sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
072a3044b6bdabb232a6de4e3bc03b4a572492b4d2f8bb545cd3e9eda5fd14ba | Python | 4,831 | 145 | ''' check_neuronmetadata.py
This program will check entries in jacs:emBody with nueronbridge:neuron
'''
import argparse
from operator import attrgetter
import sys
import inquirer
from tqdm import tqdm
import jrc_common.jrc_common as JRC
# Configuration
EDEFAULT = ["fib19", "hemibrain", "hemibrain:v0.9",
... |
a038d41b7975ac41f3c9cc03628aabb4990524e9b0ef69de556c920849419e88 | Python | 4,831 | 129 | ''' find_annotation.py
Find a line, cell type or body ID in the janelia-neuronbridge-custom-annotations
DynamoDB table.
'''
import argparse
import collections
import json
from operator import itemgetter
import sys
import boto3
import jrc_common.jrc_common as JRC
#pylint:disable=broad-exception-caught,logging-... |
75b84b5080b7c866efc9a602c342ad3612c84bdb74f1fa3e2f8732680cd8de3f | Python | 4,833 | 123 | """Averaging operator."""
from collections.abc import Sequence
from warnings import warn
import torch
from mrpro.operators.LinearOperator import LinearOperator
from mrpro.utils.reshape import normalize_index
class AveragingOp(LinearOperator):
"""Averaging operator.
This operator averages the input tensor ... |
ab4514b85e4e49e631f066c61cdf9c52ca1fbc4f1cb9ad524d15c397beaafb3e | Python | 4,833 | 156 | from typing import Iterable, List, Literal, Optional, Sequence, Tuple, Union
import numpy as np
import pandas as pd
from anndata import AnnData
from matplotlib import cm
from matplotlib import pyplot as plt
from matplotlib import rcParams
from matplotlib.axes import Axes
_rankby = Optional[Literal["pvalues", "logfold... |
b6ef78d45c5ef695fd478e12214d56214e05a27718af8ccdd67982f61f8e3fe2 | Python | 4,833 | 91 | """Test Indexing helper"""
import pytest
import torch
from mrpro.utils.indexing import Indexer
@pytest.mark.parametrize(
('shape', 'broadcast_shape', 'index', 'expected_shape'),
[
((1, 6, 7), (5, 6, 7), (slice(None), torch.ones(4, 5).int(), slice(None)), (4, 1, 5, 7)), # array index #0
((1, ... |
d874ce29dd69783fe27d6161098a5cbc21458241243bcadc894acc052da0d8d7 | Python | 4,833 | 127 | # Copyright 2021 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agr... |
c9e3d12eb1613bc25725c6d2843f1e8398040c6eb82e7cea101bc967c61ca8e8 | Python | 4,837 | 108 | """Tests for `multimodal_ad.models.regions` (no TensorFlow needed)."""
import numpy as np
import polars as pl
import pytest
from multimodal_ad.models.regions import (
ATLAS_PLACEMENT,
HEATMAP_PLACEMENT,
pad_to_frame,
rank_regions,
)
def test_pad_to_frame_places_volume_at_the_expected_offset() -> Non... |
d4b6ae0ab2e08a80704db985ff74efeaa0452ffc89c4ac60997321d929c8d53f | Python | 4,837 | 126 | """End-to-end smoke tests for the supervised SIMS workflow.
These are direct ports of the three tests that used to live in
``scsims/tests.py`` (which itself never ran via pytest because the
package shipped no test runner config). The originals had two latent
bugs:
1. They referenced ``predictions["first_pred"]`` whic... |
09593cc01dea331e3cd67bd2945814092b01d0d4d4a8247e0950d52386251e64 | Python | 4,841 | 144 |
import sys
import numpy as np, matplotlib.pyplot as plt, networkx as nx, pickle, json, gzip
import pandas as pd
import itertools
N_READS = 10
N_UMIS = 9
N_HAMMING = 6
CELL_BCS_PATH = "<file path of whitelist>"
LIB_NAMES_PATH = "<file path of lib.txt>"
# cell_bcs = open(CELL_BCS_PATH).read().strip('\n').split('\n'... |
2299adbdec34463597c47959f7b04692038d233068caf5b8c4d4aa712cbf8f8c | Python | 4,841 | 141 | """
Tests for TimedeltaIndex methods behaving like their Timedelta counterparts
"""
import numpy as np
import pytest
from pandas._libs.tslibs.offsets import INVALID_FREQ_ERR_MSG
from pandas.errors import Pandas4Warning
import pandas as pd
import pandas._testing as tm
class TestVectorizedTimedelta:
def test_tdi... |
82d508cf8cb8b40699ddfc8ce71ec6192c9d2299265fc26922d418e4ee6e490b | Python | 4,841 | 108 | """PAOPAC Conventional: public author trees and cohort-dependent inference."""
import numpy as np
import torch
from sklearn.preprocessing import StandardScaler
from statsmodels.nonparametric.smoothers_lowess import lowess
from ._base_models import pyagingModel
class PAOPACTrees(torch.nn.Module):
"""Evaluate the... |
9144835aa938f3583efca194b0b93f1fdaeecfb394e1c2c1c5897d33bc2c33f0 | Python | 4,841 | 100 | import pandas as pd
import os
import sys
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from load_db.ADNI import get_adni_dx, get_visit_code
from app import create_app, db
from app.models import Subject, ... |
ae48cd1436b2c756ab59ff00e1ec4733cf753a5436dd80b87351f6989de65a40 | Python | 4,841 | 129 | # Copyright 2025 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agre... |
22b1688a70e98f8c72787402bde9b297a96710861ea9e4dd8d2b1a8bd0473d49 | Python | 4,842 | 129 | # Copyright 2024 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agre... |
fb2dd4b9ca3e6cd75a41366de7d8c639e6b9d478ebebabd179dab74c8dfa0632 | Python | 4,843 | 153 | """Serializable descriptors for models, metrics, and parameters.
