sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
8cedbb16cb462b5732ccd4f4f7a183f6516ad9880dc58d4367a36d03fc8a751f | Python | 1,852 | 72 | """Global values and configuration that apply to all of LangChain."""
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from langchain_core.caches import BaseCache
# DO NOT USE THESE VALUES DIRECTLY!
# Use them only via `get_<X>()` and `set_<X>()` below,
# or else your code may behave unexpectedly wi... |
805e062800afe90fc9c949728590d427fdfabdc553dbbd7a73ebf88c99f02aba | Python | 1,854 | 52 | import glob
import os
import subprocess
import pandas as pd
from tqdm import tqdm
'''
/mnt/media32TB/home/yyasumizu/bioinformatics/MEnet/notebooks/210422_array2bismark.ipynb
convert methyaltion arry file (series_matrix.txt downloaded in GEO) to bismark.
n_read : virtual coverage
'''
n_read = 10
list_manifest = ['..... |
64cae150b63f8f03619e6ba20ce9d6fae2f483cbcd93d705e675a9d6af34aa14 | Python | 1,855 | 48 | """Test in memory docstore."""
from langchain_classic.output_parsers.regex_dict import RegexDictParser
DEF_EXPECTED_RESULT = {"action": "Search", "action_input": "How to use this class?"}
DEF_OUTPUT_KEY_TO_FORMAT = {"action": "Action", "action_input": "Action Input"}
DEF_README = """We have just received a new resu... |
9b15f3c00782db51f6c1707a6a5bba6f9497708005aad13126f1fe6448dc3eb2 | Python | 1,857 | 53 | # coding=utf-8
import torch
import torch.nn.functional as F
from alg.algs.ERM import ERM
class VREx(ERM):
"""V-REx algorithm from http://arxiv.org/abs/2003.00688"""
def __init__(self, args):
super(VREx, self).__init__(args)
self.register_buffer('update_count', torch.tensor([0]))
self.... |
08713afa30605457b50460c0a560f79a5c11892cb60b6d8f8fefddfef731b1d2 | Python | 1,858 | 72 | #!/usr/bin/env python3
"""
Warp a probabistic atlas onto a brain containing a lesion.
Requires a T1w image of the lesioned brain and a binary lesion mask, both in the same space.
This command outputs lesion volumes within each probabilistic atlas label
Usage
----
atlas2lesion.py -i <lesion T1w> -m <lesion mask> -t <at... |
9d7eb52f5f9c9328626893a8509d7ffa7763a51a920d57fd4152298d17bff4cb | Python | 1,860 | 54 | from importlib.resources import open_text
import pytest
from neurovisfit.common.config import TomlConfig
def test_toml_config_get_dict(mock_toml_config, mock_data_path):
database_config = mock_toml_config.get_dict("some_data_name")
print(database_config)
assert isinstance(database_config, dict)
asse... |
c870594ea1f7bdecf856070a535ce432d61e7cb310fedd24a2e452e6a411d9c7 | Python | 1,860 | 46 | # this will combine a single command that will run all analysis and save everything
from . import plotting, wrangle
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser(description="Get input")
parser.add_argument("csv", type=str, help="Path to the results csv file")
parser.add_... |
3d40cdb4b025ecc65e9110fd0a9ed09b5fe1679b179d9d14d211d7e14f7b7561 | Python | 1,861 | 60 | import os
import pytest
from qupkake.mol_utils import Tautomerize
from rdkit import Chem
@pytest.fixture
def example_tautomer(request):
smiles = "Oc1c(cccc3)c3nc2ccncc12"
tautomer = Tautomerize(smiles=smiles, name="pytest_mol")
# Delete the mol_t0.mol file before the test
tautomer.mol_dir = "molecul... |
5e6a1c97f999f683556718690b7ce2bad31d5c52c3e7f742c6ce5f135f60eb6d | Python | 1,861 | 58 | from typing import Dict
import openmm
import openmm.unit
def _compare(
system1: openmm.System,
system2: openmm.System,
tolerances: Dict[str, openmm.unit.Quantity],
):
"""Check that two OpenMM systems have the same parameters.
