sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
1a7166eba214be02e44f56ee6da355c39d423400d6e86dd9cb71060a6a2806f0 | Python | 651 | 31 | # pylint: disable=too-many-function-args, invalid-name, unused-argument
""" HCP MNI dataset loading script"""
import numpy as np
import pandas as pd
from omegaconf import DictConfig
from src.settings import DATA_ROOT
def load_data(
cfg: DictConfig,
dataset_path: str = "/data/users2/ppopov1/datasets/hcp_mni/... |
7882adf80cabcb78a054c67bb0566fcd3fddcde72c2e2e9a87cd3fbbb4870e68 | Python | 651 | 17 | from pytorch_image_classification.scheduler.combined_scheduler import (
CombinedScheduler, )
from pytorch_image_classification.scheduler.components import (
ConstantScheduler, )
class MultistepScheduler(CombinedScheduler):
def __init__(self, steps, base_lr, gamma, milestones):
lrs = [base_lr * gam... |
e1fff5812a6e13fc1dd1766efe2ac30e1c33f978b9b1b5b38c88488b4fc97da2 | Python | 651 | 18 | try:
import binutil # required to import from dreamcoder modules
except ModuleNotFoundError:
import bin.binutil # alt import if called as module
from dreamcoder.domains.regex.main import main, regex_options
from dreamcoder.dreamcoder import commandlineArguments
from dreamcoder.utilities import numberOfCPUs
... |
e62ff436aba94d5017326b25e4a7eee326dc18bbee79b94a83c63ce0c34e8aab | Python | 651 | 24 | """Headless check that the pixel-size field exists and flows to _get_params."""
import os
import pytest
os.environ.setdefault("QT_QPA_PLATFORM", "offscreen")
@pytest.fixture
def tab():
pytest.importorskip("PySide6")
from PySide6.QtWidgets import QApplication
app = QApplication.instance() o... |
8fb42c31e45012dd91ecdc43c6a6ea983b23430923243ae16cbd583bbc0bf51d | Python | 652 | 18 | import os
from torch.utils.cpp_extension import load
_src_path = os.path.dirname(os.path.abspath(__file__))
_backend = load(name='_hash_encoder',
extra_cflags=['-O3'], # '-std=c++17'
extra_cuda_cflags=[
'-O3',
'-U__CUDA_NO_HALF_OPERATORS__', '-U_... |
ca8c341000805bfa51bea471a94d5c467260f1601e12dcfbef93e8e785ac246f | Python | 652 | 19 |
try:
import binutil # required to import from dreamcoder modules
except ModuleNotFoundError:
import bin.binutil # alt import if called as module
from dreamcoder.domains.list.main import main, list_options
from dreamcoder.dreamcoder import commandlineArguments
from dreamcoder.utilities import numberOfCPUs
... |
620ecf5fdea8e66c5e532e03f003a4ab9cc58c955e34c110e21df83860d3e2ed | Python | 653 | 27 | from ..neuralnodes import params
import dataclasses
@dataclasses.dataclass
class Params(params.Params):
filter_inh_dur: float = 8.0
filter_inh_gain: float = 1.0
filter_delay: float = 7.0
filter_exc_dur: float = 4.0
filter_exc_gain: float = 0.1
def _make_bounds(self):
self.bounds = {... |
b642cef338a79f8b20adb9293356f558e64f8759438f553eac565cf60cd5fb1e | Python | 653 | 31 | """
Set of utilities for segmentation and analysis of n-dimensional images.
# Author: Vladan Lucic (Max Planck Institute for Biochemistry)
# $Id$
"""
from __future__ import unicode_literals
from __future__ import absolute_import
__version__ = "$Revision$"
from . import util
from . import core
from . import grey
from... |
7fc3d3d4ac057188eea45101e848d47519cc5e8712f4d7da6a2b99a8babb079a | Python | 654 | 17 | from nnunetv2.training.nnUNetTrainer.nnUNetTrainer import nnUNetTrainer
import torch
import torch._dynamo
torch._dynamo.config.suppress_errors = True
class nnUNetTrainer_DefaultLoss(nnUNetTrainer):
def __init__(self, plans: dict, configuration: str, fold: int, dataset_json: dict, unpack_dataset: bool = True,
... |
5e78cb7bc8c0c7ad71669fbffbc117915e8c793442664666bd691e7c0262ed04 | Python | 655 | 28 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
import common_setup
REVS = ["issue269-base", "issue269-v1"]
LIMITS = {"search_time": 600}
SUITE = suites.suite_satisficing_with_ipc11()
CONFIGS = {
"random-successors": ["--search", "lazy_greedy(ff(),randomize_successors=true)"],
"p... |
7765ad2995153022642107c2c22e957916d0dfa6cc7435ced3090f55cc1e2959 | Python | 655 | 28 | #!/bin/env python
"""
OXASL - Prefiltering module
This is run before any model fitting and is intended for volume selection, denoising etc.
