sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
7eca9176139205e3011d1c84430f4eeef62c88ef985237a328be7476175aadb6 | Python | 2,434 | 69 | import numpy as np
import pandas as pd
import pkg_resources
def mouse_symbol_to_mouse_ens(df_unmapped: pd.DataFrame, drop_unmapped: bool=False, verbose: bool=False) -> None:
"""Map dataframe index mouse gene symbol to mouse ensemble id inplace
Parameters
----------
df_unmapped : DataFrame
Data... |
eec0ab99fe77ad37eb21de20a1810b457f3c058cedb18cb6ae354af0431fac7e | Python | 2,436 | 68 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
class TestIndexConstructor:
# Tests for the Index constructor, specifically for cases that do
# not return a subclass
@pytest.mark.parametrize("value", [1, np.int64(1)])
def test_constructor_corner(self, value):
... |
696b67e0a0320256fa019d0b3ba360a9583ec63b1adbddfb14b568b85ebd0d3c | Python | 2,437 | 64 | """Create Pulseq test file with radial trajectory."""
import pypulseq
import torch
from einops import repeat
from mrpro.data import KTrajectory, SpatialDimension
class PulseqRadialTestSeq:
def __init__(self, seq_filename: str, n_k0=256, n_spokes=10):
"""A radial 2D trajectory in Pulseq.
Please n... |
cdb35f8278983bc0fe37a323f8db039bdda8a833889a0f1c37d93f32e4ff11e0 | Python | 2,438 | 67 | """RunningMeanStdObs must survive torch.jit.script -- models.py wraps it
unconditionally for dict observation spaces (regression: upstream #315
scripted the container whose forward lacked the Dict annotation, so
dict-obs + normalize_input crashed at model construction)."""
import torch
from rl_games.algos_torch.runni... |
d06bf177ddb150807726a0eca5200a06caab9d02f8a2e9e8409dd5f54b124747 | Python | 2,438 | 58 | from Common import loggingUtils
from Common.kernelFunctions import *
from Surfaces.surfaceMultiPhase import *
def compute():
outputDir = '/cis/home/younes/Development/Results/biocardSliding10test'
#outputDir = '/cis/home/younes/Development/Results/biocardStitched10'
if __name__ == "__main__":
log... |
ad9553b2913e37f1f791bf39b019fdaa2f549c7e5bfd1f07590c6a2257c5fa33 | Python | 2,439 | 62 | """Saturation recovery signal model for T1 mapping."""
from collections.abc import Sequence
import torch
from mrpro.operators.SignalModel import SignalModel
from mrpro.utils.reshape import unsqueeze_right
class SaturationRecovery(SignalModel[torch.Tensor, torch.Tensor]):
"""Signal model for saturation recovery... |
ab3b5f16c2192292c30ac5fd70053caf985de585b75749e84b1bbd1952547bac | Python | 2,440 | 70 | import copy
import yaml
class Experiment:
def __init__(self, config, experiment_config):
self.config = copy.deepcopy(config)
self.best_config = copy.deepcopy(self.config)
self.experiment_config = experiment_config
self.best_results = -100500, 0
self.use_best_prev_result = se... |
efda308d573e4f0471eae463065b5d29d53e73a7bdcad7ffab0424b488baeca5 | Python | 2,441 | 65 | #%%
import torch
# import tensorboardX as tbx
# writer = tbx.SummaryWriter('runs')
from utils.dataset import get_output, FilterData2, load_data
from utils.unet import *
from utils.model import MyNet2, Model
from utils.emd_ring_torch import emd_loss_ring
GPU_INDEX = 0
USE_CPU = False
if torch.cuda.is_available() and no... |
c25f9d2e851adcfa8b558c76ff0c00d88f41e7f95ec5bd1bf781fbf1581744f9 | Python | 2,442 | 67 | """
Tests for the Table of Correlated Phenotypes feature
Verifies that the sample file is correctly combined with phenotype information
"""
import os
import shutil
import pytest
from pheweb.load import pheno_correlation
from pheweb import weetabix
# Simplified files for testing purposes
CORREL_FILE = os.path.join... |
800832f394bb4604123bd93b0baa971b2b52ea227156ba3e9a7eea73f2728691 | Python | 2,443 | 60 | # -------------------------------------------------------------------------------------------------------------------------------------
# Following code curated for GCPNet (https://github.com/BioinfoMachineLearning/GCPNet):
# ----------------------------------------------------------------------------------------------... |
f12159adc54769e32355fb0688cb926e6adb6714ba7be69a39e5500dc4807477 | Python | 2,443 | 70 | # MOFTransformer version 2.0.0
class CLICommand:
"""
Download pre-trained model, database, and fine-tuned model
"""
@staticmethod
def add_arguments(parser):
from moftransformer.utils.download import (
DEFAULT_PRETRAIN_MODEL_PATH,
DEFAULT_COREMOF_PATH,
... |
a718a7fc9f8b098efb0b6d814885056a4bc75a26e57b974507f152d9cccf9720 | Python | 2,444 | 85 | from pathlib import Path
import pytest
import tbparse
from omegaconf import DictConfig, ListConfig, OmegaConf
from lightning_pose.train import train
pytestmark = pytest.mark.gpu
def _get_base_cfg(cfg):