Adapted from the OpenFF Toolkit:
https://github.com/openforcefield... |
c9381d9138e2064f8455f70816a7e2e73d671f97ad2e9fc9d83b5a0978394e68 | Python | 1,861 | 65 | from __future__ import annotations
import numpy as np
from sklearn.cluster import KMeans
from tslearn.clustering import TimeSeriesKMeans
from libs.function.utils import pca, tsne
# time x dim -> time
def ts_kmean(data: np.ndarray, n_cluster: int) -> np.ndarray:
engine = KMeans(n_clusters=n_cluster, max_iter=300... |
8d695a632289288461258ee332d09c1ecde0a39a6278af389d9aaddd212d66e2 | Python | 1,862 | 53 | from langchain_core.agents import AgentAction
from langchain_core.messages import AIMessage, HumanMessage
from langchain_classic.agents.format_scratchpad.log_to_messages import (
format_log_to_messages,
)
def test_single_intermediate_step_default_response() -> None:
intermediate_steps = [
(AgentActio... |
db6ad5dd8167da230922ec0afe93a7c2bb2edc34cba414522ed63af4a62b6a20 | Python | 1,862 | 59 | from ChipseqReport import *
class MacsSummary(DefaultTracker):
pattern = "(macs_summary)"
def getTracks(self, subset=None):
return self.getValues("SELECT track FROM macs_summary ORDER BY track")
def __call__(self, track, slice=None):
resultsdir = os.path.abspath(os.path.join(EXPORTDIR, ... |
311102100d614e982c4bff9d334682661c2b6c3a82c57e71da435ddf1b3cb72e | Python | 1,863 | 54 | from typing import TYPE_CHECKING, Any
from langchain_classic._api import create_importer
if TYPE_CHECKING:
from langchain_community.document_loaders import (
UnstructuredAPIFileIOLoader,
UnstructuredAPIFileLoader,
UnstructuredFileIOLoader,
UnstructuredFileLoader,
)
from lan... |
bd4934ea559a8f9e254080e430cd4900e72973b71ec3bfe77f2375aa7be49b6c | Python | 1,863 | 44 | from config_FaceName import group_name,Ids,RSA_data_path,Results_data_path,MRI_data_path
import mne
import os.path as op
from custom_functions import prepare_X_and_one_data,prepare_stats_list,write_stats_list,generate_adjacency_matrix
from scipy import stats as stats
import numpy as np
from mne.stats import permutation... |
9274ca3bc01cce9a47113ff5ea4cf2ece2ec41370473a6131dd33c0f7261fd2a | Python | 1,864 | 56 | # Copyright Generate Biomedicines, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to ... |
aa28e3d3962bcafaa5a65bbdef4bc332756a937f80fc19972ed9907d8e5173bb | Python | 1,864 | 60 | import numpy as np
import pandas as pd
import pytest
from coffeine import (make_filter_bank_regressor,
make_filter_bank_classifier)
frequency_bands = {'alpha': (8.0, 15.0), 'beta': (15.0, 30.0)}
n_subjects = 10
n_channels = 4
n_frequency_bands = len(frequency_bands)
@pytest.fixture
def toy_data... |
8fb4ba110fce4bd49ff6dbe53399029b40f9e6a182dec7fbe661dbb8ab4759d8 | Python | 1,865 | 57 | import torch
from equivariant_diffusion.utils import \
center_gravity_zero_gaussian_log_likelihood_with_mask, \
standard_gaussian_log_likelihood_with_mask, \
center_gravity_zero_gaussian_log_likelihood, \
sample_center_gravity_zero_gaussian_with_mask, \
sample_center_gravity_zero_gaussian, \
sam... |
a94e76b33265cd784fec529728c9c4154a38745b92495de3e72a7e4f49387c7f | Python | 1,865 | 83 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
from __future__ import division, print_function
import argparse
from time import time
# import pylab as pl
import nibabel as nib
import numpy as np
DESCRIPTION = """
Compute average from an arbitrary amount of images.
"""
class CustomFormatter(argparse.ArgumentDefa... |
d369b4e0783880a1ea06bc0e3d58fb43b2b400c110b01c5141555dc53b2545ef | Python | 1,867 | 54 | from typing import TYPE_CHECKING, Any
from langchain_classic._api import create_importer
if TYPE_CHECKING:
from langchain_community.tools import APIOperation
from langchain_community.tools.openapi.utils.api_models import (
INVALID_LOCATION_TEMPL,
PRIMITIVE_TYPES,
SCHEMA_TYPE,
S... |
5e850844b8e4ce75002ab379dd9652928a7c1c3de4a8a86a375262a479ff8495 | Python | 1,868 | 76 | #!/usr/bin/env python3
import argparse
import pathlib
from typing import Optional
import yaml
import subprocess
def parse_arguments(
key: Optional[str] = None, stage: Optional[str] = None, method: Optional[str] = None
):
"""
Parses command line arguments
"""
parser = argparse.ArgumentParser(descr... |
30a1bf743735c1f46a55d085aae5cb4205bc9b3b98cc041fa4b52413eb294017 | Python | 1,869 | 53 | # Prepare images and labels for validation #2
# Copyright (c) 2022 Laurent Caplette
import numpy as np
import os, csv, h5py
from PIL import Image
np.random.seed()
homedir = '' ### path of home directory
nBlocks = 5
nTrialsInBlock = 20
nTrials = nBlocks * nTrialsInBlock
f = h5py.File('vis_mostnamed_ultimatefinal.h5'... |
6bd2abdd773a00823429e456fce34291119f9ea1cd46f9cab2861e6a7f98d442 | Python | 1,869 | 44 | import numpy as np
def width_estim(df, model, processor, train_data_notnormalized, slide_window):
"""
Predicts drop width from side-view features using a trained model.
Args:
df (pd.DataFrame): DataFrame containing raw drop measurements.
model (tf.keras.Model): Trained LSTM model for predi... |
728ff86e92e5cd8d2ac0f4794b53f5e8da69fec1e4c6512b3a824f5bdcf9b8e2 | Python | 1,869 | 43 | import argparse
from pensa.preprocessing import load_selection, extract_coordinates_combined
# -------------#
# --- MAIN --- #
# -------------#
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--sel_file", type=str, default='')
parser.add_argument("--sel_base_a", type=s... |
2d5ee957582c5cad01ea9078514e749a0fdde3b13c7908cb193baf59d20c1767 | Python | 1,872 | 44 | import argparse
from pensa import load_selection, extract_coordinates_combined
# -------------#
# --- MAIN --- #
# -------------#
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--sel_file", type=str, default='')
parser.add_argument("--sel_base_a", type=str, default=... |
8e55fce7994bbcea9cf4fd2263cae28c711267466307b52aa5b8e417d4f397ca | Python | 1,872 | 35 | PREFIX = """Assistant is a large language model trained by OpenAI.
