3 | Python | 5,787 | 137 | import typing
import unittest
from itertools import zip_longest
import arbor
from arborize import Schematic, arbor_build
from arborize.builders._arbor import get_decor, get_label_dict, hash_labelset
# This import only works when tests are executed from root dir.
from tests._shared import SchematicsFixture
if typing... |
ae32284fbf9aa8ac0648136863180a9e20c582a483c15f07876d659164581951 | Python | 5,787 | 155 | r"""Computation of graph non-randomness."""
import math
import networkx as nx
from networkx.utils import not_implemented_for
__all__ = ["non_randomness"]
@not_implemented_for("directed")
@not_implemented_for("multigraph")
@nx._dispatchable(edge_attrs="weight")
def non_randomness(G, k=None, weight="weight"):
""... |
ae6a408b726a52dc40bbb387a2af0c29ff89b7806e630567783b74717fc0e6cb | Python | 5,787 | 160 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... |
369feab129a84d8d5671ce6aad9563ac3a5326ce7b709f66d93a07b36872852b | Python | 5,790 | 151 | from pathlib import Path
from scipy.cluster.hierarchy import ward
from sklearn.metrics.pairwise import cosine_similarity
class MetaClusterData():
"""Store the state of the clusters and metaclusters
Args:
cluster_type (str):
the type of clustering being done
raw_clusters_df (pd.Da... |
8f3b7a929f2960936a075b7f9dff65cf5ba3ca0e42e605aff48d1a0fe16fd3a3 | Python | 5,791 | 164 | # cluster.py
# Authors: Jacob Schreiber <jmschreiber91@gmail.com>
# adapted from code written by Avanti Shrikumar
import sys
import itertools
import numpy as np
from . import forked
# Edges handed to igraph per chunk in _graph (about 1.3 MB of Python ints).
_EDGE_CHUNK = 16384
def _leiden(g, weights, seed, n_lei... |
342a026c59538e45afdd1962bb2c852dbdc34d1f713354f32b8e984b95961f5b | Python | 5,792 | 173 | """Functions for generating graphs based on the "duplication" method.
These graph generators start with a small initial graph then duplicate
nodes and (partially) duplicate their edges. These functions are
generally inspired by biological networks.
"""
import networkx as nx
from networkx.utils import py_random_state... |
0bef7bb61d839566aa460f8abf4862c252252a1d02de4c617a7268927c6c71b4 | Python | 5,794 | 195 | import matplotlib
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from matplotlib import gridspec
import matplotlib.patches as mpatches
from sklearn import datasets, linear_model
import parmap
import numpy as np
import os
import pickle
from sklearn.decomposition import PCA
import pycorrelate
from tqdm impor... |
07ad3c4f348638e952b8f51ca0541d5311cd588d34bf9f224c7b8569a9b8b061 | Python | 5,796 | 139 | # 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.
# pyre-strict
from collections.abc import Iterable, Sequence
from typing import final
from ax.adapter.base import Adapter
from ax.analysi... |
a35dacdb49d12edac834a3b733aea73f42e5f67c8ec106869989e382055240f0 | Python | 5,799 | 146 | #!/usr/bin/env python3
# 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.
# pyre-strict
import dataclasses
import datetime
import enum
import math
from collections import OrderedDict
from co... |
68fd21dfa3445ece1eea0affbd97490174d4a9cb9d6cc3aea3c6af777e6893e9 | Python | 5,801 | 146 | # %% import
import sys, os, platform
from src.imaging_derivs import DataMatrix
from src.pipelines import ComputeMinimumControlEnergy
from src.plotting import my_reg_plot
from src.utils import rank_int
import scipy as sp
# %% import workspace
os.environ["MY_PYTHON_WORKSPACE"] = 'ave_adj'
os.environ["WHICH_BRAIN_MAP"] ... |
90ea3e246b975221efe1f6044040e9273ac4e47519d081456dd62b2c1f73a7cb | Python | 5,804 | 157 | #!/usr/bin/env python
