sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
4eb25ea785f853ddf02076a0968c57e4ca43c894acd97e130c34c08cdca9df16 | Python | 10,620 | 269 | # Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
from collections import OrderedDic... |
b97109461e8fc587e376c629ea7b7217e4ef289e1a8636db296df639a2adc810 | Python | 10,623 | 301 | # Misc utils to deal with summary stat files.
# Some parts of the code in this file originates from https://github.com/bulik/ldsc/,
# which is licensed under GNU General Public License v3.0
# See https://github.com/bulik/ldsc/blob/master/LICENSE for complete license.
import sys, os, re, logging, datetime
import numpy ... |
f19bc56f5ef8c670a5857487699b8eb9b4b338e10caefabd29fa0bd7e09e63f8 | Python | 10,632 | 451 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import csv
from pathlib import Path
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
import torch
from scipy.stats import pearsonr
from sklearn.metrics import mean_absolute_error, mean_squared_error
from tor... |
edf33c34bbfe2592cb2a668fd21b12b2ca1df1a8928bfbb4a489a4c367b54954 | Python | 10,634 | 295 | import os
import numpy as np
import lmdb
import pickle as pkl
from Bio import SwissProt
from goatools.obo_parser import GODag, GOTerm
NODE_TYPE_MAPPING = {
'biological_process': 'Process',
'molecular_function': 'Function',
'cellular_component': 'Component'
}
def create_goa_triplet(fin_path, fout_path, p... |
b3d624b7434ecd675a52d80e3f25b3e9e2abc5eb89a70db0491637920d564ffa | Python | 10,641 | 357 | """
* author: Abolfazl Danayi
* created on 01-01-2026-07h-03m
* copyright 2026
"""
GLOBAL_MUTE = True
import typing as T
import numpy as np
import keras
import pickle
import os
DEFAULT_Projects_Dir = "./Output/Models"
def log(msg: str):
print(msg, flush=True)
def imp_log(msg: str):
print("**** IMPORTANT ***... |
706852ac8844c87110fa07311607adad845d3727f480826c4c7d9ed706182379 | Python | 10,649 | 309 | #!/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... |
4b2516c0a5106b20ecd41d48904f5f682d16c3b4be95313cde52ba4c77f9d471 | Python | 10,651 | 255 | #!/usr/bin/env python
import argparse
import csv
import sys
import re
import os
def argsParse():
"""
Parsing input & outputs CSV files. Also takes in a boolean to indicate if
the raw reads are single-end or paired-end
"""
parser = argparse.ArgumentParser()
parser.add_argument("-d", "--design",... |
5a20497f1acc6965b844449db062676fbc315130d2051d87ab454125b7777205 | Python | 10,656 | 196 | #04 threehead
import sys
sys.path.append("..")
from modelR.backbones.mobilenetv2 import MobilenetV2
from modelR.backbones.mobilenetv3 import MobileNetV3
# from modelR.necks.conv_csa_drf_fpn_hbb import Conv_CSA_DRF_FPN,FC2_CSA_DRF_FPN,Cat_Conv_CSA_DRF_FPN,M_CSA_DRF_FPN
from modelR.necks.Three_Head import FC2_CSA... |
ef1f0080b906cfd5f9e0bddc00a0337e8626d991e824778557fddd61b97d4eb6 | Python | 10,658 | 211 | import os
import argparse
import torch
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import colors as mpl_colors # Renamed to avoid conflict
from src.utils import load_pretrained_ernierna, prepare_input_for_ernierna # Assuming creatmat is in prepare_input
from src.downstream_heads.closeness_model ... |
3d07d9de1dea393d2ae20d6cbaed7e39c313a9a5cd8afe4930a96e2937ffac76 | Python | 10,666 | 290 | import pandas #likely to go away for a streaming approach
import numpy
import logging
import gzip
import scipy.stats as stats
from . import GWASSpecialHandling
from .. import Exceptions
from ..Constants import SNP
from ..Constants import EFFECT_ALLELE
from ..Constants import NON_EFFECT_ALLELE
from ..Constants impor... |
a9ad3418ea00e1c5f0a38ba906ef9cd666ff362f6758e667071057b2113f0334 | Python | 10,666 | 270 | """End-to-end characterisation of OCE forces driving an ASE optimiser.
This script answers the operational question that closes Phase 1 of
the JCTC roadmap:
With a *real* (production) ridge-fit OCEModel and the analytic
gradients now in :mod:`oce.forces`, can the v1.0.0 basis act as
a useful force field f... |
89118b7733cfdbb00c4ab67de99a9893dcde2a6178a2b2e35ea84d470eac4934 | Python | 10,672 | 317 | # 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.modules.fairseq_dropout import FairseqDropout
... |
45655332b3789f36b4b14071eb837fca696811bfefcb7c15b977b41ff3b5f50c | Python | 10,674 | 351 | #!/usr/bin/env python3
"""
Utilities for running MSMC2 on tree sequences.
MSMC2 estimates effective population size trajectories from phased genotype data.
