sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
df645f8a47d3040f0d1f06e4e77e87bfe20e17e8f6275fc540dd7cb6ca4120ff | Python | 380 | 13 | from pdearena.configs.config_coal import CoalVelocityVfracTempDeltaTPredConfig
from pdearena.utils.constants import Paths, CoalConstants
config = CoalVelocityVfracTempDeltaTPredConfig(
model="convNeXT-tiny-max",
noise_level=1e-2,
include_derivatives=True,
include_cfl_features=True,
lr=2e-4,... |
58ea3c5c17bbc0de788988db00aef1e875846d6bcfb11c9b045a0bce3eea2039 | Python | 384 | 24 | # -*- coding: utf-8 -*-
""" Imports dataset classes so they can be used directly
Submodules
==========
.. autosummary::
:toctree: _autosummary
fashion
tabulardataset
multidataset
"""
from .fashion import FashionData
from .multidataset import MultiDataset
__all__ = [
'fashion',
'tabular_data... |
0126bac522947b59487d421f8a9970549b7f209fcd37f6905050f50ad819940d | Python | 386 | 15 | from pycromanager import JavaClass, ZMQRemoteMMCoreJ
tester = JavaClass('org.micromanager.acquisition.internal.acqengjcompat.speedtest.SpeedTest')
pass
dir = r'C:\Users\henry\Desktop\data'
name = r'speed\test'
core = ZMQRemoteMMCoreJ()
num_time_points = 1000
show_viewer = True
output_dir = tester.run_speed_test(dir... |
db4b68ec30dae5cc21857c11006db3337f46c6b1fc62a2b4120e9f2fb638cd59 | Python | 386 | 16 | """
WSGI config for tffp 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/1.11/howto/deployment/wsgi/
"""
import os
from django.core.wsgi import get_wsgi_application
os.environ.setdefault("DJANGO_SETTING... |
8055235256007f31894c9e11e73989b0b32e70d1f93f3d78cbc824e2fc8bd616 | Python | 387 | 16 | """
Entrypoint module, in case you use `python -momicscope`.
Why does this file exist, and why __main__? For more info, read:
- https://www.python.org/dev/peps/pep-0338/
- https://docs.python.org/2/using/cmdline.html#cmdoption-m
- https://docs.python.org/3/using/cmdline.html#cmdoption-m
"""
import sys
from omicscop... |
cf57301b42b35ede05aba1442d326d19eb472b046621919522f9a537d0809276 | Python | 387 | 18 | from langchain_classic import storage
EXPECTED_ALL = [
"EncoderBackedStore",
"InMemoryStore",
"InMemoryByteStore",
"LocalFileStore",
"RedisStore",
"InvalidKeyException",
"create_lc_store",
"create_kv_docstore",
"UpstashRedisByteStore",
"UpstashRedisStore",
]
def test_all_impor... |
cc5ace3c7808592f34d855fd24489ff93f14a1483a0fba65736ef85414201358 | Python | 388 | 10 | import morgana.ImageTools.compositeImageJ
import morgana.ImageTools.io
import morgana.ImageTools.processfeatures
import morgana.ImageTools.fluorescence
import morgana.ImageTools.locoefa
import morgana.ImageTools.morphology
import morgana.ImageTools.objectsparsing
import morgana.ImageTools.preprocessing
import morgana.I... |
f958d33048d85bd70d923e13d31be44e97509d3bc999ae3326191cf81b822529 | Python | 388 | 15 | import torch,sys
import torch.nn as nn
from functools import partial
import logging,pickle
import ml_collections
import numpy as np
import torch,math
import torch.nn as nn
from typing import Dict, Optional, Tuple
# change unbound rsa loss : need to exclude probe, add exclude probe flag
# add unbound sidechain predictio... |
3541633be7baa08d89b0bcea99e7e81d831d87e835f9972ec7c0978fdc9b6446 | Python | 390 | 12 | from glob import glob
import imageio
if __name__ == '__main__':
images = []
experiment_name = 'Experiment_00'
for filename in sorted(
glob(f'models/unet_se_resnet50_3101_2254/images_per_epoch/{experiment_name}_epoch_*.png'),
):
images.append(imageio.imread(filename))
imageio.mimsav... |
7567744a5fd77a2ecf6f90e3fec622528024775bffd0bf1b22c2aab70b76e8ca | Python | 390 | 15 | """
This script downloads a file containing the Allen Brain Atlas 10um hierarchy. "1.json"
"""
import json
import urllib.request
path = "http://api.brain-map.org/api/v2/structure_graph_download/1.json"
with urllib.request.urlopen(path) as url:
data = json.load(url)
with open("data/1.json", "w", encoding="utf-8... |
83412c5d7f9e490f7287228941b0312c7beae9f78818353834ed76bdc8352157 | Python | 392 | 17 | """Different ways to combine documents."""
from langchain_classic.chains.combine_documents.reduce import (
acollapse_docs,
collapse_docs,
split_list_of_docs,
)
from langchain_classic.chains.combine_documents.stuff import (
create_stuff_documents_chain,
)
__all__ = [
"acollapse_docs",
"collapse... |
60b31a232fc9510e020e2a0191efa14bdf5454fbdc944b8818556a7f7609a6bb | Python | 394 | 23 | """Internal representation of a structured query language."""
from langchain_core.structured_query import (
Comparator,
Comparison,
Expr,
FilterDirective,
Operation,
Operator,
StructuredQuery,
Visitor,
)
__all__ = [
"Comparator",
"Comparison",
"Expr",
"FilterDirective",... |
daad4542c78d6572e778e63ce58fce21b74c9690a0843321219add799063c442 | Python | 394 | 18 | """Cross Encoder interface."""
from abc import ABC, abstractmethod
class BaseCrossEncoder(ABC):
"""Interface for cross encoder models."""
@abstractmethod
def score(self, text_pairs: list[tuple[str, str]]) -> list[float]:
"""Score pairs' similarity.