# Smallest possible test: two steps per epoch.
return OmegaConf.merge(
cfg,
{
... |
dfa80d0b798ffe40746f6b97cb9bf7f57208243087ab31d6b6fe77705103b4c0 | Python | 2,444 | 80 | """
Modified from: https://github.com/milesial/Pytorch-UNet
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
def double_conv(in_channels, out_channels, mid_channels=None):
if not mid_channels:
mid_channels = out_channels
return nn.Sequential(
nn.Conv2d(in_channels, mid_ch... |
41e968584ae76883fa13673c992fe29c58cca30edc73ee4987712eaa3a9977d7 | Python | 2,445 | 69 | import os
from cptools2 import utils
import pandas as pd
import numpy as np
CURRENT_PATH = os.path.dirname(__file__)
TEST_PATH = os.path.join(CURRENT_PATH, "example_dir")
TEST_PATH_PLATE_1 = os.path.join(TEST_PATH, "test-plate-1")
def test_flatten():
"""utils.flatten(list)"""
test1 = [[1, 2, 3], [4, 5, 6], [... |
6903e926c78fe326b908421a95f27e66c15b303f46a9298580042c42e2e6ef1c | Python | 2,445 | 105 | """
Benchmarks for code in pandas/_libs, excluding pandas/_libs/tslibs,
which has its own directory.
If a PR does not edit anything in _libs/, then it is unlikely that the
benchmarks will be affected.
"""
import numpy as np
from pandas._libs.lib import (
infer_dtype,
is_list_like,
is_scalar,
)
from pand... |
83d0ceb0284816cbec006f6ec95322d0a5989ffdba61dac49b2b1468f54d40ef | Python | 2,445 | 75 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
class TestCopy:
@pytest.mark.parametrize("deep", ["default", None, False, True])
def test_copy(self, deep):
ser = pd.Series(np.arange(10), dtype="float64")
# default deep is True
if deep == "default":
... |
f5c7d527b4e142eb0d9dc0cbe7aa4172d09d7f7d389498ed29e9767bdcfad689 | Python | 2,445 | 64 | import numpy as np
import pandas as pd
import sys
def interp(x):
dtype = x.dtype
vals = x.values
ref = 0
for i, v in enumerate(vals):
if not np.isfinite(v):
vals[i] = ref
else:
ref = v
return pd.Series(x, dtype=dtype)
evmeasures_path, itemmeasu... |
052ecbd2d7e7dcab5da85cfbbd75f00147c1561ca47e1110ea8a3bd38bd97e19 | Python | 2,446 | 84 | """Tests for gradec.plot module."""
import matplotlib as mpl
import numpy as np
from gradec.plot import plot_cloud, plot_radar, plot_surf_maps
def test_plot_radar(tmp_path_factory):
"""Test plotting radar chart."""
tmpdir = tmp_path_factory.mktemp("test_radarplot.png")
corrs = [0.8, 0.6, 0.4, 0.2]
... |
5c0eba74ac7df93c7e83c2480ce00ee6426ba1b8f3bd5ba4b7c801ed25452d09 | Python | 2,446 | 74 | """Anthropic Claude provider.
Uses Claude's native *tool-use* feature to force a JSON response that matches
`output_schema`. The tool is declared inline per-call with the schema; we
consume the first `tool_use` block the model emits.
Imports the ``anthropic`` SDK lazily so the base server install doesn't
depend on it... |
a57b2518c7006c41d94c07319f0d71fd69be341f4db78a028b0d9afb24687689 | Python | 2,447 | 91 | """
This script demonstrates
* the multi-shell sampling pattern for diffusion MRI.
Author: Zhengguo Tan <zhengguo.tan@gmail.com>
"""
import matplotlib.pyplot as plt
# from mpl_toolkits.mplot3d import Axes3D
import numpy as np
from sigpy.mri import dvs
import os
fontsize1 = 12
fontsize2 = 16
# %% Import and Plot... |
fbf6ab35958dcfbb37c66b5de5fc55f6cd1bf00d32cd7f526c9dc47a0e39cc9d | Python | 2,447 | 77 | """
Created on November 10, 2019
functions for writing/reading data to/from disk
@modified_by: Soroosh Tayebi Arasteh <soroosh.arasteh@fau.de>
"""
import yaml
import numpy as np
import os
import warnings
import shutil
import pdb
def read_config(config_path):
"""Reads config file in yaml format into a dictionar... |
9fd42a2c3adfdb3a9d1a4ba7013b36ae90a129cf4e6622a5ae7a3f1db49df33a | Python | 2,450 | 65 | import tensorflow as tf
import model
# maybe needs to be None?
BATCH_SIZE = 1
def get_per_subword_surprisal(*, corpus, hparams, encoder):
start_token = encoder.encoder['<|endoftext|>']
context = tf.fill([BATCH_SIZE, 1], start_token)
def step(hparams, tokens, past=None):
lm_output = model.model(h... |
191e4e1f05f44c5411dfa9ae1f2130973101a1a25e7bc5fd483b0befe24a9a1f | Python | 2,453 | 70 | import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.model_selection import GridSearchCV
from sklearn.metrics import mean_squared_error, r2_score, mean_absolute_error
import logging
# %% binning
def bin_data(df, col_name, min_val=0.0, max_val=100.0, step=2.5):
""... |
65c7a022ccd672adfb3069973171afc925fb2a1c7c47ab1e704b18267b1fb58d | Python | 2,453 | 65 | """Returns the trajectory saved in an ISMRMRD raw data file."""
from collections.abc import Sequence
import ismrmrd
import torch
from mrpro.data.KTrajectory import KTrajectory
from mrpro.data.SpatialDimension import SpatialDimension
from mrpro.utils.reshape import unsqueeze_at
class KTrajectoryIsmrmrd:
"""Get ... |
9846413117130dcd2b272fdf6354247a600955505630ebb6b7da52a5986babf8 | Python | 2,453 | 75 | # -*- coding: utf-8 -*-
from copy import deepcopy
import numpy as np
__all__ = ["State"]
class State(object):
"""The state of the ensemble during an MCMC run
For backwards compatibility, this will unpack into ``coords, log_prob,
(blobs), random_state`` when iterated over (where ``blobs`` will only be
... |
34dd0f2ecff7b53fed8d679fdcf45f855bd322405460359fcd73297dd793cbf9 | Python | 2,454 | 76 | #!/usr/bin/env python3
"""
trim-gam.py: trim GAM records from JSON standard input to contain only mappings to nodes in the given range.
