sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
45592cd56b6a934f5852bdecc8789f39466fdafc8dae00cb562f83d8050df444 | Python | 3,760 | 99 | # coding=utf-8
# Copyright 2023 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... |
83691980befd60e7f80dd695b31181818030e040345b457b82736eedcaeac755 | Python | 3,760 | 92 | """The capture-door inventory lint (lane F40c, XS; foldA MEMO s5 item 8).
The one-door law (trace-verb verdict section 1): ``tl.trace`` is the ONLY
public live-capture door to a ``Trace``. This lint enumerates every root
callable whose return type mentions ``Trace`` (classes count by name) and
asserts the set equals t... |
8f06d43d9eadb8d14f1fc49de238a0dd180976e91604ea1870c34be691315e98 | Python | 3,760 | 125 | from typing import Optional
import numpy as np
from numpy.testing import assert_almost_equal
import gym
from gym.wrappers.normalize import NormalizeObservation, NormalizeReward
class DummyRewardEnv(gym.Env):
metadata = {}
def __init__(self, return_reward_idx=0):
self.action_space = gym.spaces.Discr... |
7c6bf2e82c1cc1e7c7651ebeab995220cec5948dd3fe224cb29c974df9832acc | Python | 3,761 | 111 | import numpy as np
from src.data.BoolQReader import BoolQReader
from src.data.CBReader import CBReader
from src.data.RTEReader import RTEReader
from src.data.MultiRCReader import MultiRCReader
from src.data.WiCReader import WiCReader
from src.data.COPAReader import COPAReader
from src.data.RecordReader import RecordR... |
7cd218f671b57cc0afd6a414755f4b99e70befe82240279a8c5fea0355bd68e6 | Python | 3,761 | 116 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch import Tensor
class MACLLoss(nn.Module):
"""Implementation of the Model-Aware Contrastive Loss (MACL) from the paper:
This implementation follows the MACL[0] paper.
- [0] Model-Aware Contrastive Learning: Towards Escaping the ... |
3a4472ab8fb431b9028ab2209dd989e3818e22620225b787785c8662af3d61ee | Python | 3,762 | 100 | import subprocess
import unittest
from unittest import skipIf
from time import sleep
from unittest.mock import patch
from io import StringIO
import sys
from carbontracker import cli
import os
def mock_password_input(prompt):
# Simulate password entry based on the prompt
if "Password:" in prompt:
return... |
78b4e399d0b06659359df507e7160475c4d4ac22ab1dea480cdae73033e88b89 | Python | 3,762 | 156 | import subprocess
import pytest
import sys
import os
import textwrap
import rpy2.rinterface as ri
ri.initr()
def floatEqual(x, y, epsilon=0.00000001):
return abs(x - y) < epsilon
def test_int():
sexp = ri.IntSexpVector([1, ])
isInteger = ri.globalenv.find("is.integer")
assert isInteger(sexp)[0]
d... |
965a1de9b3c019ebf54655f2cce3dcf6fdeb59e71bbe7696b176ea9ac08d1bcd | Python | 3,762 | 99 | import math
import torch
import torch.nn as nn
import torch.distributions as D
class RepresentationLayer(torch.nn.Module):
'''
Implements a representation layer, that accumulates pytorch gradients.
Representations are vectors in nrep-dimensional real space. By default
they will be initialized as a ten... |
26976a8d6c0b3e651afb9c3af50fe83b1ea903ce91162e61975a76aea5328edf | Python | 3,763 | 117 | # --- 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 Spaceframe(_BaseTraceHierarchyType):
_parent_path_str = "volume"
_path_st... |
37d1fd3ce4382548588b1d2af67b867f0d7a72dd2d99748ee43b5fcc5c3f76e2 | Python | 3,763 | 116 | # --- 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 = "bar.unselected"
_pat... |
e1c84a9371b087750bd248615ee11efea3e197ef94a1f151dca57e3ce3da3d00 | Python | 3,766 | 100 | import warnings
from unittest import mock
import numpy as np
from keras.src import backend
from keras.src import callbacks
from keras.src import layers
from keras.src import testing
from keras.src.models import Sequential
from keras.src.utils import numerical_utils
try:
import requests
except ImportError:
re... |
2d5f9fd109d67d4652dd1a7aca957075e3363f38ccef2728d94825760a9ff6d6 | Python | 3,767 | 87 | # pylint: disable=arguments-differ,line-too-long,missing-docstring,missing-module-docstring
import math
import random
# code adapted from:
# https://github.com/kakaobrain/fast-autoaugment
# https://github.com/rpmcruz/autoaugment
class EfficientNetRandomCrop:
# pylint: disable=misplaced-comparison-constant
def ... |
7cf60eb8aa6bef4f67071ea22ec0dbb50ffa72adb3bc0fc1868b686b3ad38ae5 | Python | 3,768 | 112 | #!/usr/bin/env python3
"""
File: check_results.py
Created: 2022/04/01
Last Changed:
Author: M.Vochteloo
Copyright (C) 2020 University Medical Center Groningen.
A copy of the BSD 3-Clause "New" or "Revised" License can be found in the
LICENSE file in the root directory of this source tree.
