sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
5e0e8ab20d9fe5450bf2f2ba4a698525914659a3ab8ea01803b64c0c3f1ca881 | Python | 2,816 | 85 | #!/usr/bin/env python3
import os
import pandas as pd
from nilearn import masking as nmask
from nilearn import image as nimg
# ------------------------------------------------------------------
# Create group mask across subjects for Emofilm movie data
# using preprocessed BOLD files
# ---------------------------------... |
89661fcf92c4daf9a87e5350bde8e44517cab050fb25c749be4d4ce8fc3e342c | Python | 2,816 | 72 | #! /usr/bin/env python
from lab.parser import Parser
parser = Parser()
parser.add_pattern('ms_final_size', 'Final transition system size: (\d+)', required=False, type=int)
parser.add_pattern('ms_construction_time', 'Done initializing merge-and-shrink heuristic \[(.+)s\]', required=False, type=float)
parser.add_patter... |
8af8d591fa8ea2a28f8365eee1c91535ca053ce3cb0421981b16c9e805fad2d0 | Python | 2,816 | 93 | #!/usr/bin/env python3
import os
import pandas as pd
import math
# ------------------------------------------------------------------
# Create participant-wise movie timing files for Emofilm
# based on events.tsv files
# Onset and Offset are saved as TR indices
# -------------------------------------------------------... |
c7f961ee72e784cc64d99f7fb1a09e4d197413bfb569af0ff07749f08b1e65d7 | Python | 2,816 | 87 | import torch
import numpy as np
import pandas as pd
import scanpy as sc
import torch.nn.functional as F
from easydl import *
from anndata import AnnData
from torch import nn, einsum
from scipy.stats import pearsonr
from torch.autograd import Function
from torch.autograd.variable import *
from einops import rearrange, r... |
dee2d9f166066b20974981788cda323150d231df7ccaac5d96cddbc6da370b51 | Python | 2,816 | 60 | #!/usr/bin/env python
## this script creates dataframes from the full distance matrices for Features (pre- and post-session),
## and Naming (pre- and post-session) and saves them to a new CSV file
## The dataframes contain the distances values for each pair of subjects.
import pandas as pd
from pathlib import Path
# ... |
6004364100b54df2ec9cb5e52f5df286c713b1874f29eecfa2815969d2d2fe98 | Python | 2,817 | 73 | # coding=utf-8
# Copyright 2026 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... |
a956373501b56d01b87b8f5368b32a66d7e834264f21117c5bc5520219492070 | Python | 2,817 | 84 | ################################################################################
# Import, Set up MPI Variables, Load Necessary Files
################################################################################
import os
from os.path import join
import sys
import matplotlib
import matplotlib.pyplot as plt
from matp... |
16eb05ea49eb14e260e74d843de749891130aa6f30ad9f4e0665fe3be2c189c6 | Python | 2,818 | 84 | # Node-group asset "Segment ID" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# _build_group() is the source of truth: the docstring, __init__ and accessors are regenerated from it on the next dump.
from typing import TYPE_CHECKING
fr... |
edd86a1729216d90aa1af57a3239b954746c7a60cde32f0b419193729fa1433f | Python | 2,818 | 77 | """Visualizes the time of the day when the HRV and RR are mostly missing
Parameters
----------
variable : str
name of the variable to preprocess. It could be heart rate (hr),
temperature (temperature), electrodermal activity (electrodermal)
path : str
path where the raw data i... |
01e5cfdf20ccadec8c477f538e8495db47433b93f62e2e338996180d0ede9298 | Python | 2,819 | 83 | #!/usr/bin/env python3
# Quick implementation of Hierarchical Clustering Analysis,
# for comparison with rootlets hPCA results,
# using input data created by hPCA.py script.
import os
import numpy as np
from numpy.linalg import norm
import seaborn as sns
from scipy.stats import zscore
from scipy.cluster.hierarchy ... |
6dfa29613b274e8ca0244181a3e961617e8efe2f6e8c1ebe0d1abdd4edb9e197 | Python | 2,819 | 113 | from __future__ import annotations
import pytest
dask = pytest.importorskip("dask")
pytest.importorskip("distributed")
from dask.distributed import get_client
from quacc import flow, job, subflow
client = get_client()
def test_dask_decorators(tmp_path, monkeypatch):
monkeypatch.chdir(tmp_path)
@job
... |
a4a79c654b43921bcab8d050fcddb37addd2b7b99f18564459c22c840ecbf98f | Python | 2,819 | 83 | import os
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Circle
from collections import defaultdict
import matplotlib.colors as colors
import cv2
import random
def scatter_plot(dir_paths, num_files=500, alpha=0.6):
fig, ax = plt.subplots()
# Dictionary mappin... |
aadcb8c2fdaca48595b73b183a3a8b96ace183306984a91e810cecea84e3debd | Python | 2,819 | 92 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jul 21 12:48:57 2023
@author: emma
data generator for bias unlearning -- returns 3 items (X, y, b) -- we manually one-hot y and b in the unlearning code
"""
from numpy.random import seed
seed(1)
import tensorflow as tf
tf.random.set_seed(1)
import... |
2dcc45b3d1ae96c0e577cfe4729e4bc8d17160e3ea93be61450f5c1571720cc4 | Python | 2,820 | 81 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterP... |
2f88aa53fb252043164f65d4d7c9f7839ba0136fa347aa5447dae59f524b2cb8 | Python | 2,820 | 81 | # Librairies
import os
import sys
code_path = os.path.split(os.path.split(os.getcwd())[0])[0]
sys.path.append(code_path)
import numpy as np
import argparse
from setting import *
from utils import *
# Arguments
argParser = argparse.ArgumentParser()
argParser.add_argument("-n", "--name", type=str, help="dataset name")
... |
4d71b53d99b172c3ebb9bd5120a02597af0117bcaa24d33254825bee32603fd6 | Python | 2,820 | 91 | """Testing module geom."""
