sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
c8990a4706691fd5aad261b4d75957642610cb30d577fcb424d7f0ab72042f09 | Python | 15,607 | 435 | ####################################################################################
#
# 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... |
baa4bddef3b806b8993716df896e1956e8bd07905c4371e53ac88c5102eab5b8 | Python | 15,610 | 513 | """
Utility functions for simulations using openeye toolkits
"""
__author__ = 'John D. Chodera'
from simtk import unit
from simtk.openmm import app
import simtk.unit as unit
import numpy as np
import logging
_logger = logging.getLogger("utils.openeye")
_logger.setLevel(logging.INFO)
def system_generator_wrapper(... |
fd2b2cbf1b48c3de6d05ebe50af2fb36af3a8845ca1083656857027fb271505c | Python | 15,616 | 398 | """EMBanded model."""
import copy
from typing import List, Tuple
import numpy as np
from .helpers import (
check_positive_float, check_input, check_boolean, check_smooth_params
)
from ._numpy_model_utils import (
prepare_smoothness_cov, create_matrix_indexer,
fit_model_multidimensional, fit_model_vectoriz... |
1a818a67edcaabd602a3fc443a2809a81c7ec967a6120bf42d7b44fb2ba02611 | Python | 15,619 | 282 | from langchain_core.output_parsers.list import CommaSeparatedListOutputParser
from langchain_core.prompts.prompt import PromptTemplate
PROMPT_SUFFIX = """Only use the following tables:
{table_info}
Question: {input}"""
_DEFAULT_TEMPLATE = """Given an input question, first create a syntactically correct {dialect} que... |
b27acc18a575b01918367654347da3b3d3f73c376040a42b3aa996f3622bb05b | Python | 15,628 | 493 | import copy
from typing import Dict, Tuple, Sequence, Union, Optional
import numpy as np
from tqdm import tqdm
from cloudfiles import CloudFiles, compression
from cloudvolume import lib, exceptions
from ....types import CompressType, MipType
from ....lib import Bbox, Vec, sip, first, BboxLikeType, toiter, xyzrange
f... |
662c680997192d50f680854eb01a080afe28b36e711a7f31ffe436e2675a7c1c | Python | 15,640 | 391 | # 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... |
bc65b9d28c0ac0da5de7965a348828c59534af3f75f4b42a16d25edfc754891c | Python | 15,648 | 405 | import numpy as np
import torch
from torch_scatter import scatter
def abs_cap(val, max_abs_val=1):
"""
Returns the value with its absolute value capped at max_abs_val.
Particularly useful in passing values to trignometric functions where
numerical errors may result in an argument > 1 being passed in.
... |
3fb5d8d71e3adbfde2084ead9815c391cecbeca52f761a892ea959379a433c02 | Python | 15,649 | 446 | """Test loading functionality."""
import json
import os
from collections.abc import Iterator
from contextlib import contextmanager
from pathlib import Path
from typing import Any
import pytest
from typing_extensions import override
from langchain_core._api import suppress_langchain_deprecation_warning
from langchain... |
9e29254cdb7053f0a5b3635d312c2a152914e0cdc32c3e4b7eb00b30327c6e32 | Python | 15,653 | 347 | #!/usr/bin/env python3
# pylint: disable=line-too-long
'''
Check for blocks of enriched genes that co-occur within the genome,
using intergenic distance boundaries and strand/order information from GFF.
'''
import logging
from collections import Counter
from itertools import chain
from enrichm.toolbox import reverse_di... |
72b1d9a4f791e3178631ec742c00b3366b1f2be48da0eef555e3e6f9e5a98964 | Python | 15,691 | 508 | """Test the LangSmith evaluation helpers."""
import uuid
from collections.abc import Iterator
from datetime import datetime, timezone
from typing import Any
from unittest import mock
import pytest
from freezegun import freeze_time
from langsmith.client import Client
from langsmith.schemas import Dataset, Example
fro... |
6a489adab927b2fc829b6ac2e8aecab3999d6c45ccadb6af8818a176822575f9 | Python | 15,713 | 378 | # -*- coding: utf-8 -*-
"""script_linearnetwork_diffbottleneck.ipynb
Automatically generated by Colab.
Original file is located at
https://colab.research.google.com/drive/15ek-TkpNbt_UcgvOihWCPfIPUttm3K8s
#Simulation for knockout training:
**Two-layer linear network, different bottleneck**
Please see "script_li... |
c42f0c9243753cd58f7ca70d4190ec537683b6050718ace32c42ec249b45a99b | Python | 15,716 | 440 | ####################################################################################
#
# 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... |
74294043c0e1bfa477a024c72e2e29751ba30241a6e96e66fdbfff51612ced55 | Python | 15,718 | 404 | import torch
import numpy as np
import torch_geometric
from EGNN_SE3 import EGNN as EGNNSE3
import torch.nn.functional as F
import torch.nn as nn
from utils import build_edge_idx
from torch_geometric.utils import from_networkx, unbatch_edge_index
import networkx as nx
from torch_geometric.data import Data, Batch
from t... |
329f4b0b303c8bc4727fe2dde954f85c36271d521b9b703131d69b14c1de2fab | Python | 15,739 | 467 | import nibabel as nib
import numpy as np
from himalaya.ridge import GroupRidgeCV
import sys
from sklearn.model_selection import KFold
from scipy.stats import pearsonr
from scipy.stats import zscore
from sklearn.model_selection import TimeSeriesSplit
from sklearn.model_selection import train_test_split
from sklear... |
b6ca63061d5f8277de199bcc5df759923164f141d0192ccf6fdd92a385c9688c | Python | 15,747 | 546 | """In-memory vector store."""