"""
# S... |
8155126cac734196fc0e7ecd64e91c87cdf2d8c45f838ac1538c1a5445b63769 | Python | 3,768 | 125 | import numpy as np
import torch
import plotly.graph_objects as go
from e3nn.io import SphericalTensor
def plot_orbitals(traces, traces_species, title_str, show_fig=False):
traces = [go.Surface(**d) for d in traces]
fig = go.Figure(data= (traces))
fig.update_traces(showscale=False)
if show_fig: fig.sho... |
42f839609a0d868587505866f61c52f97098cbf675c4195f016aa5c7a29e2bd9 | Python | 3,769 | 113 | # --- 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 = "waterfall.increasing"
... |
ae5db2d420d7d8931e907ddde9ac6f33b33015dd7357e13a6a71422bf3c34699 | Python | 3,769 | 113 | # --- 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 = "waterfall.decreasing"
... |
29dd20f0897777ed017e690ef1ef2a9cf55cacc1d9ed13c844322499ff876084 | Python | 3,771 | 126 | #!/usr/bin/env python
"""
That tools tries so solve a simply mapping problem in the easiest and propably dirtiest way ever.
In galaxy we need often so called mapping of identifiers, e.g. EC-2-GO, UniProt-2-PDB, UniProt-2-PDB and so on.
Normally such mapping files are available in a tab-separated format.
AIM: Write a m... |
5148039b39b472877cb87fbea7035dee045c06203d233fdc2eddab8971f63db6 | Python | 3,771 | 131 | # --- 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 Caps(_BaseTraceHierarchyType):
_parent_path_str = "volume"
_path_str = "v... |
860233382ccd00b1dbccf9c7f8c8b99ea4d6082d6bae4e8cd1f9cbf96d4fcc29 | Python | 3,772 | 106 | import re
from modular_splicing.dataset.datapoint_extractor import DatapointExtractor
from modular_splicing.dataset.generic_dataset import GenericDataset, dataset_types
from modular_splicing.utils.construct import construct
from modular_splicing.utils.mulitple_contexts import MultipleContexts
from modular_splicing.util... |
954a8b55f4f940810b606ecd49f2c8e0a982ee5fb9cf6f2a8528d6a7d94602a8 | Python | 3,772 | 136 | __author__ = "Yasunobu OKAMURA"
__copyright__ = "Copyright (c) 2012 Y.Okamura"
__license__ = "GPL v3+"
import xml.parsers.expat
import networkx as nx
class XGMMLParserHelper(object):
""""""
def __init__(self, graph=nx.DiGraph()):
"""
Arguments:
- `graph`: Network X graph object
... |
976cadaee4eff4f14868a29329060314ceb0f801074c9226c69d3eaa959c60ab | Python | 3,772 | 126 | from typing import (
Callable,
List,
Optional,
Tuple,
Iterable,
Union,
)
from pysam.libcutils import _pysam_dispatch
class SamtoolsError(Exception):
'''exception raised in case of an error incurred in the samtools
library.'''
def __init__(self, value):
self.value = value
... |
378ec8fc01b9831cb8576f82cadeeb4ef88600ef83dafe77d69ad0e072a3a6e6 | Python | 3,773 | 85 | """
Ethoscope is a platform developed at `Gilestro lab <http://lab.gilest.ro/>`_.
It provide an integrated set of tools to acquire behavioural data on small animals and build feed back modules to interact with them in real time.
A description of the whole system is available on its `website <http://gilestrolab.github.i... |
49a93c20b59b9977276f3a2ce144f08ab1ecfdf22e9a6674e4120834f756b6a3 | Python | 3,773 | 115 | """Reproducing angles."""
import numpy as np
from neurogym.core import TrialEnv
from neurogym.utils import spaces, tasktools
class AngleReproduction(TrialEnv):
"""Angle reproduction.
The agent has to reproduce to two angles separated
by a constant delay.
"""
metadata = { # noqa: RUF012
... |
93ccce152fd1ea944beefe344b6c071fd51ca4d8e59e456e3415921cedab2966 | Python | 3,773 | 126 | """Worker Pidbox (remote control)."""
import socket
import threading
from kombu.common import ignore_errors
from kombu.utils.encoding import safe_str
from celery.utils.collections import AttributeDict
from celery.utils.functional import pass1
from celery.utils.log import get_logger
from . import control
__all__ = (... |
e132deedcf3d8cf1d53a24db01d2b620c5bddf74ef20f7b2ada894c9bdf3b4a7 | Python | 3,773 | 153 | import numpy as np
import torch
import sklearn
from sklearn.ensemble import RandomForestClassifier
from train_utils import *
# Step 1: Read and preprocess data
# f = open('large_dataset/protein_19.txt')
f = open('protein_dataset/protein_19.txt')
vals = [line.strip().split(', ') for line in f]
f.close()
def convert... |
2464cab151fa7a911b01ac05122fa6d406adb04b4a1a4b50e6204153d0e8e58f | Python | 3,774 | 98 | import torch.nn as nn
import torch
import math
import numpy as np
import torch.nn.functional as F
from torch.nn.parameter import Parameter
class GraphConvolution(nn.Module):
def __init__(self, in_features, out_features, residual=False, variant=False):
super(GraphConvolution, self).__init__()
self... |
42f7716cca0d2c65a4d062e5a046b9a09bb89d7f08094419832643cb8ee6b0e8 | Python | 3,774 | 112 | """
Code related to detection and measurement of action potentials (APs)
"""
import warnings
import logging
import numpy as np
import pyabf
import os
import sys
PATH_HERE = os.path.abspath(os.path.dirname(__file__))
PATH_DATA = os.path.abspath(PATH_HERE+"../../../../data/abfs/")
PATH_SRC = os.path.abspath(PATH_HERE+".... |
1c86956d6fe64f2fa66ff20662810fc7b2da413190188b5d66f2189e0235888b | Python | 3,775 | 111 | # Linear-circular regression