import os
import numpy as np
from numpy.testing import assert_array_almost_equal
from treem import Morph
from treem.utils.geom import (
fibonacci_sphere,
repair_branch,
rotation,
rotation_matrix,
sample,
)
def test_fibonacci_sphere():
"""Tests fibonacci_sphere."""... |
a83051991217dbe7bec656dff933ca58f73b7cf4835c44ed856edb487de22734 | Python | 2,820 | 64 | # coding=utf-8
# Copyright 2026 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... |
b768b6438dacd56cc2a030511259ba4c32a01aadb36b96ca8d099a0bddd134ba | Python | 2,820 | 83 | from .utils import AtomsDataset, register_dataset
from typing import List, Optional, Dict, Union, Tuple
import torch
PtDict = Tuple[
Dict[str, torch.Tensor],
Dict[str, torch.Tensor],
Dict[str, Union[float, int]],
]
@register_dataset("pt")
class PtData(AtomsDataset):
def __init__(
self,
... |
195ae1bbfe97fa9a3ace816ead1e1cd019956004ccc5cc40b4b9effa21819ec0 | Python | 2,821 | 79 | import unittest
import numpy as np
from neurolib.utils.parameterSpace import ParameterSpace
class TestParameterSpace(unittest.TestCase):
def test_parameterspace_init(self):
# init from list
_ = ParameterSpace(["a", "b"], [[3], [3]])
# init from dict
_ = ParameterSpace({"a": [1, 2]... |
8e66de4a2a099404d2971d3dee9b5c2519741ba747ce9db1fdfc8e70a618e991 | Python | 2,821 | 112 | """
IMPORTANT: it's just draft
"""
# built-in
from functools import reduce
from typing import Any
# app
from .base import Base as _Base, BaseSimilarity as _BaseSimilarity
try:
# external
import numpy
except ImportError:
numpy = None # type: ignore[assignment]
class Chebyshev(_Base):
def _numpy(sel... |
bafe5394bd082f984146a1e2e862b8eb0e82cff78579e3f87498a94c291e25f0 | Python | 2,821 | 72 | import unittest
import os
import pandas as pd
import sys
sys.path.append(os.path.dirname(os.path.realpath(__file__)) + "/../../src")
from hornet.model import predict
class TestPredictFunction(unittest.TestCase):
def setUp(self):
self.path = ".output_test_pred"
self.input_path = ".input_test_pred"
... |
364a361c6fb81bb95f31ffbf5f7395ea003374e91f725d9bf443cea3c8b3b143 | Python | 2,822 | 122 | from __future__ import annotations
import warnings
import pytest
jf = pytest.importorskip("jobflow")
from quacc import flow, job, subflow
def test_jobflow_decorators(tmp_path, monkeypatch):
monkeypatch.chdir(tmp_path)
@job
def add(a, b):
return a + b
@job
def mult(a, b):
retu... |
20582a8d873e585d5538c6efc250cfb057778aaa37682144f8ea350ee82f87b4 | Python | 2,823 | 78 | # set QT_API environment variable
import os
os.environ["QT_API"] = "pyqt5"
import qtpy
# qt libraries
from qtpy.QtCore import *
from qtpy.QtWidgets import *
from qtpy.QtGui import *
# app specific libraries
import control.widgets as widgets
import control.camera as camera
import control.core as core
import control.m... |
9b7f2a4b04aaa7026c6ea6133db80cabe0b0a72029e1187fe80ca1588088eabb | Python | 2,823 | 91 | import random
import sys
import unittest
import neurolib.optimize.evolution.deapUtils as du
import neurolib.optimize.evolution.evolutionaryUtils as eu
import numpy as np
import pytest
from neurolib.optimize.evolution import Evolution
from neurolib.utils.parameterSpace import ParameterSpace
class TestEvolutinUtils(un... |
52c68a18118214ed2d1d02516b7451b1aff3297cc3a142ff4a563d48e9146e89 | Python | 2,824 | 74 | from __future__ import absolute_import, division, print_function, unicode_literals
import argparse
import logging
import os
import sys
import tensorflow as tf
import matplotlib.pylab as plt
from tensorflow.keras import layers
from tensorflow.keras import models
import numpy as np
import PIL.Image as Image
import glob
... |
80970eeb7a63f0165052e332e705d9ddb7cb98d2a4fe5b76fc3928782276de8b | Python | 2,825 | 75 | from typing import Tuple, Union
import numpy as np
import torch
import torch.distributed as dist
import yacs.config
from torch.utils.data import DataLoader
from pytorch_image_classification import create_collator
from pytorch_image_classification.datasets import create_dataset
def worker_init_fn(worker_id: int) ->... |
971712232ec3820e9a712be84267d2a32dda3ace5cd06fdfe5ddc5c2f62a1e1a | Python | 2,825 | 117 | import sys; import os
sys.path.insert(0, os.path.abspath('../eyewire'))
import mesh
from volume import *
from shove import Shove
from tqdm import *
import pickle
