sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
fa1a3c191013120b0f24846b15b856973f987c103c5454a2fa4b8280c8bf0fab | Python | 32,937 | 743 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#Version Jela! 5.5
import xml.dom.minidom as dom
import xml.dom
from decimal import *
import sys
import os
import datetime
#from Numeric import *
# Dokument erzeugen
implement = xml.dom.getDOMImplementation()
###################Globale Variablen###################
musi... |
13b5bef0aa6bf99ee24731a68d4144f2cc2932acb3116fb32f623a2346ba7767 | Python | 32,973 | 781 | import numpy as numx
import pydeep.base.numpyextension as numxExt
from pydeep.base.activationfunction import Sigmoid
import pydeep.misc.visualization as VIS
import pydeep.misc.io as IO
from scipy.signal import convolve2d
# Set the same seed value for all algorithms
numx.random.seed(42)
class Weight_layer(object):
... |
f2436287e4ce33af94d05bdf2be477e206ba23cd2dbd7053275488b47fdcfa0f | Python | 33,005 | 891 | import sys
import os
import re
import string
import datetime
import steps
if(sys.version_info >= (3,0)):
import configparser as cfg_parser
else:
import ConfigParser as cfg_parser
class Parser(object):
"""
Matlab to STEPS parser to convert a Matlab simbiology model into a STEPS model.
The ... |
6b8b2b74d9148c2beecf7eefd8f5bf94b51da6481bb0ed512499928303bf6afe | Python | 33,054 | 751 | # 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 ... |
210a52722e5f424c0bbcfd1a27455338b2150ca27b2ee57ef89c3099e3babdd9 | Python | 33,057 | 925 | from __future__ import annotations
import inspect
import json
import os
import re
import shutil
from collections.abc import Callable
from dataclasses import dataclass
from pathlib import Path
from typing import Any
DEFAULT_SITE_URL = "https://pgmpy.org"
DEFAULT_VERSIONS_FILE = Path(__file__).resolve().parents[1] / "v... |
96730f89877fac718d019a8408bd74c1f1ebca652c8b799fb211490ae88e60b0 | Python | 33,065 | 783 | import numpy as numx
import pydeep.base.numpyextension as numxExt
from pydeep.base.activationfunction import Sigmoid
import pydeep.misc.measuring as MEASURE
import pydeep.misc.visualization as VIS
import pydeep.misc.io as IO
from scipy.signal import convolve2d
from sklearn.linear_model import LogisticRegression
# Set ... |
29f1ea842313464d65c7288bf512d1ebfde9a7ff90fc8834f5a51519f9209ee2 | Python | 33,095 | 910 | from types import ModuleType
import copy
import pylab
import numpy as np
import pandas as pd
import os
from matplotlib.patches import Polygon
from matplotlib.text import Text
from matplotlib.markers import TICKDOWN
import matplotlib
import networkx as nx
import ast
import json
import pickle
import defaultSimulate as d... |
503e32f97db692eb59150080ce5967cc545f5f43b490cd2cb491972464d8ea16 | Python | 33,108 | 680 | import os
import gc
import argparse
import json
import random
import math
import random
from functools import reduce
import numpy as np
import pandas as pd
from scipy import sparse
from sklearn.model_selection import train_test_split, ShuffleSplit, StratifiedShuffleSplit, StratifiedKFold
from sklearn.metrics import acc... |
0cddf24ebdee86be5e8801930d95a7f775b770f9b8195719ebf5cb83c635897b | Python | 33,128 | 765 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# :noTabs=true:
# (c) Copyright Rosetta Commons Member Institutions.
# (c) This file is part of the Rosetta software suite and is made available under license.
# (c) The Rosetta software is developed by the contributing members of the Rosetta Commons.
# (c) For more inform... |
40181fd77aea8041348521251b43903298ccdcdd543a9b1403415802ea9d4d06 | Python | 33,140 | 936 | import pylab
import numpy as np
from scipy.signal import convolve2d
from scipy.stats import gamma
from bisect import bisect_right
import unittest
import os
from scipy.integrate import quad
from scipy.optimize import fmin
from scipy import vectorize
import pickle
import pyximport
pyximport.install(setup_args={"include_d... |
a79783c0b34f68a81d415153d4e1dd912bb3d047714a59033eefec7f936fab60 | Python | 33,145 | 744 | import random
from torch.utils.tensorboard import SummaryWriter
import time
import argparse
import torch
from torch import optim
from torch.optim.lr_scheduler import StepLR
from models import ModeFormer, SRCNN, UNet, RDN, Wrapper
from models_FNO import FNO2d
from DataLoader import PDEDataset, train_valid_test_split
fro... |
6b8ff3627060f5b875ef1a96ddd3a699d77dcc82b9fefcf197e050283d850f7f | Python | 33,208 | 804 | # This file borrowed from Swin-UNet: https://github.com/HuCaoFighting/Swin-Unet
import torch
import torch.nn as nn
import torch.utils.checkpoint as checkpoint
from einops import rearrange
from timm.models.layers import DropPath, to_2tuple, trunc_normal_
class Mlp(nn.Module):
def __init__(self, in_features, hidden... |
2b7edbe583fe3eac003c5ced97aee4b48a48777fd2b5a096b3287b9102c7656d | Python | 33,245 | 769 | # 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 ... |
a7fbd0da4ca0b0cc77e3a3ad8ed223e6d1fb33676e8e1785169d9fea32d2af16 | Python | 33,263 | 853 | from equivariant_diffusion import utils
