sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
0f7fb61d25c40689dc81b79d05eacb32a9cd8d393c33283ee3fbe313d4478eca | Python | 6,469 | 157 | import torch
from e3nn import o3
def FirstOrder4NormActivation(act, features, R, irreps = None):
norms = act.norm(features)
if act._eps_squared > 0:
# See TFN for the original version of this approach:
# https://github.com/tensorfieldnetworks/tensorfieldnetworks/blob/master/tensorfieldnetw... |
60a764b8b1dc506a6b5a085924e5afc9cba807c09fbf3101be823a807051104c | Python | 6,469 | 181 | import warnings
from typing import Any
from typing import Callable
import ptrnets
import torch
from ptrnets.utils.mlayer import clip_model
from ptrnets.utils.mlayer import hook_model_module
from torch import nn
class Core2d(nn.Module):
def initialize(self, cuda: bool = False) -> None:
self.apply(self.ini... |
8e786a85eeffeb0eaf14fb750cad21ad6ea21e2b38a3b24d052d1d64491fb2ed | Python | 6,469 | 208 | # 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... |
a22624d7d40d3d207d91e92163441da5a778c867ed6ea85aa546cc9fdbeb2105 | Python | 6,469 | 198 | #!/usr/bin/env python
"""
Inference script.
To run with base.yaml as the config,
> python run_inference.py
To specify a different config,
> python run_inference.py --config-name symmetry
where symmetry can be the filename of any other config (without .yaml extension)
See https://hydra.cc/docs/advanced/hydra-comman... |
7f510cc3e4bfd81c478f62aaa52dc1a3458b7ab9b983ef7f1e8099caf8a848f0 | Python | 6,470 | 171 | # Author: Seyedeh Somayyeh Mousavi and Reza Sameni
# 2024-2025
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import gaussian_kde
from scipy.ndimage import gaussian_filter
import matplotlib.ticker as ticker
# =========================================================================================... |
f0e00cbbabf7d726b2e9605b96e3d9754d3323931b548b3fc2b00c96a0ed5ce7 | Python | 6,471 | 195 | #!/usr/bin/env python3
from typing import Optional
import pandas as pd
import argparse
import yaml
import pathlib
import matplotlib.pyplot as plt
import upsetplot
import tqdm
def get_upset_data_frame(data, reference, query):
sets = data.groupby(reference)[query].unique().map(set)
all_values = data[query].uni... |
1ee68ad7482bbbe37a0e415606f5bc358e954752afa531be2facbab7ecb37268 | Python | 6,476 | 177 | import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
from matplotlib.colors import hsv_to_rgb
import cv2
import moviepy.editor as mpy
import numpy as np
from nowcasting.helpers.gifmaker import save_gif
def flow_to_img(flow_dat, max_displacement=None):
"""Convert optical flow data to HSV images
... |
3d10c064e29ad64f8bb955d8b780766098a77cb35fa0876b68933571f16b43b5 | Python | 6,479 | 193 | # this script count the result based on detectron2 inference
#
import argparse
import os
import random
import time
import warnings
import pickle
import numpy as np
import math
import sys
import copy
import re
import pandas as pd
import json
import cv2
from shapely.geometry import Polygon
from detectron2.structures imp... |
6b5ae20a25166e25f2824bcb9f1204983ba29221d2c2ba26d0589b9001e7b663 | Python | 6,483 | 191 | ####################################################################################
#
# 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... |
92f7cc3c456807be782e83cd5916301e101f157967cfa9646d87897520f11961 | Python | 6,483 | 194 | # this script count the result based on detectron2 inference
#
import argparse
import os
import random
import time
import warnings
import pickle
import numpy as np
import math
import sys
import copy
import re
import pandas as pd
import json
import cv2
from shapely.geometry import Polygon
from detectron2.structures imp... |
aa276f7e64051cc4e73480a69946df10cfcdc20c2aebf95b8db296606487abd1 | Python | 6,483 | 186 | """
Test util functions
"""
__author__ = 'John D. Chodera'
import os
from perses.utils.openeye import smiles_to_oemol
from unittest import skipIf
import pytest
running_on_github_actions = os.environ.get('GITHUB_ACTIONS', None) == 'true'
# functions testing perses.utils.data
#@skipIf(running_on_github_actions, "Sk... |
b98f2d111171ce02a00aa707b1050950449211ef3b610030932e4a333e069c83 | Python | 6,484 | 191 | ####################################################################################
#
# 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... |
631193580df41672d467f6bff9592822af02c417adc4e6a7a45e9ae68924f91a | Python | 6,487 | 235 | from typing import Any
import pytest
from langchain_core.utils.function_calling import _rm_titles
output1 = {
"type": "object",
"properties": {
"people": {
"description": "List of info about people",
"type": "array",
"items": {
"description": "Infor... |
6de10805ddd023146ecea16ecde3b7205dea2d3d50f2f9f0a8f91dbedc88d0fe | Python | 6,488 | 169 | """**Retriever** class returns Documents given a text **query**.
