sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
c3241ad163491842768ef6415f77f148d52110bcded032024eed0604e2dd469e | Python | 26,377 | 538 | ###20211011,修改日期文件夹的获取方式
from SystemUI.MainUIApp import Ui_MainWidget
from PyQt5.QtWidgets import *
from PyQt5.QtCore import *
from PyQt5.QtGui import *
import sys
import numpy as np
from threading import Thread
import os
import time
import cv2 as cv
from SystemUI.Function_Voltagesupply import Turnon_volt... |
63bc642c8f00ec8190953c055f86ef16348e1417b91ae01b47f36f32ef634567 | Python | 26,421 | 601 | # -*- coding: utf-8 -*-
import sys, os
sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
import time
import os
import numpy as np
import scipy.io
from scipy.spatial import Delaunay
import matplotlib as mpl
import matplotlib.pyplot as plt
mpl.rcParams["figure.dpi"] = 200
fro... |
5a950d232de5cd2afd1827002e67f73d7388fc5118bce6fe5f73b79a22af2f28 | Python | 26,432 | 600 | import random
import numpy as np
from torch.utils.data import Dataset
import sys
import pandas as pd
from tqdm import tqdm
from sklearn.preprocessing import LabelEncoder
from collections import OrderedDict
import os
import math
import torch
import torch.optim as optim
import torch.optim.lr_scheduler a... |
6fc3be4995faac358b00bf0becb88b486c82a3f391815bee264bc456c83a9f6d | Python | 26,442 | 601 | # -*- coding: utf-8 -*-
import sys, os
sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
import time
import os
import numpy as np
import scipy.io
from scipy.spatial import Delaunay
import matplotlib as mpl
import matplotlib.pyplot as plt
mpl.rcParams["figure.dpi"] = 200
fro... |
770ed13ff82aad51536b7abd7496671b87277e444d245e7ccbf0a77fecc719c1 | Python | 26,462 | 691 | """Functional forms of transformations
related to frame labels,
i.e., vectors where each element represents
a label for a frame, either a single sample in audio
or a single time bin from a spectrogram.
This module is structured as followed:
- from_segments: transform to get frame labels from annotations
- to_labels: t... |
13feee13569be28c5ec18ec6edf2361edc4fcaeb0a9369dac931ce267ebdfa3c | Python | 26,463 | 828 | import copy
import gc
import time
import torch
from lib.utils.utils_preprocess import append_obsvspred, export_obsvspred, destandardize_concentration, compute_global_stats, append_metrics, export_all_metrics_and_residuals
from lib.utils.utils_post_processing import plot_individual_fits, compute_test_metrics
from lib... |
d3ed69cfbdcbcb7b9ff04d66c967ab9a9ca4bd09098282c694ab710258a129e5 | Python | 26,468 | 751 |
import torch
import torch.nn as nn
import math
import torch.nn.functional as F
class ODEFunc(nn.Module):
"""
ODE function with optional EMA for parameters, dose handling, and skip connection.
Supports multiple event types via `evid` (bolus=1, infusion=2, observation=0).
"""
def __init... |
0bb0534bb71b0e2c47e3cc46ef1e3fd422ff502f49db7f746f9c96fe3f6c73f6 | Python | 26,521 | 742 | # Copyright (c) 2024, Shenghao Cao & Ye Yuan. Shanghai Jiao Tong University, Shanghai 200240, China
# The script is modified from scGPT (https://github.com/bowang-lab/scGPT), copyright (c) 2022 suber
import json
import pickle
from pathlib import Path
from collections import Counter, OrderedDict
from typing import Dict... |
7d946c7d794a62830984eddf70331ff295ee5eeeafa849e5590ffaa8cdb0f4b5 | Python | 26,557 | 639 | import math
import numpy as np
import torch
import torch.nn.functional as F
from torch import nn
from torch.cuda.amp import autocast
from einops import rearrange, repeat
from functools import partial
from contextlib import contextmanager
from local_attention import LocalAttention
from performer_pytorch.reversible imp... |
8266d1428ee1bb11d70b978b91342af0669be1c1b81f475c90ac071b54afd8e0 | Python | 26,561 | 629 | import argparse
parser = argparse.ArgumentParser(description='feature extractor and drug name')
parser.add_argument('--feature_extractor','-e',help='feature extractor')
parser.add_argument('--drug_name','-d',help='drug name')
parser.add_argument('--geneset','-g',help='geneset')
parser.add_argument('--adjust','-adj',hel... |
2c2e3e6ddbdc97a3316062896275fec9391bf27e4d06691902fd253cc6b7a57a | Python | 26,571 | 754 | """What `train` writes into the checkpoint.
The heads' weights are the whole product of a run, and which epoch's they are
is decided two files away, in `Trainer.fit`. This drives `train.main` with a
scripted validation schedule whose best epoch is not its last, and asserts at
the *file* — not at the model object — tha... |
9242cfa6426f6d93bebeefa58973ee942688bbe6d33cf15bdb8189764e7fd369 | Python | 26,577 | 779 | """`precompute-encodings` must not store a document that has no text.