import numpy as np
import math
import torch
from egnn import models
from torch.nn import functional as F
from equivariant_diffusion import utils as diffusion_utils
# Defining some useful util functions.
def expm1(x: torch.Tensor) -> torch.Tensor:
return torch.expm1(x)
def... |
5d607e53779ee75d9a03b7c88d3545a5b65b743322c0d34d25bb50c4806eb5c5 | Python | 33,300 | 756 | # -*- coding: utf-8 -*-
from __future__ import print_function
import json, time, os, sys, glob
import shutil
import numpy as np
from collections.abc import Sequence
import math
PI = math.pi
import torch
import random
from torch import optim
from torch.utils.data import DataLoader
import torch.utils
import torch.utils.c... |
0ea7ec4554e94b738251b30782fb38c0d3cdcf49fc7f8efe18e28415685bee30 | Python | 33,339 | 855 | from equivariant_diffusion import utils
import numpy as np
import math
import torch
from egnn import models
from torch.nn import functional as F
from equivariant_diffusion import utils as diffusion_utils
# Defining some useful util functions.
def expm1(x: torch.Tensor) -> torch.Tensor:
return torch.expm1(x)
def... |
9c429b35478a540587ca748c4c23698762b2312a02147d0b0a44907c6c60e8b3 | Python | 33,379 | 934 | ####################################################################################
#
# 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... |
03949645bfe016c6b8b4c5f0e7b9f83b0210bd9560ce0c0f6e98bcea077e67f1 | Python | 33,395 | 934 | ####################################################################################
#
# 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... |
99b9b51894127ba95fc63645e4af7f4bc2206af59b50a72684caf524a29fe610 | Python | 33,409 | 698 | # -- coding: utf-8 --
# @Time : 2023/4/3 18:26
# @Author : Biao Zhang
# @Email : littlebiao@outlook.com
# @File : analysis_anatomical.py
# @Description: This file is used to ...
import pickle
import numpy as np
import scanpy as sc, anndata as ad
import scipy.sparse as sp
import pandas as pd
import sys
import matplotli... |
3e83fd0a91585559734fb0c7e7979f9d66b705483f6d3872a73bde1522c591dd | Python | 33,452 | 843 | """
This module provides utility functions related to training a VAMPnet model on
molecular dynamics simulation data as well as analyzing its results.
"""
import numpy as np
import h5py
import os
import pyemma as pe
pe.config.mute = True
import yaml
import itertools
import mdtraj as md
from os.path import join
from sc... |
0eb5bcc028939c772760aa764242f7a4cbdc776af07999b1fb6a9456afc26a5e | Python | 33,524 | 687 | import os
import gc
import argparse
import json
import random
import math
import random
from functools import reduce
import numpy as np
import pandas as pd
from scipy import sparse
from sklearn.model_selection import train_test_split, ShuffleSplit, StratifiedShuffleSplit, StratifiedKFold
from sklearn.metrics import acc... |
748ff4d9a1f59dad7067cd2a17be78302d6d30831ae2f991c1ca4ca8808cdc24 | Python | 33,547 | 752 | import numpy as np
from tqdm import tqdm
from pensa.features import *
from pensa.statesinfo import *
# -- Functions to calculate SSI statistics across paired ensembles --
def ssi_ensemble_analysis(features_a, features_b, all_data_a, all_data_b, torsions=None, pocket_occupancy=None, pbc=True,
... |
8e363bdd10971c0a58560f8ed159c45e818d61f707940318d0217d3e479661ea | Python | 33,554 | 702 | ####################################################################################
#
# 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... |
3278281c284e935a40004fae1b1f6a703298981d1a7057d8fefbb512e5dadbdb | Python | 33,580 | 804 | """unit tests for the summary-spreadsheet/cohort-spreadsheet pieces of
api/results_bundle.py - pure function tests, no FastAPI/mesh pipeline
needed, same style as test_craniometrics.py/test_metopic.py testing the
underlying math directly.
_report_pdf's own layout isn't covered here beyond the line-advance
arithmetic b... |
8ec9c1a861a8f6604e5f9caf9f812697c532040240513e9d09d21a139b29438d | Python | 33,677 | 916 | # This file is part of the markovmodel/deeptime repository.
# Copyright (C) 2017, 2018 Computational Molecular Biology Group,
# Freie Universitaet Berlin (GER)
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by... |
e6597765b0b75e82c1ea31ff5cb5786796f2ea13e6fd9fb3d7a74b63f8aa540e | Python | 33,697 | 924 | # This script is part of navis (http://www.github.com/navis-org/navis).