def _dump(object, filename):
pickle.dump( object , open( "./{}.p".format(filename) , "wb" ) )
def _load(filename):
try:
return pickle.load... |
a0ed7d89a65a7281ec24654776b9e39270f84b5ba8d37223ff5b4651f6874f55 | Python | 2,825 | 74 | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import pymc as pm
import aesara.tensor as tt
import warnings
import pdb
warnings.filterwarnings("ignore", category=FutureWarning)
import arviz as az
from scipy.special import expit
from matplotlib import gridspec
from IPython.d... |
0aab551040041ac9531f7c14e9e14da48b8e425aaa315029fd9baf770294a10c | Python | 2,826 | 103 | #!/usr/bin/env python3
import os
import pandas as pd
import numpy as np
from sklearn.metrics import pairwise_distances
# ------------------------------------------------------------------
# paths
# ------------------------------------------------------------------
projpath = '/project/3011157.03/Simon/proj_2022_CABB_... |
3f87e95747fcd289c5199ee53a04bdb4ddfac54765a4fcda0eebe2dbbfe9b6e0 | Python | 2,827 | 88 | from wsilearn.utils.cool_utils import is_string
def is_string_int(value):
try:
int(value)
return True
except:
return False
def is_string_float(string):
""" checks if the string is a float """
try:
float(string)
return True
except:
return False
def... |
b8688967f7b8ef47cc6a021dc68a5155009948c03cb42a9734b47ca66718ab09 | Python | 2,827 | 71 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from common_setup import IssueConfig, IssueExperiment, is_test_run
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue696-base", "issue696-v1"]
CONFIGS = [
IssueConfig(
... |
17c1453b1c4128f1762e3f2f9040162d97b4c7e88fe9665b8c128993e78dbaca | Python | 2,828 | 78 | import cocotb
import pytest
from cocotb.triggers import Timer
import elasticai.creator_plugins.adders as adders
from elasticai.creator.arithmetic import int_arithmetic
from elasticai.creator.testing import CocotbTestFixture, eai_testbench
from elasticai.creator_plugins.multipliers.utils import (
generate_mult_test... |
3db7a5cf6b6fdfa2f2e19c6c4df9bf0b03797be8a79f4dafb3f530ec298b193b | Python | 2,828 | 87 | # Written by Minh Nguyen and CBIG under MIT license:
# https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
import math
import torch
import torch.nn as nn
class MinimalRNNCell(nn.Module):
"""A Minimal RNN cell .
Args:
input_size: The number of expected features in the input `x`
hidden_s... |
400b4334805935434ee3f11c2a5e8556038be546fd435cf2a7d44251edb7d231 | Python | 2,828 | 78 | import os
from typing import List, Tuple
import torch
from constants import N_ITEMS
from src.models import get_regressor, get_classifier
def get_classifiers_checkpoints(trained_classifiers_root, max_ckpts=-1) -> Tuple[List[int], List[str]]:
checkpoints = []
items = []
for i in range(1, N_ITEMS + 1):
... |
59ed0ddf75f82dfe203dc24a636dd4764facb214b0cba69b259e6f8a5db8906f | Python | 2,828 | 65 | from __future__ import print_function,division
from typing import Any, Dict, Tuple, Union
import numpy as np
import pandas as pd
from PIL import Image
from topaz.utils.picks import as_mask
def coordinates_table_to_dict(coords:pd.DataFrame, dims:int=2) -> Union[Dict[str,np.ndarray], Dict[Any,Dict[str,np.ndarray]]]:
... |
ed2fba74a8b4754bab990cc038937d06f49a9e16b38c42fcff0d8b89adaa6227 | Python | 2,828 | 60 | #!/usr/bin/env python
## this script creates dataframes from the full distance matrices for Features (pre- and post-session),
## and Naming (pre- and post-session) and saves them to a new CSV file
## The dataframes contain the distances values for each pair of subjects.
import pandas as pd
from pathlib import Path
# ... |
2b1e2151f58fa19a4488aa854157c3bc64d51e052d596afa84a32d005c4f2f0c | Python | 2,829 | 90 | from __future__ import print_function
from setuptools import setup
from setuptools.command.test import test as TestCommand
import codecs
import os
import sys
import re
here = os.path.abspath(os.path.dirname(__file__))
def read(*parts):
# intentionally *not* adding an encoding option to open
retu... |
83a0276d8819262e91e5aebb5dfc2df412c8b64208c640c23c663788092e4f46 | Python | 2,829 | 100 | # coding=utf-8
# Copyright 2026 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... |
b907b25e9b985585c7c63af9eacce52bf8d45e56ab08871e963f6a7fc05c12e9 | Python | 2,829 | 83 | # flake8: noqa