Pre-filtering processes do not depend on the type of ASL data (e.g. multiphase, vessel-encoded)
Copyright (c) 2008 University of Nottingham
"""
try:
import oxasl_enable
exce... |
b823a1346df35d8e557ecec99431bea143b9e37fcfbe92c9a02dadd9de42d680 | Python | 655 | 28 | import setuptools
setuptools.setup(
name="PyReliMRI",
version="2.1.0",
description="A package for computing reliability of fMRI images",
packages=setuptools.find_packages(),
install_requires=[
"numpy",
"pandas",
"pytest",
"nilearn",
"nibabel",
"scipy"... |
27348bcf0b156a384fdc66f8af09ca385f66de8d8fb8c634eadf77000a4f9ba9 | Python | 656 | 25 | from typing import TypeVar
from elasticai.creator.graph._types import NodeConstraintFn
from .vf2 import Graph, find_all_matches, match
TP = TypeVar("TP")
T = TypeVar("T")
class SubGraphMatchError(Exception):
def __init__(self):
super().__init__("No matching subgraph found")
def find_subgraph(
pat... |
40cb61893911d5043737ffba62f8550989590087ff234e6c217daad1f2eeebdb | Python | 656 | 17 | from __future__ import annotations
from wikibaseintegrator.models.language_values import LanguageValue, LanguageValues
class Labels(LanguageValues):
def from_json(self, json_data: dict[str, dict]) -> Labels:
"""
Create a new Labels object from a JSON/dict object.
:param json_da... |
d34e34ac77369fc1d83a765811f998caf9712417d5a146ee3ba147cd4ebabbe4 | Python | 656 | 26 | from matplotlib import pyplot as plt
from matplotlib import animation
import seaborn as sns
def animate_matrix_change(matrices, file_path='animation.gif', fps=60):
"""
Plot a list of equally shaped matrices as an animation.
"""
assert len(matrices) >= 2
fig = plt.figure()
frames_qty = len(ma... |
ee0d1b8b7525de672b7934b2d774de26182204a9e47964bcf438d88f4ce61191 | Python | 656 | 17 | from __future__ import annotations
from wikibaseintegrator.models.language_values import LanguageValue, LanguageValues
class Lemmas(LanguageValues):
def from_json(self, json_data: dict[str, dict]) -> Lemmas:
"""
Create a new Lemmas object from a JSON/dict object.
:param json_da... |
f5e2a655903d5421bbaf48ea1661aeba97412dee43f726e9514751bc54e34aa4 | Python | 656 | 25 | ### Submit script "XY.py" to HPC (Slurm) cluster
import subprocess
## Configurable job parameters
job_name = "create_is-distance_matrices_CONTROL_length" # Name of the job
output_file = f"{job_name}.out"
error_file = f"{job_name}.err"
script_to_run = "create_is-distance_matrices_CONTROL_length.py" # Name of the script... |
99500f31120613df2097a7974370b65a8faa3ce825f656c7f90fd8b1b2eea9e8 | Python | 657 | 21 | from setuptools.command.setopt import edit_config, option_base
class saveopts(option_base):
"""Save command-line options to a file"""
description = "save supplied options to setup.cfg or other config file"
def run(self):
dist = self.distribution
settings = {}
for cmd in dist.com... |
81739f72124776983fb7c1f8f650e3fcf82ed3217444f08bbd983d8e982f4ddf | Python | 658 | 28 | from tqdm import tqdm
from protonets.utils import filter_opt
from protonets.models import get_model
def load(opt):
model_opt = filter_opt(opt, 'model')
model_name = model_opt['model_name']
del model_opt['model_name']
return get_model(model_name, model_opt)
def evaluate(model, data_loader, meters, d... |
b26db6b54536ccb9efe4e3b0216b8159b14c71d700b5c78a461f8fe5b8e94c8c | Python | 658 | 27 | from abc import abstractmethod
from typing import Protocol, runtime_checkable
from torch import Tensor
from elasticai.creator_plugins.grouped_filter import FilterParameters
@runtime_checkable
class LutronModule(Protocol):
@abstractmethod
def forward(self, x: Tensor) -> Tensor: ...
@abstractmethod
d... |
df7c9d6648bc5a75d95109696654144c4c431c3c9f1c172eb6a83e0f148fac1f | Python | 658 | 17 | from typing import Callable, Optional
import torchvision
from Utilities.transforms import get_transforms
class MnistDataset(torchvision.datasets.MNIST):
def __getitem__(self, index: int):
img, target = super().__getitem__(index)
return {"data": img, "label": target}
def get_mnist(train, config):
... |
0a2c4e8c302e3c4e48c4b544ab4a6620dbfc7155bf9864bee5ae03323d1a61e8 | Python | 659 | 23 | """Basic analysis tools."""
from .file_dictionary import FileDictionary
from .annotation_util import (
check_df_columns,
df_to_hed,
extract_tags,
generate_sidecar_entry,
hed_to_df,
str_to_tabular,
strs_to_sidecar,
to_strlist,
)
from .event_manager import EventManager
from .hed_tag_manag... |
ba001220edb0d685321fcfc23aa4365ffb34ac38636e1402df2268703d378767 | Python | 661 | 26 | # This file is dual licensed under the terms of the Apache License, Version
