sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
4ec4ee353d99b58f39d6f2fef37f88cbe25eb26cf64d17d16d12cbcd9f05acc1 | Python | 377 | 12 |
def save_data(df, filename, data_id, dset):
"""
Helper function to save results from the analysis of a single subvolume.
To be used to generate plots of mean +- std over subvolumes.
"""
import os
root = os.path.split(filename)[0]
if not os.path.exists(root):
os.makedirs(root)
... |
9621da163ec52194dd5188dd45d45ef09bba0d3cc6a9b10095ff89fb36ebbbdf | Python | 377 | 15 | import unittest
class TestDreaming(unittest.TestCase):
def test_imports(self):
try:
from dreamcoder.dreaming import backgroundHelmholtzEnumeration
from dreamcoder.dreaming import helmholtzEnumeration
except Exception:
self.fail('Unable to import from dreaming m... |
2becc2d64dcd279d421d32128c2223590576fb5c03c23e25dcafe4c76fdae4d4 | Python | 379 | 14 | #!/usr/bin/env python
#================================================================
# Copyright (C) 2022 Yufeng Liu (Braintell, Southeast University). All rights reserved.
#
# Filename : __init__.py
# Author : Yufeng Liu
# Date : 2022-04-18
# Description :
#
#======================... |
9bc378fce5ac5aa201bc427f5432bab51fe0ff4490ec85f61d6d424fd6819573 | Python | 379 | 15 | #!/usr/bin/env python
import sys
from ckg.init import installer_script
from ckg.graphdb_builder.builder import builder as builder
import ckg.debug as debug
if __name__ == '__main__':
if len(sys.argv) > 1:
if sys.argv[1] == 'init':
installer_script()
elif sys.argv[1] == 'debug':
... |
d6a3ee8b9d42fd71a0c9d95c6de2207635d6c599ffa4f28193b22359f0544f82 | Python | 379 | 9 | """
Manual Contour Correspondence module.
Interactive GUI for defining, saving, and exporting correspondence points
between a registered brain volume and the Allen CCF template. Default
target region is CA3 (Allen CCF id 463) - the dominant source of DG
over-counting in this pipeline. Override via ``region_ids... |
194744894f8975ea6b7b76d67c6c977067a82fbbf45101041076a5cd980addd8 | Python | 380 | 14 | from __future__ import print_function
import argparse
from topaz.commands.normalize import add_arguments, main
name = 'preprocess'
help = 'downsample and normalize images in one step'
if __name__ == '__main__':
parser = add_arguments()
parser.prog = 'Script for performing image downsampling and normalizatio... |
a28ceb3a97feb9eac6b27293f09e37c20f5ec56963186f08828b14107a65913c | Python | 381 | 17 | import tensorflow.keras as tfkeras
from .models_factory import ModelsFactory
class TFKerasModelsFactory(ModelsFactory):
@staticmethod
def get_kwargs():
return {
'backend': tfkeras.backend,
'layers': tfkeras.layers,
'models': tfkeras.models,
'utils': tfk... |
707fe508cee0288c3203093def43e0a597188ac2d661c03d196e40d81cc72bad | Python | 382 | 13 | from __future__ import division, print_function
import numpy as np
def compute_R2(x, y):
return(((x - x.mean()) * (y - y.mean())).mean() / (x.std()*y.std()))**2
def effective_dof(X, lambda_val):
""" Compute the effective degrees-of-freedom for data matrix X and lambda value. """
s = np.linalg.svd(X, co... |
ffa4a964ecf86c416c5ffc1a2f337e72c96081977c543745fb384f3fd7a6a10f | Python | 383 | 20 | import os
from sys import argv
def countstep(filename):
textfile=open(filename, "r")
inputString=textfile.readlines()
i = 0
for line in inputString:
line = line.split()
wanted='Step'
if wanted in line:
i+=1
print( i)
if __name__ == "__main__":
try:
filename, outputfile = argv
except... |
15df8891dbdc2ec1d61ecd60018db7cf8a3b2659dd15802b8be53fa124cb0873 | Python | 384 | 12 | """Solving one dimensional heat conduction equation."""
try:
from importlib.metadata import version, PackageNotFoundError # type: ignore
except ImportError: # pragma: no cover
from importlib_metadata import version, PackageNotFoundError # type: ignore
try:
__version__ = version(__name__)
except Packag... |
9a9306bd1b725c2358a27145380251db944058a215c454552c38b94f5531f632 | Python | 384 | 12 | """
Set of specific utilities for combining PySeg with Subtomogram Averaging tools (PyTom)
# Author: Antonio Martinez-Sanchez (Max Planck Institute for Biochemistry)
# Date: 1.06.16
"""
__author__ = 'Antonio Martinez-Sanchez'
from .plist import TomoPeaks, SetTomoPeaks, Score, SingleTiltWedge, Particle, ParticleList,... |
0d231a989259a4b9a2920eb54b1760b20e661f2b82f3393a3935af342b7b7e4e | Python | 385 | 18 | from .base import Canvas, ViewTransform
from .camera import Camera, Viewpoint
from .compositor import CompositorTree
from .engines import EEVEE, Cycles
from .recorder import FrameRecorder
from .world import WorldTree
__all__ = [
"Canvas",
"Camera",
"Viewpoint",
"CompositorTree",
"EEVEE",
"Cycle... |