These dataclasses are the primary contract between the PyCaret engine and
anything that needs to describe its capabilities to a human (via a React form,
a help text, a tutorial generator) or to an LLM (as structured context).
All fields are plain-Python... |
2d6467c2436a976171003083a6a0c18604677a407af869c0d63bdd180c569c52 | Python | 4,847 | 161 | import numpy as np
from PyQt5 import QtGui
class DarkPalette(QtGui.QPalette):
"""Class that inherits from pyqtgraph.QtGui.QPalette and renders dark colours for the application."""
def __init__(self):
QtGui.QPalette.__init__(self)
self.setup()
def setup(self):
self.setColor(QtGui.... |
e21faa10e333eff2a92485a4e4d5fb9b019d5fba14c1b3d834fb527e607d9a9f | Python | 4,848 | 122 | import importlib.resources
from pygments import highlight, lexers, formatters
from PyQt6 import uic, QtCore, QtWidgets
class LogPanel(QtWidgets.QWidget):
"""Log panel widget
Visualizes logs stored in the .rtdc file
"""
def __init__(self, *args, **kwargs):
super(LogPanel, self).__init__(*arg... |
571e0d677ada085f6a5bddfeebabc1425b8e2addba94426237201f2bb7ce8513 | Python | 4,851 | 118 | #!/home/UNIXHOME/etseng/anacondaPy37/envs/anaCogentPy37/bin/python
__author__ = 'etseng@pacb.com'
import pdb
import os, sys, math
from csv import DictReader
from collections import defaultdict, Counter
"""
Based on the script by Gloria Sheynkman for creating a BED12 file where isoforms are shaded by abundances
Read ... |
cdf6dffca59b16333b419af6dc02aef4854c3b84a8e1bdfe015b121d5bd4b67e | Python | 4,851 | 130 | import collections
import numpy as np
import pytest
from pandas.errors import Pandas4Warning
from pandas.core.dtypes.dtypes import CategoricalDtype
import pandas as pd
import pandas._testing as tm
class TestCategoricalMissing:
def test_isna(self):
exp = np.array([False, False, True])
cat = pd.... |
f3583efe77dfa3441ef7f191c13f59735f2c8337453713f5d335b6150b5953ec | Python | 4,855 | 154 | import types
import warnings
import argparse
import logging
from typing import cast
NOT_DOC = True
def doc_mode():
global NOT_DOC
NOT_DOC = False
def not_doc():
return NOT_DOC
class RST:
def __init__(self, rst) -> None:
self.rst = rst
def __str__(self) -> str:
return rst2txt... |
d86d9356eb508fcebd0137dc3deea1266e52677908082aa1943897e4c227c6a9 | Python | 4,859 | 145 | import sys
sys.path.append('.')
import queue
import os
from tkinter import *
from threading import Thread
import time
from CommonSystem.Config import Config
from PIL import Image, ImageTk, ImageGrab
class Vtkinter(Tk):
def __init__(self) -> None:
super().__init__()
... |
4d6d9ba28041aac6917694d36e41caecaf353228ed75393ae4c31b047ffde2d2 | Python | 4,860 | 127 | import ntpath
from sys import path as sys_path
#sys_path.append('..')