# Copyright (C) 2018 Philipp Schlegel
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of... |
f3b072e6a77ef9365f088346822d56947986b40f5147dcd6a270eff87fb9a4f0 | Python | 33,704 | 832 | """Pytorch script for training SE(3) protein diffusion.
To run:
> python experiments/train_se3_diffusion.py
Without Wandb,
> python experiments/train_se3_diffusion.py experiment.use_wandb=False
To modify config options with the command line,
> python experiments/train_se3_diffusion.py experiment.batch_size=32
""... |
423968497bfbb8bbcc866c775e732ae6b59e1e7560b888a2ca15f708484a64bb | Python | 33,741 | 607 | # 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... |
0a9d35b275a73fc6094c2a00a5eb0e6e6b2c914b70bea2ec323914bdeeb0a7b6 | Python | 33,763 | 841 | """Compat bridge: convert `AIMessageChunk` streams to protocol events.
The bridge trusts `AIMessageChunk.content_blocks` as the single
protocol view of any chunk. That property runs the three-tier lookup
(`output_version == "v1"` short-circuit, registered translator, or
best-effort parsing) and returns a `list[Conten... |
331468e71307fc0d0b48de9b9a2a28ed6b1404e1fd457304e7e72b0ed402bffb | Python | 33,797 | 754 | import torch
import math
import copy
from .activation import (
SmoothLeakyReLU,
check_activation_name,
get_activation,
has_scalars,
add_dropout,
prepare_activation_forward_param,
LinearSwiGLU,
LinearSquare,
SwiGLU
)
from .layer_norm import (
get_normalization_lay... |
c882f9d581df48d7a807b157ae779491c3d052f406c262ae72d48c1e64e4cd1d | Python | 33,833 | 756 | # 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... |
a67c336263c5f86e65dfaccbb24cd91ad523d75413ccd387b6c6e2a515c2c26a | Python | 33,872 | 917 | ####################################################################################
#
# 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... |
db8cbd88df80806fcd8f9cd881acbee12989f0d1efeba4ef05a1832d045bcffa | Python | 33,888 | 917 | ####################################################################################
#
# 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... |
1247b428ad4ac960ebce12e9b4118acd1791d821fecd8d5cfae399adb810fc11 | Python | 33,922 | 1,029 | from ChipseqReport import *
import xml.etree.ElementTree
import Glam2
def computeMastCurve(evalues):
'''compute a MAST curve.
see http://www.nature.com/nbt/journal/v26/n12/extref/nbt.1508-S1.pdf
returns a tuple of arrays (evalues, with_motifs, explained )
'''
if len(evalues) == 0:
rais... |
69014cf64b005d2b90541d208be454ba6eae70848b32a639e6586f26d7ef335a | Python | 33,927 | 951 | import concurrent.futures
import threading
import time
import unittest.mock
import uuid
from typing import Any
from uuid import UUID
import pytest
from langsmith import Client
from langsmith.run_trees import RunTree
from langsmith.utils import get_env_var, get_tracer_project
from langchain_core.messages import AIMess... |
0fb8458a894b6be16195d5d63709dde2a7824db026b100ce314d29c3d03d019c | Python | 33,946 | 856 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
This experiment was created using PsychoPy3 Experiment Builder (v2021.2.3),
on 8月 23, 2022, at 10:39
If you publish work using this script the most relevant publication is:
Peirce J, Gray JR, Simpson S, MacAskill M, Höchenberger R, Sogo H, Kastman E, Lindeløv J... |
b3ed4d2620134256690f5512fef47442a5227fdd81a0fb49da621e5acc728601 | Python | 34,020 | 722 | # -- coding: utf-8 --
# @Time : 2023/4/3 18:26
# @Author : Biao Zhang
# @Email : littlebiao@outlook.com
# @File : analysis_anatomical.py
# @Description: This file is used to ...
import pickle
import numpy as np
import scanpy as sc, anndata as ad
import scipy.sparse as sp
import pandas as pd
import sys
import matplotli... |
f992d0f20b87e9d68a96b5fd3850a033b75db169080bf26e40f65e7c767dce60 | Python | 34,036 | 1,088 | """
Tests for I/O functionality of the toolkit wrappers
"""
import pathlib
import sys
import tempfile
from io import BytesIO, StringIO
import numpy as np
import pytest
from numpy.testing import assert_allclose
from openff.toolkit import Quantity, unit
from openff.toolkit._tests import create_molecules
from openff.t... |
cf6824701fbe272151ae79e1c2aab3dfbb4a5cc620255204585a2b1ebb4aad88 | Python | 34,054 | 744 | """
This is a modified version of fourier_2d_time.py from https://github.com/zongyi-li/fourier_neural_operator
"""
import datetime
import os
import random
# os.environ["CUDA_VISIBLE_DEVICES"]="7" # TODO: for debugging
from models.FNO import FNO2d, FNO3d
from models.GFNO import GFNO2d, GFNO3d
from models.GFNO_steerable... |
3f2ada5ce08b3df341b05ec50bf37d876e8de727e3a70dadee7fcccea085bf40 | Python | 34,057 | 744 | """
This is a modified version of fourier_2d_time.py from https://github.com/zongyi-li/fourier_neural_operator
"""
import datetime
import os
import random
# os.environ["CUDA_VISIBLE_DEVICES"]="7" # TODO: for debugging
from models.FNO import FNO2d, FNO3d
from models.GFNO import GFNO2d, GFNO3d
#from models.GFNO_steerabl... |
c58861f6119304d73a22dce043bccdd4bffc7f45241823fdcb21a2f2f9a7a7fa | Python | 34,093 | 860 | import torch
from torch import nn
import torch.nn.functional as F
from copy import deepcopy
from torch.jit.annotations import List, Dict, Tuple
from torch import Tensor
import numpy as np
from typing import Iterable
from torchvision.ops import roi_align
from Unet import UNet
from MuTILs_Panoptic.configs.panoptic_model... |
9a84a6bc73888f490b407608dab2b14220a31f99d45be04ab9b55e3986830a85 | Python | 34,095 | 916 | # -*- coding: utf-8 -*-
# author: Felix Repp felix.repp@mpikg.mpg.de
# !/usr/bin/env python
"""@package tinaskel
%This module provides the tools to obtain a network structure from the skeletonized images.