3f0e297712eec1861bc1317877461877cd2bcdb3ab02c7cdcb0b3fdac98d0676 | Python | 385 | 14 | import my_notebook
from cog import BaseRunner, Input
class Runner(BaseRunner):
def setup(self) -> None:
"""Prepare the model so multiple predictions run efficiently (optional)"""
def run(self, name: str = Input(description="name of person to greet")) -> str:
"""Run a single prediction"""
... |
4dfd2dbb03c40409fde373446c5c8451515b8bd1ec02ce05c4f0eea9abab9b71 | Python | 385 | 12 | import argparse
from trainval import main
parser = argparse.ArgumentParser(description='Re-run prototypical networks training in trainval mode')
parser.add_argument('--model.model_path', type=str, default='results/best_model.pt', metavar='MODELPATH',
help="location of pretrained model to retrain ... |
4fe109ea71593fc51f87e143cf023d7acf893ab13c43753964dde6b41e85d77d | Python | 385 | 10 | from .conv2_5d_converter import Conv2_5dConverter
from .conv3d_converter import Conv3dConverter
from .acsconv_converter import ACSConverter
from .soft_acsconv_converter import SoftACSConverter
print("The ``converters`` are currently experimental. "
"It may not support operations including (but not limited to) "
"Funct... |
cd69de2bc3873b6755c9d626c5b161867193648abb7ee2891c7464798e9dd7af | Python | 385 | 15 | from __future__ import annotations
from ase.build import bulk
from maggma.stores import MemoryStore
from quacc.wflow_tools.db import results_to_db
def test_results_to_db():
atoms = bulk("Cu")
store = MemoryStore(collection_name="db3")
results_to_db(store, {"atoms": atoms})
with store:
assert... |
25cec086c9a4086e0834934c74983b6fff43b6e19b36e969b0b8db778202f4fe | Python | 386 | 12 | import logging
import os
from cirrocumulus.envir import CIRRO_LOG_LEVEL
logger = logging.getLogger("cirro")
log_level = os.environ.get(CIRRO_LOG_LEVEL, "ERROR")
logger.propagate = False
logger.setLevel(log_level)
logger.addHandler(logging.StreamHandler()) # Logs go to stderr
logger.handlers[-1].setFormatter(logging.... |
71a7ddb67e6abe44f9ba49688912eda417c9732cce877b69ad4142f2d3cbcf9a | Python | 387 | 15 | from .config import InstanceRefinementConfig
from .stage import (
InstanceRefinementResult,
load_saved_instance_refinement,
passthrough_instance_refinement,
run_instance_refinement,
)
__all__ = [
"InstanceRefinementConfig",
"InstanceRefinementResult",
"load_saved_instance_refinement",
"... |
98ccf10cf688a28ce48928e4dc4600e6d34b1f98b7340d47715d2431890b79e6 | Python | 387 | 20 | # set QT_API environment variable
import os
import sys
os.environ["QT_API"] = "pyqt5"
import qtpy
# qt libraries
from qtpy.QtCore import *
from qtpy.QtWidgets import *
from qtpy.QtGui import *
# app specific libraries
import control.gui_tiscamera_DZK250 as gui
if __name__ == "__main__":
app = QApplication([])
... |
516e2f3c42327d92b8f4dc8de90494b722c81a13869b4d4ccf065a1aefc86625 | Python | 389 | 20 | # Overwrite values of src/default_net_params.py
net_params = {}
# Overwrite values of src/default_sim_params.py
sim_params = {
't_sim': 12500.0,
'master_seed': 2106
}
# Parameters for the analysis
ana_params = {
'plotRasterArea': {
'fraction': 0.05,
'low': 12000,
'high': 12500
... |
b4f14b884e03fe69187c4d6d3899759e4b200ccda0f8f152e6207bc4aa0a04e8 | Python | 390 | 12 | """
DeepLabCut2.0 Toolbox (deeplabcut.org)
copyright A. & M. Mathis Labs
https://github.com/AlexEMG/DeepLabCut
Please see AUTHORS for contributors.
https://github.com/AlexEMG/DeepLabCut/blob/master/AUTHORS
Licensed under GNU Lesser General Public License v3.0
"""
#from deeplabcut.post_processing.filtering import *
fr... |
1d0aea2d1327a5ff7992e233b85a7cb80d129aecf81eed00e4d462fda5f42aa4 | Python | 391 | 16 | from biotite.structure.io.mol import MOLFile
from .reader import ReaderBase
class SDFReader(ReaderBase):
_extra_annotations = {}
def read(self, file_path):
return MOLFile.read(file_path)
def get_structure(self):
return self.file.get_structure()
def _assemblies(self):
# TODO ... |
42787398e029ad50664f8baa23776b3a99682f0ec8f66e1a8cb4d69f2515083c | Python | 391 | 18 | """
Plot memory usage of a numeric computation using numpy and scipy
"""
import pylab as pl
import numpy as np
from memory_profiler import memory_usage
from scipy import linalg
X = np.random.randn(1000, 1000)
mem = memory_usage((linalg.qr, (X,)))
x = np.linspace(0, len(mem) * .1, len(mem))
p = pl.fill_between(x, mem... |
56e91819fd1abb2068ef4839acf9a908748bdf334fa7ec49715775c0ea7c4fba | Python | 391 | 19 | #!/usr/bin/python3
class ModelConfigError(Exception):
"""Error to be raised in the case of wrong parameters of a model config."""
pass
class DatasetError(Exception):
"""Error to be raised in the case of problems with the dataset."""