Args:
text_pairs: List of ... |
523d7e88980f91139333e024ba077151f541c3d5c8302ec3013b08c540a9bdd1 | Python | 395 | 13 | """Run one of the shared servers over stdio, chosen by argv.
`MCPAdapter` launches this as a subprocess; it is not part of the API being
demonstrated.
"""
import sys
from _servers import run_calculator_stdio, run_weather_stdio
if __name__ == "__main__":
which = sys.argv[1] if len(sys.argv) > 1 else "weather"
... |
985175c3a1c502d31722b3963a8e372eb052b2674a6b7c0cf59f209d638ce8c7 | Python | 396 | 12 | #!/usr/bin/python
import sys
import json
import os
doc = json.loads(sys.stdin.read())
if doc['input']['mode'] == 'local' and (doc['input']['user'] == doc['state']['clientId']):
raise Exception('local throws error with runid: ' + os.path.basename(os.path.normpath(doc['state']['baseDirectory'])))
output = { "outpu... |
1e14e83a1b1b632c577f66b0b4b9a956c3f6446fe41dd6b28fc570d3615a6106 | Python | 398 | 13 | from pdearena.configs.config_blast import BlastVelocityDensityTemperatureDeltaTPredConfig
from pdearena.utils.constants import Paths, BlastConstants
config = BlastVelocityDensityTemperatureDeltaTPredConfig(
model="convNeXT-tiny",
noise_level=1e-2,
include_derivatives=True,
include_cfl_features=T... |
7255eef7dcdc931154f4e37d1cc6e3ef3a27529bab2e85af82a8c4005afdfe34 | Python | 398 | 11 | from langchain_core.prompts import PromptTemplate
prompt_template = """Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.
{context}
Question: {question}
Helpful Answer:""" # noqa: E501
PROMPT = PromptTemp... |
beb00d64ae0dbadfd6f0d5bfa2087048c4465b1871d3b6d3c96a1a4930d93a4d | Python | 399 | 18 | from langchain_core.callbacks import __all__
EXPECTED_ALL = {
"RetrieverManagerMixin",
"LLMManagerMixin",
"ChainManagerMixin",
"ToolManagerMixin",
"CallbackManagerMixin",
"RunManagerMixin",
"BaseCallbackHandler",
"AsyncCallbackHandler",
"BaseCallbackManager",
"Callbacks",
}
de... |
50853d47bde01d269eed940f67db36d3dc3752bcc0de040bf5f8dca424d20b33 | Python | 400 | 13 | import tensorflow as tf
def custom_loss(y_true, y_pred):
p = 1 # Weight when predicted value is greater than true value
q = 0.6 # The weight when the predicted value is smaller than the true value
error = y_true - y_pred
condition = tf.less_equal(error, 0)
loss = tf.where(condition, q ... |
1866d53117d889f934d711952cecf303d68e8e13f4dd99c1e9dc9288849df161 | Python | 401 | 16 | # coding=utf-8
import pytorch_lightning as pl
class Algorithm(pl.LightningModule):
def __init__(self, args):
super(Algorithm, self).__init__()
self.args = args
self.save_hyperparameters()
self.batch_size = args.batch_size
def update(self, minibatches, opt, sch):
raise ... |
ba2b4f92ce703b17d8c7c583b48faadcae90f0df853b7551e4a71e8fd5095143 | Python | 401 | 11 | ########################################################################
# Validation: checkpointing
# These models perform the usual validation tests for the stochastic
# solvers, each model separated into two separate scripts: one to
# checkpoint the solver state and the second to restore from the
# checkpoint da... |
c1f729837b52ca627f5b3cd804722e90e68eb60aacdc321b414bd62df14294ba | Python | 401 | 25 | import random
try:
import numpy as np
HAS_NP = True
except Exception:
HAS_NP = False
try:
import torch
HAS_TORCH = True
except Exception:
HAS_TORCH = False
def pytest_runtest_setup(item):
# Fix seeds at the beginning of each test.
seed = 20220714
random.seed(seed)
if HAS_NP... |
293e2ab8debfc66830df3df9a1c0897111e4e76de0c4bc85369e374d15faee63 | Python | 402 | 13 | from pdearena.configs.config_blast import BlastVelocityDensityTemperatureDeltaTPredConfig
from pdearena.utils.constants import Paths, BlastConstants
config = BlastVelocityDensityTemperatureDeltaTPredConfig(
model="convNeXT-tiny-max",
noise_level=1e-2,
include_derivatives=True,
include_cfl_featur... |
30f3211f7d69e871d4fa6b4cb44bf746a2efcbebe7878465d4c69d0dfc79b1be | Python | 402 | 15 | import pandas as pd
input_file = '1-s2.0-S0002929716300428-mmc3.csv'
df = pd.read_csv(input_file)
df.eGene = df.eGene.str.replace('*', '')
print(df.head())
grouped_df = pd.DataFrame(df.groupby(by='eGene')['eQTL_pvalue'].count())
grouped_df.reset_index(inplace=True)
grouped_df.columns = ['Gene_Name', 'platelets_eQTL... |
4472d53e543290bb7d74c3518ee83b890d9aa17841b31edce71263ebb566980c | Python | 403 | 16 | from langchain_core.indexing import __all__
def test_all() -> None:
"""Use to catch obvious breaking changes."""