# There's no way to ignore "F401 '...' imported but unused" warnings in this
# module, but to preserve other warnings. So, don't check this module at all.
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use thi... |
0edff45bdfa12efd9f89d82d7d50744fa9c15a413c99c2be7b3119261dcfd393 | Python | 2,830 | 74 | """
Created on Sat Mar 26 14:24:27 2022
@author: Haotian Teng
"""
import h5py
from xron.utils import seq_op
import numpy as np
from umap import UMAP
from sklearn.manifold import TSNE
from matplotlib import pyplot as plt
import matplotlib.cm as cm
from typing import List
fast5_f = "/home/heavens/Documents/FAQ... |
de194a24f66c418d496ccf0e3ca519ebdbc83d48106ee1e0ae1f6612c6d4da52 | Python | 2,830 | 105 | import random
import pregex as pre
import math
assert(pre.create("f(a|o)*") == pre.Concat([pre.String("f"), pre.KleeneStar(pre.Alt([pre.String("a"), pre.String("o")]))]))
assert(pre.create("fa|o*") == pre.Concat([pre.String("f"), pre.Alt([pre.String("a"), pre.KleeneStar(pre.String("o"))])]))
assert(pre.create("(f.*)+"... |
f985b9bb1f1e1a42a9a202f4aa047afa5bddcee36a363d9257e669a1bf066e79 | Python | 2,831 | 78 | """`--affine_init` must reject a degenerate ants.affine_initializer result.
``ants.affine_initializer`` runs an UNSEEDED internal rotation search, so it is
nondeterministic and can occasionally return a near-singular or grossly
over-scaled affine. Seeding SyN with one silently corrupts the registration:
SyN's loc... |
3d7347d8220a11f93617df45985fbf3fdad188b588e560f41f0b7e4bbcec985a | Python | 2,832 | 56 | ############################################
# REFLECT ontologies - DO, BTO, STITCH, GO #
############################################
def parser(files, filters, qtype = None):
"""
Parses and extracts relevant data from REFLECT ontologies: Disease Ontology, Tissues, STITCH and \
Gene Ontology databases.
... |
7e89e07b89e4e274368db1da09a33240d07cab7917856798bf2d0f646fd334aa | Python | 2,832 | 63 | import torch
import torch.nn as nn
import torch.nn.functional as F
class LSTM(nn.Module):
r'''
A simple but effective long-short term memory (LSTM) network structure from the book of Zhang et al. For more details, please refer to the following information.
- Book: Zhang X, Yao L. Deep Learning for EEG-Ba... |
f12ab0277e77a45ff6936b338e88e2573dfcebc0e2e5e2e258b4637f4f59d331 | Python | 2,832 | 73 | import argparse
import numpy as np
import os
import pandas as pd
import sys
from tabulate import tabulate
from constants import *
from src.training.train_utils import Logger
from src.models import get_regressor, get_regressor_v2
from src.evaluate import RegressionEvaluator
from src.evaluate.utils import *
# setup ar... |
326c2a9e7176351fbe38a80e49e6bc8a459967b878c9e7a0d4d6f9bd271d83bb | Python | 2,833 | 97 | """
This Python module provides just the code from the 'conceptnet5' module that
you need to represent terms, possibly with multiple words, as ConceptNet URIs.
It depends on 'wordfreq', a Python 3 library, so it can tokenize multilingual
text consistently: https://pypi.org/project/wordfreq/
Example:
>>> standardized... |
77929dbf69ea6e739a3ec7822960ceb88cef4636c962e73d2458a7d0e085d370 | Python | 2,834 | 80 | from __future__ import print_function
from . import conditions
class Axiom(object):
def __init__(self, name, parameters, num_external_parameters, condition):
# For an explanation of num_external_parameters, see the
# related Action class. Note that num_external_parameters
# always equals ... |
873ab88816283cf52a142449366ffdcd91ca23f7a83cc41b60d861b3c990b4d5 | Python | 2,834 | 43 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
import common_setup
REVS = ["issue548-base", "issue548-v1"]
LIMITS = {"search_time": 1800}
SUITE = suites.suite_optimal_with_ipc11()
B_CONFIGS = {
'rl-b50k': ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_orde... |
7c95718f81fd319b83a587cf64d91c36a1a0838a71bd93ede07390f611a31188 | Python | 2,835 | 66 | """Affine -> the four anatomical edge letters of a displayed slice.
