sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
be8a5fbce140df6152589debc0153904250dab4d40511bc466f8599269091e5a | Python | 12,189 | 308 | """A synthetic Haxby-like dataset, built the way `Simulator` builds data.
Despite living beside the fetchers in `nltools.datasets`, `load_haxby_example`
downloads no data: it injects condition-specific signal into a few spheres of
the package's 3 mm MNI brain mask (or, on request, into a tiny synthetic
volume). That m... |
8e5e307f49143efa7f4669486cbdc9188f3016c4e3f7ceafe26c6ca55e337bf6 | Python | 12,192 | 349 | r"""The manifold of Positive Semi Definite matrices of rank k PSD(n,k).
Lead author: Anna Calissano.
"""
import geomstats.backend as gs
from geomstats.geometry.fiber_bundle import FiberBundle
from geomstats.geometry.full_rank_matrices import FullRankMatrices
from geomstats.geometry.general_linear import GeneralLinear... |
bb0b948f4381a64c882cca82c5d7038ca8be7b18ca9bb36574af90f12d86718f | Python | 12,204 | 347 | # -*- coding: utf-8 -*-
"""
Created on Thu Jun 8 15:45:24 2023
@author: Em
"""
from torch import (#where,
zeros_like,
tensor,
exp,
ones,
zeros,
is_tensor,
#stack,
... |
3c99f90614a49962642ef81981b06595de925f3f2f12ce33bcb9e74d272db5d6 | Python | 12,215 | 254 | import numpy as np
import scipy
import pandas as pd
import itertools
import os
from sklearn.preprocessing import minmax_scale
from sklearn.linear_model import LinearRegression
from sklearn.cluster import KMeans
from sklearn import metrics
from .data_loading import PTIterator, CNIterator, Paired_data_iterator, val_PT_co... |
92f23cf2c5ba17975c0b25592ccd13329e9a7a6933c31bbee48af423485c708e | Python | 12,220 | 241 | # Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# This work is licensed under the Creative Commons Attribution-NonCommercial
# 4.0 International License. To view a copy of this license, visit
# http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to
# Creative Commons, PO Box 1866, Mountain ... |
5692998db334c0f2dda7aee3cae3c364482ac33819c2b9ea23280d15491b9fb4 | Python | 12,222 | 344 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
import torch
from ._workflow_utils import set_workflow_state
from ._compile_utils import COMPILE_TARGET_DICT
from nequip.model.utils import _EAGER_MODEL_KEY
from nequip.model.saved_models.load_utils im... |
d5c35af9ac630f877b7d5b01442bb700eb44305e7fffb888def3066216e5455a | Python | 12,223 | 384 | # ==============================================================================
# Copyright 2025 Technical University of Denmark
# Author: Nikolas Borrel-Jensen
#
# All Rights Reserved.
#
# Licensed under the MIT License.
# ==============================================================================
"""Unit tests fo... |
0c8f6ddf06275d3739223498e102282fc57c56e87bfbd54b17a89ef102d710dc | Python | 12,228 | 348 | """Represent stimulus epochs for one recording sweep."""
from __future__ import annotations
from collections.abc import Mapping, Sequence
from typing import Any, Literal, Optional
from pprint import pprint
import pandas as pd
import pyabf
from pydantic import BaseModel, ConfigDict, field_validator
from sanpy.sanpy... |
834c69e1c57523decb296fa58d8e90e9943e27b1735c01e48771387e9eb3fcbf | Python | 12,233 | 290 | """The published MACE-MDP model reproduces its committed reference.
``mace_mdp`` loads an ``AtomicDielectricMACE``, which is the **only** class in
the tree that emits a ``polarizability`` (``mace/modules/models.py:1190``), so
this is the one place that quantity is pinned at all. FM-2 converts this
checkpoint; the numb... |
f68c687bc33fd67a9cbb6217fce9a8e94e7f5075e1c50193b1a6ebfd6a5e3671 | Python | 12,238 | 373 | from __future__ import annotations
import platform
import re
import subprocess as sp
import sys
import tempfile
from pathlib import Path
from typing import Any, Final, Literal, TypedDict
import copier
import more_itertools as itx
import pathvalidate
import pytest
import requests_mock
from hypothesis import HealthChec... |
e41b82b1f678237ca27785b6519f7620382f080ec331ff82ea52a5e12886e300 | Python | 12,239 | 348 | from time import time
import numpy as np
from PymoNNto.NetworkCore.Base_Attachable_Modules import *
from PymoNNto.NetworkCore.Synapse_Group import *
from PymoNNto.Exploration.Evolution.Interface_Functions import *
import copy
import time
import sys
float32 = np.float32
float64 = np.float64
SxD = 0
DxS = 1
class Netw... |
fa2a801315e4b968de961db3227a367cdad83f2cf687016d6c725eeb43ca0c72 | Python | 12,247 | 337 | """Functions to train and evaluate the classifier"""
import gc
import os
import time
import numpy as np
import pandas as pd
import torch
from matplotlib import pylab as plt
from .ConvNet import compute_device, accuracy
torch.cuda.empty_cache()
gc.collect()
def find_lr_bounds(model, train_loader, opt_func, save,... |
06dc0679263dbff1e74c460b1446b914f9f5cd845f7cfdbecfbbda1d143a7c80 | Python | 12,274 | 343 | import os
import random
import time
from pathlib import Path
import numpy as np
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
import webdataset as wds
import yaml
from torch import optim
from torch.distributed.algorithms.join import Join
from torch.nn.parallel import DistributedDataP... |
1cf366690a77c56e2c68f54489e6b90ae2799aa1503c302a5b8bae30a5a1c327 | Python | 12,284 | 287 | """Tests for Adjacency modeling: bootstrap, regression, SRM, cluster summary,
permutation generation."""