A document whose halves are missing, or are markup wrapping whitespace,
tokenizes to one window of `[CLS]` and `[SEP]`. The command warned about
exactly that and wrote the group anyway, leaving the data layer to detect and
drop it at read time. The ... |
48eda689c1ce8230e0a03f0e5070e41a8f4c83354132398c2a918c8a9db6506c | Python | 26,722 | 642 | from PyQt6.QtWidgets import (
QMainWindow, QWidget, QVBoxLayout, QHBoxLayout, QGridLayout,
QPushButton, QLabel, QGraphicsView,
QCheckBox, QScrollArea, QFrame, QComboBox, # ← ここに QComboBox を追加
QDoubleSpinBox, QSpinBox # ✅ ← これを追加
)
from PyQt6.QtGui import QColor, QPixmap, QFont
from PyQt6.QtCore... |
1d3e28232045f5ab3267cdc0167b286648dc46fc4951d2c102df986ff91e6eca | Python | 26,737 | 733 | """The label-store reader: space checked at open, codes carried across the
window merge by the same arithmetic that merges the embeddings."""
import gc
import types
import h5py
import numpy
import pytest
import torch
from d3text import token_labels
from d3text.models import token_supervision
from d3text.models.token_... |
613cca9cd1b3068f16ae8e7eb024ff6e9bbc087f437582a63f04da6e7e341271 | Python | 26,749 | 791 | import contextlib
import functools
import logging
from typing import Sequence, Type, TypeVar
import jax
import jax.flatten_util as jfu
import jax.numpy as jnp
import jax.tree_util as jtu
import numpy as np
from .api import (
IS_LEAF,
JAC_DIM,
Array,
ArrayOrFwdLaplArray,
Arrays,
Axes,
Extra... |
5238f57feef24c9ce4806b5ecc2e8567a49232a12f07869b32dbd9cedf220a0c | Python | 26,763 | 513 | 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 scipy.stats import sem
# from sklearn.decomposition import PCA
# from sklearn.preprocessing import StandardScaler, MinMaxScaler, MaxAbs... |
a7a3ffaf5b79653dd3c61cfe45e71cabc991eb9d541f512e794cc3c1e7f5ebf8 | Python | 26,779 | 813 | # 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
from dataclasses import dataclass, field
from typing import Optional, Callable
from functools import partial
import... |
21f2a6296174004c1f5898dd331fa9ecfd522f4f21fa0a45171b2a9a3b258b22 | Python | 26,790 | 607 | # 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 dataclasses import dataclass, field
from typing import Optional
from omegaconf import II
from fairseq import options, utils
from fairs... |
e27fe4e438ff1877d1c5f456e5b7fdad4525e1160fa67aa5f8d1e7575043dfeb | Python | 26,791 | 872 | import datetime
import itertools
import os
import pickle
import random
import sys
import numpy as np
import pandas as pd
import pytz
import torch
from Bio.PDB.Polypeptide import index_to_one, one_to_index
from scipy.stats import pearsonr
from sklearn.utils import resample
from torch.nn.functional import softmax
from t... |
7b53395e6e936f8f62f5ffa9e88fcb089f9ef96c156835cfbb49b5d2f94f1534 | Python | 26,814 | 699 | # 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... |
a84d6c766d59f51d47866093dd5851ec050748d19fe87aad5b3e6c34f6bf4070 | Python | 26,831 | 814 | import networkx as nx
import numpy as np
import pandas as pd
import pytest
from sklearn.exceptions import NotFittedError
from sklearn.utils.estimator_checks import parametrize_with_checks
from pgmpy.base import PDAG, UndirectedGraph
from pgmpy.causal_discovery import PC, ExpertKnowledge
from pgmpy.example_mod... |
6e92ae554b865ec430e4238dfe29d7f55cfbd6a9d0ec0d499c10ec0a6312f68a | Python | 26,866 | 592 | #!/usr/bin/env python