Assistant is designed to be able to assist with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics. As a language model, Assistant is able to generate human-like text base... |
903e4549b233acdffef46a5d6bb4cfc02a402d6b679fbaac342fccbc375dc4c2 | Python | 1,872 | 52 | import numpy as np
import cy_argwhere as argwhere
def test_argwhere_1d():
# Test with a simple case
assert argwhere.argwhere_1d([0, 1, 2, 0, 3, 0, 4]) == [1, 2, 4, 6], "Test case 1 failed."
# Test with all zeros
assert argwhere.argwhere_1d([0, 0, 0, 0]) == [], "Test case 2 failed."
# Test with no... |
79f60bf4808bc817b10e7db67f5bfc092e0fe89deb466ee9babc88c5d94ffb9d | Python | 1,873 | 74 | #!/usr/bin/env python3
import re
import subprocess as sp
import shlex
import sys
import time
import logging
from CookieCutter import CookieCutter
logger = logging.getLogger("__name__")
STATUS_ATTEMPTS = 20
jobid = sys.argv[1]
cluster = CookieCutter.get_cluster_option()
for i in range(STATUS_ATTEMPTS):
try:
... |
7d11edc08fd8d0f007ca9ab7fe3f7d7a0615e9a59a3fa81ab8c820b6e3fe00d3 | Python | 1,874 | 76 | from __future__ import annotations
from typing import List
import numpy as np
import numpy.linalg as LA
from libs.common.graph import Graph
from libs.function.utils import sparse_matrix
class Weight(Graph):
def __init__(
self,
input_size: int,
hidden_size: int,
output_size: int,... |
8938c9927d9202659d640ee44563dd519d444d7d1329e20368eea4f41d7905e4 | Python | 1,874 | 64 | import torch
import torch.nn as nn
import torch.nn.functional as F
def l2loss_atomwise(pred, target, reduction="mean"):
dist = torch.linalg.vector_norm((pred - target), dim=-1)
if reduction == "mean":
return torch.mean(dist)
elif reduction == "sum":
return torch.sum(dist)
else:
... |
f4783a9809e795f048ddc3d2e744d432a843e2155486d62245b5ae79762c05eb | Python | 1,874 | 53 |
def path_functions(linux:bool=False):
import os
directory = os.getcwd()
if linux == True:
directory_functions = str(directory +"/functions/")
path = directory_functions
else:
path = str(directory +"\\functions\\")
#path = "C:\\Users\\gabri\\Box\\Do... |
073216bed5ff771b81db72612aec36fbda06d7a52b25805f9b0ebf61bf913f96 | Python | 1,876 | 66 | """**Chat Models** are a variation on language models.
While Chat Models use language models under the hood, the interface they expose
is a bit different. Rather than expose a "text in, text out" API, they expose
an interface where "chat messages" are the inputs and outputs.
"""
import warnings
from langchain_core._... |
00264126d82055110fdd75d8b1cfbfa441e520c625a85c5e3ba38cdcc6157538 | Python | 1,877 | 71 | """
This script summarized DE results by chromosome
"""
import session_info
import pandas as pd
from pyhere import here
from scipy.stats import kstest
from functools import lru_cache
@lru_cache()
def load_data():
fn = "BrainSeq_sexGenotypes_4features_3regions.txt.gz"
return pd.read_csv(fn, sep='\t')
@lru_cac... |
a2e3eede5b8504d7889a9e2b148cf1add5d89537df1f9e14c1c74e0d6c56b9cc | Python | 1,884 | 63 | from torch import nn
class Cov1(nn.Module):
def __init__(self, input_size, output_size):
super(Cov1, self).__init__()
self.cov1 = nn.Sequential(
nn.Conv1d(input_size, output_size, kernel_size=3, padding=1),
nn.BatchNorm1d(output_size),
nn.MaxPool1d(ke... |
53157c577261b90b932084242409c800e230d6eb7455fd7bba9bf7b9431d99d1 | Python | 1,885 | 55 | # Copyright 2022 MONAI Consortium
# 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 to in writing, s... |
cb5ed5c70c052ba6a5fb7165cab51996cce3be8b95e7fcd2409b035ba94be048 | Python | 1,885 | 55 | ####################################################################################
#
# STEPS - STochastic Engine for Pathway Simulation
# Copyright (C) 2007-2023 Okinawa Institute of Science and Technology, Japan.
# Copyright (C) 2003-2006 University of Antwerp, Belgium.
#
# See the file AUTHORS for d... |
b67bc8078809e676e0a7c83e18b8ac3990581ad441e15a4dccd180c4626dc7e5 | Python | 1,886 | 55 | ####################################################################################