The preview draws a slice with array axis 1 vertical and axis 2 horizontal
(``_show_array`` uses ``axes={"t": 0, "x": 2, "y": 1}``; a 2D slice reaches the
same mapping through ``prep_slice_for_pg``'s transpose), and ``invertY`` puts
row 0 at the ... |
15ae77f449aea1af5c4ebb8b46c4d446dcf48e27712e9b5ab4473b832f75d23d | Python | 2,836 | 79 | # ruff: noqa
# Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup ----------------------------------------------------------... |
a3a47e0b63eba2cae4eb6b712fd0a725f209a229f1c5f2d19bd557fca3fb5062 | Python | 2,836 | 88 | # -*- coding: utf-8 -*-
# Copyright (c) 2012 Giorgos Verigakis <verigak@gmail.com>
#
# Permission to use, copy, modify, and distribute this software for any
# purpose with or without fee is hereby granted, provided that the above
# copyright notice and this permission notice appear in all copies.
#
# THE SOFTWARE IS P... |
dd214a67074aa6232efd0f177ab745fa345d764d8d28a8c6f965ef17fbfbb1e4 | Python | 2,836 | 102 | from __future__ import annotations
import gzip
import os
import pytest
from quacc.schemas.vasp import bader_runner, chargemol_runner
def mock_bader_analysis(*args, **kwargs):
return {
"min_dist": [1.0],
"charge": [1.0],
"atomic_volume": [1.0],
"vacuum_charge": 1.0,
"vacu... |
1243a874c6128362a881ef85eba0d4c01727a424a0a4f4f7ae40061f777807c9 | Python | 2,837 | 110 | """
Cog SDK Coder system for custom type encoding/decoding.
This module provides the Coder base class for defining custom type
serialization between Python types and JSON.
"""
from abc import abstractmethod
from typing import Any, Dict, Optional, Set, Type
class Coder:
"""
Base class for custom type encoder... |
454d1a8bdac4ee02e73c1a70b37cd757eb252129e74e46ac86d37ec3ba1f4ce1 | Python | 2,838 | 36 | """BRAKES_OR_BIG.py 2026-10-05. Pre-registered: 04-NOTES/PREREG-2026-10-05e-BRAKES-OR-BIG.md (sha in .sha256 next to it).
Are dominant inputs inhibitory per se, or just giant one-of-a-kind cells that happen to be inhibitory? Male CNS v1.0.
usage: python BRAKES_OR_BIG.py -> 06-OUTPUT/brakes_or_big.txt"""
import os
imp... |
65fbb21bac78d62b98ee17b04413cf0b6fbb5d9806ab18e770661496979fd2aa | Python | 2,838 | 92 | import tensorflow as tf
from tensorflow.keras.layers import Input, Dense
from tensorflow.keras.models import Model
import tensorflow.keras.callbacks
import os
import numpy as np
import tensorflow.keras.backend as K
from utils import onehot_test_label
class LossHistory(tensorflow.keras.callbacks.Callback):
def on... |
88b682c00eb3330f597bf9991b8e3161fcf52e746329fbb7fe3252bfd5db6309 | Python | 2,838 | 88 | import torch
from torch import nn
from typing import List, Dict, Callable, Any, Optional, Union
from .equivalent import TensorLinear, ElementTensorLinear
from .activate import TensorActivateDict
from ..utils import EnvPara
__all__ = ["ReadoutLayer"]
class ReadoutMLP(nn.Module):
def __init__(
self,
... |
15e5620eb50834865caf9d393c0c6f5380235f3d5ab048802ecf465cc87045a1 | Python | 2,839 | 76 | # Copyright Jonathan Hartley 2013. BSD 3-Clause license, see LICENSE file.
import sys
from unittest import TestCase, main
from ..ansi import Back, Fore, Style
from ..ansitowin32 import AnsiToWin32
stdout_orig = sys.stdout
stderr_orig = sys.stderr
class AnsiTest(TestCase):
def setUp(self):
# sanity chec... |
dee5e6142251e362d8d50e4ab1cf2ac9cea840a8314b74724c7b1d79cc57f65d | Python | 2,839 | 71 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 11 19:55:38 2022
@author: haotian
"""
import os
import sys
import toml
import numpy as np
import argparse
def merge(args):
fs = args.fs
keys = args.keys
collections = {x+'.npy':[] for x in keys}
for f_i,sub_f in enumerate(fs):
... |
d4b32b3559fd038e48ff93220b1b30f7d592a243755e3e0748f7367de3652be4 | Python | 2,840 | 99 | """
Optuna example that optimizes a configuration for hand-written digits dataset using
skimage.
In this example, we optimize a classifier configuration for hand-written digits dataset.
We optimize parameters of local_binary_pattern function in skimage and the
choice of distance metric classes.