#sys_path.append('../base')
sys_path.append('/cis/home/kstouff4/Documents/MeshRegistration/master/py-lddmm/')
sys_path.append('/cis/home/kstouff4/Documents/MeshRegistration/master/py-lddmm/base')
import os
import multiprocessing as mp
from multiproce... |
ad46bb047f25cb99550e920de406c661ca2663555fd85e59892fb95300d4d178 | Python | 4,866 | 132 | #!/usr/bin/env python
import sys, argparse, os, glob, csv, pdb
from tqdm import tqdm
from pathlib import Path
import regex, re
import wave
import contextlib
import pandas as pd
seed=4
def get_args():
parser = argparse.ArgumentParser()
parser.add_argument('--lang', '-l', type=str, required=True)
parser.a... |
c17583c02599f5184353db81ae67242adc808f3929eb499eddaa5217f8494354 | Python | 4,866 | 130 | #!/usr/bin/python3
"""
analyze_indels.py: take GAM JSON as input and produce tables of non-softclip
indel positions in the read and lengths
"""
import argparse
import os
import sys
import time
import subprocess
import collections
import json
def parse_args(args):
"""
Takes in the command-line arguments ... |
8b8e7ca9bdf3c05375e71c5546fb99a2c9526dc7e049d14d6157ecfa9b06c07f | Python | 4,867 | 135 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jul 5 11:47:43 2023
@author: Noelia Martinez-Molina, adapted from code provided by Yonatan Sanz-Perl at CNS, UPF
"""
from numpy import genfromtxt
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.style as style
import seaborn as sn... |
18afaee25927844e1963a326bad2a91051194589df92eb61a3aca5a56bca0110 | Python | 4,868 | 100 |
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from pathlib import Path
plt.rcdefaults()
from matplotlib.backends.backend_pgf import FigureCanvasPgf
matplotlib.backend_bases.register_backend('pdf', FigureCanvasPgf)
if __name__ == "__main__":
data_dir = '/Users/eghbalhosse... |
3c8cb98305fc660f3f904964c1ddce37ec9c40455ca8f2ee5e43d4680cc1e318 | Python | 4,872 | 144 | #!/usr/bin/env python
# coding: utf-8
import warnings
warnings.filterwarnings('ignore')
import numpy as np
from torch import nn
import torch
from torchsummary import summary
import sys
from utils import *
import unet3d
from config import models_genesis_config
from tqdm import tqdm
print("torch = {}".format(torch.__v... |
6db192bfbf8ddf7640c904d897bbc818c97482a9ac1db19c9be914eb81d5af4a | Python | 4,872 | 152 | """
Compare evolutionary couplings to distances in 3D structures
Authors:
Thomas A. Hopf
"""
import numpy as np
def add_distances(ec_table, dist_map, target_column="dist"):
"""
Add pair distances to EC score table
Parameters
----------
ec_table : pandas.DataFrame
List of evolutionary ... |
d3f341e09ae53b2777675985a3ba4687bc936e30f0169dd1de473e6c649b5af9 | Python | 4,874 | 93 | import pandas as pd
import numpy as np
import statsmodels.api as sm
import statsmodels.tools.tools as sm_tools
import os
def fit_multivar_LM(es_mu, df_magma, specificity_id, cond_annotation):
'''
Fit linear model between an ESmu matrix 'specificity_id' with one extra ESmu covariate 'cond_annotation' added to each... |
b280d8433144b7030e1289b7ceb3e06d24a9e90a0dc18a1cf85c7d5a263c343f | Python | 4,877 | 187 | import os
import collections
def make_dir(directory):
"""
sensible way to create directory
Parameters:
Cursor - cptools2 - Cursor
------------
directory: string
path to the directory to be created
Returns:
--------
nothing, creates empty directory if successful, othe... |
a653b69e5878696f99716ac38ca78d1918e41513a3ea08b48b591bcd35e367f8 | Python | 4,881 | 141 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 26 15:12:17 2021
@author: ehsesp
"""
import argparse
import numpy as np
import time
import twixtools
from twixtools import map_twix
from twixtools.contrib import cfl
from twixtools.recon_helpers import remove_oversampling
cfl_order = [
'READ_DI... |
36379461d6ff2a4dd90fd87a842c96e63736453345413d8eda08e2d73b40d1e9 | Python | 4,885 | 109 | """Native 3D Grad-CAM, ported from `Heatmaps.ipynb`.
**Documented choice**: `Heatmaps.ipynb` computes Grad-CAM two ways: a
hand-written, unused 2D `make_gradcam_heatmap()` (standard single-layer
Keras Grad-CAM recipe, adapted from
https://keras.io/examples/vision/grad_cam/), and the actually-used
[`tf-keras-vis`](http... |
1d11fa49b030376566a168c491be8b52c8b180cf142ef03f84275775847f0be9 | Python | 4,888 | 127 | from typing import Iterable
import math
import numpy as np
from torch.utils.data import Sampler, BatchSampler
class SortishSampler(Sampler):
"""Returns indices such that inputs with similar lengths are close together."""
def __init__(self, sequence_lengths: Iterable, bucket_size: int, num_replicas: int = 1,... |
4160d90eb0ebe1eff4aa02d041fff5f79dc2dff672869655e23d1a2299beb753 | Python | 4,888 | 135 | import operator
class SegmentTree(object):
def __init__(self, capacity, operation, neutral_element):
"""Build a Segment Tree data structure.
https://en.wikipedia.org/wiki/Segment_tree
Can be used as regular array, but with two
important differences:
a) setting item's va... |
5882e4c3834afa7c20043492382bf189ae117159e236bca05ae6685c8547f52c | Python | 4,888 | 136 | """This script produces a figure summarising varcope smoothing."""
import os
import glmtools as glm
import matplotlib.pyplot as plt
import mne
import numpy as np
import osl
import sails
import lemon_plotting
from glm_config import cfg
from lemon_support import (get_eeg_data, lemon_make_bads_regressor,
... |
df916fa71543d3bfae66dfd730472ff286ac894b981e7e1d8b93a788ad33a619 | Python | 4,888 | 136 | # Copyright 2018-2025 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or... |
5cf689c1552377db2a75cd0b7cb5f6382e2839106b3a7a47a1d0d4f3f916dac1 | Python | 4,891 | 102 | import argparse
import sys
import os
import pickle
import pandas as pd
from cdr.config import Config
from cdr.baselines import py2ri, LM, LME
from cdr.formula import Formula
from cdr.util import mse, mae, filter_models, get_partition_list, stderr
pd.options.mode.chained_assignment = None
if __name__ == '__main__':
... |
90fd52c00e6b10855fb33096a28acca026369c4207ecf1d043037ae16a62da8c | Python | 4,891 | 142 | #
# Glucose transporters, include SGLT1/SGLT2, GLUT1/GLUT2
from values import *
import math
import numpy as np
#
# SGLT cotransporters modules
#---------------------------------------------------------------------
#This subroutine to computes the fluxes across SGLT (Na-glucose)
#cotransporters, based on the model of ... |
293fe31af88b6119a3c380942a583848b1c711396b9f5bb18de7281cb4dc2702 | Python | 4,895 | 131 | import random
from models import input_dim, output_dim
from utilities.utilities import *
import os
import shutil
oversample_foreground_percent = 0.3
dim_offset = (input_dim - output_dim) // 2
# https://github.com/MIC-DKFZ/nnUNet/blob/6d02b5a4e2a7eae14361cde9599bbf4ccde2cd37/nnunet/training/dataloading/dataset_loadin... |
9d6a432a471cad2b0294e3d7528c5b7bc73635849c6f04f000517e4c683d0b8e | Python | 4,895 | 143 | """Class for Finite Difference Operator."""
