sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
b0f596d057b7ae186c9c61d8687a1deda49680a33152cc2e37edce45d6067db3 | Python | 3,067 | 98 | import numpy as np
import torch
from torch import nn
from torch.nn import functional as F
class DNN(nn.Module):
''' Autoencoder for dimensional reduction'''
def __init__(self, cdim, chid1, gdim, ghid1, hid2):
super(DNN, self).__init__()
#self.qc = qc
self.cdim = cdim
... |
167cf9e0805d6d9afd807395972f55bd1af6e4114588ca61381eac82285abd34 | Python | 3,068 | 74 | import glob
import sys
import pandas as pd
from nilearn.glm.second_level import SecondLevelModel
def group_onesample(fixed_files,group_out,contrast,smoothing=None):
"""
This function takes in a list of fixed effect files for a select contrast and
calculated a group (secondlevel) model by fitting an interc... |
b7f4489b0df21499c7c55f57f33364f4c2b7b1f685b741268edd470bd1618711 | Python | 3,068 | 59 | #==============================================================================#
# Author: Dominik Müller #
# Copyright: 2024 IT-Infrastructure for Translational Medical Research, #
# University of Augsburg ... |
05988813ecbfe0bb80d8a373148a1fdf1b960fc97a86c5db32852c51e6169423 | Python | 3,069 | 85 | import torch
import sys
import numpy as np
from sklearn.manifold import TSNE
import matplotlib.pyplot as plt
from utils_ensemble import list_of_result_to_dico
sys.path.append("../")
sys.path.append("../models_architectures/")
prefix = "../data/models/fine_tune_models/result_previous_may_2021/"
# Which model I want to ... |
0c4c9f1f310a72c4fff7eadc81d4399117c35360ba34569f9489331a3a232a68 | Python | 3,069 | 74 | import glob
import sys
import pandas as pd
from nilearn.glm.second_level import SecondLevelModel
def group_onesample(fixed_files,group_out,contrast,smoothing=None):
"""
This function takes in a list of fixed effect files for a select contrast and
calculated a group (secondlevel) model by fitting an interc... |
1158a731a47b942ec61239393a42ffa4a8a5ed8eec4a383e1c3d659108c548ef | Python | 3,070 | 79 | from typing import Tuple
import pytest
import torch
from pytorch_lightning import LightningModule, Trainer
from torch import Tensor, nn
from torch.optim import SGD
from torch.utils.data import DataLoader
from torchvision.datasets import FakeData
from lightly.transforms.torchvision_v2_compatibility import torchvision_... |
53ab084daeabb3bab75dadc50d2252f376eebbd264982132dac358e7ae97f629 | Python | 3,070 | 89 | '''Script for experimenting with the RNN component of the model without the RL component.'''
# © Thomas Akam, 2023, released under the GPLv3 licence.
#%% Imports.
import numpy as np
from tensorflow import keras
from tensorflow.keras import layers
import pylab as plt
from sklearn.decomposition import PCA
import two_s... |
bb1217d6d9abb6f1b672c3d118482384056ec84716805518b0c8365303201157 | Python | 3,070 | 109 | """Append rerun regression tests for active streaming traces."""
from __future__ import annotations
from pathlib import Path
import pytest
import torch
from torch import nn
import torchlens as tl
from torchlens.intervention.errors import AppendStreamingNotSupportedError
from torchlens.options import CaptureOptions,... |
16856782ce4725250ea62c2f291a52b32e875de2b2e6306d7720b0a02579041b | Python | 3,071 | 88 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import Sequential, Linear, ReLU
from torch_geometric.nn import GINConv, global_add_pool
from torch_geometric.nn import global_mean_pool as gap, global_max_pool as gmp
# GINConv model
class GINConvNet(torch.nn.Module):
def __init__(sel... |
5122cd077fb87793061a26571937986b956c3eec72ca725186b2692548fe3bc2 | Python | 3,071 | 93 | import numpy
from skimage.metrics import structural_similarity as ssim
import model
from propagation_ASM import *
import tools
from scipy import io
def psnr(img1, img2):
mse = numpy.mean((img1 - img2) ** 2 )
if mse < 1.0e-10:
return 100
PIXEL_MAX = 1.0
return 20 * math.log10(PIXEL_MAX... |
a5c72b1aa79c62d6340facf3c9e648fff36c0d20aa124db4247239775c8231d2 | Python | 3,071 | 90 | # --- 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 Textfont(_BaseTraceHierarchyType):
_parent_path_str = "scattercarpet.unselect... |
2aad9d2e74ed29998d85ec8a94af4af8fff20736bbad33156098758d437fb0ef | Python | 3,072 | 58 | #==============================================================================#
# Author: Dominik Müller #
# Copyright: 2024 IT-Infrastructure for Translational Medical Research, #
# University of Augsburg ... |
c3440a1a75564a29800a6948a1f1be077b8039ae00f8f0f08ca167a7c395c7a4 | Python | 3,072 | 99 | # -*- coding: UTF-8 -*-
import numpy as np
from sklearn import svm
import math
import random
import operator
import csv
from sklearn.cluster import KMeans
from sklearn.metrics import adjusted_rand_score
'''
@author:hunter
@time:2017.03.31
'''
class kmeans(object):
def __init__(self):
pass
def load... |
e9b7a90a719c34f552942378835179a3529ba4b282d5dbe9823dd95640d66882 | Python | 3,072 | 103 | from functools import lru_cache
import os
import pandas as pd
from .data_directory import DATA_DIRECTORY
from .rbns import read_rbns_motifs
from .rbns_v2 import read_rbns_v2p1_motifs
RBNS_MOTIF_FUNCTIONS = os.path.join(DATA_DIRECTORY, "motif_functions")
RBNS_MOTIF_FUNCTIONS_v1p0 = os.path.join(RBNS_MOTIF_FUNCTIONS, ... |
697c4f6090c274da62fe8228689aaf3367f07e13b64021bf8c147844381af65c | Python | 3,073 | 85 | import time
import copy
from docking.pdbbind_docking import PDBbindDocking
from data.split import RandomSplit, ScaffoldSplit
from conf_ensemble import ConfEnsembleLibrary
from rankers import (NoRankingRanker,
RandomRanker,
EnergyRanker,
ModelRanker,
... |
a93878759be6b605c63a95cde8d2dd0105bf907f6926da4b3e69415d84800294 | Python | 3,074 | 93 | import numpy as np
from neurogym.core import TrialEnv
from neurogym.utils import spaces
from neurogym.utils.logging import logger
class MatchingPenny(TrialEnv):
"""Matching penny task.