import numpy as np
import pandas as pd
import pytest
from scipy.linalg import block_diag
from nltools.data import Adjacency, DesignMatrix
# Only `bootstrap` emits these two quality advisories, and the bootstrap t... |
b26e8bb1e2e25e36224b74d300237677b25c0bbfd8adc98b2b0d2742abf68df9 | Python | 12,290 | 320 | import warnings
warnings.filterwarnings('ignore')
import pandas as pd
import numpy as np
import statsmodels.api as sm
import statsmodels.formula.api as smf
from statsmodels.tools.sm_exceptions import PerfectSeparationError
import scipy.stats as stats
from co... |
7ab3c444ec06211b0e535b70aba3d25b3b2f461b2e50d6bac7dcb1b28bdd1e37 | Python | 12,296 | 347 | """Determine sample sizes by interpolating run simulation outcomes."""
import numpy as np
import xarray as xr
from scipy.stats import linregress
from scipy.interpolate import InterpolatedUnivariateSpline
from ..metrics import mk_betweenAssocRelError, mk_weightError, \
mk_scoreError, mk_loadingError, mk_betweenCor... |
4542289785ebe10d65e2f24811047f8ad0744ac0c1ee9b9d6191b77f8472cea4 | Python | 12,308 | 323 | from torch import (tensor,
is_tensor,
cat,
zeros,
arange,
exp,
rand,
randperm,
manual_seed,
bool as tbool,
eye,
... |
8fec2bb4aa57bbba5e60f1b8420f16783843a7cb7662ba5cd1dfde1853e28888 | Python | 12,319 | 349 | """
mesh_parser.py
parse mesh data from constant/polymesh
"""
from __future__ import print_function
import numpy as np
import os
import re
import struct
from collections import namedtuple
from .field_parser import parse_internal_field, is_binary_format
Boundary = namedtuple('Boundary', 'type, num, start,... |
f5a346b1c023fbba3cedc7498567a8c29ff91a8f3e61b6ef42a435a2d997d2e5 | Python | 12,326 | 346 | import numpy as np
from typing import List, Optional, Dict, Union
import hashlib
import pathlib
import pandas as pd
import ase
from deeperwin.run_tools.geometry_utils import BOHR_IN_ANGSTROM
import json
ROUND_R_DECIMALS = 5
def dump_to_json(data, fname):
def default_encoder(o):
if hasattr(o, "to_json"):
... |
176a6fc7d3467a431d048357aba71d9e2fe539e9e7ed356931b3c55cfdb192d7 | Python | 12,331 | 329 | import pytest
import geomstats.backend as gs
from geomstats.geometry.diffeo import AutodiffDiffeo
from geomstats.test.random import RandomDataGenerator
from geomstats.test.test_case import TestCase
from geomstats.test.vectorization import generate_vectorization_data
class CircleSO2Diffeo(AutodiffDiffeo):
"""Diff... |
bcd8e09e11894888cbfdcbaf38f147c95e94ed249ab5e206114019c4cbac00f2 | Python | 12,339 | 338 | import uuid
from random import randint
from typing import cast, List, Any, Dict, Tuple
import hypothesis
import pytest
import hypothesis.strategies as st
from hypothesis import given, settings
import chromadb
from chromadb.api import ClientAPI
from chromadb.api.types import Embeddings, Metadatas
from chromadb.test.conf... |
10da171b85691535bd021dda160b79d6db3c0e19a841c10a5d6bb10b98fadc82 | Python | 12,356 | 297 | '''
Description:
Author: voicebeer
Date: 2020-12-10 08:47:27
LastEditTime: 2021-02-27 03:08:48
'''
# standard
import models
import utils
import argparse
import torch
import torch.nn.functional as F
import torch.nn as nn
import numpy as np
import copy
import random
import time
import math
from torch.utils.tensorboard i... |
a44f3f3de00f6394c348cd02cf222ed92fe5ffd02db437cd938c9482ccd8955c | Python | 12,358 | 350 | from __future__ import annotations
from typing import Any, Dict
import numpy as np
import pytest
import torch
from ase import Atoms
from e3nn import o3
from mace import data, modules, tools
from mace.calculators.foundations_models import mace_polar
from mace.cli.convert_cueq_e3nn import run as run_cueq_to_e3nn
from ... |
8251a3881d8f669c4497ef7c2ffb3c0549091a9e35b9fed1c2ae00bf41bb69fc | Python | 12,359 | 260 | """Optional pgmpy contract, run in the pinned confidence environment."""
import json
import pytest
pytest.importorskip('pgmpy')
from vdjdb.score.bayes import fit, predict, predict_marginals
def test_exact_missing_inference_roundtrip_and_deterministic_tree():
rows = [{'a_studies': '2' if i % 2 else '0', 'b_tcrne... |
5271589869d29408e5d8e34faddeb264c60da8902791d77207bbc88a3d4a7268 | Python | 12,371 | 384 | """
NeuroLearn Utilities
====================
handy utilities.