from collections.abc import Sequence
from typing import Literal
import torch
from mrpro.operators.LinearOperator import LinearOperator
from mrpro.utils.filters import filter_separable
class FiniteDifferenceOp(LinearOperator):
"""Finite Difference Operator."""
@s... |
53ef1fe8f6b3231b3e320453dd2bcad823ab9ee6eb7948f8ea7df3b6f8061dd4 | Python | 4,898 | 119 | # AUTOGENERATED! DO NOT EDIT! File to edit: nbs/06_data_augmentation.ipynb (unless otherwise specified).
__all__ = ['randomize_smiles', 'precursor_permutation_given_index', 'randomize_rxn', 'do_randomizations_on_df',
'do_random_permutations_on_df']
# Cell
import random
import math
import numpy as np
import... |
61b006cef427abad287b1f3afd989aefe34b81fed35fb6c4699f42cc6819b6c2 | Python | 4,898 | 121 | # Copyright (c) 2018-2023, NVIDIA Corporation
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this
# list of condit... |
a20a663ec0a8a5c4503228792c5b6d79cc8616679a33d6cdfb5994bf6d52970e | Python | 4,899 | 158 | import pandas as pd
import numpy as np
import math
from statistics import mean, stdev
import warnings
pd.options.mode.chained_assignment = None
def load_data(dataSheet):
metadata = pd.read_excel(dataSheet, sheet_name="metadata")
fluorescence = pd.read_excel(dataSheet, sheet_name="fluorescence")
od600 = p... |
eea82867bb49151258bc8bf9cd91003324805c1d749147a920895183a97974fe | Python | 4,899 | 158 | # coding: utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
def initialize_weights(m):
if isinstance(m, nn.Conv2d):
nn.init.kaiming_normal_(m.weight.data, mode='fan_out')
elif isinstance(m, nn.BatchNorm2d):
m.weight.data.fill_(1)
m.bias.data.zero_()
elif isi... |
b17273fa3da98216c5b858c1c72f9a734adb304e5923fa59725e652dc8d82192 | Python | 4,902 | 153 | """Cartesian trajectory class."""
from collections.abc import Sequence
import torch
from mrpro.data.KTrajectory import KTrajectory
from mrpro.data.SpatialDimension import SpatialDimension
from mrpro.data.traj_calculators.KTrajectoryCalculator import KTrajectoryCalculator
from mrpro.utils.RandomGenerator import Rando... |
74e9b1ba8dc80911c1e5a97766199c607b3e0e7b694fcd6f2f375dd1c40eb270 | Python | 4,904 | 160 | """Segmentation module."""
from abc import ABCMeta
import numpy as np
from sklearn.cluster import KMeans
class Segmentation(metaclass=ABCMeta):
"""Base class for segmentation methods.
Parameters
----------
n_segments : int
Total number of segments.
"""
def __init__(self, n_segments=... |
98b006577613e2bf8ee5f2aee8dd3c3a1bf8ad83a8d1308f1ef6cd1926cbc76f | Python | 4,904 | 119 | import os
import numpy as np
import pandas as pd
import cc3d
import datetime
import pickle
from filehandling import read_nifti, write_nifti
def load_cached_brain(settings, brain):
"""
Check if we already performed a costly connected component analysis
If so, return the name of the file (contains the numb... |
e9eef48965f05e273a35a1636ad3a7d7c486e075d0dafee572898c0e7dc381fa | Python | 4,905 | 163 | import os
import pandas as pd
import yaml
import numpy as np
import shutil
dataset_root = "/path/to/your/dataset"
image_root = os.path.join(dataset_root, "train")
export_root = os.path.join(dataset_root, "export")
num_clients = 4
iid = False
alpha = 0.5
seed = 0
n_classes = 4
class_names = [
"CNV",
"DME",
... |
8d4d2efbc509e618a46bd7125bb262045e26b8d9ade56b26c754b6ca4370ff10 | Python | 4,907 | 134 | #!/usr/bin/env python
# coding: utf-8
# In[1]:
from __future__ import print_function
import warnings
warnings.filterwarnings('ignore')
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' # or any {'0', '1', '2'}
import keras
print("keras = {}".format(keras.__version__))
import tensorflow as tf
print("tensorflow-gpu ... |
b7d8c94e8790507c93f3af8c3fd345bec224e6b1a2358218f2285d17432484a1 | Python | 4,907 | 169 | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import argparse
import pathlib
from argparse import ArgumentParser
from typing import Optional
import h5py
import numpy as np
from runstats ... |
475b96819d7967efc0e12a02893654374f316fc4815b0d1ecde80dbd725f2643 | Python | 4,909 | 177 | """Common utilities for Numba operations with groupby ops"""
from __future__ import annotations
import functools
import inspect
from typing import (
TYPE_CHECKING,
Any,
)
import numpy as np
from pandas.compat._optional import import_optional_dependency
from pandas.core.util.numba_ import (
NumbaUtilErr... |
1e8af0c6d8ff724601803bf85d803983e818f32e4b543b337caf3c3583a9d265 | Python | 4,914 | 92 | # -*- coding: utf-8 -*-
"""