# This script is used to process FASTQ files in a folder in parallel.
# It uses the fastp command to preprocess the FASTQ files.
# It can also generate a summary HTML report of the QC metrics.
import os,sys
from optparse import OptionParser
import time
from multiprocessing import Process, Queue
... |
1a253fa58ab86879e43cc12b8abafd6273d54222869b724864d63ca306ecb6c8 | Python | 26,891 | 651 | import io
import os
import unittest
import numpy as np
import numpy.testing as np_test
import pandas as pd
from pgmpy.example_models import load_model
from pgmpy.factors.continuous import LinearGaussianCPD
from pgmpy.factors.discrete import TabularCPD
from pgmpy.models import LinearGaussianBayesianNetwork
class Tes... |
148d72de54187b4c8335ba86c0df1a10b4fdc4a9a93622d5c4f0616714feaf9c | Python | 26,901 | 607 | import os
import argparse
from typing import Tuple, Optional
import numpy as np
import matplotlib.pyplot as plt
from dgr.physics.b0_field_read import load_b0_map
from dgr.physics.dicom_io import load_dicom_stack
from dgr.physics.dicom_register import read_series_params, build_affine, resample_volume_to_target
from dg... |
a07103aa0e2c3c202458a9845c9aeabaa7104a03271b71eb090b29175615ca24 | Python | 26,939 | 733 | # 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 csv
import logging
import re
from argparse import Namespace
from collections import defaultdict
from dataclasses import dataclass
from ... |
ca0d790706d474ebf328a244ade18055740c3c414e6ed367fbb22c2367efcee1 | Python | 26,948 | 632 | import torch
import torch.nn as nn
import torch.nn.functional as F
import math
import torch_geometric
import copy
from .activation import (
ScaledSiLU,
ScaledSwiGLU,
SwiGLU,
ScaledSmoothLeakyReLU,
SmoothLeakyReLU,
GateActivation,
SeparableS2Activation,
S2Activation
)
from .layer_n... |
99eee3d8fd30b6e87e126034116c33587ca164bdbf6607dcde129fd1f7215a1e | Python | 26,996 | 765 | import os.path as op
import json
import os
from bids.layout import BIDSLayout, BIDSLayoutIndexer
import nipype.interfaces.io as nio
import nipype.pipeline.engine as pe
from omegaconf import OmegaConf
import re
def create_datasource(
output_query,
data_dir,
nipype_dir,
subjects=None,
sessions=Non... |
2b2aeed859914972e9c37cafaf21af2caacd66141c317f4cf16ffd0ac8919fa1 | Python | 27,003 | 513 | 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 scipy.stats import sem
from sklearn.decomposition import PCA
from sklearn.preprocessing import StandardScaler, MinMaxScaler, MaxAbsScal... |
c5a90bcee60b078390523906318191fe3f0b5d7486da5776ccebaf4b50d189a7 | Python | 27,007 | 634 | import numpy as np
import theano
import theano.tensor as T
from .. import init
from .. import nonlinearities
from .base import Layer
from .conv import conv_output_length, BaseConvLayer
from .pool import pool_output_length
from ..utils import as_tuple
from theano.sandbox.cuda.basic_ops import gpu_contiguous
from pyl... |
0319832c7acb0ecff27e5111b4fe355e58f8dc7ee20f1d2904d47a855ab18fa0 | Python | 27,017 | 642 | import copy
import itertools as it
import networkx as nx
import numpy as np
from pgmpy.factors.discrete import DiscreteFactor
from pgmpy.inference import Inference
from pgmpy.models import DiscreteMarkovNetwork
class Mplp(Inference):
"""
Class for performing approximate inference using Max-Product Linear Pr... |
ec7386abaaf5ac65a335cadf39536f5329bef28e25533ca9815e2daddb5ac1b8 | Python | 27,017 | 647 | """
Inference script: Computes concept direction and performs counterfactual prediction using a trained node-level conditional point cloud diffusion model.
Usage Examples (Batch processing of multiple slices):
# 1. For MERFISH_mouse_cortex dataset
python scripts/run_inference.py \
--config configs/config.yaml \
... |
078e94df89393b75edfaf2a9db991e2eaf60a9f743d0c949c4f351cd5b9caf5d | Python | 27,037 | 708 | import math
import numpy as np
import torch
import torch.nn.functional as F
from torch import nn
from torch.cuda.amp import autocast
from einops import rearrange, repeat
from functools import partial
from contextlib import contextmanager
from .reversible import ReversibleSequence, SequentialSequence
try:
from ap... |
e2546101ad6185507a7b6f6032bad2a8577a0d49f2fc2702ff40000d136bd7fa | Python | 27,040 | 711 | from types import ModuleType
import pytest
from matplotlib.backend_bases import PickEvent
# scikit-learn is imported lazily by rnalysis.utils.generic (see tests/test_imports.py), so the
# star-import below no longer re-exports it -- the tests import it directly instead.
from sklearn.preprocessing import PowerTransfor... |
f48b12fd4e2092683f959b122b12ae2bda6be86191c05100333a94f813191dea | Python | 27,053 | 772 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import csv
import math
import time
import numpy as np
import torch
import scipy.io as sio
'''******************** Functions for computing simulated BOLD signals
***************... |
e114e3da939f17a0975209ac4163cd1042fd146628ca0661f62695b79ca8814e | Python | 27,061 | 672 | #!/usr/bin/env python3
"""
Proper RAG-GNN Analysis for Cancer Signaling Networks
=====================================================
Uses REAL data from STRING database (already downloaded).
Implements:
1. GNN message passing layers
2. Knowledge retrieval based on protein functional annotations
3. Proper fusion of ne... |
1f0c7d0ce39561b9a6c495ed3285fe7ddf38f0d865c19f90578d433ed11fc3b8 | Python | 27,071 | 669 | """
workers.py — Subject-level worker functions for the cross-session pipeline.