#
# STEPS - STochastic Engine for Pathway Simulation
# Copyright (C) 2007-2026 Okinawa Institute of Science and Technology, Japan.
# Copyright (C) 2003-2006 University of Antwerp, Belgium.
#
# See the file AUTHORS for detai... |
4c8e08d00b98b2e5bbd5d1a36286b3afb08bd86e754801ae1b37c52e81214ba7 | Python | 1,887 | 80 | import numpy as np
import joblib
import torch
import matplotlib.pyplot as plt
from matplotlib import colors, gridspec
from dt_utils import Timer
from data_utils import generate_recognition_data
from torch_net_utils import maxabs, plot_W_seq, plot_xahy_seq, run_net, plot_corr, list2tensor
from neural_net_utils... |
07985a49bf9fff01421a6c2395168d20c2bf701c807f3ea949cd3d7644287328 | Python | 1,888 | 61 | import tifffile as tiff
import os
from pynwb import NWBHDF5IO
# this script reads .nwb files and writes corresponding new .tif files, for analysis in ImageJ.
# source data: https://dandiarchive.org/dandiset/000467
# written by Taylor Hart
# specify the input and output directories below:
indir_path = "/Volumes/My ... |
2c748e00ddb7b0837804cf8ad2a96242971d5a7e183e43ef84d4e104df988d4a | Python | 1,888 | 66 | from llama_index.core.schema import TextNode
from llama_index.core import Settings
from llama_index.core import VectorStoreIndex
import pandas as pd
from tqdm import tqdm
def evaluate(
dataset,
embed_model,
top_k=5,
verbose=False,
):
corpus = dataset.corpus
queries = dataset.queries
releva... |
45a90cf529edc38158d95aad74102ec7ef21dfdef105453000cf9a6b65eebb34 | Python | 1,888 | 66 | from __future__ import annotations
import logging
from copy import deepcopy
from typing import List, Union
import numpy as np
from libs.common.connenction import Connection
from libs.common.position import Position
from libs.common.weight import Weight
log = logging.getLogger(__name__)
class Generator:
def __... |
4a13da1d0af9e5c9fe3a12eedae7b8ef3680812abb0fd69c27dddf8e3387a30c | Python | 1,889 | 49 | """tests for asymmetry.py.
a perfectly symmetric mesh (icosphere, symmetric across x=0 just by how
it's built) should score close to zero, and pushing one side out should
clearly raise the score. just checking this behaves sensibly, no need for
a real registered face scan for that.
"""
import numpy as np
import trime... |
b4bcd01f2b6552439a80b98817ab12978b609d8a647483f780afd7ba9c408fb0 | Python | 1,890 | 54 | import subprocess
import sys
import pytest
from pytest_benchmark.fixture import BenchmarkFixture
@pytest.mark.parametrize(
"import_path",
[
pytest.param(
"from langchain_core.messages import HumanMessage", id="HumanMessage"
),
pytest.param("from langchain_core.tools import... |
18ac4afe4026134cbb9dfe7cb245f0d5a0f2da8c280c61cfe84252737e8f5a12 | Python | 1,891 | 70 | import torch
from pdearena.configs.config import Config
from typing import Tuple
class Normalizer(torch.nn.Module):
def __init__(self, args: Config):
super().__init__()
self.norm = args.normalize
def reshape_stats(
self,
shape: torch.Size,
mean: ... |
6941b5c604df778a1539f751f183c065c7380cdba4da4c4572392209ccaddbf6 | Python | 1,891 | 51 | from langchain_core.prompts.prompt import PromptTemplate
EXAMPLES = [
"""Setup: You are now playing a fast paced round of TextWorld! Here is your task for
today. First of all, you could, like, try to travel east. After that, take the
binder from the locker. With the binder, place the binder on the mantelpiece.
Alr... |
87d240616e573e8f3ada8241465f8eaacd536db7503196bed7f43a691325fff5 | Python | 1,891 | 63 | """String output parser."""
from typing_extensions import override
from langchain_core.output_parsers.transform import BaseTransformOutputParser
class StrOutputParser(BaseTransformOutputParser[str]):
"""Extract text content from model outputs as a string.
Converts model outputs (such as `AIMessage` or `AIM... |
be150001019611582f8e176f038139bc3c8de3a23dc8c0795b4ed4f30684a49f | Python | 1,891 | 51 | import re
class Tokenizer():
def __init__(self):
pass
def tokenize_words(self, doc_string):
token_list = doc_string.strip().split()
token_list = [x.strip("\u200c") for x in token_list if len(x.strip("\u200c")) != 0]
return token_list
def tokenize_sentences(sel... |
98e40f138b6455ed15faa340aa9d25d670db3b54facfd73978d1d4d6d544c33e | Python | 1,892 | 62 | """
This script runs tensorQTL in python.
"""
import pandas as pd
import argparse, session_info
from functools import lru_cache
from tensorqtl import cis, read_phenotype_bed
from tensorqtl import calculate_qvalues, genotypeio
@lru_cache()
def get_genotypes():
plink_prefix_path = "../../plink_format/_m/genotypes"
... |
c17d56f82f02f61dacfb007dd68f0b76c5cb00f42cf2a59cf23c9178b2236c6b | Python | 1,892 | 69 | import pandas as pd
import numpy as np
import pathlib
import yaml
import argparse
import decoupler as dc
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--key", type=str, required=True)
parser.add_argument("--method", type=str, required=True)
args = parser.parse_args()
with op... |
d42b087398f27f260ce688deb63df4a09532f037a4955176914bd338ea67d358 | Python | 1,892 | 54 | """ Prepares input for Zilany et al. (2014) model.
This is my pipeline to prepare the speech waves for the Zilany model. The speech waves are normalized, resampled to 100
kHz (as required by the model), and scaled to a given presentation level. The arrays are then saved as .npy files.