"""
import subprocess
import numpy as np
import pandas as pd
import tempfile
import os
from pathlib import Path
# Default MSMC2 binary location
MSMC2_DEFAULT = ... |
2df02c0c446fa68761bac031c1b38c3f75284e61040ba34a4be6a0b39b0f021a | Python | 10,677 | 250 | import unittest
from unittest.mock import patch
from pyecharts import options as opts
from pyecharts.charts import Line, Bar
class TestChartClass(unittest.TestCase):
@patch("pyecharts.render.engine.write_utf8_html_file")
def test_chart_dark_mode(self, fake_writer):
x_data = ["周一", "周二", "周三", "周四", ... |
935caad437cf6cb6ab6a5df497be0814a18c50c192caa2cf291c02f32797f53c | Python | 10,681 | 231 | #!/usr/bin/env python3
"""
═══════════════════════════════════════════════════════════════════════════════
EIF2S1 R3 REVISION — PIPELINE 3: DEPMAP CO-DEPENDENCY VALIDATION
═══════════════════════════════════════════════════════════════════════════════
Author: Drake H. Harbert (D.H.H.) | ORCID: 0009-0007-7740-3616
Affi... |
df0dfc45a02c2dac56957c37165ad2d082138a8f8e1ae2867f3298b932d29471 | Python | 10,684 | 305 | # 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 json
import logging
from typing import Dict
import numpy as np
import torch
import torch.nn.functional as F
from torch import nn
from... |
a7f5bfd4cc14301fbf009c21216347c0823788acd93d5e6ce5086845d8f2bc4d | Python | 10,700 | 288 | import numpy as np
from collections import namedtuple
# Define MATLAB-style color matrices
red_colors = np.array([
[0.8627, 0.0784, 0.2353], # Crimson
[1.0000, 0.1412, 0.0000], # Scarlet
[0.7255, 0.0000, 0.0000], # Cherry
[0.5020, 0.0000, 0.1255], # Burgundy
[0.5020, 0.0000, 0.0000], # Maroon
... |
6da294fc3c99db05a2225a6b5595be8d15ab8e0afbe855bb736c956e5a663f69 | Python | 10,705 | 273 | # 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 defaultdict
from dataclasses import dataclass, field
from typing import Dict, Any, List, Optional
impo... |
257a234151f46edfb069ca9c65afd0660f0e5930bce18bc69d16a9dbb8a93a22 | Python | 10,710 | 343 | """The taxid bridge resolves the corpus's names as written.
`other_organism_forms` also yields a genus abbreviation, because that is what
running text says; an index of NCBI's names is not running text. An
abbreviation NCBI lists under an unrelated taxon would make an entity whose
binomial resolved cleanly look contes... |
d8ce150d6af1dd8cec5e1be570f4461cee287b2325a39d925926f716bd551af3 | Python | 10,710 | 309 | """
Compute linear CKA between two TDANN (spacetorch) models with different spatial
weights on NSD stimuli. Supports subsampling units to keep covariance sizes
manageable.
"""
import argparse
from pathlib import Path
import numpy as np
import torch
from spacestream.core.paths import RESULTS_PATH
from spacestream.data... |
226803a4c6c5f9b1384317246ac909fd43a132f3ff67e2db176c64ad34d662f3 | Python | 10,712 | 221 | """Page 10: Efficiency & Progress."""
import streamlit as st
import plotly.express as px
import plotly.graph_objects as go
import pandas as pd
import numpy as np
from utils import PIPE_ORDER, PIPE_COLORS, style_figure
def render(store, dataset):
st.header("Runtime & Efficiency")
st.markdown(
"How lon... |
e54e9721e95eb0c5514a0f86f8c45c8aa463abe68eb3bfc6e16690604fc08d06 | Python | 10,718 | 258 | #!/usr/bin/env python3
"""Minimal HIPPIE trainer for the CVAE-only experiment harness.
Trains MultiModalCVAE on one or more datasets' CSVs and saves a checkpoint
for the G1–G7 experiments. Multi-dataset training is what makes conditioning
embeddings carry real information (single-source = degenerate conditioning =
pos... |
5976b30bf4533525573a6d7bcf5479335646e4861fc965fdad2125ba02147115 | Python | 10,728 | 309 | from __future__ import annotations
from typing import TYPE_CHECKING
import pytest
from poetry.core.constraints.version import Version
from poetry.repositories import Repository
from poetry.repositories import RepositoryPool
from poetry.repositories.exceptions import PackageNotFoundError
from poetry.repositories.leg... |
edad5802572b0100c4459f1c49aca8a2d881ca2f128b243abc72b2b2fba1d570 | Python | 10,729 | 235 | """Reproducibility harness for the lazy-evaluation work in ``filtering.Filter`` (epic #66, issue #139).
Converting eager operations to fused lazy query plans must not change results (hard invariant #5). CSV
reference files can't prove that -- serializing to text loses float precision, which is why the older
tests fall... |
84c06f3529e214332737c1720e3c4ea97fc77ffe4973ea284110463a42e5b4da | Python | 10,733 | 352 | """
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
from .atom_update_block import AtomUpdateBlock
from .base_layers import Dense, ResidualLayer
from .efficient impor... |
cceda95bf1cb190c3b3b8a4cc4203540d975642352e7f560e0015e77fd4a5d44 | Python | 10,738 | 269 | #!/usr/bin/env python3
"""
Generate B0 variants by adjusting spherical harmonic coefficients.