"""
from __future__ import annotations
import logging
import gc
import os
import pickle
import time
from typing import Any, Dict, List, Optional
import numpy as np
import pandas as pd
from ..config import resolve_pipeline_spec, normaliz... |
6d29f968518495e703ab5677ec14358d2f3e9bc4edb5a24438569a40e2a81c9e | Python | 27,121 | 693 | import functools
import logging
import numpy as np
import traceback
import bigstream.transform as bs_transform
from itertools import product
from dask.distributed import as_completed
from .image_data import ImageData, get_spatial_values
from .io_utility import read_block as io_utility_read_block
logger = logging.... |
2b7f1b372b3b3fd4ad65398dd852d14dbb05940dd19df16e57cca7d6ba1928ef | Python | 27,145 | 654 | """`BrendaClassificationModel` — entity-class detection over pooled logits."""
import logging
from collections.abc import Sequence
import torch
import torch.nn as nn
from d3text import tracking
from d3text.constraints import FREQUENCY_CLAMP_EPS, UnitInterval
from d3text.mention_metrics import (
DetectionAccumulat... |
8e40ec86e24e93ca95f087ab4749ca0ca8b23cd14be57eb63b1c76358a03b213 | Python | 27,149 | 698 | """The encodings HDF5's own provenance stamp.
`precompute-encodings` writes token ids into an HDF5 keyed by pubmed id; the
ids alone say nothing about which model, window or stride tokenized them, and
`d3text.embeddings_store` already showed the aggregated row count comes to the
same value under any window or stride. ... |
a67441fd3f06167e52dd66ff52f0e998ba5628a322623073bdd3822a32492206 | Python | 27,171 | 783 | """
This module builds rna pretraining.
Author: wangning(wangning.roci@gmail.com)
Date : 2022/9/8 1:21 PM
"""
# built-in modules
from paddlenlp.transformers import ErniePretrainedModel
from paddlenlp.transformers.ernie.modeling import ErnieOnlyMLMHead
from paddle import nn
import random
from paddlenlp.data import St... |
096fe826b7cbec1fdb97090416b87943d99df09868a2d11c6a1baf391c6b8de8 | Python | 27,187 | 812 | ## modified by cell2location and scTM
## please refer to https://github.com/JinmiaoChenLab/scTM/blob/main/sctm/pl.py
import anndata as ad
import matplotlib as mpl
import matplotlib.pyplot as plt
import textwrap
import numpy as np
import scanpy as sc
# import seaborn as sns
from matplotlib import rcParams... |
a10bf54d97d34c64fa95b3fcdfb4ae0c2883df14eb840d9412abf613a4c744b7 | Python | 27,213 | 753 | """Scoring a linker against gold it had no part in choosing.
The failure these tests exist to catch is silent and flattering. Reconstruct a
span's gold entity from the surface-form index and the linker — which reads
that same index — agrees with it by construction: measured that way the score
is 1.000 over ten thousan... |
c5f171d04642f3ad4c4312381984f9f0196fe802a8a830fae9996dd2b501c456 | Python | 27,218 | 683 | import functools
import logging
from typing import Any, Literal, ParamSpec, TypeVar, overload
import jax
import jax.numpy as jnp
import numpy as np
try:
from jax.extend.core import Primitive
except ImportError:
from jax.core import Primitive # type: ignore[import-error]
try:
from jax.extend.core.primiti... |
ee84cef0a43e66dd53f31e7feeebccf766f3c7fce5016e284129921d43a37e4a | Python | 27,227 | 704 | # -*- coding: utf-8 -*-
"""End-to-end workflow for the working-memory EEG analysis."""
#%%
import ast
import seaborn as sns
from pathlib import Path
import pickle as pkl
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import mne
from scipy import stats
from project_package.project_functions.prep... |
c1162e87401e92170bfabc4e24336e67b45e3bf69ef3bbcbb55e7ef620a27af5 | Python | 27,240 | 654 | import copy
import os
import pickle
import tempfile
import unittest
import numpy as np
from .mock_data import simple_data, create_simple_bam
import libmedaka
import medaka.features
from medaka.common import Region, Sample
import medaka.labels
__reads_bam__ = os.path.join(os.path.dirname(__file__), 'data', 'test_read... |
5033432139890882045869d746992cb30431ec2c4703bf757d97b00e9518a83b | Python | 27,251 | 633 | import torch
import torch.nn as nn
import torch.nn.functional as F
from utils.tools import hier_half_token_weight
from layers.SelfAttention_Family import FullAttention, AttentionLayer
from layers.Embed import PatchEmbedding
from utils.tools import create_sin_pos_embed
import math
import random
from typing import List
... |
fea4310a55f8a4fa1ee81bb9c8f870565695446098fb9dbdb5ad9491a5e1f37a | Python | 27,264 | 761 | # Copyright 2015 Google Inc. 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 applicable law or a... |
e13e8b121adb3e453991fb18fabedbf0eaf9668c35e1fa3067f50c4a0bf584b2 | Python | 27,293 | 645 | """Preprocesses the Visual Genome + COCO dataset."""