pass
class LayerDefinitionError(Exception):
"""Error to be ... |
9744014f818371b62bcbdc63421a0589391f47fb2d8c4ca4ae27222b45544746 | Python | 391 | 12 | banner = r"""
_____ _ __ __
/ ____| | | \/ |
| (___ | | ___ _| \ / | __ _ _ __
\___ \| |/ / | | | |\/| |/ _` | '_ \
____) | <| |_| | | | | (_| | |_) |
|_____/|_|\_\\__, |_| |_|\__,_| .__/
__/ | | |
|___/ |_... |
080abaf7746ee037cff1734625c4b1393d3ba43c4419cda6c72b39efb4644585 | Python | 392 | 13 | from unittest import TestCase
from codex.data.neuron_data_initializer import (
HEATMAP_GROUP_BY_ATTRIBUTES,
NEURON_DATA_ATTRIBUTE_TYPES,
NETWORK_GROUP_BY_ATTRIBUTES,
)
class Test(TestCase):
def test_group_by_attribute_types(self):
for k in HEATMAP_GROUP_BY_ATTRIBUTES + NETWORK_GROUP_BY_ATTRIB... |
923d9ddbfcb8dc22a5da4bfa3e0c8870c9d1008795df60863da5946df570a250 | Python | 392 | 20 | # set QT_API environment variable
import os
import sys
os.environ["QT_API"] = "pyqt5"
import qtpy
# qt libraries
from qtpy.QtCore import *
from qtpy.QtWidgets import *
from qtpy.QtGui import *
# app specific libraries
import control.gui_camera_only_tiscamera as gui
if __name__ == "__main__":
app = QApplication... |
93d4fbd01fc64ed954fffaef04a912110b840900ebdeeac7aa12d9cf6e2c7d2a | Python | 392 | 17 | import optuna
def objective(trial):
# Binh and Korn function.
x = trial.suggest_float("x", 0, 5)
y = trial.suggest_float("y", 0, 3)
v0 = 4 * x**2 + 4 * y**2
v1 = (x - 5) ** 2 + (y - 5) ** 2
return v0, v1
study = optuna.create_study(directions=["minimize", "minimize"])
study.optimize(objecti... |
2fda94f014934bb9656cee53681d96028956df55e9b9fb279c1ee3de6dcdd419 | Python | 393 | 19 | from elasticai.creator.function_utils import FunctionDecorator
def test_can_call_with_name_and_fn():
outer_name = ""
def callback(name: str, fn):
nonlocal outer_name
outer_name = name
return fn
decorate = FunctionDecorator(callback)
def fn():
return "x"
fn = dec... |
448757e588de58a6d9a36480905b471983409679ac94a165f57cc7df27858a5d | Python | 394 | 18 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
import common_setup
exp = common_setup.IssueExperiment(
search_revisions=["issue422-base", "issue422-v1"],
configs={"lmcut": ["--search", "astar(lmcut())"]},
suite=suites.suite_optimal_with_ipc11(),
)
exp.add_absolute_report_... |
c6c3fcf0a66eb4d8c07112d430d99d8f351528e5f4d35707d86e81b5504caff8 | Python | 394 | 17 | #!/bin/env python3
"""
Example script to test ithildin.filament
"""
import ithildin as ith
import matplotlib.pyplot as plt
filaments = ith.filament.read_filaments("example_filament.yaml")
print(f"read {len(filaments)} filaments")
for fil in filaments:
print(fil.points)
print(fil.payload.get('color'))
pri... |
2e4f2e6d5947212a3e9440bd11576a7b9ecda09daa2f7e1f3b22ca0b7e241a9e | Python | 395 | 11 | import torch
import torch.nn as nn
def run_network(inputs, fn, netchunk):
"""
Prepares inputs and applies network "fn".
"""
uvt_flat = torch.reshape(inputs, [-1, inputs.shape[-1]])
out_flat = torch.cat([fn(uvt_flat[i:i + netchunk]) for i in range(0, uvt_flat.shape[0], netchunk)], 0)
out = out_f... |
5d1b371691f20fa4686d64ec222cef7b3bd5be1c8b2214baaccdc80dddcb385c | Python | 395 | 20 | """
Utility file to select GraphNN model as
selected by the user
"""
from nets.contrastpool_net import ContrastPoolNet
def ContrastPool(net_params):
return ContrastPoolNet(net_params)
def gnn_model(MODEL_NAME, net_params):
models = {
"ContrastPool": ContrastPool
}
model = models[MOD... |
cc37dc62592a3b5538cbb641507178552ab8d895a84acf1332347a2b629d2344 | Python | 395 | 13 | from enum import Enum, auto
class BondOrderType(Enum):
'''Enum class for the different modes of determining bonds in the molecule.'''
# Use the Wiberg index matrix to determine bonds
WIBERG = auto()
# Use the Localised Molecular Orbitals (LMO) to determine bonds
LMO = auto()
# Use the Natura... |
e1b5eaa0c1ac8a34de16cf21f3aae1bdb8edcc2696ee5768cda9605ac1d70686 | Python | 395 | 12 | """
Set of specific utilities for combining PySeg with Subtomogram Averaging tools (PyTom)
# Author: Antonio Martinez-Sanchez (Max Planck Institute for Biochemistry)
# Date: 1.06.16
"""
__author__ = 'Antonio Martinez-Sanchez'
from .plist import TomoPeaks, SetTomoPeaks, Score, SingleTiltWedge, Particle, ParticleList,... |
1d9952a69381f15ae8ef77dfbcffb1ace46e32b8781a75643aa26ca45446f0f8 | Python | 396 | 12 | from distutils.command.bdist import bdist
import sys
if 'egg' not in bdist.format_commands:
try:
bdist.format_commands['egg'] = ('bdist_egg', "Python .egg file")
except TypeError:
# For backward compatibility with older distutils (stdlib)
bdist.format_command['egg'] = ('bdist_egg', "Pyt... |
26153057ae830758381efb7551009531d7c2bbe220015f055e6bc353da27c5de | Python | 396 | 11 | # SPDX-License-Identifier: MIT