A nice description of the skeletonization process can be found [here](http://www.inf.u-szeged.hu/~palagyi/skel/sk... |
64d0143887580389ca1a109150c5a0611739250a92ae7b5b3dd24219c5f1453e | Python | 34,152 | 721 | import numpy as np
import tensorflow as tf
from tensorflow.keras.utils import to_categorical
from scipy.signal import convolve2d
import matplotlib.pyplot as plt
import copy
import cv2
import gc
from load_save_helpers import find_matching_masks, list_imgs_and_sizes, get_image_list, load_image_list, distance_maker, prime... |
fbff851e8723e60d587a2817865d5beb43acc08c436b8fbbeeaed15e87b5a192 | Python | 34,234 | 734 | import numpy as np
from copy import deepcopy
import time
import pickle
import sys
import signal
sys.path.append("..")
import ClusterHelper
import GeneralHelper
import nest
class ClusteredNetworkBase:
"""
Creates an object with functions to create neuron populations,
stimulation devices and recording dev... |
8f705da359b1b09bfa0678cfd55ebb83ea9d0030ca2adbd2a9d737f7ca0207f4 | Python | 34,269 | 828 | """Load LangChain objects from JSON strings or objects.
## How it works
Each `Serializable` LangChain object has a unique identifier (its "class path"), which
is a list of strings representing the module path and class name. For example:
- `AIMessage` -> `["langchain_core", "messages", "ai", "AIMessage"]`
- `ChatPro... |
105beaadd07977b456ac911cda6a79f628fdb94afd598eaa4a329267a8214e77 | Python | 34,330 | 747 | import traceback
from pathlib import Path
import dask.array as da
import numpy as np
import seaborn as sns
import yaml
from matplotlib import gridspec, pyplot as plt
from shiny import App, reactive, render, ui
from astrocast import detection
from astrocast.preparation import Delta, IO
class Explorer:
def _... |
cce5ef357b3e516d6bca88c0c380a69d21d17f1f03dd1175202aed3b303da754 | Python | 34,334 | 1,066 | """===========================
Variant annotation pipeline
===========================
:Author: Andreas Heger & David Sims
:Release: $Id$
:Date: |today|
:Tags: Python
The Variants pipeline attempts to annotate variants in
a :term:`vcf` formatted file. It computes
1. The effects of SNPs on transcripts and genes
... |
f96890a99fc951de4bdd912af37863d054295b5b31af1e54026ac5da6d68f720 | Python | 34,397 | 949 | """Middleware that exposes a persistent shell tool to agents."""
from __future__ import annotations
import contextlib
import logging
import os
import queue
import signal
import subprocess
import tempfile
import threading
import time
import uuid
import weakref
from dataclasses import dataclass, field
from pathlib impo... |
023972873cbbdc44864b1ba0ecd62464cf2571cbefa07408163b2cb5f50c9ac0 | Python | 34,440 | 843 | # Author: Katiana Kontolati
# Last update: Sept. 12, 2022
# Important: Make sure to: $conda activate latent_deeponet before running this script!!
import keras
import numpy as np
import matplotlib.pyplot as plt
#from IPython import get_ipython
#get_ipython().run_line_magic('matplotlib', 'inline')
import tensorflow as t... |
1cc5dac50103c63e493d85f6ca1b71d60755eaa4438e1631805360594c418bb0 | Python | 34,550 | 1,003 | # This script is part of navis (http://www.github.com/navis-org/navis).
# Copyright (C) 2018 Philipp Schlegel
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of... |
20becca5a90c01958e6897ba739bd4357d04a590c44954a373fcf61242a7c742 | Python | 34,626 | 607 | import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.data import Subset, Dataset
import pandas as pd
import numpy as np
import random
import json, os
import h5py
import scipy
from scipy.sparse import csr_matrix
import pysam
from torch.utils.data.dataloader import DataLoader, Sampler
from tqdm... |
29e613b5764fcff61cf867003bc26e528a76089f9dcad47f2ac7f27b33ad265f | Python | 34,629 | 1,049 | """===========================
Pipeline IDR
===========================
Overview
========
This pipeline is a wrapper for the Irreproducibility Discovery Pipeline
outlined by Anshul Kundaje.
