sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
00e49322a58f0560e46701d74f19f176c14c213671fa81a5007d43b568c7b738 | Python | 15,766 | 319 | import os
import torch
import hydra
from omegaconf import OmegaConf
from sklearn.metrics import roc_auc_score
from dig.xgraph.method import PGExplainer
from dig.xgraph.evaluation import XCollector
from dig.xgraph.method.base_explainer import ExplainerBase
from dig.xgraph.utils.compatibility import compatible_state_dic... |
c8ef0d1d25ddecbcb35c4e703422282098b0c8ba577596c9936510137de45de0 | Python | 15,770 | 345 | # 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. "
from mpi4py import MPI
import numpy as np
from nest_elephant_tvb.transformation.communic... |
0106b6cb4701a0264c005d691e4dd887ec9b78107572977c14f7f939308fcf3e | Python | 15,774 | 484 | from torch_cluster import radius_graph
from torch_geometric.nn import GraphConv, GraphNorm
from torch_geometric.nn import inits
from torch_scatter import scatter, scatter_min
try:
from ocpmodels.common.registry import registry
from ocpmodels.common.utils import conditional_grad, get_pbc_distances, radius_grap... |
a345b44e8673513de922d939860af46fceac4524c40906eb4a29ec8b2d523f4a | Python | 15,788 | 444 | # 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... |
195a32e084975fea55a85bd7f5aee31c87d4df693d6744dab37d2313b8d838c5 | Python | 15,810 | 467 | #cript containing the modular version of the code
# so far we have only implemented the non_linear_embedding layer
# for simplicity we can just use dense layers for the merge operations
import numpy as np
# import matplotlib.pyplot as plt
import torch
import h5py
import torch.nn as nn
import torch.nn.functional as F... |
a4bb447b72e249b12980bb2054a894c3123bb2111c11ef1eea0d4cb5180063cd | Python | 15,811 | 445 | # ==============================================================================
# Copyright 2025 Technical University of Denmark
# Author: Nikolas Borrel-Jensen
#
# All Rights Reserved.
#
# Licensed under the MIT License.
# ==============================================================================
import collectio... |
824964960d43f871b008ac15ab0767473dd418c50103e5c6cd07143cb4fa51b4 | Python | 15,813 | 482 | # Copyright 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""Workspace module."""
import logging
import os
import shutil
import subprocess # nosec
import sys
import tempfile
from hashlib import sha256
from pathlib import Path
from typing import Union
from click import Choice, echo, group, optio... |
4c4fb21fde665624ab71259cb2e15f65c91c3a9305f503cfa2fc745d02725263 | Python | 15,834 | 386 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Dec 9 10:35:43 2018
@author: ngritti
"""
import numpy as np
from matplotlib import pyplot as plt
from skimage.filters import threshold_otsu
import sys, os,tqdm
from tifffile import imsave
from multiprocessing import Pool
import matplotlib as mpl
impor... |
81da5ec5edfd6749eceb4f7a6f7b82204e9f9faaf3ab639bf3b399806f86e2c2 | Python | 15,857 | 289 | """Publication retrieval and record-level receptor association.
``score``, ``lift`` and ``lift_family`` query publication postings. ``receptor_lift``
uses the definitive record and chain tables to measure assigned epitope associations.
"""
from __future__ import annotations
from dataclasses import dataclass
import p... |
6056a963c2cc01737da41e18106996ec2fcd789f186c0eecaccdbc1f50693c11 | Python | 15,874 | 291 | import numpy as np
import cv2
from scipy import sparse
from skimage.segmentation import watershed
def watershed_CV(img):
'''Apply watershed from OpenCV to further segment the mask "img".
Adapted from [https://docs.opencv.org/master/d3/db4/tutorial_py_watershed.html]
Inputs:
img (2D numpy.nd... |
d9f362776befe1cd0f41d0bc9ece2f5f3e1f9dc7786b50a64a810f5a0325b25a | Python | 15,880 | 448 | import sys
import os
import torch
import numpy as np
from torch_geometric.data.dataset import Dataset
from torch_geometric.data.data import Data
from tqdm import tqdm
import h5py
import copy
from .community_pooling import community_detection, community_pooling
def DivideDataSet(dataset, percent=[0.8, 0.2], shuffle=T... |
9fa6b1be4b18a5c33173bd46e57a9f898e55fd6e50cb12092d19baacde239a45 | Python | 15,882 | 287 | """Reported peptides and allele-conditioned presentation predictions.
Predictions annotate observations; they never rewrite them or supply identity keys.