"""
import numpy as n... |
47a4302af19b14f772dc093ad3da43fddac2ddd76512efe400d47cbbbe780f97 | Python | 2,841 | 104 | from datetime import datetime
from numpy import (append,
cumsum,
where,
ndarray,
)
DEFAULT_DATETIME = datetime(2000, 1, 1)
def decode(s):
return s.decode('utf-8', errors='replace')
def _select_blocks(blocks, begsam, endsam):
"""Co... |
e2a46b22d4532de94893f9b01ba996be12a4d3822a77eb947e41fe9064542504 | Python | 2,841 | 83 | """
oxasl.gui.structure_tab.py
Copyright (c) 2008 University of Nottingham
"""
import os
import wx
from oxasl.gui.widgets import TabPage, OptionError
class StructureTab(TabPage):
"""
Tab page containing options for providing structural data
"""
EXISTING_FSLANAT = 0
NEW_FSLANAT = 1
INDEP_STR... |
7ce54f6b73eab8bafbc505c8209c2efe3ae4f072e84e9fc07afb9f06a55bd4ee | Python | 2,842 | 76 | # Plots TVAT surfaces and polynomial regressions from Fig 5A-B
from os.path import join
from get_paths import *
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
import pickle
from colors_paultol import cmap_iridescent
if __name__ == "__main__":
... |
d179caad943174e0103b9ea88ff195d6847ed1416d6917b9ae8ab7388ee5a497 | Python | 2,843 | 108 | import autograd.numpy as np
import autograd.numpy.random as npr
from autograd import grad, make_vjp
from autograd.misc import const_graph, flatten
from autograd.test_util import scalar_close
from autograd.tracer import primitive
def test_const_graph():
L = []
def foo(x, y):
L.append(None)
ret... |
f336ee096c08b0404a2f9f9379a33c8b72f22b2b23f90b9d57ff1c5a23edf1a6 | Python | 2,843 | 56 | #!/usr/bin/env python
import os
import pandas as pd
import numpy as np
from nltools.data import Brain_Data, Adjacency
from nltools.mask import expand_mask
from sklearn.metrics import pairwise_distances
## location of main project directory on HPC
projpath = '/project/3011157.03/Simon/proj_2022_CABB_movie/'
print('Th... |
026096893d40c80c0be6a48c7d0ff4df367c5c1688c62e4ee11f41f0a8fd98ed | Python | 2,844 | 93 | import click
import pandas as pd
from lib.sequence import SeqRegressionDataLoader1D
# options
@click.command()
@click.option('--test',
'test_file',
required=True,
type=click.Path(exists=True, readable=True),
help='Test sequences')
@click.option('--model',
... |
0147e385c33270003ee5e749ef484365e3fcbc75abd3ab24e95541dffa0b900e | Python | 2,845 | 84 | import torch
from typing import Callable, List
class Table:
def __init__(self, col_names: List, row_names: List):
self.col_names = col_names
self.row_names = row_names
self.content = {
col_name: {
row_name: None
for row_name in row_names
... |
2af99dc4a60d0e879a2a9cf0af6f784bf5491ce6271b608dd0178eda6ca0fcfe | Python | 2,845 | 84 | # coding=utf-8
# Copyright 2026 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... |
60d327c77e31cfe9d9d2edd53708e64ed354fd27ae1fdb2ad4e84a0f706d9f6d | Python | 2,846 | 101 | """
Tests for the wbi_backoff decorator: retry on transient HTTP/JSON failures,
give up on permanent ones.
"""
import pytest
import requests
import ujson
from wikibaseintegrator.wbi_backoff import wbi_backoff, wbi_backoff_backoff_hdlr
from wikibaseintegrator.wbi_config import config
@pytest.fixture(autouse=True)
def... |
88bbeb8f381ac715dff55863d4d4c09300d1a0844b66f41881b32a0b2993864f | Python | 2,846 | 86 | from collections.abc import Callable
from elasticai.creator.file_generation.savable import Path
from elasticai.creator.file_generation.template import (
InProjectTemplate,
module_to_package,
)
from elasticai.creator.vhdl.auto_wire_protocols.port_definitions import create_port
from elasticai.creator.vhdl.code_g... |
a6e5e48499e3b7d691b431532eb377942f9712d42e80c2e1886fbc02c79cea16 | Python | 2,847 | 85 | import numpy as np
import keras.backend as K
def dice(y_true, y_pred):
#computes the dice score on two tensors
sum_p=K.sum(y_pred,axis=0)
sum_r=K.sum(y_true,axis=0)
sum_pr=K.sum(y_true * y_pred,axis=0)
dice_numerator =2*sum_pr
dice_denominator =sum_r+sum_p
dice_score =(dice_nu... |
ba161aa1314ba441f12aaa6daacb035ea268684def63dadf89203d42f60c6d78 | Python | 2,847 | 90 | import json
import os
import pandas as pd
from argparse import ArgumentParser
def read_files(path_data):
"""
Load all functional files into Nifti format
Parameters
----------
path_data: string
path containing the functional images
Returns
----------
files_h... |
e110efac3fe924097fb4bd4a2c64c04fefac8707751868d79aae386e09d3e648 | Python | 2,848 | 81 | from pathlib import Path
import numpy.testing as npt
import pytest
from pycudadecon import RLContext, decon, rl_cleanup, rl_decon, rl_init
from pycudadecon.util import imread
ATOL = 0.05 # tolerance for np.allclose
DATA = Path(__file__).parent / "test_data"
PSF_PATH = str(DATA / "psf.tif")
OTF_PATH = str(DATA / "o... |
03cdcef8355c43f580f8569d41592d7de0ac0625062680d86cc2b9c4c5b65491 | Python | 2,849 | 98 | from math import ceil
import cocotb
import pytest
from cocotb.clock import Clock
from cocotb.triggers import RisingEdge
from elasticai.creator.testing.cocotb_pytest import (
CocotbTestFixture,
eai_testbench,
)