# SPDX-FileCopyrightText: 2021 Taneli Hukkinen
# Licensed to PSF under a Contributor Agreement.
__all__ = ("loads", "load", "TOMLDecodeError")
__version__ = "2.0.1" # DO NOT EDIT THIS LINE MANUALLY. LET bump2version UTILITY DO IT
from ._parser import TOMLDecodeError, load, loads
# Pre... |
5cddd8cd8cf3629a7da88fe778304ee5f2a15de4076e791b73771a1769053be4 | Python | 396 | 16 | import random
from .shape import Shape
class RandomShapeSelector:
def __init__(self, shapes: list[Shape]):
self.__shapes = shapes
def __len__(self):
return len(self.__shapes)
def __getitem__(self, idx):
if idx >= len(self.__shapes):
raise StopIteration
idx... |
a28862e39dd6125e18ba9392dc2f00bc14c6f511b5e145145a23d285ea0913dc | Python | 396 | 22 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
import common_setup
CONFIGS = {
'astar_gapdb': [
'--search',
'astar(gapdb())'],
}
exp = common_setup.IssueExperiment(
search_revisions=["issue482-base", "issue482-v1"],
configs=CONFIGS,
suite=suite... |
ab8169dccdedc1a564813053f85c5713b2041f0fa5fa23a733630dab903854e4 | Python | 396 | 17 | from __future__ import annotations
import pytest
@pytest.fixture(autouse=True)
def ESPRESSO_PARALLEL_CMD():
from shutil import which
import psutil
from quacc import change_settings
if which("mpirun") and psutil.cpu_count(logical=False) >= 2:
change_settings({"ESPRESSO_PARALLEL_CMD": "mpiru... |
bf3683f5eb5cab994c6dac7b44b489a5af5ff4db734b4e507bb42ba52995af92 | Python | 396 | 15 | from cellmincer.models.denoising_model import DenoisingModel
from cellmincer.models.fetch_model import \
init_model, \
get_temporal_order_from_config, \
get_window_padding_from_config, \
load_model_from_checkpoint
__all__ = [
'DenoisingModel',
'init_model',
'get_temporal_order_from_config'... |
42e177ff244507b704439f0f4fe2f431d4c244bdd1b3ea8809c9b132226f2315 | Python | 397 | 14 | from elasticai.creator.base_modules.relu import ReLU
from .batchnorm2d import BatchNorm2d
from .conv1d import Conv1d
from .conv2d import Conv2d
from .linear import Linear
__all__ = ["ReLU", "BatchNorm2d", "Conv1d", "Conv2d", "Linear", "parametrized_modules"]
parametrized_modules = [
"ParametrizedBatchNorm2d",
... |
727cbef14daa1c4008717dc719c5ac63308881ffff3a4d2cf086bf3c5a8104fb | Python | 397 | 27 | import numpy as np
import glob
import re
def load_elbow_flow(path):
return np.load(f"{path}")[1:]
def load_channel_flow(
path,
t_start=0,
t_end=1200,
t_every=1,
):
return np.load(f"{path}")[t_start:t_end:t_every]
def load_periodic_hill_flow(path):
data = np.load(f"{path}")
return data
... |
9081d3d2ab4bb95d72fbebdbd41fdd7ee80a277de4505f459f902cbeb1e238e5 | Python | 397 | 16 | # Libraries
import os
import sys
code_path = os.path.split(os.path.split(os.getcwd())[0])[0]
sys.path.append(code_path)
from setting import *
from download_data import *
# Download
data_path = get_data_path("tcga")
database = "gdc"
## cancers = read_file(os.path.join(data_path, "cancers"))
cancers = ["BRCA", ] # "KI... |
cabd070ab7e4beb310f6d6aca1afe9d63cd99d50cc7ee734869c25d1c793114d | Python | 397 | 11 | import torch
class AdaptableSiLU(torch.nn.SiLU):
def __init__(self) -> None:
super().__init__(inplace=False)
self.scale = torch.nn.Parameter(torch.ones(1, requires_grad=True))
self.beta = torch.nn.Parameter(torch.zeros(1, requires_grad=True))
def forward(self, input: torch.Tensor) -> ... |
3b70d4de24492d8c894d5ee903cf7030dc7f213dcfd38d72592623d1c642fea0 | Python | 398 | 22 | import numpy as np
import scipy.signal
@profile
def create_data():
ret = []
for n in range(70):
ret.append(np.random.randn(1, 70, 71, 72))
return ret
@profile
def process_data(data):
data = np.concatenate(data)
detrended = scipy.signal.detrend(data, axis=0)
return detrended
if __na... |
41e376f69fda079f9693da5f757e87e262c0c8469c49f6447f58f23977a5e8ed | Python | 398 | 20 | # set QT_API environment variable
import os
import sys
os.environ["QT_API"] = "pyqt5"
import qtpy
# qt libraries
from qtpy.QtCore import *
from qtpy.QtWidgets import *
from qtpy.QtGui import *
# app specific libraries
import control.gui_PDAF_demo as gui
if __name__ == "__main__":
app = QApplication([])
win... |
7d8525344229be66880d355cd4b85224e928e2c7bf81778d64e2e8621c4aa368 | Python | 398 | 22 | from datetime import date
import os
today = date.today()
# delete old version file
os.remove('+crabsort/version.m')
out_file = open('+crabsort/version.m','a+')
out_file.write('function v = version()')
out_file.write('\n')
temp = ("v = 'v" + today.strftime('%y.%m.%d') + "';")
temp = temp.replace('.0','.')
out_file.... |
a3f32b33aba1c84fd960d4045618df46fa7a7b59aa08adf2be9ab0c68c14d7c9 | Python | 398 | 17 | from cocotb.triggers import RisingEdge
async def _write_current_d_in(dut) -> None:
dut.src_valid.value = 1
await RisingEdge(dut.clk)
dut.src_valid.value = 0
async def _reset_dut(dut) -> None:
dut.src_valid.value = 0
dut.dst_ready.value = 0
dut.rst.value = 1
await RisingEdge(dut.clk)
... |
c15fab9836772a287e6209ecd320f82fbf2b28446d7df6059a69759088d5f3f3 | Python | 398 | 16 | """
see kernel.m
"""
import numpy as np
from numba import jit
@jit # @partial(jit, static_argnums=(0,))
def exponential(duration, tau):
""" kernel = exponential(duration, tau)
normalized exponential kernel: EXP(-t/tau), width TAU in points."""