# 2.0, and the BSD License. See the LICENSE file in the root of this repository
# for complete details.
__all__ = [
"__title__",
"__summary__",
"__uri__",
"__version__",
"__author__",
"__email__",
"__license__",
... |
e3f71dea1f626b7d9eab4ea81b85dd1226d6aa6ebd730909acefb48fca56a2d1 | Python | 661 | 27 | from omegaconf import DictConfig
import numpy as np
from . import reducer_factory
def apply_dimred(X: np.ndarray, cfg: DictConfig):
'''
Applies dimensionality reduction to X and returns the reduced data matrix
Parameters
-----------
X: np.ndarray
Latent space vectors of shape n_sample... |
15de1ed3a7dbc9eda60fa97191f3d6a8de8f5a9d900d080b588f8a80e436c61e | Python | 663 | 31 | # pylint: disable=too-many-function-args, invalid-name, unused-argument
""" HCP non MNI dataset loading script"""
import numpy as np
import pandas as pd
from omegaconf import DictConfig
from src.settings import DATA_ROOT
def load_data(
cfg: DictConfig,
dataset_path: str = "/data/users2/ppopov1/datasets/hcp_... |
4087e2d2e6efb3a6f721bf287e50e5bfd59b883ce54917ef910d39343991c250 | Python | 663 | 33 | from typing import Union
import numpy as np
from scipy.stats import spearmanr
from torch import Tensor
def get_summary(
model: str,
seed: int,
num_exp: int,
v_caus: float,
v_hp: float,
scale: float,
weight: float,
ss_n: float,
e_star: Union[Tensor, np.ndarray],
e_sim: Union[Ten... |
d8de4c244dc2a4eb7e900e9acecf0feedc72eb78f5f400a9e84d0ce2f0bb876a | Python | 663 | 34 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
from relativescatter import RelativeScatterPlotReport
import common_setup
REVS = ["issue582-base", "issue582-v1"]
SUITE = suites.suite_optimal_with_ipc11()
CONFIGS = {
"astar_lmcut": [
"--search",
"astar(lmcut())"],
}
ex... |
e40b74468c2b8d33e9643567ffae1cbc6271b074b377629e0545dfc28d7e3eb9 | Python | 663 | 14 | # Copyright (c) 2023-2024 Blue Brain Project/EPFL
# 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 agreed ... |
dbed128f24e3dde8658f68290f5523d1d79201a6e4eed890086e78ca40bebea6 | Python | 664 | 23 | import torch
import torch.nn as nn
class Network(nn.Module):
def __init__(self, sched_iter=32):
super(Network, self).__init__()
dtype = torch.cuda.DoubleTensor
self.l1 = nn.Linear(sched_iter, 300).type(dtype)
self.relu1 = nn.ReLU().type(dtype)
self.l2 = nn.Linear(300, 300).... |
cebced9b8b25709823195b342f56f653771c73ef4b95a1f6fb8bf7cf28cb0209 | Python | 666 | 14 | """Cell-analysis helpers retained after the HTML builders retired.
The HTML-rendering functions this module used to carry (top-N table,
hemisphere asymmetry note, parent-structure roll-up) are superseded by the
data-driven mounts in ``mounts.py`` / ``report_render.js``, sourced from
``point_sets.py`` - see ``RETI... |
3f4acb87051856c15dbc78d7a702fd0900798fe26e18440c4014375c046c3537 | Python | 667 | 25 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Aug 12 18:57:59 2020
@author: usingh
"""
import psutil
import multiprocessing
###Estimate procs and chunk
#total cores available
_max_procs=int(multiprocessing.cpu_count())
#total system memory in MB
mem_values=psutil.virtual_memory()
_max_mem=mem_valu... |
e74e45628cceacf1f9901893a4e8796c295be0d77e2dd2897f5ca4f714cdc9d4 | Python | 667 | 29 | #!/usr/bin/env python
import sys, subprocess, re
import matplotlib.pyplot as plt
INFILE = sys.argv[1] if (len(sys.argv) == 2) else "outputs_from_test/stdout.out"
x = []
y = []
nres = 0
for line in open(INFILE) :
tokens = re.split("\s+",line.strip())
dssp_energy = float(tokens[12])
xi = int(tokens[0])
y... |
032b852e49745605fa977b9a98e6dff2a8d5fec984cfc88c9571d500398d46e2 | Python | 668 | 26 | #!/bin/env python3
'''
Example script to plot a sensor
'''
import ithildin as ith
import matplotlib.pyplot as plt
import numpy as np
import sys
# read simulation results
stem = sys.argv[1] if len(sys.argv) > 1 else 'results/bayes_26'
sd = ith.SimData.from_stem(stem)
label_time = 't'
for idxs, sensor in sd.sensors.it... |
8915c9aa04aebc0a69db0415e95d58014ca415db94e9b1b92cbe93d3fe52c83b | Python | 668 | 24 | # -*- coding: utf-8 -*-
#
# Supported Syncopy classes and file extensions
#
def _data_classname_to_extension(name):
return "." + name.split("Data")[0].lower()
# data file extensions are first word of data class name in lower-case
supportedClasses = (
"AnalogData",
"SpectralData",
"CrossSpectralData"... |
b536bf178abba3ba9bc049c19a32d49ac0c75224e09ec37486b6ae7bd9e24b4b | Python | 668 | 19 | import torch
import yacs.config
from pytorch_image_classification.config.config_node import ConfigNode
def get_env_info(config: yacs.config.CfgNode) -> yacs.config.CfgNode:
info = {
'pytorch_version': str(torch.__version__),
'cuda_version': torch.version.cuda or '',
'cudnn_version': torch... |
bdc0da23123194a223a3973bb6ef243e890c82939a639e4aaf1cd083d87382e5 | Python | 668 | 24 | """
SLIDING WINDOW AND AGEING FUNCTIONS
These functions calculate the beginning of the sliding window and ageing coefficients for AnDePeD.