from __future__ import annotations
import json
import uuid
from pathlib import Path
from typing import (
TYPE_CHECKING,
Any,
)
from typing_extensions import override
from langchain_core.documents import Document
from langchain_core.load import dumpd, load
from langchain_core.ve... |
74590175ef1042dd8bd97f5c88a988b3818ef1e450eefd8f0ec67d7c6324fd2f | Python | 15,770 | 473 | """Types for setting agent response formats."""
from __future__ import annotations
import json
import uuid
from dataclasses import dataclass, is_dataclass
from types import UnionType
from typing import (
TYPE_CHECKING,
Any,
Generic,
Literal,
TypeVar,
Union,
cast,
get_args,
get_orig... |
822ba1f0cc9d2500a4662f65a300a4779fcc2c1cee4ae356e001d9aa120ea526 | Python | 15,775 | 457 | """Runnable that selects which branch to run based on a condition."""
from collections.abc import (
AsyncIterator,
Awaitable,
Callable,
Iterator,
Mapping,
Sequence,
)
from typing import (
Any,
cast,
)
from pydantic import ConfigDict
from typing_extensions import override
from langchai... |
e392685779df7a905cf6e40f56d8c2ebf8a0b13c1b0f32987b9bcb87c17f993c | Python | 15,782 | 492 | import os
from contextlib import nullcontext
import torch
import torch.distributed as dist
from torch import nn
from torch.nn.parallel import DistributedDataParallel as DDP
from torch.optim import Adam
from torch.optim.lr_scheduler import CyclicLR, CosineAnnealingLR, ReduceLROnPlateau
from torch_scatter import scatter... |
38780dbbe3d7650bb2c3e6a7c70b0718510e9d4caeaee07e634c5780ef9b9b75 | Python | 15,788 | 371 | #!/usr/bin/env python
# Usage: python3.8 ingestion.py input_dir output_dir ingestion_program_dir submission_program_dir
# =========================== BEGIN OPTIONS ==============================
# Verbose mode:
##############
# Recommended to keep verbose = True: shows various progression messages
verbose = True # ou... |
e8aebe100f5f3d13567b1406fbe287d6ef78b2bba6ade7b4a27dd608180635c0 | Python | 15,806 | 488 | """The command line entry point for Casanovo."""
import datetime
import functools
import logging
import os
import re
import shutil
import sys
import warnings
from pathlib import Path
from typing import Optional, Tuple
warnings.formatwarning = lambda message, category, *args, **kwargs: (
f"{category.__name__}: {mes... |
e238f3f0051a2e2d40749b3b6bea27f486c0d37663ecbcc1f5297aa1959cf453 | Python | 15,820 | 414 | # Copyright 2023 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... |
cccd6cbe29df7afb28f568ca6daa8ae8eeee4523d3af386aa7c18a29ad5520fe | Python | 15,821 | 404 | import numpy as np
import nltk
import csv, os, re
import h5py, json, pickle
import pkg_resources
from symspellpy import SymSpell, Verbosity
import inflect
from sklearn.metrics.pairwise import cosine_similarity as cos_sim
np.random.seed() # randomly initialize the seed
sym_spell = SymSpell(max_dictionary_edit_distance... |
630df0553c257e5fa933180de948c0e6b75404c88050829a9b6fc81329a7d082 | Python | 15,827 | 430 | """Tests for secret injection prevention in serialization.
Verify that user-provided data containing secret-like structures cannot be used to
extract environment variables during deserialization.