if duration>=1:
kernel = np.exp(-(np.arange(0, dur... |
7b3e0546f37929a4a8b09789d96cd4c8a743760df91c3cbf4922cf5ca09db793 | Python | 402 | 16 | from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
# TypedDict was introduced in Python 3.8.
#
# TODO: Remove the else block and TYPE_CHECKING check when dropping support
# for Python 3.7.
from typing import TypedDict
class ResultDict(TypedDict):
encoding: Optional[str]
... |
b41da0e55fb38e840e27fe9dd6966f8dbf32e2abba956b5230fc0fbe7112bf66 | Python | 402 | 7 | ################################################################################
# Copyright (c) 2021-2023, Lawrence Livermore National Security, LLC.
# Produced at the Lawrence Livermore National Laboratory.
# Written by D. Jones <djones@llnl.gov> and UCSD collaborators in listed in CONTRIB.md
#
# All rights reserved.... |
4e8cab58507f78765fc1639dce458a520b07e8fbec62b5676588c3600a09d7da | Python | 403 | 16 |
from . import actflowcomp
from .actflowcomp import *
from . import model_compare
from . import connectivity_estimation
from . import dependencies
#from . import infotransfermapping
#from . import pipelines
#from . import preprocessing
from . import simulations
from . import tools
#from . import latent_connectivity
__... |
81a779b00aa57b6482991374e2f3e648b9f363c816ce0c0edc826330bcb9a231 | Python | 403 | 10 | from .config import get_default_config, update_config
from .collators import create_collator
from .transforms import create_transform
from .datasets import create_dataset, create_dataloader
from .models import apply_data_parallel_wrapper, create_model
from .losses import create_loss
from .optim import create_optimizer
... |
20f174f646a5badbec647c4f5a6a5489e6e6bc336a587467c2e4e9ddbfe125d1 | Python | 404 | 19 | #!/bin/env python3
'''
Draw Feynman diagrams for the quasi-particles in the 2D patterns of cardiac
arrhythmia
'''
import sys
import yaml
from pdlfeynman.diagram import layout_diagram
diagramfile = sys.argv[1]
posfile = sys.argv[-1]
with open(diagramfile) as f:
diagram = yaml.safe_load(f)
pos = layout_diagram(dia... |
30310b1fc02f82c3c1ef2d629eab8b4b11cf0f5158b35c3116a46459f1a7f35d | Python | 404 | 19 | from . import analysis as analysis
from . import build as build
from . import cfg as cfg
from . import components as components
from . import interactions as interactions
from . import sequence as sequence
from . import sim as sim
from . import utilities as utilities
__all__ = [
"analysis",
"build",
"cfg",... |
4ef4859e0c59e53798e1de62184cc730a8228e9b8d4aa055ef0110caf3d58c51 | Python | 404 | 10 | import molecularnodes as mn
def test_coll():
assert mn.blender.coll.mn().name == "Molecular Nodes"
assert mn.blender.coll.mn().name == "Molecular Nodes"
assert mn.blender.coll.data().name == ".MN_data"
assert mn.blender.coll.cellpack().name == "cellpack_"
assert mn.blender.coll.frames().name == ".... |
6a38a54cd4fa8e3916a53ca0b69fb865c5803e340d328730911d43f83b57fa00 | Python | 404 | 20 | # -*- coding: utf-8 -*-
'''
Python module to read common electrophysiology file formats.
'''
from . import utils
from . import haussio
from . import movies
from . import scalebars
from . import pipeline2p
from . import spectral
from . import cnmf
try:
from . import thor2tiff
except ImportError:
print("Could no... |
cfed37a08e7330854da9b986dfa8056c8a01ebf8478c309f0ce7fb4e6370435a | Python | 404 | 14 | import unittest
class TestOrderExample(unittest.TestCase):
def test_z_third(self):
print("This runs third despite being defined first")
def test_a_first(self):
print("This runs first despite being defined second")
def test_b_second(self):
print("This runs second de... |
385fbe5e31decd59c44f5a7e3b26e3c72c9363d41a633f2f207e1cba0bc10a95 | Python | 405 | 17 | from neuroquery_image_search import _datasets
def test_fetch_data(request_mocker):
data = _datasets.fetch_data()
assert data.keys() == {
"masker",
"atlas_maps",
"atlas_inv_covar",
"studies_loadings",
"terms_loadings",
"studies_info",
"document_frequenci... |
39bdb5c576bbdddeb0820e348b46a052a845bbc8667f630c672230fc89454776 | Python | 405 | 20 | # set QT_API environment variable
import os
import sys
os.environ["QT_API"] = "pyqt5"
import qtpy
# qt libraries
from qtpy.QtCore import *
from qtpy.QtWidgets import *
from qtpy.QtGui import *
# app specific libraries
import control.gui_PDAF_calibration as gui
if __name__ == "__main__":
app = QApplication([])
... |
01447932062b1ab183ab8e609795e22dc972f19fa80cc0d2a2855eb88c6fc861 | Python | 406 | 11 | import sys
import os
from PySide6 import QtCore, QtWidgets
if hasattr(QtCore.Qt, 'AA_EnableHighDpiScaling'):
QtWidgets.QApplication.setAttribute(QtCore.Qt.AA_EnableHighDpiScaling, True)
if hasattr(QtCore.Qt, 'AA_UseHighDpiPixmaps'):
QtWidgets.QApplication.setAttribute(QtCore.Qt.AA_UseHighDpiPixmaps, Tru... |
5f26668103e8c5ccc0eec25a2964c34b53b7072cb36df79b43aae7edaab5cd8a | Python | 406 | 11 | """
DeepLabCut2.0 Toolbox (deeplabcut.org)
copyright A. & M. Mathis Labs
https://github.com/AlexEMG/DeepLabCut
Please see AUTHORS for contributors.
https://github.com/AlexEMG/DeepLabCut/blob/master/AUTHORS
Licensed under GNU Lesser General Public License v3.0
"""
from deeplabcut.pose_estimation_tensorflow.dataset.fact... |
db76c9d41cfc16ef341e68e0a29af82a201392bee5beb2ec9fe2de954f877b33 | Python | 406 | 18 | import torch
import torch.nn as nn
from pathlib import Path
from abc import ABCMeta, abstractmethod
class Predictor(metaclass=ABCMeta):
@abstractmethod
def __init__(self,
model: nn.Module,
model_pth: str | Path,
device: torch.device):
...