"""
# calculating window
def update_window_beginning(self, time):
if time - self.WINDOW_SIZE + 1 <= self.B:
self.window_beginning = self.B
else:
self.wind... |
4ecc3049d33ed7978a59e6b29b35d3b8a4081674ee44ade1a81031796674be2d | Python | 669 | 29 | from constants import var_t15
from constants import var_t5
from constants import var_t7
from constants import var_t2
from constants import var_t0
from constants import label_weak_strong
from constants import label_large
from constants import label_norm
def choose(ac):
if ac == 't2':
return var_t2
if a... |
efa7e181fa856489a221c9070120b7f786ea76c5151331915b7f417a76dff9f6 | Python | 669 | 28 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import downward.suites
import common_setup
CONFIGS = {
"ehc_ff": [
"--search", "ehc(ff())"],
"ehc_add_pref": [
"--heuristic", "hadd=add()", "--search", "ehc(hadd, preferred=[hadd])"],
#"ehc_add_ff_pref": [
# "--search", "ehc(add(), pre... |
08394f2443617cb46462ec6416570757da0c2b6de4a9b1645a6b7dda2420c9fc | Python | 670 | 26 | import os
import pytest
os.environ.setdefault("QT_QPA_PLATFORM", "offscreen")
@pytest.fixture(scope="module")
def app():
from PySide6.QtWidgets import QApplication
a = QApplication.instance() or QApplication([])
yield a
def test_config_menu_registers_and_rethemes(app):
from regtools... |
a9a95c41c3ea984a943e6082a14ca61148d1fc2e88e6291ecfe4cbe37d266c65 | Python | 671 | 25 | import string
CHARS = string.digits + string.ascii_uppercase + string.ascii_lowercase
CHARSLEN = len(CHARS)
def number_to_compact_repr(num):
if num < 0:
return f"-{number_to_compact_repr(-num)}"
assert isinstance(num, int)
s = ""
while num:
s = CHARS[num % CHARSLEN] + s
num //... |
e919e7459cc075fc50f4cafded69ecaf3785a3b60eabfe6e06617cbe17e80ff0 | Python | 671 | 25 | import torch.nn as nn
import numpy as np
from abc import abstractmethod
class BaseModel(nn.Module):
"""
Base class for all models
"""
@abstractmethod
def forward(self, *inputs):
"""
Forward pass logic
:return: Model output
"""
raise NotImplementedError
... |
fbe88a0c2b32efc9ee4ca596620f7cf717cd99071ef6111a2647493493711fb0 | Python | 671 | 28 | from setuptools import setup, find_packages
setup(
name="fastglioma",
version="1.0",
packages=find_packages(),
install_requires=[
"setuptools",
"pip",
"pytest",
"yapf",
"tqdm",
"pyyaml",
"pytest==8.3.2",
"pandas==1.5.3",
"numpy==1.... |
128242f20558308bf6b40d4da550365c3c824f5a86a780449fb697ff9bded60c | Python | 672 | 31 | import sys
def _pythonlib_compat():
"""
On Python 3.7 and earlier, distutils would include the Python
library. See pypa/distutils#9.
"""
from distutils import sysconfig
if not sysconfig.get_config_var('Py_ENABLED_SHARED'):
return
yield 'python{}.{}{}'.format(
sys.hexversi... |
be15c20723ce95ad89bbe8cf19f16bcbb6d7a70da0529edeea82920f53b6d4e1 | Python | 672 | 28 | # UTILITY FUNCTIONS
#####################
import tensorflow as tf
def tf_mat_vec_dot(matrix, vector):
"""
Matrix product between matrix and vector.
"""
return tf.matmul(matrix, tf.expand_dims(vector, 1))[:, 0] # TODO: tf.linalg.matvec(matrix, vector)
def tf_outer_product(first_vec, second_vec):
... |
c3644113b989b6b39fe75e9639354242505a0aa5ea421176a9e06a5c85205318 | Python | 672 | 27 | from importlib import import_module as _import_module
_EXPORTS = {
'plot_signal': '.raw',
'plot_raw_topomap': '.topomap',
'plot_feature_topomap': '.topomap',
'plot_3d_tensor': '.tensor',
'plot_2d_tensor': '.tensor',
'plot_adj_connectivity': '.connectivity',
'plot_graph': '.graph',
}
__all... |
dc9bbca68cbfaa5cfd27e92080e54a5ed4b3b0ba78e0e26fa2ed657ab892be74 | Python | 672 | 23 | """Small thread-safe copies of measured observatory state."""
from __future__ import annotations
from copy import deepcopy
from threading import RLock
from typing import Any
class Telemetry:
def __init__(self, **initial: Any):
self._lock = RLock()
self._values = dict(initial)
self._values... |
0c96b1b6827a9570121e066fab9ca260c3789ed81b4e593cbefae2d087508277 | Python | 674 | 24 | import torch
import torch.nn as nn
class Network(nn.Module):
def __init__(self):
super(Network, self).__init__()
dtype = torch.cuda.DoubleTensor
sched_iter = 30
self.l1 = nn.Linear(sched_iter, 300).type(dtype)
self.relu1 = nn.ReLU().type(dtype)
self.l2 = nn.Linear... |
3681658f7402239038df4a695b8df3e68bffa4f725c19cf6b0642d025fb646fe | Python | 674 | 17 | from __future__ import annotations
from wikibaseintegrator.models.language_values import LanguageValue, LanguageValues
class Descriptions(LanguageValues):
def from_json(self, json_data: dict[str, dict]) -> Descriptions:
"""
Create a new Descriptions object from a JSON/dict object.
... |
4cadd8bd0b96bd2e18fe57fda7e30d1cb504c0a422311a52f40639dfcb3a0bbf | Python | 674 | 24 | import autograd.numpy as np
from autograd import grad
from autograd.builtins import isinstance
def test_isinstance():
def checker(ex, type_, truthval):
assert isinstance(ex, type_) == truthval
return 1.0
examples = [
[list, [[]], [()]],
[np.ndarray, [np.zeros(1)], [[]]],
... |
7f47ad7cce0a2ed363f631334c8b0ac838af91bc291732cb19789f92fdc5aef9 | Python | 675 | 22 | import warnings
import torch
def simulate_bitshifting(
x_q: torch.IntTensor, m_q_shift: torch.IntTensor, m_q: torch.IntTensor
):
# TODO: check if torch.int64 could be downgraded to torch.int32
x_q = x_q.to(torch.int64)
m_q_shift = m_q_shift.to(x_q.device)
m_q = m_q.to(torch.int64).to(x_q.device)
... |
a590205cdcfab513d41671c068a27dd310200f480b3de99c135dfde99833ef7a | Python | 675 | 23 | from setuptools.extern.more_itertools import consume # noqa: F401
# copied from jaraco.itertools 6.1
def ensure_unique(iterable, key=lambda x: x):
"""
Wrap an iterable to raise a ValueError if non-unique values are encountered.
