sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
cc6b93b3b4f22073de330de7f2ca16e63aa244bb3dafac78caf0a035804d9a28 | Python | 9,341 | 170 | import sys
import numpy as np
from tensorflow.keras import Sequential
from pdb import set_trace
from cvnn import logger
import cvnn.layers as layers
from cvnn.layers.core import ComplexLayer
from typing import Type, List
from typing import Optional
EQUIV_TECHNIQUES = {
"np", "alternate_tp", "ratio_tp", "none"
}
... |
4168add527bb861942df2253e55835af964b96c67c63bae20c63474fb9ebdb9c | Python | 9,352 | 268 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Step(_BaseTraceHierarchyType):
_parent_path_str = "indicator.gauge"
_path... |
07e65e6b2657518290a5ba2afb156ae74e417870fc3e71fd6235eacb2f250a81 | Python | 9,353 | 232 | from __future__ import annotations
import logging
import time
from typing import Optional
import numpy as np
from bream4.device_interfaces.devices.base_device import BaseDeviceInterface
from bream4.device_interfaces.devices.promethion import PromethionGrpcClient
DEFAULT_FLICK_DURATION = 3.0
DEFAULT_REST_VOLTAGE = 0... |
a49ed48f27c04d54c0c9259c5278936f3ee0e5408496012f966b71ac87a0a079 | Python | 9,356 | 222 | __author__ = 'Aaron Gudmundson'
__email__ = 'agudmund@uci.edu'
# from scipy.optimize import minimize, curve_fit
import matplotlib.pyplot as plt # Create Figures
# import scipy.ndimage as ndimage # Image Manipulation
# import scipy.linalg as linalg
# import scipy.sparse as sparse ... |
795d7fda974b70f1216fb16d7bf387883873af80d0a1251f1b1721ac330ae8ae | Python | 9,359 | 164 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'ObjectSpace/trial_dialog_ui.ui'
#
# Created by: PyQt5 UI code generator 5.6
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_TrialDialog(object):
def setupUi(self, TrialDialog... |
95dc22ab98b82202d254d3e26a9579b2c9d080924b51e5cb1b590138e12432f5 | Python | 9,359 | 267 | from functools import partial
import numpy as np
import pickle as pkl
import os
import mne
from mne.datasets import sample
from mne.simulation import simulate_raw, simulate_sparse_stc, add_noise, add_ecg, add_eog
EEG_CHANNELS = {
'EEG 001': 'Fp1',
'EEG 003': 'Fp2',
'EEG 008': 'F7',
'EEG 010': 'F... |
be496c14975fb4545a21f3e656617c8110e91645ea23355c11487efb9f6e84ac | Python | 9,359 | 279 | import os
import time
import numpy as np
import pickle as pkl
import nibabel as nib
from os.path import join as pjoin
from scipy.stats import pearsonr
from scipy.spatial.distance import cosine
from cxy_visual_dev.lib.predefine import proj_dir, get_rois
anal_dir = pjoin(proj_dir, 'analysis')
work_dir = pjoin(anal_dir, ... |
e2fab750d577ee52352d1484a11897f2b0b1e09b164f2062121601c98ae51f8a | Python | 9,359 | 308 | import networkx
import networkx as nx
import numpy as np
from anndata import AnnData
from scipy.spatial.distance import cdist
from stlearn.utils import _read_graph
def global_level(
adata: AnnData,
list_clusters: list[str],
w: float,
use_label: str = "leiden",
use_rep: str = "X_pca",
n_dims: ... |
e281b742d8067c961dd03dbbbd6dff335641b7e3406ea7f9ac4985df8926b421 | Python | 9,365 | 255 | from __future__ import annotations
import typing as t
from werkzeug.exceptions import BadRequest
from werkzeug.exceptions import HTTPException
from werkzeug.wrappers import Request as RequestBase
from werkzeug.wrappers import Response as ResponseBase
from . import json
from .globals import current_app
from .helpers ... |
67933b3dc4459dd342106dd93d8e9b99e6fec55d4d77dea1c4e3d6d003f07210 | Python | 9,366 | 261 | import pathlib
import shutil
import tempfile
import numpy as np
import pytest
import impose.data
import impose.structure
from impose import session
data_path = pathlib.Path(__file__).parent / "data"
def test_session_base():
"""Open a test session and extract data"""
path = data_path / "brillouin.impose-se... |
f847a60ab4cf1bd9531a01fee101b7ade676cf79f84b0e2d9d94980d5b2abfdc | Python | 9,369 | 248 | # SOURCE: vendored from aicb-ZhangLabs/Impeller @ main
# (model.py, classes PathGNN and PathGNNLayer)
#
# Impeller's flagship contribution: a path-based heterogeneous graph learning method for
# spatial transcriptomic data imputation (Bioinformatics 2024). `PathGNN` aggregates node
# features along pre-sampled random-w... |
c20a1f7c1958b734da0306e33c14a226206fdbef48c47fc0c69b8af0cc5e8574 | Python | 9,372 | 255 | """C03: the ONE immutable public InterventionSpec accepted at every door.