Range end is exclusive.
usage: vg view -aj input.gam | trim-gam.py 123 456 | vg view -JGa - >output.gam
"""
import sys
import json
import base64
def mapping_to_length(mapping: dict... |
ea2837c28791f0de7011ce8e49347a1a94b52629293390da04b818e309f084f8 | Python | 2,454 | 63 | """
signal.py
Created February 17, 2021
Provides methods for converting images of leads into signal data.
"""
from typing import Callable
from ecgdigitize.image import BinaryImage, ColorImage
from .. import common
import numpy as np
def extractSignalFromImage(
image: ColorImage,
detectionMethod: Callable[[C... |
92dff4d0b1e6524a2ced81e02e67f3689e632d08945345671ef937213ad433f1 | Python | 2,455 | 75 | __all__ = ["PeptideMS2SpectrumProto", "PeptideMS2Spectrum"]
import itertools
from dataclasses import dataclass
from typing import Any, Iterable, Optional, Protocol, Tuple, Union
import numpy as np
import numpy.typing as npt
from ..common.spec import IntensityArray, MzArray, MS2SpectrumProto
ChargeArray = Union[npt.... |
77f5dc311010f6bfbec8800059274930be8a796824b32e6a44d157698d413100 | Python | 2,456 | 84 | import pytest
from pandas.util._validators import validate_args_and_kwargs
@pytest.fixture
def _fname():
return "func"
def test_invalid_total_length_max_length_one(_fname):
compat_args = ("foo",)
kwargs = {"foo": "FOO"}
args = ("FoO", "BaZ")
min_fname_arg_count = 0
max_length = len(compat_... |
cf81d317d22a4cd015f9f8673be3dd2794e3732c1707039d889a47a55a2b8512 | Python | 2,456 | 81 | # 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... |
9a5119e21157ddb5759dee4886202d4939d7e29b9984bf8ce6efedbf76884641 | Python | 2,457 | 88 | import numpy as np
from collections import defaultdict
class LinearValueProcessor:
def __init__(self, start_eps, end_eps, end_eps_frames):
self.start_eps = start_eps
self.end_eps = end_eps
self.end_eps_frames = end_eps_frames
def __call__(self, frame):
if frame >= self.end_... |
aa0c79080b22da3ea32fa1861cd3891f3c861d99f76963337aec7c5df0322f9c | Python | 2,459 | 59 | """Command-line interface for the error command.
"""
from atropos.commands.cli import BaseCommandParser, writeable_file
from atropos.io import STDOUT
class CommandParser(BaseCommandParser):
name = 'error'
usage = """
atropos error-se input.fastq
atropos error -pe in1.fq -pe2 in2.fq
"""
description = """
Es... |
eb9d603c78c1e5849be17a05435f7ad57ce68fbe76385dfa1e355a616ce97931 | Python | 2,459 | 87 | # 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... |
2342a3a31cacfd87dcbae12b4a7c3de51a4bbbc10db2efff91f99bcc1d978552 | Python | 2,460 | 91 | # ---
# jupyter:
# jupytext:
# text_representation:
# extension: .py
# format_name: percent
# format_version: '1.3'
# jupytext_version: 1.16.0
# kernelspec:
# display_name: Python 3 (ipykernel)
# language: python
# name: python3
# ---
# %%
from pathlib import Path
import sys... |
462914ba8bf241d47b43f81cdfc5cd670e56a5428b3ebe8b80c7233a28169775 | Python | 2,460 | 71 | import numpy as np
import pytest
from pandas._libs.tslibs import IncompatibleFrequency
import pandas as pd
import pandas._testing as tm
class TestSearchsorted:
@pytest.mark.parametrize("freq", ["D", "2D"])
def test_searchsorted(self, freq):
pidx = pd.PeriodIndex(
["2014-01-01", "2014-01-... |
b0084eae7b77cc283b23a251477c07fb3225bb42b3b8f169fe90fcf7a62944de | Python | 2,460 | 43 | import sys, re, argparse, pandas as pd
argparser = argparse.ArgumentParser('''Collapses user-specified numeric per-event measures from *.evmeasures input into per-item median and mean measures. Unspecified columns are assigned the first value encountered in the input data table for each item.''')