"""
__all__ = [
"get_resource_path",
"get_anatomical",
"set_algorithm",
"attempt_to_import",
"all_same",
"concatenate",
"_bootstrap_apply_func",
"set_decomposition_algorithm",
]
__author__ = ["Luke Chang"]
__license__ = "MI... |
1010afc83d832e128604ad9290316c43d98af8622e5dff1972bd1e266da50152 | Python | 12,389 | 336 | #!/usr/bin/env python3
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
import method.io as io
import method.nn as nn
import numpy as np
import pandas as pd
import argparse
from sklearn.preprocessing import StandardScaler
from imblearn.over_sampling import SMOTE
"""
Treat this as a multi-label classification problem... |
2f85cd826dd1fcf9677f8cbf12d00f411a95b1627cd207be028bc78e9d9f7848 | Python | 12,391 | 323 | import os, argparse, subprocess, shlex, io, time, glob, pickle, pprint
import sys
import os
import numpy as np
import pandas as pd
# import matplotlib.pyplot as plt
# import tqdm, fire
from PIL import Image
Image.warnings.simplefilter('ignore')
import torch
import torch.utils.model_zoo
from torch.utils.data import D... |
1353f43fc22b9d65d985b6cb1787096cf47f4c994d8237807ad64258df03be34 | Python | 12,393 | 349 | #
# For licensing see accompanying LICENSE file.
# Copyright (C) 2022 Apple Inc. All Rights Reserved.
#
import random
import argparse
from utils import logger
from typing import Optional
from common import DEFAULT_IMAGE_WIDTH, DEFAULT_IMAGE_HEIGHT
from . import register_sampler, BaseSamplerDP, BaseSamplerDDP
from .ut... |
2edca220b18feec2bb8ab67cec9dfc60f58b4bf802b942acd67b864afc340f0a | Python | 12,397 | 344 | # ---
# jupyter:
# jupytext:
# text_representation:
# extension: .py
# format_name: light
# format_version: '1.5'
# jupytext_version: 1.16.4
# kernelspec:
# display_name: Python 3
# language: python
# name: python3
# ---
# # `REINVENT 4.4`: Reinforcement Learning with DockSt... |
71d6b5d2b32b69fc72d08cb3f19235d645ed4abff76448f86f916fe49382f9e8 | Python | 12,399 | 340 | import pytest
import logging
import hypothesis.strategies as st
from chromadb.test.property.invariants import check_metadata
import chromadb.test.property.strategies as strategies
from chromadb.api import ClientAPI
import chromadb.api.types as types
from hypothesis.stateful import (
Bundle,
RuleBasedStateMachin... |
6694ae0b273a5ad95bca1b63fccb5d0c533120669a13cb462a228f8cb05b3348 | Python | 12,409 | 344 | import numpy as np
from math import *
#ms_per_step=2
#def step_ms(x):
# return x*ms_per_step
def SpikeTrain_ISI(x):
result = []
last = -1
for i, x in enumerate(x):
if x > 0:
if last!=-1:
result.append(i-last)
last=i
return result
def get_bins(numbe... |
832e14cc654c19e2ce3a1e512f48f468ba0db5973bda122d6fc3b13e446d5d4d | Python | 12,410 | 284 | """How the magnetic anchor is driven, on each of the three surfaces.
Shared by ``regenerate.py`` and by the two magnetic golden test modules, and
that sharing is the point: a reference and the test that checks it have to
drive the model the same way, and the only reliable way to guarantee that is
for there to be one d... |
8e9d4ff7459b03723fcab7099575838f7d4860bd5e0983ed82825ad18c668004 | Python | 12,414 | 513 | import matplotlib
import matplotlib.patches
import matplotlib.pyplot as plt
import numpy as np
def plot_1d(
domain,
u_ref,
u_state,
path=None,
title=None,
umin=None,
umax=None,
slice_lim=0.1,
transpose=False,
invertx=False,
nslices=6,
dpi=300,
transparent=True,
... |
46a197f7c4071211699a656140ea233e7c4d646a1460db15ed079ca610aa57c9 | Python | 12,418 | 217 | #*----------------------------------------------------------------------------*
#* Copyright (C) 2024 ETH Zurich, Switzerland *
#* SPDX-License-Identifier: Apache-2.0 *
#* *
... |
e7ad4cf4e834f1807bcfdcd54d29d449b3d5569574077722b0295494e7a2f8cd | Python | 12,420 | 349 | # model2b_experiment2.py - A simulation and model fit of Model 2b and Experiment 2
#
# Copyright (C) 2023 Michael D. Nunez, <m.d.nunez@uva.nl>
#
# 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, e... |
d16062a158487d6356a736a1c6b2bfddb8e76d950c505316d8cad4bf4c6cca09 | Python | 12,428 | 224 | """Structural audit of the cropped Stereo-seq fixture (called from the test script)."""