assert list(__all__) == sorted(__all__, key=str)
assert set(__all__) == {
"aindex",
"DeleteResponse",
"DocumentIndex",
"index",
"IndexingResult",
... |
c7cb8cbc705ffa59238754ec7e33b325efb2752241204662e09ca2e9ace88d00 | Python | 403 | 10 | from matformer.train_props import train_prop_model
props = [
"e_form",
"gap pbe",
# "mu_b",
"bulk modulus",
"shear modulus",
# "elastic anisotropy",
]
train_prop_model(learning_rate=0.001,name="pygatt", dataset="megnet", prop=props[0], pyg_input=True, n_epochs=500, batch_size=64, use_lattice=Tr... |
0c0dfb63e76dff784fdf447c9b3afca80ce22ef4cf39be362efb1c4183bcda6d | Python | 404 | 12 | import pickle
from mrQA.project import plot_patterns
dict_ = pickle.load(open(
'/home/sinhah/scan_data/vertical_abcd_mrqa_files/abcd-fmap-baseline-non-recommended_hz.adt.pkl', 'rb')
)
config_path = '/home/sinhah/github/mrQA/examples/mri-config-abcd.json'
plot_patterns(non_compliant_ds=dict_['non_compliant'],
... |
4893595ab42f947c3b1c609a8186fe54f9023dfdcc79db92f8cced883169abbd | Python | 404 | 17 | from langchain_classic.schema.output_parser import __all__
EXPECTED_ALL = [
"BaseCumulativeTransformOutputParser",
"BaseGenerationOutputParser",
"BaseLLMOutputParser",
"BaseOutputParser",
"BaseTransformOutputParser",
"NoOpOutputParser",
"OutputParserException",
"StrOutputParser",
"T... |
82aab33d2d0e693a84f3aaf8fe1143aee8ed878e606e47841506f95ad16738a5 | Python | 404 | 17 | import numpy as np
import pandas as pd
# 读取名为"metric"的表格数据
data = pd.read_excel('../result/metric.xlsx') # 你需要根据你的数据格式来读取表格数据
# 计算每列的均值
mean_values = data.mean()
# 计算每列的标准差
std_values = data.std()
# 打印均值和标准差
print("均值:")
print(mean_values)
print("\n标准差:")
print(std_values) |
3a175fd6a753bed0cf9dfc19fed0a2d65681f198f718c869e05947d68e830ce4 | Python | 405 | 16 | import numpy as np
def topological_sort(dependencies: np.ndarray) -> np.ndarray:
order = []
while len(order) < len(dependencies):
for i in range(len(dependencies)):
if i in order:
continue
if np.sum(dependencies[:,i]) == 0:
order.append(i)
... |
10d8f71ea30b703956ea1cf3fec909cb49cdabad3a96b1e2800db517be4777fa | Python | 406 | 11 | # Transforms
from .patch import FocusedRandomPatch, RandomPatch, SelectedRegionWithPaddingPatch, SelectedRegionFixedSizePatch
from .select_chain import SelectFocused
from .select_atom import SelectAtom
from .mask import RandomMaskAminoAcids, MaskSelectedAminoAcids
from .noise import AddAtomNoise, ChiSelection
from .cor... |
8202f15c2f319fdff58f9f340fcef1321e1c055ec04379e995717e23605d5472 | Python | 406 | 10 | from setuptools import setup, find_packages
setup(name='rfdiffusion',
version='1.1.0',
description='RFdiffusion is an open source method for protein structure generation.',
author='Rosetta Commons',
url='https://github.com/RosettaCommons/RFdiffusion',
scripts=["scripts/run_inference.py"],... |
a9b20ab6e20ae496801ccf460a7189d5fb360b077deb47a18a1028db48002201 | Python | 408 | 18 | # -*- coding: utf-8 -*-
"""
Created on Wed May 6 12:56:52 2020
@author: nishe
"""
from connection import coordination
import numpy as np
def findnearbyneuron(lattice, position, withinrange, width):
neuron = np.arange(len(lattice))
dist = coordination.lattice_dist(lattice, width, position)
... |
e281723b60cc5c60362c08b24707c4abf448eb73bb367e9249e64c50a48e7706 | Python | 408 | 15 | #!/usr/local/bin/env python
"""
Various Python utilities for OpenMM.
"""
from openmmtools import testsystems, integrators, alchemy, mcmc, states, cache, utils, constants, forces, forcefactories, storage, multistate
# Handle versioneer
from ._version import get_versions
versions = get_versions()
__version__ = versio... |
35460f5a633937efa9b6d610a39c265428a78b8597c50c6232935a2d187d5f1d | Python | 410 | 16 | from ctypes import *
cdll.LoadLibrary("../libmorphy_x86_64-Darwin.so")
morphylib = CDLL("../libmorphy_x86_64-Darwin.so");
morphylib.mpl_new_Morphy.argtypes = []
morphylib.mpl_new_Morphy.restype = c_void_p
morphylib.mpl_delete_Morphy.argtypes = [c_void_p]
morphylib.mpl_delete_Morphy.restype = c_int
morphylib.mpl_init... |
22748e8ccb60e4d532558765d8f9d0ad55200bdf799793598e501d20c9dfd2cb | Python | 411 | 15 | from bindsnet.pipeline import action
from bindsnet.pipeline.base_pipeline import BasePipeline
from bindsnet.pipeline.dataloader_pipeline import (
DataLoaderPipeline,
TorchVisionDatasetPipeline,
)
from bindsnet.pipeline.environment_pipeline import EnvironmentPipeline
__all__ = [
"EnvironmentPipeline",
"... |
b41f046e99b23966ab9df83da648722c91538ef9e144943549d1f9904ac1aa48 | Python | 411 | 15 | import torch.nn as nn
def convert_state_dict(state_dict):
new_state_dict = state_dict.copy()
for k in state_dict.keys():
if 'module' in k:
k2 = k.split('module.')[1]
new_state_dict[k2] = new_state_dict.pop(k)
return new_state_dict
class Identity(nn.Module):
def __init__... |
df8a2f36595712ab952c99170539b60c099f4d57623c1dda8df819651e625359 | Python | 411 | 10 | from collections import OrderedDict
def update_state_dict_key_names(weights_initial):
"""update key names across pretrained and current models to match"""
