sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
ecbe4778d3c7a7f340b43363423b6685f304540c6d8aa0b554d3473267ccfb17 | Python | 5,427 | 123 | import torch
from torch_scatter import scatter
from torch_sparse import SparseTensor
from math import pi as PI
def xyz_to_d(edge_index, num_nodes, distance_vectors):
"""
Compute the diatance, angle, and torsion from geometric information.
Args:
pos: Geometric information for every node in the grap... |
bca2c85122d500f8a537ba3529f4c9aff147a8f43bc5cb69560aa5faa40726d1 | Python | 5,430 | 165 | 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
from pydeep.dbm.unit_layer import *
from pydeep.dbm.weight_layer import *
from pydeep.dbm.model im... |
f44d462cee75e1ff3a689aea02e707a8b36492192354ed0c5e6ff1c45da46393 | Python | 5,430 | 123 | import os
import sys
from time import time
import multiprocessing
import subprocess
from queue import Empty as qEmptyException
import traceback
import json
import warnings
import numpy as np
sys.path.insert(0, "../")
from preprocess_rhd.preprocess_rhd import preprocess_one_session
from utils_here import clear_folder
... |
9c6ae742f23f01b471d54a36d772c9afe007714432e0aa2d40c258cc5f781c10 | Python | 5,432 | 150 | ####################################################################################
#
# 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... |
211dbda1194f9511e8fded849657e41f36596b3ff2149bd109202ba1dc1d7eac | Python | 5,434 | 142 | import sys
import os
import numpy as np
import torch
import torch.utils.data as du
from torch.autograd import Variable
import torch.nn as nn
import torch.nn.functional as F
import util
from util import *
class DrugGene_network(nn.Module):
def __init__(self, term_size_map, term_direct_gene_map, graph, ngene, ndrug, s... |
158141fbbb252092c9c6476a0007f828b30ff969005232e1c169cc0a2d5edf10 | Python | 5,439 | 177 | #!/usr/bin/env python
# coding: utf-8
# In[12]:
import numpy as np
from numpy.random import randn
import pandas as pd
import math
from scipy import stats
import numpy as np
import pandas as pd
from pandas import Series,DataFrame
import pingouin as pg
import matplotlib as mpl
import matplotlib.pyplot as plt
impor... |
cf9c7dcdd265edcff52a7b388d5f753fd77f6f7f3a813eaf9f49ab4c0fa67eed | Python | 5,444 | 134 | import os
import torch
from torch.utils.data import DataLoader
from orbevo.datasets.pyg_dataset import TDDFTv2_pyg, collate_fn, keep_qm9_good_after_split
from torch.utils.data.distributed import DistributedSampler
import numpy as np
class DataModule:
def __init__(self, cfg, world_size, time_start=0, time_cond=1,... |
55ec8fb6624e28507c53a047e25d74874204e01cd39657a244d22bd83db15210 | Python | 5,445 | 155 | #!/usr/bin/env python
# coding: utf-8
# ## Calculate predictions for Wu combinatorial Library
# Ran this section on the group server
import numpy as np
import pandas as pd
from os.path import isfile, join, exists
from os import listdir, chdir
from tqdm import tqdm
from os.path import abspath
import sys
# for relat... |
74c3b2bb3937642f6aa00d957029a93df6b2fff914e76def5579f0bf81f90efa | Python | 5,445 | 176 | # from analysis.data_filter import load_seqs
import os
import shutil
import sys
import pickle as pkl
from tqdm import tqdm, trange
import argparse
import pickle
def check(names, target_folder):
processed = os.listdir(target_folder)
processed = [p[:-5] for p in processed]
rest_names = []
... |
8e96df5b312081b1beac21bbeffc2edb8eac790cb1ea5e6b14fa4ec2208b0e4b | Python | 5,446 | 149 | # Training procedure for CIFAR-100 using ResNet 110.
# ResNet model from https://github.com/BIGBALLON/cifar-10-cnn/blob/master/4_Residual_Network/ResNet_keras.py
import keras
import numpy as np
from keras.datasets import cifar100
from keras.preprocessing.image import ImageDataGenerator
from keras.layers.normalization ... |
2338a50bad04a92f4bfd316f048ec0ffdebf8b9f276808d64350bc165c5b5cf6 | Python | 5,448 | 163 | 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
#from DBM_centered_flexible import Binary_layer
#from DBM.unit_layer import *
#from DBM.weight_laye... |
5bf4bdc94bb3fbf021ca8e3cc09f2c183cd18d4bdffe0caee0733f5045cfc3c9 | Python | 5,450 | 149 | import numpy as np
import scipy as sp
import scipy.stats
import scipy.spatial
import scipy.spatial.distance
import pyemma
from pyemma.util.contexts import settings
import MDAnalysis as mda
import matplotlib.pyplot as plt
import os
from pensa.features import *
def kolmogorov_smirnov_analysis(features_a, features_b, a... |
8a4c4c66f380a509d0cd4146c24e049aec60fe880f667965e808b165722fcc5d | Python | 5,453 | 133 | from collections import defaultdict
import csv
import json
from logging import Logger
import os
from typing import Callable, Dict, List, Tuple
import numpy as np
import pandas as pd
from .run_training import run_training
from HMSA.args import TrainArgs
from HMSA.constants import TEST_SCORES_FILE_NAME, TRAIN_LOGGER_NA... |
222e34efdbf532a26bb1bc634b7b08cdd25a82d6f2e52a6a99fbfbd8662da413 | Python | 5,455 | 166 | """R^3 diffusion methods."""
import numpy as np
from scipy.special import gamma
import torch
class R3Diffuser:
"""VP-SDE diffuser class for translations."""
def __init__(self, r3_conf):
"""
Args:
min_b: starting value in variance schedule.
max_b: ending value in varian... |
d1f4a29a3dbdaf686f5381e02b29caec8cb4f6b7e5570b9b1f14503f8c6cd595 | Python | 5,458 | 149 | # Training procedure for CIFAR-10 using ResNet 110.