wrapper for resampling and registration with Slicer
"""
import os
import numpy as np
from ..inout.inout import spacing_from_directions
from app.utils import get_exitcode_stdout_stderr, cast_to_type, end_execution, wrap_string
import nrrd
import logging
logger = logging.getLogger(__name__)
... |
2df707ff72b84bb490a80006316dea2f7bb1ae941756cb24533560141ce77f97 | Python | 4,914 | 176 | # -*- coding: utf-8 -*-
"""
Created on Wed Jan 25 14:19:27 2023
@author: jeanbaptiste
"""
import os
import copy
import numpy as np
import deepcellcontrol as dcc
from tensorflow.keras.callbacks import ModelCheckpoint, EarlyStopping
import matplotlib.pyplot as plt
#%% Parameters
# Load default params:
params = copy.... |
3d7136d5b1fb0b4a97b6ab8f374bf8a8273cfc0c941e66dcaf564376abc3c3dd | Python | 4,914 | 110 | ################################################################
import numpy as np
import matplotlib.pylab as plt
import matplotlib.gridspec as gridspec
import matplotlib
matplotlib.rcParams.update({'text.usetex': False, 'font.family': 'stixgeneral', 'mathtext.fontset': 'stix',})
matplotlib.rcParams['pdf.fonttype'] = ... |
35de67f6f5d74fb09550f7f758c75c63bd36020c24b3f0b25dc8a5aaa4b388d5 | Python | 4,915 | 176 | import logging
import argparse
from datetime import datetime
from torch import compile
from sbrnet_core.sbrnet.model import SBRNet
# from sbrnet_core.config_loader import load_config # Not needed anymore
from sbrnet_core.sbrnet.trainer import Trainer
# Get the current timestamp as a string
current_time = datetime.no... |
78a734ee2002d7333d225eaf5655dc1a7eb2fdf5211db991f4a9cf3a0d72ad86 | Python | 4,916 | 167 | """
Tests that duplicate columns are handled appropriately when parsed by the
CSV engine. In general, the expected result is that they are either thoroughly
de-duplicated (if mangling requested) or ignored otherwise.
"""
from io import StringIO
import pytest
import pandas as pd
import pandas._testing as tm
def tes... |
797d9f623883bf7adcce32752ad5dae58e6f9d753d32f42327c917bc438374a2 | Python | 4,916 | 72 | config = {
"experiment_folder": "/home/user/experiment", # Path to save outputs. Default: "/home/user/experiment"
"simulation_params": {
"scdata": "/home/user/experiment/data.h5ad", # Path to sc/snRNA-seq data, should be anndata
"save_expr": True,
"n_samples": None, # Number of samp... |
0c0295b916ebee98d8b9cb829971437c6e1fd027f6105c1f4ca7c53b7ac072f5 | Python | 4,917 | 138 | # emacs: -*- mode: python-mode; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-
# ex: set sts=4 ts=4 sw=4 et:
"""
.. _metas_estimators_and_kernels:
===================================
Combine CBMA kernels and estimators
===================================
Collection of NIDM-Results packs downloaded from... |
7782c85913277de380858f9047c6488d071429d1d1d732aec6edce8ca8239235 | Python | 4,918 | 128 | """Tests for `multimodal_ad.models.training`."""
from pathlib import Path
from unittest.mock import MagicMock
import numpy as np
import pytest
pytest.importorskip("tensorflow")
from multimodal_ad.models.architecture import Cnn3DConfig, build_3d_cnn # noqa: E402
from multimodal_ad.models.training import ( # noqa: ... |
6e2ee63e749803dd871b715de74a59805f1364feebb84222ec1f3e350439a029 | Python | 4,924 | 103 |
from ..utils import get_gene_tuples_with_ensg, PheWebError
from ..file_utils import get_filepath, get_tmp_path
from .. import conf
import re, json, shutil
from pathlib import Path
import urllib.request
import sqlite3
from typing import List, Dict, Iterable
def get_genenamesorg_ensg_aliases_map(ensgs_to_consider: Ite... |
bfcb72b39f52a060c1b22ae8af99c9dc47df4a5dc272f54f82e0e3b3849d5e23 | Python | 4,924 | 140 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Oct 24 16:01:52 2022
@author: fm02
"""
# plot results of concat_indivisual_SemCat_confusion-matrix_slurm
import numpy as np
import pandas as pd
import pickle
import seaborn as sns
import matplotlib.pyplot as plt
from scipy.stats import sem
from scipy ... |
ce85d46287966fee5d7f5b73d3523420cb3074e26814134f7ab52498702eb2e8 | Python | 4,926 | 190 | import functools
import uuid
import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
pytest.importorskip("odf")
@pytest.fixture
def ext():
return ".ods"
@pytest.fixture
def tmp_excel(ext, tmp_path):
tmp = tmp_path / f"{uuid.uuid4()}{ext}"
tmp.touch()
return str(tmp)
fr... |
169617bc6a998f64006418bb9338eb214da510228434e72f16f4eaca7fc9b62a | Python | 4,928 | 130 | import multiprocessing
import numpy as np
import sys
sys.path.append('..')