... |
f1c4ee460272511e9f32aa6a2908babe7b5afe43c852e85d1761733d2306e7bb | Python | 406 | 15 | class Memory:
def __init__(self):
self.episodes = []
def __len__(self):
return len(self.episodes)
def __getitem__(self, idx):
episode = self.episodes[idx]
return episode["observations"], episode["actions"]
def add_episode(self, observations, actions):
self.epis... |
f3f0c61871065024b228aea7c04db67e8e15d2fce0a935f81ae1c8adb547845a | Python | 406 | 8 | ### Submit script "XY.py" to HPC (Torque) cluster
import subprocess
subprocess.run(['echo "$PWD/create_dataframes_from_matrices_upper.py" | qsub -l nodes=1:ppn=1,walltime=01:00:00,mem=8gb -N create_dataframes_upper'],
shell = True)
subprocess.run(['echo "$PWD/create_dataframes_from_matrices_full.py" | qsub -l no... |
38e604c75b7ef4d8cd7ce7a08ec6caf3b1342c38ed7db91d729607fb7b6cdfe4 | Python | 407 | 16 | # version:1.0.1808.9101
import control.gxipy as gx
def main():
# create a device manager
device_manager = gx.DeviceManager()
dev_num, dev_info_list = device_manager.update_device_list()
if dev_num is 0:
print("Number of enumerated devices is 0")
return
for i in range... |
7d25065f492d4d421917461fd0464ef39868b50ccf1d7c541749381703226503 | Python | 407 | 21 | #!/usr/bin/env python
"""Tests for `m6a_calling` package."""
import unittest
from m6a_calling import m6a_calling
class TestM6a_calling(unittest.TestCase):
"""Tests for `m6a_calling` package."""
def setUp(self):
"""Set up test fixtures, if any."""
def tearDown(self):
"""Tear down test... |
dca1f2d41a012a4c74eefe1ef2e9bae3e849656cd2ff83501838e6ed6a0bf70c | Python | 407 | 12 | """Look at alpha values of model's PReLUs"""
from src.model import ModelSpikeSorter
from torch.nn import PReLU
import torch
model = ModelSpikeSorter.load("/data/MEAprojects/DLSpikeSorter/models/v0_4/2954/rms_conv")
prelus = [module for module in model.modules() if isinstance(module, PReLU)]
for i, prelu in enumerate... |
5543c5e5e3b24e8147677ddda0c4a5c333621028f9248c074116d5061047813b | Python | 408 | 16 | """Interfaces init file."""
from .dimensions import Dimensions
from .acquisition_data import AcquisitionData
from .rx_data import RxData
from .unrolled_sequence import UnrolledSequence
from .acquisition_parameter import AcquisitionParameter
from .enums import DDCMethod
__all__ = [
"Dimensions",
"AcquisitionDat... |
00167e2f2c3e8a02b0045a0b177418b4599fbadc192e201d59ca5131b71a7065 | Python | 411 | 20 | import functools
# from jaraco.functools 3.5
def pass_none(func):
"""
Wrap func so it's not called if its first param is None
>>> print_text = pass_none(print)
>>> print_text('text')
text
>>> print_text(None)
"""
@functools.wraps(func)
def wrapper(param, *args, **kwargs):
... |
8c55d9c4fc8405b206b509209b8e371b71b51de1693105baa6286d947f26dc42 | Python | 411 | 16 | """
ASGI config for PeerJCode project.
It exposes the ASGI callable as a module-level variable named ``application``.
For more information on this file, see
https://docs.djangoproject.com/en/4.1/howto/deployment/asgi/
"""
import os
from django.core.asgi import get_asgi_application
os.environ.setdefaul... |
fe76ab1331ffd154e8f294d7a6d303e9045bd4c4c2a2fb51a584ec70535bda5b | Python | 411 | 16 | """
WSGI config for PeerJCode project.
It exposes the WSGI callable as a module-level variable named ``application``.