#
# Method published in Kempter, R., Leibold, C., Buzsáki, G., Diba, K., & Schmidt, R. (2012).
# Quantifying circular – linear associations : Hippocampal phase precession. 207, 113–124.
# https://doi.org/10.1016/j.jneumeth.2012.03.007
#
# This python script is first implemented by Dr. Dusti... |
3608cb547ea55d201d3da239a8a82912e9513dd12e6ec2eb3fae13d25e235961 | Python | 3,775 | 104 | """Shared receptive-field rule-registry isolation for the RF test suite.
Every ``tests/test_rf_*.py`` file needs the same process-global hygiene: the
RF rule registry (``torchlens.receptive_field._rules._RF_RULES``) and its
cache-invalidation epoch (``_RF_RULES_EPOCH``) must be snapshotted before a
test mutates them a... |
47c8822d857311e8c6483e0fc25fadfa244894d2b8451c30ed0679eba405b959 | Python | 3,775 | 124 | # coding: utf-8
'''Tests for ml'''
import unittest
import numpy as np
from bdpy.ml.crossvalidation import cvindex_groupwise, make_cvindex, make_cvindex_generator
class TestCVIndexGroupwise(unittest.TestCase):
def test_cvindex_groupwise(self):
# Test data
x = np.array([
1, 1, 1,
... |
29c46b1f38dc4be05a55087ff8dc1dc3d1f69ae3a85f7d63c9a6940c9500ae1d | Python | 3,776 | 257 | """
Sequential color scales are appropriate for most continuous data, but in some cases it \
can be helpful to use a `plotly.colors.diverging` or \
`plotly.colors.cyclical` scale instead. The color scales in this module are \
mostly meant to be passed in as the `color_continuous_scale` argument to various functions.
""... |
4ad08689210c011f1f487874482d402444e799917c1306f1124df8c65baa89c6 | Python | 3,776 | 72 | #==============================================================================#
# Author: Dominik Müller #
# Copyright: 2024 IT-Infrastructure for Translational Medical Research, #
# University of Augsburg ... |
8c017dd5ccb90bba03a0a625b6a252fbec0901f2879c9a3b49ef22a6631e1758 | Python | 3,776 | 92 | # main code to wrap up all the steps from data fetching to curation
import pandas as pd
from MoleculeACE.benchmark.const import WORKING_DIR
def main(chembl_targetid='CHEMBL2047', bar=True, endpoints=["EC50"], assign_class=True, thr_class=100,
working_dir: str = WORKING_DIR, rm_high_std=True):
from benchm... |
ca4c843ee5409b35a4e1d6156ac8242a8c86bd5ddd7b4a5ab674c5aa6904ef89 | Python | 3,776 | 103 | import json
import logging
import os
import tempfile
import time
import unittest
from codecarbon.emissions_tracker import (
EmissionsTracker,
OfflineEmissionsTracker,
track_emissions,
)
from codecarbon.output import LoggerOutput
def heavy_computation(run_time_secs: int = 3):
end_time: float = (
... |
a111dd334e7c71ed02df7939dfe7a778c5cc1491090b72f862c6268fe427f66c | Python | 3,777 | 107 | """Base segmentation dataset"""
import random
import numpy as np
from PIL import Image, ImageOps, ImageFilter
import mxnet as mx
from mxnet import cpu
import mxnet.ndarray as F
from .base import VisionDataset
__all__ = ['ms_batchify_fn', 'SegmentationDataset']
class SegmentationDataset(VisionDataset):
"""Segmenta... |
4dc47942d688066954da5e11b1deef51b53469145872f1b9911e628afe217b41 | Python | 3,778 | 120 | """W051-EXTRACT: default collation of (input, label)-shaped items teaches (audit 3.13).
Tuple items, ``TensorDataset`` rows, and ``DataLoader`` batches default-collate
to one positional input per element and used to die inside the model with a
raw ``TypeError``; when ``forward`` cannot bind that many positionals the
e... |
cc972f1a477dd13258a1720d1fb006a1b1aa616cc4cbf580935b490475c5ce0b | Python | 3,779 | 108 | """Extract segmentation performance"""
import os
from os.path import join as opj
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from scripts.utils.constants import CSV_ORG_OVERVIEW
from scripts.utils.metrics import get_dice
class SegmentationPerformanceExtractor():
"""Extracts perform... |
fa7f66ba03f5abea02804838c01b8f83d24d990581f9ee5a877eebe445b111f3 | Python | 3,779 | 114 | """Schema audit tests for intervention Phase 1 fields."""
from __future__ import annotations
from typing import Any
import torch
import torchlens as tl
from torchlens._trace_state import TraceState
from torchlens.constants import LAYER_PASS_LOG_FIELD_ORDER, MODEL_LOG_FIELD_ORDER
from torchlens.data_classes.op impor... |
2e0bf1a08e6d1a865ba998e4bae324b74be93d6f5f2fd598a2807e9dc80c3779 | Python | 3,781 | 144 | """
Useful functions that don't deserve a CLI.