# ResNet model from https://github.com/BIGBALLON/cifar-10-cnn/blob/master/4_Residual_Network/ResNet_keras.py
import keras
import numpy as np
from keras.datasets import cifar10
from keras.preprocessing.image import ImageDataGenerator
from keras.layers.normalization im... |
8e5a74324ee5fa74b81c8d7860fcbec58aba9d534089c5a75fbf72ead93f0fe9 | Python | 5,459 | 147 | import os
import torch
from torch.autograd import Variable
import re
from collections import Counter
import pickle
"""
Note: The meaning of batch_size in PTB is different from that in MNIST example. In MNIST,
batch_size is the # of sample data that is considered in each iteration; in PTB, however,
it is the number of... |
1d20f4aabd3167037dba2d8794fca81c15b9581d68ea11c6ff63e94de2a64376 | Python | 5,466 | 146 | # Copyright (c) 2023 Shihao Ma, Haotian Cui, WangLab @ U of T
# This source code is modified from https://github.com/yuyangw/MolCLR
# under MIT License. The original license is included below:
# ========================================================================
# MIT License
# Copyright (c) 2021 Yuyang Wang
#... |
31b7e13198026f6e9cca4e522e04a13e40357288544a30c3a9eefd1541e85017 | Python | 5,467 | 127 | '''
preprocess rhd files into mda files;
called from <repo_dir>/main_runnables/preprop_and_sort.py
8/31/2022 jz103
'''
import os
import gc
import warnings
from copy import deepcopy
from time import time
import numpy as np
# import pandas as pd
# from scipy.io import loadmat, savemat
from .load_intan_rhd_format impor... |
b18ab0b9d4c6e531f1b5dfbd6f7ecece3429dc890dc4ca18d643f1a73a2daa7a | Python | 5,467 | 158 | import Bio.SeqIO as sio
import tensorflow as tf
import numpy as np
from sklearn.preprocessing import LabelBinarizer
from tensorflow.keras.utils import to_categorical
import random
import os
os.environ['CUDA_VISIBLE_DEVICES'] = '0'
import tqdm
#load model
filterm = tf.keras.models.load_model(os.path.join(os.path.dirnam... |
aa790ab1298675032d40522da6efdef29f8b35308b3cace98b85b2780fb7a995 | Python | 5,470 | 146 | '''
@author: Xu Yan
@file: ModelNet.py
@time: 2021/3/19 15:51
'''
import os
import numpy as np
import warnings
import pickle
from tqdm import tqdm
from torch.utils.data import Dataset
warnings.filterwarnings('ignore')
def pc_normalize(pc):
centroid = np.mean(pc, axis=0)
pc = pc - centroid
m = np.max(np.... |
12c9de10ee719d77ae42bb051b2bd42f8283b8b3b3c26a07080d749e38c7525d | Python | 5,471 | 156 | ####################################################################################
#
# 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... |
778764f5c6429d388427c7447d0e99009a72818646f626916104e3e4256f743b | Python | 5,471 | 159 | """
SynergyNet
chemical hypergraph
dose hypergraph
"""
import numpy as np
import math
import torch
from torch import nn
import torch.nn.functional as F
from torch.nn.parameter import Parameter
import HyperGAT_Model as srcHGATmdl
class DrugCombHypergraph(nn.Module):
def __init__(self, in_chemical_n,
... |
c6ffe5fc22b1754b3f81e825c194a8954b9965a7c246a683a0bb9a55e32d46b1 | Python | 5,471 | 159 | # coding=utf-8
import os
import sys
sys.path.append('/projectnb/ivc-ml/dlteif/transferlearning/codebase')
sys.path.append('/projectnb/ivc-ml/dlteif/transferlearning/codebase/DeepDG/alg')
import time
import numpy as np
import argparse
from tqdm import tqdm
import torch.distributed as dist
import alg
from alg.opt impor... |
8b5ef9cf613faa17ac7e3ec41ae7899d6475a915d810738b9ac30d2b03519d2f | Python | 5,475 | 165 | import tensorflow as tf
import tensorflow_datasets as tfds
import jax.numpy as jnp
import jax.random as jrng
from clu.preprocess_spec import PreprocessFn
from dataclasses import dataclass
from typing import Tuple, Sequence
from projectlib.utils import maybe
@dataclass
class ToFloat:
name: str = "image"
def _... |
4e1fa1da2c11d3229894908cee30b0d15187c52c4399c49c5996587f43ad4452 | Python | 5,476 | 166 | """Custom **exceptions** for LangChain."""
from enum import Enum
from typing import Any
class LangChainException(Exception): # noqa: N818
"""General LangChain exception."""