"""
import json
import os
import re
from typing import Any
from unittest import mock
import pytest
from pydantic import B... |
82b564440d615863de4d636e771ad452634931485e44c82bb996817b0552319e | Python | 15,842 | 321 | ####################################################################################
#
# 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... |
a5258ececf75d047e40ed47ec1ee5ee971e492ad7312aa6e91e5a9c02fb42f4c | Python | 15,850 | 437 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import os
import random
from typing import Callable, Optional, Sequence, Union
import numpy as np
import torch
# import torchdata.datapipes as dp
import pdearena.data.utils as datautils
from pdearena.data.utils import PDEDataConfig
def build_... |
2c541b5de18fa647e02304e6b13685dea125e090c5e756d829ee0df837e7ea98 | Python | 15,855 | 452 | import torch
import numpy as np
import os
import glob
import random
import matplotlib
import imageio
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from qm9 import bond_analyze
##############
### Files ####
###########-->
def save_xyz_file(path, one_hot, charges, positions, dataset_info, id_from=0, name='mol... |
34cb0d3031b570ce66ea7c039d38df09717c7c3434c824fbde0d957c178cfba0 | Python | 15,877 | 321 | ####################################################################################
#
# 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... |
e949ea35e2c2899e8af000875404b618707caaea6294d29d9487a79761ad441a | Python | 15,886 | 492 | from copy import deepcopy
from typing import Any
import pytest
from langchain_core.messages import AIMessage, AIMessageChunk, HumanMessage
from langchain_core.messages import content as types
def test_convert_to_v1_from_bedrock_converse() -> None:
message = AIMessage(
[
{
"ty... |
d24eb90b48d1bc3138b7847c8b7dd01793e83568b1ea8e2ea1c49a5ca6ce7cff | Python | 15,898 | 335 | import os
import argparse
import torch
from tqdm import tqdm
# import matplotlib.pyplot as plt
import numpy as np
from torch.utils.data import DataLoader
# from plot_utils import Dipole, Efield
import math
import importlib
import yaml
import torch_scatter
from orbevo.eval_utils import tfn_to_abacus_mol, normalize_d... |
9d13af1712f19c0f1eb49f2effbe284083b2a9b3b3d6996484dc18c49a0898fa | Python | 15,908 | 474 | """Base classes for comparing the output of two models."""
from __future__ import annotations
import logging
import re
from typing import Any
from langchain_core.callbacks import Callbacks
from langchain_core.language_models import BaseLanguageModel
from langchain_core.output_parsers import BaseOutputParser
from lan... |
cfd6eb2be21b8d5ec3c1b31f739a66e0156afffb153a7e5f43cadfab2eef761e | Python | 15,921 | 382 | from typing import List, Tuple, Union
from itertools import zip_longest
from rdkit import Chem
import torch
import numpy as np
from HMSA.rdkit import make_mol
MAX_ATOMIC_NUM = 100
ATOM_FEATURES = {
'atomic_num': list(range(MAX_ATOMIC_NUM)),
'degree': [0, 1, 2, 3, 4, 5],
'formal_charge': [-1, -2, 1, 2, 0],
... |
2098ea86879b0905eeae34fcc6bb456cc7ee5936e2a2deaf4f5da2bcbcf4486d | Python | 15,928 | 468 | import logging
import os
import socket
import sys
from fcest.helpers.data import to_3d_format
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import scipy
import seaborn as sns
from configs.configs import get_config_dict
from helpers.figures import set_size
from helpers.plotters import convert_... |
ecf4ac2456fa785ea65014ef22226d044623e0aa93e381910ff386020817a5b8 | Python | 16,005 | 197 | """Protocol P5: laboratory to field (Changan EVs), vehicle-disjoint, on top of corpus B.
Stages
point F1 random labels within the field fleet (leaky reference, 20 % test) -> results/<tag>_point.csv
F3 vehicle-disjoint 5-fold within the field fleet
P5 train on the twelve laboratory... |
0a90815a3cc42ade6764bbf6b8d9936558bc57bf95d16d38881338c4501100e1 | Python | 16,009 | 299 | """
This script contains the classess of the layers that we have implemented for our model
"""
import tensorflow as tf
class AttGraphConvLayer(tf.keras.layers.Layer):
def __init__(self, outDim,activation=None,alphaLReLU=0.2,dropAtt=None, **kwargs):
# constructor, which just calls super constructor
... |
b3fa844e1f8c36f68bbd24f6cd2a2ce14e6ef68ca9bf6b77edb011130fe2aceb | Python | 16,020 | 582 | """PipelineGO - Tasks for a GO analysis
============================================
Reference
---------
"""
import re
import glob
import os
import collections
import sqlite3
import cgat.Experiment as E
import cgatPipelines.Pipeline as P
import cgat.Stats as Stats
import cgat.iotools as iotools
import cgat.csv as C... |
f1d225684bb1c98ccc47770495f1c21cdfe19898fce1d9fcd07e4dc23d90fe82 | Python | 16,021 | 320 | """cutting the mesh down to just the cranium or just the face.
ported the geometry from gui_methods.py's cranial_cut/facial_clip (old repo),
swapping pyvista's .clip()/.clip_surface() for trimesh's slice_mesh_plane.
works on an already-registered mesh (see registration.rigid.landmark_align) -
the plane/sphere numbers ... |
8fb1dc744e0c17d066ac2143101da4ace23dccb30077b2fa98cc525cb6a438b2 | Python | 16,042 | 383 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import pdb
import torch
from torch import nn
from functools import partial
from .activations import ACTIVATION_REGISTRY
import numpy as np
from torchdiffeq import odeint # faster but more memory
# from torchdiffeq import odeint_adjoint as odeint... |
1aca28f16b00237c61c0f64feb140bd914b1fb5f748ecbe9d697fe30de37b173 | Python | 16,050 | 451 | from collections import namedtuple
import json
from pycromanager.acquisition.acq_eng_py.main.acq_eng_metadata import AcqEngMetadata
class AcquisitionEvent:
class SpecialFlag:
ACQUISITION_FINISHED = "AcqusitionFinished"
ACQUISITION_SEQUENCE_END = "AcqusitionSequenceEnd"
def __init__(self, acq, ... |
389ecec8d685469ee8574ab4a7ac0280d5a97e5453453fe9bd5df093b914fb93 | Python | 16,071 | 407 | """
cluster_session.py
SSH connection and cluster capability detection for the BrainCell deployment
panel. Decoupled from the GUI so it can be tested on its own.