update_state_dict_weights = OrderedDict()
for key, value in weights_initial.items():
if "module." in key:
key = key[7:] # remove "m... |
38565cfd76478ad7ddaa9a65339650ff9d790d4b7a640f843792c2510240e336 | Python | 412 | 19 | from langchain_core.load.serializable import (
BaseSerialized,
Serializable,
SerializedConstructor,
SerializedNotImplemented,
SerializedSecret,
to_json_not_implemented,
try_neq_default,
)
__all__ = [
"BaseSerialized",
"Serializable",
"SerializedConstructor",
"SerializedNotIm... |
3eec9377a471ff658d6c95f41651fb654e7ac0b24d4da80caf89e657ef458e48 | Python | 412 | 18 | from scaden.simulation import BulkSimulator
"""
Merge simulate datasets
"""
def merge_datasets(data_dir, prefix, files=None):
bulk_simulator = BulkSimulator()
if files:
files = files.split(",")
# Merge the resulting datasets
bulk_simulator.merge_datasets(data_dir=data_dir,
... |
02c63962967ad36bf650c3a9713a59c8983ad58dffa7cfddd2f89d52e2c73a40 | Python | 413 | 14 | from ._base import BaseGraphicalIdentification, BaseFormulaIdentification # isort: skip # noqa: E402
from .ID import ID
from .adjustment import Adjustment
from .frontdoor import Frontdoor
from .probability_expression import ProbabilityExpressionTree
__all__ = [
"BaseGraphicalIdentification",
"BaseFormulaIden... |
3eb9272e6d2718ad9b27e67ee268b199d5a8483e7d73fc5b9875dfc0c2ae4409 | Python | 414 | 19 | from voxcell import VoxelData
import numpy as np
import sys
import flatmap_util as fmutil
flatmap_nrrd = sys.argv[1]
rdepth_nrrd = sys.argv[2]
fmap_vd, fmask = fmutil.load_flatmap(flatmap_nrrd)
rdepth_vd = VoxelData.load_nrrd(rdepth_nrrd)
mask = ~np.isnan(rdepth_vd.raw)
n_total = np.sum(mask)
n_mapped = np.sum(fma... |
7df9ce238031eb3cb591c2159eeaba948cf62b1012e09d3cc1afb83a0cc5e664 | Python | 414 | 15 | import re
import pytest
from langchain_core.utils import check_package_version
def test_check_package_version_pass() -> None:
check_package_version("PyYAML", gte_version="5.4.1")
def test_check_package_version_fail() -> None:
with pytest.raises(
ValueError, match=re.escape("Expected PyYAML version ... |
e0815f2a8f9da17126681b32727c62ca05a553f98b065f2a67fd0a5aed5ac6ad | Python | 415 | 16 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"FPDF for python"
__license__ = "LGPL 3.0"
__version__ = "1.7.2"
from .fpdf import FPDF, FPDF_FONT_DIR, FPDF_VERSION, SYSTEM_TTFONTS, set_global, FPDF_CACHE_MODE, FPDF_CACHE_DIR
try:
from .html import HTMLMixin
except ImportError:
import warnings
warnings.war... |
6470d00e81b37237b53121cf2b0b6d5995dbd9be2e87ead7aa76f88b25e7f52a | Python | 420 | 11 | """
This package contains four submodules, with each submodule implementing a series of subclasses based off typical
tensorflow objects. In other words, this module can be conceptualized as an extension of tensorflow for the purpose of
bridging `motornet.plants` classes and tensorflow itself.
"""
from . import callbac... |
f2e83747b64ed1c025f07daf0ada847f7af16a28a31cfac51b2c91b9fedd7b69 | Python | 420 | 14 | # write log file
import time
def write_log(log_file, parameters):
# step, step_time, vacancy_id, vacancy_type, vacany_x, vacancy_y, vacancy_z, neighbor_id, neighbor_type, neighbor_x, neighbor_y, neighbor_z
# time_1 = time.time()
log_file.write("%d\t%f\t%d\t%d\t%f\t%f\t%f\t%d\t%d\t%f\t%f\t%f\n" % t... |
6587c888d44a47a796aabef97b0014062bcb8570d3d81b01b34b1b8c286914a5 | Python | 421 | 17 | import numpy as np
from voxcell import VoxelData
import sys
from scipy.ndimage import laplace
rdepth_nrrd = sys.argv[1]
mask_nrrd = sys.argv[2]
output_nrrd = sys.argv[3]
rdepth = VoxelData.load_nrrd(rdepth_nrrd)
mask = VoxelData.load_nrrd(mask_nrrd)
lapl = laplace(rdepth.raw, mode='nearest')
lapl[mask.raw != 1] = n... |
d6cf648c0b1fc32d776f05877f761da406f4528a95da223cb3a90dfe5ad327c0 | Python | 421 | 19 | from langchain_core.utils.html import (
DEFAULT_LINK_REGEX,
PREFIXES_TO_IGNORE,
PREFIXES_TO_IGNORE_REGEX,
SUFFIXES_TO_IGNORE,
SUFFIXES_TO_IGNORE_REGEX,
extract_sub_links,
find_all_links,
)
__all__ = [
"DEFAULT_LINK_REGEX",
"PREFIXES_TO_IGNORE",
"PREFIXES_TO_IGNORE_REGEX",
"S... |
c0e2cc570734892bab86399dd3d56b6bc9c87f8ac1ce04e4aeca3cd20f222ecd | Python | 423 | 7 | from .peak_det_amp_threshold import peak_det_amp_threshold
from .peak_det_local_search import peak_det_local_search
from .peak_det_matched_filter_robust import peak_det_matched_filter_robust
from .peak_det_modified_pan_tompkins import peak_det_modified_pan_tompkins
from .peak_det_pan_tompkins import peak_det_pan_tompki... |
ccbdce77c9cf7a00a089f76ff1fc5a5f8795e433cc4629f89992ae83ac3291e8 | Python | 424 | 14 | import os, glob
import numpy as np
def get_image_list(input_folder, string_filter='', mode_filter='include'):
flist = glob.glob(os.path.join(input_folder,'*.tif'))
if string_filter:
if mode_filter=='include':
flist = [f for f in flist if string_filter in f]
elif mode_filter=='exclu... |
c0832bd7357925ba213b7403c19e9e48f7fb43b29ad249525bacb113aebc8d3f | Python | 425 | 11 | # Python implementation for adding Gaussian noise over the signal s for a certain target SNR.