from util import window_tools
from util.stas_compute import *
from util import stas_compute
import allel
from script_real_fev import write_real_ehhbase
def write_stats_real(data_generator, fi,stats, gridNum, snpNum):
with open(... |
c02a9358f5c8a6e0f980110e1c939f23bb596d4dfb3e9de73e3f8e2ae70e95c8 | Python | 4,928 | 109 | import argparse
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
def get_args():
"""
Get arguments from command line with argparse.
"""
parser = argparse.ArgumentParser(
prog='Plot-Qualities.py',
description="""Make informative figures from pre- and post-filtere... |
315091ffed305f8b7d890630d5396a9e00c02651e2f9961783c2fdb4d363353d | Python | 4,929 | 124 | # Copyright 2018-2025 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or... |
a4bd8ab40fe8141910d54d51b2396c8750730fe3fd8cdb565c3e97908ff3440a | Python | 4,935 | 142 | ######################
### Import Library ###
######################
# My library
from molgraph.dataset import *
from molgraph.graphmodel import *
from molgraph.hyperparameter import *
from molgraph.testing import *
from molgraph.visualize import *
from molgraph.experiment import *
# General library
import os
import a... |
7a1b17b9ab6473d37facce02e719742e4e7341a2368bd84c086b5ab30100014a | Python | 4,936 | 148 | import os
import numpy as np
from math import sqrt
from scipy import stats
from torch_geometric.data import InMemoryDataset, DataLoader
from torch_geometric import data as DATA
import torch
import matplotlib.pyplot as plt
class TestbedDataset(InMemoryDataset):
def __init__(self, root='/tmp', dataset='davis',
... |
4b73fda21b8fd2bf67b11b247109ee1772d0d5f1dea66cd5227a0359637dac95 | Python | 4,937 | 174 | """
@author: mkowalska
"""
import os
import numpy as np
import matplotlib.pyplot as plt
from figure_properties import *
import matplotlib.gridspec as gridspec
from kcsd import KCSD1D
__abs_file__ = os.path.abspath(__file__)
def pots_scan(n_src, ele_lims, true_csd_xlims,
total_ele, ele_pos, R_init=0.23... |
a68fb03b30175d9374a780ece5c10254fb94227f8ab1bac11f3fb641298cc2c5 | Python | 4,937 | 139 | """
.. module:: tool_polygon
:platform: Linux, Windows
:synopsis: Polygon tool (2D only)
.. moduleauthor:: Fredrik Nysjo
"""
from tool_common import *
import numpy as np
import scipy as sp
import scipy.sparse
import scipy.sparse.csgraph
import scipy.ndimage
import glm
class PolygonTool:
def __init__(self... |
c00a426ce3b6799adcbf6a4d0e78a2711066a4a1a4e8e0c8d2030ab744cc83bc | Python | 4,937 | 125 | # %% [markdown]
# # Different ways to obtain the trajectory
# This example builds upon the <project:direct_reconstruction.ipynb> example and demonstrates three ways
# to obtain the trajectory information required for image reconstruction:
# - using the trajectory that is stored in the ISMRMRD file
# - calculating the t... |
bb70bca3764901f76c94ed2c5ad613e874d8723e69aa7e6a7bd27056215c8645 | Python | 4,939 | 131 | # -------------------------------------------------------------------------------------------------------------------------------------
# Following code curated for GCPNet (https://github.com/BioinfoMachineLearning/GCPNet):
# ----------------------------------------------------------------------------------------------... |
4f56464133f293c5504cb46bf9891e9805616632d25b5f3e14d5ab670c6c1889 | Python | 4,941 | 142 | import h5py
import numpy as np
import matplotlib.pyplot as plt
from skimage.metrics import structural_similarity as ssim
from skimage.metrics import mean_squared_error
import os
DIR = os.path.dirname(os.path.realpath(__file__))
print('> current directory: ', DIR)
# %% read in files
# fully sampled
f = h5py.File('re... |
c40a0a1aba3370adf723c1cd504c291fd96934b58e122f3f45c0e34b22731a29 | Python | 4,942 | 150 | import os
import torch
from datetime import datetime
from collections import deque
from onmt.utils.logging import logger
from copy import deepcopy
def build_model_saver(model_opt, opt, model, fields, optim):
# _check_save_model_path
save_model_path = os.path.abspath(opt.save_model)
os.makedirs(os.path.di... |
8f32181773e143893ca4a0b1795ba75c4a81b944e73e1567e01273763d23377a | Python | 4,943 | 157 | from __future__ import annotations
from datetime import (
datetime,
time,
)
from typing import TYPE_CHECKING
import numpy as np
from pandas._libs.lib import is_list_like
from pandas.core.dtypes.generic import (
ABCIndex,
ABCSeries,
)
from pandas.core.dtypes.missing import notna
if TYPE_CHECKING:
... |
642223122c3021d53ffcb5f919d571b58e665b650391b41a75fbe2537874e291 | Python | 4,948 | 148 | import numpy as np
from pandas import (
DataFrame,
Index,
MultiIndex,
Series,
date_range,
period_range,
)
class Reindex:
def setup(self):
rng = date_range(start="1/1/1970", periods=10000, freq="1min")