# Imports
import json
import os
from typing import Dict, List, Optional, Union
import click
import networkx as nx
import pandas as pd
import spacy
from datasets import Dataset, load_from_disk
from loguru import logger
from spacy import Language # type: ignore
from... |
10731f8b4d9c00b45c499ad206a0ca6b3e3af5771c1a9134704d3173a81ada49 | Python | 27,305 | 551 | import os
import argparse
import numpy as np
import pandas as pd
import random
import torch
import torch.nn as nn
import torch.nn.functional as F
from transformers import EsmModel, AutoTokenizer, get_scheduler
from torch.optim import AdamW
from torch.utils.data import Dataset, DataLoader
import xgboost as xgb
from peft... |
e7ed3b0ce78975860b73a4b1ebb11b4f04ce350e61618dd828af021500a5f757 | Python | 27,354 | 638 | #!/usr/bin/env python3
"""
WF-RF — handcrafted waveform features + Random Forest baseline.
Referred to as "WF-RF" in the paper (Methods § Baselines). The four core
shape descriptors follow Jia et al. (2019, Journal of Neurophysiology);
the five additional features follow the Allen Institute ecephys waveform
metrics co... |
79f0301f772accd956122c68792953f962dae5a91118ea231c870d7d9a6f53c6 | Python | 27,385 | 645 | # -*- coding: utf-8 -*-
"""
Created on Tue May 13 10:35:03 2025
Adapted for delivering open-loop complex-trajectory stimuli, from:
- AFOF3D_OL_record.py
- AFOF3D_CLflightAFOF.py
@author: mayc06
"""
## To use this code, simply hit run in a python ide like spyder. This code has
## three sections: the importer ... |
73f5c534108733b106a6acf3da9cbf6a991e9806f45d776ddf60acde0d820312 | Python | 27,397 | 713 | import argparse
import csv
import os
import random
import numpy as np
from process_pretrain_data import get_kmer_sentence
max_length = 0
def write_file(lines, path, kmer, head=True, seq_index=0, label_index=1):
with open(path, 'wt') as f:
tsv_w = csv.writer(f, delimiter='\t')
if head:... |
915edcb36b3ea12c1c6a39c41125762afad21f7a33f36cd4789342916b505141 | Python | 27,401 | 757 | """Durable, resumable storage shared by maintained inference families.
This module deliberately does not know about models, datasets, or distributed
execution. The inference runner is responsible for making the same batch
decision on every process and for allowing only its main process to call the
filesystem-mutating ... |
0bbd781f8a9cad0f65919941e6ed4ef254e4b25a826c6da7a82adccfe087266d | Python | 27,469 | 709 | # 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
import warnings
from argparse import Namespace
from typing import Any, Callable, Dict, List
import torch
from fairse... |
2ce2f30807632c1a1c743334c8bf332c4986caa7ec1ac2920d16f02d0324e263 | Python | 27,484 | 661 | import numpy as np
import streamlit as st
from streamlit_image_coordinates import streamlit_image_coordinates
from streamlit_extras.image_selector import image_selector
from msi_visual import visualizations
import math
import cv2
import cmapy
import joblib
import time
from PIL import Image
from pathlib impo... |
eb6837258289f97919b7b7f597a20d1ffc984a71baa96d60bee5eb1445eebcf1 | Python | 27,531 | 639 | """
Library for instantiating and running the optimizer for Tangram. The optimizer comes in two flavors,
which correspond to two different classes:
- Mapper: optimizer without filtering (i.e., all single cells are mapped onto space). At the end, the learned mapping
matrix M is returned.
- MapperConstrained: optimizer w... |
249f16b97ec99fd824ba5c870c59c7666abc59bf49221817a7684adaf198c5e4 | Python | 27,628 | 700 | from __future__ import annotations
import logging
import warnings
from collections import OrderedDict
from typing import TYPE_CHECKING
import numpy as np
import pandas as pd
import torch
from scipy.sparse import csr_matrix
from scvi import REGISTRY_KEYS, settings
from scvi.data import AnnDataManager
from scvi.data._... |
a6532e2c7875c536f470a2a187d3f47f9ae89cd5868361c7a663e781596220f9 | Python | 27,670 | 772 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import csv
import math
import time
import numpy as np
import torch
import scipy.io as sio
'''******************** Functions for computing simulated BOLD signals
***************... |
ca1d2bc3f2c481fa6dac3094ebfee00939fa5ef35b81ad4498dc9fe0eaa31eb4 | Python | 27,676 | 772 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import csv
import math
import time
import numpy as np
import torch
import scipy.io as sio
'''******************** Functions for computing simulated BOLD signals