If they do, they belong in utils.py.
"""
import numpy as np
import pandas as pd
import pkg_resources
import os
# ### Math functions ###
def running_avg(x):
"""
Given a 2D numpy array, calculate a running average of each of the columns.
That is, the ijth e... |
5273c3d59204dd8e4275804596adc39f42340782c3d3c8757fae71aee06273c8 | Python | 3,782 | 97 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Nov 14 21:03:49 2021
@author: fcheng
"""
import numpy as np
from itertools import product
def CalSimilarityIndex(image, maskinfo):
"""
calculate similarity index for image, given two masks
Output:
Index - a float number, positive if... |
f789b3625adb35dd1a69a67315ffc8f082acfdd8a74fb28539457829b4a54a58 | Python | 3,783 | 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... |
78841f4583b5a153afd45e2c52d3432922e66ed57ddbcdf9e17df076ca07a6f2 | Python | 3,784 | 100 | import h5py
import numpy as np
from Desert import *
from Land import *
pi = math.acos(-1.0)
dtr = pi / 180.0
confdnc_l = np.zeros([32, 32])
cmin21_list = np.zeros([32, 32])
cmin22_list = np.zeros([32, 32])
cmin31_list = np.zeros([32, 32])
cmin32_list = np.zeros([32, 32])
def read_hdf5_file(file_name, size):
f =... |
9d0a07c77e103d6e9738f900a4aed8812db3cb59fd3cd7fb9d8e12bf19eeed63 | Python | 3,784 | 119 | import os
import pickle
import tqdm.auto as tqdm
import h5py
import numpy as np
import torch
from modular_splicing.models.modules.lssi_in_model import BothLSSIModels
from modular_splicing.utils.arrays import Sparse
from modular_splicing.utils.run_batched import run_batched
from modular_splicing.utils.io import load... |
428189eeb706b15bf866830c125f37dfadc13e50c0fe521a8a0b19b76e4e8e13 | Python | 3,785 | 92 | # FAITHFUL PORT of RTH-tools/crispron @ master (original framework: TensorFlow 2 / Keras,
# bin/DeepCRISPRon_train.py)
#
# CRISPRon predicts Cas9 on-target editing efficiency from a 30-mer (4-base one-hot,
# length 30) plus a scalar deltaG (binding free energy) side input. The real repo ships
# only trained `tf.keras` ... |
537428682eb03d983da93ba32b97d9dc19e34f3ed41d969b9dacd8a5cc0cf8ed | Python | 3,785 | 130 | import numpy as np
import torch
from numpy.random import default_rng
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from tqdm import tqdm
import multiprocessing
from multiprocessing import Pool, freeze_support, current_process, RLock
from functools import partial
import pathlib
from causal_o... |
7399d54ce30fbb1a16a509e7492a0908dfd97572a8607897d4805a29acde19dd | Python | 3,785 | 102 | # -------------------------------------------------------------------------------------
# Code to perform parallel processing
# From https://github.com/ThomasAkam/Two-step_ACC/blob/4a0c5ad6a40b84721af972a11d9952e4e305f7e5/analysis_code/two_step/Two_step/parallel_processing.py#L4
# -----------------------------------... |
a43521ef0d95e677c6b7a37ef506a4234136fd15782940b80364414be0c7a6f9 | Python | 3,785 | 147 | """
Validation used in tkinter Entry widgets.
SimplyFire - Customizable analysis of electrophysiology data
Copyright (C) 2022 Megumi Mori
This program comes with ABSOLUTELY NO WARRANTY
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as publishe... |
cdc2483cdbb45708c15d83a7552c6c8957d1395a7b9437a9fc245151de3e7871 | Python | 3,785 | 103 | """
Gregory Way 2017
PanCancer Classifier
scripts/map_mutation_class.py
Merge per sample classifier scores with mutation types present in each sample
Usage: Run in command line:
python scripts/map_mutation_class.py
with required command arguments:
--scores string indicating the location of all sample p... |
0f86a31cc4ce203bc0462c43e70e825b3e092d1f7a2142ff493b08785235a016 | Python | 3,786 | 129 | import pandas as pd
import numpy as np
import torch
import torch.nn as nn
from torch.utils.data import Dataset, DataLoader
from torchvision import datasets
import torchvision.transforms as transforms
import random
import os
import umap
import anndata
import scanpy as sc
from torch.autograd import Variable
import h5py
i... |
0effcb6797ce7389a467f70bf78a6c721a4e7a2daf29ea96e11fadbaf4acaa67 | Python | 3,787 | 132 | """PP-PicoDet compact mobile object detector.