This script takes B0_registration_outputs_sweep files and generates variants by:
1. Extracting SH coefficients from b0_fitted_2d
2. Adjusting only high-order coefficients (order >= 3)
3. Keeping low-order coefficients (order... |
463f487b4c425d3dbb727c0dc8c77e51938920ded2d046f0efc9bf447cf08ebb | Python | 10,740 | 322 | #!/usr/bin/env python3
__all__ = ["_GraphRolesMixin"]
class _GraphRolesMixin:
"""Mixin class for handling roles in a causal graph."""
def get_role(self, role: str):
"""Return list of nodes in graph G with a specific role.
Parameters
----------
role : str
The role ... |
1ec35c6068471364f4a301e12752b1bdea0a18b0e9abc416410a65d6804e12d7 | Python | 10,741 | 262 | """Prints a Python sections file."""
import sys
from ..wr_tbl import prt_txt
from .tasks import SummarySec2dHdrGos
__copyright__ = "Copyright (C) 2016-2018, DV Klopfenstein, H Tang, All rights reserved."
__author__ = "DV Klopfenstein"
class WrSectionsBase(object):
"""Tasks for writing a sections file."""
d... |
b5866d298cfdd011a934a3974d91625ee0fc53945f7bba6189404bcaf551e170 | Python | 10,745 | 255 | import os
import argparse
import requests
import json
import re
import threading
from rich.console import Console
from rich.progress import Progress, SpinnerColumn, BarColumn, TextColumn
from rich.live import Live
from rich.table import Table
from config.PLIPProcessor import PLIPProcessor
from config.PDBInteractionExtr... |
320170f9b5c2545e3ca1e5f96de29d0c323ddcfe54854e7b06a80dea8c18e159 | Python | 10,755 | 323 | from lifelines.utils import concordance_index
import numpy as np
from sklearn.model_selection import StratifiedKFold
from sklearn.preprocessing import StandardScaler
from keras.models import Sequential
from keras.layers import Dense
from keras.regularizers import l1, l2
#from keras.optimizers import adam_v2, gradient_d... |
6e6f9b9fe2b2d37795665ea4f32b756e695f572faad0ae2dbe229b3892c7f12f | Python | 10,757 | 272 | import numpy
import numpy.testing
import pandas
import unittest
from metax import Exceptions
from metax.gwas import GWAS
from metax.gwas import Utilities as GWASUtilities
from metax.Constants import SNP
from metax.Constants import EFFECT_ALLELE
from metax.Constants import NON_EFFECT_ALLELE
from metax.Constants impo... |
56f247aa302173d0d5e071ac49ce65cd711bdd3118af98fa79c432e130f848cf | Python | 10,759 | 271 | """
HVM Fitter class for fitting linear readout layer for the HVM dataset
(highly inspired by/credit to: https://github.com/neuroailab/VisualCheese)
"""
import os
import sys
import numpy as np
from scipy.stats import pearsonr
from sklearn.linear_model import Ridge
from sklearn.model_selection import GridSearchCV
fro... |
efee17bf6390dea61667192230951ec7f5fb912b9306bd932b076c4f26ad9b7f | Python | 10,760 | 186 | import logging
from typing import List, Optional, Tuple
import lightning as L
import torch
from torch import Tensor, nn
from aestetik.data_modules.data_module import AESTETIKDataModule
from aestetik.metrics.loss_function import compute_loss
from aestetik.models.model import AE
logger = logging.getLogger(__name__)
cl... |
cb1ad3aa0ff16814e28ecfde5ef72773caf074b5b34a2790367b24caa94e627c | Python | 10,763 | 253 | from mdt.model_building.model_functions import SimpleModelCLFunction, WeightType, ModelCLFunction
from mdt.model_building.parameters import FreeParameter, DataCacheParameter, NoiseStdInputParameter
from mot.lib.cl_function import SimpleCLFunction
from mot.lib.kernel_data import Struct, PrivateMemory, LocalMemory
__aut... |
bfb0ba38b1e9f6916d3241f768be6ac8d4e0620624006a9c974a7715c0d46cd2 | Python | 10,764 | 309 | import copy
from collections import defaultdict
from copy import deepcopy
import pandas as pd
from simulation_encoder.logger import Logger
from simulation_encoder.loaders.loader import Loader
from simulation_encoder.loaders.arcade_loader import ARCADELoader
from simulation_encoder.loaders.gastruloid_loader import Gast... |
ab8e6a1af4e9fe57e45b6d2a2c1ef7cb04e09c66e378f7ef3b4ef758c95a1b6c | Python | 10,775 | 339 | import numpy as np
import pandas as pd
import pytest
from sklearn.ensemble import RandomForestRegressor
from sklearn.linear_model import LinearRegression
from sklearn.utils.estimator_checks import parametrize_with_checks
from pgmpy.base import DAG
from pgmpy.prediction.NaiveIVRegressor import NaiveIVRegressor
@pytes... |
3fbc20adb066e083eb8f06c0b258b8c9fbcc6dad689f25a9b3328587f51d4ab1 | Python | 10,776 | 343 | import math
import os
import numpy as np
import pandas as pd
import pytest
from anndata import AnnData
from numpy.testing import assert_raises
from scipy import sparse
from scvi.external import SysVI
def mock_adata(cells_ratio: float = 1):
"""Mock adata for testing."""