#
# Copyright (c) 2017 10X Genomics, Inc. All rights reserved.
#
from collections import namedtuple, OrderedDict
import h5py
import cellranger.io as cr_io
FeatureDef = namedtuple('FeatureDef', ['index', 'id', 'name', 'feature_type', 'tags'])
# Required HDF5 datasets
REQUIRED_DATASETS = ['id', '... |
c80b019457f99218a152bbbc72d2a41ce92ef6e64b781ad16e8f30a60b8a4a32 | Python | 5,804 | 149 | import io
import pickle
import sys
import time
from tqdm import tqdm
from src.gru import *
from src.pre_data import *
from src.train_and_evaluate import *
from src.warmupLR import *
import warnings
warnings.filterwarnings("ignore")
USE_CUDA = torch.cuda.is_available()
size_split = 0.8
PAD_token = 0... |
50492629a80dc3db23f248940dd6c0798bb3bd9df5a602cc5eace58aa3241bce | Python | 5,805 | 150 | """Distance measures approximated metrics."""
import networkx as nx
from networkx.utils.decorators import py_random_state
__all__ = ["diameter"]
@py_random_state(1)
@nx._dispatchable(name="approximate_diameter")
def diameter(G, seed=None):
"""Returns a lower bound on the diameter of the graph G.
The functi... |
e4e76d065358ba190316f30bc077aa7b87ae6de2e6e375d61c4364e2b1c37a75 | Python | 5,807 | 162 | # 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.
# pyre-strict
from collections.abc import Sequence
from typing import Any
import torch
from botorch.models.model import Model
from botorch... |
51ff90ca2a3ec85909da7a8182e71894eec45db10246235623c1e161f626b099 | Python | 5,809 | 167 | import pickle
import time
from torch.nn.parallel import DistributedDataParallel
from tqdm import tqdm
from src.S2S_greedy_feedback import *
from src.pre_data import *
from src.train_and_evaluate import *
import os
import warnings
from src.warmupLR import GradualWarmupScheduler
warnings.filterwarnings(... |
2d713e1320c8b7cca87fa9bf76bc02f05bcdd030afa657e0f2fc8e2dba4877e3 | Python | 5,810 | 150 | """
Plot Figure 5 (Lorenceau)
"""
import numpy as np
import strinf as si
# # # PARAMETERS # # #
ZOOM = 2.0
SAVE = True
SHOW = True
PANEL = ("C",)
lorenceau = {
"DSL_low_noise" : "2021-08-26-12-09-10-696387_110_lorenceau_1996_low_noise",
"DSL_high_noise" : "2021-08-26-12-07-25-644304_110_lorenceau_1996_high... |
7ac10465b0a8173ea43bc3bbea4fd50f840aa94b122bd108a28e553e699b1370 | Python | 5,810 | 180 | """Define and provide model RDMs.
NOTE: The order in MODELS determines the order of orthogonalization.
"""
import copy
import numpy as np
from scipy.spatial.distance import squareform
from config import NUMBERS
from utils import calc_rdm, eq1, spm_orth
MODELS = {
"9x9": {"numberline", "extremity"},
"18x18"... |
508a4a625dca5dba50fb2189dae8f2ac012e6f316f811dd1b7f9b7ccf02d3a18 | Python | 5,811 | 148 | import os
import click
import sys
import logging
from .job_manager import BatchManager, Job
from .config_json_parser import ClpipeConfigParser
from .error_handler import exception_handler
@click.command()
@click.argument("subjects", nargs=-1, required=False, default=None)
@click.option(
"-config_file",
type=c... |
5da0809318fdecdc9b2f17473157f97f04e77d6860ffe2c8518d9c95251acb98 | Python | 5,812 | 148 | import os
import click
import sys
import logging
from .job_manager import BatchManager, Job
from .config_json_parser import ClpipeConfigParser
from .error_handler import exception_handler
@click.command()
@click.argument("subjects", nargs=-1, required=False, default=None)
@click.option(
"-config_file",
type=c... |
2b6d7095f3479dc289ac74d51c6f7d880268f68e7fb1cfed7e6e79b242e53710 | Python | 5,815 | 140 | # -*- coding:utf-8 -*-
__author__ = 'yangjian'
"""
Denoise Auto-encoder
Denosing auto encoders are an important and crucial tools for feature selection and extraction.