argparser.add_argument... |
7cb7e4a3226df66069a11e6725c85f40bd0a0531835b58766a83fc56b6030224 | Python | 2,461 | 89 | import copy
import os
from typing import cast
import numpy as np
import pandas as pd
from sklearn.base import BaseEstimator
from sklearn.model_selection import GridSearchCV, KFold
import statsmodels.api as sm
from scipy.interpolate import interp1d
from sklearn.isotonic import IsotonicRegression
from sklearn.linear_mode... |
dd466e7d22d33301251816f1860774f47f41abff3ca14bff29d8fb204395abc2 | Python | 2,463 | 66 | import os
import time
import concurrent.futures
import json
apkinfo_api = [] #存放一组字典信息
apkfilename = []
path = r'E:\pythonProject\Experiment\out_benign_samples'
apk_list = os.listdir(path)
for apk in apk_list:
apk = os.path.join(path, apk)
apkfilename.append(apk)
apiheadlist=["Landroid/", "Lcom/a... |
5519466145ac746da1ce1be1be8455ffbe5f4e1ca44fb3b83f7ab5773a710909 | Python | 2,464 | 74 | __all__ = [
"PeptideFragmentTypeInfo",
"PeptideFragmentTypeCollection",
]
import os
from dataclasses import dataclass
from typing import Dict, Mapping, Optional
from ...util.io.yaml import load_yaml
from ..common.elements import ElementCollection, ElementComposition
@dataclass(frozen=True)
class PeptideFrag... |
b155719a8a08f918bddcad3546c1aa3f3f23a6f8782632f4cbaed0b44db9b027 | Python | 2,464 | 49 | from Environment_ui import *
def concat(image_list, save_path, index, param):
start_x, start_y= 0, 0
restored_array = np.zeros((int(param['Network_input_z']), int(param['Patch_weight_num'])*int(param['Network_input_x_y']),
int(param['Patch_height_num'])*int(param['Network_input... |
1e5517e85f7b2157327261566db1b1a37ba58fd9c23cf3111e89ae3f6f88dc57 | Python | 2,465 | 63 | """Mono-exponential decay signal model."""
from collections.abc import Sequence
import torch
from mrpro.operators.SignalModel import SignalModel
from mrpro.utils.reshape import unsqueeze_right
class MonoExponentialDecay(SignalModel[torch.Tensor, torch.Tensor]):
"""Signal model for mono-exponential decay."""
... |
584a7559d0c09a15d809d72c8501ab3a7c79e165c344430b816a72f516b65b4f | Python | 2,465 | 69 | #!/usr/bin/env python3
'''
This script is for getting more test data.
In theory I could just make random variants from the reference, but I don't have an `hg19.fa` on hand.
'''
import csv
import requests
import random
import re
import itertools
def format_float(x):
if x >= 0.01: return '{:.3}'.format(x)
rv =... |
7013f848a65b160a8ee90bba56b687e744471d0327a95d6cc70d0be35544df07 | Python | 2,465 | 84 | from xml.etree import ElementTree
from os import path
import re
import json
from tensorflow.keras import utils
FILENAME = path.dirname(__file__) + "/CVATdata/annotations.xml"
def split_coord_string(s):
pairstrs = s.split(';')
strpairs = list(map(lambda pair : pair.split(','), pairstrs))
coordpairs = list... |
55c9e8bc5f24f60399a2643c6f85a56ed355886c8119ed2cf732375d30246e5a | Python | 2,468 | 77 | import argparse
from timeit import default_timer as timer
import matplotlib.pyplot as plt
import pandas as pd
import SimpleITK as sitk
import torch
from src.model import ProbabilisticModel
def predict(opt):
"""Predict on CPU using sample data."""
print("Load the model...")
if opt.model == "resnet":
... |
dd5b4d8a418320636cd88f6358637e5f4b94e6ec72ef788e382437b625479371 | Python | 2,468 | 72 | import os
from cptools2 import filelist
CURRENT_PATH = os.path.dirname(__file__)
TEST_PATH = os.path.join(CURRENT_PATH, "example_dir")
TEST_PATH_NEW = os.path.join(CURRENT_PATH, "example_dir_new_paths")
def test_files_from_plate():
"""see if we get image files from a plate directory"""
plate_path = os.path.j... |
e6c1b5d8795bc325ce4325795ec91de0f2e3bb789ead4f815586860b2e44d3bc | Python | 2,468 | 95 | # -*- coding: utf-8 -*-
"""
This script generates plots for Figure 1
Note that it uses microscopy images and can not be reproduced from the zenodo
archive data only.
Created on Tue Sep 13 16:19:56 2022
@author: jeanbaptiste
"""
import sys
import numpy as np
import cv2
import matplotlib.pyplot as plt
import deepcell... |
1d64001fd00691e739ec6549be57a33b2e7767ab27bf43f877d310d566d3bb6e | Python | 2,470 | 71 | import numpy as np
import pytest
from pandas.core.dtypes.common import is_float_dtype
import pandas as pd
class TestSetValue:
def test_set_value(self, float_frame):
for idx in float_frame.index:
for col in float_frame.columns:
float_frame._set_value(idx, col, 1)
... |
1f5ec560b52df20a92ab025e3b662f130d8e534d4f42d976a09d2d73983a70ce | Python | 2,471 | 80 | #!/usr/bin/env python3
"""
Cluster items by transitive closure of pairwise associations.
Conceptually, we are given a series of pairwise "connections" -- a pair of
items which should be in the same cluster. We group any items for which there
is a pairwise connection in a cluster.
Note: this is a quick-and-dirty imple... |
a923789bb99a9143f31acf8c589647da659742b938c27ce00453438a80aadc25 | Python | 2,471 | 69 | # -*- coding: utf-8 -*-
"""
Reference for colormaps included with typhon.
The original version of this script [0] is provided by Matplotlib.
This reference example shows all colormaps included with typhon. Note that
any colormap listed here can be reversed by appending "_r" (e.g., "pink_r").