class TracerException(LangChainException):
"""Base class for exceptions in tracers module."""
class OutputParserException(ValueErro... |
85c077bb59782f9024745bdddeed6f6f1969ce2f006c8347ec04d9d53c47b08d | Python | 5,479 | 138 | import os
# this stops jax from stealing all the memory
os.environ["XLA_PYTHON_CLIENT_PREALLOCATE"]="false"
import jax
import jax.numpy as jnp
import jax.random as jrng
import tensorflow as tf
import optax
import seaborn as sns
import hydra
from omegaconf import DictConfig
from orbax.checkpoint import (CheckpointMana... |
2da25ec8ff2e648987cfdc78447253a41bef18a679d614e7b938f8cb3e058585 | Python | 5,482 | 151 | import numpy as np
import scipy as sp
import scipy.stats
import mdshare
import pyemma
from pyemma.util.contexts import settings
import MDAnalysis as mda
import matplotlib.pyplot as plt
from pensa.clusters import obtain_clusters, obtain_combined_clusters
def wss_over_number_of_clusters(data, alg... |
98659e858b647b5449a2746fd663190359bb80ef651ea1bdec801b1343e23b1e | Python | 5,483 | 105 | import gym
import random
from gym import spaces
import numpy as np
import logging
from random import sample, uniform
from math import ceil
from Environments.DSSdirect_123bus_loadandswitching.DSS_Initialize import *
from Environments.DSSdirect_123bus_loadandswitching.state_action_reward import *
from gym.utils ... |
09a88a7e3013c808805398af260925681e11c7a21edcb6694611109d9addca14 | Python | 5,486 | 189 | #!/usr/bin/env
"""
# Author: Kai Cao
# Modified from RAE
"""
import torch
from torch.distributions import Normal, kl_divergence
__all__ = ['kl_div', 'distance_matrix', 'distance_gmm', 'unbalanced_ot']
def kl_div(mu, var, weight=None):
loss = kl_divergence(Normal(mu, var.sqrt()), Normal(torch.zeros_like(mu),torc... |
3b08b3a4bc5e6b6fbeb0dc311e666472321401f435b555f46ae8673fd3479284 | Python | 5,486 | 189 | #!/usr/bin/env python3
"""
Use a new key to reorder label numbers in label volumes.
Usage
----
remap_labels.py -ok <Old Key> -nk <New Key> <Label Volumes> ...
remap_labels.py -h
Example
----
>>> remap_labels.py -ok old.txt -nk new.txt labels1.nii.gz labels2.nii.gz
Authors
----
Mike Tyszka, Caltech, Division of Human... |
a1bfe79b085c296917aac4005c79dd654d8c63049140159b9f80a0a75bc511ef | Python | 5,486 | 152 | # coding=utf-8
"""Contains all visualization utilities."""
import torch
from torch.nn import ReLU, SELU, ModuleList
import logging
logger = logging.getLogger(__name__)
def get_notable_indices(feature_importances, top_k=5):
"""
Return dict of top k and bottom k features useful from matrix.
Parameters:
... |
c96079c77a12f9b5642078b7d6a1caeb07f1bb45628687101ee187d44a63f708 | Python | 5,486 | 120 | """This module contains various functions for plotting data from `MotorNet` training and simulation sessions.
"""
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
def compute_limits(data, margin=0.1):
"""Computes the limits to use for plotting data, given the ran... |
119319c7696be33c284325e3ee3110c71d5b4e50d9e222980f504234de2ccc3f | Python | 5,491 | 175 | #!/usr/bin/env python3
"""
Create an ITK-SNAP label key from a subset of the Allen Brain Atlas human
ontology via the online API
Usage
----
allen2itksnap.py -k <ITK-SNAP label key file>
allen2itksnap.py -h
Example
----
>>> allen2itksnap.py -o Amy_BG_Labels.txt
Authors
----
Mike Tyszka, Caltech, Division of Humaninit... |
25e714929eb9ae6e3e7e7f9dcdc99cfbe04837ea0c379ef3af29ae2dcc87a46f | Python | 5,493 | 179 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# bindsnet documentation build configuration file, created by
# sphinx-quickstart on Tue May 1 21:54:09 2018.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# a... |
ab05515c83b680806645e90338f4f4cd6fd2aa1c1a9a5bf1298a766776218532 | Python | 5,494 | 150 | import numpy as np
import os
import torch
import torch.utils.data as data
import pymeshlab
from data.preprocess import find_neighbor
type_to_index_map = {
'night_stand': 0, 'range_hood': 1, 'plant': 2, 'chair': 3, 'tent': 4,
'curtain': 5, 'piano': 6, 'dresser': 7, 'desk': 8, 'bed': 9,
'sink': 10, 'laptop'... |
e6216702c28894d19591bc00214b1c731b496734c70a4a586700669bc418ca87 | Python | 5,494 | 186 | import pandas as pd
import numpy as np
from cgatReport.Tracker import SingleTableTrackerRows
from cgatReport.Tracker import SingleTableTrackerHistogram