from elasticai.creator.testing.cocotb_stream import (
ResetControl as ClockReset,
)
from elastic... |
04f4f3382e4ebff486fb0229daac0941f48a721ac2bad7a53e4755096963d1e4 | Python | 2,849 | 72 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Dec 22 12:22:46 2023
@author: daltonm
"""
import h5py
import dill
from pathlib import Path
from importlib import sys
import pandas as pd
import numpy as np
# sys.path.insert(0, '/project/nicho/projects/marmosets/code_database/analysis/trajectory_encod... |
94c8096085cfae2c93d5ca7c4ed5aefe46f234761b56c012f25824430ff2d7f8 | Python | 2,849 | 80 | # coding=utf-8
# Copyright 2026 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... |
d41b72378a9c826f42b8a4a6fc5a701222da074b552783bae8a30ecb4a89a1ee | Python | 2,849 | 93 | # coding=utf-8
# Copyright 2026 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... |
1c81b492448c6e713fed8d8e1dddddd8b2c1e04f4ca0c12388c67be351d05548 | Python | 2,850 | 90 | from copy import deepcopy
from unittest import TestCase
import numpy as np
import matplotlib.pyplot as plt
from numpy.fft import fftfreq, fftshift
from scipy.fftpack import fft
from scipy.ndimage import convolve1d
from scipy.signal import welch
from scipy import signal
from soundsig.signal import correlation_function,... |
a0a33196715a6da272464af3c6a5056d185c25821f2f0cd958752cdd50ac3285 | Python | 2,850 | 87 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
1c51f6079b62eec0d81a37b327fcc737a35de04716f2261c3ff2e86a7d374441 | Python | 2,851 | 87 | from typing import Any
import torch
import torch.nn.functional as F
from torch import nn, Generator
from ..prixfixe import FinalLayersBlock
from .utils import initialize_weights
class AutosomeFinalLayersBlock(FinalLayersBlock):
def __init__(self, in_channels=64, seqsize = 230):
super(AutosomeFinalLayersB... |
444e09017ab2e411fc389d8beeaad4bc29f9b77b5f5191fe0373c37e6a106735 | Python | 2,851 | 62 | import numpy as np
import pandas as pd
import scipy.io
import os
import argparse
def get_parser(parser=None):
if parser == None:
parser = argparse.ArgumentParser()
parser.add_argument("-i", "--input", type=str, help="Path to the input file or the 10X directory.")
parser.add_argument("-o", "--output... |
11ebb45f83bb6af887edbba125d5200ba78926bcfdbbf061784ed38378c620a2 | Python | 2,852 | 123 | import abc
import numpy as np
import torch
from diff_frech_mean.frechetmean.utils import EPS
class Manifold(metaclass=abc.ABCMeta):
@abc.abstractmethod
def zero(self, *shape):
pass
@abc.abstractmethod
def zero_like(self, x):
pass
@abc.abstractmethod
def zero_tan(self, *sha... |
fb8e3b9203d54e36f36e6607ab54dd684fe477ad0d840853c1cc8935d6b24fdb | Python | 2,853 | 88 | # coding=utf-8
# Copyright 2026 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... |
15e85fc194effb97027ec6dc325be55249b7c59d1c461b1ebfa5d5a667931787 | Python | 2,854 | 91 | # Copyright (c) 2012 Giorgos Verigakis <verigak@gmail.com>
#
# Permission to use, copy, modify, and distribute this software for any
# purpose with or without fee is hereby granted, provided that the above
# copyright notice and this permission notice appear in all copies.
#
# THE SOFTWARE IS PROVIDED "AS IS" AND THE A... |
236271afe7686687b0ae402720594e5570cd24e739da727c71493d40ac11c746 | Python | 2,854 | 89 | ### Modules
# basic
import pysam, numba, h5py
from Bio.Seq import Seq
from numba.typed import List
# dask
import dask
import dask.bag as db
from dask.distributed import Client, LocalCluster
from dask.diagnostics import ProgressBar
from .ResquiggleUtils import *
def ViterbiRead(dset, read_id):
### from hdf5
t... |
290a8f8f2e7f1ef6490330b00a40965d6d7ceefb888bb16953f5fbf36106b127 | Python | 2,854 | 88 | #!/usr/bin/env python3
import os
import pandas as pd
from nltools.data import Brain_Data
from nltools.mask import expand_mask
from nilearn.image import index_img
# ------------------------------------------------------------------
# paths
# ------------------------------------------------------------------
projpath =... |
b884fbab7c9b1b6ff6e2c6b1a9963a0bd39e226ff519ed7bf173990ddd2627c4 | Python | 2,854 | 89 | import inspect
from typing import Any, Callable, Dict, Optional, Text, Union, Iterable
import numpy as np
import tensorflow.experimental.numpy as tnp
import tensorflow as tf
#tnp.experimental_enable_numpy_behavior(prefer_float32=True)
from tensorflow.keras import layers as kl
'''
Genformer helper functions
'''
@tf.... |
25a43fbdaebfe3776ed0fff438652b6d2f017c22d17272291ee26dbba6fdd25b | Python | 2,855 | 111 | import json
from collections import Counter
import math
import numpy as np
import pandas as pd
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import DataLoader
from torch import Generator
from pathlib import Path
CODES: dict[str, int] = {
"A": 0,
"T": 3,
"G": 1,
... |
b8fd8e21b7bada14adf7aaf40a3045113d7598af747a7a841769478d69593212 | Python | 2,855 | 55 | """
Created on Wed Jul 20 00:42:56 2022
This script is used to evaluate the methylation ratio of the basecalled reads for partially methylated IVT dataset.