It is more general than a vector store. A retriever does not need to be able to
store documents, only to return (or retrieve) it. Vector stores can be used as
the backbone of a retriever, but there are other types of retrievers as well.
"""
from typing ... |
a100636e883901c4071191ce4dd18688f7882824170e8eb92cbb6b16ae935b71 | Python | 6,489 | 187 | """
Utility classes and functions to create objects supporting callback registration.
"""
__all__ = [
"Callbackable",
"callback_method",
]
import functools
import inspect
from openff.toolkit.utils.exceptions import CallbackRegistrationError
def callback_method(func=None, events=()):
"""Decorator used... |
1d19bb137fe26fe2dd663eed48f6e3c9c2a35485fe4bc8eff97389832ecca0fd | Python | 6,492 | 195 | ### #################################################################################
#
# 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 deta... |
1aa3cbaf3a998241da02c9def3da32e022c8d196807bc67999f8763e6c3d88aa | Python | 6,494 | 197 | ####################################################################################
#
# 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... |
f5d8475fa0e4cfc5692eb41da8648ae250995b1a07dd18e60e29f354a02870b1 | Python | 6,494 | 203 | from typing import List, Optional, Tuple
import matplotlib.animation as animation
import matplotlib.pyplot as plt
import numpy as np
import torch
def plot_weights_movie(ws: np.ndarray, sample_every: int = 1) -> None:
# language=rst
"""
Create and plot movie of weights.
:param ws: Array of shape ``[n... |
f625c325452886cc69711f6456f8e5f6b2e4f47f017fe29f2f1a5ffc6d963acd | Python | 6,494 | 178 | import copy
from warnings import warn
import torch
import numpy as np
from torch.optim import Adam, SGD
from torch.nn import MSELoss, BCELoss
from odl.contrib.torch import OperatorModule
from dival import IterativeReconstructor
from dliplib.utils.losses import poisson_loss, tv_loss
from dliplib.utils.models import ... |
66f2f0f6ec0e917591ca2368e5f3798bf9262cbf9dc9b99b6aa60ccc678fb017 | Python | 6,495 | 197 | ####################################################################################
#
# 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... |
7559b0507fec6b2750ec0a4498f0fb2add338bee260a4c292483b11599a52705 | Python | 6,496 | 139 | """Publication-quality figures for DeepMapper evaluations.
matplotlib only (no seaborn). Every figure is saved as BOTH a 300-DPI PNG and a vector
PDF, with a consistent clean style. Legends are placed OUTSIDE the data area so they never
overlap bars. All functions take an output stem (no extension) and write ``<stem>.... |
9ca21849cf4e6b045ca4a0bf60f5db1e58a61ab02572e37107ec5915a6f33399 | Python | 6,497 | 201 | import numpy as np
import torch
from scipy.stats import multivariate_normal
def box_radial_dist(shape):
Z, Y, X = shape
z, y, x = np.meshgrid(np.linspace(-Z // 2, Z // 2, Z),
np.linspace(-Y // 2, Y // 2, Y),
np.linspace(-X // 2, X // 2, X),
... |
bbb5de28b2378727fc1bc7b72c419aacf1e7cebfbd1b42dc7aac5347893c9d16 | Python | 6,500 | 165 | """Tests for langchain_core.vectorstores.utils module."""
import math
import pytest
pytest.importorskip("numpy")
import numpy as np
import numpy.typing as npt
from langchain_core.vectorstores.utils import _cosine_similarity
class TestCosineSimilarity:
"""Tests for _cosine_similarity function."""
def test... |
076d85f2024865a567fa6f31eead2f6649dce1fe20c1481e9d465a7095da4867 | Python | 6,502 | 157 | """
This script is used to prep files for plotting with
eQTpLot for eQTL-GWAS colocalization plots.
It is modified from a jupyter-notebook Apua development.
Changes are for module plotting.
"""
import numpy as np
import pandas as pd
from pyhere import here
from functools import lru_cache
import subprocess, argparse, s... |
9cbfe7e28da6180c2fb80db0245d6d08be272b11aa0d68e508933ce4cdd408f6 | Python | 6,503 | 251 | from typing import Any, Optional, Union, Literal, Sequence, Tuple, Dict, List
import numpy as np
from ..utils import _eval_remote_instance
from ..client import CatmaidInstance
from enum import IntEnum
from dataclasses import dataclass, asdict
Dimension = Literal["x", "y", "z"]
class Orientation(IntEnum):
XY = 0
... |
3eb47d7be70c47a539e6b898d61d104e85c74519f434b5b0f9b3e42f93642f62 | Python | 6,505 | 179 | from typing import Any
from langchain_core._api import deprecated
from langchain_core.messages import BaseMessage, get_buffer_string
from langchain_core.utils import pre_init
from typing_extensions import override
from langchain_classic.base_memory import BaseMemory
from langchain_classic.memory.chat_memory import Ba... |
dc93f25ad4d15687e72324b18ad371db448d7b03246b40afe95593e3f5867123 | Python | 6,513 | 215 | """Helper class to draw a state graph into a PNG file."""