"""
import numpy as np
from tensorflow.keras.callbacks import EarlyStopping, ReduceLROnPlateau
from tensorflow.keras.layers import Dense, Input
from te... |
2f31ebae67d72331bf7b9ed1c87bac4d8d0ddbd73f82178879e643489d425dff | Python | 5,817 | 179 | import torch
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.ticker import AutoLocator
from ..utils.convert_units import freq_to_wl, wl_to_phys_wl
from ..utils.compute_spectrum import compute_spectrum
from ..training.model.model_to_eps_grid import model_to_eps_grid
from ..utils.global_constants ... |
75827054c2180da933ed0236aff6ca15e34110631fe4f7d64d03043621397246 | Python | 5,819 | 189 | # -*- coding: utf-8 -*-
#
# Configuration file for the Sphinx documentation builder.
#
# This file does only contain a selection of the most common options. For a
# full list see the documentation:
# http://www.sphinx-doc.org/en/master/config
# -- Path setup ------------------------------------------------------------... |
26a0a049d624d7f8e5953132089e131d644fc5306f63cecc1bc8973ba84869d9 | Python | 5,820 | 156 | #!/usr/bin/env python
###############################################################################
###############################################################################
## Created on February 1st 2017 to remove singletons from paired-end BAM file
###########################################################... |
9085878ed5d49c2cb32d2cd26d97ac510b7c29b832ced06b04085be624449e66 | Python | 5,820 | 141 | """
Evaluation functions to measure the performance of a given loss function on a
given dataset
"""
import sys
sys.path.append('..')
from losses.losses import *
from misc.utils import *
from misc.loaders import *
import lightgbm as lgb
from sklearn.metrics import *
from scipy.special import expit
from sklearn.model_... |
4f4bd8482574cb7041eb5bd330a50075a29136b233bf87f73a743799e74913dd | Python | 5,827 | 163 | from enum import Enum
import numpy as np
from learnMSA.model.tf.model import LearnMSAModel
from learnMSA.util.dataset import Dataset
from learnMSA.util.sequence_dataset import SequenceDataset
class SelectionCriterion(Enum):
POSTERIOR = "posterior"
LOGLIK = "loglik"
AIC = "AIC"
CONSENSUS = "consensus... |
c6f6a2372c76d1eea14ab2bf25c02f222338f2c6deddab88b0e2fc18557feeef | Python | 5,828 | 144 |
"""
Copyright (c) 2019 10x Genomics, Inc. All rights reserved.
aggregation metrics are devised from final fragments file
"""
import martian
from tools.io import get_counts_by_barcode
from tools import ReferenceManager
from metrics.generate_metrics import (add_doublet_rate_metrics, add_purity_metrics, add_bulk_target... |
1e762514a49a848b10b44b2dc7654d88011c708fe2384b337a15c538d8ec47b9 | Python | 5,829 | 155 | import numpy as np
import sklearn
import pytest
from himalaya.backend import set_backend
from himalaya.backend import ALL_BACKENDS
from himalaya.validation import _assert_all_finite
from himalaya.validation import check_cv
from himalaya.validation import validate_data
@pytest.mark.parametrize('backend', ALL_BACKENDS... |
5022a53f965fa2d45e025fb70eb2f47be374905003fc48bebb5bd173c69fbf7d | Python | 5,831 | 173 | from collections import Counter, defaultdict
import numpy as np
from scipy.signal import find_peaks, peak_widths
from sklearn.cluster import dbscan
from scipy.spatial.distance import euclidean
def parse_peakachu(fil, thre, res):
D = defaultdict(dict)
score_pool = defaultdict(dict)
with open(fil,... |
7f7ba7bcbfb6f38a9a4523a0356fcd999bef5f7f9cc1248aef9c27df33af50b9 | Python | 5,831 | 170 | """
Module for the Report class.