These colormaps are divid... |
c8dc61506bdf722f3204aec37cdc1bd919b722d15b80d9b14dad0e23bc26bc6e | Python | 2,471 | 92 | import numpy as np
import vegas
import math
import gvar as gv
from outputsplitter import log_stdout, unlog_stdout
def f(x):
dx2 = 0
for d in range(4):
dx2 += (x[d] - 0.5) ** 2
return math.exp(-dx2 * 100.) * 1013.2118364296088
# save
gv.ranseed(12578)
log_stdout('eg9a.out')
integ = vegas.Integrator... |
2b5c6bfc10610b4c9166248da3111ea408ef3bb1da51ffc18ace6165898a5d45 | Python | 2,472 | 72 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
from pandas.api.types import is_scalar
class TestSeriesSearchSorted:
def test_searchsorted(self):
ser = pd.Series([1, 2, 3])
result = ser.searchsorted(1, side="left")
assert is_scalar(result)
assert... |
fb43d7a5062b3786dd81ad9a2ac085154f4eb2865ee9d3cff665d973c4d37b48 | Python | 2,472 | 59 | from src.cv import CVGenerator, CVSpec
from sklearn.model_selection import GridSearchCV
from sklearn.model_selection import KFold, RepeatedStratifiedKFold
N_SPLITS = 5
N_REPEATS = 1
RANDOM_STATE = 42
SHUFFLE = True
def test_cv_spec():
cv_spec = CVSpec(n_splits=N_SPLITS, n_repeats=N_REPEATS, random_state=RANDOM_S... |
dc155e41d5bdb7051eb7f6bc0fc98bae9ac713ba32197d2ffc73a23831e73fcf | Python | 2,473 | 84 |
import numpy as np
from loess import loess_1d
import pathlib
from sklearn.ensemble import IsolationForest
from matplotlib import pyplot
import glob
from skimage.filters import threshold_isodata
MIN_AREA = 1000
MIN_WIDTH = 15
def get_stem(filename: str) -> str:
return pathlib.Path(filename).stem
def load_meas... |
1a60df3d380d22c5aa6480c56e3de3b6300a641b339dff84564c009685fca010 | Python | 2,475 | 91 | #!/usr/bin/env python3
import subprocess
# commands to include
######### If you add to this, also add it to the intro section of vgmandmd.desc.md
cmds = ['align', 'annotate', 'augment', 'autoindex', 'bench-dist-query',
'benchmark', 'call', 'chains', 'chunk', 'circularize', 'clip',
'cluster', 'combine'... |
3300d9b435cf396f75dc14a9258083d238dca6b2970ae61da78bfbd34e0760aa | Python | 2,475 | 85 | """
This version computes summary statistics for regions of real data along the
genome.
Authors: Rebecca Riley, Sara Mathieson
Date: 12/14/22
"""
# python imports
import math
import numpy as np
import random
import sys
sys.path.insert(1, "../")
sys.path.insert(2, "../plotting/")
# our imports
import global_vars
impo... |
15ebe94eeb2878dd82f6a399c680eab0d8135f9e8060e5a0815bc15dad947c3e | Python | 2,476 | 49 | #! /usr/bin/env python
##############################################################################
## DendroPy Phylogenetic Computing Library.
##
## Copyright 2010-2015 Jeet Sukumaran and Mark T. Holder.
## All rights reserved.
##
## See "LICENSE.rst" for terms and conditions of usage.
##
## If you use this wo... |
a63e6d750c8e33444d815d3e9081dc7b9fb5d18b1319c2447a437d44af59fded | Python | 2,476 | 79 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Jun 4 11:50:50 2023
@author: tomas
"""
import pathlib
import math
import random
import numpy as np
from cine import Cine
import tube2
from skimage.io import imshow
from matplotlib import pyplot, patches
from sklearn import cluster, ensemble
video_fol... |
4b7a4efd219ab3ef1c90fa7c220d10cc0d35fd00562be71a39ee5e5684889b32 | Python | 2,478 | 73 | """Class for Sensitivity Operator."""
import torch
from mrpro.data.CsmData import CsmData
from mrpro.operators.LinearOperator import LinearOperator
class SensitivityOp(LinearOperator):
"""Sensitivity operator class.
The forward operator expands an image to multiple coil images according to coil sensitivity... |
cfb3df03a6c7f502940efefcc0c9ca8579a050f97b4b06793c9118b570d13c97 | Python | 2,480 | 81 | """Display changelog with links to GitHub issues
Usage
-----
The directive
.. include_changelog:: ../CHANGELOG
adds the content of the changelog file into the current document.
References to GitHub issues are identified as "(#XY)" (with parentheses
and hash) and a link is inserted
https://github.com/RI-imaging/... |
fc2e0dc5084f8ee2ba24b3eb7fa1ca1432dd5d14274c6f4e4d4e5d477bb2c37c | Python | 2,481 | 89 | """
Test extension array that has custom attribute information (not stored on the dtype).
"""
from __future__ import annotations
import numbers
from typing import TYPE_CHECKING
import numpy as np
from pandas.core.dtypes.base import ExtensionDtype
import pandas as pd
from pandas.core.arrays import ExtensionArray
... |
7963af274e7f9156d9e325755d74bf50814d7ad97e3bd69dc799a0424c93cd42 | Python | 2,483 | 88 | # Created by G. Peter Lepage (Cornell University) in 05/2019.
