sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
493799ced9dd83c64198377a98992f3073f2e14b3dc4c65debd4aed78d2b870a | Python | 21,145 | 526 | # 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 logging
from collections import OrderedDict, namedtuple
import torch.nn as nn
from fairseq import checkpoint_utils, utils
from fairse... |
762648ccca1d8aac1d4a4dae5aed9769defc567b320792b644bbbf5a5b561abd | Python | 21,157 | 643 | import copy
import inspect
import pandas as pd
import numpy as np
from tqdm.auto import tqdm
from pathlib import Path
import torch
import torch.nn as nn
from torch.utils.data import Dataset, DataLoader
from .measures import compute_eta_gauss, compute_rmse, compute_rmsse
from .parse_data import split_by_subject, norm... |
2714f27b467fbc376beefcd76a00821ee366a329a271fe705e8c8bddba936e08 | Python | 21,162 | 487 | #!/usr/bin/env python3
"""
hippie-wf3dacg transductive training script.
Protocol (mirrors the HIPPIE training script exactly):
1. Load all neurons from a C4 H5 file.
2. Precompute 3D ACGs from spike_indices (expensive, done once).
3. Train the hippie-wf3dacg CVAE transductively on ALL neurons for --epochs.
4. ... |
9110ae52b56041b19219a5ec249c0433ab09dd8cbf6d9ad1674677367dab6362 | Python | 21,187 | 561 | # 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 logging
import os
from dataclasses import dataclass, field
from typing import Optional
from collections import OrderedDict
import nump... |
b7cbc391874b2dac41fbf81f6db9d8d2783b71b53e99c0ac5b136451ce70c1b6 | Python | 21,187 | 549 | # ------------------------------------------------------------------------------
# Copyright (c) Microsoft
# Licensed under the MIT License.
# Written by Bin Xiao (Bin.Xiao@microsoft.com)
# Modified by Ke Sun (sunk@mail.ustc.edu.cn)
# ------------------------------------------------------------------------------
from ... |
1a52816498442939bc5302d6ca25ec480bd16c8f54e5a1094f36103270a1bdb1 | Python | 21,194 | 642 | """Maintained GPN-Star inference operations."""
from __future__ import annotations
from pathlib import Path
from typing import Any
import numpy as np
import pandas as pd
import torch
from datasets import Dataset, disable_caching
from jaxtyping import Float, Int
from torch import Tensor
from transformers import AutoM... |
f288321afab713c1066cb949188e7f0141fb38253a61526d7c995166d0f2755e | Python | 21,211 | 513 | from math import gamma
import os
import json
import copy
from typing import Optional, Tuple, Union
import torch
import torch.nn.functional as F
from dataclasses import dataclass
import torch.nn as nn
from torch.nn import CrossEntropyLoss
from torch.nn.modules.sparse import Embedding
from transformers import PreTrainedM... |
5b4d8c692c2c429c5f30363198514618cc05f8ef86afd9a08328bfc4bf569785 | Python | 21,221 | 463 | # -*- coding: utf-8 -*-
"""Standalone Figure 12 generator for slippage sensitivity heatmaps.
This script reads phi_total.npy, computes the same hydraulic-radius proxy used
in app.py Step 5, samples active throat radii, and writes the formatted Figure 12
PNG/PDF outputs without importing Streamlit or torch.
"""
import... |
12352145b7aeed48b4854e90151f0be490d6a2e43d174191b3e6234345f09579 | Python | 21,237 | 490 | #!/usr/bin/env python3
"""Render Figure 6 panels (CVAE-only generative experiments).
Mirrors the original paper plot (final_paper_figures/.../figure_6_paper.py).
Four panels, written as separate files into --out (default: figures/figure_6/):
panel_a_cross_species.{svg,png} — 3 cell types (GoC/MLI/PkC_ss) × 3
... |
129cb8bdc1b6b74260d2edebfee3dcd396ff2f62627d0a26ac1d98dd7e38885a | Python | 21,243 | 576 | # %%
"""Train and save source-separation GRU models.
It can reproduce the main training
conditions by switching ``--condition``:
* ``mine_l2``: MINE penalty + L2 regularization, saved as model_<id>
* ``l2_only``: no MINE penalty + L2 regularization, saved as model_nm<id>
* ``mine_no_l2``: MINE penalty without L2 reg... |
edc7d278803bba41626eacd050d91d7247f1c5999f9dceb99a8877e238bc73d6 | Python | 21,261 | 633 | #!/usr/bin/env python
#
# Copyright 2005 Google Inc. All Rights Reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of... |
30fcd6d415ec45c8e4c1112bf4b4b6c6bbe910b7616ad7a38acc59d8b7ac4639 | Python | 21,293 | 654 | """Tracking must be invisible when off and harmless when it breaks."""
import os
import pathlib
import subprocess
import sys
import types
import warnings
from typing import Any
import lmdb
import pytest
import torch
from d3text import metric_docs, tracking
from d3text.embeddings_store import (
EmbeddingsStore,
... |
51ff0877a31ec8ca2f468f816d9f9ad0d035382454d8f06810484060d211fb20 | Python | 21,294 | 446 | import sys
sys.path.append("..")