"""
from typing import List, Union
from warnings import warn
import matplotlib.backends.backend_pdf
import numpy as np
from bsb import Scaffold, from_storage
from cerebellum.analysis.plots import Plot, ScaffoldPlot
class PlotTypeInfo:
"""
Class storing information about ele... |
60b7e20e2e5913d398ac0cd2728d501d0e52cf8ec39f5876fad1069f0950a832 | Python | 5,834 | 174 | '''
The implementation of PIGNPI and the baseline
'''
import numpy as np
import torch
import torch.nn as nn
from torch.functional import F
from torch.optim import Adam
from torch.nn import Sequential as Seq, Linear as Lin, ReLU, GELU, Tanh, Softplus, Sigmoid, LeakyReLU
from torch.autograd import grad
torch.set_defaul... |
d7ae1a0fd9838838d79e82cfa7bd9b64dcf94334ad5045e0da911020dd355f13 | Python | 5,834 | 167 | import numpy as np
import scipy
import scipy.cluster.hierarchy as sch
from .dmg import PairwiseDMG
class ClusterMerge:
"""Perform cluster merge based on the given merge criterion."""
def __init__(
self,
merge_criterion,
stop_criterion=None,
stop_clusters=-1,
n_cells=2... |
25f44680fba217ebc9bb97dcdbfa5c25844411ba3170afdd9b2fa7a77f5ce00c | Python | 5,839 | 147 | import pytest
pytest.importorskip("numpy")
pytest.importorskip("scipy")
import networkx as nx
from networkx import edge_current_flow_betweenness_centrality as edge_current_flow
from networkx import (
edge_current_flow_betweenness_centrality_subset as edge_current_flow_subset,
)
class TestFlowBetweennessCentrali... |
64b48ecda9c47dab15b04c26de1c2abdb1434a6c6f88cced214a837c014295e5 | Python | 5,839 | 182 | import pathlib
import subprocess
from concurrent.futures import ProcessPoolExecutor, as_completed
from functools import lru_cache
import anndata
import numpy as np
import pandas as pd
import pysam
from scipy import stats
from scipy.sparse import csr_matrix
from .._doc import *
from ..utilities import parse_mc_pattern... |
35a1c66f02ee402c7f181e51ed46a0d8008a4a6ae908540ab11937cbd844e88a | Python | 5,841 | 190 | import networkx as nx
__all__ = ["cytoscape_data", "cytoscape_graph"]
def cytoscape_data(G, name="name", ident="id"):
"""Returns data in Cytoscape JSON format (cyjs).
Parameters
----------
G : NetworkX Graph
The graph to convert to cytoscape format
name : string
A string which is... |
1feca8f01d5d19e8603c65c7d6d064993f0e2c1248d7e4566b047a285e3fc520 | Python | 5,842 | 188 | # This file was automatically generated by SWIG (http://www.swig.org).
# Version 3.0.12
#
# Do not make changes to this file unless you know what you are doing--modify
# the SWIG interface file instead.
from sys import version_info as _swig_python_version_info
if _swig_python_version_info >= (2, 7, 0):
def... |
ece92b5267d68a8f53efcc40d4e2691174cd5f1b6e8bad7a92318a04f8055ce5 | Python | 5,843 | 199 | import matplotlib.pyplot as plt # To plot
import numpy as np
import random
import math
# 17.09.20: Hexagonally tethered chains for input to LAMMPS.
# Set variables
N = 100 # Number of bond vectors = number of units - 1 # Per chainaffect
gridspacing = 3.5 # The spacing in our g... |
08c6c2019a608a69df43055cf036f8d8a49a893fb3c9af7f1f65a6e5ed4ed83c | Python | 5,844 | 157 | import torch
import random
import rdkit
import rdkit.Chem as Chem
import networkx as nx
from MolRep.Explainer.Attribution.utils.fuseprop.chemutils import *
from MolRep.Explainer.Attribution.utils.fuseprop.nnutils import *
from MolRep.Explainer.Attribution.utils.fuseprop.vocab import common_atom_vocab
from collections i... |
a7c5e9faa5bbc0585158f32fa144f713826b31f283fc5dbe44d7a6b0700409bb | Python | 5,845 | 198 | import nibabel as nb
import numpy as np
import os
from nipype.interfaces.base import (
BaseInterface,
BaseInterfaceInputSpec,
traits,
File,
TraitedSpec,
CommandLine,
CommandLineInputSpec,
)
from nipype.utils.filemanip import split_filename
import nipype.pipeline.engine as pe
from nipype.int... |
5b8ed5bb3ca06be6ef898b528f83e429d4cc35c1d6116759aea135cec1da8bf4 | Python | 5,846 | 159 | # MIT License
#
# Copyright (c) 2019-2024 The PyQMC Developers
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, m... |
e40f3f8137e1ba8504396f2efee1827cf02c24217c5193276d94df483aa567f5 | Python | 5,847 | 137 | from uff.ic.mell.sentimentembedding.datasets.dataset_loader import DataSetLoader
from uff.ic.mell.sentimentembedding.classificadores.analisador import Analisador
from uff.ic.mell.sentimentembedding.vocabularios.deepmoji_vocabulario import DeepMojiVocabulario
from uff.ic.mell.sentimentembedding.vocabularios.emo2vec_voc... |
1e4c78071477c5a4ebb58e401df7ea6e100c44ace7730087576b5204b4dc811a | Python | 5,849 | 149 | """
Utility functions for doing stratified random sampling (at the sentence
level) for those corpora which do not have test/train splits, and for saving
the test and train data in CONLL 2003 format in separate directories.