The agent is rewarded when it selects the same target as the computer.
opponent_type: Type of opponent. (def: 'mean_act... |
da42cb9f28d000a0f67ab62b51a69aec2255eb234433ef918fb64867c1d9dfc0 | Python | 3,074 | 73 | import glob
import sys
import pandas as pd
from nilearn.glm.second_level import SecondLevelModel
def group_onesample(fixed_files,group_out,contrast,smoothing=None):
"""
This function takes in a list of fixed effect files for a select contrast and
calculated a group (secondlevel) model by fitting an interc... |
791e74f9860e2224f27ff2b9a8d4c72c6cded4e211fa41cff91ceb5be724d68f | Python | 3,075 | 78 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import json
from pathlib import Path
from ultralytics.utils import LOGGER, YAML
from ultralytics.utils.checks import check_requirements, parse_requirements
def onnx2deepx(
onnx_file: str | Path,
imgsz: tu... |
91d2d817fe2a83623ac078ef1d07d53cc00b73bd684978b9a77a7a7abae4ef33 | Python | 3,075 | 97 | # 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 complian... |
0f3a9a4030539ee95645c89dcf364d25beb69d6880e687e4df016579dd3be752 | Python | 3,076 | 95 | import matplotlib.pyplot as plt
import re
import os
def read_roc(path):
acc_dict = dict()
threshold_list = list()
non_bind_acc_list = list()
bind_acc_list = list()
with open(path, 'r') as f:
i = 0
for line in f:
if i % 2 == 0:
# print(line)
... |
cc3b3bb8b243e6e5be0c81935d1abf1e5a391d05b2c114a9e2ef99fa2b025301 | Python | 3,076 | 90 | # --- 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 Textfont(_BaseTraceHierarchyType):
_parent_path_str = "scatterternary.unselec... |
d38ec012775435d140e1324e98091595dba11c2ffd8b5060c8fd0333f1821440 | Python | 3,076 | 90 | # --- 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 Textfont(_BaseTraceHierarchyType):
_parent_path_str = "scatterpolargl.unselec... |
0344e1bd29c4b1d01a463d307885b626db2b25e2d6d5d9bbbf1c4390f96b7055 | Python | 3,077 | 106 | import configparser
from pathlib import Path
from typing import Optional
import typer
from rich.prompt import Confirm
from codecarbon.core.config import get_hierarchical_config
def get_config(path: Optional[Path] = None):
p = path or Path.cwd().resolve() / ".codecarbon.config"
if p.exists():
config... |
582aacb276a43caa2bc75254ae5ec0e5cf4c75eb58973f6baa71735f7bc8a703 | Python | 3,077 | 94 | # coding=utf-8
# Copyright 2025 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... |
e86af9ddf92d59bfdda47b73373751ef1aec82512458e28ca332ee446637b84d | Python | 3,077 | 92 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Import raw (MaxFiltered) MEG data to remove metadata then save in same format for
further BIDSifying. For passive movements task.
@author: mikkel
For information about NatMEG-PD please refer to the data descriptor:
Vinding, M. C., Eriksson, A., Comarovschii, I., Wal... |
e8dfec0cecc424217ca498007d5dc4d7c9ba92db11a7085c7a87a3186796c3d5 | Python | 3,077 | 113 | import os
import random as python_random
import numpy as np
import tensorflow as tf
import tensorflow_datasets as tfds
from tensorflow.keras.models import load_model
from gradient_accumulator import GradientAccumulateOptimizer
from .utils import get_opt
from .utils import normalize_img
from .utils import reset
tf_v... |
410ab6602afa697a7ae14517ef5349f165f5b6b9cb0387752e24bb371c812940 | Python | 3,078 | 78 | import torch
from config_manager.config_manager import ConfigManager
from dataset_manager.training_dataset_manager import TrainingDatasetManager
# pylint: disable=no-member
class GenerateEmbeddingProt:
def __init__(self, path_folder_xp):
self.save_path = "data/embeddings_of_prots/"
self.xp_name =... |
ca63fad377786fe187519e613915226ecf76d2612c93abee9dad652295edf93c | Python | 3,078 | 98 | from abc import ABC, abstractmethod
import numpy as np
class Motif(ABC):
@abstractmethod
def score(self, rna, pad=True):
"""
Score the given RNA sequence. If pad is True, then the score is padded
with zeros on the left and right.