n_cells_base = 200
n_cells = int(n... |
a127f57bcd1c75d1448535358ab854aa7a41dec5ca75f0da673cd580cc3ae7ee | Python | 10,776 | 268 | import scipy
from msi_visual.normalization import spatial_total_ion_count, total_ion_count, median_ion
from sklearn.metrics.pairwise import euclidean_distances, cosine_similarity
from scipy.stats import entropy
import random
import time
import sys
import numpy as np
import matplotlib
from PIL import Image
imp... |
23ccdbb2b3be9ad734cabb6ff2b0cdc11545e86e3f72cc3d593a64e19a67a00a | Python | 10,777 | 265 | """Phase 14 — extend 3D universality test to BCC, FCC, and diamond cubic.
Adds 3 more 3D Bravais lattices to phase 13 (which had only simple cubic):
bcc_3d z=8 p_c = 0.24596 (Lorenz & Ziff 1998)
fcc_3d z=12 p_c = 0.19923 (Lorenz & Ziff 1998)
diamond_3d z=4 p_c = 0.43003 (van der Marck 1998... |
bbc3f4955b31b07ff0f49d50362478b18baee57c9d03505e1afe510f683baf45 | Python | 10,777 | 297 | """HIPPIE inference API — latent embeddings, UMAP projection, and HDBSCAN clustering."""
from __future__ import annotations
from pathlib import Path
from typing import Iterable, Optional, Tuple, Union
import numpy as np
import torch
# ----------------------------------------------------------------------
# KNN k-s... |
39ffa196aa86fe000d8d6f668db0d240f714eb7808d93e8b2d926f0ca81698ba | Python | 10,798 | 252 | import numbers
from collections.abc import Hashable
from typing import Any
import numpy as np
import pandas as pd
from joblib import Parallel, delayed
from pgmpy.base import DAG
from pgmpy.estimators import ParameterEstimator
from pgmpy.factors.discrete import TabularCPD
from pgmpy.models import DiscreteBayesianNetwo... |
449b0cb8ae19471c4a608736941f6ae8ef93b69cd81dbcdd6fb0dcb97a6ce234 | Python | 10,799 | 256 | """
sim.py
======
Driven Brunel (2000) network simulation with Markov input spike trains.
The recurrent network implementation is based on the NEST example:
"Random balanced network (alpha synapses) connected with NEST"
https://nest-simulator.readthedocs.io/en/stable/auto_examples/brunel_alpha_nest.html
"""
i... |
dd0a514dc8c5334d89eeef60d61aa2fc3224e21c905e9096abddf6260cc62c90 | Python | 10,799 | 263 | """
Slice Areas Clustering Module.
This module provides functionality for clustering the slice areas of chromatophores.
Each chromatophore is divided into a number of slices so that the underlying data are
represented by time series for each slice (with overall shape: n_frames x n_chromatophores x n_slices).
The... |
27a40feb2248b97a8caedfac5132e9f97dcf53707bd7ea3565ac6a6aae86f1a9 | Python | 10,803 | 211 | import logging
import warnings
import community
import networkx as nx
import numpy as np
import scipy.sparse as sparse
from umap import UMAP
from sklearn.manifold import TSNE
from numba import NumbaPerformanceWarning, NumbaPendingDeprecationWarning
from scipy.sparse import SparseEfficiencyWarning
from pynndescent impo... |
4bd215e0742f44b1a11c072bc0feb0d073a63ab21b360ea94bcd5df8ae63fc69 | Python | 10,804 | 369 | import numpy as np
from scipy.signal import correlate, find_peaks, cwt, ricker
from sklearn.ensemble import RandomForestClassifier
from scipy.interpolate import griddata
from scipy.ndimage.filters import gaussian_filter1d
from ...common.utils import printProgressBar
import multiprocessing
from functools import part... |
74da5615c15eafebdf1d0d8eb31c18e505b31926264e5c2d549c3d0787be6d7b | Python | 10,809 | 192 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'UI/HardwareWindowEdited.ui'
#
# Created by: PyQt5 UI code generator 5.9.2
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_MainWindow(object):
def setupUi(self, MainWindow: Q... |
55c9f9fce7453aa115d9632e7dca451f65b1c27846fd85d599551310c2940836 | Python | 10,831 | 463 | import csv
from pathlib import Path
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
import torch
from scipy.stats import pearsonr
from sklearn.metrics import mean_absolute_error, mean_squared_error
from torch_geometric.loader import DataLoader
from mod... |
91c725c0c158a845707ba19b9241ed06795a2a0ddcf9bf4f87196b89361550b3 | Python | 10,833 | 246 | # ##############################################################################
# GPLv3 LICENSE INFO #
# #
# Copyright (C) 2020 Mario S. Valdés-Tresanco and Mario E. Valdés-Tresanco ... |
998203e62dd0d8f591fc9e404a54930427218d8cf17d3f4cfbfd94dbdba37664 | Python | 10,833 | 287 | #!/usr/bin/env python
"""
Created on Mon Mar 23 16:45:00 2020
This file create functions used for demo_pipeline_voltage_imaging.py
@author: caichangjia
"""
#%%
from IPython import get_ipython
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider
import numpy as np
import os
import tensorflow as tf
impo... |
12b3c5890c41641571a52ba1122ff2ad6dffbe1f67365f1d0047215883624a30 | Python | 10,837 | 327 | # 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
import numpy as np
from omegaconf import II, MISSING, OmegaConf
from fairs... |
9be9a3eb6da361957da9d58bbfd54ee9ddb784e17b56f53397fa719ef473a99f | Python | 10,837 | 237 | import numpy as np
import numpy.testing as np_test
import pytest
from scipy.special import softmax
from pgmpy.factors.discrete import TabularCPD
from pgmpy.inference import DBNInference, VariableElimination
from pgmpy.models import DiscreteBayesianNetwork, DynamicBayesianNetwork
# The sample Dynamic Bayesian Network ... |
a333a989a133334160c7bdc29b6da2c6e3139c8e816b3ffd61c14454376ad7e7 | Python | 10,838 | 427 | """Typed public command-line interface for maintained GPN workflows."""