(see https://sites.google.com/site/anshulkundaje/projects/idr)
It is split into two stages and performs several basic steps:
F... |
25ca1192f79a59c07becdffc41ae6592a9b5f01fec22e0f1e527cd2f9d1d6d6f | Python | 34,641 | 820 | import logging
from typing import List, Literal, Tuple, Union
import numpy as np
import pandas as pd
import seaborn as sns
import torch
import torch.nn as nn
import torch.nn.functional as F
from matplotlib import pyplot as plt
from matplotlib.lines import Line2D
from torch.utils.data import DataLoader, Dataset
from a... |
c0c85c6f57a77da408674668f65da14908f505c24acb0bab5130fc8d8bafdbfd | Python | 34,663 | 925 | import argparse
import torch
from torch import nn
import numpy as np
from data import get_dataset
import pandas as pd
import pickle as pk
from pymatgen.io.jarvis import JarvisAtomsAdaptor
from pymatgen.core.lattice import Lattice
from pymatgen.core.structure import Structure
from jarvis.core.atoms import Atoms
from tor... |
b0be86ed7707608a724842851af440195609187f7ab22f829a0a83a8142e8c7d | Python | 34,741 | 926 | """Training and testing functionality for the de novo peptide sequencing
model."""
import glob
import logging
import os
import tempfile
import warnings
from pathlib import Path
from typing import Iterable, List, Optional, Sequence, Union
import lightning.pytorch as pl
import lightning.pytorch.loggers
import torch
fro... |
542ff02040a30ec0c87ce2f6449a927b2f637f6e81792209bcf5f00b521eb5bc | Python | 34,825 | 804 | ####################################################################################
#
# 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... |
30c4085699c83521d487081ac3592e412ce92275f493c41d15aaccde7e67af3c | Python | 34,826 | 804 | ####################################################################################
#
# 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... |
6ea731d4e27595871171624f4d43ea284224427b2901f0a27f050f89d7e56acc | Python | 34,863 | 644 | import numpy as np
import tensorflow as tf
from tensorflow.keras.layers import Lambda
from abc import abstractmethod
class Muscle:
"""Base class for `Muscle` objects. If a plant contains several muscles, this object will contain all of
those in a vectorized format, meaning for any given plant there will alway... |
2b4172352d78629b1a7f7d7f53950b6d4af9aef51322a89e3078e3c96d192cf1 | Python | 34,965 | 897 | # 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
#
# Unless required by applicable law or agr... |
55b19d8378a43d0b8664f270e98a04e7d54614e496511d7816b460a2d71e8352 | Python | 34,974 | 915 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from .activations import ACTIVATION_REGISTRY
# from .fourier import SpectralConv2d
from functools import partial
# Largely based on https://github.com/labmlai/an... |
cd37212ea3c532539b635b94e05e0926e5348ceb16cc982111ec0b9a3a42e2b5 | Python | 35,007 | 961 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import dash_bootstrap_components as dbc
import plotly.graph_objects as go
from dash import Dash, dcc, html
metric_options = [
"euclidean",
"cosine",
"manhattan",
"chebyshev",
"minkowski",
"canberra",
"braycurtis",
"haversine",
"mahalan... |
2688a9e4dbb5e51d7f5fb70271b21844dc64fe8fc4448382d1557b318d71cc1c | Python | 35,057 | 818 | import numpy as numx
import pydeep.base.numpyextension as numxExt
from pydeep.base.activationfunction import Sigmoid
import pydeep.misc.measuring as MEASURE
import pydeep.misc.visualization as VIS
import pydeep.misc.io as IO
from scipy.signal import convolve2d
import scipy.ndimage.interpolation as sci
from sklearn.line... |
f61a1af39957e3569018851c3ca359e4c1c5357003bfe453da5aa1e70a110d35 | Python | 35,115 | 967 | import torch
import torch.nn as nn
from h3xsemble.utils.rigid_utils import Rigid
from h3xsemble.utils.residue_constants import restype_atom14_to_rigid_group, chi_angles_mask
from h3xsemble.model.primitives import Linear
from h3xsemble.model.structure_module import (
InvariantPointAttention,
InvariantPointAtte... |
fbf42e5b37b34a3d327fe512dc84fcca3bb388d0d3667f92fe81bba6308c29dc | Python | 35,153 | 989 |
import os
os.environ["CUDA_VISIBLE_DEVICES"]="1"
import sys
sys.path.insert(0,"/examples")
from modulusDL.models.arch import (
CustomModuleArch,
FullyConnectedFlexiLayerSizeArch,
CaseIDtoFeatureArch,
CaseIDArch,
FixedFeatureArch,
MaxPoolArch,
MatrixMultiplicationArch,
SumMultiplication... |
6bd76d5022cc66276daacb1cc700cac22b1a0fda6596062f9e17badc1e6ad456 | Python | 35,175 | 855 | from __future__ import print_function
import json, sys, os, math, argparse, time
import multiprocessing as mp
from cytoolz.itertoolz import partition_all
import svtyper.version
from svtyper.parsers import Vcf, Variant, Sample, SamFragment, confidence_interval
from svtyper.utils import die, logit, prob_mapq, write_sam... |
a25cc34b41574e62e01bc09aa0d16cf36fe2d5150cd0be5bdf323a7305483965 | Python | 35,236 | 969 | #!/usr/bin/env python
"""
Generate poses for relative free energy calculations using fragment structures
"""
from openeye import oechem
import numpy as np
import logging
logging.basicConfig(level=logging.INFO)
def GetFragments(mol, minbonds, maxbonds):
from openeye import oegraphsim
frags = []
fptype = o... |
618f36dbd567bb5a91ffdaf0202407f8da1755cadba9e7bbd1d01bbe19b15171 | Python | 35,277 | 971 | # Rewritten to mirror aedann.py but using KANLinear instead of nn.Linear.