import torch.nn as nn
from modelR.backbones.mobilenetv2 import MobilenetV2
from modelR.necks.conv_csa_drf_fpn_hbb import Conv_CSA_DRF_FPN
from modelR.head.dsc_head_hbb import Ordinary_Head
from utils.utils_basic import *
from modelR.loss.loss_hbb import Loss
from dropblock i... |
8c4e55207cafe313bee7ea9970dbed8cc4c213d8015a3ce35ac4298a33b06c2c | Python | 21,300 | 426 | # -*- coding: utf-8 -*-
"""
Created on Sat Nov 22 11:54:33 2025
@author: mayc06
"""
# Scripts for making Stupski data distributions and scatterplots for May et al 2025
from extract_trajectories_from_orcoflashStupski import *
from math import isnan
from scipy.stats import circmean
traj_list40 = get_tr... |
99222b715a543e4a48184f5d2de94b24ad1e255aa510f82dad1d9a0eb0973cc0 | Python | 21,304 | 606 | # cluster.py
# -----------------------------------------------------------------------------
# Purpose
# - Run clustering on protein graphs and persist:
# (1) per-residue hard assignments
# (2) per-segment embeddings + metadata (ready for FAISS)
#
# Notes
# - Protygus encoder output convention:
# ... |
58b82b2608726389f2aa77f5dae20376ff25acdbbda3b43c3743fa4716a20f39 | Python | 21,313 | 595 | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... |
666cf4339ccb073968191fe3882381a447025045f7853ff0dd75aa25db5714e9 | Python | 21,331 | 416 | # coding=utf-8
# Copyright (c) Facebook, Inc. and its affiliates.
# Copyright (c) HuggingFace Inc. team.
#
# 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... |
4c6f4a0d37a34d53968f012c5078598d4c7ca36b932c9b103f8f7cd1222b3719 | Python | 21,347 | 570 | from __future__ import annotations
import sys
from collections import defaultdict
from copy import deepcopy
from dataclasses import dataclass
from io import StringIO
from typing import TYPE_CHECKING
from uuid import uuid4
import rich.pretty
import rich.table
from mudata import MuData
from rich.console import Console
... |
d9f9a1456b0e0d0492d82a9e59e8da966e309ccd3f5cabe95825514f1b809e49 | Python | 21,362 | 419 | # coding=utf-8
# Copyright (c) Facebook, Inc. and its affiliates.
# Copyright (c) HuggingFace Inc. team.
#
# 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... |
dd922ba8d2ebe119c566f2b9794f43db1acd0c68b356da38edf8ab71fdb6e958 | Python | 21,404 | 638 | #!/usr/bin/env python3
"""
Compare posterior distributions from multiple trained models.
This script runs tree sequences through different trained models
and creates comparison plots showing how different architectures perform
on the same data.
Modified version:
- For each config, it will first look for
<OUTPUT>/si... |
2be5625be392564b0b5f757f6dc9ec37a19f25bb1c159f40a26b3d272f247730 | Python | 21,405 | 673 | """Contains the runtime configuration of MDT.
This consists of two parts, functions to get the current runtime settings and configuration actions to update these
settings. To set a new configuration, create a new :py:class:`ConfigAction` and use this within a context environment
using :py:func:`config_context`. Exampl... |
ce0158aae127b46ea6216489e25c9c79544c3ae4b8f14038754fcbf2f5e1092d | Python | 21,414 | 540 | from __future__ import annotations
import logging
import warnings
from copy import deepcopy
from typing import TYPE_CHECKING
from scvi import REGISTRY_KEYS, settings
from scvi.data import AnnDataManager, fields
from scvi.data._constants import _SETUP_ARGS_KEY, _SETUP_METHOD_NAME, ADATA_MINIFY_TYPE
from scvi.data._uti... |
a33d8b52a38ad64fba65abb16e838b2fc221403ee37379d0d720278d82db73fa | Python | 21,425 | 522 | import logging
import numpy as np
import pandas as pd
import scipy.sparse
import yaml
from os import makedirs
from os.path import join, exists, dirname, realpath
from matplotlib import pyplot as plt
from sklearn import decomposition
from sklearn.manifold import TSNE
from sklearn.metrics import confusion_matrix
from skl... |
e5518928e0595b0c85275221ce44018351672cbccf78d887e420ed104a1f97cd | Python | 21,428 | 625 | # Copyright 2021 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agr... |
f296f7dc00d6b8c9a8b9c3183cec5aeb2237919b029a1fe5c4dbd5d7508ae8df | Python | 21,440 | 537 | #!/usr/bin/env python3
# MIT License
#
# Copyright 2025 Broad Institute
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use... |
8aef1ecf82c2b7ab9891bc5bae449ac5e04f88da40fc09ae7abdf3483315e6ed | Python | 21,460 | 540 | from __future__ import annotations
import inspect
import logging
import warnings
from copy import deepcopy
from typing import TYPE_CHECKING
import anndata
import numpy as np
import pandas as pd
import pyro
import torch
from anndata import AnnData
from mudata import MuData
from scipy.sparse import csr_matrix
from torc... |
c7de1d33627280a2d3746ca20230c07cdf6c688a8a142f59c72e65e248396b1a | Python | 21,461 | 584 | # 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 copy
import torch.nn as nn
from fairseq import checkpoint_utils
from fairseq import utils
from fairseq.data.data_utils import lengths_... |
da631f4b4f49d64e8a608c732246ccb74dfa404c39e6b47eeadee32526c173b5 | Python | 21,468 | 598 | """Run a univariate GLM on fMRIPrep outputs and aggregate group-level maps."""