from cgatReport.Tracker import *
from cgatReport.Utils import PARAMS as P
from IsoformReport import *
class imagesTracker(TrackerImages):
'''Convience Tracker ... |
f731a79ccc77517b16320a317d52979f1ff0a90d184695a20b9a43487d2ee606 | Python | 5,495 | 155 | from ChipseqReport import *
import Annotations
##########################################################################
##########################################################################
##########################################################################
# Looking at distance
########################... |
eef59499984d206466b86d86ba8ea02d7b18d55fc74ca50fde1b186313fbfec3 | Python | 5,496 | 104 | import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from FiguresFunctions.FiguresPattern import *
font = {'size' : 16}
matplotlib.rc('font', **font)
name = ['Symmetric LTD']
name_J = ['No Inhibition', 'Bilateral Inhibition', '2 -> 1', '1 -> 2']
def path_name(Apostpre,Aprepost,J_matrix,P,epsilon,h... |
56a2eb22dde9f58bfba0d7e142f85f94de70a15e46b95b44f8b98f04e4e473e7 | Python | 5,501 | 139 | # Copyright 2020 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... |
235466680400e48bde88c5b72b8f33b5115edaba105c370fb78f90432019535e | Python | 5,503 | 134 | #pylint: disable=E1101, E0401, E1102, W0621, W0221
import argparse
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
import time
from random import SystemRandom
import models
import utils
parser = argparse.ArgumentParser()
parser.add_argument('--niters', type=int, default=2000)
parser.... |
dfb31711d267ae0b2c478db60cb77c663f82541fecde293d971ec8190dd7882f | Python | 5,503 | 170 | import pathlib
import re
import numpy
import pytest
from openff.utilities import has_package, skip_if_missing
from openff.toolkit import Molecule, unit
from openff.toolkit._tests.create_molecules import (
create_acetaldehyde,
create_cis_1_2_dichloroethene,
create_cyclohexane,
create_ethanol,
creat... |
2736d92cb106e736c9684178fab5429fd683ef98987d4cbbd5748f413fd74df2 | Python | 5,506 | 141 | """Compatibility wrapper for Ax optimization APIs.
Provides an `optimize` function with the historical managed_loop signature,
implemented on top of `ax.api.client.Client`.
"""
from __future__ import annotations
from typing import Any, Callable
try:
from ax.api.client import Client
from ax.api.configs impor... |
2effb9a299d0e59957e2adf9812b7ad36f2a0ea0906073cda22809bf32a10cd3 | Python | 5,507 | 158 | """
recommend_frames.py: search and determine optimal reference frames to annotate for ZephIR.
Determine median frames to recommend as reference frames via k-medoids clustering
based on thumbnail distances (see build_pdists). Clustering is done iteratively,
such that one cluster is determined at a time. n_iter > 0 wil... |
471dfd818eac9882c7dacec35b5bed57050374d9a8a7df974c6234611e8e0fae | Python | 5,508 | 197 | import gzip
import io
from skbase.base import BaseObject
from skbase.lookup import all_objects
from pgmpy.base import DAG
from pgmpy.readwrite import BIFReader
from pgmpy.utils.hf_hub import read_hf_file
class BaseExampleModel(BaseObject):
"""
Base class for all models in pgmpy.
Inherits from `skbase.b... |
7f73dc236b0a6219d7178ec7f83a4f1c9705f399febf1d96b7f4d83cca843fe1 | Python | 5,511 | 188 | from __future__ import annotations
import logging
from copy import deepcopy
from pathlib import Path
from typing import List
import numpy as np
from omegaconf import DictConfig, OmegaConf
from libs.common.metrics import Metrics
from libs.common.position import Position, Position2D, Position3D
from libs.common.weight... |
326639e646361d84bd6e4423ce4abda925b8e60875e480cb4333864149ece324 | Python | 5,514 | 177 | """Image prompt template for a multimodal model."""
from typing import Any, Literal, cast
from pydantic import Field
from langchain_core.prompt_values import ImagePromptValue, ImageURL, PromptValue
from langchain_core.prompts.base import BasePromptTemplate
from langchain_core.prompts.string import (
DEFAULT_FORM... |
7d98b5c742338f17d5bdfa9098b72e7c5301fd3de12d4a3a462388502969089d | Python | 5,530 | 142 | """unit tests for src/craniumpy_core/facial_cohort_link.py and
facial_measurements_io.py - pure function tests, no FastAPI needed, same
style as test_cohort.py. router-level plumbing (the /facial-measurements/
load endpoint) is covered separately in test_facial_api.py."""