@author: Haotian Teng
"""
import os
import pandas as pd
from tqdm import tqdm
import numpy as np
from xron.utils.fastIO import read_fastqs
import seaborn as sns
fro... |
fa81c8132e0acbd68b417a1c5db63403a0d7e8762e1eeef1b2ff57986289872e | Python | 2,855 | 95 | from __future__ import annotations
from pathlib import Path
from shutil import which
import pytest
from ase.build import bulk
from numpy.testing import assert_allclose
from quacc.recipes.espresso.bands import bands_flow
from quacc.utils.files import copy_decompress_files
pytestmark = pytest.mark.skipif(
which("... |
320ac54cd9072e30426dd4a22ccc841f54f0bbb8b178af8e1f051589d15a74b0 | Python | 2,856 | 74 | # -*- coding: utf-8 -*-
"""
Spyder Editor
This is a temporary script file.
"""
import os
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import rcParams
import toml
rcParams['figure.dpi'] = 300
plt.rcParams["font.family"] = "Arial"
#make font bold
plt.rcParams["font.weight"] = "bold"
BRIDGE_F=o... |
55797b034b084de47b27cbcd8401070050294cc17b5ef96ffc7f566ce5489cb9 | Python | 2,856 | 77 | #
# # -*- coding: utf-8 -*-
from keras.models import load_model
import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
import tensorflow as tf
tf.reset_default_graph() # Reset default graph
tf.keras.backend.clear_ses... |
bcd015d3d482ade4ff2ce42d0dd97a24c3dfab80d025c1cdf5bb46ae7ca0792d | Python | 2,856 | 94 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Process MRI files:
- convert DICOM to NII
- Call to `recon-all`
Example
-------
To run `recon-all` on all subjects data using 8 parallel cpu cores (one per
subject):
``python mri.... |
e4922c03c58a1c5b5a2c5c3414ee7e137d57f03fce82c611d0f4abe6df81c327 | Python | 2,856 | 83 | """Computes the number of missing datapoints
Parameters
----------
variable : str
name of the variable to preprocess. It could be heart rate (hr),
temperature (temperature), electrodermal activity (electrodermal)
path : str
path where the raw data is stored
savefile : str
... |
3ac90efc25bee9ab7ae202818e1fc86eccce852a12c27ccb0d5f71868ae88633 | Python | 2,858 | 102 | from typing import cast
import pytest
import torch
from elasticai.creator.arithmetic import (
FxpArithmetic,
FxpParams,
)
from elasticai.creator.nn.fixed_point.fxp_round_cut import (
CutToFixedPoint,
FloorToFixedPoint,
RoundToFixedPoint,
)
from tests.tensor_test_case import assertTensorEqual
def... |
685a679dcf44361a2e426472232cde60b81456e2dab355a78afde0b0e7556f7d | Python | 2,859 | 94 | # coding=utf-8
# Copyright 2026 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... |
aab136938dc0dfde210903cf8d0124c296b546ebbb0fac30fcebbee638a34fe1 | Python | 2,859 | 80 | __author__ = "Zoe Wefers"
__credits__ = ["Ryan Huang"]
__version__ = "1.0.0"
__maintainer__ = "Zoe Wefers"
__email__ = "zoe.wefers@mail.mcgill.ca"
"""Purpose: Object definitions for various cellular compartments."""
import ui
class Dendrite:
def __init__(self, img_name):
self.img_name = img_name
... |
787788600dc311a227721a903b2aeb5adfe565eff68da38a32a44813a1295e57 | Python | 2,860 | 33 | """posthoc_spiking_weights_line_2026-10-03.py — POST HOC (after SPIKING_WEIGHTS returned NO: with weights from one spiking
baseline the laboratory prior already sits at 0.449, so the frozen 0.456 cannot transfer). Do the spiking weights still
mark the break, only at their own line? The share with spiking weights at e... |
ab5bf7859ff7bb68144f744cea2ad5fd27ae9e6ba62b3788031159a7d8d2e032 | Python | 2,860 | 82 | """Each encoder should have following attributes and methods and be inherited from `_base.EncoderMixin`
Attributes:
_out_channels (list of int): specify number of channels for each encoder feature tensor
_depth (int): specify number of stages in decoder (in other words number of downsampling operations)
_... |
06b349350c98cdd6ac965d51b45d247ad43c32b51d61e56ad624d7149167fd37 | Python | 2,861 | 124 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
import common_setup
CONFIGS = {
"blind": [
"--search",
"astar(blind)"],
"ff": [
"--heuristic",
"h=ff()",
"--search",
"eager_greedy(h, preferred=h)"],
}
REVS = ["issue533-base", "issue5... |
5a009af232aa60908faa060cfd747314ed7786b016c4bd37497cf5046a8b719b | Python | 2,861 | 98 | import numpy as np
def e_step(matrix, counts):
"""
Performs E-step of EM algorithm: proportionally assigns reads to features
based on relative feature abundances.
"""
colsums = matrix.dot(counts)[:, np.newaxis]
out = (matrix / colsums).multiply(counts)
return out
def m_step(matrix):
... |
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