For more information on this file, see
https://docs.djangoproject.com/en/4.1/howto/deployment/wsgi/
"""
import os
from django.core.wsgi import get_wsgi_application
os.environ.setdefaul... |
0c064e13271b67575e9da7e632588314d097c5995436e14b7b77758fb6edb139 | Python | 412 | 16 | """
Set of specific utilities for processing biological membranes
# Author: Antonio Martinez-Sanchez (Max Planck Institute for Biochemistry)
# Date: 12.06.15
"""
__author__ = 'Antonio Martinez-Sanchez'
from .connectors import CloudMbConn
from .connectors import ConnSubGraph
from .filament import ConnDom
from .filame... |
3b4b3b0f1b8e9eadf04f48327df3f93ab0f10bab17887a51567c3b360d1fefc0 | Python | 412 | 20 | from .functional import (
get_stats,
fbeta_score,
f1_score,
iou_score,
accuracy,
precision,
recall,
sensitivity,
specificity,
balanced_accuracy,
positive_predictive_value,
negative_predictive_value,
false_negative_rate,
false_positive_rate,
false_discovery_rat... |
c61e221093d3e97a90917d42bafb73aafd0807010b1d3c790de3e168bf58ec83 | Python | 413 | 14 | import torch
AVAILABLE_OPTIMIZERS = {
"Adam": torch.optim.Adam,
"SGD": torch.optim.SGD,
}
def get_optimizer(config:dict):
lr = config["lr"]
optimizer = AVAILABLE_OPTIMIZERS[config["optimizer"]]
if config["optimizer_params"] is not None:
return lambda params: optimizer(params, lr=lr, **... |
078154fe364faf9c47c2b53e9ec8805be3b3d5e9d233d05378a6ca58516bcca6 | Python | 414 | 15 | import numpy as np
def get_matrix(n, m, pd=False, symm=False, rng=None):
"""Generates a random n-by-m matrix"""
if rng is None:
rng = np.random.RandomState(1)
A = rng.normal(size=(n, m))
if symm:
assert n == m
A = 0.5 * (A + A.T)
if pd:
assert n == m
lams, ve... |
1957333026e5b28f3a3852c90a997384ac6b98c684e7e3c4f2448d4e88355bcb | Python | 415 | 11 | from .amigos import AMIGOSDataset
from .bci2022 import BCI2022Dataset
from .deap import DEAPDataset
from .dreamer import DREAMERDataset
from .mahnob import MAHNOBDataset
from .seed import SEEDDataset
from .seed_feature import SEEDFeatureDataset
from .seed_iv import SEEDIVDataset
from .seed_iv_feature import SEEDIVFeatu... |
dcb09920d0e3c2036e03d2d025015bdc3559404bb57e71199bf93facfb71dd1b | Python | 415 | 20 | import sys
argv = sys.argv
tag_ids = argv[1].split(',')
tag_files = argv[2].split(',')
id_out = argv[3]
id_len = len(tag_ids)
file_len = len(tag_files)
if id_len != file_len:
raise ValueError("Arrays must have the same size")
i=0
with open('%s_samples.txt' % id_out,'w') as f:
while i < id_len:
id = ... |
33d89f55a5758264fb96a5212b4562ed8db15883bf227961dbf0ac42e74f8337 | Python | 417 | 15 | # This file is to check that future division works.
from test_binary_ops import arg_pairs
import autograd.numpy as np
from autograd.test_util import check_grads
def test_div():
fun = lambda x, y: x / y
make_gap_from_zero = lambda x: np.sqrt(x**2 + 0.5)
for arg1, arg2 in arg_pairs():
arg1 = make_... |
3b510c60c423803e53ac884c1e283009c18e126d681b9c5d4e5ac335a94dd382 | Python | 417 | 12 | import cv2
from synergy3DMM import SynergyNet
if __name__ == '__main__':
model = SynergyNet()
I=cv2.imread('img/sample_2.jpg', -1)
# get landmark [[y, x, z], 68 (points)], mesh [[y, x, z], 53215 (points)], and face pose (Euler angles [yaw, pitch, roll] and translation [y, x, z])
lmk3d, mesh, pose ... |
272a21d7de53bd0ec4e932fa5268c1b426b59c42b3f44d062211621d9910b5a9 | Python | 418 | 18 | """FID Net Wrapper."""
import warnings
try:
from fidnet._version import __version__
except ImportError:
__version__ = "not-installed"
warnings.warn(
"You are running a non-installed version of fidnet."
"If you are running this from a git repo, please run"
"`pip install -e .` to ins... |
8b205190a4747fe344430e9bc2922e07cb5aed19c1784d4a5c657e9d14a3c8df | Python | 418 | 11 | from .dataprocessor import AutosomeDataProcessor
from .first_layers_block import AutosomeFirstLayersBlock
from .coreblock import AutosomeCoreBlock
from .final_layers_block import AutosomeFinalLayersBlock
from .trainer import AutosomeTrainer
__all__ = ("AutosomeDataProcessor",
"AutosomeFirstLayersBlock",
... |
941e2461fb541ca7e3c52d2ee23751a9805b2397ce887126c1b61d61f7d3a36d | Python | 418 | 12 | from cog import BaseRunner, Input
class Runner(BaseRunner):
def run(
self,
text: str = Input(description="A string input"),
count: int = Input(description="An integer", default=5),
temperature: float = Input(description="A float", default=0.7),
flag: bool = Input(descriptio... |
97cf152c59422950fc56614ea69d33c153f1916d2a304c30863e5fea2a4adfc4 | Python | 418 | 11 | from downward.reports import PlanningReport
class CSVReport(PlanningReport):
def get_text(self):
sep = " "
lines = [sep.join(self.attributes)]
for runs in self.problem_runs.values():
for run in runs:
lines.append(sep.join([str(run.get(attribute, "nan"))
... |
50a77a5eb9b3d0bf18d4e05434297680b63cd41af3bd5a3ff73479867d97694e | Python | 419 | 16 | """Opaque marker for Cog input and output annotations.
Use inside ``typing.Annotated[T, Opaque]`` to tell Cog to treat ``T`` as an
opaque JSON object. Cog emits an object schema and passes values through
without custom encoding or decoding.