# It returns the noisy signal, the noise itself and the noise variance.
import numpy as np
def AddNoise(target_snr_db, s):
s = np.asanyarray(s)
var_n = np.mean(s**2) / (10**(target_snr_db/10))
n = np.random.normal... |
c412e7ba591d7557b8bd64013fafa331e76e9cff4e2eac57d529e0d2d9d5e818 | Python | 425 | 12 | # Python function that returns the beats representation of an ECG
# Inputs: ecg_bwr - the input ECG
# mids - the middle points between R-peaks, which represents the boundaries between different beats
# Output: x_hhs - ECG beat representation
def ECGHeartBeatsList(ecg_bwr, mids):
x_hbs = []
for i in ran... |
5893e97447e5fefd7677873ab0538021a863e4c4e7af391f9a6a77dfab4d960e | Python | 426 | 20 | from pycromanager import ZMQRemoteMMCoreJ
import numpy as np
import time
from arduino_triggering import TriggerTester
### Setup
trigger_arduino = TriggerTester('COM3')
core = ZMQRemoteMMCoreJ()
core.set_exposure(500)
camera_name = core.get_camera_device()
trigger_arduino.send_trigger(5)
def wait_and_pop_image():
... |
a702477c70453ef81241b80e075da60870372004aae3f75f16de12183cc1aef1 | Python | 427 | 19 | import numpy as np
import pandas as pd
import voxcell as vc
def indices_to_mask(indices, depth):
mask = np.zeros(depth.shape, dtype=bool)
mask[tuple(indices.T)] = True
return mask
def positions_to_mask(positions, annotation):
mask = np.zeros(annotation.shape)
indices = annotation.positions_to_in... |
72d991f9f07cbff355f104c81ddb7885c13c65e3a011102cbd3460e64a3380e8 | Python | 428 | 10 | """
This package contains shifter-networks. These are used to modify the neurons' readout position
based on the eye position.
Usually, the input to the shifters are the pupil centers of both eyes. Given that input,
a horizontal and vertical shift of the readout position is returned by the shifter.
"""
from .base impor... |
f5779cbec4342be08e3c479330ff62a947e8c209c2a436d0d2f8e319ad663a15 | Python | 428 | 10 | import sys
sys.path.append("/yourpath/comformer")
from comformer.train_props import train_prop_model
props = [
"e_form",
"gap pbe",
"bulk modulus",
"shear modulus",
]
train_prop_model(learning_rate=0.001,name="iComformer", dataset="megnet", prop=props[0], pyg_input=True, n_epochs=500, max_neighbors=25,... |
2822851883f308c9037b5b4dc9a9e9e731f047b4375e535cf9de871b9870197d | Python | 429 | 19 | import os
fh=open("components.cif","r")
data_count=0
curHetCode=""
for line in fh.readlines():
line=line.strip()
if (line[0:4]=="data"):
het_code=line[5:]
if (line[0:15]=="_chem_comp.type"):
lastWord=line.split(" ")[-1]
lastWord=lastWord.upper().strip("\"")
if lastWord=="LIN... |
dad8592bfd89a45a72d4135f5f9f6229f5aab05b47888e518a3bb4873a755485 | Python | 430 | 13 | import spectral
import matplotlib.pyplot as plt
# Open HDR and RAW files using the envi.open function of the spectral library and display them
img = spectral.envi.open(r'Thyroid Nodule1\2082500.HDR')
# Display the grayscale image of the 100th band data
band_data = img.read_band(100)
plt.imshow(band_data, ... |
2a474b475628e3b7df3d2b9706f1f95e3533255cddedbeda652f5f09de524ef4 | Python | 432 | 14 | """
diffnets
Supervised and self-supervised autoencoders to identify the mechanistic basis for biochemical differences between protein variants.
"""
# Add imports here
from . import training, data_processing, analysis, utils, exmax, nnutils
# Handle versioneer
from ._version import get_versions
versions = get_version... |
31c0152b2a94ee3544cef01a0dd5595e5ee511951b33a1fbfacc885259831c92 | Python | 432 | 17 | from fastapi.testclient import TestClient
from api.main import app
def test_health() -> None:
client = TestClient(app)
response = client.get("/api/health")
assert response.status_code == 200
assert response.json()["status"] == "ok"
def test_frontend_served() -> None:
client = TestClient(app)
... |
9b2d20fbec68429bdda2d61fde45067c5ceaf92d8774cadd613ee036f85f9526 | Python | 433 | 22 | import json
import sys
release_tag = sys.argv[1]
python_version = sys.argv[2]
ci_os = sys.argv[3]
platform_mapping = {
"ubuntu-latest": "linux-64",
"macOS-latest": "osx-64",
}
data = {
"name": "openff-toolkit",
"channel": "conda-forge",
"python": [python_version],
"platform": [platform_mappin... |
eef6c6914cebb1cb14908d2cdcc2135061bb1217d16ae0e8281e8dc20612d242 | Python | 434 | 14 | from importlib.resources import files
tfs_resources = [
"human_tfs_r_hummus",
"mouse_tfs_r_hummus",
]
def load_tfs(tfs_list) -> list[str]:
if tfs_list not in tfs_resources:
raise ValueError(f"The name of the tfs list must be in {tfs_resources}")
text = files("hummuspy.data").joinpath(tfs_list... |
f7f05cf4797bbfc5215755d3b73871eeb0b000927c3b94735536494c4775992d | Python | 434 | 11 | from analyze_results import plot_auc_graphs
def main():
plot_auc_graphs.graph_mapping['CirSqr'] = 'CircleSquareSrc'
plot_auc_graphs.graph_mapping['CirSqrExt'] = 'CircleSquareDst'
plot_auc_graphs.classes_to_evaluate['CirSqr'] = [0,1]
plot_auc_graphs.classes_to_evaluate['CirSqrExt'] = [0,1]
plot_a... |
3756099ce52eaa58a50951e3ea3dcf23e85cfde41d45bf848803f7432ba746e5 | Python | 435 | 12 | import pandas as pd
import argparse
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('original_count', help="original count file")
parser.add_argument('transposed_count', help="transposed count file")
args = parser.parse_args()
counts = pd.read_csv(args.original_co... |
851a8d38c768847cea3b049e7b25cbec9b918c0c719acd849657cae977e929de | Python | 435 | 16 | from setuptools import setup, find_packages
setup(
name='btstn',
version='1.0',
description='Bidirectional Time-series State Transfer Network (BTSTN)',
author='Shaohua Xu, Ting Xu, Yuping Yang, Xin Chen',
author_email='12218022@zju.edu.cn',
packages=find_packages(),
install_require... |
f75de78f89a0de0950f9c1c686053bbd12b8b40b01751b8120282bfe22b3653b | Python | 435 | 15 | import time
import pytest
from blockbuster import BlockingError
from langchain_core import sys_info
async def test_blockbuster_setup() -> None:
"""Check if blockbuster is correctly setup."""