from __future__ import annotations
import os
from pathlib import Path
from typing import List, Sequence, Tuple, Optional
import click
import numpy as np
import pandas as pd
from loguru import logger
from nilearn import image
from nilearn.... |
6646f700a45166d0ccfa87a72af594a5a47a48871ba902b22777808712baf82f | Python | 21,477 | 597 | """DIAGVAE module for multi-modal variational autoencoder."""
from __future__ import annotations
import logging
from typing import TYPE_CHECKING
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.distributions import Categorical, Independent, MixtureSameFamily, kl_divergence
from scvi imp... |
062a5531ae8f301c0e59bcce1d6665d6ce0ae8faf4f1fedb2bedbfdd452975d7 | Python | 21,501 | 632 | import math
from abc import abstractmethod
from dataclasses import dataclass
from numbers import Number
from turtle import forward
import torch as th
import torch.nn.functional as F
from utils.choices import *
from config_base import BaseConfig
from torch import nn
from .nn import (avg_pool_nd, conv_nd, linear, normal... |
503e65d8e5ba0ac9f49f819e0e58431ff394cceac37fe4b81d715c72916f863b | Python | 21,510 | 599 | #%% Script to calculate the transfer functions
import numpy as np
import matplotlib.pyplot as plt
from bfieldtools import sphtools as sph
import functions
font = { 'size' : 20}
plt.rc('font', **font)
#%% Plot parameters
legendfontsize = 15
linewidth = 2.5
#%% Define parameters
#the path to save the figures in... |
a3abcb5fea319ddc1ec76a8788a345f6f575769164c9418efa26e1d60dc4ea1e | Python | 21,510 | 675 | from imblearn.over_sampling import RandomOverSampler
from imblearn.under_sampling import RandomUnderSampler
from imblearn.over_sampling import SMOTE
import seaborn as sns
import pandas as pd
from sklearn.metrics import f1_score
from sklearn.pipeline import make_pipeline
from sklearn.linear_model import SGDClassifier
fr... |
1d8c72827337db61d42422f56237973384e6eccdd38496ccdcde7614666dba02 | Python | 21,521 | 473 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jan 14 18:29:05 2026
@author: forel
"""
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Oct 8 19:05:08 2025
@author: forel
"""
import os
import sys
import shutil
import subprocess
import numpy as np
#from scipy.io import loadmat
i... |
35a20d462d6155722345209e2945a45be25a7a269c1f193a54024d6f7721153b | Python | 21,546 | 653 | # @license
# Copyright 2017 Google Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in... |
15dc52a08eb3968a09aaef3e8c73fba745b06788cc82fe4e05787d0b9e0c910e | Python | 21,554 | 575 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import sys
import warnings
from collections import OrderedDict
import numpy as np
import tensorflow as tf
from skimage.util import view_as_windows
from tensorflow.python.framework import ops
from tensorflow.py... |
2c4fe4f1b3500586a1351237870f23b05c986201db8345bc52e948c96e60c98f | Python | 21,579 | 466 | import os
import numpy as np
import matplotlib.pyplot as plt
def scatterPlot(X_f,figHeight,figWidth,filename):
plt.figure(figsize=(figWidth,figHeight))
plt.scatter(X_f[:,0], X_f[:,1],s=0.5)
plt.xlabel('$x$',fontweight='bold',fontsize=14)
plt.ylabel('$y$',fontweight='bold',fontsize=14)
plt.xtic... |
a08d83af70f0d8e3f5deea4b4dabfd6a3445429a40db07cac612a53a81a3aa46 | Python | 21,596 | 649 | """Build a database of article references from BRENDA.
Each reference is linked to the enzymes it is associated with on BRENDA and to
the organisms the article references as expressing each one. `sync_doc_db` is
the entry point.