from itertools import groupby
from typing import Any, cast
from langchain_core.runnables.graph import Graph, LabelsDict
try:
import pygraphviz as pgv # type: ignore[import-not-found]
_HAS_PYGRAPHVIZ = True
except ImportError:
_HAS_PYGRAPHVIZ = F... |
5f8e855e76bb2cad6ee3d39963355abd7500fd99d50412045db6417554e03add | Python | 6,515 | 186 | from rdkit import Chem
def has_one_oxygen_and_sp3_carbons_in_ring(m, ring_elements):
'''has one oxygen and sp3 carbons in ring'''
cnt = 0
cflag = 1
hflag = 1
for i in range(len(ring_elements)):
idx = ring_elements[i]
atom = m.GetAtomWithIdx(idx)
atom_type = atom.GetSymbol(... |
1e48bcfa28bf144aadae6951fd9592b5045d472e9b9b7fecf0fbeea0443f7411 | Python | 6,517 | 196 | import functools
import pandas as pd
from torch.utils.data import DataLoader
import numpy as np
import pandas as pd
from sklearn.metrics import roc_auc_score
from sklearn.linear_model import LinearRegression
from tqdm.auto import tqdm
import torch
import os
import pickle
import random
from rde.utils.misc import inf_it... |
cca1739e3ff90d4b3ae3b6a030358b3870517ba1bbe03dcfda659cef8fc206bf | Python | 6,525 | 172 | import os
import matplotlib.pyplot as plt
plt.rc('savefig', format='pdf', bbox='tight')
plt.rc('legend', fontsize=8) # legend fontsize
import torch
from data import generate_recog_data
from plotting import plot_train_perf, plot_W, plot_B, plot_recog_generalization, maxabs
from networks import HebbNet
... |
19854478334b27b40ab624bca052db427070f7eb0ff54c355cd5ea4c72cf625b | Python | 6,529 | 175 | import math
from EPI_MRI.utils import *
class LeastSquaresCorrection:
"""
Given a field map, produces a corrected image.
This class provides functionality to correct distorted images using a field map.
The method is based on Least Squares Restoration.
Reference: https://fsl.fmrib.ox.ac.uk/fsl/fs... |
3a8d138d09af8b377de37af5546da98fe6870bb000e3032883c70e86e9616f81 | Python | 6,531 | 171 | """Test conversation chain and memory."""
import re
from typing import Any
import pytest
from langchain_core.callbacks import CallbackManagerForLLMRun
from langchain_core.language_models import LLM
from langchain_core.prompts.prompt import PromptTemplate
from typing_extensions import override
from langchain_classic.... |
b337842311fc35a6b3b3efe7bd4233637d1fcfc7e3f8c07ae5312b25c73380cf | Python | 6,533 | 190 | import numpy as np
from params_emt import *
from numba import jit_module
import matplotlib.pyplot as plt
def pos_hill(x, x0, n):
'''
positive hill function
'''
return ((x/x0)**n)/(1+(x/x0)**n)
def neg_hill(x, x0, n):
'''
negative hill function
'''
return 1./(1+(x/x0)**n)
def joint_hill(x1, x2, x01, x02, n1, ... |
f5837b670a5c5c1419d524bcfbfc508aa67855c46ea0001fcfd3340815b21e50 | Python | 6,534 | 165 | import os
import shutil
import subprocess
import tempfile
import mdtraj as md
import numpy as np
from diffnets.utils import get_fns
CURR_DIR = os.getcwd()
UP_DIR = CURR_DIR[:-len(CURR_DIR.split('/')[-1])]
CLI_DIR = UP_DIR + 'cli'
def test_preprocess_default_inds():
curr_dir = os.getcwd()
try:
td = tem... |
a2646e390e2b3c49a9cdc28cc35684564654fdd5be0de57844a12d6c96adf426 | Python | 6,537 | 189 | ########################################################################