from __future__ import annotations
import importlib.metadata
import sys
from collections.abc import Sequence
from pathlib import Path
from typing import Annotated
from cyclopts import App, Parameter
from transformers import TrainingArguments
fr... |
688b3eee2d053cd273f3eeebc1a0adca13f7c269f8a5f15f686337e8c77a5fea | Python | 10,839 | 337 | #!/usr/bin/env python
"""Put the compiled and eager arms' epoch timings side by side.
Medians over repeats rather than one pair of numbers: the arms were
interleaved because a card throttles under load, and a mean would hand a single
thermal outlier the answer. The first epoch is tabulated apart from the rest
because ... |
71a42ba09526185098489dca0381ec2124b27ed9871399ce9f1c4100a3fb3e5f | Python | 10,841 | 304 | """`prefetch_layer_boundary_reads`: cross-batch overlap, and no cross-talk.
`_resolve_layer_boundary_cached` (see `test_layer_boundary_overlap.py`)
already overlaps one item's store read with the previous item's replay
*within* a batch. `prefetch_layer_boundary_reads` extends that across
batches: it submits batch `k +... |
e7e49aae532733a58388069081f42c4f7a7ed3b38b9aa963269821b7431cd929 | Python | 10,852 | 327 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Applies a previously trained RdF model to a properties.csv file"""
import csv
import shutil
from typing import List, Tuple, Literal
from pathlib import Path
import warnings
import numpy as np
import pandas as pd
import matplotlib
matplotlib.use("Qt5Agg")
import matp... |
d58da9a4d3d7d417954161b6175f4efacce896071e16f616e9387dc23bfc63cd | Python | 10,854 | 198 | # coding=utf-8
# Copyright 2018 The 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/LICENSE-2.0
#
# Unless required by applicable... |
0564e663df8b71941d6d07abc18cf8b5ff507800ccd8fae0cdf167becb4603e1 | Python | 10,855 | 199 | # coding=utf-8
# Copyright 2018 The 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/LICENSE-2.0
#
# Unless required by applicable... |
573a38c55aa31098dd25d19f10a76af38b0678c8043407eccf5ea9b3a6ef753d | Python | 10,861 | 336 | #!/usr/bin/env python3
import warnings
from typing import Callable, Union
import matplotlib.pyplot as plt
import numpy as np
import numpy.typing as npt
from scipy import sparse
from scipy.sparse.linalg import eigs
from .funcs import rect_PSP
from .matrix import transition_matrix
PSPFunc = Callable[[int, int, int], ... |
0efbc620e98ddc2dcfcef2eaa5e4847da0ad0eadf4ef97dc3934f6d842ab73e4 | Python | 10,864 | 346 | # 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... |
aff7d707aedd22bc6972115a4124a8fb7a103dad39f13acdcaad786a3c2438c6 | Python | 10,876 | 268 | #!/usr/bin/env python3
"""
Author: Ken Chen
Email: chenkenbio@gmail.com
"""
import argparse
from tqdm import tqdm
import pickle
import os
os.environ["TOKENIZERS_PARALLELISM"] = "false"
import json
import sys
import shutil
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch ... |
a6ac82c69792a5db4b02b302ce368a0853eba7d4c5b8d64d8e8e97bdec04a577 | Python | 10,882 | 281 | from functools import partial
import haiku as hk
import jax
import jax.numpy as jnp
import numpy as np
import pytest
from jax import random
from jax.experimental import enable_x64
from oneqmc import Molecule
from oneqmc.types import (
ElectronConfiguration,
ModelDimensions,
MolecularConfiguration,
Nuc... |
ce4cb0d1cb7c30436a2a1b4c05f195c212792f94a52fc6342e740f4c4ad54fbd | Python | 10,883 | 463 | import csv
from pathlib import Path
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
import torch
from scipy.stats import pearsonr
from sklearn.metrics import mean_absolute_error, mean_squared_error
from torch_geometric.loader import DataLoader
from mod... |
913dde5d84980a48e18a2c52a346497317b4529266f5cbefd0ba2a24354bf69d | Python | 10,887 | 311 | """
Tests for the sklearn-compatible GES class in pgmpy.causal_discovery.