Responsibilities:
* Connect to a remote machine over SSH (password or key-file auth).
* Detect what's available there: Docker? Singularity? Neither?... |
9c9397b5febd7eeb5fefe7261d49eda7244b0999db0e7a6ea3cfdc3b6dbdd1c9 | Python | 16,088 | 462 | ###########################
# Latent ODEs for Irregularly-Sampled Time Series
# Author: Yulia Rubanova
###########################
import matplotlib
# matplotlib.use('TkAgg')
matplotlib.use('Agg')
import matplotlib.pyplot
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D
import os
from scipy.stats i... |
c8b43156574faa0cf6c5788d893759c712dac618382326a7b335c783bc40f223 | Python | 16,092 | 351 | from typing import Any, Tuple, List
import os
from os.path import join
from pathlib import Path
from sys import stderr
import time
from torch.utils.data import DataLoader
from torch import nn
import torch
from pprint import pprint
import warnings
warnings.filterwarnings("ignore")
import pytorch_lightning as pl
warnin... |
af0e1d2ddf6412b9134708e1072845c6c7e85fbe673a709f9b06d6fe824f465c | Python | 16,100 | 336 | # Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (the "Software"),
# to deal in the Software without restriction, including without limitation
# the rights to... |
2ddfa589a9788b0272aeb44cd5e819976445140d0e1d823dbfdfa2290a79be3f | Python | 16,119 | 503 | from pathlib import Path
from time import time
import argparse
import shutil
import random
import matplotlib.pyplot as plt
import seaborn as sns
from tqdm import tqdm
import numpy as np
from Bio.PDB import PDBParser
from Bio.PDB.Polypeptide import three_to_one, is_aa
from rdkit import Chem
from scipy.ndimage import ... |
e428c5a5ec964a638a4c5b266516ac2284edd402d8e1e17a63ad55c71c55096c | Python | 16,122 | 290 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# 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://w... |
f586ddd8f7945399937be4bdac8bb9448f3d38bf949cc29cf4368a3321a9798c | Python | 16,124 | 480 | """
Copyright (c) Meta, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
---
MIT License
Copyright (c) 2021 www.compscience.org
Permission is hereby granted, free of charge, to any person obtaining a copy
of this softwa... |
8f0806b2a030b392496901e5f9af388f20abfa4b64ce7ace50baadbb68302de1 | Python | 16,127 | 414 | import torch
import torch.nn as nn
from torch.nn import functional as F
import numpy as np
def adjust_spines(ax, spines):
"""
axis spine
use it like: adjust_spines(ax, ['left', 'bottom'])
"""
for loc, spine in ax.spines.items():
if loc in spines:
spine.set_position... |
fb2aa66b25d4f0cc11ada7f9ee351c52cf937c6a6796a6f6dd5fa6e9a05082ec | Python | 16,127 | 404 | # -*- coding: utf-8 -*-
"""script_linearnetwork_samebottleneck.ipynb
Automatically generated by Colab.
Original file is located at
https://colab.research.google.com/drive/156AuJeYr-300s3wEpTG_6Nv_P7l2hskC
#Simulation for knockout training:
**Two-layer linear network, same bottleneck**
Idea:
Treat a ground trut... |
cb44b684eb837bd1f3c9c552c98643ec0a5376b2881b340f0a41d2ef2497d25b | Python | 16,132 | 441 | # 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... |
7b90c968bc565d9dae224e14d6f3206d0333d4598113e4b6459beb52c051d2a7 | Python | 16,133 | 422 | import argparse
import logging
import os
import re
import random
import shutil
import sys
import time
from xml.etree.ElementInclude import default_loader
import numpy as np
import torch
import torch.backends.cudnn as cudnn
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import torch.d... |
30da4bef2b0c3305559bb25e4b639e79c9a4ec4e06fea5505b4a703f04262a4b | Python | 16,156 | 307 | import numpy as np
import networkx as nx
import torch as pt
import pytorch_lightning as ptl
import torch_geometric as ptg
import torch
from torch.nn import Sequential as Seq, Linear, ReLU
from torch_geometric.nn import MessagePassing
from pytorch_lightning import LightningModule
from torch.optim.adam import Adam
from t... |
8f1a127a36b68b615d721dca13fd38e8157f615ae68cd987f702eec6874795d1 | Python | 16,159 | 483 | """Prompt template that contains few shot examples."""