# 2D diffusion on an infinite strip from line "point source".
# AIMS: to verify STEPS spatial-stochastic solver 'Tetexact' supports
# local initial conditions and calculates surface diffusion rates correctly.
# STEPS equivalent model: Stochas... |
f0076c0f23316ffd2b94627b0f5977c4d8931c4b93b28d0d72c66a5ff3808028 | Python | 6,538 | 259 | import click
import sys
import scaden
import rich
import rich.logging
import logging
import os
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
import tensorflow as tf
from scaden.train import training
from scaden.predict import prediction
from scaden.process import processing
from scaden.simulate import simulation
from scade... |
76d83fa099ed099a7ec1fec2e25c4b9b48a943fc147dabf9871aec17c0c4cb18 | Python | 6,539 | 217 | import torch
from models.cnn import cnn3d
from models import (cnn, C3DNet, resnet, ResNetV2, ResNeXt, ResNeXtV2, WideResNet, PreActResNet,
EfficientNet, DenseNet, ShuffleNet, ShuffleNetV2, SqueezeNet, MobileNet, MobileNetV2, vgg2)
# from opts import parse_opts
import argparse
def getDNN(cnn_name, m... |
f592cb2ca971719565e21d7b97764a25b7486b4c8f5bf311ef997cb994e27d5d | Python | 6,539 | 201 | ####################################################################################
#
# 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... |
1447bb3e7ba872246defd42fa43d11329711c54f46aaecf246fe56d93b3e9760 | Python | 6,541 | 260 | # -*- coding: utf-8 -*-
"""
Created on Thu Jul 30 21:13:03 2020
@author: nishe
"""
neuron_e_AD = '''
dv/dt = (1/C)*(-g_l*(v - v_l) + (-g_k)*(v - v_k) + I_inh + I_exi + I_extnl_spk + I_extnl_crt) : volt (unless refractory)
g_l : siemens
t_ref : second
I_inh = (-g_I)*(v - v_rev_I) : amp
I_exi = (-g_E - g_E_inter)*(v -... |
55dec3ff79fc97718b2b22a1317478ffbf6c27126e2f94937e974d264cde55c6 | Python | 6,544 | 162 | import rdkit
import rdkit.Chem as Chem
import numpy as np
'''
This module is a duplicate of mol_graph.py in this same directory. It adds additional atom features,
including some calculated electronic properties, which turn out to not actually help model performance
'''
# Extra atom features
import rdkit.Chem.rdMolDes... |
723fce7f35ace4fe85d8d9809ed56f9a9fdaab6dc0bef3cb31cc958ef1343915 | Python | 6,548 | 170 | #!/usr/bin/env python3
import logging
from os import path
from itertools import chain
from collections import Counter
from enrichm.databases import Databases
# Local
###############################################################################
class Writer:
'''
A collection of functions to write files in vari... |
8916875fa072546884e010bf35f93cfcb497023f40abbbd8e1497e6733ec9018 | Python | 6,549 | 147 | import tensorflow as tf
from rexgen_direct.core_wln_global.nn import linearND, linear
from rexgen_direct.core_wln_global.models import *
from rexgen_direct.core_wln_global.ioutils_direct import *
import math, sys, random
from collections import Counter
from optparse import OptionParser
from functools import partial
imp... |
9003b80f280cf0b94cb931fbd30f44ca48cece3cb80c9be5a3ceebf215dd7821 | Python | 6,549 | 156 | import numpy as np
from rdkit.Chem import AllChem
from rdkit.Chem import Descriptors
from rdkit.Chem import rdMolTransforms
#from rdkit.Chem import AllChem, Draw, Descriptors, rdMolTransforms
import rdkit.Chem as Chem
import rdkit.Chem.rdMolDescriptors as rdMolDescriptors
import rdkit.Chem.EState as EState
import rdkit... |
d2d2b697254f3e3f1b9fb18f8ae5b281b8be20e0c878aadfc003ff2f36dfdbe0 | Python | 6,551 | 43 | from langchain_core.prompts import PromptTemplate
template = """Given the following extracted parts of a long document and a question, create a final answer with references ("SOURCES").
If you don't know the answer, just say that you don't know. Don't try to make up an answer.
ALWAYS return a "SOURCES" part in your an... |
46a823a14c64a41d2213a7832829bcaa6fc7ac21ff0d5cf2da8b03b4d95df516 | Python | 6,556 | 204 | import pandas as pd
import pytest
from cwas.binomial_test import BinomialTest
import sys
import cwas.cli
import zarr
class BinomialTestMock(BinomialTest):
"""This class do not make outputs"""
def save_result(self):
pass
def update_env(self):
pass
@pytest.fixture(scope="module")
def cat_p... |
6bb76b61728f8f727779fa8621fe88afc09a6a95bdc7c0cf22a4d015700ecef2 | Python | 6,556 | 185 | # Source: https://github.com/choosehappy/PytorchDigitalPathology/blob/ ...
# master/segmentation_epistroma_unet/
# Adapted from https://discuss.pytorch.org/t/unet-implementation/426
import torch
from torch import nn, Tensor
import torch.nn.functional as F
from typing import List
class UNet(nn.Module):
def __ini... |
3a737c9bb951d488f283bc679ad5cf29f6ac3d45e3a2fc5e1d17ecc5e7c448f8 | Python | 6,558 | 193 |
import scanpy as sc, anndata as ad
import numpy as np
import pandas as pd
from sklearn.cluster import KMeans
from sklearn.metrics import adjusted_rand_score
import matplotlib.pyplot as plt
import re, seaborn as sns
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.colors import ListedColormap
if __name__ =... |
cf07891fb7123744628882010f5eea2172f8b74b7c1979b1afbef379c445edec | Python | 6,559 | 135 | # main file for CNN classifier
# Updated: 9/16/2023
# Status: OK
# CUBLAS_WORKSPACE_CONFIG=:4096:8 python classifier_main.py
# results in current setting:
# ----------------------------------------------------------------------------------------------------
# Model Accuracy Precision (weighted avg)... |
f53df1b1eed2690a81814ea1dd0628d5305f1b4cd9ea8b979dbd6b59f75a5129 | Python | 6,559 | 168 | import tensorflow as tf
from tensorflow.keras import Model
from tensorflow.keras.layers import InputLayer, Dense, Lambda, LayerNormalization
from typing import Union
from .utils import fuse_batchnorm, remove_activation
from ..layers import get_lrp_layer, PoolingLRPLayer, StandardLRPLayer
from ..utils import infer_gr... |
cb7a4811e12e534a5e62c72d9d7897f13b73a5ff2ee56a3e1f685a8907582019 | Python | 6,561 | 153 | #!/usr/bin/env python3
# Adapted from http://revigo.irb.hr/CodeExamples/revigo_restful.py.txt (excessed 2022-06-09)
# Python script for programtic access to Revigo. Run it with (last output file name is optional):
# python3 revigo.py example.csv result.csv
import requests
import time
import sys
import pandas
import ... |
eec1ed8f4c89b9263084cbfd5c577ca0d6a093dc31827a5d53f4b2a6ced63f96 | Python | 6,562 | 219 | # Configuration file for the Sphinx documentation builder.