The reference panel is an explicit, checksum-verified input. No download or stored
calibration is used during assembly. Each supported MHC species/class is scored
on... |
105cad6dab0f8010ca9941aea88dd9559707f6fc73531c5ae4ea1ce6ff63f728 | Python | 15,896 | 348 | #########################################################################
# SlumberNet: Sleep Stage Classification using Residual Neural Networks #
#########################################################################
# This Python script implements SlumberNet, a deep learning model for classifying
# sleep stages ... |
037fd4344ac5ba3c1ee6db435a7e3946f754a76de0aeb8f496241b4e4c92c60d | Python | 15,898 | 407 | import asyncio
import concurrent.futures
import json
import logging
import queue
from pathlib import Path
from collections import defaultdict
import numpy as np
import scipy.io as sio
from ScanImageTiffReader import ScanImageTiffReader
from ..alerts import Alert
from ..analysis.traces import process_data
from ..guis ... |
aae93169cf954171c822d6cc8991830f6633be418d2dee26729f522df8a8e6bf | Python | 15,904 | 424 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# OS stuff
import os
import sys
import warnings
from pathlib import Path
from tqdm import tqdm
# Computational stuff
import numpy as np
import matplotlib as mplb
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpecFromSubplotSpec
from matplotlib impor... |
30c9cbe4f0e1f3d49fd0941440af894ec9de37ea570347359ffd7cba92281af3 | Python | 15,905 | 384 | import torch.utils.data as data
import torchvision.transforms as transforms
from PIL import Image
import os
import os.path
import numpy as np
try:
import accimage
except ImportError:
accimage = None
import pdb
from mapcrop import MapCrop # , MultiscaleMapCrop
from torch.nn import functional as F
import torch
i... |
3f8ad29b76c705ccdd8476e3657f391e7ecd7d93f439e561f674aeaf800bb7ff | Python | 15,909 | 323 | #!/usr/bin/env python3
#
# Sniffles2
# A fast structural variant caller for long-read sequencing data
#
# Created: 15.08.2021
# Author: Moritz Smolka
# Contact: moritz.g.smolka@gmail.com
#
import pysam
import os
from sniffles import sv
from sniffles import util
def format_info(k,v):
if isinstance(v,float):
... |
39dfea27e72aa5b84b07b5fe65d7a71576322551c378d479b646e4c8b2035050 | Python | 15,914 | 399 | import math
import paddle
import numpy as np
import paddle.nn as nn
import paddle.nn.functional as F
from ppdet.core.workspace import register
from ppdet.modeling.initializer import normal_
from ppdet.modeling.lane_utils import Lane
from ppdet.modeling.losses import line_iou
from ppdet.modeling.clrnet_utils import ROI... |
c05afd643fd83bb482ff8d72d4fc80296602d94bfc074063738693172e2b9597 | Python | 15,915 | 503 | import argparse
from typing import Optional
from data.sampler import arguments_sampler
from data.collate_fns import arguments_collate_fn
from options.utils import load_config_file
from data.datasets import arguments_dataset
from cvnets import arguments_model, arguments_nn_layers, arguments_ema
from loss_fn import argu... |
d5d3b56ba9c18fc6fdcb9787b2749806bf1c2e928de4a7db84ac70b0086f0a1d | Python | 15,918 | 456 | from __future__ import absolute_import
import numpy as np
import scipy
import torch
from pysurvival.models import BaseModel
from pysurvival import utils, HAS_GPU
from pysurvival.utils import optimization as opt
from pysurvival.utils import neural_networks as nn
class BaseParametricModel(BaseModel):
""" Base class... |
56888ebab5a4662e10728cfc6c54a5f674d534f660e3c245e04f3d1576a24396 | Python | 15,930 | 458 | import numpy as np
# from brian2.units import *
from scipy.stats import lognorm, norm
from scipy.interpolate import UnivariateSpline
from optimization import slsqpopt, blahut_arimoto, jimbokunisawa
import pickle
import warnings
import os
from matplotlib.pyplot import get_cmap
ELEMENTARY_CHARGE = 1.6e-19
AP_COST = 0.12... |
f0f44dfc59116e34741d3e7db3d5ecd4cf22f8a2cc9714d9fa330404c7e24fc6 | Python | 15,933 | 465 | # -*- coding: utf-8 -*-
#
#
# PyRates software framework for flexible implementation of neural
# network model_templates 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 Cogn... |
7ebaa55f03b5f8da467f0809b57fd5475aa99dcacf0283d931bd82dff1f5f28c | Python | 15,977 | 507 | from anthropic import Anthropic as AnthropicClient
from openai import OpenAI as OpenAIClient
from anthropic.types.message_create_params import MessageCreateParamsNonStreaming
from anthropic.types.messages.batch_create_params import Request
from typing import Dict, List
from tqdm import tqdm
import pandas as pd
import r... |
8fc14f58aea93ef3ce2c3681c144ee59dc61c785ebfb26ae8c15e6f8eec1536e | Python | 16,001 | 271 | """What a chunk does to the database, for the pull request that adds it.