self.df = DataFrame(np.random.rand(10000, 10), index=rng, columns=range(... |
9492f5e875a2fb08887dc5bbd78faeef36dc2de87beb88a0a0f0ff5eef1b609d | Python | 4,950 | 142 | ######################
### Import Library ###
######################
# My library
from molgraph.dataset import *
from molgraph.simplemodel import *
from molgraph.hyperparameter_simple import *
from molgraph.testing_simple import *
from molgraph.visualize import *
from molgraph.experiment import *
# General library
imp... |
f36d06be5184bdc2544cf69674c029cb7b6ffbf1f1b26f659b4972e3191da0af | Python | 4,953 | 156 | from typing import List, Tuple, Optional, Callable, Union
import torch
from math import log, sqrt
from .types import DeviceType
GAUSSIAN_FWHM = 1 / (2 * sqrt(2 * log(2)))
SINC_FWHM = 1.206709128803223 * GAUSSIAN_FWHM
def resolution2sigma(rx, ry=None, rz=None, /, isotropic=False):
if isotropic:
fx = fy = ... |
3d35fc54ea3b46cfa2587c27bf4ccb9eba6bf8e7e114fce09ab27dde8f971d22 | Python | 4,954 | 142 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
@pytest.mark.parametrize(
"op, expected",
[
["sum", np.int64(3)],
["prod", np.int64(2)],
["min", np.int64(1)],
["max", np.int64(2)],
["mean", np.float64(1.5)],
["median", np.float... |
0ccce03f6b8428de76a5ed61165f708d6546995f0c591289af24756a25af2d53 | Python | 4,959 | 149 | """
Tests for DataFrame.mask; tests DataFrame.where as a side-effect.
"""
import numpy as np
import pandas as pd
import pandas._testing as tm
class TestDataFrameMask:
def test_mask(self):
df = pd.DataFrame(np.random.default_rng(2).standard_normal((5, 3)))
cond = df > 0
rs = df.where(con... |
fb1063daff2fa0cff52a401116fae6259748bcdbe7ae1d58f430bc38598ce110 | Python | 4,960 | 114 | # Copyright (c) 2018-2023, NVIDIA Corporation
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this
# list of condit... |
0415de7109fa706db9525cec5cef6b8dfd2af4f80ce1b024daffcc5d9f3a6a50 | Python | 4,962 | 169 | """Experiment template CRUD.
A template captures a known-good ``setup_params`` + plan defaults that a
user can pick from on the New-Experiment screen instead of filling out the
dynamic form from scratch.
Routes:
GET /workspaces/{ws_id}/experiment-templates
POST /workspaces/{ws_id}/experiment-templates
GET... |
558082914bc6575113782d74d4f2162ad851b5ca2364861d6ad7ee3f00240d5c | Python | 4,963 | 128 | # Copyright 2026 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agre... |
16b3eb0ed3d77b8b49bb9f6a10f8186e9084da152f9445fd32a2941f37ae98e4 | Python | 4,964 | 104 | import argparse
import textwrap
from pgen.esm_sampler import ESM_sampler
from pgen import models
from pgen.utils import parse_fasta, RawAndDefaultsFormatter, unalign
from pathlib import Path
import sys
import tqdm
import math
POSITIONAL_SCORE_SEP=";"
model_map = {"esm1b":models.ESM1b, "esm6":models.ESM6, ... |
9737c7e75227adeb8c9835809234698f4f5c935c9e405c14587989c836a7ebeb | Python | 4,966 | 165 | """Audit-log viewer routes.
Two surfaces:
- ``GET /admin/audit-logs`` — installation-wide, superuser only.
- ``GET /workspaces/{workspace_id}/audit-logs`` — workspace-scoped, workspace
admin or superuser.
Both support pagination (``limit``, ``offset``) + filters
(``action``, ``user_id``, ``target_... |
cbdf174225e71c84ffc4e3cafa470dd6e73c69205315476645335f3e1d1e6c7f | Python | 4,966 | 114 | import argparse
import os
import json
import random
from multiprocessing import Pool
from sklearn.model_selection import train_test_split
from tqdm import tqdm
import numpy as np
import pandas as pd
from utils.interface import cal_interface_worker
from utils.encode import encoding_worker
from utils.dataset import sa... |
36fe36272046e6a92211d6286072535371edf803988ae1a9941143ad52406936 | Python | 4,967 | 117 | from datetime import datetime
from tensorflow.keras.callbacks import TensorBoard, ModelCheckpoint, ReduceLROnPlateau
from models.model import get_net
import tensorflow as tf
import os
from training import load_data, VolumeDataGenerator
from models import input_dim
from utilities.utilities import *
if __name__ == "__ma... |
3fded205fa0f95c8c2c90dfe0c804e7277c283dd106932209a4316c54289d60d | Python | 4,969 | 167 | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
# Created by Roberto Preste
#
# mtoolnote documentation build configuration file, created by
# sphinx-quickstart on Fri Jun 9 13:47:02 2017.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration va... |
e33234d929d783f2c186c2132bc73acf93e7f64e8c4e59a51806b05e4b63a475 | Python | 4,969 | 128 | from __future__ import print_function, division
import torch
import torch.nn as nn
class ConvLayer(nn.Module):
"""
Convolutional operation on graphs
"""
def __init__(self, atom_fea_len, nbr_fea_len):
"""
Initialize ConvLayer.