"""
import numpy as np
import sc... |
f9dec942d8208664cf116b1391f823c7e27767297e56df5fc52f2bbb0065aa2b | Python | 1,892 | 58 | import shutil
import sys
from pathlib import Path
# ruff: noqa: E402
REPO_ROOT = Path(__file__).parent.parent.parent.resolve()
sys.path.append(f"{REPO_ROOT}")
from get_predictions import predict, load_model, PredictionResult
DEFAULT_DISORDERED_DOMAIN_THRESHOLD = 0.35
def get_length_from_pdb_file(pdb_file):
with... |
5e271b572e251865e53f5ac1ead8f6cb11bc17a3efe4b5e905ce89c068c70950 | Python | 1,893 | 56 | import argparse
arg_parser = argparse.ArgumentParser()
arg_parser.add_argument("chain_info_file")
arg_parser.add_argument("--chain_mapping_file")
arg_parser.add_argument("--sep_char", default="")
ARGS = arg_parser.parse_args()
import sys
import json
def readChainMappings(file_name):
with open(file_name) as FH:
... |
606e29f59012f1d4b98f418a2745acce746656ea91fd277e3f4d5c3167900eeb | Python | 1,895 | 61 | import os
import glob
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image, ImageDraw
PATH = r"H:\learned spectral unmixing\test_final\forearm/"
for folder_path in glob.glob(PATH + "*"):
if not os.path.isdir(folder_path):
continue
folder = folder_path.split("/")[-1].split("\\")[-1]... |
4b6bde841200327b5e5a99bb65bcdaacef23292e0ccb0b32226542a9919cd566 | Python | 1,896 | 68 | import logging
import os
from pathlib import Path
import hydra
import pandas as pd
from omegaconf import DictConfig, OmegaConf
from tqdm import tqdm
from src import PROJECT_DIR
from src.data.utils import get_file_list
log = logging.getLogger(__name__)
log.setLevel(logging.INFO)
@hydra.main(
config_path=os.path... |
6b5776bfce4f79fbbe6133ab9d30407ea9bd1404b19446f18b15d10e2ebd7e0c | Python | 1,896 | 69 | import os
import logging
import datetime
from tensorboard.backend.event_processing import event_accumulator
from utils.distribution import is_master_process, sync_barrier_re1
from utils.my_containers import singleton, Register
from torch.utils.tensorboard import SummaryWriter
@singleton
class SummaryWriterManager(o... |
5c2db227927e10cb08e52d280c8eddd03535c77aa4f48a713072626bc1c00847 | Python | 1,897 | 66 | import numpy as np
from scipy import interpolate
from skimage.morphology import binary_dilation, disk
import matplotlib.pyplot as plt
from matplotlib import rc
rc('font', size=17)
rc('font', family='Arial')
# rc('font', serif='Times')
rc('pdf', fonttype=42)
# rc('text', usetex=True)
def compute_spline_coeff(ma, bf, an... |
7c9d534a50902d3b6bf5f4351da322fa6eec959fea95a2a9cce920b7ac2d6541 | Python | 1,898 | 61 | from typing import List, Union
import torch
from torch_geometric.data.datapipes import functional_transform
from torch_geometric.transforms import BaseTransform
@functional_transform("y_to_indices")
class YToIndices(BaseTransform):
r"""Normalizes node features to mean :obj:`0` and standard deviation :obj:`1`
... |
115d579c7404f6c989a25d37b543311fbe9ba84c874aa5aa07a0e331223dc870 | Python | 1,901 | 38 | # Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this sof... |
6357b4110dee0d033dac40881b8ab96488c11287249ffef38c3e1ebeb8f1a532 | Python | 1,902 | 50 | """this FastAPI app is shared by both the web version and the desktop app.
desktop/app.py just runs this exact same app via uvicorn on localhost and
points a pywebview window at it. same backend, same frontend, two ways to
run it, no duplicated code.
"""
import sys
from pathlib import Path
from fastapi import FastAP... |
91049daf30df203343600005e30eb2d004ae52ce65a80c9c25e55fb14cf6b460 | Python | 1,902 | 51 | #!/usr/bin/env python
# Imports
import unittest
import os
import sys
import tempfile
import filecmp
import shutil
PATH_TO_DATA = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'data')
sys.path = [os.path.join(os.path.dirname(os.path.realpath(__file__)), '..')] + sys.path
from enrichm.predict import Predict... |
2a490690a6b044e64e5498aa6cecd0087251b55a6a4480fcb32a2a960959f144 | Python | 1,903 | 88 | import torch
from torch import nn
from genie.model.modules.invariant_point_attention import InvariantPointAttention
from genie.model.modules.structure_transition import StructureTransition
from genie.model.modules.backbone_update import BackboneUpdate
class StructureLayer(nn.Module):
def __init__(self,
c_s,
c_... |
25f42c96fff8fe7b0eda34515a05f25dbac9b73b36fcd06f111fb37704a17023 | Python | 1,904 | 57 | from __future__ import annotations
import logging
from langchain_core.agents import AgentAction, AgentFinish
from langchain_core.exceptions import OutputParserException
from langchain_core.utils.json import parse_json_markdown
from typing_extensions import override
from langchain_classic.agents.agent import AgentOut... |
e13d7c97ef77009081abc3791f5fd243db285f5d9dcd390e43370612043903c8 | Python | 1,904 | 68 | from torchvision.models import densenet121
import torch.nn as nn
import torch
from torchvision.models import resnet34
from networks import vgg3d
from networks import ecg1d
def get_arch(arch,pretrained=False,num_classes=14,num_channels=1):
if arch == 'dn121':
net = densenet121(pretrained=pretrained)
... |
e45c6e48d39d919939d9f594adbc10077da48b4ef2a1ede59cc6127d9f3a5061 | Python | 1,905 | 66 | # Adapted from OpenFold
# Copyright 2021 AlQuraishi Laboratory
# Copyright 2021 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/l... |
5e63dd0dcbf933c0132e0f4651022f280fcc067ad5acd5b4e0d261bfa65fbd0a | Python | 1,906 | 58 | import os
import requests
import time
from src import constants
def download(source):
# Download all public/shared workflows from the given usegalaxy source
out_dir = os.path.join(constants.RAW_GALAXY_FILES, source.replace(".", "_"))
os.makedirs(out_dir, exist_ok=True)
# Don't download workflows ... |
3ad97dd7cff316e8b4d594eda4e1afce646215f5d4b0b1b5025889164ac8b7e8 | Python | 1,907 | 48 | """
Analyze time taken by participants to complete the experiment
(from the moment the subject gave their informed consent
to the end of the last session of the task).