#
# This file does only contain a selection of the most common options. For a
# full list see the documentation:
# http://www.sphinx-doc.org/en/master/config
# -- Path setup --------------------------------------------------------------
# If extensions (or mo... |
2e598fd1574f0d6a418e6b5e67d5f1e1081ac796697519514927d7a9e792c7fc | Python | 6,563 | 141 | import torch
import torch.nn as nn
from rfdiffusion.Embeddings import MSA_emb, Extra_emb, Templ_emb, Recycling
from rfdiffusion.Track_module import IterativeSimulator
from rfdiffusion.AuxiliaryPredictor import DistanceNetwork, MaskedTokenNetwork, ExpResolvedNetwork, LDDTNetwork
from opt_einsum import contract as einsum... |
19bf038242f259b9c951e78ead662f6ee84b05c139f218db6615b4c150e3b255 | Python | 6,565 | 211 | # !/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on: Thu 15 Sep 2022 17:08:06
Description: Create new fasta file with short unique ids and a csv file
containing the mapping back to the original file
Usage: python main.py
@author: tsenoner
"""
import argparse
from itertools import product... |
26578c9f11d6cf8f0a8008cb3c0ca8ae95e1d30b018743f6c59ed6b20079c25d | Python | 6,566 | 189 |
import ClusterModelNEST
import defaultSimulate as default
from analyse_nest import cut_trials, split_unit_spiketimes
from copy import deepcopy
import numpy as np
import matplotlib.pyplot as plt
import pylab
from GeneralHelper import (Organiser, round_to_resolution, random_pick)
def stimulus_protocol(condition,trials... |
f82ec95f9b9ada059f9963b2cf6ef863fa9ca7eaeabedfe4e55ed59a6284c8f3 | Python | 6,568 | 221 | import types
import numpy as np
import matplotlib.pyplot as plt
from fastweights_numpy import FastWeights, FeedforwardNet
from data_utils import generate_recognition_data
from neural_net_utils import Sigmoid, Relu, Quadratic, CrossEntropy, plot_W, plot_B
#%% Generate data
d = 50 #length of input vector... |
5469bc45f5a3743a5f24b3a167fbd7955a58125880de19858428e7870c211f91 | Python | 6,587 | 160 | import logging
import os
import socket
import sys
from fcest.helpers.inference import run_adam_svwp, run_adam_vwp
from fcest.models.wishart_process import SparseVariationalWishartProcess, VariationalWishartProcess
import gpflow
from gpflow.ci_utils import ci_niter
from configs.configs import get_config_dict
from help... |
f68b1630d6822bf87d167ea37e659fddd81bc877fa00f6ccf8f374f369abf6b1 | Python | 6,588 | 200 | import numpy as np
from scipy.linalg import solve
from typing import Tuple
# Code from: https://github.com/smrfeld/Total-Variation-Regularization-Derivative-Python/blob/main/python/diff_tvr.py
class DiffTVR:
def __init__(self, t, alpha):
"""Differentiate with TVR.
Args:
n (int): Number... |
5fad46476e4c435108bd8246adcc1b4bf6afce2b729cc8935c434e8627e8840a | Python | 6,593 | 190 | ########################################################################