Yu et al., 2021, "PP-PicoDet: A Better Real-Time Object Detector on Mobile
Devices". PicoDet uses an ESNet-style lightweight backbone, CSP-PAN neck,
anchor-free detection, and a GFL/quality focal style head. This compact
random-init reconstruction keeps those inference c... |
223a31d42d2d2063a62b6bd324eebf46f82d9cea758d19c8cb967a51337679cc | Python | 3,787 | 131 | import json
import os
import zipfile
_this_dir = os.path.dirname(os.path.abspath(__file__))
_opencc_rootdir = os.path.abspath(os.path.join(_this_dir, '..', '..'))
_testcases_path = os.path.join(_opencc_rootdir, 'test', 'testcases', 'testcases.json')
_TEXT_ZIP_CONFIG = """{
"name": "Python Resource Zip Test",
"seg... |
8101fc97149685e1826cea4bd9c171fed287b70cbe146950128190378bbf91c8 | Python | 3,787 | 131 | model = dict(
type='FPSiam',
lamda=0.5,
backbone=dict(
type='ResNet',
depth=50,
in_channels=3,
out_indices=[1, 2, 3, 4],
norm_cfg=dict(type='SyncBN'),
zero_init_residual=True,
init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),
... |
598246d1537d65b6cc59fa61936de6ace103ab812b3c9b0c788daa4f5f3e6ec7 | Python | 3,788 | 90 | """Plots for the event model object.
Notes
-----
This file contains plotting functions that take as input an event model object.
"""
from itertools import cycle
from specparam.modutils.errors import NoModelError
from specparam.modutils.dependencies import safe_import, check_dependency
from specparam.utils.properties... |
9ff4c3657f074bbcbdf8a01df6b7fd403c4310e74dd34ddfef69fbf915bae4bd | Python | 3,788 | 116 | # --- 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 = "barpolar.unselected"
... |
9ef776fc504fdefd0c44f2673919a9b002d1d9dc17855fc2d0bdca031dff654e | Python | 3,789 | 112 | import seaborn as sns
from matplotlib import pyplot as plt
from collections import OrderedDict
from sklearn.metrics import roc_curve, auc, roc_auc_score, brier_score_loss, precision_recall_curve, f1_score, precision_score, recall_score
from math import sqrt
def plot_box_kde(df, dep, y):
fig,axs = pl... |
c0d28f2759817c270141f2162701d2ba4829c21106aeae3bb39500d255d84a9a | Python | 3,789 | 126 | import os
import numpy as np
from binary_motif_model import (
load_model as load_motif_model,
)
from map_protein_name import (
get_map_protein,
get_rbns_name_psam_idx_map,
)
import splice_point_identifier
from utils import prod
import torch
RBNS_MOTIFS_DIRECTORY = os.path.join(
os.path.dirname(__... |
ca36e010e37575c97b029e882ec79c02b602c3d3feb39c073e96167d72f107ef | Python | 3,789 | 134 | # --- 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 Title(_BaseTraceHierarchyType):
_parent_path_str = "indicator"
_path_str ... |
9cdeb0715d03c3fac38933677f545b6991e0e4f3a86d4037bffc33f07da290c1 | Python | 3,790 | 82 | """
Read PyTorch model from .pth.tar checkpoint.
Code from:
https://github.com/rgeirhos/texture-vs-shape/blob/master/models/load_pretrained_models.py
Accessed 02.03.2020
## Architecture modified by jfeather for metamer code compatability##
"""
import os
import torch
from torch.utils import model_zoo
from .resnet imp... |
eae6884effd20e080a64725aeda6310efae1c612a0af843a1a8c716fd52fa324 | Python | 3,790 | 86 | from typing import Optional
from uuid import UUID
from carbonserver.api.errors import AuthenticationError
from carbonserver.api.infra.repositories.repository_emissions import (
SqlAlchemyRepository as EmissionRepository,
)
from carbonserver.api.infra.repositories.repository_experiments import (
SqlAlchemyRepos... |
eb8115544ed824e94a1647107d007436ba173726925d6d5ca75256cb651d2865 | Python | 3,791 | 93 | import numpy as np
import pandas as pd
import pickle
import argparse
import logging
from time import sleep
parser = argparse.ArgumentParser()
parser.add_argument('-f', "--file",
default='data/example_df.csv',
type=str,
help='csv file including 77 variables ... |
0b1d652126a75f23001150ba20214c7b7bcee7b34ff3b9047090ac3ab4d3854b | Python | 3,792 | 113 | import numpy as np
import torch
from torch import nn
from neurogym.wrappers.components.modules import LayerProbeBase
class ActivationProbe:
def __init__(
self,
module: nn.Module,
steps: int | None = None,
name: str | None = None,
populations: set[str] | None = None,
):... |
7141b320e8dadec766102f5711bb8d0c87932df00378a457a12f3904537f5c96 | Python | 3,792 | 146 | # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
"""Miscellaneous file manipulation functions."""