import os
import h5py
import numpy as np
BORDER_PAD = 32767
def audit(out_dir, source_dir, sn, x0, y0, size):
res = []
def ck(name, cond, detail=""):
res.append({"name": name, "pass": bool(cond), "detail": str(det... |
42a1f41a221602297d1f13e7fa8bf90175ef858bf797706568fbe1a7030ed351 | Python | 12,433 | 334 | ###########################################################################################
# This code is adapted from the Atom3d paper and the GVP paper
# ATOM3D:
# https://arxiv.org/pdf/2012.04035.pdf
# https://github.com/drorlab/atom3d
#
# GVP:
# https://arxiv.org/abs/2106.03843, https://ope... |
574fbcede8b8c4511acaaa9319eac8186af0aa69331de4f79c0c88829e0d1edf | Python | 12,438 | 359 | # 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 mmap
from pathlib import Path
import io
from typing import BinaryIO, List, Optional, Tuple, Union
import numpy as np
import torch
imp... |
ca3a2f061b470600dc49bcb55b2c50a72fa6e387794950b6be9acc5b24d6f1fd | Python | 12,442 | 324 | # 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 math
from typing import Dict, List, Optional
import torch
import torch.nn as nn
from torch import Tensor
from fairseq import utils
fr... |
910e5e42f6a340c6b23e0a516d6778c831640b2b5c7acda181ad5db28eaac279 | Python | 12,446 | 355 | # nolapse_test_pystan.py - Testing fits of HDDM models without lapse process in Stan using pystan in Python 3
#
# Copyright (C) 2021 Michael D. Nunez, <m.d.nunez@uva.nl>
#
# 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 ... |
e1e0875c704f5addf90817f44343ac361fe02934c9bf28c86ddd652be9e238af | Python | 12,446 | 414 | ## In this script we use to train both the permutation
# equivariant network and the data augmentation during
# training
import numpy as np
# import matplotlib.pyplot as plt
import torch
import h5py
import torch.nn as nn
from torch.utils import data
import itertools
# number of available gpu
ngpu = 1
batch_size =... |
5fcb93bb5b54623c3d18e6bbeb30320039cb46496fd96eaf7186a8ac4a662d61 | Python | 12,451 | 355 | """plotting_help.py
Useful functions for matplolib plots
"""
import numpy as np
from matplotlib.collections import LineCollection
from matplotlib.colors import to_rgba
import matplotlib.gridspec as gridspec
import matplotlib.pyplot as plt
from matplotlib.offsetbox import AnchoredOffsetbox
redorange = (.96, .59, .2)... |
2b295f8454b0a12f7ca7163d92a434b0e5e6c151c28ce7516136afe7b64af885 | Python | 12,452 | 364 | """
Code for sampling from diffusion models
"""
import json
import os
import multiprocessing as mp
from pathlib import Path
import tempfile
import logging
from typing import *
from tqdm.auto import tqdm
import numpy as np
import pandas as pd
import torch
from torch import nn
from torch.utils.data import default_coll... |
aa1b8276225e9ed49ed44506f9d16cf98b5bc70f5ff17b1214d8a15378d9eced | Python | 12,459 | 317 | # Copyright 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""Experimental Director module."""
import asyncio
import logging
import time
from collections import defaultdict
from pathlib import Path
from typing import Any, AsyncGenerator, Dict, Iterable, Optional, Tuple, Union
import dill
from op... |
abd0863bd3291e39eb65d4fadb75f276616ef4f647b41164f284df54b0bafc94 | Python | 12,467 | 341 | # -*- coding: utf-8 -*-
#
#
# PyRates software framework for flexible implementation of neural
# network models and simulations. See also:
# https://github.com/pyrates-neuroscience/PyRates
#
# Copyright (C) 2017-2018 the original authors (Richard Gast and
# Daniel Rose), the Max-Planck-Institute for Human Cognitive... |
e30069326e76779cf25720b960789a4b90dc968acac8122f48e35eb8e78c5088 | Python | 12,467 | 334 | import pytest
from unittest.mock import patch
from chromadb import CloudClient
from chromadb.errors import ChromaAuthError, NotFoundError
from chromadb.auth import UserIdentity
from chromadb.types import Tenant, Database
from uuid import uuid4
def test_valid_key() -> None:
with patch(
"chromadb.api.fastap... |
7810446986d03540e0b4677de9f8eea13b697977b91b76aa8f1c4a1340305d03 | Python | 12,477 | 334 | # -*- coding: utf-8 -*-
import numpy as np
import functions.time_functions as tf
from scipy import stats
from sklearn.svm import SVC
from sklearn import metrics
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import KFold
from sklearn.model_selection import cross_val_predict
from rando... |
175efb8d8547ac09829267273a18611760d5eba087295e3b6e491230a40d5548 | Python | 12,480 | 294 | import copy
import torch
import numpy as np
from scipy.special import comb
from itertools import combinations
import torch.nn.functional as F
from torch_geometric.utils import to_networkx
from torch_geometric.data import Data, Batch, Dataset
from torch_geometric.loader import DataLoader
def GnnNetsGC2valueFunc(gnnNet... |
2a9958bc6a089ddc1f2cb21ec7cf87766fb66066f2f366806b2d0604c5199202 | Python | 12,488 | 364 | # 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 contextlib
from argparse import Namespace
from dataclasses import dataclass, field
from typing import Any
import torch
import torch.nn... |
20251f38a00b05a51aeca887ab1a1a2ca3b81da5c379144e279eec63732d735c | Python | 12,498 | 291 | '''
Description:
Author: voicebeer
Date: 2020-09-14 01:01:51
LastEditTime: 2021-03-11 00:27:11