>>> list(ensure_unique('abc'))
['a', 'b', 'c']
>>> consume(ensure_un... |
c5a2774ca66c49c793bfc9f5117504830d90df87fc75227b6d85735f1dd6e12e | Python | 675 | 14 | import pandas as pd
import numpy as np
import scipy.stats as sci
def get_coexpression(gene_exp, gene_names):
rank_test_py_exp = sci.rankdata(gene_exp, method = 'average', axis = 1) #Row ranks
rank_test_py_exp = rank_test_py_exp - rank_test_py_exp.mean(axis = 1)[1] #Cente... |
ff3906aac4454dcba88c53ab7ef339537c0e6a4fd6a2e358c0495e9151ecd541 | Python | 675 | 29 | import torchio as tio
import sys
# I need to also pass in the number of the label that we're doing this for
if (len(sys.argv) != 5):
print('\n\nUsage: python betcrop.py <T1> <T2> <MASK> <BASE>\n\n')
exit()
# transform the t1, t2, and mask
subject = tio.Subject(
t1=tio.ScalarImage(sys.argv[1]),
t2=t... |
172c13b374d06876c2b47c089eaf14b93e34bbebf8a31a1fd790dd5814fca89b | Python | 676 | 25 | import torch
from .ball import Poincare
from .hyperboloid import Lorentz
manifold_id = {Poincare:0, Lorentz: 1}
def get_manifold_id(x):
if isinstance(x, Poincare):
return 0
elif isinstance(x, Lorentz):
return 1
else:
raise NotImplementedError
#TODO don't need to include this
def t... |
79ae827e1293e287b1c0b89552a4c849bf7f3de46fa20560a39cea93fc3d7cf6 | Python | 676 | 17 | """
Package for handling surfaces
# Author: Antonio Martinez-Sanchez (Max Planck Institute for Biochemistry)
# Date: 1.05.17
"""
__author__ = 'Antonio Martinez-Sanchez'
from .utils import *
from .surface import Particle, ParticleL, TomoParticles, ListTomoParticles, SetListTomoParticles, Simulation, \
ListSimulat... |
5affd88163e1b0d1e1143197048164f54594513e1e7396532b7e4ebf0404972b | Python | 677 | 26 | """
Training and evaluation settings
"""
config = dict()
"""
Data related settings
"""
config['data_root'] = {
'78 100': 'serialized-data/data_78x100-seed_1',
'116 150': 'serialized-data/data_116x150-seed_1',
'232 300': 'serialized-data/data_232x300-seed_1',
'348 450': 'serialized-data/data_348x450-s... |
a0ae9c7533326704b57c4a42912561f798c343a439f6360c3d534e3045290824 | Python | 677 | 24 | # -*- coding: utf-8 -*-
def get(network_spec):
"""Retrieve a PiNN network
Args:
network_spec: serialized specification of network, or a Keras model.
"""
import tensorflow as tf
from pinn.networks.pinet import PiNet
from pinn.networks.bpnn import BPNN
from pinn.networks.lj import LJ
... |
9393287544b232b5aac195a4fd8dc33fa17cce89e426f382c8a554386ba8790a | Python | 678 | 17 | import torch
import torch.nn as nn
import torch.nn.functional as F
import yacs.config
class DualCutoutLoss:
def __init__(self, config: yacs.config.CfgNode, reduction: str):
self.alpha = config.augmentation.cutout.dual_cutout_alpha
self.loss_func = nn.CrossEntropyLoss(reduction=reduction)
def ... |
e6b7dfbffcf53fa8f3520440b3ddb27eb03b56750b2041dee219d73c3ddcbce9 | Python | 679 | 24 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
from lab.reports import Attribute
import common_setup
import os
exp = common_setup.IssueExperiment(
search_revisions=["issue479-v2"],
configs={
'dfp-b-50k': ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimul... |
eb74c4dbdc60fe947955c697affbaff58d4cbd6a5e6083b24ab460af5602f64e | Python | 679 | 15 | def test_batchrow_edit_fields_roundtrip():
from regtools.registration.gui.batch_2d_model import BatchRow
r = BatchRow(image_path="a.tif", atlas_edit_mask_path="e.nii.gz", atlas_edit_fill=5.0)
d = r.to_dict()
assert d["atlas_edit_mask_path"] == "e.nii.gz" and d["atlas_edit_fill"] == 5.0
r2 = B... |
cef17e5526229fab18d7ef958ea76817513321976e35f7c873dc53bc38e01f87 | Python | 680 | 24 | import cv2
import numpy as np
from PIL import Image
image_idx = "01"
gt_path = "/home/jenazzad/PycharmProjects/medical_image_segmentation/input/DRIVE/test/1st_manual/%s_manual1.gif"%image_idx
predicted_path = "/home/jenazzad/PycharmProjects/medical_image_segmentation/output/baseline_unet_aug_do_0.1_activation" \
... |
cfd187b66510eadbb37f5363cbb0eecf970825948d150813a2757827e568d107 | Python | 680 | 13 | from de.csbdresden.stardist import StarDist2D
args = getArguments()
print(args);
img_seg = args[0]
probability = args[1]
overlap = args[2]
model_file = args[3]
n_tiles = args[4]
#run("Command From Macro", "command=[de.csbdresden.stardist.StarDist2D],args=['input':'"+img_seg+"', 'modelChoice':'Model (.zip) from Fil... |
315edbd8f1095277a17c2462100c4e19ac00ecbb57aa7a63c70598a3bc027d21 | Python | 681 | 22 | #%%
import os
import numpy as np
import seaborn as sns
from xron.xron_train_supervised import main
import tkinter as tk
from tkinter import filedialog