***************... |
1c7901e4c51b0535e10e9aee9ef167c2b7285722ba427be38f3db586fe632fd0 | Python | 27,706 | 577 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# ----------------------------------------------------------------------------------------------------------------------
# Author: Lalith Kumar Shiyam Sundar
# Institution: Medical University of Vienna
# Research Group: Quantitative Imaging and Medical Physics (QIMP) Team... |
51b3b383ad8f05c72e1ad0137f58eb28333ea863aa4f449e26bff55d63ddfaa9 | Python | 27,707 | 588 | # ##############################################################################
# GPLv3 LICENSE INFO #
# #
# Copyright (C) 2020 Mario S. Valdés-Tresanco and Mario E. Valdés-Tresanco ... |
e7e138bdfd2846f7f9daab2b763146ca80d3b8587b5c004c4d1828abdbe9e0f0 | Python | 27,709 | 772 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import csv
import math
import time
import numpy as np
import torch
import scipy.io as sio
'''******************** Functions for computing simulated BOLD signals
***************... |
55127510a1f55217c0021c844d0574416e506d473a2727a9faeb9671cacd179b | Python | 27,765 | 718 | from __future__ import annotations
import logging
from typing import TYPE_CHECKING
import numpy as np
import torch
from lightning.pytorch.callbacks import Callback
from pyro import poutine
from scvi import settings
from scvi.dataloaders import DataSplitter, DeviceBackedDataSplitter
from scvi.model._utils import get_... |
0fed3a7d83e63bdbb622c370201a81066874f98d329b5e9454b96b49a6cb6d63 | Python | 27,767 | 771 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import csv
import math
import time
import numpy as np
import torch
import scipy.io as sio
'''******************** Functions for computing simulated BOLD signals
***************... |
39ae66f5cfca2d6e8bbae846dbeef61b4777f19cb937b27bd8a1357b655b36cf | Python | 27,772 | 775 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import csv
import math
import time
import numpy as np
import torch
import scipy.io as sio
'''******************** Functions for computing simulated BOLD signals
***************... |
bed49c09e03f64341105bdf95487df14fc7356a68f645d2ba8bc43c6fa30978d | Python | 27,782 | 741 | import os
import pickle
import numpy as np
import pandas as pd
import pytest
import torch
from scvi.data import synthetic_iid
from scvi.model import SCANVI, SCVI
from scvi.utils import attrdict
def test_saving_and_loading(save_path):
def legacy_save(
model,
dir_path,
prefix=None,
... |
f289d4837ef4afed461cf9a7a4934149c51552d84f2840659551b1a448abfe0d | Python | 27,802 | 676 | from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
import torch
from torch.distributions import (
Categorical,
Exponential,
Independent,
MixtureSameFamily,
Normal,
)
from torch.distributions import kl_divergence as kl
from scvi import REGISTRY_KEYS
from scvi.di... |
ac2ac1b992b40127a8a74518b50d034dd510a91c46a6baebf2bb2d1e99a70e8e | Python | 27,810 | 744 | # 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 argparse
import math
import tempfile
import unittest
import numpy as np
import torch
import tests.utils as test_utils
from fairseq im... |
3e1adffaac5a81a140dcab1ddad970f621cfe827b28976bef9577c20342a9dbe | Python | 27,831 | 771 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import csv
import math
import time
import numpy as np
import torch
import scipy.io as sio
'''******************** Functions for computing simulated BOLD signals
***************... |
1c04499d6f17f5ee4d0c54252c235d59ad85e88473c1a17b59eaad68e6ffa9c8 | Python | 27,867 | 793 | import argparse
import ast
import multiprocessing as mp
import time
from functools import partial
from pathlib import Path
from typing import Dict, Iterable, List, Optional, Tuple
import numpy as np
import pandas as pd
from sklearn.feature_extraction.text import CountVectorizer
def parse_hairpins(hairpin_str: str) -... |
fdf78e7cfef890c3302b99dd52aa95d287f5a807dcb1b39ae886829ec51d9c7b | Python | 27,873 | 748 | from __future__ import annotations
import logging
import warnings
from functools import partial
from typing import TYPE_CHECKING
import numpy as np
import pandas as pd
import pyro
from pyro.infer import Trace_ELBO
from scvi import REGISTRY_KEYS, settings
from scvi.data import AnnDataManager
from scvi.data._utils imp... |
6b5fe0eaf11de223d5295f5d7270fade01687e3a5d3f6247a0109d7e6376caf0 | Python | 28,072 | 713 | from __future__ import annotations
import copy
import os
import pathlib
from collections import Counter
from typing import Optional, Union
import crowsetta
import numpy as np
import pandas as pd
from . import constants, files
from .typing import PathLike