from typing import Any, Optional, Tuple, List
# try:
import torch
from torch import nn
from torch.autograd import Variable
import torch.nn.functional as F
from torch.autograd import Function
# TORCH_AVAILABLE = True
# except ImportError:
# T... |
a365e7f8658f5c94ec71ed571d81ca44a0c10bf9695ca82920c666a942e19038 | Python | 35,374 | 807 | import warnings
from collections import deque
from collections.abc import Callable, Generator, Hashable
from itertools import combinations, permutations
import networkx as nx
import numpy as np
import pandas as pd
from joblib import Parallel, delayed
from skbase.base import BaseObject
from sklearn.base import BaseEsti... |
fbc58be14c827945e05fb613d46ab61aa56ab1b725af19b6931b3e9f4fe414e2 | Python | 35,381 | 928 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from pdearena.modules.activations import ACTIVATION_REGISTRY
from .condition_utils import ConditionedBlock, fourier_embedding, zero_module
from .fourier_cond impo... |
ed8b93b35180a7d4d142d4cec4f1093cbc274067d0b8515a05d4305f9ef9375b | Python | 35,554 | 1,015 | import numpy as np
import os
from omegaconf import DictConfig
import torch
import torch.nn.functional as nn
from rfdiffusion.diffusion import get_beta_schedule
from scipy.spatial.transform import Rotation as scipy_R
from rfdiffusion.util import rigid_from_3_points
from rfdiffusion.util_module import ComputeAllAtomCoord... |
c14420a6f7626b275080d8e1b8bd5eb940096662d08b4df30d0a5daab4d64f06 | Python | 35,598 | 1,007 | ####################################################################################
#
# 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... |
1e1a7def7834be803dfbc989784c08982e04ad8b54280e6dfd2653c45f2b2bf4 | Python | 35,607 | 866 | # Author: Katiana Kontolati
# Last update: Sept. 12, 2022
# Important: Make sure to: $conda activate latent_deeponet before running this script!!
import keras
import numpy as np
import matplotlib.pyplot as plt
#from IPython import get_ipython
#get_ipython().run_line_magic('matplotlib', 'inline')
import tensorflow as t... |
11b296af85c7efb0b9b0ad54fed4de815180b376294457570ac8b6c65ff3d790 | Python | 35,633 | 674 | __author__ = 'dominic rufa'
"""
Application API for setting up perses relative free energy calculations on Folding@Home.
argv[1]: setup.yaml (argument for perses.app.setup_relative_calculation.getSetupOptions)
"""
import numpy as np
import os
import simtk.unit as unit
from simtk import openmm
import logging
import da... |
beeee42afc338d2180584c8325ad285b661def8dbe39747ef8c3096e80d4b0ac | Python | 35,652 | 675 | __author__ = 'dominic rufa'
"""
Application API for setting up perses relative free energy calculations on Folding@Home.
argv[1]: setup.yaml (argument for perses.app.setup_relative_calculation.getSetupOptions)
"""
import numpy as np
import os
import simtk.unit as unit
from simtk import openmm
import logging
import da... |
a8d75afbc5780bf974436a880d42c120b836b8c8368a6e8319c2185013aa73f5 | Python | 35,695 | 1,040 | #!/usr/bin/env python
# =============================================================================
# MODULE DOCSTRING
# =============================================================================
"""
General utility functions for the repo.