root = tk.Tk()
root.withdraw()
#%% Load data
DF = filedialog.askdirectory()
# DF="/home/heavens/bridge_scratch/ELIGOS_dataset/IVT/control/kmers_guppy_4000_noise/"
chun... |
cd79a2e03ea4daba6c8d461ee0d2663c5df9d5723fbf523d8a7b6abe00f37fd2 | Python | 681 | 26 | from subprocess import CalledProcessError
import pytest
from cuppa.misc.executors import RscriptExecutor
class TestRscriptExecutor:
def test_crash_on_error(self):
executor = RscriptExecutor(
args=["dummy_rscript"],
ignore_error=True
)
executor.run()
asser... |
1a2f95dc6bf71067f27762d55e75687079c5969ddae94abbcd4444ce765cf2d7 | Python | 682 | 32 | from typing import Tuple
import pandas as pd
from .exposure import simulate_exposure
from .outcome import simulate_outcome
def simulate_agg_risk_and_dis_outc(
dfE: pd.DataFrame,
dfG: pd.DataFrame,
num_exp: int,
v_caus: float,
v_hp: float,
activation: str = "relu",
scale: float = 1.0,
... |
0df909621970bc76004c0ef2c601b9e2376209a5b678f05594cddebba4058976 | Python | 683 | 20 | from sys import argv
import pandas as pd
import nibabel as nib
from nilearn.image import clean_img, smooth_img
subject = argv[1]
task = argv[2]
strategy = argv[3]
nii = f'/m/cs/scratch/networks-pm/pm_denoise/{subject}/{subject}_task-{task}_SGdetrend.nii'
confound = f'/m/cs/scratch/networks-pm/pm_denoise/{subject}/{su... |
5df7bf45de34a0cc4f98a71e7a02c5247f773c2087ff5a155e3f94a631f883a6 | Python | 683 | 44 | import numpy as np
import scipy.stats
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
from topaz.methods import GE_KL, PN, PU, GE_binomial, autoencoder_loss
def test_autoencoder_loss():
pass
class TestPN():
def test_pn_init(self):
pass
def... |
7145cad721ee33804f474d84f5de4f9f4cccbbb1287bf084a07ae72b174414cc | Python | 683 | 28 | import numpy as np
class Quadratic_func:
def __init__(self, a=1, b=1):
self.a = a
self.b = b
self.name = 'quadratic'
self.formula = r'$\min\ f(x_1,x_2)={0}x_1^2+{1}x_2^2$'.format(self.a, self.b)
def function(self, x):
return self.a * x[0] ** 2 + self.b * x... |
d68d368f22d5badc69e930b660225849f539c354c1f67f52cb73230929df84f6 | Python | 683 | 21 | """ Generate txt files for MFA from excel file. """
import numpy as np
import pandas as pd
from pathlib import Path
from helpers import load_config
if __name__ == '__main__':
config = load_config('speech_config.yaml')
transcripts_dir = Path(config['stimuli_parameters']['stimuli_folder'])
transcripts_dir.... |
1463bb6623f4718e09f9ede79ecb4ee77f06d3b9addffc3f419e82318f457235 | Python | 684 | 14 | # if appear_feature is imported as a module, then logger will be effective.
# Otherwise, if appear_feature is ran as a script, logger will not be recognized
import logging
import os
import coloredlogs
logger = logging.getLogger(__name__)
logger.setLevel(os.environ.get('LOGLEVEL', logging.DEBUG))
# must have a handler, ... |
19f59b1a7f2a895f6225d04ccac2fed83e3cd9ebdeebb4962575261aa30f8fb4 | Python | 684 | 18 | from PIL import ImageDraw
from typing import Optional
from .shape import Shape, calculate_short_side
class Ellipse(Shape):
def draw(self, draw: ImageDraw.Draw, color: tuple[int, int, int]):
draw.ellipse((self.x, self.y, self.x + self.width, self.y + self.height), fill=color)
class HorizontalEllipse(Elli... |
71878e3a16e92b441ce98b9c0b5cc5845bb7350565e61f4a40992abf72f831ab | Python | 684 | 34 | from sklearn.linear_model import LinearRegression
import numpy as np
def linreg(
X: np.ndarray,
property: np.ndarray
):
'''
Perform linear regression of property vs X
Parameters
----------
X: np.ndarray
The free variables, shape n_samples x n_dimensions
property: np.ndarra... |
78c5eee18442bb861844b8ae7fcafa12ce7f694ae4ffd9a9283f43fec827fce1 | Python | 684 | 22 | import scipy.stats
import autograd.numpy as np
from autograd.extend import defvjp, primitive
from autograd.scipy.special import digamma
rvs = primitive(scipy.stats.dirichlet.rvs)
pdf = primitive(scipy.stats.dirichlet.pdf)
logpdf = primitive(scipy.stats.dirichlet.logpdf)
defvjp(
logpdf,
lambda ans, x, alpha: ... |
9e818e388f034cd26b2f2a8e830f4c42857424ab71e2f7f2c3d47dd17fe7a5c9 | Python | 684 | 26 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import common_setup
import downward.suites
# This experiment only tests the Lama-FF synergy, which sat1 did not
# test because it did not work in the issue77 branch.
CONFIGS = {
"synergy":
["--heuristic", "hlm,hff=lm_ff_syn(lm_rhw(reasonable_orders=true))",
... |
c142c48e257951f08c0e230e9f5c513c1d003bf0353124b96b78a7b46b362607 | Python | 684 | 19 | """Write MANIFEST.sha256.json: SHA-256 of every bundled data and configuration file.