"""
pass
def width(self):
... |
cb2efca65bfbb8e970d4e0f64c1475515aa1a963df0397deab6a29e9e3ff3a5a | Python | 3,078 | 83 | import numpy as np
import requests
import json
import zlib
import sys
import os
# Add src to path
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
from src.neuron_morphology import NeuronMorphology
from src.synthetic_morphology import MorphologyInterpolator
def load_neuron_from_web(neu... |
5c61de409fe52511064f15e36c1e06c7e8d5d74e1badb22302502b882cda0314 | Python | 3,079 | 86 | # 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... |
e399b64d8443385cc2f11aaedf1e5dd637682da4d36fd019253becf26e1f9deb | Python | 3,080 | 84 | #!/usr/bin/env python3
import predict
import sklearn.metrics
import argparse, sys
import os
import numpy as np
import glob
import re
import matplotlib.pyplot as plt
def calc_auc(predictions):
y_true =[]
y_score=[]
for line in predictions:
values= line.split(" ")
y_true.append(float(values[1]))
y_score.append... |
0f93a6fcf4da607ef4551791ce66e733153e8cc46831d78c949195f839cad549 | Python | 3,082 | 104 | # --- 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"
_path... |
09f24f51c28964742fa549600bb7b55c1b7c24de9d6b505df5157d2e157a3cbe | Python | 3,088 | 90 | #!/usr/bin/env python
#=========================================================================
#
# Copyright NumFOCUS
#
# 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://... |
34d8e9022e94f4e0ef51d2decb06957e77f086c0d8a17ed2387fc859810cc4a9 | Python | 3,088 | 112 | # coding=utf-8
# Copyright 2022 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... |
e445bf0385d1c847b71e8b3e07a7209366579963748d20ea1cd9f7d290fc730c | Python | 3,088 | 100 | """Entry-point wiring tests for grouped option classes.
The flat option kwargs were removed by the 2026-08-19 shim-removal lane, so
the grouped objects are the ONE spelling: these tests pin that the grouped
door works warning-free and that the removed flat spellings refuse as unknown
keywords instead of silently doing... |
e64c80021f2fa6f167954c5c5566cbbbf6ce1b42d6570607dd34a9d4663e002b | Python | 3,089 | 92 | from pathlib import Path
import h5py
import numpy as np
import scanpy as sc
from mudata import MuData
from muon.atac.tl import initialise_default_files
#
# Reading data
#
def read_10x_h5(filename: str | Path, extended: bool = True, *args, **kwargs) -> MuData:
"""Read data from 10X Genomics-formatted HDF5 file.... |
e73854b22e9c9641312e6eae3ae160ae8a5b1a2ae0c3c0e7225fdeeae147be8f | Python | 3,089 | 99 | # -*- coding: UTF-8 -*-
import numpy as np
from sklearn import svm
import math
import random
import operator
import csv
from sklearn.cluster import KMeans
from sklearn.metrics import adjusted_rand_score
'''
@author:hunter
@time:2017.03.31
'''
class kmeans(object):
def __init__(self):
pass
def load... |
8228ae1838f9498cb125a51669e21f8d9b23d16f5c75762cafeea22aa854b449 | Python | 3,090 | 83 | import numpy as np
from keras.src import backend
from keras.src import ops
from keras.src import testing
from keras.src.optimizers.adadelta import Adadelta
class AdadeltaTest(testing.TestCase):
def test_config(self):
optimizer = Adadelta(
learning_rate=0.5,
rho=0.9,
ep... |
ce340f37ec3a87aef857ef4b8cc6d567e952a2be9c4cb2ae3d01aed3b66f23dd | Python | 3,090 | 81 | import unittest
import h5py
import numpy as np
import tqdm.auto as tqdm
from modular_splicing.dataset.dataset_aligner import (
DatasetAligner,
bin_starts,
split_bin,
to_absolute_index,
)
from modular_splicing.utils.sequence_utils import draw_bases
class DatasetAlignerTest(unittest.TestCase):
def... |
db6c979d9d23612218746d16b547bd0e42ba197403a278cd3e232cddf00d259e | Python | 3,090 | 81 | """Tests for the xcp_d.utils.concatenation module."""
import os
import nibabel as nb
import numpy as np
import pandas as pd
from xcp_d.utils import concatenation
def test_concatenate_tsvs(ds001419_data, tmp_path_factory):
"""Test xcp_d.utils.concatenation.concatenate_tsvs."""
tmpdir = tmp_path_factory.mkte... |
1ce69c8a0b8cbde928127992d0a1a5e17479ef2c3e2848cd976d6201c76245f0 | Python | 3,091 | 95 | """
Plot beta weights of M1 beta lateralization vs. single-trial bias during baseline
"""
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from stats import permutation_test_two_tailed
from stats.stars import stars
############ Load data from baseline regression model #####... |
45102ce6223708825b5b216be01ee6a6fedb9eb67a1afd8d490ff97d82208de0 | Python | 3,091 | 110 | # %%
'''
Generates fc matrices from rest. Can be run on Lucky as it is fast.