import os.path as op
import numpy as np
from nipype import logging
from nipype.utils.misc import is_container
fmlogger = logging.getLogger('nipype.utils')... |
081ee89837de1ee7e0f73d3913f509d6b9cc6279985ceb24a228074f1b9ad9a7 | Python | 3,793 | 121 | import numpy as np
from numpy.random import default_rng
import pathlib
from mpi4py import MPI
from causal_optoconnectics.tools import conditional_probability, joint_probability, roll_pad
from causal_optoconnectics.generator import (
construct_connectivity_filters,
construct_connectivity_matrix,
simulate,
... |
187922065b773e32fe029fbf25f20c4a307764e6bef7c5d98e2c8ca38fe906f3 | Python | 3,793 | 153 | import os
import yaml
import pickle
import inspect
import datetime
import contextlib
import joblib
from rich.console import Console
from rich.progress import (
BarColumn,
MofNCompleteColumn,
Progress,
SpinnerColumn,
TaskProgressColumn,
TextColumn,
TimeElapsedColumn,
TimeRemainingColumn,... |
2d529032a3c5abc8539831eb2479403a3203b6e6a207954236f9c576d02bc9d4 | Python | 3,793 | 128 | from pathlib import Path
from typing import Literal
import pandas as pd
from hobj.data.download import resolve_data_root
# %%
def load_human_behavior(
experiment: Literal["highvar", "oneshot"] = "highvar",
cachedir: Path | None = None,
) -> pd.DataFrame:
"""Load trial-level human behavior for one of the... |
b46dfd5f401a96ac2c1a118ca494b6f94bfe6010587c6ff64cb113e9d33c46a0 | Python | 3,793 | 116 | # --- 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 = "histogram.unselected"
... |
3b56e4b509516827980ca5f6365d3fea7cd0f669edd1bcd842b48402ac7fda1a | Python | 3,794 | 44 | from .base_options import BaseOptions
class TrainOptions(BaseOptions):
"""This class includes training options.
It also includes shared options defined in BaseOptions.
"""
def initialize(self, parser):
parser = BaseOptions.initialize(self, parser)
# visdom and HTML visualization para... |
c2cdca6ceb036dcc32d96ff5d1ea10c3e9347334ae38be5ed3e2018dcdee0f56 | Python | 3,794 | 111 | import datetime
from typing import TYPE_CHECKING
import numpy as np
import requests
from carbontracker import exceptions
from carbontracker.emissions.intensity.fetcher import IntensityFetch, IntensityFetcher
if TYPE_CHECKING:
from carbontracker.loggerutil import Logger
API_URL = "https://api.carbonintensity.org... |
cb57244aa6bcb472ac04a3c0605d43c16a61627d397f0fef8ffe683e25d704de | Python | 3,794 | 116 | """Portable I/O primitives for TorchLens model logs (declared re-export FACADE).
The ``torchlens._io`` package implements TorchLens' portable save/load path:
it scrubs a ``Trace`` into metadata plus tensor blobs, writes directory
bundles backed by ``safetensors``, and rehydrates those bundles into eager or
lazy model ... |
e5706c411c7c2dd7926404ee2f8a9865023fe9059217e488ee2311be75b78a15 | Python | 3,794 | 83 | import sys
# setting path
sys.path.append('../TM2_segmentation')
import os
import numpy as np
import nibabel as nib
import itk
import pandas as pd
import tarfile
from scripts.preprocess_utils import find_file_in_path
# load metadata file
input_annotation_file = 'data/csv_files/calgary.csv'
df = pd.read_csv(inp... |
f0f284ae415db3c2920d91d1b5873704f85ce7c466dadfa3d525565b35fafb63 | Python | 3,795 | 105 | """Persistence honesty: save levels may not silently override explicit include flags.
WT1 A-IV item 19 (lane A08): ``level="executable_with_callables"`` used to
silently force ``include_saved_args=True`` / ``include_rng_states=True`` over an
EXPLICIT ``False`` -- shipping raw input tensors against an explicit opt-out.... |
07a43fee186d858b621921bcbe2cd0a875b07c04607962c30d5cbd0bfd431cc5 | Python | 3,796 | 180 | # Copied from
# https://github.com/plotly/plotly.js/blob/master/src/components/colorscale/scales.js
# NOTE: these differ slightly from plotly.colors.PLOTLY_SCALES from Plotly.js because
# those ones don't have perfectly evenly spaced steps ...
# not sure when this skew was introduced, possibly as early as Plotly.py v4... |
73a75d02afde8bbbdd982c76309b5bdfb7e8c41d712895e33dda8129cda3e955 | Python | 3,796 | 132 | import os.path as opath
import json
import _plotly_utils.basevalidators
from codegen.utils import PlotlyNode, TraceNode
def get_validator_params(node: PlotlyNode, store: dict):
"""
Get params for the validator instance for the supplied node
and add them to the store.
Parameters
----------
no... |
78a860b506e3262c0e26b486d7f59d71ad9db258ee86ff1bb30dcd9dfc82e236 | Python | 3,796 | 101 | """
Author: Bruno De Santi, PhD
Affiliation: Multi-modality Medical Imaging Lab (M3I Lab), University of Twente, Enschede, The Netherlands
Date: 20/09/2023
Description: Collection of visualizing techniques used in MUVINN-reg
Paper/Project Title: Automated three-dimensional image registration for longitudinal photoaco... |
aa570491e7a76a292a2d08b521148c006ee180e1bf1b85c74314ec2dd7c7d09e | Python | 3,796 | 115 | """Multi-Sensory Integration."""
import numpy as np
from neurogym.core import TrialEnv
from neurogym.utils import spaces
# TODO: This is not finished yet. Need to compare with original paper
# TODO: In this current implementation, the two stimuli always point to the
# same direction, check original
class MultiSens... |
aaf458f852346c70971b8aadfa92e60a59d25c8a6b566575f15700644e8b3e22 | Python | 3,796 | 98 | # Copyright 2017 The TensorFlow Authors All Rights Reserved.