Surgery memo 3.1: ``tl.when(...)`` returns the immutable multi-clause spec;
the exact same object is accepted by ``fork.do``, ``fork.attach_hooks``,
``intervene=``, ``sweep``, and the save/load path. Lane options never enter
the spec, no lane si... |
ce69a778ca6eb3e708d7d7381291b8d176741ed29517d40ad359d7712eee0e5b | Python | 9,372 | 257 | """C03 row gate: the fire-evidence rule and the misfire test.
Leverage B6 / ledger D1a / edits D12, one substrate:
- FIRE EVIDENCE: ``intervention_audit`` is NEVER empty after an attempt --
every door (do/replay, do/set_only, capture ``intervene=``) writes one
transaction envelope, including no-fire and error out... |
99601fc42db886f0e26eb72ecfc2f29056e5805d5468c156d2170448f8c97e4e | Python | 9,374 | 319 | from pathlib import Path
import pytest
from pyrosm import get_data
@pytest.fixture
def test_pbf():
pbf_path = get_data("test_pbf")
return pbf_path
@pytest.fixture
def helsinki_pbf():
pbf_path = get_data("helsinki_pbf")
return pbf_path
@pytest.fixture
def helsinki_history_pbf():
pbf_path = get... |
a81d1826bc3917423d788c5269cf934459642941af2661c68e99ef059642f632 | Python | 9,374 | 280 | from plotly import exceptions, optional_imports
from plotly.graph_objs import graph_objs
pd = optional_imports.get_module("pandas")
def validate_table(table_text, font_colors):
"""
Table-specific validations
Check that font_colors is supplied correctly (1, 3, or len(text)
colors).
:raises: ... |
b7f13a990050d0ea87e73053819fb119c2fcc65b02364cd6a8cff8255bc1d5cc | Python | 9,375 | 231 | import time
import datetime
import serial
import logging
from pyoperant.interfaces import base_
from pyoperant import utils, InterfaceError
logger = logging.getLogger(__name__)
# TODO: Smart find arduinos using something like this: http://stackoverflow.com/questions/19809867/how-to-check-if-serial-port-is-already-ope... |
5592942893db53a2367073cb0ce8a48a7f9a0b1ecebcb719ddfcd8a77c72b5df | Python | 9,378 | 261 | """Base option parser setup"""
from __future__ import absolute_import
import logging
import optparse
import sys
import textwrap
from distutils.util import strtobool
from pip._vendor.six import string_types
from pip._internal.cli.status_codes import UNKNOWN_ERROR
from pip._internal.configuration import Configuration,... |
5e20984f3ca5569018a0af25582a86d8159e3f32c982aafddd5dbb59203a79d1 | Python | 9,378 | 252 | from typing import Dict, List, Tuple, Union
from PIL.Image import Image
from torch import Tensor
from lightly.transforms.gaussian_blur import GaussianBlur
from lightly.transforms.image_grid_transform import ImageGridTransform
from lightly.transforms.random_crop_and_flip_with_grid import RandomResizedCropAndFlip
from ... |
73ff0a24ad5090fd3b3e44241c230764cb9047b2758ca042656c054ddcb568ed | Python | 9,379 | 266 | #!/usr/bin/env python
import sys
if ((sys.version_info[0] < 3) or
(sys.version_info[0] == 3 and sys.version_info[1] < 10)):
print('rpy2 is no longer supporting Python < 3.10.'
'Consider using an older rpy2 release when using an '
'older Python release.')
sys.exit(1)
import enum
import i... |
11c21fda7562d9bc1600b23590fbb2d50357ffafd131e7dc2042f12df26b72b7 | Python | 9,382 | 210 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 29 18:04:08 2021
This is the configuration file for Experiment 2, post-cue delay length = 6 cycles variation. To run the experiment,
pass the path to the folder which is to contain the data from all Experiments on lines 179-180.
@author: emilia
"""... |
fdec9f167bd4bd0e5d4d20678d00dfd1536ec3d9a9fe7f3b7364b989e6d64828 | Python | 9,382 | 233 | """S2 marker-combination table TOTALITY test (P1 duty, S2-RATIFICATION sec 5).