'''
import h5py
import sys
import os
from sklearn.linear_model import LinearRegression
import numpy as np
from time import time
from nilearn.signal import clean
sys.path.insert(0, '..')
from functions.data_helpers import get_computer
# globa... |
2c081d52997b74bce6274d9de5b25bc9366b5cf3b743a812e166954a8c91d2b3 | Python | 3,092 | 128 | """Functionality to compute model error."""
from inspect import isfunction
import numpy as np
###################################################################################################
###################################################################################################
def compute_mean_abs_e... |
c2198c3d1edab4479dd09d99f214f5f34d738f89ffe695acfce4c067c146a91b | Python | 3,092 | 96 | """Intervention honesty: a failed ``do()`` detaches the hooks it attached
(WT A-II item 11 -- the contamination defect).
A hook that raises at fire time used to stay in the sticky spec after the
failed ``do()``, so every LATER push (including unrelated edits) re-fired it.
``do()`` is transactional about its own attach... |
d23301efd7e9878e4018fef50610d547d261a30b878bf2a1cb3b7dbf7f861fbc | Python | 3,093 | 89 | """
core.roc — ROC curve helpers and operating-point selection.
"""
from __future__ import annotations
import numpy as np
def roc_curve_sens_spec(scores, labels):
"""Sweep thresholds; return (thresholds, sens, spec) sorted ascending."""
scores = np.asarray(scores, float)
labels = np.asarray(labels, int)
... |
bd471aba70b20bf7a879e01989f7fd0250551fa869b7a0b6dab6d389f2b0b389 | Python | 3,094 | 89 | """Behavioral tests for the gated (Llama-style) MLP recipe."""
from __future__ import annotations
import torch
import torch.nn.functional as F
from torch import nn
import torchlens as tl
class LlamaMLP(nn.Module):
"""Tiny Llama-style gated MLP surrogate matching the recipe class name."""
def __init__(self... |
22079f5bf4f74eae23c4a82e9d50eede8232fb7cbc40babc4d95c3b5d4919ea5 | Python | 3,095 | 78 | from math import exp
import torch.nn.functional as F
import torch.nn as nn
import torch
class LpLssimLoss(nn.Module):
def __init__(self, window_size=5, size_average=True):
"""
Constructor
"""
super().__init__()
self.window_size = window_size
self.size_average = ... |
bef5693dadc89fec1718c1094dc3455625bd21d26922d5c2eafb87434792081c | Python | 3,095 | 97 | #!/usr/bin/env python
# coding: utf-8
# for each hla, whether the TCRs from all positive pairs appears in
# at least two subjects with known exist or not status for that hla
import os
import sys
import math
import random
import argparse
import numpy as np
import pandas as pd
from collections import defaultdict
... |
a2ef45ac56b2d8e38b8ce04dcd678f982ebb38c71cb6b22d920adad1ac9fb659 | Python | 3,096 | 129 | from typing import Literal
import pandas as pd
import numpy as np
def ffill(
x: np.ndarray
) -> np.ndarray:
"""
Forward fill time series.
Parameters
----------
x(np.ndarray):
Time series to be filled.
Shape(n_times, n_features).
Returns
-------
Filled time serie... |
b0717f2d5cb89821c9f67e2de142f2ddee9d8dba44eba9e4eb71a79101ad193c | Python | 3,096 | 90 | """The ``celery upgrade`` command, used to upgrade from previous versions."""
import sys
import click
from celery.app import defaults
from celery.bin.base import CeleryCommand, CeleryOption, handle_preload_options
from celery.utils.functional import pass1
@click.group()
@click.pass_context
@handle_preload_options
d... |
044aa4cd49858cb69eb85d7d13361698168efc888d6ba8141a752e53e96385ec | Python | 3,097 | 106 | import sys
sys.path.extend(["../TDNODE", "src"])
from torch.utils.data import DataLoader
from data.dataset import TGIData
from data.collate import make_batch
import src.utils
import warnings
from prodict import Prodict
warnings.filterwarnings("ignore")
def prepare_TGI(
data_root_path: str,
augment: bool = ... |
0bf790f246c11344c35b5a692bfdb9d3c76b46a64fbc196d0809aad75d100bdf | Python | 3,097 | 66 | # AUTOGENERATED BY NBDEV! DO NOT EDIT!
__all__ = ["index", "modules", "custom_doc_links", "git_url"]
index = {"read_file": "Importing.ipynb",
"extract_rawfile_unique_values": "Importing.ipynb",
"import_spectronaut_data": "Importing.ipynb",
"import_maxquant_data": "Importing.ipynb",
... |
417078e94305a126ed1bd1641e1e261ed25e337c97691dc5d84a8643faafb89e | Python | 3,097 | 118 | # -*- coding: utf-8 -*-
"""
Various methods of drawing scrolling plots.