"""
import numpy as np
import pandas as pd
import pytest
from skbase.utils.dependencies import _check_soft_dependencies
from sklearn.utils.estimator_checks import parametrize_with_checks
from pgmpy.base import PDAG
from pgmpy.causal_discovery i... |
b8223d0e87791d12a114d91f9e73b70cdaf03652ca32e4525b6ad8828142765f | Python | 10,888 | 293 | # 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 numpy as np
import torch
from . import Dictionary, FairseqDataset, data_utils
def collate(
samples,
pad_idx,
eos_idx,
... |
c798c25e856add3e1f1c79baa804460d7cab09801913611666f653d0a350e4d9 | Python | 10,890 | 316 | from __future__ import annotations
import os
from pathlib import Path
from types import SimpleNamespace
import matplotlib.image as mpimg
import numpy as np
import pandas as pd
import pytest
from matplotlib.figure import Figure
from src.features.behaviour_alignment.services.plot_service import save_image
from src.gui... |
4ee84c3ccc3659ca5c0cb1e5f0206b1ed3d8352a27f1f496aa74efb2bcac9914 | Python | 10,898 | 266 | import numpy as np
import matplotlib.pyplot as plt
import scipy as scipy
from scipy.signal import convolve
import collections
def find_ISI(spike_times1):
#spike_times = template_times_list[template_ID]
intervals = np.diff(spike_times1)
return intervals
def find_cISI(spike_times1, spike_times2, ... |
5a02479ff970c9f10d66540814ddf3441b1dbe3069ee9499724e96092112b2ad | Python | 10,898 | 313 | # 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 numpy as np
import json
class Metric(object):
def __init__(self, config, metric_names):
self.metric_names = metric_names
... |
d9afe0094f757782082dc69ce8c93c1e053beb0266101d4de0e61837d8e69b55 | Python | 10,900 | 268 | # 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.optim
from . import LegacyFairseqOptimizer, register_optimizer
@register_optimizer("adafactor")
clas... |
4170dce01978ab1daaf0f735d32bc96314440538daf21b54348e7178bf8affe2 | Python | 10,901 | 316 | from __future__ import annotations
import warnings
import torch
import torch.nn.functional as F
from torch.distributions import Distribution, LogNormal, Normal, constraints
from torch.distributions.utils import (
broadcast_all,
lazy_property,
logits_to_probs,
probs_to_logits,
)
from scvi import setti... |
46c3d09e40bcd22b32c52c257200398db52a1c75b8535d8f261867df661edade | Python | 10,904 | 198 | import contextlib
import gzip
import io
import json
from pathlib import Path
import sys
import tempfile
import unittest
from unittest.mock import patch
import nibabel as nib
import numpy as np
sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
import trainref3d_backend as backend
from trainref3d_fixtures im... |
94378487a84f0dd607f3bbee04ceb6b213d830b979458c18a231216e70b63bf4 | Python | 10,908 | 290 | """Every tracked metric has to say what its y-axis measures.
The glossary is the only record of a metric's unit — MLflow charts a key and
nothing else — so what these tests protect is its agreement with the keys the
code actually emits.
"""
import ast
import importlib
from pathlib import Path
import d3text.models
im... |
ba88c59cf165af6e1bf1533f874e61440758bf474559cc080f91d31410279f90 | Python | 10,908 | 288 | import os
import json
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
import dataclasses
from dataclasses import dataclass
import tqdm
import torch
import torch.nn as nn
from torch.utils.data import DataLoader, Dataset
from transformers import BertModel, BertTokenizer
from transformers import P... |
20324417d6fce345085fb6c19f4f607d41d49902078d06bc4920c7c89b70d077 | Python | 10,910 | 344 | """
Copyright (c) Facebook, Inc. and its affiliates.
Copyright (c) Microsoft Corporation.
Licensed under the MIT License.
Adapted from https://github.com/FAIR-Chem/fairchem/blob/main/src/fairchem/core/models/gemnet/layers/interaction_block.py.
"""
import math
import torch
from mattergen.common.gemnet.layers.atom_upd... |
ca1c331128fc885356c2e72d6e3f48d813a2fd9b5b982f6fe1ffbbfb300f342e | Python | 10,917 | 266 | #!/usr/bin/env python3
"""
Make UpSet plots and Venn diagrams comparing transcripts across SFARI, Patowary,
Joglekar, and ENCODE4 studies.