# Blocking call outside of langchain_core is allowed.
time.sleep(0.01) # noqa: ASYNC251
with pytest.raises(B... |
6c484ffc362a24deb702a041603f86c4e0e5928744a4d313233d2fc68f647a82 | Python | 437 | 16 | """
WSGI config for analyze_electrophysiology_data 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/3.1/howto/deployment/wsgi/
"""
import os
from django.core.wsgi import get_wsgi_application
os.environ.s... |
9e58f8549399346a922b50fed72d49d66a909a90683ba0ae6f6a245fcefdb2c5 | Python | 437 | 16 | """
ASGI config for analyze_electrophysiology_data 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/3.1/howto/deployment/asgi/
"""
import os
from django.core.asgi import get_asgi_application
os.environ.s... |
af61f38121db01dab3d59320939df5c4b9392d9cd37d9b6fcd16af663cd82c47 | Python | 437 | 13 | from pycromanager import ZMQRemoteMMCoreJ, Studio
core = ZMQRemoteMMCoreJ()
studio = Studio()
for i in range(20):
core.start_sequence_acquisition(400, 0, True)
while core.get_remaining_image_count() > 0 or core.is_sequence_running():
if core.get_remaining_image_count() > 0:
tagged = core.p... |
c7fa8b10a2e9bf0dfdabd623a2679611025e5b15bfc29e4fd463819535eb85f3 | Python | 437 | 24 | import numpy as np
# Generate experimental data
np.random.seed(42)
X = np.random.randn(20)
def z_score(x):
mean = np.mean(x)
std = np.std(x)
threshold = 1
if std == 0:
return None
z = (x - mean) / std
outliers = np.where(np.abs(z) > threshold)
# print(outliers)
... |
999c2db796d64b2508a04cc41b329188ac2466078a2fb6a9815efaa2ba69b0c3 | Python | 439 | 12 | from langchain_classic.chains.router.base import MultiRouteChain, RouterChain
from langchain_classic.chains.router.llm_router import LLMRouterChain
from langchain_classic.chains.router.multi_prompt import MultiPromptChain
from langchain_classic.chains.router.multi_retrieval_qa import MultiRetrievalQAChain
__all__ = [
... |
b117969b8256b3f50f292d6e73b464dfec815d829b860b3d0ad5113f16aed3b1 | Python | 439 | 17 | # -*- coding: utf-8 -*-
"""
Created on Thu Aug 24 10:30:41 2023
@author: biener
"""
import numpy as np
from NN_Rslt_Anal import NN_Stat as stat
NN_Stat_O = stat()
Multi_fParmas_Array = NN_Stat_O.Assemble_Data()
Bins_Range = np.arange(-10, 10, 0.1)
Bins_Range = np.exp(Bins_Range)
cou... |
8a83e9dad7246dda4375b5aea9ffccbc61b5f02944c2c06b598c1b14226ff158 | Python | 441 | 23 | from voxcell import VoxelData
import numpy as np
import sys
img_nrrd = sys.argv[1]
savefile = sys.argv[2]
msk_nrrd = None
if len(sys.argv) > 3:
msk_nrrd = sys.argv[3]
img = VoxelData.load_nrrd(img_nrrd)
if msk_nrrd is None:
valid_msk = ~np.isnan(img.raw)
else:
msk = VoxelData.load_nrrd(msk_nrrd)
ass... |
2b489a2d6a9a528a5104473954e37b1b339b2506ff09316f95e8110b9fceb90c | Python | 442 | 14 | import numpy as np
import torch
import neurogym as ngym
def load_dataset(config_file, args):
dataset = ngym.Dataset(config_file, batch_size = args.batch_size, seq_len = args.seq_len)
dataset.seed(args.seed)
return dataset
def add_task_indicator(dataset, indicator):
inputs, labels = dataset()
inpu... |
062453bf9e2d6ed1c5fa2d65ab8e500faf9996fedde962e36272240a62ff5361 | Python | 443 | 20 | from pycromanager import ZMQRemoteMMCoreJ
import gc
# core = Core(debug=False, convert_camel_case=False)
#
# core.startSequenceAcquisition(500, 0., True)
#
# while core.getRemainingImageCount() > 0 or core.isSequenceRunning():
# if core.getRemainingImageCount() > 0:
# tagged = core.popNextTaggedImage()
# ... |
07c4a5fb2c3c695823f60792077038d728b85419fbabec5d0ae3299a8f6ea591 | Python | 446 | 10 | import pytest
def test_SaveDownsampledTiff(tiff_path_fixture):
from imagingplus.utils.images import ImportTiff
start, end = 0, 4000
stack = ImportTiff(tiff_path_fixture, frames=(start,end))
from imagingplus.utils.images import SaveDownsampledTiff
SaveDownsampledTiff(stack=stack, save_as=f'/home/ps... |
a91e1978ccbaa84a41520d1fdf7ac330a5fd5fd1643f44c4fbc8a135f17cd330 | Python | 446 | 21 | from langchain_core.prompts.loading import (
_load_examples,
_load_few_shot_prompt,
_load_output_parser,
_load_prompt,
_load_prompt_from_file,
_load_template,
load_prompt,
load_prompt_from_config,
)
__all__ = [
"_load_examples",