"""
import argparse
import ast
import asyncio
import itertools
import logging
from collec... |
44045d57828fa5c9da84047ce37836f271785609c07564d29bb74c4a1062fecc | Python | 21,639 | 500 | """Physical-space geometry helpers shared by SegRef3D desktop builds."""
from __future__ import annotations
from dataclasses import dataclass, field
from pathlib import Path
import re
from typing import Iterable, Sequence
import nibabel as nib
import numpy as np
LPS_TO_RAS = np.diag([-1.0, -1.0, 1.0, 1.0])
class... |
16d2278c7a904a81b37d1ca56fbc79998e3b33cf1fafcea8638b54a3785dd72a | Python | 21,649 | 661 | import jax
import jax.nn
import jax.numpy as jnp
from flax import nnx
from flax.typing import Dtype
from nucleotide_transformer_v3.layers import (
ConvBlock,
ConvTowerBlock,
DeConvBlock,
DeconvTowerBlock,
DeConvUpsampleType,
RotaryEmbeddingConfig,
SelfAttentionBlock,
)
from nucleotide_trans... |
124b0f0d4d983b6ce62b2dafa29bfcf933f391c1711ef84b6c239ce88e0e4bea | Python | 21,655 | 444 | # Utility classes for univariate and bivariate fit
# Contains
# _log_exp_converter, _logit_logistic_converter, _arctanh_tanh_converter - converters to map bounded parameters into -inf, +inf range
# UnivariateParams, BivariateParams - represent parameters, with basic functionality like "calculate cost"
# Several univari... |
f5ccf6f54ea5f2b61482ecfb5df88bb0884d53b5e9b8e29ac21e0404d56f5d76 | Python | 21,676 | 682 | from imblearn.over_sampling import RandomOverSampler
from imblearn.under_sampling import RandomUnderSampler
from imblearn.over_sampling import SMOTE
import seaborn as sns
import pandas as pd
from sklearn.metrics import f1_score
from sklearn.pipeline import make_pipeline
from sklearn.linear_model import SGDClassifier
fr... |
3bc2d9b22997d4961349d80a517f242235d1128e78ac30c45f07aabf0f64058d | Python | 21,701 | 562 | # 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 Dict, List, Optional
import torch
import torch.nn as nn
from torch import Tensor
from fairseq import utils
from fairseq.m... |
d1755534b72f27947b98d483910f37a651eb1bb5be7995e314397365d26a5270 | Python | 21,708 | 558 | # 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 collections import defaultdict
from itertools import chain
import torch
from omegaconf import DictConfig
from fairseq import optim
fro... |
4510f11f173281045e5f5441dbf6f6177ede87e6a05a33ccd42e7a4659a0b225 | Python | 21,716 | 565 | import os
from functools import lru_cache, partial
from typing import Any, Iterable, Optional
import haiku as hk
import jax
import jax.numpy as jnp
import pytest
from jax import grad, random, tree_util
from jax.experimental import enable_x64
from lenses import lens
from oneqmc.clip import MedianAbsDeviationClipAndMas... |
152389313dde2c05ed5013f8634903931ca564cdb8b4d7100cb1d31e609e859c | Python | 21,720 | 417 | """Functions to build BPNet-style models.
The model architectures are generally derived from the basepairmodels
repository, which is released under an MIT-style license. You can find a copy
at ``etc/basepairmodels_license.txt``.
The arithmetic for residual models is derived from ChromBPNet, but the code is
not derive... |
2a5c8c2fc659d8b44349f1ad6c43ec078ec7a5dc26274475fe569da56d2a99e5 | Python | 21,721 | 548 | import os
import re
import glob
import argparse
from typing import Tuple, List, Optional, Dict
import numpy as np
import matplotlib.pyplot as plt
from dgr.physics.dicom_io import load_dicom_stack, save_header_to_txt
try:
import pydicom
except ImportError as e:
raise SystemExit("The 'pydicom' package is requi... |
ffe391a0009905b89647dcd9b60298fc5a7eeab23a5ae4cbff929afd927daaeb | Python | 21,737 | 681 | from imblearn.over_sampling import RandomOverSampler
from imblearn.under_sampling import RandomUnderSampler
from imblearn.over_sampling import SMOTE
import seaborn as sns
import pandas as pd
from sklearn.metrics import f1_score
from sklearn.pipeline import make_pipeline
from sklearn.linear_model import SGDClassifier
fr... |
24a7d95d0821e9ecdbeea68632c9143aa461bbcf62e0cc8dbac4f0dcd787231e | Python | 21,754 | 570 | """
Supervised Vision Classification System
Implements downstream classification tasks using pretrained vision encoders.
Supports MIL aggregation for study-level predictions.
"""
import logging
import gc
from typing import Dict, Optional, List, Tuple, Any
import torch
import torch.nn as nn
import torch.distributed as... |
99ffbd6d5ac568860a4a29fec317d40d79f9c09d9f5523454c5f13477a435bd9 | Python | 21,767 | 681 | from imblearn.over_sampling import RandomOverSampler
from imblearn.under_sampling import RandomUnderSampler
from imblearn.over_sampling import SMOTE
import seaborn as sns
import pandas as pd
from sklearn.metrics import f1_score
from sklearn.pipeline import make_pipeline
from sklearn.linear_model import SGDClassifier
fr... |
bf8ce6ecc451d2a2d0fc216d785b5a4978ae6bff7157da516cc3b904d2b3dcf7 | Python | 21,784 | 520 | """Convert the HF dataset with the selected stimuli into locally saved images and text."""
import os
import random
import string
from typing import List
import click
import numpy as np
import pandas as pd
from datasets import load_from_disk
from PIL import Image
from tqdm import tqdm
from compositionality_study.cons... |
36255d6e646bfdd905328248ceccc23cf2274afd71d0809194c54044763cd803 | Python | 21,786 | 469 | import os, re
import numpy as np
import pandas as pd
import argparse
import logging
import random
from distutils.version import StrictVersion
from pyliftover import LiftOver
Intro = r'''
Lifting SNPs 'rs' number and genomic position across different builds.