`vdjdb qc` says whether a chunk is well formed. That is a different question from whether it is the
chunk the curator meant to submit, and the second one is answered by comparing it against the corpus
it is joining: a mistyped epitope is perfectl... |
f5731e896d72ca8b652a94ef07c3a71db1a119627d06d6fc41a6435028d75031 | Python | 16,005 | 435 | import warnings
from numbers import Integral, Real
import numpy as np
from joblib import effective_n_jobs
from sklearn.isotonic import IsotonicRegression
from sklearn.metrics import euclidean_distances
from sklearn.utils import check_array, check_random_state, check_symmetric
from sklearn.utils._param_validation impor... |
9136c3d48f7ba6b24222215665f159cd81e24afed8c4c9af17686bd74b6d96df | Python | 16,008 | 474 | import datetime
import hashlib
import hmac
import selectors
import subprocess
import time
import urllib.error
import urllib.parse
import urllib.request
import xml.etree.ElementTree as ET
import uuid
from typing import Dict, List, Optional, Tuple, cast
import pytest
from chromadb.api import ClientAPI
from chromadb.api... |
49418b37c937c34136a4be6b537ddcfb5a49259351106e9f5ce99aac18718778 | Python | 16,045 | 426 | """Bootstrap resampling for `BrainData` — aggregate statistics and Ridge model statistics.
`BrainData.bootstrap` delegates here.
"""
import numpy as np
from .utils import _result_from_array
#: Statistics that reduce `bd.data` directly and need no fitted model.
SIMPLE_STATS = ("mean", "median", "std", "sum", "min", ... |
34ba62a81aa8c0be0e03889e33c28beb42ceb91d8206c5811b0dbc217aed5fc4 | Python | 16,050 | 451 | from __future__ import absolute_import
import numpy as np
import pandas as pd
import random
import scipy
import copy
from pysurvival import utils
from pysurvival.models import BaseModel
# %matplotlib inline
# List of Survival Distributions
DISTRIBUTIONS = ['Exponential',
'Weibull',
'... |
a0493275d9492b6dbf5ef1e01cdda1583e5c195d7b0982811f57aac7aa76a839 | Python | 16,072 | 372 | """The tiny AtomicDipolesMACE anchor reproduces its committed reference.
The energy anchors next door pin an energy assembly. This one pins the other
half of the model zoo: a graph dipole, which is a scatter-sum of per-atom
vectors plus a fixed-charge baseline and shares no arithmetic with an energy.
RET-4 deletes the... |
83323c8a69e9f20bd7546ab70360a2fa41b5aa90d141a6499831ed5973f70892 | Python | 16,083 | 455 | """Tests for the frozen `FitResult` record `BrainData.fit` leaves on `.model`."""
from dataclasses import FrozenInstanceError
import nibabel as nib
import numpy as np
import polars as pl
import pytest
from nltools.data import BrainData, DesignMatrix, FitResult
N_SAMPLES, N_VOXELS = 20, 8
@pytest.fixture
def maps... |
9f4dadde4eeb3847410eeec409866ecb5751c5f0630f54822de26b9fbf732858 | Python | 16,090 | 479 | from numba import jit
import numpy as np
import math
from fimpy.utilities import fast_pearson
import itertools
from fimpy.utilities import to_4d, to_3d
from lightparam import Param
def correlation_map(video: np.ndarray, window_size=(1, 3, 3)) -> np.ndarray:
"""Calculate the correlation map of a video
:param ... |
f13f1eaf334a72e3ca202a0fe56f0eca167d704dbbb0897837205bfe086425ea | Python | 16,097 | 488 | # 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.
from typing import Tuple, List
import torch
import torch.nn.functional as F
from fairseq.models import FairseqEncoder
from fairseq.models.spe... |
ba0ad2b98b750c9e4d5775a70532c3560c675e505ede425712bd96a35557242d | Python | 16,100 | 434 | import inspect
import numpy as np
import pytest
from nltools.data import BrainData
from nltools.data.results import BootstrapResult
from nltools.mask import create_sphere
SUMMARY_FIELDS = ("estimate", "standard_error", "ci_lower", "ci_upper")
# Only `bootstrap` emits these two quality advisories, and the bootstrap ... |
09c037dcf657f78aa738e41a1808426dc788b3cd3650a22fd6635e4156c68f9f | Python | 16,121 | 292 | # Copyright (c) 2018, 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 ... |
5c1522b1790ea3aca89953fa4b71a1c3fc5a2747e01d4998fd3d787c0a1ba69a | Python | 16,125 | 288 | # Copyright (c) 2018, 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, Moun... |
4f14729d94d4b4d09e1a49bbd8fe533f267606e82153296ebffea7f4185f7f36 | Python | 16,146 | 460 | """The n-dimensional hyperbolic space.
The n-dimensional hyperbolic space embedded with
the hyperboloid representation (embedded in minkowsky space).
Lead author: Nina Miolane.
"""
import math
import geomstats.algebra_utils as utils
import geomstats.backend as gs
from geomstats.geometry._hyperbolic import _Hyperbol... |
bc56a9fb162b878d274e2cdf787aa441e62370c344b98f1829c9b8117a8dad44 | Python | 16,147 | 453 | import numpy as np
import xarray as xr
from unittest.mock import patch, create_autospec
from numpy.testing import assert_allclose, assert_array_almost_equal, assert_raises, assert_warns
from xarray.testing import assert_equal as assert_xr_equal, assert_allclose as assert_xr_allclose
from testtools import assert_array... |
b9532e79090b9e3e291f28f947759a9bcf416ca88ee51c02b2b44c543e765330 | Python | 16,148 | 476 | """A Python class containing an implementation of MPPCA denoising for magnitude and/or phase images.