'''
# standard
import models
import utils
import argparse
import torch
import torch.nn.functional as F
import torch.nn as nn
import numpy as np
import copy
import random
import time
import math
from torch.utils.tensorboard i... |
af005c99dfe310c42e738cb47cfaf967c57d9e1d045d6a2032ffcb85abb37172 | Python | 12,500 | 299 | import tensorflow as tf
class WideResNet():
def __init__(self,
spectrogram_length,
spectrogram_width,
outputs_list):
self.spectrogram_length = spectrogram_length
self.spectrogram_width = spectrogram_width
self.outputs_list = outputs_list
... |
163462af25e5de0d0ce30c430b549122187475c9d63406a1ec819ee5ca90155a | Python | 12,501 | 319 | import argparse
from contextlib import nullcontext
import numpy as np
from scipy.spatial import cKDTree
from model_angelo.utils.affine_utils import (
get_affine_translation,
get_affine_rot,
get_affine,
init_random_affine_from_translation,
)
from model_angelo.utils.fasta_utils import fasta_to_unified_s... |
6d73e3f44a30740eab118d6027ced124046dfaf17d292a877b9666a590d83597 | Python | 12,501 | 246 | import numpy as np
import pandas as pd
import seaborn as sns
from multiprocessing import Pool
from orientation_reconstruction_utilities import *
from random_orientation_utilities import *
import matplotlib.pyplot as plt
import matplotlib as mpl
from mpl_toolkits import mplot3d
from mpl_toolkits.mplot3d import Axes3D
fr... |
f7e88cf562dcc81523d2e5176fceccfd51d4f1a8d84765510b9593f9d72e63a9 | Python | 12,501 | 428 | import torch
import torch.nn as nn
import numpy as np
import pysurvival.utils.optimization as opt
# --------------------------- Activation Functions --------------------------- #
class Swish(nn.Module):
def forward(self, x):
return x * torch.sigmoid(x)
class Gaussian(nn.Module):
def forward(self, x)... |
fe740b6425c0a4036614e8748ea3cde7565f38d685d8b8b19bcfbc987963eb30 | Python | 12,507 | 357 | from __future__ import annotations
import abc
import functools as ft
import re
from typing import TYPE_CHECKING, Any, Final, Iterable, Mapping, Sequence, cast
import attrs
import more_itertools as itx
from bids.layout import BIDSLayout, Query
from bids.layout.models import BIDSFile
from typing_extensions import Self,... |
ae4f2d05497bea7a17a35bf32ce2abf182ea4e0b8767ce5c6f48bab974848b04 | Python | 12,512 | 386 | # Stack class
# Stack of sections
# defined by:
# 3d bounding box
# cv
# section is a stack with thickness == 1
import copy
import os
import math
import six
from corgie import exceptions, helpers
from corgie.layers import str_to_layer_type
from corgie.log import logger as corgie_logger
class StackBase:
def __in... |
361d529a4e211085eed058e17a5ba3c6dde2320686570ec0a666d01feb70207e | Python | 12,525 | 353 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# TODO : add a colorbar in the top-right of the PRC instead of a legend
# 1. https://stackoverflow.com/questions/32462881/add-colorbar-to-existing-axis
# 2. https://stackoverflow.com/questions/43805821/matplotlib-add-colorbar-to-non-mappable-object
import o... |
447b52f18ecd17d589e7b8da93b6a9f529cad8be32d7430745c1abdbb595d1e4 | Python | 12,527 | 291 | '''
Description:
Author: voicebeer
Date: 2020-09-14 01:01:51
LastEditTime: 2021-03-11 00:27:52
'''
# standard
import models
import utils
import argparse
import torch
import torch.nn.functional as F
import torch.nn as nn
import numpy as np
import copy
import random
import time
import math
from torch.utils.tensorboard i... |
540d7e588fbe855504b8f9fc01fca4bc4035ec4f4f2238d18fad7ea9ff7f83ba | Python | 12,529 | 291 | '''
Description:
Author: voicebeer
Date: 2020-09-14 01:01:51
LastEditTime: 2021-03-11 00:27:35
'''
# standard
import models
import utils
import argparse
import torch
import torch.nn.functional as F
import torch.nn as nn
import numpy as np
import copy
import random
import time
import math
from torch.utils.tensorboard i... |
a9c5e20f613e87e8d72e93cd34fb2a47a4d36746e8a35f48f3ecb07741e92a74 | Python | 12,533 | 301 | import re
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint as cp
from collections import OrderedDict
from torch.hub import load_state_dict_from_url
from torch import Tensor
from torch.jit.annotations import List
__all__ = ['DenseNet', 'densenet121', 'densenet169', 'dens... |
3243cb55fa8d8bae45ff856c92ee936bf0973774a28af38e999ed0ef8f5694b9 | Python | 12,536 | 371 | import logging
import os
from collections.abc import Callable, Iterator, Sequence
from functools import partial
from itertools import count
from pathlib import Path
from typing import Literal, Protocol
import numpy as np
import torch
from rich.console import Console
from torch.nn import CrossEntropyLoss
from torch.opt... |
fd873e673caf48648ccc86848e68a87c8283ababb660567fa35da92e7d8aa11f | Python | 12,537 | 357 | import os
import random
import time
from pathlib import Path
import numpy as np
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
import webdataset as wds
import yaml
from torch import optim
from torch.distributed.algorithms.join import Join
from torch.nn.parallel import DistributedDataP... |
f9e05f0d433280576296393524d7c6bda7daf9fecf392bde45264e7316019b65 | Python | 12,538 | 226 | """The retired build's two master-table checks, replayed over the whole corpus and accounted for.