Option --find-build require biopython. Install it with "pip ... |
3984e4a23cbed7f785e6195a88c54caab925e70142e6c5e906af6e22a6767089 | Python | 21,788 | 609 | import os
import anndata as ad
import numpy as np
import pytest
import scanpy as sc
import torch
from mudata import MuData
import scvi
from scvi import REGISTRY_KEYS
from scvi.data import synthetic_iid
from scvi.model import MULTIVI
from scvi.module import MULTIVAE
from scvi.utils import attrdict
@pytest.mark.inter... |
8ca891ec72f0619568eb73d040edf5d9edf43ce48ebb26520fc8658a56b6e01b | Python | 21,795 | 629 | # Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ ... |
d14faaea1312c906f06885593cd409af29a1acf3dffe5097cafd39f9eb638949 | Python | 21,840 | 744 | import math
from functools import reduce, wraps
from inspect import isfunction
from operator import mul
import torch
import torch.nn as nn
import torch.nn.functional as F
from aml.multimodal_video.utils.einops.lib import rearrange, repeat
from aml.multimodal_video.utils.einops.lib.layers.torch import Rearrange
from f... |
356b07be48c5ea2e33edd328ee6e743eedfafd0ee7ac79b882856715d8ac3957 | Python | 21,851 | 554 | # Copyright 2022 InstaDeep Ltd
#
# Licensed under the Creative Commons BY-NC-SA 4.0 License (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://creativecommons.org/licenses/by-nc-sa/4.0/
#
# Unless required by applicable law or a... |
0c6f48d946bbacc8625cf7a233e047128075e3645a4de89f821e7550a3b08caf | Python | 21,857 | 541 | from collections import Counter
import argparse
import os
import json
import numpy as np
import pandas as pd
from pathlib import Path
from tqdm import tqdm
from p_tqdm import p_map
from scipy.stats import wasserstein_distance
from scipy.sparse import csr_matrix, lil_matrix, eye
from pymatgen.core.structure import Str... |
dc39325f13f3b4de99597c65325f0f1fde9f670a04ac5219baa2565465e9ab03 | Python | 21,871 | 423 | import collections
import numpy as np
import numpy.ma as ma
import glob
import logging
import os
import shutil
import time
import timeit
from contextlib import contextmanager
import mot
from mdt.__version__ import __version__
from mdt.lib.nifti import get_all_nifti_data
from mdt.lib.components import get_model
from mdt... |
770cd458f0007ae7aaadce9bbe3da72d7fcaa01804645e5abf67e6ee65e35947 | Python | 21,872 | 559 | from __future__ import annotations
import functools
import time
from collections import defaultdict
from contextlib import contextmanager
from typing import TYPE_CHECKING
from poetry.core.version.markers import AnyMarker
from poetry.core.version.markers import EmptyMarker
from poetry.core.version.markers import Mult... |
480057ce76f477b2957db60733ebe54cdc30e1ad7f4270d74a665c80ce7c2ec5 | Python | 21,875 | 532 | import re
from copy import deepcopy
import numpy as np
import tatsu
from mdt.component_templates.base import ComponentBuilder, ComponentTemplate
from mdt.lib.components import get_component
from mdt.model_building.parameters import FreeParameter, ProtocolParameter
from mdt.models.composite import DMRICompositeModel
fr... |
3f9e1b41e8b7be85e67ed864b3a7225f11aafa95f2137d3babef5a7b7d1a6ebc | Python | 21,884 | 537 | #!/usr/bin/env python
"""Produce the per-token distant-supervision targets, offline.