"""
#import initExample ## Add path to library (just for examples; you do not need this)
import pyqtgraph as pg
from pyqtgraph.Qt import QtCore, QtGui
import numpy as np
win = pg.GraphicsWindow()
win.setWindowTitle('pyqtgraph example: Scrolling P... |
ac51c6780a5e06928d0378b9b6d0f125ce3f573621b8b9959be5a9a9cd96a052 | Python | 3,097 | 108 | """Benchmark ``tl.trace`` capture overhead on a 20-layer MLP."""
import argparse
import os
import statistics
import sys
import time
from collections.abc import Sequence
import torch
from torch import nn
PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
if PROJECT_ROOT not in sys.path:
sy... |
bd99bfe385c7db668ad433cdeb3c8ecf0d7f912f5eeee3a86c4c91a6fe73bd0a | Python | 3,097 | 93 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
@author: Pramod Bharadwaj Chandrashekar
@email: pchandrashe3@wisc.edu
"""
import sys
from collections import Counter
import pandas as pd
import numpy as np
import scipy as sp
from sklearn import preprocessing
from imblearn.over_sampling import SMOTE
def perform_overs... |
ceb22bdcf6c54e28ea58878f467b6ea0fed97757ea7c8be98c2c50deb5d1e29d | Python | 3,097 | 99 | # -*- coding: UTF-8 -*-
import numpy as np
from sklearn import svm
import math
import random
import operator
import csv
from sklearn.cluster import KMeans
from sklearn.metrics import adjusted_rand_score
'''
@author:hunter
@time:2017.03.31
'''
class kmeans(object):
def __init__(self):
pass
def load... |
e72d0e9f8491d5346176383ccf9cc5a9a73fb928eafe1167c1cca70949822e49 | Python | 3,097 | 109 | from rectipy import Network, random_connectivity, input_connections, wta_score
import numpy as np
import matplotlib.pyplot as plt
# preparations
##############
# network parameters
N = 100
p = 0.1
Delta_in = 2.0
J = 2.0
# input parameters
m = 5
p_in = 0.5
s1 = [0, 2, 1]
s2 = [4, 2, 3]
s3 = [3, 2, 0]
signals = [s1, ... |
adb49d0bd0e778b8aba5ec183830e0e19178678fcab23e6d3f7fc798a850094e | Python | 3,099 | 110 | import sys
import copy
import argparse
import logging
import pathlib
import numpy as np
import joblib as jb
import mudcod.sutils as sutils
import mudcod.community_detection as community_detection
logging.captureWarnings(True)
parser = argparse.ArgumentParser(
description="Cell-type-specific subject split experime... |
00fb4dfaa64f98fe32f69e514e70137cacedfc48d95ec0cba3e1d28d6dc281f0 | Python | 3,100 | 94 | #!/usr/bin/env python3
"""Helper script to adapt datavzrd report configuration files for Galaxy.
Subcommands:
rewrite: rewrite the dataset paths of a config file to point to the
Galaxy input files. Datasets are matched to the input files
in the order in which they appear in the config fil... |
1c47f57b1051638621aead4803a54dc458e26a33658fa603d684a06eb1dc1c17 | Python | 3,100 | 90 | import json
import os
import struct
import sys
import traceback
import urllib.request
from packaging.version import parse as parse_version
from PyQt5 import QtCore
class UpdateWorker(QtCore.QObject):
finished = QtCore.pyqtSignal()
data_ready = QtCore.pyqtSignal(dict)
@QtCore.pyqtSlot(str, str)
def p... |
8b1190471ac40b5c2f31382bf30c9a206b5abacf5b1fe1139a576a26ead4a5c1 | Python | 3,100 | 133 | import pytest
import numpy as np
from functools import partial
from pyriemann.datasets import make_matrices, make_masks
def requires_module(function, name, call=None):
"""Skip a test if package is not available (decorator)."""
call = ("import %s" % name) if call is None else call
reason = "Test %s skippe... |
c7fbbf4c0ff9e85127498569e138685c420cdacb0cc6a650b0fa72f48fe8493c | Python | 3,100 | 99 | from keras.losses import binary_crossentropy
import keras.backend as K
import tensorflow as tf
epsilon = 1e-5
smooth = 1
def dsc(y_true, y_pred):
smooth = 1.
y_true_f = K.flatten(y_true)
y_pred_f = K.flatten(y_pred)
intersection = K.sum(y_true_f * y_pred_f)
score = (2. * intersection + smooth) / ... |
d86f157e3e9d3caf095e8d4ba980d002b8e45e2c75c57bcb4e3fc827e5cb91ac | Python | 3,100 | 82 | """Wrapper for rescaling actions to within a max and min action."""
from typing import Union
import numpy as np
import gym
from gym import spaces
class RescaleAction(gym.ActionWrapper):
"""Affinely rescales the continuous action space of the environment to the range [min_action, max_action].