"""
# ================================================================... |
4cd5f21aec461cd8ebcba448345a6edfe49889387537cbe5add2ccd0b314106c | Python | 35,718 | 897 | import torch
from torch import nn
from torch.autograd import Variable
import torch.nn.functional as F
from torch.autograd import Function
from .utils.stochastic import GaussianSample
from .utils.distributions import log_normal_standard, log_normal_diag, log_gaussian
from .utils.utils import to_categorical
import pandas... |
0d21da3e3f3a6f24fcf3535e09965ba1f11dc863fddda3c3160aa09ba4547eb2 | Python | 35,726 | 961 | from einops import rearrange
from copy import deepcopy
from nnsegnext.utilities.nd_softmax import softmax_helper
from torch import nn
import torch
import numpy as np
from nnsegnext.network_architecture.initialization import InitWeights_He
from nnsegnext.network_architecture.neural_network import SegmentationNetwork
imp... |
26669c2abaebcd5c989a1ade1cb8b5ede0b265035b2b3e58da3dab220706f173 | Python | 35,730 | 961 | from einops import rearrange
from copy import deepcopy
from nnsegnext.utilities.nd_softmax import softmax_helper
from torch import nn
import torch
import numpy as np
from nnsegnext.network_architecture.initialization import InitWeights_He
from nnsegnext.network_architecture.neural_network import SegmentationNetwork
imp... |
3ccdaefaa29882767b0c41f13472e1960c05bd42a7fe895f0782be63e306c6f3 | Python | 35,764 | 957 | """Utilities for working with genome neighbors (complete genomes) from NCBI.
"""
from collections import defaultdict
import datetime
import gzip
import http.client
import logging
import random
import re
import socket
import tempfile
import time
import urllib.parse
import urllib.request
from xml.dom import minidom
from... |
d9f9c24b65e88e9898542f8d10f7bbf1f29c4cfb5d659876b2b93d30f94cbf26 | Python | 35,778 | 713 | import os
import argparse
import random
import numpy as np
import pandas as pd
from scipy import sparse
from sklearn.model_selection import train_test_split, ShuffleSplit, StratifiedShuffleSplit, StratifiedKFold
from sklearn.metrics import accuracy_score, f1_score, confusion_matrix, precision_recall_fscore_support, cla... |
d9d007379a82a463b046bd894ffb55edbaf6780bf276f1ac27767ccace2204e0 | Python | 35,831 | 863 | # Standard library imports
import os
import math
import itertools
from itertools import cycle
# Third-party imports
import torch
from bernn.utils.mlflow_compat import mlflow, MLFLOW_AVAILABLE
import sklearn
import numpy as np
try:
import tensorflow as tf
except ImportError: # TensorFlow is optional for lightweigh... |
b9ead987172cc14776a36d6429ad2a5464a8e4f65e5782f61a68741fc039f260 | Python | 35,904 | 1,101 | """Internal tracer to power the event stream API."""
from __future__ import annotations
import asyncio
import contextlib
import logging
from typing import (
TYPE_CHECKING,
Any,
TypedDict,
TypeVar,
cast,
)
from typing_extensions import NotRequired, override
from langchain_core.callbacks.base impo... |
83a04f32d6f64777d41e9ba9bdb81a2910bab098a067dac3dafbcfe4467f7851 | Python | 35,906 | 761 | # Modified from: PDEBench/pdebench/data_gen/data_gen_NLE/CompressibleFluid/CFD_multi_Hydra.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
<NAME OF THE PROGRAM THIS FILE BELONGS TO>
File: CFD_multi_Hydra.py
Authors: Makoto Takamoto (makoto.takamoto@neclab.eu)
NEC Laboratories Europe GmbH, Copyr... |
c0c8de0e75e86052b233acd342ec8c1e71f946414f429e19980c2f0b19a02344 | Python | 35,911 | 885 | # Author: Katiana Kontolati
# Last update: Sept. 12, 2022
# Important: Make sure to: $conda activate latent_deeponet before running this script!!
import keras
import numpy as np
import matplotlib.pyplot as plt
#from IPython import get_ipython
#get_ipython().run_line_magic('matplotlib', 'inline')
import tensorflow as t... |
d298927c803ca3fa7bb498b0263c266269c4a4abfe3f80c253d7edf894ebfcf3 | Python | 35,925 | 810 | __docformat__ = "restructuredtext en"
import mdp
from mdp import numx
import pydeep.rbm.model as MODEL
import pydeep.rbm.trainer as TRAINER
import pydeep.rbm.estimator as ESTIMATOR
class BinaryBinaryRBMNode(mdp.Node):
''' Implementation of a restricted Boltzmann machine with binary visible
and binary hi... |
a33cc372f1a478ca852e91440f8bd146f7f8715bb6051db6a9ed5a56ad8ac055 | Python | 36,144 | 887 | # 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 ... |
7d72307e1a3be6ab5ca379bbbc25daa390f22e8bf07dd0de94b91e9d74ebe144 | Python | 36,154 | 1,009 |
import os
os.environ["CUDA_VISIBLE_DEVICES"]="1"
import sys
sys.path.insert(0,"/examples")
from modulusDL.models.arch import (
CustomModuleArch,
FullyConnectedFlexiLayerSizeArch,
CaseIDtoFeatureArch,
CaseIDArch,
FixedFeatureArch,
MaxPoolArch,
MatrixMultiplicationArch,
SumMultiplication... |
ff097158cf234645ab02714fa2a8d9f5b165e6f315d677da9183fa4200f59c13 | Python | 36,156 | 1,025 | ####################################################################################
#
# 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... |
9929b15f6a82ecdb685f40924244c506dfb14a8071b34cc2de4d531809c9bdc5 | Python | 36,167 | 734 | # 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... |
d03f42a274f49c3c0d7ec4d3323db263ba3fbe4b7cdb4455bcdd94502aa04634 | Python | 36,246 | 527 | """ Class for evalutating datasets with different properties.