from __future__ import annotations
from typing import TYPE_CHECKING, Any, Literal
from pydantic import (
BaseModel,
ConfigDict,
Field,
model_validator,
)
from typing_extensions import override
from langchain_core._api import deprecated
from lang... |
7e2fa141668a8b2d44b96b08e41afa0cbd91707884e54564186b5ac54c3e3226 | Python | 16,161 | 596 | #############################################################################
#
#Updated by: Yiqin Wang
#
##############################################################################
import os
import re
from FileIO import FileIO
#from collections import defaultdict
def flip(x):
#return a reverve complementary stri... |
763febd7795cc7f546988e31f9b35434713745d646e8b466d08cf8f9905f3ce1 | Python | 16,189 | 318 | import copy
import torch
import os
from tqdm import tqdm
import numpy as np
from CEL.utils.register import register
import torch.nn as nn
import optax
import equinox as eqx
import jax
from CEL.data.data_manager import MyDataLoader
from CEL.networks.models.meta_model import ModelClass
import pathlib
from munch import M... |
d1b6db85618d104eb6694e4b3d3f9507b02092ac6507281de8323b4ca2cd42a2 | Python | 16,191 | 521 | """Generic utility functions."""
import contextlib
import datetime as dt
import functools
import importlib
import os
import warnings
from collections.abc import Callable, Iterator, Sequence
from importlib.metadata import version
from typing import Any, overload
from uuid import uuid4
from packaging.version import par... |
8be20f55249b6babc19931067425c3816c008881eaf49f4cf8bcd5ab1fdf7af8 | Python | 16,194 | 293 | #!/usr/bin/env python
# =============================================================================
# MODULE DOCSTRING
# =============================================================================
"""
Test Force classes in forces.py.
"""
# ========================================================================... |
dba13f16d831d48d1b9bb1b427207d0603a48c8687273d68ee7b599fe57afec9 | Python | 16,196 | 183 | import numpy as np
from rdkit import Chem
import torch
# ------------------------------------------------------------------------------
# Computational
# ------------------------------------------------------------------------------
FLOAT_TYPE = torch.float32
INT_TYPE = torch.int64
# --------------------------------... |
91ca1dd1a32d396a88f008fd6e192946cbfe3824e4704e6e642fb8ec297f89df | Python | 16,198 | 460 | ########################################################################
# Well-mixed chemical reactions.
# AIMS: to verify STEPS well-mixed deterministic solver 'wmrk4' computes
# reaction rates correctly when many different chemical species and
# reactions are present in the model.
# This model combines all we... |
ed974c6e47d12fc223fa51d1e19d56b90beff9dbb8691a1cbbfca645002c9a50 | Python | 16,199 | 467 | from ChipseqReport import *
class FoldChangeTracker(TrackerSQL):
'''the fold change tracker ignores unstimulated tracks.'''
def __init__(self, *args, **kwargs):
TrackerSQL.__init__(self, *args, backend=DATABASE, **kwargs)
def getTracks(self, subset=None):
tracks = TrackerSQL.getTracks(s... |
ff6ce2bda83fe13650c5c121005bae48c36ab0e1cbad23884aed6e2e3b2379da | Python | 16,215 | 460 | ########################################################################
# Well-mixed chemical reactions.
# AIMS: to verify STEPS well-mixed deterministic solver 'wmrk4' computes
# reaction rates correctly when many different chemical species and
# reactions are present in the model.
# This model combines all we... |
b063b1d4cbc54b5c003a1176334d1e862a35512532057ac156f081416720475d | Python | 16,228 | 413 | import pandas as pd
import numpy as np
import json
import os
import torch
import rpy2.robjects as robjects
import rpy2.robjects as ro
import rpy2.robjects.numpy2ri
from rpy2.robjects import pandas2ri
from rpy2.robjects.packages import importr
from rpy2.robjects.conversion import localconverter
from rpy2.rinterface impo... |
395fab03284aa69795de86a1c62af58b401c6085fca9328df176a35bf65fb3c6 | Python | 16,230 | 415 | # image processing
import os
from typing import Union
import cv2 as cv
import numpy as np
import tifffile as tf
from matplotlib import pyplot as plt, patches
from skimage import io as skio
# simple ZProfile function for any sized square in the frame (equivalent to ZProfile function in Fiji)
def ZProfile(stack: Union... |
7ebf4b8a3761e395c41f5f04b0664ba2251e3b4fd77b6b6adacdbcf2aa417137 | Python | 16,245 | 348 | # -*- coding: utf-8 -*-
# @title Generate configuration files for SNN HH
# @file gen_config.py
# @author Romain Beaubois
# @date 23 Oct 2023
# @copyright
# SPDX-FileCopyrightText: © 2023 Romain Beaubois <refbeaubois@yahoo.com>
# SPDX-License-Identifier: GPL-3.0-or-later
#
# @brief Script to generat... |
af60098250f4a9d3ec1bdac0589646ea57ffe1a115901f16a776adb36cf9fbbb | Python | 16,260 | 467 | ########################################################################