from __future__ import annotations
import io
... |
bb76bcb29abf224483e47fa85837d98b34e5c9d7abb4bca99dd6fbdf06e38cfb | Python | 5,530 | 135 | import os
import glob
import numpy as np
import matplotlib.pyplot as plt
from utils.constants import ALL_MODELS
from scipy.stats import iqr, linregress
from paths import TRAINING_DATA_PATH, TEST_DATA_PATH
from utils.distribution_distance import compute_jsd, compute_kld
def compile_distance_measures(data_path):
ou... |
781e79956dd1c176e55dfa008a2d3f1a683fb8fea5cdc38d6c1edf6b30a60536 | Python | 5,537 | 193 | import tempfile
import time
from pathlib import Path
import matplotlib
import numpy as np
import pytest
from matplotlib import pyplot as plt
from scipy.cluster.hierarchy import linkage
from astrocast.autoencoders import CNN_Autoencoder
from astrocast.helper import DummyGenerator
from astrocast.reduction import Featur... |
ca4e8425eee134c6824aeff155cdf9fc0da2b5d63927b91a7598f0bf71cb3462 | Python | 5,537 | 195 | from ChipseqReport import *
# for trackers_derived_sets and trackers_master
if not os.path.exists("conf.py"):
raise IOError("could not find conf.py")
exec(compile(open("conf.py").read(), "conf.py", 'exec'))
class SNPSlicer(ChipseqReport.DefaultTracker):
def getSlices(self, subset=None):
return self... |
e24e8a44996bce12d10933db47c2704b3577edfdb6c811ff7a22b44c426e8cd3 | Python | 5,539 | 193 | import numpy as np
import tensorflow as tf
from tensorflow.keras import Model
from tensorflow.keras.layers import Activation, Add, Dense, Input, \
LayerNormalization, Subtract
from explainability import LRP
# def test_non_sequential_model():
# i1 = Input((5,))
# d1 = Dens... |
9408b23be9c18bf4e8164f751560959e1887572fa27e95e7e5e4ed04c06ec854 | Python | 5,540 | 156 | from neuron import h
from bmtk.simulator.bionet.io_tools import io
from bmtk.simulator.bionet.default_setters.cell_models import fix_axon_peri, fix_axon_allactive, \
set_params_allactive, fix_axon_perisomatic_directed,get_axon_direction
import numpy as np
def set_params_allactive_AIS_seg(hobj, para... |
e2788cce1fad7997b99749f7291a8a8a93322c9123fd04cd526864f4b6cf431b | Python | 5,540 | 124 | import numpy as numx
import pydeep.base.numpyextension as numxExt
class DBM_model(object):
def __init__(self, layers):
''' This function initializes the weight layer.
:Parameters:
model: Model, basically a list of layers
-type: Weight_layer ... |
d3b074a20e0b8d38333d6b6cf7d65a37c0341d5879551161075b903fabc214cd | Python | 5,542 | 195 | """**Tools** are classes that an Agent uses to interact with the world.
Each tool has a **description**. Agent uses the description to choose the right
tool for the job.
"""
import warnings
from typing import Any
from langchain_core._api import LangChainDeprecationWarning
from langchain_core.tools import (
BaseT... |
57211219759d9ed02806bd1dc111bd457bd8cb5239c4af8809df99ea86322555 | Python | 5,543 | 173 | # -*- coding: utf-8 -*-
"""
Created on Mon Jan 16 11:04:35 2023
@author: dell
"""
import tensorflow as tf
from tensorflow.keras.models import Model
import tensorflow.keras.layers as klayers
import tensorflow.keras.models as kmodels
import tensorflow.keras.backend as kbackend
from tensorflow.keras.layers... |
8f4a5951844201364e5d7d90d8b4cc11d285c17361e72adb1d23c320c0c43515 | Python | 5,548 | 154 | ####################################################################################
#
# 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... |
a5ed9dc172b0e0f993fb029f9b246904ae4020f1c3f5947685661c0f36cd45be | Python | 5,548 | 155 | from enum import Enum
from typing import Any
from langchain_core.callbacks import (
AsyncCallbackManagerForRetrieverRun,
CallbackManagerForRetrieverRun,
)
from langchain_core.documents import Document
from langchain_core.retrievers import BaseRetriever
from langchain_core.stores import BaseStore, ByteStore
fro... |
027a000e62347614e73fe516b52bb1f156ade0d6dca2735c850b327ec61b0758 | Python | 5,549 | 157 | ####################################################################################
#
# 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... |
a82f4636fcb807d1aac80a214454dc757477a4c8123ee58d46e2bb5c79073a07 | Python | 5,549 | 143 | from typing import Union
import matplotlib.pyplot as plt
import networkx as nx
import numpy as np
import pandas as pd
from . import stats
def read_csv(filename: str) -> dict:
raw_results = {"Experimental": {}, "Calculated": []}
expt_block = False
calc_block = False
with open(filename, "r") as f:
... |
200b731def0e55dd3f87d1cd283d3e14248ac1fa9163422b45ef5dbe64b1033b | Python | 5,550 | 119 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Main program running KINNTREX
This program accepts three inputs
input:
Param_fName: parameter file name
Save_Path: The path in which the program saves the out put information
Sample_Name: Uses the sample name for picking the parameters that are relevant to... |
e7d493431db9dfdcd8014db4b36ff4b47c5a55afa2965155c32a920dbb8fb94b | Python | 5,553 | 157 | # Python plugin that supports loading batch of images in parallel
import cv2
import numpy
import threading
import os
import struct
import concurrent.futures
from concurrent.futures import ThreadPoolExecutor, wait
_imread_executor_pool = ThreadPoolExecutor(max_workers=16)
class UnknownImageFormat(Exception):
pass
... |
4085c06010a67368b08bd73feeb40b1977e38f5b80183a452e9d48320068ac27 | Python | 5,555 | 134 | import torch
import torch.nn as nn
from egnn.egnn_new import EGNN, GNN
from equivariant_diffusion.utils import remove_mean, remove_mean_with_mask
import numpy as np
class EGNN_dynamics_QM9(nn.Module):
def __init__(self, in_node_nf, context_node_nf,
n_dims, hidden_nf=64, device='cpu',
... |
489312ace37e6558c141c3eb6d58b9060dba115aefe66c3f95baf7629b276f6d | Python | 5,557 | 156 | from __future__ import annotations
from typing import Annotated, Any, TypeVar
from langchain_core.exceptions import OutputParserException
from langchain_core.output_parsers import BaseOutputParser, StrOutputParser
from langchain_core.prompts import BasePromptTemplate
from langchain_core.runnables import Runnable, Run... |
aac790af5f8677c30ecfc680f19f2352cf6686eac884f77af2010de0cf816a96 | Python | 5,557 | 166 | '''utilites for generating tf.data.Dataset pipelines from tfrecords
generated, e.g. by .tfrec_utils
'''
from glob import glob
from math import ceil
import tensorflow as tf
from .tfrec_utils import count_samples_in_records
def random_patch(patch_size):
'''constructs a patch sampling function.