Parameters
----------
atom_fea_le... |
48355927fce8fabcec126117e91e6e9df8fccb20ae4d6bc47f2572559830082d | Python | 4,973 | 169 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
@pytest.fixture
def simple_multiindex_dataframe():
"""
Factory function to create simple 3 x 3 dataframe with
both columns and row MultiIndex using supplied data or
random data by default.
"""
data = np.random.... |
909adffc3cd96995e6f44db1adc5cfd23a558125a24d73faa4fe1f373f7457df | Python | 4,973 | 107 | """Tests for `multimodal_ad.models.architecture`."""
import numpy as np
import pytest
tf = pytest.importorskip("tensorflow")
from multimodal_ad.models.architecture import ( # noqa: E402
Cnn3DConfig,
build_3d_cnn,
build_fusion_model,
build_mri_input_model,
build_pet_input_model,
extract_featu... |
fcf204b1cd0830fcb08087cba41813ecea2ebdc2128ca08103d5561be841b7f3 | Python | 4,973 | 162 | import numpy as np
import pathlib
import dclab
from shapeout2.gui import pipeline_plot
datapath = pathlib.Path(__file__).parent / "data"
def test_compute_contour_opening_angles():
contour = [
[0, 0],
[1, 0],
[0.5, np.sqrt(3)/2]
]
plot_state = {"general": {"range x": [0, 1],
... |
12949f7b0d92b8863a4eb15760d1540f37a78fab8008d1a7c7c0ede43d687e1a | Python | 4,976 | 172 | import codecs
import locale
import os
import platform
import pytest
from pandas._config.localization import (
can_set_locale,
get_locales,
set_locale,
)
from pandas.compat import (
ISMUSL,
WASM,
is_platform_windows,
)
import pandas as pd
_all_locales = get_locales()
_skip_if_only_one_local... |
c81a124c16d1eb1143c5ab5d3a36f434fd1e6f6f1823d030e09bf3ecb3ea0c68 | Python | 4,978 | 136 | # Could do old one based on
# https://github.com/mabdullah1994/Text-Classification-with-BERT-PyTorch/blob/master/Classifier.py
# Instead just use Pytorch Lightning
from pytorch_lightning.callbacks.early_stopping import EarlyStopping
from pytorch_lightning.utilities import rank_zero_only
from pytorch_lightning.loggers i... |
631fb07e9991c9319c747f705951451c5af1f5bac0a72d1016cf1f8d50e35070 | Python | 4,979 | 147 | ''' check_neuronmetadata.py
This program will check entries in jacs:emBody with nueronbridge:neuron
'''
import argparse
from operator import attrgetter
import sys
import inquirer
from tqdm import tqdm
import jrc_common.jrc_common as JRC
# Configuration
EDEFAULT = ["fib19", "hemibrain", "hemibrain:v0.9",
... |
45c8ae8ba3ec65e538e6e7f95fc982aa08b9c892d3728871f4a4b2d45d160117 | Python | 4,981 | 148 | import pytest
import pandas as pd
mpl = pytest.importorskip("matplotlib")
plt = pytest.importorskip("matplotlib.pyplot")
from pandas.plotting._matplotlib.style import get_standard_colors
class TestGetStandardColors:
@pytest.mark.parametrize(
"num_colors, expected",
[
(3, ["red", "gre... |
d7aed1523f6e41299f43ddca1e1e339ffcce969aacb23013547ec06ed9a868c3 | Python | 4,981 | 120 | import torch
from torchvision import datasets, transforms
from tnn.layers import Permute, View, LinearLayer
from tnn.networks import tFullyConnected
from tnn.loss import tCrossEntropyLoss
from tnn.training.batch_train import train
from tnn.tensor_utils import dct_matrix, random_orthogonal
from tnn.utils import seed_eve... |
1b2517e0f0f939636388961a44b59b9d84c07b840ce7e3705814d4a9f25cccaa | Python | 4,984 | 139 | # This module is mostly borrowed from Olivecrona original implementation
# (https://github.com/MarcusOlivecrona/REINVENT).
# We adpted it to pytorch0.4.0.
#
# Shuangjia Zheng, Aug 2018
#
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from data_struct import Variable
class Multi... |
1ed3b0991ba17728abd41360dcf201d89270b627f869d121ea876f0c31c34199 | Python | 4,988 | 111 | import sys
import numpy as np
import matplotlib.pyplot as plt
from game_functions import Game, Game_Bayes
import color_palette as cp
from game_functions import percentile_discrete
from os.path import join
def mean_squared_error(act, pred):
diff = pred - act
differences_squared = diff ** 2
mean_diff = differen... |
2e82a81329e3046793fe44da5ea229798fe4aa08719474fd7d94f75506998a5b | Python | 4,988 | 91 | # Copyright 2019 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# 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://w... |
4be16e505bad1da3713326879b4cda00b181f59c621fc13b1a8cb18c8447f42d | Python | 4,988 | 178 | # Copyright 2018-2025 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or... |
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