# Well-mixed chemical reactions.
# AIMS: to verify STEPS well-mixed stochastic solver 'Tetexact' computes
# reaction rates correctly when many different chemical species and
# reactions are present in the model.
# This model combines all we... |
9781b13fbfeb003ff82a8904fafc8cfce7cafc61afc5225c641599afc99331c7 | Python | 16,267 | 451 | ########################################################################
# Well-mixed chemical reactions.
# AIMS: to verify STEPS well-mixed stochastic solver 'TetVesicle' computes
# reaction rates correctly when many different chemical species and
# reactions are present in the model.
# Note, while these are well-mi... |
7cc4fe3710f5444841e878621d6b69ae8923f9b1e291df72e0e4f699cea2b4ee | Python | 16,272 | 558 | # 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 ... |
8553cb6b5a4ed2a44ce8f88ac5bad92c9045baeca4792c316692e33b65ad3fd9 | Python | 16,272 | 449 | # 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/licenses/LICENSE-2.0
#
# U... |
3238aefcca1948304f9dafb244ad2185c8e0a695255942566cf9f179a4cc357d | Python | 16,277 | 467 | ########################################################################
# Well-mixed chemical reactions.
# AIMS: to verify STEPS well-mixed stochastic solver 'Tetexact' computes
# reaction rates correctly when many different chemical species and
# reactions are present in the model.
# This model combines all we... |
0966bb7625423a1fa44154ea7e63972d1bcc8359152a74faaebf3e6764d304cb | Python | 16,282 | 333 | #!/usr/bin/env python3
# coding: utf-8
"""
Run ABCD Task Prep Level 1 analysis for pipeline_wrapper.py
Greg Conan: gconan@umn.edu
Created: 2021-01-15
Updated: 2021-12-03
"""
# Import standard libraries
from glob import glob
import os
import shutil
import subprocess
import sys
def find_local_imports(flg):
"""
... |
973e3ab715ee8e82209c1543cf17682823a9c33629c9e0b0bb23387f5ec0fcc8 | Python | 16,282 | 185 | # code adapted from https://github.com/arneschneuing/DiffSBDD/blob/main/constants.py
import numpy as np
from rdkit import Chem
import torch
# ------------------------------------------------------------------------------
# Computational
# ------------------------------------------------------------------------------
... |
7392508bad73e285899b8b1e34e882031773a7ee9ec8cea9c75b3324be522cdf | Python | 16,284 | 451 | ########################################################################
# Well-mixed chemical reactions.
# AIMS: to verify STEPS well-mixed stochastic solver 'TetVesicle' computes
# reaction rates correctly when many different chemical species and
# reactions are present in the model.
# Note, while these are well-mi... |
039d624d1eab72aa384c3f09095e61e766252fe3c91f7fbdd215b2518dd96ad5 | Python | 16,321 | 416 | from typing import Union
import numpy as np
import pandas as pd
from mne import EvokedArray
from scipy.linalg import eigh, pinv
from sklearn.base import BaseEstimator, TransformerMixin
def _shrink(cov, alpha):
n = len(cov)
shrink_cov = (1 - alpha) * cov + alpha * np.trace(cov) * np.eye(n) / n
return shrin... |
d5f4b5bd4fba1b43862b24648a05c52ba6d1f0e7d1ff197f6ca5ee184a7d7ae5 | Python | 16,325 | 393 | import albumentations as A
from albumentations.pytorch import ToTensorV2
from joblib import Parallel, delayed
from torch.utils.data import DataLoader
from modulable_CNN3D import CNN3D
import os
import torch
from torch import nn
import numpy as np
from skimage.io import imread, imsave
from src.napari_svetlana.CustomDa... |
7bc73df9b57ba90eaafecfd4dc391509b25fc2984032d204fd363421ac9dabaf | Python | 16,342 | 374 | # 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... |
55c87336d9d6414ff4e325d46f23282544fc66ca787b60ca350dd75e1d05e74d | Python | 16,354 | 384 | import torch
import os, json
import os.path as osp
from itertools import repeat
import numpy as np
from rdkit import Chem
from torch_geometric.data import InMemoryDataset, Data
from tqdm import tqdm
import msgpack
import pickle
dict_drug = {1:'H', 5:'B', 6:'C', 7:'N', 8:'O', 9:'F', 13:'Al', 14:'Si', 15:'P', 16:'S', 17... |
d8da508d0804d446d573d17057ed94f14ccc61937debb247fb4f5426a258ad8c | Python | 16,354 | 468 | ########################################################################
# Well-mixed chemical reactions.
# AIMS: to verify STEPS well-mixed stochastic solver 'TetVesicle' computes
# reaction rates correctly when many different chemical species and
# reactions are present in the model.
# This model combines all ... |
651dcc6b437928bf3ddd33b26ed2b301673004999c445acaea134a0a717b4840 | Python | 16,376 | 477 | # Copyright 2023 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... |
3daf9aba90f69ee88c09e9f45d327c0cb1dee8352c07f67232b25d2c7467fa6c | Python | 16,386 | 469 | ########################################################################