"""
import argparse
import data_analysis_utils as dana
import numpy as np
import os.path as op
import pandas as pd
OUT_FNAME = "experiment_completion_... |
5b819a07474e4a73ed59072ce2c52a2adeb2ec5ed1627c738dfb0fffcdb86774 | Python | 1,907 | 75 | '''
cgat_ini2yml
=======================================
'''
import sys
import re
import cgatcore.experiment as E
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv is None:
argv = sys.argv
# setup command line parser
... |
53a4e0fb4e69946b2b521375529e6c3498c92f38a6dc1d96d8257ac07fca7fa2 | Python | 1,908 | 51 | # Copyright 2024 DeepMind Technologies Limited.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed... |
6b608a5fdb7e86c4dbd9924ef349ac46fe59470d3487cba9ff603ee1a8b1c453 | Python | 1,908 | 58 | import os
from pathlib import Path
def run_input_indiv(pdbname, num, output_folder, localopt_data_path, localopt_exec_path):
Path(f"{output_folder}/relaxed").mkdir(exist_ok=True)
Path(f"{output_folder}/relaxation_scripts").mkdir(exist_ok=True)
input_line = f"""data_directory {localopt_data_path}
to... |
b5b11c288dab5ea69dee18cc0b2a0b4c3a28a7b050269ebd3653b4d479120fce | Python | 1,908 | 70 | #!/usr/bin/env python3
import yaml
import pathlib
# yaml makes me cry
# https://github.com/yaml/pyyaml/issues/98#issuecomment-436814271
# This was causing a warning of NA coercion in R because some kegg pathways were specified as "03602,034,0230"
# and were not being quoted properly by this pkg
from yaml import Dumpe... |
83029af50dbf23e7102c01f524a9e5105ad08017a18da543782551b5efdae6db | Python | 1,909 | 54 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# http://www.sphinx-doc.org/en/master/config
# -- Path setup --------------------------------------------------------------
# If extensions (or module... |
1b5b32ecb2ef9196d848c5096d38e5586831693830c6b647e8443b24eb952927 | Python | 1,911 | 43 | from langchain_core.prompts.prompt import PromptTemplate
_DEFAULT_TEMPLATE = """Question: Who lived longer, Muhammad Ali or Alan Turing?
Are follow up questions needed here: Yes.
Follow up: How old was Muhammad Ali when he died?
Intermediate answer: Muhammad Ali was 74 years old when he died.
Follow up: How old was Al... |
c612548e4c733634f5145958843c46abd2c6ab0eed8f3b1980ef71e1329501f5 | Python | 1,911 | 45 | import os
import time
import pandas as pd
from get_predictions import predict, load_model, parse_args
import matplotlib.pyplot as plt
if __name__=="__main__":
args = parse_args()
# structure_dir = "/Users/judewells/Documents/dataScienceProgramming/data_for_domdet/human_200_c2m"
outer_save_dir = "/Users/... |
06ee952f3852286bdbe5ac7cdcffdbd1792eaa97a4078f94ad99d77e4a087c69 | Python | 1,912 | 69 | import os
from bindsnet.network import Network, load
from bindsnet.network.monitors import Monitor
from bindsnet.network.nodes import Input, LIFNodes
from bindsnet.network.topology import Connection
class TestNetwork:
"""
Tests basic network functionality.