#
# 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... |
b23f3639b34d3dfa157147f0c903724ed2f63af570075334fb1f1b696ed99cda | Python | 3,796 | 152 | import pytest
from pyrosm import get_data
import sys
def get_source_url(name):
name = name.lower()
from pyrosm.data import sources
for source, available in sources.available.items():
if source == "cities":
available = [src.lower() for src in available]
if name in available:
... |
40020ca452bf6b212126f211559de11f6dc55a529ab49ae4c2798af7078c9c83 | Python | 3,797 | 114 | from array_api_compat import array_namespace as get_namespace, device as xpd
import numpy as np
import pytest
from conftest import approx, assert_array_equal
from pyriemann.geometry.ajd import ajd, ajd_pham, jade, rjd, uwedge
@pytest.mark.parametrize("kind", ["sym", "spd"])
@pytest.mark.parametrize(
"method, alg... |
551286a7119d5f62c9e8ba5435d20607bccf6a8b236773f37ab76f446c467003 | Python | 3,797 | 100 | import numpy as np
from keras.src import backend
from keras.src import ops
from keras.src import testing
from keras.src.optimizers.rmsprop import RMSprop
class RMSpropTest(testing.TestCase):
def test_config(self):
optimizer = RMSprop(
learning_rate=0.5,
rho=0.8,
moment... |
569847797374344605aa86bdad0893852b114902f97d1507e350374048768379 | Python | 3,797 | 107 | from argparse import ArgumentParser
import torch
from pytorch_lightning import LightningModule, Trainer
from torch.nn import functional as F
from torch.utils.data import DataLoader, random_split
from pl_bolts.datasets import MNIST
from pl_bolts.utils import _TORCHVISION_AVAILABLE
from pl_bolts.utils.warnings import w... |
cbcabfb46559524b6a6d68ac764f63eec315bbe78096155385d100cf9f852e4d | Python | 3,798 | 120 | import torch
import tqdm
from modular_splicing.utils.io import load_model
from modular_splicing.motif_names import get_motif_names
from modular_splicing.utils.io import save_model
from .rbns_data import RBNSData, MotifModelBasedClassifer
# TODO document how to get this data
data_path = "../data/500k_binary_rbns_dat... |
b912eb3b69797eb56e7a9604ed18ca67919351627c19905b53961ad6d0a56ee8 | Python | 3,800 | 115 | from collections.abc import Callable, Mapping
from types import MappingProxyType
from typing import Any, Literal
import numpy as np
import scanpy
from anndata import AnnData
from numpy.random import RandomState
_Method = Literal["umap", "gauss"]
_MetricFn = Callable[[np.ndarray, np.ndarray], float]
# from sklearn.met... |
ec5295e221bf26559793ebee09548ca11b39e8a0bee8eed91506e5008dd9031e | Python | 3,800 | 114 | # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# 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 app... |
8d2c7c4bd7e9e06f8fb6819a8ac36548d9e337c62e0b9e16f665913f56bb1f8e | Python | 3,801 | 120 | """Tests for bdpy.recon.torch.modules.encoder."""
import unittest
import torch
import torch.nn as nn
from bdpy.dl.torch.domain.image_domain import Zero2OneImageDomain
from bdpy.recon.torch.modules import encoder as encoder_module
class MLP(nn.Module):
"""A simple MLP."""
def __init__(self):
super(... |
bbaba842903e51272674e19eb002321ef9a95b9581dcca3fd8a1557b743c998b | Python | 3,801 | 94 | #!/usr/bin/env python
"""
convert fastqsolexa file to separated sequence and quality files.
assume each sequence and quality score are contained in one line
the order should be:
1st line: @title_of_seq
2nd line: nucleotides
3rd line: +title_of_qualityscore (might be skipped)
4th line: quality scores
(in three forms: a... |
02aee1c4717c9483f196165252af84a4a3cf8c5b712e1418f5dba5f8058101e9 | Python | 3,802 | 112 | from __future__ import division
import unittest
import numpy as np
from wyrm.processing import apply_spatial_filter
from wyrm.processing import swapaxes
from wyrm.types import Data
SAMPLES = 1000
CHANS = 3
EPOS = 5
class TestApplySpatialFilter(unittest.TestCase):
def setUp(self):
data = np.random.ra... |
083644e7c71a8eaa11d9c6802fdd0d2aea6affc6c2ae8eccebf7066a8d9a8bdf | Python | 3,802 | 126 | import logging
from threading import local
from typing import (
Optional,
TYPE_CHECKING,
)
from galaxy import model
from galaxy.model import (
mapper_registry,
setup_global_object_store_for_models,
)
from galaxy.model.base import SharedModelMapping
from galaxy.model.orm.engine_factory import build_engi... |
c01bd9dfa5f0069de699b46c9ab373ea135bd1ac80ed7eae9a95a0b5df530664 | Python | 3,802 | 117 | # --- 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 Line(_BaseTraceHierarchyType):
_parent_path_str = "icicle.marker"
_path_s... |
507a6d59405c9a6b4418f7d70f9f83e6e6fedc6ee5408158351d4e43fd9b403a | Python | 3,803 | 114 | import os
import pytest
from mirp import extract_features_and_images
from mirp._images.generic_image import GenericImage
from mirp._images.mr_image import MRImage
from mirp._masks.base_mask import BaseMask
CURRENT_DIR = os.path.dirname(os.path.abspath(__file__))
@pytest.mark.ci
def test_intensity_scaling():
dat... |
91b8b594c0f9f2bdf6c0c62f40be0fbe6b0d4770b9d1069ac20f52f58545e119 | Python | 3,803 | 131 | """
utils.py: Useful utility functions.