"_load_few_shot_prompt",
"_load_output_parser"... |
adaa522b0593c475616a75bd96210a3904c70fe3b669052c54e49fe4d4df2187 | Python | 446 | 21 | from langchain_core.utils.utils import (
build_extra_kwargs,
check_package_version,
convert_to_secret_str,
get_pydantic_field_names,
guard_import,
mock_now,
raise_for_status_with_text,
xor_args,
)
__all__ = [
"build_extra_kwargs",
"check_package_version",
"convert_to_secret_... |
b7ceb6c65ea96734eb49166f98e7be1e4a4e26c8c9612257006c7f1282795b99 | Python | 446 | 13 | import requests
from ptrnets.utils.gdrive import _get_name
def test_get_name_with_requests_session(mocker):
mock_get = mocker.patch.object(requests.Session, "get")
mock_get.return_value.headers = {"Content-Disposition": 'attachment; filename="example_model.pth"'}
name = _get_name("example_id")
mock... |
ccd12f25871338301d3b43a7024f2f3fb0874cb199bd1b1cb303350f05f2881f | Python | 446 | 21 | from bindsnet.conversion.conversion import (
ConstantPad2dConnection,
FeatureExtractor,
PassThroughNodes,
Permute,
PermuteConnection,
SubtractiveResetIFNodes,
ann_to_snn,
data_based_normalization,
)
__all__ = [
"Permute",
"FeatureExtractor",
"SubtractiveResetIFNodes",
"P... |
4c535850635e80225e635d3ff310b3f580e30991ca9697c12709efbababba826 | Python | 447 | 16 | import os
import glob
import importlib as importlib
_files = glob.glob(os.path.join(os.path.dirname(__file__), "*.py"))
__all__ = [
os.path.basename(f)[:-3]
for f in _files
if os.path.isfile(f) and not f.endswith("__init__.py")
]
_modules = [(m, importlib.import_module("." + m, __name__)) for m in __all__]... |
5b071fd943969db4551c31122f54692e205162b23e31953c2c022b49d044367b | Python | 450 | 19 | import os
import numpy as np
import random
import torch
def set_seeds(seed):
np.random.seed(seed)
random.seed(seed)
torch.manual_seed(seed)
torch.cuda.empty_cache()
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
torch.cuda.manual_seed_all(seed)
os.envir... |
5473d9d0a0fbb1f69c738af29322b463bc1a6adc8ce7525c5cac22e4c6d0b34d | Python | 454 | 20 | # -*- coding: utf-8 -*-
"""
Created on Fri Sep 1 23:22:31 2023
@author: biener
"""
import torch
import numpy as np
from NN_Rslt_Anal import NN_Stat as stat
import mAECell_Utils as utils
NN_Stat_O = stat()
GT_File = utils.fOpen(Title='Load ground truth')
GT_plusCoord = np.loadtxt(GT_File)
GT ... |
54f7f61203ec87fbb1a6bd9b35174792bb778a153ce3233cd0252a32acab6b5b | Python | 454 | 26 | from .pipelines import (
check_cfg_parameters,
close_loggers,
init_wandb,
load_envs,
load_from_checkpoint,
seed_everything,
set_additional_params
)
from .transform import (
TransformOptim3D,
TransformRDKit3D
)
__all__ = [
check_cfg_parameters,
close_loggers,
init_wandb,... |
b3fc94426f9c0924e4ba7ba2449e3269358abf04ba70067531cd27e2aed69a61 | Python | 458 | 14 | import numpy as np
from neurovisfit.data.session import Session
def test_session_from_path(mock_session_path, mock_responses):
session = Session.from_path(mock_session_path)
assert session.subject_id == "001"
assert session.session_id == "123"
assert (session.responses == mock_responses).all()
a... |
5c88ed256be99095d3fe02c23946edb2d211432b63540f0337fd18e8912ff5e4 | Python | 460 | 14 | import numpy as np
def compute_ensemble_average(estimates, distances, smaller_is_better=False):
distances = distances.copy()
distances = (distances - np.min(distances)) / (np.max(distances) - np.min(distances))
if smaller_is_better:
distances = 1 - distances
distances = distances ** 2
prin... |
6c41636ef85f1693e4128fe5fe82d2ce5f3b446aeef663db2f45c79ad52f42f3 | Python | 460 | 19 | import torch
import torch.nn as nn
class Flatten(nn.Module):
def __init__(self):
super(Flatten, self).__init__()
def forward(self, x):
return x.view(x.size(0), -1)
def conv_block(in_channels, out_channels, kernel_size=3, padding=1):
return nn.Sequential(
nn.Conv2d(... |
a8ee5245edd0433b448a820ed57fc27368bd4bce47464f4a33e089500c8ff7bc | Python | 460 | 13 | # third party packages
class Interpolator(object):
def __init__(self, fileName):
try:
from gridData import Grid
except ModuleNotFoundError:
raise ModuleNotFoundError("The dependency 'GridDataFormats' is required for this functionality!")