The base envir... |
621161e94b595fa3dab071aad01a361a0010e6840d20c87cbb3c4d793c5a7ffa | Python | 3,101 | 90 | """Define model components object."""
from specparam.utils.array import unlog
from specparam.modutils.errors import NoModelError
###################################################################################################
#########################################################################################... |
7c880e22676871123dbca683f396cddee11e6108802d8a21b58715eb74180e8d | Python | 3,101 | 99 | """
modif_analysis_plots.py
This script is used to modify plot designs on the fly for ROI and running
analyses from dictionaries, e.g. for presentations or papers.
Authors: Colleen Gillon
Date: October, 2018
Note: this code uses python 3.7.
"""
from pathlib import Path
import warnings
from matplotlib import pyp... |
06ebb7843ee3715aedcd927b3d43f9c10163602a43c876d4140c4fbd9e7b1c7e | Python | 3,102 | 102 | """CRFasRNN, 2015, Shuai Zheng et al.
Paper: Conditional Random Fields as Recurrent Neural Networks.
Dense-CRF mean-field inference is unrolled as recurrent softmax, Gaussian
message passing, learned compatibility, and unary re-injection.
"""
from __future__ import annotations
import torch
from torch import Tensor, ... |
50d9f746c1b273bc8584a4f20efbee09076742c474677ef84a75c45a3b85f6e1 | Python | 3,102 | 63 | #==============================================================================#
# Author: Dominik Müller #
# Copyright: 2024 IT-Infrastructure for Translational Medical Research, #
# University of Augsburg ... |
543bde516e5bd66680ffe77b8c5929cd3c19f78927177914450a78dfb17a2a62 | Python | 3,102 | 97 | from . import lack
# Lazy loading for MERFISHVI to avoid importing scvi unless actually needed
class _MERFISHVILazyLoader:
"""Lazy loader for MERFISHVI module to make scvi-tools optional."""
def __init__(self):
self._module = None
self._import_attempted = False
self._import_error = No... |
cf47cdd6ffec5c0f52fcf0764ed2dc36099be8a493810e6d5138b30341482a60 | Python | 3,102 | 113 | import numpy as np
import pandas as pd
import scipy.sparse as sp
import torch
import torch.backends.cudnn as cudnn
from tqdm import tqdm
from .STAGATE import STAGATE
from .utils import Transfer_pytorch_Data
cudnn.deterministic = True
cudnn.benchmark = True
import torch.nn.functional as F
def train_ST... |
f53c2417cabb1a7fcc925ac8737e85078b65799083cd88f8e0d79e5694a84ace | Python | 3,102 | 77 | # visualisation related functions
import matplotlib.colors as colors
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
import torch
from matplotlib.lines import Line2D
#from umap import UMAP
import warnings
from numba.core.errors import NumbaPerformanceWarning
warnings.filte... |
6322496315851504639ab29c86d5237224213b80434113a3f48b70946a8b0828 | Python | 3,103 | 114 | import multiprocessing as mp
def run_experiment():
import os
import tensorflow as tf
import tensorflow_datasets as tfds
from tensorflow.keras import mixed_precision
from gradient_accumulator import GradientAccumulateModel
from .utils import normalize_img
# disable GPU
os.environ["C... |
aabc005db47a16f2155346338fdeab18867af3fc87687e472636f693e64e524e | Python | 3,103 | 70 | #!/usr/bin/env python3
import argparse
from tabulate import tabulate
parser = argparse.ArgumentParser()
parser.add_argument('-p', help="Pairtools stat output")
parser.add_argument('-d', help="preseq report output")
args = parser.parse_args()
output_dict = {}
with open(args.p,'r') as f:
for line in f:
at... |
1125d01319225a36fd5cd3ba1b8072d0e07558630508487412fd4f13aad3d316 | Python | 3,104 | 107 | #!/usr/bin/env python3
"""
Authentication System Test Runner
This script runs all authentication-related tests and provides a comprehensive
report on the authentication system's functionality.
"""
import os
import subprocess
import sys
from pathlib import Path
def run_test_suite(test_path, description):
"""Run ... |
15336f642ce4a8ba422d482287a0c22532715b6effdefa48e403637b7390fc3e | Python | 3,104 | 106 | from modular_splicing.utils.construct import construct
import numpy as np
class InSilicoDeltaPsiAnnotator:
"""
Annotates the results of a knockdown analysis with a delta psi value.
"""
def __init__(self, *, filter_spec=dict(type="DoNotFilter"), agg_spec):
self.filter = construct(
... |
cf6c7c3ef4d2635f0fb338008a3f694510c582fba21ec89343436b6c574c085a | Python | 3,104 | 91 | # --- 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 Fill(_BaseTraceHierarchyType):
_parent_path_str = "table.cells"
_path_str... |
0dc092ae80fe047e7b084e93cae6ce3ec9e163648c1b95ff0dcde25966192ece | Python | 3,105 | 102 | """ GPU-agnostic helper fuctions go here.