# Copyright (c) 2019 G. Peter Lepage.
#
# 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 3 of the License, or
# any la... |
a56c30b077823f892e9ce39886d5ac0e270ef7450e9dcb1eafab3f739413cab2 | Python | 2,483 | 82 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Oct 30 12:08:21 2023
@author: nrq2
"""
# https://pycistarget.readthedocs.io/en/latest/pycistarget_scenic%2B_wrapper.html
#%matplotlib inline
import pycistarget
pycistarget.__version__
import os
import pyranges as pr
import os
from scenicplus.wrappers.r... |
de6d67caab10e9d8cde58957171cca1d367e27a9ed17dedd94b3b89104fba4e2 | Python | 2,483 | 82 | # ---
# jupyter:
# jupytext:
# text_representation:
# extension: .py
# format_name: percent
# format_version: '1.3'
# jupytext_version: 1.16.0
# kernelspec:
# display_name: .venv
# language: python
# name: python3
# ---
# %%
import os, datetime
from pathlib import Path
impor... |
41c5ba0a97b43e43d2a04da04c10e5a0cee28d1e7e63a2cf01eec717c650a3e2 | Python | 2,484 | 67 | import matplotlib.pyplot as plt
import numpy as np
def get_values(region_info, output):
"""
Extract metrics and statistical values for the given region from the output data.
"""
metrics, lh_stats, rh_stats, asymmetry_stats = [], [], [], []
for i, elt in enumerate(output['norm']['metric_names']):
... |
9f8a04378ddddb38bf3fe628246b8da3924f95721f9a07e40120935280c524aa | Python | 2,485 | 83 | """
Tests for np.foo applied to DataFrame, not necessarily ufuncs.
"""
import numpy as np
import pandas as pd
import pandas._testing as tm
class TestAsArray:
def test_asarray_homogeneous(self):
df = pd.DataFrame({"A": pd.Categorical([1, 2]), "B": pd.Categorical([1, 2])})
result = np.asarray(df)
... |
e6adef4ec799b6923574ef9ebaed34d5d53f6d299be7a1daaa11119fe8461fe2 | Python | 2,485 | 77 | from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
)
import numpy as np
from pandas._config import is_nan_na
from pandas._libs import lib
from pandas._libs.missing import NA
from pandas.errors import LossySetitemError
from pandas.core.dtypes.cast import np_can_hold_element
from pan... |
2793ffc7421207df0db2d87f79909823274d769a917c16cdbb992ee5c4e6e631 | Python | 2,488 | 77 | # -*- coding: utf-8 -*-
from functools import lru_cache
import numpy as np
from .red_blue import RedBlueMove
__all__ = ["DEMove"]
class DEMove(RedBlueMove):
r"""A proposal using differential evolution.
This `Differential evolution proposal
<http://www.stat.columbia.edu/~gelman/stuff_for_blog/cajo.pdf>... |
808609eddfe29979adf142ac216786c9e46a396353f7103ea57e7e1afec4f0cc | Python | 2,491 | 89 | import pandas as _pd
from parserix import parse as _parse
def _well_site_table(img_list):
"""
parse metadata from image paths and return a pandas dataframe
of image_path and metadata columns
Parameters:
-----------
img_list: list
list of image paths
Returns:
--------
pand... |
76263bb9d31100b6a4003e27d61e901343859c16a38b46d141bf94cd0b093911 | Python | 2,493 | 64 | import time
import matplotlib
import numpy as np
import pandas as pd
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from brainflow.board_shim import BoardShim, BrainFlowInputParams, LogLevels, BoardIds
from brainflow.data_filter import DataFilter, FilterTypes, AggOperations, NoiseTypes
def main():
Board... |
f07eb5bf4973f221f7474d9192a3cec7fb2b8c96f235afa47c35d6d046ad8e5c | Python | 2,494 | 79 | # -*- coding: utf-8 -*-
import torch
class Interleaver(torch.nn.Module):
def __init__(self, array=None):
"""
Class that represents an interleaver.
:param array: That array that is needed is used to change the order.
"""
super(Interleaver, self).__init__()
if array... |
4681c8c260b3f13e2047e050e881ea79b6770ad65ff91220396b5a7ca169eabe | Python | 2,495 | 78 | """In-memory + optional file-backed logger.
The default logger when a user does `Experiment(log=True)`. Stores every event
in a list so the UI / notebook can replay it afterwards, and optionally tees
each event to a JSON-lines file.
Cheap, thread-safe enough for single-process use (the event list uses a list
append w... |
8ba2a2c3cdf186d8161348ae350130b5df55fdf9a376969c2661ebd2c04742f7 | Python | 2,495 | 92 | """
Timedelta benchmarks with non-tslibs dependencies. See
benchmarks.tslibs.timedelta for benchmarks that rely only on tslibs.
"""
from pandas import (
DataFrame,
Series,
timedelta_range,
)
class DatetimeAccessor:
def setup_cache(self):
N = 100000
series = Series(timedelta_range("1 ... |
aea9af51e34d6626e25b1f60686a00ff3164ba69f663845a7ab8204cd2fa8dd7 | Python | 2,496 | 81 | """Test fetching data from OSF."""
import numpy as np
import pytest
from nimare.annotate import GCLDAModel
from gradec.fetcher import (
_fetch_features,
_fetch_metamaps,
_fetch_model,
_fetch_neuroquery_counts,
_fetch_spinsamples,
)
@pytest.mark.parametrize(
"dset_nm,model_nm",
[
(... |
71a850d43fffd4c28a957d875f2d1d1eb3e7fd1dc3de67504652efaa82493c5a | Python | 2,497 | 56 | import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import matplotlib.ticker as ticker
import matplotlib.transforms as transforms
plt.rcParams['font.family'] = 'Gargi'
#create figure
fig, ax = plt.subplots()
bar_width = 0.4
palette = ['#999999', '#999999','#999999','#999999', '#999999', '#2E6AFF'... |
bccc0881ff12a60242a3925ec7ea9dee6286532f24c55920d7ea123f9967e984 | Python | 2,501 | 68 | #! /usr/bin/env python
##############################################################################
## DendroPy Phylogenetic Computing Library.
##
## Copyright 2010-2015 Jeet Sukumaran and Mark T. Holder.
## All rights reserved.
##
## See "LICENSE.rst" for terms and conditions of usage.
##
## If you use this wo... |
34d34bd0cab3d9d8f9ee1aa7eb6ba26d3bbd602a5cf32c07c65139948b6d51b3 | Python | 2,502 | 73 | """Provider registry + factory.