"""
__author__ = "Louis Kang"
__date__ = "2023/03/07"
__license__ = "GPLv3"
__reference__ = "To be determined"
import os, sys
import time
import itertools
import numpy as np
import torch
import matplotlib.pyplot as plt
# Detecting if code is run from a Jupyter noteboo... |
910a91bb5d6d84062b48776ac593736cb2eeda82dd7988dc4eb5918669664f1e | Python | 3,804 | 120 | import os
import shutil
import time
import unittest
from pandas import read_csv
from codecarbon import EmissionsTracker
OUTPUT_DIR = "test_task_data"
def heavy_computation(run_time_secs: float = 3):
end_time: float = (
time.perf_counter() + run_time_secs
) # Run for `run_time_secs` seconds
whi... |
2386ff666b21cedcfdf576dee34337d9df0b8708333d3fa3e03f157f997738d0 | Python | 3,805 | 120 | import copy
import torch
import torch.nn as nn
from modular_splicing.utils.construct import construct
from modular_splicing.models.motif_models.types import motif_model_types
class AlternateDonorSeparatingMotifModel(nn.Module):
motif_model_dict = True
_input_is_dictionary = True
def __init__(
... |
6dc7eab127e5bce089540e8ac01927fd7733dce3b542aaab56b3b154a64246d8 | Python | 3,805 | 99 | """Public named-sibling receptive-field extension tests."""
from __future__ import annotations
from collections.abc import Iterator
import pytest
import torch
from support.rf_isolation import preserved_rf_registry
from torch import nn
import torchlens as tl
from torchlens.receptive_field import ReceptiveFieldDirect... |
c358140bfbebbd3f446ba1e2100c7907b29a7ed2199d1dd4e4fe3f46fe397570 | Python | 3,806 | 109 | import logging
from uuid import UUID
import jwt
from fastapi import HTTPException
from carbonserver.api.infra.repositories.repository_organizations import (
SqlAlchemyRepository as OrganizationRepository,
)
from carbonserver.api.infra.repositories.repository_projects import (
SqlAlchemyRepository as ProjectRe... |
e2ff34d6d7346ace3a3e68f3bca28f2e82f8fc05f258473c21a21347206435cb | Python | 3,806 | 120 | """ eFEL setup """
"""
Copyright (c) 2015, EPFL/Blue Brain Project
This file is part of eFEL <https://github.com/BlueBrain/eFEL>
This library is free software; you can redistribute it and/or modify it under
the terms of the GNU Lesser General Public License version 3.0 as published
by the Free Software Foundatio... |
5ed6a5b726410dbaeea53dc518207f5dd08c2037c7b7647a6a1fa637e5193036 | Python | 3,807 | 114 | # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# 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 app... |
ad3b31e40c2b15e26618d7a185a70928b1d35f538175fb4005441ad97e56207c | Python | 3,807 | 117 | # --- 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 Line(_BaseTraceHierarchyType):
_parent_path_str = "treemap.marker"
_path_... |
234e7bbef85fb6cb95d4aa0b04b2ee0063c2f601fbf92b4678f0028682be7d04 | Python | 3,808 | 131 | """Geodesics for SPD/HPD matrices."""
from .base import sqrtm, invsqrtm, powm, logm, expm
def geodesic_euclid(A, B, alpha=0.5):
r"""Euclidean geodesic between matrices.
The matrix at position :math:`\alpha` on the Euclidean geodesic
between two matrices :math:`\mathbf{A}` and :math:`\mathbf{B}` is:
... |
ab4173105c62f58ebefd50440f6039352798c4862eaec3e94db3b576b70d5f95 | Python | 3,808 | 107 | import os
import random
import torch
from torch.utils.data.dataloader import DataLoader
# from torchsummary import summary
from hn_cnn.cnn import MODELS
from hn_cnn.constants import *
from hn_cnn.data_augmentation import get_training_augmentation, TRANSFORM_TO_TENSOR
from hn_cnn.fit import predict
from hn_cnn.parse_d... |
1ef639c9f0d9220c7df74bd99f57d394d5196fc265e9524d553a6360baeec319 | Python | 3,810 | 91 | # Copyright (c) 2024 PaddleHelix Authors. All Rights Reserved.
#
# Licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0
# International License (the "License"); you may not use this file except
# in compliance with the License. You may obtain a copy of the License at
#
# http://creativecommo... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.