def format_from_df(dataset_df: pd.DataFrame) -> str:
"""... |
aab2646a23f653dad391335c4f35c3a41b4ff2d5cd496f9f33d1107bf14b8dae | Python | 28,099 | 866 | # Module containing information theoretic measures and error metrics
import numpy as np
from tqdm.auto import tqdm
# ============================================================
# Basic utilities
# ============================================================
def fit_value_bin_edges(Y_train, n_bins=100, mode="quantile... |
834aec9431a06ac340dcf676e967f1ba493d8bb601658e4c82b1e160a2520e70 | Python | 28,112 | 716 | import json
import logging
import os
from functools import partial
from multiprocessing import Pool, cpu_count
import numpy as np
from tqdm import tqdm
from ...file_utils import is_tf_available, is_torch_available
from ...tokenization_bert import whitespace_tokenize
from .utils import DataProcessor
if is_torch_avail... |
0f2198ff6f692bd2409b5f7d854adbd988f8eb6406fd273688f439fb4f813767 | Python | 28,113 | 717 | import json
import logging
import os
from functools import partial
from multiprocessing import Pool, cpu_count
import numpy as np
from tqdm import tqdm
from ...file_utils import is_tf_available, is_torch_available
from ...tokenization_bert import whitespace_tokenize
from .utils import DataProcessor
if is_torch_avai... |
6fcbfef2a8d79a1f789bc43cd4483b7b6112ccca5493b7dfbc964d09a886a9a0 | Python | 28,122 | 718 | """
PyTorch Dataset and Sampler for Medical Images
ImageDataset: Loads individual images with optional augmentation
StudyAwareBatchSampler: Groups images from same study into batches
"""
import json
import torch
import numpy as np
import pandas as pd
import math
import logging
from torch.utils.data import Dataset, Sa... |
fe1c61ba69e013e1e6f14501bf9860cf35d6c27f7e5e413f16f41246b2af74ea | Python | 28,154 | 815 | from __future__ import annotations
import logging
import numpy as np
import pytest
from matplotlib.colors import to_hex
from PySide6.QtWidgets import QApplication, QLabel, QToolButton
import src.features.raw_photometry.photometry_processing_widget as raw_app
from src.dfer.df_common import expected_analysis_output_pa... |
366834d20f1f52bf6413f0c6ef94a1637c2de7303bc95191897cf5700e984e36 | Python | 28,155 | 654 | import numpy as np
import zarr
import cv2
from tqdm import tqdm
import os, shutil, sys
from pathlib import Path
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
import matplotlib as mpl
import zarr
from numcodecs import Blosc
import pandas as pd
import skimage
import pickle
from tangl... |
30a038d21f9c8a1337f17734c32197b07de08b85342c87cc3258784b543f770d | Python | 28,277 | 735 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Jul 14 11:14:05 2026
@author: vbp
Model-based analysis for Figure 3B-H and Figure S4 A, C, D, E, F, H.
Section -> panel mapping (see comments for details):
Fig 3B - predicted GRAB-DA, example session
Fig 3C, 3D - R2 score (pl... |
7b7276d16d737286bd0979f935193e7b12ac34081164701e0b2569d1935e0650 | Python | 28,283 | 796 | """The three mention-level scores: detection, linking, and what is masked.
Detection and linking are scored separately because a detection miss is
unrecoverable while a false positive is cheap, and the ignore set — mentions
distant supervision refuses to label — is masked rather than counted, since
calling a hit on on... |
367feafcf5ac8950e56b9b0d1eb3cbd314fa6c664b0535a9777be1b059d62505 | Python | 28,291 | 645 | import sys
import filesys as fs
import numpy as np
import ephys as ep
import matplotlib.pyplot as pl
def create_meta(ephysFolderPath, ephysFilePath):
'''create meta file to save identity of each of the channels'''
ch_num = ep.getchannelnumber(ephysFilePath)
version = ep.getversion(ephysFilePath)
pr... |
a9253ab30c4405121d02accbacc9d54004f13a29fb38580d7e025b609787572f | Python | 28,303 | 705 | # moovegui.py – PyQt6 main window
import os
import sys
import configparser
import shutil
import platform
import ctypes
import logging
import threading
import signal
import time
from pathlib import Path
# Import torch early to avoid DLL/OpenMP conflicts on Windows when
# scientific/GUI stacks (e.g., matpl... |
ca56bb2c43dcee90d7c334d2d5ce97303f7d9c657b9cb801765e4cf23a670da5 | Python | 28,437 | 925 | import copy
import csv
import glob
import json
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import os
from pathlib import Path
from scipy.interpolate import interp1d
import sys
import time
root_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
config_pat... |
14064858579e654cadc43642c3d76e6993a2abd69c164f0649c7e4921057849d | Python | 28,480 | 659 | #