Transcripts are compared by intron chain:
multi-exon : 'chrom:strand:e1end-e2start,e2end-e3start,...'
mono-exon : 'chrom:strand:start-end:mono'
ISM filtering (Patowary and Jo... |
b59159d4ad15b59b4065033aa02a922b22fc6272f71f0708716e1369643e51e7 | Python | 10,918 | 297 | """
hippie-wf3dacg Dataset
===================
Loads paired (waveform, spike_times) data and converts spike_times → 3D ACG
on the fly (or from a precomputed cache), using NEMO's feature conventions:
waveform — 90-sample L∞-normalised peak-channel waveform (float32)
acg — (1, 10, 101) 3D autocorrelogram ten... |
b31e7fcccd0a9c953f0b5f84f468250949210223d99bd75b49fcbdf6f0f88220 | Python | 10,919 | 310 | # 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 torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import utils
from fairseq.incremental_decoding_utils import wi... |
dc361a9db7fe02ba1324dc20623a57dce4f1460cb5aab5b230627ab09dbd4932 | Python | 10,919 | 261 | # _*_ coding: UTF-8 _*_
# Version information START --------------------------------------------------
VERSION_INFO = \
"""
Author: ZHANG YUBO
Version-01:
2025-03 Inferring evolutionary relationship from multiple sequence alignment for three population
"""
# Version information END -----------... |
79536d5d34c54f45fc2c220627a43bc73c64cee7e4ed89d761c9f849c15768a9 | Python | 10,920 | 270 | import sys, pysam, time, os, copy, argparse, subprocess, random, re, datetime
import pysam
import numpy as np
from subprocess import Popen, PIPE, STDOUT
from argparse import ArgumentParser, SUPPRESS
from sys import exit, stderr
def subprocess_popen(args, stdin=None, stdout=PIPE, stderr=stderr, bufsize=8388608... |
04291b95fde268fea796399e7f7db19a1958b181657a8664385a10c53650e38e | Python | 10,925 | 297 | import collections
import operator
import os
from typing import Mapping
import matplotlib.pyplot as plt
import networkx as nx
import numpy as np
import pandas as pd
import scanpy as sc
import seaborn as sns
import tqdm
from sklearn.metrics.pairwise import cosine_similarity
from sklearn.preprocessing import MinMaxScale... |
706df39f3f0c411bc2d7d422e2963305fb8d3e2d4d44b02ac50af99296df1cf8 | Python | 10,935 | 320 | # 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... |
d98ef0b9925a8007547d30d65653ae55a89a2ab6434dbe9b26be84afc3719340 | Python | 10,940 | 244 | # from data.pathways.pathway_loader import get_pathway_files
import itertools
import logging
import numpy as np
import pandas as pd
from keras.layers import Dense, Dropout, Activation, BatchNormalization, multiply
from keras.regularizers import l2
# from data.pathways.pathway_loader import get_pathway_files
from data... |
daa0150a00a2144c700b03a854b7161036ad04563b9910fe12d94417a6f26144 | Python | 10,943 | 248 | """Stores miscellaneous data for medaka."""
# note this module is imported into setup.py, so do not use any
# non-stdlib packages
import importlib.resources
import os
import pathlib
# the models used by default for CLI entry points
default_models = {
'consensus': 'r1041_e82_400bps_sup_v5.2.0',
'variant': 'r10... |
5034b8759ab4cbb91804aa1fe989e0df82bfae4a61b8399802a3fc2ccc22ca38 | Python | 10,944 | 288 | # 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 dataclasses import dataclass, field
from itertools import chain
import numpy as np
import torch
import torch.nn.functional a... |
4b41092e7fa81e6384ffa19ddb8dddfd6861fdc33a1b6a67feb398e0286c6526 | Python | 10,946 | 308 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 28 15:51:12 2025
@author: vbp
Time-resolved regression weights for Figure 3I and 3J.
For each session x region, refits the R/S regression model (using each
session's already-fitted alpha, delta from the non-cross-validated
regression script) indep... |
9c71892e2c62b3edb44eab81829dc21690340416a77e26758cbecdb1e0f816e3 | Python | 10,946 | 292 | """Feature builder for perovskite + MOF subsets.
Walks data/<subset>/structures.json, enumerates 1F+2F+3F figures via the PBC
pipeline, bins 2F (distance) and 3F (angle), prunes low-support columns,
and writes:
data/<subset>/features.npz — compressed X matrix + feature index
data/<subset>/features_summary.json — ... |
be8c7d3835112bd3bca15a9773af800a2751febcafd7b89d3b44eedbcca41e58 | Python | 10,947 | 269 | #
# 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 numpy as np
import os, sys, pickle
#To import parameters
sys.path.append("../../.... |
8a801d962b03f73df2cf923a1e44001c39a0de09532216e4f85e07ef23ccfa64 | Python | 10,951 | 288 | # %% Imports and setup
import os
from pathlib import Path
import numpy as np
import tifffile as tiff
import matplotlib.pyplot as plt
from cellpose import models, io
from skimage.measure import regionprops, label
from skimage.color import label2rgb
from skimage.morphology import remove_small_objects
from skimage.segment... |
12703564c17aa5e421230dc4ba76ca8a3bc4909abf175221f11630dfbfb6208f | Python | 10,954 | 277 | import os
import torch
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import seaborn as sns
from torch_geometric.loader import DataLoader
from sklearn.model_selection import KFold
from sklearn.metrics import mean_absolute_error, mean_squared_error
from scipy.stats import pe... |
64f443bad196c8f0be4b6e4f13ebb5dc2e577780f6ff5b1765661160c0b8bfef | Python | 10,954 | 319 | from collections import defaultdict
from json import decoder
import math
from dataclasses import dataclass, field
from transformers import logging
from transformers.training_args import TrainingArguments
from src.sampling import negative_sampling_strategy
@dataclass
class KMAEModelArguments:
encoder_model_file_n... |
13d63f5d911b78da35a9666a7f56d55dd082134d7c527ecc24cbbf17419cfdbc | Python | 10,959 | 373 | """Fixtures used just by test_datasets"""
import json
import numpy as np
import pandas as pd
import pytest
SPLITS_JSON = {
"splits_csv_path": "splits/inputs-targets-paths-csvs/Mouse-Pup-Call.call.id-SW.frame-dur-1.5-ms.id-data-only.train-dur-1500.0.replicate-1.splits.csv",
"sample_id_vec_path": {
"te... |
3687c7097409258d6de42a8cb87e9a50bf08e69db02b03d44ffafc5e4d0d5f64 | Python | 10,962 | 253 | from __future__ import annotations
from pathlib import Path
from typing import Any
import numpy as np
import pandas as pd
from st_risk.data.harmonize import choose_reference_celltype_column, intersect_gene_names
from st_risk.data.io import open_h5ad
from st_risk.models.base import BaseSpatialModelOutput, BaseSpatial... |
1136e132f9d4b33177acd65023ce78056e3c5053286eafa67b52681ff0d117d0 | Python | 10,966 | 257 | """Controller for telemetry static settings and data-dict population."""