Transcribes the ratified marker-combination table (S2-RATIFICATION.md sec 5)
plus the S2-AMENDMENT-01 deltas verbatim and proves TOTALITY: every cell of
the full axis product {capture_kind} x {structure_only} x {truncation} x
{per-step prov... |
9a461e22da09b665957f6c0a914b39a178f075b4dd192a39787c62d3ed66699f | Python | 9,383 | 233 | import math
import re
from collections import OrderedDict
import torch
import torch.nn.functional as F
from transformers import GPT2Config, GPTBigCodeConfig, PretrainedConfig
def remap_state_dict_hf_bigcode(state_dict, config: PretrainedConfig):
"""
Map the state_dict of a Huggingface BigCode model to be fla... |
4d2020879bd7d4f5cc7dc9ff4c534f01312962969520dc85e78611507cc71b20 | Python | 9,384 | 210 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 29 18:04:08 2021
This is the configuration file for Experiment 2, post-cue delay length = 7 cycles variation. To run the experiment,
pass the path to the folder which is to contain the data from all Experiments on lines 179-180.
@author: emilia
"""... |
43a86222b37488274513abea8767c45bb91f3260ad41b9f038c7536b9634fac2 | Python | 9,386 | 209 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 29 18:04:08 2021
This is the configuration file for Experiment 2, post-cue delay length = 2 cycles variation. To run the experiment,
pass the path to the folder which is to contain the data from all Experiments on lines 179-180.
@author: emilia
"""... |
b4b55097e163cf01e00036eea921e060cb5f151eb7e9ae52930f49fae8f6cdba | Python | 9,386 | 211 | import numpy as np
from keras.src import layers
from keras.src import ops
from keras.src import testing
from keras.src.layers.core.input_layer import Input
from keras.src.layers.input_spec import InputSpec
from keras.src.layers.input_spec import assert_input_compatibility
from keras.src.models import Model
class Ass... |
6a6dbb88396c46e4583b7aad53c4b1a95f7347bea979544e6a292edc14e6f38b | Python | 9,387 | 213 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 29 18:04:08 2021
This is the configuration file for Experiment 2, post-cue delay length = 4 cycles variation. To run the experiment,
pass the path to the folder which is to contain the data from all Experiments on lines 180-181.
@author: emilia
"""... |
b6fb8247fa8c3b4772a032cc4c00c1c002ed10688d2588c0be1e508387340a85 | Python | 9,387 | 212 | #!/usr/bin/env python3
# import required modules
from keras import layers
from keras import models
from keras import optimizers
from keras import regularizers
from keras import callbacks
from keras.models import load_model
from scipy import stats
import numpy as np
from argparse import ArgumentParser
import os
def p... |
d41a81f6f49dac9647bf7e7436ebe78d3479b4f4fb3853bd8b5a92e3249a8407 | Python | 9,393 | 313 | """
Main module for cleaning mimic data
Some functions copy pasted from https://github.com/huaxiuyao/Wild-Time/blob/main/wildtime/data/mimic.py
Additional reference: https://github.com/Google-Health/records-research/tree/master/graph-convolutional-transformer
"""
import logging
import os
import pickle
import random
i... |
c44c316b7784c6a92cb05f92dfd56cfd08ab2f44bd1c3fff9725d0eb5dc0d8f1 | Python | 9,394 | 303 | """
BoAmps data models for standardized AI/ML energy consumption reporting.
These dataclasses map to the BoAmps JSON schemas defined at:
https://github.com/Boavizta/BoAmps/tree/main/model
All fields use snake_case internally and are converted to camelCase on serialization.
"""
import re
from dataclasses import datac... |
35d718f969bed485881540941e8fba66634b490b43f30d04ef7c5927febdcac7 | Python | 9,395 | 296 | """Utilities for creating a transformnd.TransformGraph from OME-Zarr metadata."""
from __future__ import annotations
import posixpath
from collections.abc import Sequence
from typing import TYPE_CHECKING
import ome_zarr_models.v06.coordinate_transforms as ozmt
import transformnd as tnd
if TYPE_CHECKING:
import ... |
c3f1c09abe0a0d9c429e0d47f2b8d4a4ec09dbd11eec3d7dd9846babd717e43b | Python | 9,396 | 237 | import hashlib
import os
import urllib
import warnings
from typing import Any, Union, List
from pkg_resources import packaging
import torch
from PIL import Image
from torchvision.transforms import Compose, Resize, CenterCrop, ToTensor, Normalize
from tqdm import tqdm
from .model import build_model
from .simple_tokeni... |
8d2f6dadb14ba7c7effd6322e7f61b09519ca268144204a2d34667bd5a5c95bc | Python | 9,397 | 301 | """Phase 8b dispatch, warning, fork, and history tests."""