# Copyright 2017-2023 Sandia Corporation. Under the terms of Contract DE-AC04-94AL85000 with
# Sandia Corporation, the U.S. Government retains certain rights in this software.
#
# See LICENSE for full license details
#
import sys, io, os, time, random
import numpy as np
import tensorflow.keras.backend as K
from simu... |
95b7fe082145b6ed39c538cdf0254d7b993d4940665fb2860f20e2b6101fadbf | Python | 28,546 | 698 | #!/usr/bin/env python3
import logging
from collections import OrderedDict, namedtuple
from typing import Dict, Optional
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch import Tensor
from fairseq import checkpoint_utils, utils
from fairseq.file_io import PathManager
from fairseq.models i... |
ae98a22be83376452544cb8d5f6b7197193a4d19d9f4b0b7e29245b9b2d8815b | Python | 28,645 | 683 | # 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
import json
import logging
import math
import os
from argparse import Namespace
from collections import OrderedDict, default... |
432597def375aad222b2ba9dcdb5b51b0a46b992e90f8a8e1641b091c8d3eb80 | Python | 28,661 | 756 | # 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
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import utils
from fairseq.models import (
Fai... |
5ea13c5cad0f7abf816938fc003f2819cf889e96bef54079b6f720c78baf74b5 | Python | 28,678 | 850 | # 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
import os
import re
import subprocess
from contextlib import redirect_stdout
from fairseq import options
from fairseq_cli import ... |
bf29d747ecab9650f3511e4ee8aa09c731bff129b9d0e57d063360bf349eb3a5 | Python | 28,679 | 754 | """ Very heavily inspired by the official evaluation script for SQuAD version 2.0 which was
modified by XLNet authors to update `find_best_threshold` scripts for SQuAD V2.0
In addition to basic functionality, we also compute additional statistics and
plot precision-recall curves if an additional na_prob.json file is p... |
e3f38f45f70febf873c64af5e2dd5dad1d62c26819d387ad6d586fb1641d4714 | Python | 28,691 | 774 | import logging
from functools import partial
from itertools import count
from statistics import mean, stdev
from typing import Any, Iterable, Sequence, Tuple
import jax
import jax.numpy as jnp
import jax.numpy.linalg as jnp_linalg
import jax_dataclasses as jdc
from jax import lax
from tqdm.auto import tqdm
from ..dev... |
9ff2690828612116d8800eed198eea41af1e346ae2a0fb3c4abfe8fe2ee5c5be | Python | 28,702 | 757 | """ Very heavily inspired by the official evaluation script for SQuAD version 2.0 which was
modified by XLNet authors to update `find_best_threshold` scripts for SQuAD V2.0
In addition to basic functionality, we also compute additional statistics and
plot precision-recall curves if an additional na_prob.json file is p... |
d8bb9fb85e177372938e08a16438676b6ec3c926705ee3e84d2663019efc5125 | Python | 28,730 | 916 | from __future__ import annotations
import json
import os
import textwrap
from pathlib import Path
from typing import TYPE_CHECKING
import pytest
from poetry.core.pyproject.exceptions import PyProjectError
from poetry.config.config_source import ConfigSource
from poetry.config.config_source import PropertyNotFoundE... |
c2ce76c7b126d23bb78956d24f9fb84b52aaa7c9bb647b9aebcb3eb679c154bc | Python | 28,756 | 743 | # 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.
"""
RoBERTa: A Robustly Optimized BERT Pretraining Approach.
"""
import logging
import torch
import torch.nn as nn
import torch.nn.functional... |
7d283daa95489020cf35bfa10fb4e92b019fd298cdda1831c2126c1f481d2054 | Python | 28,777 | 647 | import unittest
import networkx as nx
import numpy as np
from pgmpy.example_models import load_model
from pgmpy.factors import factor_product
from pgmpy.factors.discrete import DiscreteFactor
from pgmpy.independencies import Independencies
from pgmpy.models import DiscreteBayesianNetwork, DiscreteMarkovNetwork, Facto... |
50cb5bdbea7a42840016c9c80a4c09e1f047c0c2623db4b7e1acc31562b0b456 | Python | 28,789 | 810 | """The schema-driven BRENDA adapter, on synthetic splits.
None of these touch the ~300 MB BRENDA files. What is pinned is that every fact
the loader used to spell out inline is now read off the `Schema`: the columns
it indexes, the prefix each ID wears, and which class column a type owns. The
old loader hardcoded a fo... |
b9be93c2480afafe3d3fbff6d48c1e5ae17f0781130aa18a7bd2d2d60ed1ecb3 | Python | 28,871 | 746 | import matplotlib.pyplot as plt
import warnings
import numpy as np
import scipy.interpolate as interp
import matplotlib.pyplot as plt
def emd(x, t = 0, stop = np.array([0.05,0.5,0.05]), ndirs = 4, display_sifting = 0, MODE_COMPLEX = 2, MAXITERATIONS = 2000,
FIXE = 0, FIXE_H = 0, MAXMODES = 0, INTERP = 'cubic', mask =... |
e49e82fc2c9292513d2f1ce91a7663b341320eecd3c81a43c2f257450f02955d | Python | 28,892 | 966 | # -*- coding: utf-8 -*-
"""
Created on Thu Feb 20 00:24:20 2025
@author: hanna
"""
"""
Figure 4: Blockwise Changes in Neural Activity
Figure 5: shared space alignment (SSA)
Additional stats:
-number of factors (dshared)
-number of excluded, included BCI neurons
... |
d173e529c58ae37f82ff0a06c9d75d03830b73d43a04343a1d960b43191c82ce | Python | 28,896 | 548 | 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 scipy.stats import sem
from sklearn.decomposition import PCA
from sklearn.preprocessing import StandardScaler, MinMaxScaler, MaxAbsScal... |
da7959a5fb218f216da32a357fca5127d1cb154db1d56ffa5678d8beda08144c | Python | 28,901 | 845 | """Helper functions and Classes for topographic maps during Lossless QC."""
# Authors: Christian O'Reilly <christian.oreilly@sc.edu>
# Scott Huberty <seh33@uw.edu>
# License: MIT
from copy import copy
import warnings
from collections import OrderedDict
import plotly.graph_objects as go
from plotly.subplots i... |
ff7ea46fe16af3f8b5a26369807c6fa549741cdccd10bec45451af0d268e3cec | Python | 28,905 | 743 | import inspect
import logging
import warnings
from collections.abc import Callable, Sequence
from typing import Literal
import numpy as np
import pandas as pd
import torch
from scipy.sparse import issparse
from sklearn.covariance import EllipticEnvelope
from sklearn.mixture import GaussianMixture
from scvi import REG... |
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