"""
import inspect, functools, logging
import numpy as np
try:
import cupy as cp
import cupy as xp
using_cupy = True
from rmm.allocators.cupy import rmm_cupy_allocator
cp.cuda.set_allocator(rmm_cupy_allocator)
from cupyx.scipy import ndimage
except Imp... |
76a583ebcf0cf61dac7d0aebefa08c3fbf47c53474c4120d9aa99af98b9bff7b | Python | 3,105 | 110 | import numpy as np
import matplotlib.pyplot as plt
import SimpleITK as sitk
import cv2
from medcam.medcam_utils import interpolate
from collections import OrderedDict
def NormalizeData(data):
return (data - np.min(data)) / (np.max(data) - np.min(data))
num_dict=OrderedDict({'435':25,'412':24,'474':20,'501':20... |
80742b3b65af33a2e0e332d14decfc23aafc716c841c358cac10e502de2cc1a8 | Python | 3,105 | 94 | # This example requires the following dependencies to be installed:
# pip install lightly
# Note: The model and training settings do not follow the reference settings
# from the paper. The settings are chosen such that the example can easily be
# run on a small dataset with a single GPU.
import pytorch_lightning as p... |
2086134d9aabfb0f185d955cac798ec9eaecfcc046536b1cb3198708c4301f4b | Python | 3,106 | 104 | import numpy as np
import torch
from torch import nn
from torch.nn import functional as F
class DNN(nn.Module):
''' Autoencoder for dimensional reduction'''
def __init__(self, cdim, chid1, gdim, ghid1, hid2):
super(DNN, self).__init__()
#self.qc = qc
self.cdim = cdim
... |
3732613f4ab643e1e85067ae04e368ecb31795a9495bffac9ab5c7989c8903dd | Python | 3,106 | 101 | """grind-p3 T11.9: registered-container aux is type-strict, subclasses refuse.
``_safe_aux`` admitted ``list``/``tuple`` SUBCLASSES through ``isinstance``
and encoded them as their plain base kind -- erasing the exact class and any
instance state (a namedtuple aux flattened to a bare ``tuple`` row), so two
registratio... |
3bd4845b9b2f6cc94950f95d148d51b81a38cbe95f7229d5f461de2e63ba7370 | Python | 3,106 | 103 | #!/usr/bin/env python
"""
Add and update the "itk_module" and "itk_group" fields in the
SimpleITK json file based on ITK source directory.
"""
import os, sys
import re
import json, collections
def IncludesToPaths(path):
"""Build a dict that maps include files to paths"""
includeToPath = dict()
prog = re.compi... |
80ef5d3cc79025f14c7cb668e9f5783f6bf3bce8367a540949c9e181b4acf0da | Python | 3,107 | 79 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# check_h264_md5.py
#
# Copyright 2020 Giorgio Gilestro <giorgio@gilest.ro>
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version ... |
8d2c0a76e83a215591ee2cbcd06071ff0d21eb7baf0916a159916ba1f4d189dd | Python | 3,107 | 86 | #!/usr/bin/env python
# Created on: August 20, 2013
__author__ = "Sven Kreiss, Kyle Cranmer"
__version__ = "0.1"
import effectiveModel
import optparse
parser = optparse.OptionParser(version=__version__)
parser.add_option("-i", "--input", dest="input", default="inputs/atlas_prodModes_hists_and_response_functions.ro... |
9064d896c42589431e2ca77dcc3828d0118728996538dd261778a3ddab4a872d | Python | 3,107 | 80 | """
Tests for backward compatibility with deprecated parameter names.
"""
import unittest
from unittest.mock import patch
from codecarbon.core.emissions import Emissions
from codecarbon.emissions_tracker import EmissionsTracker
from codecarbon.input import DataSource
class TestElectricityMapsBackwardCompatibility(u... |
f812c11786a4fe92ffd8e756f6629d14d02edbfef37a4885808da5a3cd23a1f2 | Python | 3,107 | 63 | p_apical1 = [[734.0, 692.0, 0.0, 0.0, 2.0943951023931953, 0.0],
[747.0, 695.0, 0.0, 0.0, 1.5707963267948966, 0.0],
[710.0, 684.0, 0.0, 0.0, 1.3962634015954636, 0.0],
[728.0, 719.0, 0.0, 0.0, 1.3089969389957472, 0.0],
[219.0, 192.0, 0.0, 0.0, 1.2566370614359172, 0.0],
[125.0, 150.0, 0.0, 0.0, 1.2217304763960308, 0.... |
4083ad7864550033a5946601b5ec8ca0c4b5765ab3d4aa86df83883aea113b14 | Python | 3,108 | 91 | # Copyright 2006, Google Inc.