Source code is identified by the git commit; this manifest pins the research inputs.
Run from the repository root after any intentional data change.
"""
import hashlib
import json
from pathlib import Path
ROOTS = ("data", "configs")
... |
c41408f88bd21d0756204922b79a0017cfdd5b0a2f78f9ec84303c094d60c279 | Python | 684 | 25 | # -*- coding: utf-8 -*-
# @Author: Sadamori Kojaku
# @Date: 2023-06-15 12:30:50
# @Last Modified by: Sadamori Kojaku
# @Last Modified time: 2023-06-15 12:50:47
import lfr
params = {
"N": 1000, # number of nodes
"k": 50, # average degree
"maxk": 100, # maximum degree
"minc": 20, # minimum commun... |
d361d175327222bd94e4f670f1b8534a06e2b44a6d6df01f674baefa6b01f2f6 | Python | 684 | 20 | import scipy.stats
import autograd.numpy as np
from autograd.extend import defvjp, primitive
from autograd.numpy.numpy_vjps import unbroadcast_f
cdf = primitive(scipy.stats.poisson.cdf)
logpmf = primitive(scipy.stats.poisson.logpmf)
pmf = primitive(scipy.stats.poisson.pmf)
def grad_poisson_logpmf(k, mu):
return... |
d651d36ef4a9276b38645476ea995628877f6c6602b3a2d657ae87ddf266769b | Python | 684 | 23 | """Testing module tree."""
from treem import Tree
def test_tree_traversal():
"""Tests tree traversal."""
tree0 = Tree()
tree1 = tree0.add(Tree())
tree2 = tree1.add(Tree())
tree3 = tree1.add(Tree())
pre = list(x for x in tree0.preorder())
post = list(x for x in tree0.postorder())
level... |
dfb40887b825a43fe2c99d1a83cd5b9085082f4a52cd16ab407930d0b2b230ac | Python | 685 | 29 | # set QT_API environment variable
import os
import sys
import argparse
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_usbspectrometer as gui
parser = argparse.ArgumentParser()
parse... |
5b4ead08146642bc9898cad15b6c109a6e6998d25231ba06145838daef0abdfb | Python | 686 | 19 | #
# Copyright Bradley Lowekamp
#
# 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.txt
#
# Unless required by applicable law or agreed ... |
d03cb98c31c01634c8d85b4bb9c83bf92f0e9fb88a4863c27971c3d9cb32b746 | Python | 686 | 30 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
import configs
import common_setup
REVS = ["issue436-base", "issue436-v1"]
LIMITS = {"search_time": 1800}
SUITE = suites.suite_satisficing_with_ipc11()
default_configs_satisficing = configs.default_configs_satisficing(extended=True)
CONFIGS... |
f869f4cb4cf6c606a5c906ffab2e2eadd08fdf64855ad6e14fd9d80db919ff2e | Python | 686 | 12 | STYLE_ITEMS = (
("spheres", "Spheres", "Space-filling atoms style."),
("cartoon", "Cartoon", "Secondary structure cartoons"),
("surface", "Surface", "Solvent-accsible surface."),
("ribbon", "Ribbon", "Continuous backbone ribbon."),
("sticks", "Sticks", "Sticks for each bond."),
("ball_and_stick"... |
0940abc242aa26d55f569b4584de2ff6af4cc2bdd971187ab364226dabbe8b4b | Python | 687 | 23 | """
WikibaseIntegrator Library
~~~~~~~~~~~~~~~~~~~~~
WikibaseIntegrator is a Wikibase library, written in Python, for human beings.
Basic read usage:
>>> from wikibaseintegrator import WikibaseIntegrator
>>> from wikibaseintegrator.wbi_config import config
>>> config['USER_AGENT'] = 'Item Get Notebo... |
3ba4f7f563475979000009e237d32b754b1b75ed06bc2acbbb3351ee72653b37 | Python | 687 | 22 | #!/usr/bin/env python
"""Django's command-line utility for administrative tasks."""
import os
import sys
def main():
"""Run administrative tasks."""