"""
import os
import codecs
from sklearn.model_selection import train_test_split
import utils
... |
64816f0f1d4a2c040a18100ecf5c6a911b51b8a07cad5c180994a398c8bb3b0a | Python | 5,850 | 208 | # -*- coding: utf-8 -*-
"""
Created on Wed Dec 4 11:35:36 2019
@author: aaussel
"""
from IB_soma_LIP import *
from IB_axon_LIP import *
from IB_apical_dendrite_LIP import *
from IB_basal_dendrite_LIP import *
from scipy import signal
prefs.codegen.target = 'numpy'
defaultclock.dt = 0.01*ms
runtime=1*second
start... |
7c12e283ccf9e3c82c041950c3a54974665be0872a263effd268b615dda77043 | Python | 5,851 | 177 | import pytest
import networkx as nx
class TestFilterFactory:
def test_no_filter(self):
nf = nx.filters.no_filter
assert nf()
assert nf(1)
assert nf(2, 1)
def test_hide_nodes(self):
f = nx.classes.filters.hide_nodes([1, 2, 3])
assert not f(1)
assert not... |
b388530b7660243975eb11c070a04055f0e54dcc3bd2075f01597659d4ee81cb | Python | 5,852 | 193 | import argparse
import torch.nn as nn
import torch.nn.functional as F
from cogdl import experiment
from cogdl.models import BaseModel
from cogdl.layers import GCNLayer, SAGELayer, GATLayer
from cogdl.datasets.ogb import OGBArxivDataset
class GCN(BaseModel):
def __init__(
self,
in_feats,
hi... |
628a38a762937c4e8d88f28f80340367d16363d29c2cc218c03cdc797a83f98f | Python | 5,853 | 142 | # coding: utf-8
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"... |
fed593c4bc6028035cd53921ed6a102ff97547c50f2c37e20cb911ea79bc0b93 | Python | 5,853 | 134 | # -*- coding: utf-8 -*-
import os
import pandas as pd
import numpy as np
import glob
def get_kif_and_condition_from_file_path(file_path):
folder_name = os.path.basename(os.path.dirname(file_path))
condition = folder_name.split("-")[3]
if condition == "Control":
condition = "control"
... |
1a47191c9c30820b801fee9ea5f5754405a607836e21e24051d3e54c297292b5 | Python | 5,855 | 152 | from PyQt5.QtWidgets import QApplication, QMainWindow, QFileDialog, QMessageBox, QLineEdit
from PyQt5.QtCore import pyqtSlot
from .run_processing_mw import Ui_MainWindow
import pyqtgraph as pg
from oct.reconstruct import *
from oct.post import *
from oct.load import *
from oct.view.ofd import *
import logging
class ... |
aa4fcbe8a987a25b1eca47eaaf40670ba24b534f5bb92beaa32a698b9f3de92d | Python | 5,857 | 142 | #!/usr/bin/env python
# interface libraries
from tkinter import *
from tkinter import filedialog
from tkinter.ttk import *
# my files
from mainbody import mainbody
from getboundary import getboundary
def makeform(root, fields):
entries = {}
rows = []
for field in fields:
row = Frame(root)
... |
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