# 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 of conditions and the f... |
8d5e419c4b5b853b3fbee9197e3998cb5785c495a11ef0bf49bc7dd971e7d62e | Python | 3,109 | 91 | # --- 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 Fill(_BaseTraceHierarchyType):
_parent_path_str = "table.header"
_path_st... |
45b3474f836fa2e02f4857dc3308036a52a7a5e25c66bca222ea8501fe8e55f3 | Python | 3,111 | 110 | from rectipy import Network
import numpy as np
import matplotlib.pyplot as plt
import torch
# preparations
##############
# check CUDA devices
print(f"CUDA available: {torch.cuda.is_available()}")
dev_id = torch.cuda.current_device()
dev_name = torch.cuda.get_device_name(dev_id)
print(f"CUDA device: {dev_name}, ID: ... |
5d200476fd90fc81d5cc9584e27121f435300223d3bc29af6a733834972599a0 | Python | 3,111 | 71 | import os, sys, pkg_resources, subprocess
from time import sleep
import yaml
def are_python_requirements_installed(requirements_file):
with open(requirements_file, 'r') as f:
requirements = f.read().splitlines()
for requirement in requirements:
try:
dist = pkg_resources.get_distribu... |
73ca3d3ef356a259fae1422254624585cafd821994c61fe96ad8a7d76c5dff17 | Python | 3,111 | 91 | from ._RL_agent import *
from numba import njit
@njit
def mf_session_value(choices, second_steps, outcomes, n_trials, transition_type, params):
# Unpack parameters.
alpha, weight_mf, lbd = params[:3]
# Variables.
Q_c = np.zeros((n_trials, 2)) # Value of the choice.
V_s = np.zeros((n_trials, 2)) # Value of... |
0c5712729f9a54e5d5c6187c01f1e1f91d30e9a44df69ca8ba56c8970e9d76d3 | Python | 3,112 | 124 | """Shared fixture builders for the F29 agent-surface suites (no tests here).
Every builder is DETERMINISTIC (explicit seeds, eval mode) so the determinism
and transcript suites can assert byte-identical output across processes.
"""
from __future__ import annotations
from pathlib import Path
import torch
from torch ... |
694351fcb3ea38b80e93ed696585be2a53088fac42954a8532ceb14fb5d77fe0 | Python | 3,112 | 63 | # skip test: data unavailable
from eelbrain.pipeline import *
class Mouse(MneExperiment):
# Name of the experimental session(s), used to locate *-raw.fif files
sessions = 'CAT'
# Pre-processing pipeline: each entry in `raw` specifies one processing step. The first parameter
# of each entry specifies... |
4c518d1e864eb2d36b8313e3a73a83feca6b9e16b6434dc1014113ce584e1c84 | Python | 3,113 | 71 | import os, sys, pkg_resources, subprocess
from time import sleep
import yaml
def are_python_requirements_installed(requirements_file):
with open(requirements_file, 'r') as f:
requirements = f.read().splitlines()
for requirement in requirements:
try:
dist = pkg_resources.get_distribu... |
06a581a91ede92f0abab93d7707fbbf3f7fbca257c2cb06ff179cca4fd92e26b | Python | 3,114 | 86 | """Test is based on a metadata JSON file generated from
running atac-seq-pipeline v1.8.0 with the following input JSON.
gs://encode-pipeline-test-samples/encode-atac-seq-pipeline/ENCSR356KRQ_subsampled_caper.json
"""
import pytest
from caper.resource_analysis import LinearResourceAnalysis, ResourceAnalysis
def test... |
ac3b0f12bf2a89e10c6b8f04d142b6103f9f1495030b8ff2c559d9952e060a00 | Python | 3,114 | 87 | from __future__ import annotations
import collections.abc as cabc
import typing as t
if t.TYPE_CHECKING: # pragma: no cover
from _typeshed.wsgi import WSGIApplication # noqa: F401
from werkzeug.datastructures import Headers # noqa: F401
from werkzeug.sansio.response import Response # noqa: F401
# The... |
c0d9dd81a119927d25b35bcf0788d75f3a70ea7a294d3edf61230745a0f1b04c | Python | 3,114 | 101 | import logging
from typing import List, Dict, Any
import os
from pymatgen.core.structure import Molecule
from pymatgen.analysis.graphs import MoleculeGraph
from pymatgen.analysis.local_env import OpenBabelNN
from pymatgen.io.ase import AseAtomsAdaptor
from ase import io as ase_io
from instance_mongodb import insta... |
d79a2867067a73c866a00c607bbbec27705e8cab09e5998f7ab8888c983c2f90 | Python | 3,114 | 81 | # 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... |
f63194beb0908fcc8d32a4374b264a8a11744205a4ea3c0261b90095c65e9963 | Python | 3,114 | 92 | """The RNG channel monitor warms torch's lazy dynamo import OUTSIDE its window.
The first wrapped op of a capture can trigger torch's own lazy
``import torch._dynamo`` (``torch/_compile.py``), whose import cascade draws
host entropy at module-exec time (``uuid.uuid4()`` in
``torch.distributed._composable.contract``, p... |
4b13873a07805c3a9faaf1e72c4c54c122969963a80dbf1b48c5e8a07244384e | Python | 3,115 | 91 | """IO functions for 10x Visium technology.
"""
import os
from typing import List, NamedTuple, Optional, Union
import numpy as np
import pandas as pd
import scipy.io
from anndata import AnnData
from typing_extensions import Literal
from ..configuration import SKM
from ..logging import logger_manager as lm
from .utils ... |
9c34525e526a6cfbd5ab53703017128b61955cbc555dc122eccda86adc257667 | Python | 3,115 | 92 | # --- 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 Root(_BaseTraceHierarchyType):
_parent_path_str = "icicle"
_path_str = "i... |
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