# 2D diffusion on an infinite strip from line "point source".
# AIMS: to verify STEPS spatial-stochastic solver 'Tetexact' supports
# local initial conditions and calculates surface diffusion rates correctly.
# STEPS equivalent model: Stochas... |
26ad7d610c5832386d962b28283a2ddf112b1e4e1151f254de06b1a62f089c60 | Python | 6,595 | 177 | from collections.abc import Callable
import networkx as nx
import numpy as np
import pandas as pd
from pgmpy.base import DAG
from pgmpy.causal_discovery._base import BaseCausalDiscovery
from pgmpy.causal_discovery.bivariate_scores import BaseBivariateScore, get_bivariate_score
from pgmpy.utils import get_dataset_type... |
45e91cb9ed1f08c4c97fd74aa6f1fb2bfe1490e12a7a3cf9bb34df197aaaa5de | Python | 6,596 | 184 | import argparse
import random
import numpy as np
import torch
from torch import nn
from modelling.model import CEEffNet, CEResNet
from preparation import dataset_functions as dpr
from preparation.datasets import BCN20k_Dataset
from processing.train import train
from processing.utils import obtain_transform
# Make w... |
61653376c3a221403572c56c1221505051c52a1c651cc2da310c5a3b09d371e7 | Python | 6,597 | 251 | # 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... |
7982c4f558fff9a48618c9787e12533a178a554a9b8d51ce6d517a4112ced221 | Python | 6,598 | 171 | import types
import random
import numpy as np
import matplotlib.pyplot as plt
from fastweights_numpy import FastWeights, FeedforwardNet
from dt_utils import Timer
from data_utils import generate_recognition_data
from neural_net_utils import Sigmoid, Relu, Quadratic, CrossEntropy
#%% Generate data
d = 50... |
11a7c14c39b73083196c80b0d77467fb4dc3a552f132f785c9d49eaa549880dc | Python | 6,601 | 169 | """ Helper class for deep believe networks.
:Version:
1.1.0
:Date:
06.04.2017
:Author:
Jan Melchior
:Contact:
JanMelchior@gmx.de
:License:
Copyright (C) 2017 Jan Melchior
This file is part of the Python library PyDeep.
PyDeep is free so... |
1f83365d53f3abdfb7f12f84ac0186de3970d4c2d14424f47ea36a14962e610d | Python | 6,602 | 157 | import copy
import logging
import os
import socket
import sys
import numpy as np
import pandas as pd
import pingouin
import scipy
from configs.configs import get_config_dict
from helpers.hcp import get_human_connectome_project_subjects, rename_variables_for_plots
def _rename_models_for_plots(config_dict: dict, orig... |
5a02a942529cb4e6102bd2a95816351ac82e7c1e169d059318e246091d9424e3 | Python | 6,607 | 164 | # 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... |
c72e9cd3cc50179f54e06f0dc1aedc9cf8f4d3d9b1fb9905ac38c452d9dc6f29 | Python | 6,607 | 216 | """Context management for tracers."""
from __future__ import annotations
from contextlib import contextmanager
from contextvars import ContextVar
from typing import (
TYPE_CHECKING,
Any,
Literal,
cast,
)
from uuid import UUID
from langsmith import run_helpers as ls_rh
from langsmith import utils as l... |
da61dbda55bc2e3178fdf03f8ebb0bb472ade879bd26fa38f12215578f846249 | Python | 6,608 | 218 | """Script for preprocessing PDB files.
WARNING: NOT TESTED WITH SE(3) DIFFUSION.
This is example code of how to preprocess PDB files.
It does not process extra features that are used in process_pdb_dataset.py.
One can use the logic here to create a version of process_pdb_dataset.py
that works on PDB files.
"""
impor... |
a7f7fe4b02b7b6e65093c1a15ae9bd25409e00e7768d0ed7b0ef11977eaa8fc5 | Python | 6,612 | 169 | # 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... |
95ee64421c30f7a6fbe49ac8b5278dfc5c5ead465b83cd4f86b3896de1918959 | Python | 6,625 | 183 | import torch
from bindsnet.learning import (
MSTDP,
MSTDPET,
Hebbian,
NoOp,
PostPre,
Rmax,
WeightDependentPostPre,
)
from bindsnet.network import Network
from bindsnet.network.nodes import Input, LIFNodes, SRM0Nodes
from bindsnet.network.topology import *
class TestConnection:
"""
... |
0ed75bbf46559e0c8433d0b5a58399c123bdda18bdbd642aa4cbb636038c0392 | Python | 6,628 | 139 | import numpy as np
import pandas as pd
from sklearn.cluster import KMeans
import random
import seaborn as sns
import torch
import matplotlib.pyplot as plt
import h5py
from sklearn.preprocessing import MinMaxScaler, StandardScaler
import shap
import sys
from modal_type_list import *
import argparse
def get_shap_pathw... |
dbc6d9e56d9b40c66344a7ccd714867c955798e4d00b860533739ba0b5f88e2f | Python | 6,630 | 175 | import torch, os
from copy import deepcopy
from data import generate_recog_data
from networks import HebbNetBatched, HebbNet
from plotting import plot_train_perf, plot_W, plot_recog_generalization, plot_recog_positive_rates, plot_multi_hist, clean_up_w, sort_w, shuffle_w, left_justify_w, plot_w1_row_col_sums
from... |
08fc03c9dff3c8a1c8a87825e57335b81bbb46040ad55a750905141b940d51a5 | Python | 6,632 | 177 | ####################################################################################