Inputs are a 4D image with dimensions (X x Y x Z x N)
Usage:
import mpcomplex as mp
imgdn, sigma, nparameters = mp.denoise(img, kernel=[5, 5, 5], shrinkage='frob', algorithm=veraart)
... |
e5186eefcb92162d76c89ed2ea0da07a753f6ca9963d241882aa1d7716a24e68 | Python | 16,156 | 389 | #/usr/bin/python
from __future__ import print_function
import argparse
import torch
import pickle
import numpy as np
import os
import math
import random
import sys
import matplotlib.pyplot as plt
import data
import scipy.io
from os.path import normpath, basename
from torch import nn, optim
from torch.nn import... |
8a705bb2e029ce43bc136bafb7ace2aa374b61677a0619b014cc66342ba23c57 | Python | 16,178 | 376 | import os, torch, json, ast
import os.path as osp
import ssl
from itertools import repeat
import numpy as np
from rdkit import Chem
import pandas as pd
import networkx as nx
from six.moves import urllib
from torch_geometric.data import Data, InMemoryDataset, download_url
bond_type_to_int = {Chem.BondType.SINGLE: 0, Ch... |
dfdee6c6a6a7f8eb94e3dc753a8fbc15480277fdd8ddc2f4546eb33992f82b1b | Python | 16,183 | 343 | import torch
import torch.nn.functional as F
from torch_scatter import scatter_mean, scatter_softmax, scatter_add, scatter_sum
from torch_geometric.nn import MessagePassing, GCNConv, NNConv, GINConv
from torch_geometric.utils import degree
import numpy as np
class MLP(torch.nn.Module):
def __init__... |
dfc25971f35ac826b26a8dd36eca7baf25abddac6ac4b011696f5f874026dd80 | Python | 16,186 | 390 | #!/usr/bin/env python3
#
# Sniffles2
# A fast structural variant caller for long-read sequencing data
#
# Created: 29.08.2021
# Author: Moritz Smolka
# Maintainer: Hermann Romanek
# Contact: sniffles@romanek.at
#
import logging
from collections import defaultdict
from dataclasses import dataclass
import s... |
b16fd7869c1fbe273e25310dfa97ff8c261d314784b86019346ff01c9365feb2 | Python | 16,199 | 413 | """Unit tests for mace/tools/finetuning_utils.py.
Builds two small ScaleShiftMACE models in-process (no network, no
pretrained checkpoints): a "foundation" over elements [1, 6, 8] and a
target over the subset [1, 8]. Checks that load_foundations_elements
transfers weights (element-subselected embeddings, scale/shift,
... |
f80f0a3bb75ea81422a20bb61ba2b1f6e6cbbb88d8a630d75813355aec878ca0 | Python | 16,214 | 408 | import argparse
import glob
import importlib
import os
import numpy as np
import shutil
import mne
import tensorflow as tf
import matplotlib.pyplot as plt
from data import load_data, get_subject_files
from model import TinySleepNet
from minibatching import (iterate_minibatches,
iterate_batch_... |
eb376ae8f5d95c1513e93e5258c30f7fb3443c4dfe3b7664d9c3913c71e0ab06 | Python | 16,216 | 474 | import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, TensorDataset
from torchvision import datasets, transforms
import utils as u
logger = u.getLogger(__name__)
class AngleDataset(TensorDataset):
def __init__(
self,
num_samples=100,
num_targ... |
ae5b5b82f0f69f6306ee9bb0ea4839e9fb3055b558e4467a2413807cd988d551 | Python | 16,219 | 469 | # Script containing the modular version of the code
# so far we have only implemented the non_linear_embedding layer
# for simplicity we can just use dense layers for the merge operations
import numpy as np
# import matplotlib.pyplot as plt
import torch
import h5py
import torch.nn as nn
from torch.utils import data
... |
7a8f06f5f6dcfedca545496e3b4156a551927b4a225677d4c0b03125c7268621 | Python | 16,220 | 287 | """Fit v3.2a/b offline from declared inputs, keeping assay data private.
Set TCRVDB_PATH or pass --tcrvdb-path. The selected-records CSV (or test.csv
member of a ZIP) uses anchor-inclusive junctions. No source paths or identities
are written into model parameters. Inputs are read anew on each invocation.
"""
from __fu... |
99e7710538f6af7e63c2fb96907e7925d4b6586a9326b92515ad35531e972481 | Python | 16,240 | 434 | """A Python class containing an implimentation of MPPCA denoising.