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "PeerJCode.settings")
try:
from django.core.management import execute_from_command_line
... |
bbeedb8778585a4ed2ca2c070b6be011f58c2f7bf5641f2325b3dece429a5fdc | Python | 687 | 30 | # pylint: disable=too-many-function-args, invalid-name
""" HCP Schaefer 200 ROIs (no FIX-ICA) dataset"""
import numpy as np
from omegaconf import DictConfig
from src.settings import DATA_ROOT
def load_data(
cfg: DictConfig,
dataset_path: str = DATA_ROOT.joinpath("hcp_schaefer/data_schaefer_200.npz"),
):
... |
600356b4019d2d530b5338cb95cb4a7ed20b17c36211e139262aaf079a951b18 | Python | 688 | 19 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
549838744a582c306c834ab164eea2aa38c15e8b703383fae508bc791debbf8b | Python | 689 | 31 | from __future__ import print_function
from openbabel import openbabel
mol = openbabel.OBMol()
print('Should print 0 (atoms)')
print(mol.NumAtoms())
a = mol.NewAtom()
b = mol.NewAtom()
mol.AddBond(1, 2, 1)
print('Should print 2 (atoms)')
print(mol.NumAtoms())
print('Should print 1 (bond)')
print(mol.NumBonds())
obCon... |
db09a6d33f0aa054aab357229098dc2878a9014ecb8f764a278c925081b94dcb | Python | 689 | 22 | from __future__ import annotations
import os
from pathlib import Path
from shutil import rmtree
TEST_RESULTS_DIR = Path(__file__).parent / "_test_results"
TEST_SCRATCH_DIR = Path(__file__).parent / "_test_scratch"
def pytest_sessionstart():
file_dir = Path(__file__).parent
os.environ["QUACC_CONFIG_FILE"] = ... |
174cbde7073ab1f9125b028a6bd364a86c3bef871f8f82c87b51f2d80084ef3c | Python | 690 | 28 | import pytest
import molecularnodes as mn
from .constants import data_dir
@pytest.fixture
def filepath():
return data_dir / "1f2n.bcif"
def test_bcif_init(filepath):
from molecularnodes.entities.molecule.reader import read_structure
reader = read_structure(filepath)
assert reader.file_path == filep... |
5d288097a1206646638521339ec8f2284c9e858de0821e72dca1494aea1492dd | Python | 690 | 29 | import torch
from torch import Tensor
from utils.common import Device
def masked_scaled_mse(
output: Tensor,
target: Tensor,
weight: Tensor,
node_ids: Tensor,
lambda_: float,
device=None,
spec_recons=None
) -> Tensor:
""" MSE loss.
"""
if device is None:
device = Device... |
ec95fe4079b75b2a416770be8c7c758a4be3c00a86255e10f498a5f6648618c2 | Python | 690 | 34 | from abc import abstractmethod
from typing import Protocol
from torch import Tensor
class Quantize(Protocol):
@abstractmethod
def quantize(self, a: Tensor) -> Tensor: ...
class MatMul(Protocol):
@abstractmethod
def matmul(self, a: Tensor, b: Tensor) -> Tensor: ...
class Add(Protocol):
@abstra... |
8b055394cf7e3c327d8f806313c7e5d8dfbacf7dc6647fa57de4f19df5ad7dad | Python | 692 | 17 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
bb30a93ed8d4180994f8db325566f0966812702169443cbe04b0d65c565cf4ca | Python | 693 | 22 | # Run interface for Cog
# https://cog.run/python
from cog import BaseRunner, Input, Path
class Runner(BaseRunner):
def setup(self) -> None:
"""Load the model into memory to make running multiple requests efficient"""
# self.model = torch.load("./weights.pth")
def run(
self,
i... |
cefa17a5cbe1cc1881162746cfda82d7f7e5b673a308c73e014c051e50bae76a | Python | 693 | 9 | """SIGN_AT_RISK.py 2026-09-24. Gives VERIFY V-49 (14 Sept) an output file: of the neurons undetermined at 95%,
how many have a runner-up transmitter of the opposite Pospisil sign? Output: 06-OUTPUT/sign_at_risk.txt"""
import pandas as pd
F = pd.read_parquet('D:/eucys/06-OUTPUT/flip_probabilities.parquet')
u = F.z_sl < ... |
1a233de8e4fe112eecb0cbfd7f83a278f34cbf5a6b0c531c5494342ff46cc310 | Python | 694 | 28 | import subprocess
import os
__version__ = "0.4.6"
base_version = __version__
__commit__ = ""
try:
_hsPath = os.path.abspath(os.path.dirname(__file__))
_commitFile = os.path.join(_hsPath, ".commit_version")
if os.path.exists(_commitFile):
with open(_commitFile) as f:
__commit__ = f.read... |
3cc40b4acd54a8cf14ef6811ef9974732a54a5ced97c65fd2c991d576ecac91d | Python | 694 | 14 | # Copyright 2022 HYBRID Team INCIA, UMR5287, CNRS, Université de Bordeaux
# 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 b... |
8a07d53d52d9f077a23e81ec5ce65a82a78dd806e6e79fbcdadd62813a0ae991 | Python | 694 | 29 | # set QT_API environment variable
import os
import sys
import argparse
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_displacement_measurement as gui
parser = argparse.ArgumentParse... |
91b118cea3abac80314cee3413b2e648a9e24ad333fdc3d95f4aa7404a27f895 | Python | 694 | 30 | from .base_graph import BaseGraph
from .graph import Graph, ReadOnlyGraph
from .graph_iterators import (
bfs_iter_down,
bfs_iter_up,
dfs_iter,
)
from .graph_rewriting import (
DanglingEdgeError,
get_rewriteable_matches,
produces_dangling_edge,
)
from .name_generation import NameRegistry
from .su... |
b7a2a18ccda14faa73e1eafea89faa9d6808b1fdf1b938aafe186e2519a7e8de | Python | 694 | 25 | from pathlib import Path
import time
import numpy as np
import openturns as ot
import seaborn as sns
import os
import pickle
import uptake.multiprocessing.run_studies_servor as umps
def build_initial_dataset(expected_sample_size):
testcase_id = "dataset_for_ANN_mechanadaptation_vs_passive_elliptic_news... |
ca608493e8d713022485f79ed6463fa146b61ad13afb2746f1318f43a6fcd2a1 | Python | 694 | 26 | import dotenv
import hydra
from omegaconf import DictConfig
# load environment variables from `.env` file if it exists
# recursively searches for `.env` in all folders starting from work dir
dotenv.load_dotenv(override=True)
@hydra.main(config_path="../configs/", config_name="train.yaml", version_base="1.1")
def mai... |
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