"""
def test_empty(self):
for dt in... |
08c36c2ab361b327dd46395ac6cc4773a35eb0eb21518fad709170a0481542bf | Python | 1,912 | 53 | """This is an automatic script to run all the Python-Matlab Unittests at ones"""
import unittest
from lp_filter_zero_phase_unit_test import lp_filter_zero_phase_unit_test
from peak_det_amp_threshold_unit_test import (
peak_det_amp_threshold_unit_test,
)
from peak_det_local_search_unit_test import peak_det_local_se... |
d1de61ae1a14889c112e27792ae2b5b35581df4061240ba4af5d99b44167bdb8 | Python | 1,912 | 50 | # coding=utf-8
import numpy as np
import torch
def Nmax(test_envs, d):
for i in range(len(test_envs)):
if d < test_envs[i]:
return i
return len(test_envs)
def random_pairs_of_minibatches_by_domainperm(minibatches):
perm = torch.randperm(len(minibatches)).tolist()
pairs = []
... |
490e45b8869a5862944ab08ef901ec5fedde2bfd843775497a5d80a2992bf6bf | Python | 1,915 | 54 | #! /usr/local/bin/python
#'#################################################################################
#'#################################################################################
#' Run random search on tcga data
#'#################################################################################
#'######... |
5d4c1838c9a6e49556922a959ff62e1cdd9d3bd121a31b71363661832d4526ee | Python | 1,918 | 70 | import os
import torch
from torch import distributed as dist
from functools import partial
from utils.my_containers import singleton
@singleton
class DeviceManager(object):
def __init__(self, device=''):
self.device = setup_device(device, mannul=False)
def get_device(self):
return self.devic... |
5bba9e2b66f286f8ce79f3f1972c49ee4500f70388e11b48128ef51d0c825424 | Python | 1,919 | 27 | PODCAST_DOCS = """API documentation:
Endpoint: https://listen-api.listennotes.com/api/v2
GET /search
This API is for searching podcasts or episodes.
Query parameters table:
q | string | Search term, e.g., person, place, topic... You can use double quotes to do verbatim match, e.g., "game of thrones". Otherwise, it's ... |
59b8f364d265bd0be6f978277fd147734b6de4b5c66fa46e9cc33d51820e814b | Python | 1,920 | 62 | #!/usr/bin/env python3
import argparse
import os
import struct
import subprocess
from datetime import datetime
import contextlib
@contextlib.contextmanager
def cd(cd_path):
saved_path = os.getcwd()
os.chdir(cd_path)
yield
os.chdir(saved_path)
parser = argparse.ArgumentParser(
description='Conve... |
bb53ccaa2c7f46baf6d9041f87be6159bffd8ebd75e21d22e8bc3c8c396abc0d | Python | 1,922 | 32 | import argparse
import torch
def get_training_config(args=None):
parser = argparse.ArgumentParser(
description="Graph Neural Network based reinforcement learning solution for Power network reconfiguration")
parser.add_argument('--features_dim', type=int, default=128, help="Embedding length")
... |
bedbc4498ea89751bb55b006b6d133bf17a7e57340e7d281b0d77b6514772398 | Python | 1,923 | 46 | from langchain_core.prompts.prompt import PromptTemplate
web_search_template = """Please write a passage to answer the question
Question: {QUESTION}
Passage:"""
web_search = PromptTemplate(template=web_search_template, input_variables=["QUESTION"])
sci_fact_template = """Please write a scientific paper passage to supp... |
af52c1e3870c632b1e1825e23424881f77ea0e75627b81a1484f37f12e98051d | Python | 1,924 | 53 | from langchain_core.prompts.chat import (
ChatPromptTemplate,
HumanMessagePromptTemplate,
SystemMessagePromptTemplate,
)
from langchain_core.prompts.prompt import PromptTemplate
from langchain_classic.chains.prompt_selector import (
ConditionalPromptSelector,
is_chat_model,
)
templ1 = """You are a... |
d1e63d4c19fc404a609acebe3a6d2eed4316d766318454c80e7f8f486150d44d | Python | 1,924 | 72 | from pathlib import Path
from omegaconf import OmegaConf
from libs.eval.character import Eval as CEV
from libs.eval.expresult import ExpResult
from libs.eval.metrics import Eval as MEV
from libs.eval.structure import Eval as SEV
from libs.utils.utils import set_seed
from libs.visualizer.metrics import CompGenVisualiz... |
3357251fb79b7ad13010f4995ac36c6aab729a743ec1bbf3d0bb6de686d001a7 | Python | 1,927 | 61 | from .clean_protein import ResidueMutator, cleanProtein
from .get_atom_charge_radius import getAtomChargeRadius
from .get_atom_sesa import getAtomSESA
from .get_atom_sasa import getAtomSASA, Radius
from .get_atom_depth import getAtomDepth
from .get_dssp import getDSSP
from .get_achtley_factors import getAchtleyFactors
... |
40996cbdf90d471206a76731f9c804ebe9bfec9e4a45aebe1c1043e76fd5b150 | Python | 1,929 | 39 | #!/usr/bin/env python
# -*- encoding: utf-8 -*-
'''
@Description: :
@Date : 2022/06/15 12:27:12
@Author : Zilan Yu
@version : 1.0
'''
from argparse import ArgumentParser
#Args parser
parser = ArgumentParser(description="Specifying Input Parameters")
# Data directory
parser.add_argument("-pd", "--p... |
7f635a4aa60a42b75db84f8594a3a341907c223169e13339863dcf7408d63c04 | Python | 1,930 | 57 | ####################################################################################
#
# STEPS - STochastic Engine for Pathway Simulation
# Copyright (C) 2007-2023 Okinawa Institute of Science and Technology, Japan.
# Copyright (C) 2003-2006 University of Antwerp, Belgium.
#
# See the file AUTHORS for d... |
edca3dd54454783d594adb2a794521147bcfafef15b78c1c4a2ec710dc2b1250 | Python | 1,930 | 57 | ####################################################################################
#
# STEPS - STochastic Engine for Pathway Simulation
# Copyright (C) 2007-2026 Okinawa Institute of Science and Technology, Japan.
# Copyright (C) 2003-2006 University of Antwerp, Belgium.
#
# See the file AUTHORS for detai... |
f22d38f579c2ca82c0194b34d2b87c20d542c1085191d32213b93664747b3f22 | Python | 1,932 | 44 | #External imports
import torch
from torch.utils.data import TensorDataset
import torch.nn.functional as F
#My imports
from data import generate_recog_data_batch
from networks import HebbNet
from plotting import plot_train_perf
from net_utils import binary_classifier_accuracy
def generate_juri_data(T=100):
... |
0404f74b129f4b24baaf473629b6268600e4294374bceb00c0026901f58df8e7 | Python | 1,933 | 52 | """Preserve legacy notebook molecules and MSAs in Boltz's RGI-capable YAML."""