Inputs are a 4D image with dimentions (X x Y x Z x N)
Usage:
import mpdenoise as mp
imgdn, sigma, nparameters = mp.denoise(img, kernel=[7,7,7], M=60, shrinkage='frobenius')
LICENCE
Authors: Benjamin Ades-Aron (... |
0adaa9094e38383fa14393bc9615b78657c103297c22f4fa57e1f455940cdfea | Python | 16,254 | 337 | # 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
#
# Unless required ... |
b9031e4e5d3af1f16fb0048be43b92019d6d21a33100e33ac81981a960615f35 | Python | 16,254 | 490 | import numpy as np
import cv2
import copy
def decode_image(im):
im = np.array(im)
img_info = {
"im_shape": np.array(
im.shape[:2], dtype=np.float32),
"scale_factor": np.array(
[1., 1.], dtype=np.float32)
}
return im, img_info
class Resize(object):
"""resiz... |
341883a57e4d06bb2c28ce633182feaf287feebeaf14cd532cec8862bd8a7c1b | Python | 16,261 | 437 | """Mutation and numerical contracts for BrainData result ownership."""
from copy import copy, deepcopy
import nibabel as nib
import numpy as np
import pandas as pd
import polars as pl
import pytest
from nilearn.maskers import NiftiMasker
from nltools.data import BrainData, DesignMatrix
from nltools.data.braindata.ut... |
d2463ef0ed130215ad7c89adbdaa3cc07a4ce0e35ac11eea59710cd04274fa13 | Python | 16,290 | 487 | # copyright (c) 2023 PaddlePaddle Authors. All Rights Reserve.
#
# 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 applica... |
fbfe9e378f7c7278ef0b4ee1bcb95346ba9f9047139ccca5af5429b130f8a6a8 | Python | 16,305 | 506 | import math
import geomstats.backend as gs
from geomstats.test.data import TestData
from .base import VectorSpaceOpenSetTestData
from .matrices import MatricesMetricTestData
from .pullback_metric import PullbackDiffeoMetricTestData
from .riemannian_metric import RiemannianMetricTestData
SQRT_2 = math.sqrt(2.0)
LN_2 ... |
737586ecf1392665e596291cf5e313ecccbbaac7275734d023996e470271e8f1 | Python | 16,319 | 430 | import torch
import torch.nn as nn
from torch.autograd import Variable
import numpy as np
import six
import copy
from collections import defaultdict
from pdb import set_trace as st
from metroem import helpers
from metroem.masks import get_mse_and_smoothness_masks
from metroem.alignment import align_sample
def lap(fi... |
0fc5e43a8d43e812db372587114b8299987097a12220bd791b342b8691b496e5 | Python | 16,322 | 486 | """Tests for pandas-backed Plot FI summary calculations."""
import warnings
from types import SimpleNamespace
from typing import Any
from unittest.mock import Mock
import numpy as np
import pandas as pd
import pandas.testing as pdt
import pytest
from qtpy import QtCore, QtWidgets
from sanpy.interface.plugins.plotFi ... |
6a10f86afe41f138fe9892c95af8da1fffb4765f492b1ec1d4dec72b6de4d10d | Python | 16,342 | 486 | # -*- coding: utf-8 -*-
#
#
# PyRates software framework for flexible implementation of neural
# network model_templates 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 Cogn... |
60cdd4da07585a2138f4f3d3c51ba4d8fb9818ac2bb670d96401adc0109f35c3 | Python | 16,343 | 399 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
import math
from e3nn import o3
from nequip.data import AtomicDataDict
from nequip.nn import (
GraphModel,
SequentialGraphNetwork,
ScalarMLP,
PerTypeScaleShift,
ConvNetLayer,
F... |
0e9ad551f63c0c1cb5a2b1c7d7784475599d8eb40093f429680330d1a31f1463 | Python | 16,347 | 267 | """Paired-junction model associations and optional complete variable-domain proof."""
from __future__ import annotations
import os
import tarfile
from pathlib import Path
import polars as pl
from .master import HASH_FIELDS
CONTEXT = ('species', 'antigen.epitope', 'mhc.a', 'mhc.b', 'mhc.class')
IDENTITY = ('species'... |
1473df957614c641b3910b7ec58a9cbb81e4a840302303965221d3fb1924cc8f | Python | 16,382 | 474 | """
Script to sample from a trained diffusion model
"""
import multiprocessing
import os, sys
import argparse
import logging
import json
from pathlib import Path
from typing import *
import numpy as np
import pandas as pd
import mpl_scatter_density
from matplotlib import pyplot as plt
from astropy.visualization import... |
3fa10f48a496b0a6811c2436430e6f37d89e9d0732effbf8c41905e59bfc8502 | Python | 16,387 | 468 | # 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
#
# Unless required by ap... |
4444ee0f8ed0641e1d26647be3e6e581d5495a5c27d5cf60b8a40d5a491d8109 | Python | 16,391 | 473 | # 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... |
661c6fd2cf1027e8cc6c5f84f17bedb7d944b95cda804a14bff0a28866d03571 | Python | 16,397 | 381 | import torch
import torch.nn.functional as F
import torch.nn as nn
import ISNetFunctions
import LRPDenseNet
import pytorch_lightning as pl
import warnings
from collections import OrderedDict
import numpy as np
from torch.autograd import Variable
import torch.autograd as ag
import torchvision
import sys
sys.path.append... |
210918866ac1934bec08486efa3d8ff374a555305e23aca844eafc9f2f61ae0a | Python | 16,398 | 463 | import pytest
import itertools
import renderapi
from test_data import (render_params,
montage_raw_tilespecs_json,
montage_parameters)
from bigfeta import bigfeta
from bigfeta import solve
import json
from marshmallow.exceptions import ValidationError
import copy
import os
i... |
5ec46d4110a4ede4c804ea3d3ddc1e8b861504cbca1f9b202872727eb8fba62f | Python | 16,404 | 379 | """The published foundation models reproduce their committed references.