self.grid = Grid(fil... |
c29183c64861d1b80c4f7e3f130123e914fd026697fda420f9d3a58c0b5e820d | Python | 460 | 20 | from easydict import EasyDict
cfg = EasyDict()
cfg.batch_size = 16
cfg.epoch = 200
cfg.learning_rate = 1e-2
cfg.momentum = 0.9
cfg.weight_decay = 1e-4
cfg.patience = 25
cfg.inference_threshold = 0.75
cfg.transunet = EasyDict()
cfg.transunet.img_dim = 512
cfg.transunet.in_channels = 3
cfg.transunet.out_channels = 128
... |
7afad6b837df4f19010b126d9b8652db1a5c3a4c7e3191ddaca1fb46c7aff0d9 | Python | 461 | 24 | import starwrap as sw
import numpy as np
arg = sw.args()
arg.trainFile = './input.txt'
arg.testFile = './input.txt'
arg.trainMode = 5
sp = sw.starSpace(arg)
sp.init()
sp.train()
# sp.evaluate()
sp.nearestNeighbor('some text', 10)
sp.saveModel('model')
sp.saveModelTsv('model.tsv')
sp.initFromSavedModel('model'... |
364dcee31a54c66b49f4c1fd1fb7dd8b6b11aad3650a9e9bd5bef1a8e8876b4a | Python | 462 | 20 | # -*- coding: utf-8 -*-
import os, sys
from bmtk.simulator import bionet
def run(config_file):
conf = bionet.Config.from_json(config_file, validate=True)
conf.build_env()
graph = bionet.BioNetwork.from_config(conf)
sim = bionet.BioSimulator.from_config(conf, network=graph)
sim.run()
bionet.nr... |
592439ae02e88756821310f0fe0bb1b43ea21fc4990af87a9daf138fca9f6e80 | Python | 462 | 21 | import time
from itertools import cycle
from langchain_core.language_models import GenericFakeChatModel
def test_benchmark_model() -> None:
"""Add rate limiter."""
tic = time.time()
model = GenericFakeChatModel(
messages=cycle(["hello", "world", "!"]),
)
for _ in range(1_000):
m... |
3a7f15c54e2b4b3e7e9b2fe27854d2c9af50f23249da74e69fb8116524d6ea78 | Python | 463 | 24 | import time
import zmq
import numpy as np
NB_NRN = 1024
IP_ADDR = "tcp://*:5559"
stim = np.zeros(NB_NRN, dtype=np.uint32)
# stim[ 0] = 1000
# stim[ 1023] = 2000
# stim[1023] = 2000
stim[0 : 1024] = 500
def main():
context = zmq.Context()
zmq_socket = context.socket(zmq.PUSH)
zmq_socket.... |
f50bb346513a7219c23f6bdad17a026f7e5c5ff71a5c126796655532802e91f3 | Python | 463 | 20 | """
This module is an example of a barebones writer plugin for napari
It implements the ``napari_get_writer`` and ``napari_write_image`` hook specifications.
see: https://napari.org/docs/dev/plugins/hook_specifications.html
Replace code below according to your needs
"""
from napari_plugin_engine import napari_hook_i... |
14c9114404bd894b0501e3eed1ebabde8e4ca8d40efd4b624769748ea30603d0 | Python | 464 | 21 | from proto_net.train import proto_train
import torch
import traceback
if __name__ == "__main__":
try:
params = {
"lr": 0.0005,
"bs": 20,
"op": 72,
"fn": 80,
"optimizer": torch.optim.Adam,
"shots": 1
}
resu... |
692d4e1b87818447ba00d905b5afcb5cf75d6a1ab2108191464d17300dc4c0be | Python | 464 | 17 | from langchain_classic.document_loaders.parsers import __all__
def test_parsers_public_api_correct() -> None:
"""Test public API of parsers for breaking changes."""
assert set(__all__) == {
"BS4HTMLParser",
"DocAIParser",
"GrobidParser",
"LanguageParser",
"OpenAIWhisper... |
7e23cbf8994d5253a71e0ce144adc26b86f29ef1b2204344289c1c88c66e75bf | Python | 466 | 28 |
"""Error class for handled errors."""
class DataError(Exception):
"""Data exception."""
pass
class FileExistsError(DataError):
"""Raised when file already exists."""
pass
class MmcifParsingError(DataError):
"""Raised when mmcif parsing fails."""
pass
class ResolutionError(DataError):
... |
ea9b747b2aa2bd376b342e54b1793e32f0ddf782b95cd6e53e0c7a08d499cb45 | Python | 466 | 10 | def __getattr__(_: str = "") -> None:
"""Raise an error on import since is deprecated."""
msg = (
"This module has been moved to langchain-experimental. "
"For more details: https://github.com/langchain-ai/langchain/discussions/11352."
"To access this code, install it with `pip install l... |
bd9223c6fc609224e49c701e066b2a997fa35426976f140067c3590eef970036 | Python | 470 | 15 | from pycromanager import ExploreAcquisition, ZMQRemoteMMCoreJ
# core = Core()
def image_process_fn(image, metadata):
image[20:60, 20:60] = 0
return image, metadata
def image_saved_callback(axes, dataset):
print(axes)
print(dataset.read_image(**axes))
ExploreAcquisition('/Users/henrypinkard/Desktop',... |
c440619f7779bc8b2a4047389cedeb1642ff5e0cdd21fc00ae9b1fe999d57f37 | Python | 471 | 17 | """PyTorch model definitions for BERNN."""
from .aedann import AutoEncoder2, SHAPAutoEncoder2
from .aeekandann import KANAutoEncoder2, SHAPKANAutoEncoder2
from .aeekandann import KANAutoEncoder3, SHAPKANAutoEncoder3
from .aedann import AutoEncoder3, SHAPAutoEncoder3
__all__ = [
"AutoEncoder2",
"SHAPAutoEncode... |
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