# Well-mixed chemical reactions.
# AIMS: to verify STEPS well-mixed stochastic solver 'TetOpSplit' computes
# reaction rates correctly when many different chemical species and
# reactions are present in the model.
# This model combines all ... |
c0fa71208b4c0d20be032d7b15da2229501bbb3ff49a3ffa0e02dc0f3fc542bf | Python | 16,392 | 389 | # 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... |
08df3f524bc23eb611827ccef6e68486c1e5d7966fda2c96efda4f67eea58510 | Python | 16,398 | 571 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Dec 9 16:52:49 2022
@author: mariano
"""
import numpy as np
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
import seaborn as sns
import esprenv as env
import func0 as func
import funinv as funinv
import setInvDict as invdict
... |
9e671e0287ce89e3bb4db26e2f1e670b3db7833e68e52920b33526432557391b | Python | 16,403 | 469 | ########################################################################
# Well-mixed chemical reactions.
# AIMS: to verify STEPS well-mixed stochastic solver 'TetOpSplit' computes
# reaction rates correctly when many different chemical species and
# reactions are present in the model.
# This model combines all ... |
4455e05e1fcdbf694de4e5c402d0fffceea0bd819deb369c468fcf1110aefe6d | Python | 16,410 | 416 | import numpy as np
import os
import sys
sys.path.append("./protein_autoencoder/")
import torch
from torch_geometric.utils import from_networkx
from torch_geometric.nn import radius_graph
from torch_geometric.data import Batch
from torch_geometric.loader import DataLoader
import matplotlib.pyplot as plt
import... |
d3bfefa839c0ca773c3e4b379a549b998f0067b3fed01ca4bc38319511d93aa6 | Python | 16,411 | 530 | """Implementation based on the template of ALIGNN."""
import imp
import random
from pathlib import Path
from typing import Optional
# from typing import Dict, List, Optional, Set, Tuple
import os
import torch
import numpy as np
import pandas as pd
from jarvis.core.atoms import Atoms
from comformer.graphs import PygG... |
016f9b46a3b1b0468892a6935bc563fd9e4890a856b596a87d19784b50a1a8ee | Python | 16,413 | 493 | import math
import random
import cv2
import numpy as np
import torch
from torchvision import transforms
def gray_scale(image: np.ndarray) -> np.ndarray:
# language=rst
"""
Converts RGB image into grayscale.
:param image: RGB image.
:return: Gray-scaled image.
"""
return cv2.cvtColor(imag... |
e65856d0f304da72a820c82f675d6c50531ecfa379c1622fa75665d78627b694 | Python | 16,430 | 324 |
import math
from neuron import h
from Utils.UnitsUtils import UnitsUtils
from Utils.OtherUtils import *
class GensForHomogenVars:
def initHomogenBiophysics(self):
if not h.exportOptions.isExportDistMechs:
return emptyParagraphHint()
lines = []
mmAl... |
e6925b3f4e8631e52a4fb372ed79de68c3be1b8f7be3767922bf297d632d6a97 | Python | 16,448 | 484 | import os
import glob
import torch
import shutil
import subprocess
import numpy as np
import pandas as pd
from tqdm import tqdm
from utils import (
hcluster,
save_as_pdb,
parse_pdb_file,
parse_tm_file,
parse_pae_file,
assign_secondary_structures,
assign_left_handed_helices
)
class Pipeline:
def __init__(
... |
3a6ae6a53558d8cb229a2c88e25c6c8592b50bf23554180ce6348e3fcf09f236 | Python | 16,468 | 414 | import inspect
from typing import List
import torch.nn as nn
from einops import rearrange
import src.models.nn.utils as U
import src.tasks.metrics as M
import torchmetrics as tm
from src.models.nn.adaptive_softmax import AdaptiveEmbedding, ProjectedAdaptiveLogSoftmax
from src.tasks.custom_torchmetrics import torchmet... |
a084a4967ab8b384a855d39dc0632fe3314763caa51f4360090c657aa97a191c | Python | 16,484 | 454 | import equinox as eqx
import jax
import jax.numpy as jnp
import jax.nn as jnn
import jax.lax as lax
import diffrax
import jax.random as jr
from typing import Union
from typing import Literal
from .meta_model import ModelClass
class CDEFunc(eqx.Module):
mlp: eqx.nn.MLP
control_channels: int
state_channels... |
fec189eb4b426b63705febf299e55dc045e1151625aba03168071096b35996cb | Python | 16,489 | 412 | from itertools import combinations
from pathlib import Path
from typing import Union, Dict, Optional
from MRdataset import save_mr_dataset, BaseDataset, DatasetEmptyException
from mrQA import logger
from mrQA.base import CompliantDataset
from mrQA.formatter import HtmlFormatter
from mrQA.utils import _cli_report, \
... |
91df7df201d4ff6261a80b115377d07b81e40257c46c3e2fc9ef2281ec88a501 | Python | 16,491 | 412 | """YOLO_v3 Model Defined in Keras."""