Three artifacts, two tiers. The tracked MACE-MPA-0 medium checkpoint is in
this repository, so `mace_mp()` with no model argument short-circuits to it
and touches no network: that golden carries no marker and runs on every pull
request, on all fo... |
14ad9836c11612fe95b6df436b71798a0a0580ab30335571885c3c2cf6cdd053 | Python | 16,409 | 442 | """
Code to convert from angles between residues to XYZ coordinates.
"""
import functools
import gzip
import os
import logging
import glob
from collections import namedtuple, defaultdict
from itertools import groupby
from typing import *
import warnings
import numpy as np
import pandas as pd
import biotite.structure... |
78018af68c7bab82887bb868aff27a24162b1cc5c7f68432beac9648d9ef6a17 | Python | 16,409 | 356 | """
reproduce RF, SVM from https://github.com/nsf-c-cas/yield-rxn/blob/master/scripts/ML_models_testing.py
"""
import argparse
from utils_ds import *
import pickle
import pandas as pd
import numpy as np
import warnings
from collections import defaultdict
import random
from sklearn.ensemble import RandomForestRegressor... |
cf05bdec00fcaeb180a4849b14d5b9334eda0d31dbb500d42b9b0d28b3ca4da4 | Python | 16,411 | 449 | # Copyright 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""AggregatorGRPCClient module."""
import logging
import time
from typing import Optional, Tuple
import grpc
from openfl.protocols import aggregator_pb2, aggregator_pb2_grpc, utils
from openfl.protocols.aggregator_client_interface import... |
666a946bc5edff7d06b6525945c6f9592c29a809a91b4c9374a1bd507c1790f2 | Python | 16,423 | 346 | import tensorflow as tf
import variational.layers as variational_layers
import variational.activations as variational_activations
from common.models.local_pooling import VariationalMaxPool2D
class VariationalConvBlock(tf.keras.layers.Layer):
def __init__(self,
filters,
use_bias... |
162736d390a8cf9290c9219f093174aebadd1e15a637987faaa6fb97b2b620c7 | Python | 16,441 | 470 | # copyright (c) 2021 PaddlePaddle Authors. All Rights Reserve.
#
# 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 applica... |
8e1ed150d4c214e6e6fbbbd4f59d742830d9e49b198072c6af7ce780b4f1fcee | Python | 16,444 | 289 | """Instantiate experiment object for imgae data.
This file runs the experiment with code designed specifically for image data;
i.e., the feature attribution is performed on pixels.
"""
import enum
from typing import Any, Callable, Optional
import numpy as np
import pandas as pd
from sklearn.model_selection import tr... |
c42e4bf99b6e7134832870f5ab53eddec96267cf87fb5fe5b02b533f20842402 | Python | 16,458 | 385 | from evaluation import community_detection, link_prediction
from input_data import create_adjacency
from louvain import *
from model import GCNModelAE, GCNModelVAE,GCNModelVAE3D
from optimizer import OptimizerAE, OptimizerVAE
from preprocessing import *
from sampling import get_distribution, node_sampling
import numpy... |
61cff94e25c22a79c659eaf95d412e4cbcb3087616355fecf689d2a750ac569b | Python | 16,466 | 397 | # 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... |
77b4317ca6599d251ece09973ff0b8fdee536b7b453b7fce6bca52d223831bdc | Python | 16,467 | 494 | import numpy as np
import cv2
import copy
def decode_image(img_path):
with open(img_path, 'rb') as f:
im_read = f.read()
data = np.frombuffer(im_read, dtype='uint8')
im = cv2.imdecode(data, 1) # BGR mode, but need RGB mode
im = cv2.cvtColor(im, cv2.COLOR_BGR2RGB)
img_info = {
"im_... |
10ce875d363388bb14c964cf0e17e13ab5704b1a579f05ca4091c1acaea4d92a | Python | 16,469 | 340 | import numpy as np
# import tensorflow as tf
import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()
import os
'''
follows files:
- P1_stdp_v4_cluster_ILAB.py
- P1_readout_learning_v0_cluster_ILAB.py
completely rewritten version of
- stdp
- output rate learning
combined into one single update func... |
b0b01d792cf6f68f6f264958ac8bfc704130d134e30399f006dd07cdbd01552f | Python | 16,480 | 477 | """
Wrapper class for o3.Linear that optionally uses cuet.Linear
"""
import dataclasses
import types
from typing import Any, List, Optional
import torch
from e3nn import o3
from mace.modules.symmetric_contraction import SymmetricContraction
from mace.tools.cg import O3_e3nn
from mace.tools.scatter import scatter_sum... |
60f61a4e11d90aec47309d493fa29bc57c325dc99bb0c106abf2394240031393 | Python | 16,484 | 500 | # in this script to fellow fairly closely Zou et al
# but the create a equivariant descriptor for each type
# of tree topology from the beggining
# We use a an embedding "across sequences" instead to
# within sequences.
import numpy as np
# import matplotlib.pyplot as plt
import torch
torch.manual_seed(0)
import h... |
31c9b1da0ea50057077338d56898502404429fb05aea583a6a01e1ee0013374f | Python | 16,508 | 333 | import tensorflow as tf
from keras import backend as K
from tensorflow.python.keras import losses
def dice_coeff(y_true, y_pred):
'''Dice coefficient between two arrays.