#
# 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... |
1a8b27e118b2c02b01372c26ddc0ce42f3539f8634aefa89e3e9cad38c59dab5 | Python | 6,633 | 177 | ####################################################################################
#
# 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... |
03633e05b780f442562a15418126ec7b9f4c28e4c48fd3ef78bb2021268c9eed | Python | 6,634 | 152 | from sklearn.impute import SimpleImputer
from sklearn.preprocessing import StandardScaler
from sklearn.linear_model import LogisticRegression
from mimic3benchmark.readers import LengthOfStayReader
from mimic3models import common_utils
from mimic3models import metrics
from mimic3models.length_of_stay.utils import save_r... |
c015e3f71784d302b87b3814d4d09225b16ec461c2f41d78280068c4018bd12f | Python | 6,640 | 178 | import matplotlib.pyplot as plt
import joblib
import numpy as np
from torch.utils.data import TensorDataset
import torch.nn as nn
import torch
from data import generate_aug_recog_data_batch, generate_recog_data_batch, recog_chance
from plotting import plot_train_perf
from networks import HebbAugRecog
#%% C... |
83b1598c9f5ca3b70404df0eecf464c73ae0229e46ecbb5da2dc56edacd76f5f | Python | 6,641 | 226 | ####################################################################################
#
# 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... |
3fa79092cdadaf4283e396e937b0410c709352272acd8b4111ab64a5bf901d8e | Python | 6,645 | 226 | ####################################################################################
#
# 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... |
297beb2efa628d2ae48b75ac5b36d190224222cac9fed13b39d23969f055a484 | Python | 6,646 | 176 | # 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... |
76880f7d736a149209933d64540bc038938354ae034bf2ac1a6aafc61f7519f5 | Python | 6,646 | 181 | import asyncio
import json
import argparse
from datetime import datetime
from pathlib import Path
from typing import Dict
from aiohttp import ClientSession
from tqdm import tqdm
async def get_status(
workflow_id: str, session: ClientSession
) -> Dict[str, Dict[str, str]]:
"""
This function gets the statu... |
ed2f3ecd56f0fbe15257b5ac7d91d2d5acc21a1d1eca8f6e4f8e0ec1d30a21d5 | Python | 6,653 | 187 | from __future__ import print_function
import tensorflow as tf
from nn import linearND, linear
from mol_graph_direct_useScores import atom_fdim as adim, bond_fdim as bdim, max_nb, smiles2graph, bond_types
from models import *
import math, sys, random
from optparse import OptionParser
import threading
from multiprocessin... |
2e92f68bc8bc1eab1ee4dc5e06b009e3947581c9e3ec46246c2172fe13dd0a8f | Python | 6,659 | 157 | # *=========================================================================
# *
# * Copyright Erasmus MC Rotterdam and contributors
# *
# * Licensed under the GNU GENERAL PUBLIC LICENSE Version 3;
# * you may not use this file except in compliance with the License.
# *
# * Unless required by applicable law or agre... |
3cfebcd455f19cbddecc48d7d96021b57dfe73fd262fb57ef20089bd532eaec7 | Python | 6,660 | 193 | # 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... |
a62f9e4978a0e19683ab70ced87dce04da745eb38ec187e45d596d43014f881c | Python | 6,661 | 122 | # Copyright (c) 2008-2026 the MRtrix3 contributors.
#
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at http://mozilla.org/MPL/2.0/.
#
# Covered Software is provided under this License on an "as is"
#... |
8ee59555bb37e6c902b9c65d687fd393f04c82f872c4d7a4871da010616283dc | Python | 6,666 | 157 | # 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... |
9f60e9b0f9b0758531afd12388bd7002218d06a571c171d70f408b3c0f239da4 | Python | 6,666 | 192 | # Generated by the protocol buffer compiler. DO NOT EDIT!
# source: animalai/communicator_objects/arenas_configurations_proto.proto
import sys
_b = sys.version_info[0] < 3 and (lambda x: x) or (lambda x: x.encode("latin1"))
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as ... |
927087b5c6c11fa4b66ac59cd7a125ed04d059598d86682df7907232aafbca74 | Python | 6,672 | 193 | import numpy as np
import networkx as nx
import torch as pt
#import torch_geometric as ptg
import pytorch_lightning as ptl
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... |
d291d725e63e71211e3d088e0900d6d8af97067ce7b202a6e2fc48ce1506926c | Python | 6,675 | 209 | import os
import json
import re
import glob
def compileRegexes(obj):
# compile regexes loaded from JSON files
objType = type(obj)
if(objType is dict):
for key in obj:
if(type(obj[key]) is str):
obj[key] = re.compile(obj[key])
else:
compileRege... |
ee21f11820f7fb4193f8a7cf4e67cf1f8073febf400544a82c1a1ecbbb690e17 | Python | 6,675 | 264 | #!/usr/bin/env python3
"""
Output volumes of each probabilistic label in an atlas in microliters.