`get_provider(row)` is the seam every consultation path goes through. It's
keyed on `LLMProviderSetting.provider`. Adding Google / Azure / Ollama later
means implementing one class + adding one registry entry here.
"""
from __future__ import annotations
from pycaret_server.llm.provide... |
f9b08535f8062e0e34689cb06d803d9fce31a32fc811d22ba25ecd6756d51fbe | Python | 2,504 | 83 | import logging
import torch
from torch import nn
from ocpmodels.common import distutils
class L2MAELoss(nn.Module):
def __init__(self, reduction="mean"):
super().__init__()
self.reduction = reduction
assert reduction in ["mean", "sum"]
def forward(self, input: torch.Tensor, target: ... |
13fb145f60c8b1b43a6de44d943663f23f0728f8c8e895345953e8a0219375af | Python | 2,505 | 58 | import cv2
from tqdm import tqdm
import plastegy_net
from glob import glob
import pandas as pd
from datetime import datetime
task = 'analyse'
if task == 'train':
training_root = ''
export_path = training_root + '/output'
training_path = training_root + '/training_data'
validation_path = training_root +... |
ff6e4b0b585efc057a0589a7bac9b0e2852209e0e678d40f33a83b1f29f92d0a | Python | 2,505 | 60 | #if two consecutive regions have the same annotation, then they should be merged into a single region
def merge_bed(file_path):
merged_rows = []
with open(file_path, 'r') as file:
previous_row = None
for line in file:
row = line.strip().split('\t')
#print(row)
... |
ea6aea11ff449d71f78462cee75ccf9d911695a0a4da0be6b2a060241f1dc0d7 | Python | 2,506 | 76 | import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from mat4py import loadmat
import scipy as sp
from matplotlib import cm
from helper_make_data import make_data
from helper_make import make
from matplotlib.ticker import FormatStrFormatter
import sys
import os
from helper_compute_performance import... |
ab6af7ef39f3264ea4fe1782a0a87c213df1b556c81c6292bfdefcb9b36cd7c7 | Python | 2,508 | 65 | import os
from unittest import TestCase, mock
import numpy as np
import pandas as pd
from scipy import stats
import dynast.estimation.p_c as p_c
import dynast.estimation.p_e as p_e
import dynast.preprocessing.aggregation as aggregation
from .. import mixins
class TestPC(mixins.TestMixin, TestCase):
def test_r... |
e18f45e3dba45dd5bb982b1aea7e2ec61ff563fa484f36a30baee797c5c36dbe | Python | 2,510 | 77 | """Test the smooth_bbox CLI command argument parsing."""
import argparse
from unittest.mock import patch
import pytest
from lightning_pose.cli.commands.smooth_bbox import get_parser, handle
class TestGetParser:
"""Test the get_parser function."""
def test_returns_argument_parser(self):
"""Returns ... |
b03ec918ed42a6c9a9037e798bcb9dfc4d29d0ddc0f2ac4bc4df36e642f82e6f | Python | 2,511 | 76 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
from pandas.tests.copy_view.util import get_array
@pytest.mark.parametrize("box", [lambda x: x, pd.DatetimeIndex])
def test_datetimeindex(box):
dt = pd.date_range("2019-12-31", periods=3, freq="D")
ser = pd.Series(dt)
idx =... |
2d99321b21e1c22f1e2da8ab164a0634f25b0e191690925e78eba58992561574 | Python | 2,512 | 74 | import cv2
import cv2
import math
from utils.logging import init_log
import numpy as np
import math
import sys
from scipy import signal
from scipy import ndimage
def fspecial_gauss(size, sigma):
x, y = np.mgrid[-size//2 + 1:size//2+1 , -size//2+1:size//2+1]
g = np.exp(-((x**2 + y**2)/(2.0*sigma**2)... |
666529fc6ef29faaebf29278ac3321cdf6251ed670035bac6b4d6446525022aa | Python | 2,512 | 74 | # 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... |
903d446ab5ba36ac034a2bf3a9460f349d6d31d1d26850fa91198ece7d10ded1 | Python | 2,512 | 60 | from PyQt5.QtCore import pyqtSignal
from PyQt5.QtWidgets import QWidget, QHBoxLayout
from .CheckBox import CheckBox
class MetricCheckBox(QWidget):