'''
def _c... |
9dc70f72e04e286eae6f95a83885ee55de4a2afcc06bf50348492ed579f3b329 | Python | 5,559 | 137 | import torch
import numpy as np
from ._base import register_transform, _get_CB_positions
from rde.utils.protein.dihedral_chi import CHI_PI_PERIODIC_LIST
from rde.utils.transforms.noise import transform_15to37, get_dihedral
@register_transform('corrupt_chi_angle')
class CorruptChiAngle(object):
def __init__(self... |
53f9c8abae1e38c62298e73cddb2d04338730f276d6116e36ace894d7f2f9e38 | Python | 5,560 | 167 | import torch
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams['savefig.format'] = 'pdf'
plt.rcParams['savefig.transparent'] = True
plt.rcParams['savefig.bbox'] = 'tight'
plt.rcParams['savefig.directory'] = '~'
from data import generate_recog_data
from net_utils import load_from_file
from plo... |
1985d3a523c7541106972b2e261deced0a262197ac1063b8642c91b9192a6fbc | Python | 5,561 | 195 | '''submit.py - run a collection of qsub scripts on the cluster
===========================================================
Purpose
-------
This script will submit a collection of qsub scripts on the cluster.
The script will only submit those jobs for which a result is not
present.
Usage
-----
For example::
pyt... |
0f3479d0ad9204d95eebc4e1f630cf87a2fcd575f6067f18e74d8780e7a76593 | Python | 5,562 | 177 | import torch
import torchvision
from torch.autograd import Variable
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import Dataset, DataLoader
from torchvision import transforms, utils
import torch.optim as optim
import torchvision.transforms as standard_transforms
import numpy as np
impor... |
5b7e1f79a83649d7fb32ca511910442f16f44773c037ea0dd6750b6829638a9a | Python | 5,562 | 160 | import os
import functools
import pickle
import multiprocessing as mp
import glob
import numpy as np
import mdtraj as md
import torch
import click
class ImproperlyConfigured(Exception):
'''The given configuration is incomplete or otherwise not usable.'''
pass
#Give me ipath to trajectories, indices, path to... |
95bbc3aafa3117fa56e910e6218f13d79a45dc64fa1a99bbface97bbe4de83b4 | Python | 5,563 | 177 | from pathlib import Path
from unittest import SkipTest, TestCase
import numpy as np
import pytest
import torch
import chroma
from chroma.data import Protein
from chroma.layers.structure.backbone import impute_masked_X
from chroma.layers.structure.mvn import (
BackboneMVNGlobular,
BackboneMVNResidueGas,
Co... |
9cae892e7251ea5cd614c6b0f1d716c0b4206816ed3d2bd4cba1a20378291e3a | Python | 5,565 | 157 | import numpy as np
from collections import namedtuple
from numpy import array, float32
from src.PID import discretize
def get_FF_activations(df):
"""
"""
transition = namedtuple('transition', ('observation', 'activation', 'reward'))
configuration = namedtuple('configuration', ('episode', 'buffer', 'su... |
02b6656dedd29b01217f5aba026f6d3b2c0515cfccdb2873d40f69572e3daa6f | Python | 5,568 | 173 | """
Train/test split for deepsignal extract output; additionally sample train/validation datasets.
"""
import multiprocessing as mp
import sys
import pandas as pd
sys.path.append('..')
from utils.constants.final_analysis import NUM_FOLDS
from utils.constants.final_analysis import DS_EXTRACT_COLS
def split_sample_e... |
4d1b294bb7e699e2c0b481a358254aa042f51394996048196b5f9f3953fda9ee | Python | 5,570 | 154 | # -*- coding: utf-8 -*-
"""
Created on Wed Feb 20 19:24:58 2019
@author: Vinícius Rezende Carvalho
"""
import numpy as np
def VMD(f, alpha, tau, K, DC, init, tol):
"""
u,u_hat,omega = VMD(f, alpha, tau, K, DC, init, tol)
Variational mode decomposition
Python implementation by Vinícius Rez... |
dd53e2c4d81e520f0b0499bc00e564d3407de4d08e2fde547bb0a4fabd5d88bf | Python | 5,571 | 147 | import pandas as pd
import numpy as np
import cv2
import torch
from torchvision import transforms
from torchvision.utils import save_image
from torch.utils.data import DataLoader,Dataset
from joblib import Parallel,delayed
from tqdm import tqdm
import matplotlib.pyplot as plt
from engine import utils
from constants im... |
ae16bdb5700cad4eed9c5c8402a580c17b623d6fab40379038eb0e37cb80a995 | Python | 5,575 | 181 | """Evaluators for parsing strings."""