Inputs:
y_true (tf.TensorArray): GT array
y_pred (tf.TensorArray): Predicted array by CNN
Outputs:
score (tf.... |
b1411ea6627d3a64149cee9439663241a71954c0a73f311e818c27c6ace663cb | Python | 16,509 | 498 | # in this script to fellow fairly closely Zou et al
# but the create a equivariant descriptor for each type
# of tree topology from the beggining
# We use a an embedding "across sequences" instead to
# within sequences.
# this is an optimized version of the lstm network
import numpy as np
# import matplotlib.pyplot... |
3eebee5df43fe2b7a2b83e8e84e76ccc70cce74f45df038f9e99046aebeb7332 | Python | 16,524 | 459 | import tempfile
from typing import Dict, Optional, Type, Iterable
import torch
from .monitors import AbstractMonitor
from .nodes import Nodes, CSRMNodes
from .topology import AbstractConnection
from ..learning.reward import AbstractReward
def load(file_name: str, map_location: str = "cpu", learning: bool = None) ->... |
5bfb59f3bcf782e9a110c7a1bfc0c4f7a5d7694bb3352d2503867237c9b235ec | Python | 16,531 | 474 | import numpy as np
import torch
# we fix the random seed for reproducibility
torch.manual_seed(0)
import torch.nn as nn
from torch.utils import data
import itertools
import json
import sys
import time
from os import path
sys.path.insert(0, '../')
import gc
gc.collect()
device = torch.device("cuda:0" if torch.cuda.... |
596edb0c40dde18ebd5961dcae19ca458606902109da544238ab0e6b6f4815af | Python | 16,532 | 471 | from pdb import set_trace as st
import glob
import h5py
import os
import re
import torch
import torchfields
import numpy as np
from collections import defaultdict
from metroem.alignment import align_sample
from metroem import helpers
class MyConcatDataset(torch.utils.data.ConcatDataset):
def __init__(self, *kar... |
ed1b90ca09ed7fd0a336ca5ffd50a9d6ddf1fb5900116b74c02bb422750f1074 | Python | 16,543 | 383 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
"""
Train a YOLOv5 classifier model on a classification dataset.
Usage - Single-GPU training:
$ python classify/train.py --model yolov5s-cls.pt --data imagenette160 --epochs 5 --img 224
Usage - Multi-GPU DDP training:
$ python -m torch.distri... |
9f639adc21af9f55b1b70ac2d4e85c80ce6a8f42ae0083637ef5cc444a93525c | Python | 16,549 | 326 | import torch
import torch.nn as nn
import numpy as np
from rdkit import Chem
from dig.ggraph.utils import check_valency, convert_radical_electrons_to_hydrogens
from .disgraphaf import DisGraphAF
class GraphFlowModel(nn.Module):
def __init__(self, model_conf_dict):
super(GraphFlowModel, self).__init__()
... |
28e3d44797de2d28db89c17b891cb111ca61fce89510cc3fa3a774146f39a2bd | Python | 16,554 | 444 | import logging
import numpy as np
from qtpy.QtCore import Signal # type: ignore[reportPrivateImportUsage]
from qtpy.QtCore import QEvent, Qt
from qtpy.QtGui import QColorConstants, QIcon, QKeyEvent
from qtpy.QtWidgets import (
QComboBox,
QGroupBox,
QHBoxLayout,
QLabel,
QMessageBox,
QPushButton... |
7f22e1b549011cfed901526dbda3472f4915e2a10a3077dbbbfeb5519a84e78f | Python | 16,554 | 507 | import math
import random
import warnings
import cv2
import torch
import numpy as np
from torchvision import transforms
def gray_scale(image: np.ndarray) -> np.ndarray:
# language=rst
"""
Converts RGB image into grayscale.
:param image: RGB image.
:return: Gray-scaled image.