`tests/unit/test_legacy_qc_parity.py` proves the two builds agree on one constructed record per
failure mode. This proves it on all 192,793 records, which is the half a fixture cannot do: a mode
nobody thought to construc... |
2924c617de0d8995cb4612c57f2b4c8913946c8cdeaffd9736a8ab4c9c1447f5 | Python | 12,543 | 363 | # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Un... |
8775192afae56651d3316b6b01d18c5d975da2681702975d4c821e83edc12531 | Python | 12,559 | 384 | ###########################################################################################
# Radial basis and cutoff
# Authors: Ilyes Batatia, Gregor Simm
# This program is distributed under the MIT License (see MIT.md)
###########################################################################################
import... |
a1a4f06c2906d7fc56a5e9d2a3e9306e478e7213777f34094edcc4bbb4fcd108 | Python | 12,564 | 312 | import copy
import torch
import numpy as np
import torch.nn as nn
from torch_geometric.loader import DataLoader
from sklearn import preprocessing
class LogReg(nn.Module):
def __init__(self, ft_in, nb_classes):
super(LogReg, self).__init__()
self.fc = nn.Linear(ft_in, nb_classes)
self.sigm ... |
07e11b0e35f7408f9d987a787f7609d5939bb1b01ffcb17dbbb572ec37bc412d | Python | 12,574 | 352 | """
Implementation of dFC methods.
Created on Jun 29 2023
@author: Mohammad Torabi
"""
import time
import numpy as np
from joblib import Parallel, delayed
from scipy.special import softmax
from sklearn.cluster import KMeans
from sklearn.preprocessing import StandardScaler
from ..dfc import DFC
from ..dfc_utils impo... |
a9a529484792201bef0b0db0b607366a2d907f39c3e945147e647de28e1cbfeb | Python | 12,586 | 302 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
import os
import shutil
import socket
import torch
import lightning
from lightning.pytorch.callbacks import Callback
from nequip.train import NequIPLightningModule
from nequip.utils import RankedLogge... |
05d604a0063fdbb85fa23e2df3bfc88758370a4924664885ca544f24ef6beb08 | Python | 12,595 | 362 | import jax.numpy as jnp
import numpy as np
import jax
from functools import partial
import sklearn.metrics
from statistics import mean
import logging
import plasticity.data_loader as data_loader
import plasticity.utils as utils
import plasticity.synapse as synapse
def initialize_params(key, cfg, scale=0.01, last_laye... |
0a6fe990e253cae419cdb2aec198596d8af0fed33e5a3f4f0eb0429d0b7a0810 | Python | 12,604 | 333 | from __future__ import annotations
import itertools as it
import os
from pathlib import Path
from typing import Iterable
import more_itertools as itx
import pytest
from hypothesis import assume, example, given
from hypothesis import strategies as st
from pathvalidate import Platform, is_valid_filename, is_valid_filep... |
7dbf2a637fb6bd3643487e8f024fcf01ec01f84e1a23a587d51cd89de611c55d | Python | 12,614 | 335 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import time
import pickle
import numpy as np
import pandas as pd
from sleeprnn.common import constants
from sleeprnn.data import utils
from sleeprnn.data import stamp_correction
from sleeprnn.data.d... |
e354964e0d77a7d39466835ee664442b19db791b3493ccc82c2dce89cec2c13d | Python | 12,614 | 288 | # Copyright 2020 Forschungszentrum Jülich GmbH and Aix-Marseille Université
# "Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements; and to You under the Apache License, Version 2.0. "
import numpy as np
import time
from threading import Lock, BoundedSemaphore
from nest_el... |
903a5c55adee6346c1e8ec095b82a5a4caf3a08467ced077157562ba24effba0 | Python | 12,616 | 302 | #Based on https://pytorch.org/vision/0.8/_modules/torchvision/models/densenet.html
import re
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint as cp
from collections import OrderedDict
from torch.hub import load_state_dict_from_url
from torch import Tensor
from torch.jit.a... |
f09137623b45e555c1fc62ca5a8aa3949260b3a41b58ac1d080808c0a7f92f9d | Python | 12,635 | 342 | import torch
import sympy as sym
import numpy as np
from scipy.optimize import brentq
from scipy import special as sp
def Jn(r, n):
"""
numerical spherical bessel functions of order n
"""
return sp.spherical_jn(n, r)
def Jn_zeros(n, k):
"""
Compute the first k zeros of the spherical bessel fu... |
a147594e3ea70bef0a4e7f3a3d0d8034b3800c945d92bea9a1c66b6841e0c4b4 | Python | 12,640 | 349 | # Based on the code from: https://github.com/TUM-DAML/gemnet_pytorch
# https://github.com/TUM-DAML/gemnet_pytorch/blob/master/gemnet/model/layers/basis_utils.py
# https://github.com/TUM-DAML/gemnet_pytorch/blob/master/gemnet/model/layers/basis_layers.py
import math
import torch
import sympy as sym
import numpy as np
f... |
9bcb295e4fd3883526eab984bb194bf7f5059d20ea4840fdce2857f8dc8dbd44 | Python | 12,658 | 458 | """Automatic differentiation in PyTorch."""
import functools
import torch as _torch
from torch.autograd.functional import hessian as _torch_hessian
from torch.autograd.functional import jacobian as _torch_jacobian
def _get_max_ndim_point(*points):
"""Identify point with higher dimension.