import json
import logging
from collections.abc import Callable
from operator import eq
from typing import Any, cast
from langchain_core.utils.json import parse_json_markdown
from typing_extensions import override
from langchain_classic.evaluation.schema import StringEvaluator
... |
121ab1857229e71006a98c25c9f8115282a969c94d2c2354f0c039bbfbd9b46f | Python | 5,579 | 161 | import json
import pytest
from langchain_core.load import load, loads
from langchain_core.prompts import PromptTemplate
from langchain_core.prompts.dict import DictPromptTemplate
def test__dict_message_prompt_template_fstring() -> None:
template = {
"type": "text",
"text": "{text1}",
"ca... |
9a1ea59baafab6b108a13c81767169ed958da0966eff99d1a65eddaf6dfc3684 | Python | 5,581 | 181 | from collections.abc import AsyncIterator, Callable, Iterator, Sequence
from typing import (
Any,
TypeVar,
)
from langchain_core.stores import BaseStore
K = TypeVar("K")
V = TypeVar("V")
class EncoderBackedStore(BaseStore[K, V]):
"""Wraps a store with key and value encoders/decoders.
Examples that ... |
27fa855c0ffe46f3e8c8cd99436efd452078cda38c191ae375c09089d65e92b7 | Python | 5,588 | 107 | import numpy as np
import pyemma as pe
import h5py
import logging
logging.basicConfig(encoding='utf-8', level=logging.INFO)
from src.utils import update_yaml
from config.paths import TRAJECTORY_PATHS_TEMPLATE, TOPOLOGY_PATH_TEMPLATE, MINDIST_PATH_TEMPLATE, INFO_PATH_TEMPLATE, CLUSTER_AVG_PATH_TEMPLATE, MODEL_OUTPUTS_PA... |
3eece6848deb6ba05a1bf7c97614075259213f42029627026ba568e8e0df6e91 | Python | 5,589 | 152 | import numpy as np
from joblib import Parallel, delayed
from scipy.interpolate import interp1d
from scipy.special import erf, erfinv
from sklearn.base import BaseEstimator, TransformerMixin
from sklearn.utils.validation import FLOAT_DTYPES, check_array, check_is_fitted
class GaussRankScaler(BaseEstimator, Transformer... |
156d13df6b194e913423a353f240da692731b35ddeccf1b3a85076d2607875a0 | Python | 5,590 | 140 | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from rdkit import Chem
from torch_geometric.data import Data
# allowable node and edge features
from utils.geometric_graph import ATOM_ENCODER
allowable_features = {
'possible_atomic_num_list': list(range(1, 119)),
'possibl... |
229b573db0f8488cb36379081c6d6f850531948dd35bc2c10645b7a6b2dd1939 | Python | 5,593 | 91 | """General-purpose training script for image-to-image translation.
This script works for various models (with option '--model': e.g., pix2pix, cyclegan, colorization) and
different datasets (with option '--dataset_mode': e.g., aligned, unaligned, single, colorization).
You need to specify the dataset ('--dataroot'), e... |
a5e25fa152d88bcef8264eb2ac9d4c3775d3f719da062978d6a72463ecb98094 | Python | 5,604 | 176 | '''MobilenetV2 in PyTorch.
See the paper "MobileNetV2: Inverted Residuals and Linear Bottlenecks" for more details.
'''
import torch
import math
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
def conv_bn(inp, oup, stride):
return nn.Sequential(
nn.Conv3d(inp, ... |
b09fc3208f6fed56bb3b2e9b6aaf419c837098435843f8949bf13d293c1b4e8c | Python | 5,604 | 161 | import os
import pickle
import numpy as np
import torch
import utils
from dopp import FeedForwardCell
def train(params, model, model_target, *, manual_grad=False):
if not manual_grad:
optimizer = torch.optim.SGD(model.parameters(), lr=params["lr"])
res = {}
res["g0"] = torch.empty(params["tria... |
b39b41d36228442b31dd5c14304d65fc210659b4e1debee64fe2ceb885346ae9 | Python | 5,604 | 151 | #!/usr/bin/env python
import os
import sys
import json
import argparse
from Bio import pairwise2
from Bio.pairwise2 import format_alignment
from Bio.Align import substitution_matrices
from Bio.PDB import PDBParser
from Bio.SeqUtils import seq1
arg_parser = argparse.ArgumentParser()
arg_parser.add_argument("structure_p... |
b002e12fee48231d31be244963deb5be41aa872281d61916c1b8dda2489db8e8 | Python | 5,606 | 164 | # Rdkit import should be first, do not move it
try:
from rdkit import Chem
except ModuleNotFoundError:
pass
import utils
import argparse
from configs.datasets_config import qm9_with_h, qm9_without_h
from qm9 import dataset
from qm9.models import get_model
from equivariant_diffusion.utils import assert_correct... |
b76f25d00adcef0bae0c3386fa819e3a13056ebde53a7b2ec70a95be1bdb038b | Python | 5,606 | 162 | import os
import sys
import re
import types
import itertools
import numpy
import Annotations
from cgatReport.Tracker import *
from PeakcallingReport import *
##########################################################################
##########################################################################
##########... |
0c1f5ea0dd0a8981a662070153a9a12a5f855b3791c3e0e8f4977b28253c9b41 | Python | 5,607 | 139 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Nov 2 13:03:58 2021
@author: cxue2
"""
import os
os.environ['CUDA_VISIBLE_DEVICES'] = '3'
import pandas as pd
import numpy as np
import tqdm
from tsnecuda import TSNE
from cupyx.scipy.ndimage import zoom
import cupy
import sys
sys.path.append('../De... |
cb68b671704c24f68a4e93de108200423f16dabd6cb0dd6fe0779d59c072f7eb | Python | 5,612 | 150 | from pathlib import Path
from unittest import TestCase
import numpy as np
import torch
import torch.nn.functional as F
import chroma
from chroma.data import Protein
from chroma.layers.structure import geometry
class TestDistances(TestCase):
def test_sample(self):
distances = geometry.Distances()
... |
c2d7b40ca404819b627ab1ce95e341a139bf81bdab6c10a2709efa09a1f3bc72 | Python | 5,614 | 165 | '''ShuffleNet in PyTorch.