:Version:
2.0.0
:Date:
04.07.2018
:Author:
Jan Melchior
:Contact:
JanMelchior@gmx.de
:License:
Copyright (C) 2018 Jan Melchior
This program is free software: you can redistribute it ... |
7a555d10275d7dd8a7a1ca1dbe92219d6a950890013bbfdb2ed931f724a1a8fb | Python | 36,292 | 956 | import re
import copy
import importlib
import ml_collections as mlc
def set_inf(c, inf):
for k, v in c.items():
if isinstance(v, mlc.ConfigDict):
set_inf(v, inf)
elif k == "inf":
c[k] = inf
def enforce_config_constraints(config):
def string_to_setting(s):
path... |
76979c76173b55b00c41caec63c7e74891ccd92531ecae567c5d7a1839ee8d17 | Python | 36,337 | 715 | import os
import gc
import argparse
import json
import random
import math
import random
from functools import reduce
import numpy as np
import pandas as pd
from scipy import sparse
from sklearn.model_selection import train_test_split, ShuffleSplit, StratifiedShuffleSplit, StratifiedKFold
from sklearn.metrics import acc... |
ea3f51eb1c03b130f638ad4d637965c52d46876eace7f1743c72fe4ae55ba4fc | Python | 36,337 | 891 | from typing import List, Union
from collections import namedtuple
from pathlib import Path
from abc import ABC, abstractmethod
import numpy as np
import pandas as pd
import scipy.signal as signal
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
matplotlib.rc('animation'... |
1ee2cd5351f5fb0f9d0ac26e56f6aa1ec9baa4158d87d0c13c01a238e57736b9 | Python | 36,365 | 1,018 |
import os
os.environ["CUDA_VISIBLE_DEVICES"]="0"
import sys
sys.path.insert(0,"/examples")
from modulusDL.models.arch import (
CustomModuleArch,
FullyConnectedFlexiLayerSizeArch,
CaseIDtoFeatureArch,
CaseIDArch,
FixedFeatureArch,
MaxPoolArch,
MatrixMultiplicationArch,
SumMultiplication... |
3c56c7323ad63be82b7a8bbce42e0e26acb84031496d3424be00b238a67fc21a | Python | 36,429 | 721 | import os
import gc
import argparse
import json
import random
import math
import random
from functools import reduce
import numpy as np
import pandas as pd
from scipy import sparse
from sklearn.model_selection import train_test_split, ShuffleSplit, StratifiedShuffleSplit, StratifiedKFold
from sklearn.metrics import acc... |
cd05b118f079529360273dba4b52c955d0b31e22916fb82e40e7546c16bbf508 | Python | 36,438 | 993 |
import os
os.environ["CUDA_VISIBLE_DEVICES"]="1"
import sys
sys.path.insert(0,"/examples")
from modulusDL.models.arch import (
CustomModuleArch,
FullyConnectedFlexiLayerSizeArch,
CaseIDtoFeatureArch,
CaseIDArch,
FixedFeatureArch,
MaxPoolArch,
MatrixMultiplicationArch,
SumMultiplication... |
234482bee4ab833017d94be0f53bf4fff0672af413c682c83c1917267a787aa2 | Python | 36,445 | 1,001 | """Equations related to Navier Stokes Equations with coordinate transformation
"""
from sympy import Symbol, Function, Number
from sympy import exp , Matrix
import numpy as np
from modulus.eq.pde import PDE
from modulus.node import Node
from typing import Optional, Callable, List, Dict, Union, Tuple
from ... |
163ad169bd1a51828c2995ba43ccbcb5b0ff9d16bced079fa08a2367ef65788b | Python | 36,453 | 1,020 |
import os
os.environ["CUDA_VISIBLE_DEVICES"]="1"
import sys
sys.path.insert(0,"/examples")
from modulusDL.models.arch import (
CustomModuleArch,
FullyConnectedFlexiLayerSizeArch,
CaseIDtoFeatureArch,
CaseIDArch,
FixedFeatureArch,
MaxPoolArch,
MatrixMultiplicationArch,
SumMultiplication... |
e6912f2470b7765a06e30a5bc8e75abd45f8d4aac7d01365eba490fe94543705 | Python | 36,497 | 1,072 | """
Copyright (c) Facebook, 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.
"""
import ast
import collections
import copy
import importlib
import itertools
import json
import logging
import os
import sys
import time
from ... |
43981a064517b0b5ef14ea6b7ca3b39cfa659237cc202aab6b21d98320c4a6d7 | Python | 36,527 | 727 | import os
import gc
import argparse
import json
import random
import math
import random
from functools import reduce
import numpy as np
import pandas as pd
from scipy import sparse
from sklearn.model_selection import train_test_split, ShuffleSplit, StratifiedShuffleSplit, StratifiedKFold
from sklearn.metrics import acc... |
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