One HDF5 store of `d3text.token_labels` targets, keyed by pubmed id and shaped
like the encodings the tagger reads. It needs no encodings file: re-tokenizing
`corpus.document_text` reproduces the stored `input_ids` element for elemen... |
d2ef3c810ae050fee761e1aa12343bd66a133a007db2c23deaa3bb455ced97bf | Python | 21,899 | 575 | import os
import sys
os.environ['WANDB_DIR'] = 'ADD YOUR DIRECTORY'
from pathlib import Path
import shutil
import math
import wandb
import numpy as np
from Images.utils import load_HVM8data
from baseModels.utils import get_model
import torch
from enum import Enum
from analysis.metrics import accuracy, dPrime_model_RL
... |
dff36774429670615b5b266e4ac765733f246fe55af9e382d4646a9bd15cf2f8 | Python | 21,909 | 443 | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... |
e0cf1b1c3ed22018ad0e8ab3fb9a929ef80874a5a4545fb2f578431ff172261a | Python | 21,910 | 444 | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... |
0a209f3c4a21851f9635e4e63cd90b0b28bcbd3f44b5603ea18f270a3ed231b2 | Python | 21,911 | 591 | import itertools
import networkx as nx
import numpy as np
import pandas as pd
from opt_einsum import contract
from pgmpy.inference import Inference
from pgmpy.utils import _check_1d_array_object, _check_length_equal, compat_fns
class BayesianModelInference(Inference):
"""
Class to calculate probability (pmf... |
e24b6bb82176e284c5872a151f573815833a5fcb25c2eb6d7390abb3ef74c305 | Python | 21,916 | 495 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from os.path import join
import math
import numpy as np
import nibabel as nib
from dipy.tracking.streamline import transform_streamlines
from scipy.ndimage import binary_dilation
from dipy.tracking.streamline... |
64ce0996a76db9c9d0d7fded4688a484992444587f5db2ba94d65a80ab7919e0 | Python | 21,918 | 532 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 27 11:31:26 2024
@author: Roxana
"""
import torch
from .preprocess import preprocess_adj,get_feature, preprocess_adj_sparse, preprocess, construct_interaction, construct_interaction_KNN,construct_interaction_KNN_edge_index, fix_seed
import numpy as... |
78fb7e20a014c251d723186eb58040e4eb32405b73c9288d787ea0a0e4ff5183 | Python | 21,984 | 730 | #!/usr/bin/env python
#
# Copyright 2006, Google Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list... |
945c966928e18ef8aaa08a25239da26284c099201828b7ed814d4efcaf97af70 | Python | 21,992 | 660 | #!/usr/bin/env python
"""
ENCODE QC log parser wrapper which converts a log file into a dict
Author: Jin Lee (leepc12@gmail.com)
"""
from collections import OrderedDict
MAP_KEY_DESC_FRAC_MITO_QC = {
'non_mito_reads': 'Rn = Number of Non-mitochondrial Reads',
'mito_reads': 'Rm = Number of Mitochondrial Reads... |
03a0259e51a93329583d1fb7b2b0a2781e951208dfe1c68aeb65863bbf18a058 | Python | 21,993 | 648 | """
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 Optional
import numpy as np
import torch
import torch.nn as nn
from torch_scatter import scatter
from torch_sparse import... |
9f2d03375e95afce91fa759e656c2271bbaf3fe45b470038e6b0f2ddb21673a4 | Python | 22,027 | 574 | from collections.abc import Callable, Hashable, Iterable
from typing import (
Any,
)
import networkx as nx
import numpy as np
import pandas as pd
from skbase.utils.dependencies import _check_soft_dependencies, _safe_import
from pgmpy import config, logger
from pgmpy.factors.hybrid import FunctionalCPD
from pgmpy.... |
2941388c5753b9cc38f9e92bab3de095aa9fa3d0d1cefcfa420ac142d2548f0b | Python | 22,028 | 516 | # -*- coding: utf-8 -*-
"""
Created on Mon Aug 7 09:14:53 2023
@author: nagellab
"""
from panda3d.core import loadPrcFileData
loadPrcFileData("", "win-origin 1806 310") #these dimensions work for screen and mirror May23
loadPrcFileData("", "win-size 1050 600")
loadPrcFileData("", "show-frame-rate-meter #f"... |
f20c1d0e032b6aee2ab5f35f48ede2201e30bae3f2e08f77567a3fe864764d08 | Python | 22,030 | 586 | """Feature selection / regularization methods for OCE.
Each strategy receives the design matrix X (n_mol × n_feat), targets y, and a
list of feature keys, and returns:
- subset of selected feature indices
- fitted coefficients on the selected subset
- intercept
- leave-many-out CV RMSE
Strategies:
... |
2b97844ce23a65cef0294c26aa2d899308873dcfa9a53e1a23c75dbb80783b11 | Python | 22,039 | 361 | import argparse
import os.path
def main(args):
import json, time, os, sys, glob
import shutil
import warnings
import numpy as np
import torch
from torch import optim
from torch.utils.data import DataLoader
from torch.utils.data.dataset import random_split, Subset
import copy
im... |
e8e97b3c663622afb6ca271ba2cff3c4114faf018e1bcc5431ca26919f2021d3 | Python | 22,057 | 698 | from __future__ import annotations
from typing import TYPE_CHECKING
from scvi.utils import dependencies
from ._built_in_data._brain_large import _load_brainlarge_dataset
from ._built_in_data._cellxgene import _load_cellxgene_dataset
from ._built_in_data._cite_seq import (
_load_pbmc_seurat_v4_cite_seq,
_load... |
38f667f0c280064998345dee3bde0667b13336dbf11e4fc7d190b9181a1a0cdc | Python | 22,105 | 483 | """
diagnose_flash_attn.py
======================
Minimal synthetic-data diagnostic for the scGPT FlashMHA backend.
Checks:
1. Which flash-attn backend is active (fa1 / fa2 / none).
2. Whether FA2's MHA has use_flash_attn=True (the most common reason for
dense-fallback and memory blowup).