# Signal emitted when the checkbox state changes. It sends the label of the checkbox when checked.
sgn = pyqtSignal(str)
def __init__(self):
super().... |
b46d62a81fcdb921338957192b571763eb7448b62a3533110d3761fc2ff59c9d | Python | 2,512 | 69 | '''
@Author: your name
@Date: 2020-01-06 14:04:27
@LastEditTime : 2020-01-06 17:28:15
@LastEditors : Please set LastEditors
@Description: In User Settings Edit
@FilePath: /KGCN_Keras-master/callbacks/eval.py
'''
# -*- coding: utf-8 -*-
from collections import defaultdict
import numpy as np
from keras.callbacks impor... |
b9b1034fb6451c6c57afb752b7ca636f72596251b2ca27f055e9840d83dc3f74 | Python | 2,512 | 75 | # 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... |
da9b30cf93090c855d8554c7b2fbf25d56ffc494e2d080d8fafab36081e432c3 | Python | 2,512 | 77 | from game_functions import Game, Game_Bayes
from helper_compute_performance import compute_performance
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm, use
from helper_percentile_discrete import percentile_discrete
from helper_set_pi import set_pi
import sys
if __name__ == "__main__":
wh... |
13d4a39438c2bef291f3555827ca275a12243bc7743555621ef08cdc1236eb68 | Python | 2,513 | 70 | #!/usr/bin/env python3
"""
concat_csv.py
-------------
Concatenates multiple CSV files into a single output CSV file.
- Accepts a list of file paths as input; files that do not exist are silently skipped.
- Prepends each input file's content with a header including the category and file name.
- Removes the input files... |
26b3972dbe14fe894040540bf37f3b23577c08acb3630461c9a32bcb7a609bca | Python | 2,513 | 86 |
#
# Main file of program intended to run analysis on protein structural data using
# holographic machine learning techniques
#
# new import statements
from argparse import ArgumentParser
import imp
import os
import sys
import numpy as np
import protein_holography.hologram.pdb_interface as pdb_int
import protein_hol... |
442a5be9c4b1724d4915080857901b35f33d30ba55f262a69b4255c71d9695bd | Python | 2,514 | 61 | import os
from unittest import TestCase, mock
import pandas as pd
import dynast.preprocessing.bam as bam
import dynast.preprocessing.coverage as coverage
import dynast.preprocessing.snp as snp
from .. import mixins
class TestSnp(mixins.TestMixin, TestCase):
def test_read_snps(self):
snp.read_snps(self... |
c74c79233f3be06f7458eea51c79dc800ee6a8ee0fd198c4fe8489236922047e | Python | 2,514 | 71 | import pytest
from pandas.errors import Pandas4Warning
import pandas as pd
import pandas._testing as tm
class TestSeriesRenameAxis:
def test_rename_axis_mapper(self):
# GH 19978
mi = pd.MultiIndex.from_product([["a", "b", "c"], [1, 2]], names=["ll", "nn"])
ser = pd.Series(list(range(len(... |
cba963cc9152d508f70cfd75f6b49d4fb6b2040d7a59f895c3a900994bc08e5e | Python | 2,514 | 72 | import os
import pytest
from cptools2 import parse_yaml
CURRENT_PATH = os.path.dirname(__file__)
TEST_PATH = os.path.join(CURRENT_PATH, "test_config.yaml")
TEST_PATH2 = os.path.join(CURRENT_PATH, "test_config2.yaml")
TEST_BROKEN = os.path.join(CURRENT_PATH, "test_config_broken.yaml")
def test_open_yaml():
"""cpto... |
5cf36b3b4a62e66e6e4c9a2e77e863231c4ce71243915ed69308b87c7675517d | Python | 2,515 | 80 | import pytest
from pandas._libs.tslibs.dtypes import NpyDatetimeUnit
from pandas.errors import OutOfBoundsTimedelta
import pandas as pd
class TestAsUnit:
def test_as_unit(self):
td = pd.Timedelta(days=1)
assert td.as_unit("us") is td
res = td.as_unit("ns")
assert res._value == ... |
a77ecb3168b6dc2343131ef6e43a6fe486e4c53cac0890a9a4d29d617837c874 | Python | 2,515 | 72 | import os
import subprocess
import sys
import pytest
pytestmark = pytest.mark.online
def test_public_hf_repository_serves_small_runtime_assets(tmp_path):
hf_home = tmp_path / "hf-home"
env = os.environ.copy()
for name in (
"ACTIONS_ID_TOKEN_REQUEST_TOKEN",
"ACTIONS_ID_TOKEN_REQUEST_URL",... |
0e0ffa02883028c584c10e17be47826cf58cbe1cce6d00228b9139a76afa31ad | Python | 2,516 | 68 | # 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... |
b001efd723ea627caadede5c012a491c5ba23f49e6d232a2c56907781cbe7866 | Python | 2,516 | 59 | from wordfreq import tokenize, simple_tokenize, word_frequency
import pytest
def test_tokens():
assert tokenize('おはようございます', 'ja') == ['おはよう', 'ござい', 'ます']
def test_simple_tokenize():
# When Japanese is run through simple_tokenize -- either because it's
# tagged with the wrong language, or because we wa... |
56624e7cd51e386fa157eae58586219292645c42d92fefc88c725ddafa1d0fa4 | Python | 2,521 | 82 | import numpy as np
from plot_configs import *
import pylab
def plotFragSize(ds, frag, log=1, prefix="test"):
"""
Plot the estimated fragment size.
"""
# print ("@plotFragSize")
ds = np.abs(np.array(ds))
ds = ds[~np.isnan(ds)]
ds = ds[ds > 0]
if log:
ds = np.log2(ds)
fig, a... |
30874731fafe85ade529f8421565d8f2dd4d6497d4e188979aa9233f70e6669c | Python | 2,522 | 67 | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
def random_image_mask(img, filter_size):
'''
:param img: [B x 3 x H x W]
:param crop_size:
:return:
'''
fh, fw = filter_size
_, _, h, w = img.size()
if fh == h and fw == w:
return img, None
... |
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