Accepts multiple 4D prob atlas files
Usage
----
prob_label_volumes.py <atlas_file>
prob_label_volumes.py -h
Example
----
>>> prob_label_vol_info.py *_probs.nii.gz
Authors
----
Mike Tyszka, Caltech Brain Imaging Center
... |
cdef233ed581be137abcd1321e7aabc2896e157096c218d38ddf274a4c0dc0d5 | Python | 6,677 | 188 | from util import *
EPS = 1e-12
def augment_data(
half1, half2, mask,
box_size, voxel_size,
do_smooth_solvent=True,
augment_orientational_bias=False,
augment_bfactor=False,
augment_noise=False,
device=torch.device("cpu"),
verbose=False
):
grids = np.... |
eae54e30716d1c1a8ca1c5c824b9b37bfe6a653c8e23d87b2507763497b91721 | Python | 6,678 | 185 | 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
#strategy = tf.distribute.MirroredStrategy()
#load model
filterm = tf.keras.... |
877737155cbd94d4955a7d25407789c1863e7163d00e06dfd43e0a9db9837c42 | Python | 6,679 | 281 | # -*- coding: utf-8 -*-
from typing import Callable, Optional
import torch
from torch import nn
from torch.nn.parameter import Parameter
from torch.distributions import Normal
from torch.distributions import kl_divergence as kl
class GraphConvolution(nn.Module):
"""
Simple GCN layer, similar to https://arxi... |
aff6a63abc3a6152650ad0aba074073b733d03438b0ff686e40764302a1e3ac0 | Python | 6,680 | 167 | # coding=utf-8
import os
import numpy as np
import torch
import sys
# sys.path.append('..')
from datautil.util import Nmax
import datautil.imgdata.util as imgutil
from datautil.imgdata.util import rgb_loader, l_loader
from torchvision.datasets import ImageFolder
from torchvision.datasets.folder import default_loader
i... |
5b7033eb75872bfd4e2504bf9432dd7b2fe522cd49f3ae9111389713427d9b8d | Python | 6,682 | 230 | import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
def add_identity(axes=None, *line_args, **line_kwargs):
if axes is None:
axes = plt.gca()
identity, = axes.plot([], [], *line_args, **line_kwargs)
def callback(axes):
low_x, high_x = axes.get_xlim()
low_y, high_... |
57124184db2f60040ff949a54fa617d3ea15321365fae1d3339af6b44adeb0ff | Python | 6,685 | 153 | import gym
import random
from gym import spaces
import numpy as np
import logging
from random import sample,choices,uniform, randint
from math import ceil
from DSS_Initialize import *
from state_action_reward import *
from gym.utils import seeding
logging.basicConfig(format='%(asctime)s %(levelname)s: %(message)s', le... |
cc0875a062ec30dbe3fdb7f631e42d4454fe65aa86f85f4545f46269d3d96569 | Python | 6,685 | 182 | import time
from contextlib import contextmanager
from typing import Optional, Tuple, Any, Union
import torch
from einops import rearrange # noqa
from torch import Tensor
from rde.utils.protein.protein_constants import INDEX_TO_AA_ONE
get_eps = lambda x: torch.finfo(x.dtype).eps # noqa
get_max_val = lambda x: torc... |
f129358857f5c0615a0b3a0cb5f0413e1bc006ebc67a3b4a936eb75e3f170fd1 | Python | 6,685 | 193 | # builtin modules
import os
import logging
# third party modules
import numpy as np
# pnabind modules
from .get_atom_kdtree import getAtomKDTree
from .get_surface_residues import getSurfaceResidues
class StructureData(object):
def __init__(self, structure, name='structure', path='.', level='S', mid=0):
... |
a37d25f17bf7c7070404a83e71456ae98c3a48ea10d9903dda5d6aa7876e2211 | Python | 6,688 | 155 | import math
import numpy as np
from tqdm import tqdm
from os.path import join
from os import listdir
import pandas as pd
import sys
import subprocess
def get_read_data(all_data):
'''
Given a line from an NGS file, return the name, sequence, and quality scores of the read
Args:
all_data: string cont... |
706c6abe0f845e70de28531d028daba4fba633d0a1d9b558dddc602abf519fc9 | Python | 6,694 | 135 | """
%Copyright (C) 2020, Manel Vila-Vidal, for the translation from Matlab to Python
Contact details: m@vila-vidal.com
%Copyright (C) 2019, Adria Tauste Campo, for the original Matlab code (https://github.com/AdTau/DI-Inference)
%Contact details: adria.tauste@gmail.com
%This program is free software; you can redistrib... |
0e852a5fa544f602fa2b9874ef0168faca0e6c222bd2977967e7dc2eed84cee9 | Python | 6,695 | 198 | import torch
import torch.nn as nn
import numpy as np
import torch.nn.functional as F
from collections import OrderedDict
class ReactionDiffusionParamPDE(nn.Module):
def __init__(self, dx, is_complete, real_params=None):
super().__init__()
self._dx = dx
self._laplacian = nn.Parameter(... |
1354bb56b04906b1900611fe6b8237ee930c4bb1a6d94d887925d7dc3459ae90 | Python | 6,695 | 191 | from typing import Optional
import torch
def single(
datum: torch.Tensor,
time: int,
dt: float = 1.0,
sparsity: float = 0.5,
device="cpu",
**kwargs,
) -> torch.Tensor:
# language=rst
"""
Generates timing based single-spike encoding. Spike occurs earlier if the
intensity of the... |
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