Same as `geomstats... |
747835fb7e0f74f4ece535aeec4dd87ae75104f2c47f39b7a6ffd9106bae8fce | Python | 12,663 | 334 | # Copyright 2020-2025 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""DirectorClient module."""
import logging
from pathlib import Path
from typing import Any, Dict, Iterator, Optional, Tuple, Union # type: ignore
import grpc
from grpc._channel import _MultiThreadedRendezvous as DataStream
from openfl.e... |
4612c14933c4419d6065d3be2b267ad765b27939c476c74253f63931fbf2f03d | Python | 12,664 | 320 | # Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Un... |
6c24e9b480eee74b1801432d3810678e34e492360518380ded3db132923838e8 | Python | 12,665 | 422 | import os
import time
import hdf5storage
import numpy as np
import scipy.io as sio
from functions.dFC_funcs import *
os.environ["MKL_NUM_THREADS"] = "64"
os.environ["NUMEXPR_NUM_THREADS"] = "64"
os.environ["OMP_NUM_THREADS"] = "64"
################################# Parameters #################################
#####... |
f74dd4724a3488ef8da211f9e5c76c4c6aa43e49d638a2b445023f5668ed1980 | Python | 12,668 | 410 | """Utility functions used throughout the rest of the package."""
import warnings
import numpy as np
import pandas as pd
import xarray as xr
from scipy.spatial.distance import cdist
from scipy.stats import norm
from sklearn.linear_model import LinearRegression
try:
import holoviews as hv
except ModuleNotFoundError... |
0b6e297040c820ea5de7aff689209b6754d0fb99a1b01d26a622466f94d89173 | Python | 12,676 | 254 | """The curation skills, checked against the build they instruct a curator to drive.
A skill is an instruction document an agent loads and follows. Nothing executes it, so nothing fails
when it goes stale, and these six went stale in a way that mattered: they were written against
``py_src/``, which phase 4 deleted, and... |
47196ca9dddb6f5b870c8984adb55a109e5bfc49183c7928eb72301a96e2fb6c | Python | 12,677 | 320 | """mass_kc.py: Defines the MASS class that manipulates the MASS database."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import time
import numpy as np
import pyedflib
from sleeprnn.common import constants
from sleeprnn.data import utils
fro... |
6e04a46ea2c63ec4be257e298010207ece86497dca5b3ecc3d2be72e657c9002 | Python | 12,689 | 388 | # Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: MIT-0
"""
DGL implementation of GVP and GVP-GNN (without the autoregressive functionality)
modified from source: https://github.com/drorlab/gvp-pytorch/blob/main/gvp/__init__.py
"""
import functools
import torch
from torch i... |
a3837e57199cb65791433926e1b18437481b5053bd4a3a0911c30af715013414 | Python | 12,696 | 449 | import time
import multiprocessing as mp
import pylsl
import numpy as np
from .. import logger
from ..triggers import TriggerDef
from ..utils.io import read_raw_fif
from ..utils.preprocess.events import find_event_channel
class StreamPlayer:
"""
Class for playing a recorded file on LSL network in another pr... |
172bb6d39f2d7995e63dfa31009c038dc8e9c230f770473b29c6c97ef9848b12 | Python | 12,698 | 199 | """Cluster metrics, vendored from TCREMP with exactly one deliberate divergence.
⚠ **The one divergence is the tie-break in :func:`binominal_test`, and it is a correctness fix.**
Upstream assigns each cluster its majority label by sorting on ``fraction_matched`` alone and keeping
the first row, so a cluster split even... |
aca5c702d46a6a4b96f243a0acff1ed86e9bc7d3342c188e1e15bd5aef99223b | Python | 12,704 | 375 | """Implementation of sub-Riemannian geometry.
Lead author: Morten Pedersen.
"""
import geomstats.backend as gs
class SubRiemannianMetric:
"""Class for Sub-Riemannian metrics.
This implementation assumes a bracket-generating distribution of constant dimension.
Only one of the arguments 'cometric_matrix... |
bdf76e7450bfa8b7212a7a5064ee8f37dec500631d292a4403168cfe3f778b78 | Python | 12,710 | 300 | """ ICC analyses
First, threshold the entire matrix at 95th percentile.
So now we have 4 matrices: the original ones, and the thresholded ones.