from functools import wraps
import numpy as np
import tensorflow as tf
from keras import backend as K
from keras.layers import Conv2D, Add, ZeroPadding2D, UpSampling2D, Concatenate, MaxPooling2D
from keras.layers.advanced_activations import LeakyReLU
from keras.layers.normalizati... |
f7c823c50d0e0e119aabb5a7b69bc2c71ed41afaee1c63954bc8fefdfdd5d245 | Python | 16,493 | 466 | import itertools
import random
from collections import Counter
from typing import Callable, Dict, List, Optional, Union
import numpy as np
import torch
from ase.data import chemical_symbols
from sklearn.linear_model import Ridge
from torch_scatter import scatter
import hienet._keys as KEY
import hienet.util as util
... |
08597ac2594bf86e1823bff94990cf453056644b740e7045ff94df5e93bd65b4 | Python | 16,505 | 311 | """
This script contains the classess of the layers that we have implemented for our model
"""
import tensorflow as tf
class AttGraphConvLayer(tf.keras.layers.Layer):
def __init__(self, outDim,activation=None,alphaLReLU=0.2,dropAtt=None, **kwargs):
# constructor, which just calls super constructor
... |
e21b893d8b1045447163da31b5d1ec6384af5f369c629037e669cca5902a7eb5 | Python | 16,506 | 311 | """
This script contains the classess of the layers that we have implemented for our model
"""
import tensorflow as tf
class AttGraphConvLayer(tf.keras.layers.Layer):
def __init__(self, outDim,activation=None,alphaLReLU=0.2,dropAtt=None, **kwargs):
# constructor, which just calls super constructor
... |
32e1e90fd93b0143c8607a1a2d902d4fe6b6d67aa637d33e2dc05a357bdb9876 | Python | 16,524 | 405 | from __future__ import annotations
from itertools import combinations, pairwise
import networkx as nx
import pandas as pd
from sklearn.base import clone
from pgmpy import config
from pgmpy.base import DAG
from pgmpy.causal_discovery._base import BaseCausalDiscovery
from pgmpy.ci_tests import get_ci_test
from pgmpy.g... |
b213174d8234fd99764268bdedbb0178bd19af787c6bded101b2da4414f685c9 | Python | 16,543 | 491 | import typing as tp
from functools import cache
import numpy as np
import pandas as pd
from pymaid.client import CatmaidInstance
from ..utils import _eval_remote_instance, DataFrameBuilder, clean_points
def get_landmarks(
with_locations=True, remote_instance=None
) -> tp.Tuple[
pd.DataFrame,
tp.Optiona... |
c00eee5b50add00535d13f73f74876577778be9c388601cd8e71fca34f5a2c7e | Python | 16,546 | 553 | """----------------------------------------------------------------------------
This program calculates transcript integrity number (TIN) for each transcript
(or gene) in BED file. TIN is conceptually similar to RIN
(RNA integrity number) but provides transcript level measurement of RNA quality
and is more sensitive to... |
f243b8284bf12807ff3811bc087e948d3e5e1612ecf087a8fd1f9196356fd3e2 | Python | 16,553 | 429 | '''runExpression.py - wrap various differential expression tools
=============================================================
:Tags: Python
Purpose
-------
This script provides a convenience wrapper for differential expression
analysis for a variety of methods.
The aim of this script is to provide a common tabular... |
520258c9dfc0addd58aa39562ece664ca09cb70a8e6e867be4bc4295963a7616 | Python | 16,567 | 390 | ####################################################################################
#
# 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... |
28ef8c553485523522ef75d993c3ee6145157b9fad6232cf570c61077a74a1f9 | Python | 16,572 | 371 | from itertools import combinations
import pytest
from pgmpy.base import ADMG, DAG, MAG, PDAG
from pgmpy.base._base import _CoreGraph
@pytest.fixture
def AncestralGraph():
"""
References
----------
[1] Zhang, Jiji. "Causal Reasoning with Ancestral Graphs."
Journal of Machine Learning Research 9 (... |
f16d5126bea6007cc928ce64e0ce8643c03225ab5853ad208fd199a5faaed3f2 | Python | 16,606 | 442 | # Copyright (c) <2021> <University of Paderborn>
# Signal and System Theory Group, Univ. of Paderborn, https://sst-group.org/
# https://github.com/SSTGroup/independent_vector_analysis
#
# Permission is hereby granted, free of charge, to any person
# obtaining a copy of this software and associated d... |
6842b416ff9c203efe860014ac82163ef8a76901d471d459bd2123222ed0f0c6 | Python | 16,614 | 444 | import os
import ast
import operator as op
import logging
# dictionary of supported operators
# ops = {ast.Add: op.add, ast.Sub: op.sub, ast.Mult: op.mul, ast.Div: op.truediv, ast.Pow: op.pow, ast.USub: op.neg}
# list of operators we support:
# Matlab | Python
# Matrix operators:
# matrix mu... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.