import copy
def notebook_input(
entries, *, config=None, conformer_chains="ligands", single_sequence=False
):
sequences = []
ligands = set()
for header, sequence in entries:
fields = header.lstrip(">").split("|")
... |
20bd651515c94f97bed59f040b6832038e9ed314c023bda45854e26435f4d5b5 | Python | 1,934 | 32 | import argparse
import torch
def get_training_config(args=None):
parser = argparse.ArgumentParser(
description="Graph Neural Network based reinforcement learning solution for Power network reconfiguration")
parser.add_argument('--features_dim', type=int, default=128, help="Embedding length")
... |
b8d3d946c68080d0bc708bca9fef7db489e10e2e0597bfc1f40a1695c844d5ac | Python | 1,934 | 79 | # Copyright (c) MONAI Consortium
# 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 to in writing, so... |
467748b09bf0e416c30d8791f6d75347a9a9173fdf807c7c5329d49c1c907d06 | Python | 1,935 | 70 | # Copyright (c) 2023 Shihao Ma, Haotian Cui, WangLab @ U of T
from typing import Iterable
import numpy as np
import skunk
from matplotlib.offsetbox import AnnotationBbox, OffsetImage, TextArea, VPacker
def _nearest_spiral_layout(x, y, offset):
# make spiral
angles = np.linspace(-np.pi, np.pi, len(x) + 1 + of... |
a4d8bede5a8aca4ec58bf245661735aa46fcfa545a3aab4e3cf91618d7b6953d | Python | 1,935 | 66 | import torch
import torch.nn as nn
from core.network.model import model_register
from core.network.utils import cosine_similarity
@model_register
class VariationalAutoEncoder(torch.nn.Module):
def __init__(self, cfg):
super(VariationalAutoEncoder, self).__init__()
self.cfg = cfg
self.emb_... |
b7e466776b206208ca75ba8073475468b35b2be94ca55b062a376c56506d998f | Python | 1,936 | 62 | from enum import Enum
from typing import Callable
from typing import Optional
from neuralpredictors.measures import modules as ml_measures
from pydantic import BaseModel
from pydantic import PositiveFloat
from pydantic import PositiveInt
from torch import nn
from ..common.config import get_config_file
from ..common.c... |
23a239918997e48f81c90a953a0854109459efe94f6fb7346c3f5effaef3fb0a | Python | 1,938 | 60 | import warnings
from contextlib import contextmanager
import torch
@contextmanager
def eval_state(model):
"""
Context manager, within which the model will be under `eval` mode.
Upon existing, the model will return to whatever training state it
was as it entered into the context.
Args:
mo... |
a799161210496cfaf397730954b17ba43ae6ea6957927f3f7aefbda7b90cb6c4 | Python | 1,938 | 52 | # Copyright 2022 DeepMind Technologies Limited. All Rights Reserved.
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by... |
0a1dcc0b2beedfa9ace76aeb4e5fb1871ce95cede56c602ec62578eda5c00aed | Python | 1,939 | 54 | # -- coding: utf-8 --
# @Time : 2022/12/19 21:16
# @Author : Biao Zhang
# @Email : littlebiao@outlook.com
# @File : test_tree.py
# @Description: This file is used to ...
import pandas as pd
from treelib import Node, Tree
tree = Tree()
tree.create_node('root', 'root')
def add_node(tree_dict, key_input):
if tree_di... |
1155a0cdb14e99fea198388066a600273b2235eae9dd8342fd366af43edf7f44 | Python | 1,939 | 77 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Most of this script is simply copied from:
https://scikit-learn.org/stable/auto_examples/linear_model/
In the example Comparing Linear Bayesian Regressors
"""
# pylint: skip-file
from matplotlib.colors import SymLogNorm
import seaborn as sns
import matplotlib.pyplo... |
392ed55811893d346eb55a228faeafbc6155e05db1b59b4f534a3c9d896160ac | Python | 1,939 | 59 | import numpy as np
import os
from brian2 import *
from brian2modelfitting import *
from Analysis.dataloader import dataloader_AP
experimentalist = 'Elodie'
neuron = 'MSN_In_Vitro'
path = '/users/gvignoud/Documents/numeric_networks/Data/'+experimentalist+'_'+neuron+'/'
file_list = [u for u in os.listdir(path) if u[-7:... |
2b03bf5ef94772aa024a269603bd972170183c3a2e932dad411754ea09241e74 | Python | 1,943 | 53 | """A server that needs input mid-call, answered by a human.
Some MCP tools cannot finish without asking something. `MCPAdapter` surfaces the
question as a LangGraph `interrupt()`, so the person already reviewing the
agent's work answers it and the run resumes.
The adapter arms every client it builds to advertise the ... |
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