"""
return c... |
8a504fb670081ac792a2d17afb2e0468eac7b0bc64cc2f99ac78f6ce9df2055a | Python | 16,567 | 448 | #!/usr/bin/env python3
import logging
import math
from typing import Dict, List, Optional, Tuple
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import checkpoint_utils, utils
from fairseq.data.data_utils import lengths_to_padding_mask
from fairseq.models import (
FairseqEncoder,
... |
4992ed23dda7c9a02e9e40f8e24206723d1cc655dd2007937edf1bc11c9f0d30 | Python | 16,568 | 456 | # 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
#
# Unless required by app... |
fd1dcffcb5ae50ef823a4eff17d01810fd406152dbd2ae2a406103e7950e0876 | Python | 16,580 | 192 | # 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 ... |
c05df4681dbc78fee5cfdceacc1f2c644fa20fb09f9af3968451752c8bfff21d | Python | 16,582 | 423 | import sys
import torch
from torch import nn
from torch_cluster import knn_graph, radius_graph
import torch.nn.functional as F
from torch_scatter import scatter_add, scatter_max
import numpy as np
from sklearn.mixture import GaussianMixture
class AttentionModule(nn.Module):
def __init__(self, input_size):
... |
a92ae3150b85869f697c0a101fdcf9c26d0fa8dfd24e1748ecf526e5768804d1 | Python | 16,601 | 524 | """Matplotlib helpers for plotting SanPy recordings and analysis results."""
from typing import Any, Optional, TYPE_CHECKING
import numpy as np
import scipy.signal
import sanpy
from sanpy.sanpyLogger import get_logger
if TYPE_CHECKING:
from matplotlib.axes import Axes
from matplotlib.figure import Figure
... |
4d1c72e046fa03d6ba83f9f0a6b326344963cd5779296c8c9663f999db99cb20 | Python | 16,609 | 368 | import numpy as np
import torch
import torch.nn as nn
import math
from torch.autograd import Variable
import torch.nn.functional as F
from SNN_layers.spike_neuron import *#
## readout layer
class readout_integrator_test(nn.Module):
def __init__(self,input_dim,output_dim,
tau_minitializer = 'unifo... |
4f72cc8eaebc6b11992f2fe787f002aaed737774bb6a5651612e375f21c951d9 | Python | 16,626 | 391 | # Copyright (C) 2020-2023 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""Tensor codec tests module."""
from unittest import mock
import numpy as np
import pytest
from openfl.pipelines import NoCompressionPipeline
from openfl.pipelines import SKCPipeline
from openfl.pipelines import TensorCodec
from open... |
f6a0d315f23a8bb2340a1d285ec3d6fe3bb8b4b56009271e61e9433b4941ba15 | Python | 16,630 | 436 | # 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
#
# Unless required by appli... |
47b1d46b22e1f61ba199ddc8f1b3d41d418cf33aa7d4ada06e40bbdd71a7b7a7 | Python | 16,631 | 416 | # 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
#
# Unless required by appli... |
49e4ce0049f6142c4afbcfd66be0bde575a0d8726b2b6c403d237b86a81c9c63 | Python | 16,631 | 422 | """Recipe for the committed end-to-end training regression set.
``datasets/regression_train.xyz`` is the dataset the legacy-versus-rewrite training
comparison is run on: small enough to train in seconds on one CPU core, and
deliberately *diverse* -- isolated atoms, molecules, slabs and bulk cells, all
three anchor ele... |
b01060ffebbe26d5182613ba2212e1ea3fb6c9a8bb54c686781e025c6efbe259 | Python | 16,634 | 515 | from turtle import clearstamps
import torch
import torch.nn as nn
from torch.utils.data import DataLoader
from torch.utils.data.sampler import SubsetRandomSampler
import numpy as np
import pickle
import time
import os
import sys
file_dir = os.path.dirname(__file__)
sys.path.append(file_dir)
from model import *
try:
... |
5ff5c9145ae4de0e86da33070fa86b899a0ad5356e1ce21b13a2e47f0917215b | Python | 16,639 | 309 | """The epitope catalogue: what VDJdb knows about each antigen, and which MHC presents it.
Two tidy tables, both derived from ``records`` and both shipped:
=============== ================================================= ===============================
``epitopes`` PK ``(antigen.epitope, antigen.species)`` ... |
d5845bee5242229a7411f8e361222e91f648b81309ee9c83cf086f0b7433cf52 | Python | 16,684 | 494 | """Statistical Manifold of Gamma distributions with the Fisher metric.
The natural coordinate system for a Gamma Distribution is:
point = [kappa, nu], where kappa is the shape parameter, and nu the rate, or 1/scale.
However, information geometry most often works with standard coordinates, given by:
point = [kappa, ga... |
88f8626d98fd2c2c3259d77420fa6db75a0439b54d840d52a03cdc7ab711f2cb | Python | 16,685 | 499 | # /// script
# requires-python = ">=3.11"
# dependencies = [
# "marimo",
# "nltools>=0.6.0",
# ]
# ///
# Working with DesignMatrix — marimo notebook. Source of truth for the docs page; rendered to the docs page by scripts/marimo_to_zensical.py.
import marimo
__generated_with = "0.24.0"
app = marimo.App(width=... |
06a56de01bc498b46df709233893a708c052c86e7fbb4e4105681b13c921bae1 | Python | 16,728 | 541 | # ==============================================================================
# Copyright 2025 Technical University of Denmark
# Author: Nikolas Borrel-Jensen
#
# All Rights Reserved.
#
# Licensed under the MIT License.
# ==============================================================================
import os
from p... |
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