See the paper "ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices" for more details.
'''
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
def conv_bn(inp, oup, stride):
return nn.Sequential(
nn... |
0715119672055bec4d13c1fc0c7e93ef869dcefbfb207d09d62c7393aad26108 | Python | 5,617 | 169 | from collections.abc import Iterator
from langchain_core._api import deprecated
from langchain_core.language_models import BaseChatModel, BaseLanguageModel
from langchain_core.messages import HumanMessage, SystemMessage
from langchain_core.output_parsers.openai_functions import PydanticOutputFunctionsParser
from langc... |
b5652dd1913ccc31c7672bfdfbd899667371c52a7a42f65257db6da1981b7380 | Python | 5,618 | 157 | ####################################################################################
#
# 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... |
c8c1cffd9c0075a3866eb8c8c103bf4e519c6c9ee7050117513225ee752d6339 | Python | 5,618 | 116 | import warnings
import os
import numpy as np
import pandas as pd
from copy import copy
warnings.filterwarnings("ignore")
class Omicscope_Snapshot():
from .GeneralVisualization import PPInteractions
from .GeneralVisualization import bar_ident
from .GeneralVisualization import volcano
def __init__(se... |
3b1f65a8e7a0ca99ee5b5223e24c959f5b956125de8b40cdf02f668a80aa4ae1 | Python | 5,620 | 131 | from typing import Optional, Callable, Union
from torch_geometric.typing import OptTensor, PairOptTensor, PairTensor, Adj
import torch
from torch import Tensor
from torch.nn import Parameter
from torch_geometric.utils import remove_self_loops, add_self_loops
from torch_geometric.nn.conv import PPFConv
def get_angle(v... |
09de8be8a331fcf1e6b1418538e7d820edb48012ff6113746dcde9cc89a5af10 | Python | 5,623 | 93 | import matplotlib.pyplot as plt
from Simulator.Pattern import pattern_DMS
from Simulator.SimulatorPattern import simulatorPattern
from Articles.DMS_DLS.Code.FiguresDMS import *
from datetime import datetime
class simulatorPatternDMS(simulatorPattern):
def init_pattern(self):
self.reward_trace = np.zero... |
085ffd06d417da7b4dd100204e529385cfb173786ac5b4d23638914c5cbae4ec | Python | 5,625 | 137 | # 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... |
21db93d2707349f0631672d4894188fd934115fbd17114b995091c0b9350f334 | Python | 5,630 | 159 | import logging
import os
from typing import List
import Bio.PDB
import numpy as np
import torch
from scipy.spatial import distance_matrix
from src import constants
from src.constants import _3to1
from src.utils.cif2pdb import cif2pdb
from src.utils.secondary_structure import renum_pdb_file, \
calculate_ss, make_s... |
2c793b825305b92b15403326d3f4420d6314d059e1f6dc20bbafddb4b6bf3812 | Python | 5,632 | 157 | """Derivations of standard content blocks from Groq content."""
import json
import re
from typing import Any
from langchain_core.messages import AIMessage, AIMessageChunk
from langchain_core.messages import content as types
from langchain_core.messages.base import _extract_reasoning_from_additional_kwargs
def _popu... |
7e74ae5b4f5d4ab86d014d889b6abf6b7d4ac5ac858de9d9b4e2bd731a9e2200 | Python | 5,635 | 139 | import numpy as np
from sklearn.decomposition import PCA
import nltk
import csv, os, re
import h5py, json, pickle
import pkg_resources
from symspellpy import SymSpell, Verbosity
np.random.seed() # randomly initialize the seed
homedir = '' ### path of home directory
sym_spell = SymSpell(max_dictionary_edit_distance=2... |
2103d8e472b378d8d464507c117afd80f2df452e0e942bb97fa1b92b6f936024 | Python | 5,636 | 182 | import odl
import torch
from warnings import warn
from copy import deepcopy
from odl.contrib.torch import OperatorModule
from odl.tomo import fbp_op
from odl.operator.operator import OperatorRightScalarMult
from odl.operator.default_ops import ZeroOperator
from dliplib.reconstructors.base import BaseLearnedReconstru... |
5a798517d6abefa906e6fd005c9d7bc020fa66e31d270949d80df7b6079b3bd5 | Python | 5,637 | 123 | # 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... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.