3. The actual tens... |
af89e3a4d084eb820d58a2ba975fb53a08f066de82ccc5329df9c328722b4489 | Python | 22,150 | 503 | from pathlib import Path
import click
from matplotlib.colors import ListedColormap
import torch
import torch.nn as nn
import torch.optim as optim
import torchmetrics.classification
import torchmetrics.segmentation
from torchvision import models
from torch.utils.data import Dataset, DataLoader
from PIL import Image
impo... |
d99583a1477f8a4d444e94a93ef8d16e0fd070404d23d2aa6bb79eb62804a650 | Python | 22,191 | 642 | # @license
# Copyright 2025 Google Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in... |
1ba7fbb242b4a535aa54b38773a9ce9fcfac075fc2acd1f770cd28fc3a8ca9c3 | Python | 22,201 | 490 | from __future__ import annotations
import argparse
import json
import sys
from pathlib import Path
import numpy as np
import pandas as pd
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import average_precision_score, roc_auc_score
ROOT = Path(__file__).resolve().parents[1]
SRC = ROOT / "src"
SCRIPT... |
2d34652c31b4ab5397d0b4c4bec82df5879817b242d254f2cefe33bcad409b01 | Python | 22,203 | 572 | # 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 Any, Dict, List, Optional, Tuple
import torch
import torch.nn as nn
from fairseq import utils
from fairseq.mod... |
8ff1130f6ee83bb5965591fe56b0024765ea6ed6b00265cef3f76aeb2e43f781 | Python | 22,226 | 637 | # Copyright 2021 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agr... |
21f0a02dff9f0b4f5427e955d5cf53e482c1b018a262faa20f1ba9bb5266bff0 | Python | 22,253 | 532 | # -*- coding: utf-8 -*-
"""
Created on Tue Apr 25 09:40:43 2023
@author: nagellab
"""
from panda3d.core import loadPrcFileData
loadPrcFileData("", "win-origin 1806 310") #these dimensions work for screen and mirror May23
loadPrcFileData("", "win-size 1050 600")
loadPrcFileData("", "show-frame-rate-meter #f"... |
a0b2cdd109e4ddb9f5eaa5a457358bba2429f783c7a5a3a919c69452631c6664 | Python | 22,253 | 684 | # 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 logging
import math
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from collections import named... |
1fa2999ac537e7368261a434e4939c5cd12a87fe4583d885415efae88a3b1241 | Python | 22,259 | 628 | ##############################################
##
## Decoding action predictions
##
## fMRI exp, this script has all settings for stimulus PC at 3T.
##
## !! Updated version !!
## - Orientations range from +/- 0.5 to 6.5°
## - Color space changed from rgb255 to rgb, because new Psychopy v... |
3c6bb4a0b49b66f363600144cfeb7c8ec618d89ebc92f4e8116c28ef5573160d | Python | 22,266 | 555 | import copy
import json
import os
from pathlib import Path
import random
import sys
import numpy as np
import tensorflow as tf
from tensorflow.keras.callbacks import EarlyStopping, ModelCheckpoint
from tensorflow.keras.losses import MeanSquaredError
from tensorflow.keras.metrics import MeanAbsolutePercentageError, Roo... |
ce906afd77639cbf24e02a4530564abdb164d1fc23f82902e1f8913278eefcd2 | Python | 22,279 | 505 | """sklearn-style estimator wrapping the AESTETIK multimodal autoencoder."""
from __future__ import annotations
import logging
import os
from typing import List, Literal, Optional, Union
import anndata
import numpy as np
import torch
from lightning.pytorch import Trainer
from lightning.pytorch.callbacks import EarlySt... |
c97c848faf79157fa1c748890b131d1d45567534a332c639bba222729edcd0e9 | Python | 22,315 | 1,508 | import numpy as np
# Cell cycle gene sets from Tirosh et al. doi:10.1126/science.aad0501, plus histones for S phase from own analyses
# Removed BIRC5 because it's expressed in certain non-cycling heart cells
g1_mouse = ['Mcm5', 'Pcna', 'Tyms', 'Fen1', 'Mcm2', 'Mcm4', 'Rrm1', 'Ung', 'Gins2', 'Mcm6', 'Cdca7', 'Dtl', 'Pri... |
7e69abb817f7fa2ab708e448f64449da5816f33bea8e5eb44935b28281f2813c | Python | 22,334 | 561 | """
This module contains the encoder used by the Garfield model.
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch_geometric.utils import dropout_adj
from torch_geometric.data import Data
from torch_geometric.nn import GCNConv, GATConv, GATv2Conv
from .utils import DSBatchNorm, drop_fe... |
06675d679be8124ca032a436615c69c8a8118c08457b4a3024cb3f81e2172687 | Python | 22,337 | 618 | """Create image files for the selected stimuli with their action annotations."""