from __future__ import annotations
import json
import logging
import re
from pathlib import Path
from src.features.telemetry_alignment.io.static_input_builders import (
build_opto_cluster_entries,
build_photometry_cluster_entries,
n... |
4c5355d09d11ad07717b40dafce49c4cd961def620296e9d47cad259cf1e8076 | Python | 10,967 | 232 | """Utility functions for adding noise.
.. warning::
This tool is deprecated and will be removed in BPReveal 6.0.
It turns out that it's not very useful.
This program is needed for a reason that I don't quite understand - gmstar is
not picklable if I put it inside addNoise.py.
"""
import json
import random
imp... |
babea142be5fa80b083c8e76093b4748181f43b8bf5f4e8abba6b1f34e4ea4fb | Python | 10,967 | 287 | """
pipeline_utils.py — Shared utilities for MAP, MMP, and BDP pipelines.
"""
from __future__ import annotations
from typing import Any, Dict, List, Optional, Tuple
import numpy as np
from numpy.typing import NDArray
from da4bci.metrics.distance import (
compute_mmd,
compute_wasserstein,
compute_energy,... |
103552fcd1f0de5f3def85631b1c1e413eb60623d9c03867c815504d6e61e29c | Python | 10,970 | 280 | import pathlib
import crowsetta
import evfuncs
import numpy as np
import pytest
import vak.common.annotation
def test_files_from_dir(annot_dir_notmat, annot_files_notmat):
annot_files_from_dir = vak.common.annotation.files_from_dir(
annot_dir_notmat, annot_format="notmat"
)
annot_files_notmat =... |
f6e89e3d4d9881e2b9b817e9dc887a99c918a37b27deb79d9a2a43f8d5239ba5 | Python | 10,976 | 302 | """
Full XAI implementation for the proposed Hybrid ViT-L/32 + MaxViT-L model.
Methods:
1. SmoothGrad
2. Integrated Gradients
3. Occlusion Sensitivity
4. LIME
5. Grad-CAM
6. Grad-CAM++
7. Score-CAM
Output:
A paper-style comparison grid with the following columns:
Original | SmoothG... |
4e3aa295b6258ae2a7605ceb42495ced65051c1d0a1c5f00b9abd517bff7643b | Python | 10,977 | 377 | from __future__ import annotations
import contextlib
import os
import re
import shutil
from importlib import metadata
from pathlib import Path
from typing import TYPE_CHECKING
import keyring
from poetry.core.packages.package import Package
from poetry.core.packages.utils.link import Link
from poetry.core.vcs.git im... |
9731d4d5fe832fcd18f9f1405c651fd6c7e5b9bfeaed747d99deb92910c921dc | Python | 10,978 | 294 | import typing
from functools import partial
from typing import Protocol
import jax
import jax.numpy as jnp
import kfac_jax
from .device_utils import DEVICE_AXIS
from .optimizers import OptEnergyFunction
from .physics import (
LaplacianOperator,
NuclearPotential,
local_energy,
loop_laplacian,
nucle... |
c7b0d3a213e09e3a370ddabd748ba41813414ddcefc75ad6d168c0c6724a14c7 | Python | 10,986 | 307 | import copy
import pytest
import torch
from vak import metrics
from vak.nets import TweetyNet
import vak.models
from .conftest import (
MockEncoder,
MockDecoder,
)
class TweetyNetDefinition:
"""Redefine here to test that ``vak.models.definition.validate``
actually works on classes we care about.
... |
93106b324385601a47f3b8ebf124e0a873bad19aa95ff38dc33ba87cb8f5adb3 | Python | 10,997 | 341 | import json
import math
import numpy as np
import pandas as pd
import pytest
import vak.common # for constants
import vak.common.annotation
import vak.prep.spectrogram_dataset.spect_helper
import vak.prep.split.split
NUM_SAMPLES = 10 # number of times to sample behavior of random-number generator
def train_test... |
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