Results to compute:
- Overlap between windows (ICC or Jaccard Coefficient) at a whole brain level
- Proportion of edges by network + test within window of proportion
First... |
df28a891c4830bf98cd5fa746e342b2a67fe48c4da092f862d2a3c95d5dafba5 | Python | 12,712 | 354 | # simpleCPP_test.py - Testing JAGS fits of a non-hierarchical Neural-DDM model
# in JAGS using pyjags in Python 3,
# assumes CPP slopes are generated from drift rates
#
# Copyright (C) 2022 Michael D. Nunez, <m.d.nunez@uva.nl>
#
# This program is free software: you can redistribute it and/or modify
# it under the terms... |
b0e767d11490154e14fa73d22dd747e4a15e6054e8d2b7c5811553b6a3030e36 | Python | 12,718 | 391 | from collections import namedtuple
from random import shuffle
import numpy as np
import torch
import tqdm
from Bio.SVDSuperimposer import SVDSuperimposer
from scipy.spatial import cKDTree
from model_angelo.utils.misc_utils import setup_logger
def get_fit_report(input_cas, target_cas, max_dist=5, verbose=False, two_... |
adc7d0d5a2bd0f08b61e62c29c95bcf09bfa219de4d727a9ab6517863178ed39 | Python | 12,727 | 364 | import os
import matplotlib.pyplot as plt
import numpy as np
import random
import shutil
from skimage import io
import math
from PIL import Image,ImageDraw
import cv2
def data_split(source_path:str, dest_path:str , train_ratio=0.8, test_ratio=0.1, val_ratio=0.1, shuffle=True):
'''
This function s... |
70c1426ef95296a85be59bfd6fae48675cc763dbe2e710364ec56a8f9a1661d7 | Python | 12,729 | 390 | import torch
import time
import torch.nn as nn
from torch.nn.parameter import Parameter
import os
import pathlib
import copy
from scipy import ndimage
import numpy as np
import artificery
import torchfields
from metroem.finetuner import optimize_pre_post_ups
from metroem import helpers, masks
def finetune_field(
... |
8472114826627c0fc7e50ec86fa9864f80f580ead20cae55bf70397b992713b2 | Python | 12,730 | 376 | # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... |
7cf271213c29300eeebbdd00c5939f3bd589b9f5c49cf5d78e1529ae1bd1e502 | Python | 12,735 | 340 | ## __doc__="""
## this sctrip is using for Shape-Map which seem no difference between
## SC or BULK
##
## the update of version 1.5
## cutadapt twice to remove the internal adapter which ligated which reverse transcript
##
## the change in version 2.5:
## 1) change to zy made reference
## 2) bowtie... |
fe23c4c70d925b2a3e95cf173744eb4b1f14253aed063ec93cefd0bfaf0dd8e3 | Python | 12,735 | 336 | """
You are standing in an open field west of a glass building, with a sliding electric front door.
There is a small mailbox here.
> Open mailbox.
There is a letter.
> Read letter.
-------------------------------------------------------------------------
Welcome to ModelAngelo! Have a look around...
This is the build c... |
8b1429849db83c0a027538ee8fc223e6e9a719b6b590261e37e3fbf63dbadae9 | Python | 12,740 | 351 | # recovery_test.py - Testing JAGS fits of HDDM models in JAGS using pyjags in Python 3,
# This hierarchical model is usuaully appropriate for trials with intermixed experimental conditions
#
# Copyright (C) 2020 Michael D. Nunez, <m.d.nunez@uva.nl>
#
# This program is free software: you can redistri... |
d829d889dcd75ac1b06b67659eab09088aa16de390e720d88a1e1ec0923ad06a | Python | 12,740 | 297 | '''
Description:
Author: voicebeer
Date: 2020-09-14 01:01:51
LastEditTime: 2021-03-16 06:00:49
'''
# standard
import models
import utils
import argparse
import torch
import torch.nn.functional as F
import torch.nn as nn
import numpy as np
import copy
import random
import time
import math
from torch.utils.tensorboard i... |
6b797113544f49c660a2d08abdea3f53db4ceddd7661ce8470943e25d88f05d3 | Python | 12,749 | 393 | from tests.helpers import REPO_ROOT
import os
import subprocess
import sys
from pathlib import Path
import numpy as np
from ase import Atoms
from ase.build import molecule
from mace.calculators import MACECalculator
def test_run_train_with_elec_temp(tmp_path):
"""Test run_train.py with electronic temperature em... |
7d15871104e9d29d6fe8538e8974af5704ded6d8aef622fa6b35ea05ffddf8f0 | Python | 12,761 | 242 | import os
import torch
import hydra
from omegaconf import OmegaConf
from torch_geometric.utils import add_remaining_self_loops
from sklearn.metrics import accuracy_score, roc_auc_score
from benchmarks.xgraph.utils import check_dir, fix_random_seed, Recorder
from benchmarks.xgraph.gnnNets import get_gnnNets
from benchma... |
21ad898f889b61a219947cc904ea0f949c0808d6167fe019c32372d6fe0d6d36 | Python | 12,768 | 421 | """Run the default preprocessing pipeline on soarrKULee."""
import argparse
import datetime
import gzip
import json
import logging
import os
from typing import Any, Dict, Sequence
import librosa
import numpy as np
import math
import scipy.signal.windows
from brain_pipe.dataloaders.path import GlobLoader
from brain_pip... |
9767a30539d2c82f96cfc63aa6e6550f9cf051481ab58d19e7c06f03775bfc24 | Python | 12,769 | 306 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import sys
import warnings
from pathlib import Path
from tqdm import tqdm
import json
# Computational stuff
import numpy as np
import matplotlib as mplb
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpecFromSubplotSpec
# TensorPAC
from t... |
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