import json
import os
from pathlib import Path
from typing import Dict, List
import amrlib
import click
import matplotlib.pyplot as plt
import networkx as nx
import pandas as pd
import seaborn as sns
import spacy
from amrlib.graph_proces... |
b2ed5e32ffa33b7ea82994948fb1aa08483338d61ddc4a496e0f8d7232ec94a9 | Python | 22,350 | 470 | import matplotlib.pyplot as plt
import numpy as np
import igraph as ig
import networkx as nx
import os
import sys
import seaborn as sns
from scipy import stats
import pandas as pd
from HierarchiaPy import Hierarchia
abspath = os.path.abspath(__file__)
dname = os.path.dirname(abspath)
os.chdir(dname)
os.chdir('..\\src\... |
c6502b24a20e173a56d35d6ff35168bd99539e50dba1b701db1d1222f9a09fa9 | Python | 22,360 | 384 | # -*- coding: utf-8 -*-
# Resource object code
#
# Created by: The Resource Compiler for PyQt5 (Qt v5.9.5)
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore
qt_resource_data = b"\
\x00\x00\x0b\x85\
\x89\
\x50\x4e\x47\x0d\x0a\x1a\x0a\x00\x00\x00\x0d\x49\x48\x44\x52\x00\
\x00\x00\x86\x0... |
bc7838a43c02f96d3d95f6fc97de9a490e75016ff707623e0f36adf304815752 | Python | 22,379 | 516 | import fnmatch
import logging
import os
import sqlite3 as sqlite
import sys
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import Dict, List, Optional, Union
from ..plotting import qc_plots
import click
import numpy as np
from loompy import create_from_fastq, connect, combine_faster
from .... |
a11d8b9e47b8582738e1093a425b703b9cfecb74d099d67d2cd9d908781519ca | Python | 22,405 | 552 | from matplotlib import pyplot as plt
import numpy as np
from scipy.signal import savgol_filter
# line plot for firing probability when activate multiple spines
def line_firingprobability(data, save=False, xpeak=[40, 175]) :
x_ctl_nspines = data['ctl_actspines']
y_ctl_prob = data['ctl_prob']
y_ctl_stdev = d... |
ac2d32fb2a325186b2f9f69612bbe525a94f8c3a0a17777e2e8704efc0a49863 | Python | 22,454 | 714 | #!/usr/bin/env python3 -u
# 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.
"""
Run inference for pre-processed data with a trained model.
"""
import ast
from collections import namedtuple
fr... |
7bc7dcbcc0b2c38a61d4541f29b8c75f3dbcc40e8df48b1a3ca3e774511df880 | Python | 22,489 | 614 | from __future__ import annotations
import contextlib
import dataclasses
import logging
import os
import re
from pathlib import Path
from subprocess import CalledProcessError
from typing import TYPE_CHECKING
from urllib.parse import urljoin
from urllib.parse import urlparse
from urllib.parse import urlunparse
from du... |
71394a7f27b3fc14890ca64250dedb70a7fecc338aaa4ba1cd4d265f20f5e9f4 | Python | 22,493 | 556 | from typing import Any, Dict
import numpy as np
import math
import copy
import json
import os
import glob
import sys
from omegaconf import DictConfig, OmegaConf
import torch
from torch import sqrt
import torch.nn as nn
from torch.nn import functional as F
from torch.nn.parallel import DistributedDataParallel as DDP
i... |
8f6ac8ab7f561caafce19ee1e1a4ca0cf219d93b2ceb948470f39407ba67a056 | Python | 22,507 | 627 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Evaluate foreground Dice/HD95/NSD for a prediction folder.
Output format is aligned with local `metrics.csv` style:
- DiceNNUNet_*
- (optional) DiceMONAI_*
- HD95_*_vox
- HD95_*_mm
- NSD_*
- per-case means + NSD_tau/NSD_unit
- dataset-level OVERALL_MEAN and OVERALL_ST... |
7e8b09a58f499d84b4ea74153e8bce80a6c28e27596d5dbc65dd19966be60eb4 | Python | 22,570 | 506 | from kwave.kgrid import kWaveGrid
from kwave.kmedium import kWaveMedium
#from kwave.utils.kwave_array import kWaveArray
from kwave.ksensor import kSensor
from kwave.kspaceFirstOrder2D import kspaceFirstOrder2DG
from kwave.options.simulation_execution_options import SimulationExecutionOptions
from kwave.options.si... |
04a8cde603cbf9408fd4cffcfa0c39407591cd405db481cf880b3567f01efb60 | Python | 22,574 | 595 | from __future__ import annotations
from abc import abstractmethod
from dataclasses import dataclass, field
from typing import TYPE_CHECKING
import pyro
import torch
from torch import nn
from torch.nn import functional as F
from scvi import REGISTRY_KEYS
from scvi.data import _constants
from ._decorators import auto... |
4c81a8359e83392b986e653d47530c90449bb14521510314431217716d25f55d | Python | 22,575 | 614 |
import functools
#import pdb
import warnings
from contextlib import contextmanager
from typing import Any
import matplotlib.pyplot as plt
import mne
import numpy as np
import pandas as pd
import scipy
from mne.filter import filter_data
from mne.preprocessing.eog import _get_eog_channel_index
from mne.utils import lo... |
f390317e7dba949625c4191b4c13dc4fae3b062a3bb9986e4a2965a14a7ffa1d | Python | 22,586 | 742 | # 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 ..roberta.model_xlmr import XLMRModel
from fairseq.models.xmod.transformer_layer_xmod import XMODTransformerEncoderLayerBase
from ..rober... |
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