"""
class _OpaqueMarker:
"""Marker singleton exposed publicly as ``cog.O... |
549c4daeed9f2e78831914f5b126eee22b46c4f2c9b693fe435ddf3d17e24363 | Python | 419 | 14 | from utils.logger import setup_logging, get_logger, TensorboardWriter
from pathlib import Path
from utils import set_random_seed
SEED = 1126
set_random_seed(SEED)
if __name__ == '__main__':
setup_logging(Path('./Logs/Tests'))
tensorboard_logger = get_logger('Tensorboard')
writer = TensorboardWriter(Path('... |
0a705073542820ab4153493ae77f4c57a7171f28684445c01fe29e793c09742d | Python | 420 | 17 | # Types
from typing import Union, Optional
import numpy as np
import torch
ArrayOrTensor = Union[np.ndarray, torch.Tensor]
OptionalArrayOrTensor = Optional[ArrayOrTensor]
# models
from .pairwise import Pairwise
from .pairwise import Pairwise as Ising
from .independent import Independent
from .rp import RP
from .rp i... |
3541020d311281475415dc29e44be15f69861084cf550ed1b395f5c00fd32e65 | Python | 420 | 14 | from __future__ import division, print_function
import numpy as np
class gaussian:
def __init__(self, mu, var):
self.mu = mu
self.var = var
self.sigma = np.sqrt(var)
def loglik(self, weights):
exponent = -0.5 * (weights - self.mu) ** 2 / self.var
log_coeff = ... |
8ae0961670ab4aba285ab3cbab30d5fbe55ee048d270b440f9bc9aea848c9583 | Python | 420 | 17 | import bpy
import molecularnodes as mn
def test_template():
mn.assets.template.install()
bpy.ops.wm.read_homefile(app_template="Molecular Nodes")
assert not bpy.data.objects.get("Cube")
mn.assets.template.uninstall()
try:
bpy.ops.wm.read_homefile(app_template="Molecular Nodes")
as... |
bcd7993c64f70d2373e00075a2c2fe6dfb47d1fc17b690e4205be11e6a993dbe | Python | 420 | 19 | import torch
def CORAL(source, target):
d = source.data.shape[1]
# source covariance
xm = torch.mean(source, 0, keepdim=True) - source
xc = xm.t() @ xm
# target covariance
xmt = torch.mean(target, 0, keepdim=True) - target
xct = xmt.t() @ xmt
# frobenius norm between source and targ... |
2a3d7ab95bd246c549856e96d651d54bc901a508d4a2d9563dc5ed4a9bc4b8de | Python | 421 | 7 | from .builder.aln import ALNNetwork, ALNNode
from .builder.fitzhugh_nagumo import FitzHughNagumoNetwork, FitzHughNagumoNode
from .builder.hopf import HopfNetwork, HopfNode
from .builder.thalamus import ThalamicNode
from .builder.wilson_cowan import WilsonCowanNetwork, WilsonCowanNode
from .builder.wong_wang import Redu... |
365ecd5168e98e9cbc8cc59897a838e421ef716e9a77ec2a9bf292620b834d39 | Python | 421 | 9 | from ..utils import IKFastInfo
from ..ikfast import *
#FRANKA_URDF = "models/franka_description/robots/panda_arm.urdf"
#FRANKA_URDF = "models/franka_description/robots/hand.urdf"
FRANKA_URDF = "models/franka_description/robots/panda_arm_hand.urdf"
PANDA_INFO = IKFastInfo(module_name='franka_panda.ikfast_panda_arm', b... |
596df61d8fd888803dc37643dcf1293177e6474bb50e5c3bf45c5e060810b6ea | Python | 421 | 15 | #!/bin/env python
outfile = '../SAMPL7-user-map-HG.csv'
# Read user map from submission server
file = open('/Users/dmobley/SAMPL/submissions/downloads/submission_table.txt', 'r')
text = file.readlines()
file.close()
# Write output file, removing e-mail addresses
file = open(outfile, 'w')
for line in text:
tmp = ... |
8e20c656a65a4cba6069a89701599a9ef030a07b927bf2bc99621746f675fe85 | Python | 422 | 28 | # .. an example with a for loop ..
import time
def test_1():
a = {}
for i in range(10000):
a[i] = i + 1
return
@profile
def test_2():
a = [1] * (10 ** 6)
b = [2] * (2 * 10 ** 7)
del b
for i in range(2):
a = [1] * (10 ** 6)
b = [2] * (2 * 10 ** 7)
del b
... |
086112e7f4128f8b980b3d9c0bcdf5089d7b93cc032e9948e814913a7474963e | Python | 424 | 17 | #!/usr/bin/env python
# -*- encoding: utf-8 -*-
import json
import bindings as bi
def main():
bi.init("Docs Json", "../../../h2o-docs", clear_dir=False)
bi.vprint("Writing schemas.json...")
bi.write_to_file("schemas.json", json.dumps(bi.schemas(raw=True)))
bi.vprint("Writing routes.json...")
bi.w... |
876819a81bf4bd573d63839da401a29ba2c0fb986de9c1a637f7bf9ebc16add5 | Python | 425 | 9 | """Registration-pipeline output viewers and writers.
This package owns code that knows how to walk a completed registration
output directory (01_affine/ - legacy runs: 01_axis_alignment/ -,
02_nonlinear/, 03_laplacian_refinement/, registered_points/, etc.) and
surface its contents to napari or other consumers. Th... |
b10166b87b22f2dcd75462894b5ab69cb4ea5e8a3a05359e246ff64f73dbcb16 | Python | 426 | 22 | # external
import pytest
# project
import textdistance
ALG = textdistance.Bag
@pytest.mark.parametrize('left, right, expected', [
('qwe', 'qwe', 0),
('qwe', 'erty', 3),
('qwe', 'ewq', 0),
('qwe', 'rtys', 4),
])
def test_distance(left, right, expected):
actual = ALG(external=False)(left, right)
... |
f915f564f9132ac9c1b0b05c84ad33c69153d8752e4e8150a29a2f56e99fb79d | Python | 426 | 16 | import torch.nn as nn
# Model should include nn.LogSoftmax layer
def nll_loss(*args, **kwargs):
return nn.NLLLoss(*args, **kwargs)
def cross_entropy(*args, **kwargs):
return nn.CrossEntropyLoss(*args, **kwargs)
# Model should include nn.Sigmoid layer
def bce_loss(*args, **kwargs):
return nn.BCELoss(*arg... |
09514217b8ed60f12f5df0c1f1b5257b1c3c0195ad31d79d3d5f17f3e41b4e9f | Python | 427 | 9 | from .src.absolute import absolute as absolute
from .src.hardtanh import hardtanh as hardtanh
from .src.heaviside import heaviside as heaviside
from .src.precomputed import precomputed_lut as precomputed_lut
from .src.precomputed import precomputed_scalar as precomputed_scalar
from .src.prelu import prelu as prelu
from... |
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