from __future__ import annotations
import warnings
from typing import Any
import pytest
import torch
import torchlens as tl
from torchlens.intervention.errors import (
DirectActivationWriteWarning,
EngineDispatchError,
ModelMismatchError,
Mu... |
a1f9ea4789ebcf26321e3c95fd3cef6be30636aa7957a69e1b13fd95931fa495 | Python | 9,403 | 306 | # -*- coding: utf-8 -*-
#
# pyoperant documentation build configuration file, created by
# sphinx-quickstart on Fri Mar 21 12:39:43 2014.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
#... |
9c2464d48ef7365de2a858ca203f86f222ec22b102725cff5d52cce80f1d5792 | Python | 9,404 | 289 | """Utilities for epoching data."""
import numpy as np
from spiketools.utils.checks import check_param_lengths
from spiketools.utils.extract import get_range, get_value_by_time, get_values_by_time_range
###################################################################################################
###############... |
33bd04e318ebf31ffa0430555760fb1acdbdca36c7f1af095c60c2cd586a8039 | Python | 9,405 | 250 | from builtins import super
import numpy as np
import numbers
from src.em_alignment import EMRegistration
def is_positive_semi_definite(R):
if not isinstance(R, (np.ndarray, np.generic)):
raise ValueError('Encountered an error while checking if the matrix is positive semi definite. \
Expected a ... |
d28195bf3ed076a62be364c390dfe620ee94d170fb9c2bebb1c0dd78a127dcc0 | Python | 9,406 | 236 | import torch
import warnings
import numpy as np
import torch.nn.functional as F
from NTD import NTD
from tqdm import tqdm
from sklearn.model_selection import ShuffleSplit
from utils import MSE, MAE, RMSE, MAPE, R2, generate_graph_Laplacian
from preprocessing import preprocessing
class GNTD():
# Initializatio... |
b741d71a475570b9f03135aa4866679bceab677cff664b0fbce0d220fbb155bb | Python | 9,410 | 300 | """Functions to generate """
import ast
from random import choices
from typing import List, Union
import pandas as pd
from rdkit.Chem import AllChem
from .utils import get_CIP_assignments, get_monomer_sequences
def get_valid_mols(smi_list):
mol_list = []
for smi in smi_list:
try:
AllChem... |
2cc094bb107c0a63cea9373370406074d34d06d50bb7e992e1c03a80d510c4ea | Python | 9,415 | 225 | import torch,math
from torch import nn
from torch_geometric.nn import MessagePassing
from torch_geometric.utils import softmax
import torch.nn.functional as F
from torch_scatter import scatter_add
from torch_geometric.nn.inits import glorot, zeros
from torch.nn import Parameter
try:
import apex
#ape... |
339181e5945b1089fb52c98361c4603db8a1715b978436f86d2c485759fed2c4 | Python | 9,415 | 188 | #!/usr/bin/env python
import h5py
import numpy
from diffusion_mapping import flatten_pathway
from projection_voxels import projection_from_json
default_vxl_shape = (132, 80, 114)
default_vxl_offset = numpy.array([0., 0., 0.])
default_vxl_dims = numpy.array([100., 100., 100.])
def write_flatmap(flattened_regions, co... |
7b792d734d81003dc1e6c21c544b3cdc38e2e3d3d2b8b9b16b63d02a1233958a | Python | 9,417 | 211 | import os
import torch
import pandas as pd
import scanpy as sc
import numpy as np
from sklearn import metrics
import multiprocessing as mp
from sklearn.metrics.cluster import adjusted_rand_score
from sklearn.metrics.cluster import (
v_measure_score, homogeneity_score, completeness_score)
import glob2
import matplot... |
b34fec705cd65d970799c49cd073bcd201b00f4d960be00ce0623d0304a26ee2 | Python | 9,417 | 259 | import json
import os
from collections import deque
from functools import partial
from http.server import SimpleHTTPRequestHandler, ThreadingHTTPServer
from pathlib import Path
from threading import Thread
import numpy as np
import pytest
import zarr
from ome_zarr.cli import main
from ome_zarr.format import CurrentFo... |
83660f267f66f300fe50767f04bdfbc6e26a13bca03b1dc4ced28b555aa98589 | Python | 9,421 | 176 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""tests for visualization of graphs"""
import tempfile
import unittest
import numpy as np
from scipy import sparse
from sknetwork.data.test_graphs import test_disconnected_graph, test_bigraph_disconnect
from sknetwork.data.toy_graphs import karate_club, painters, movie... |
a92dcab2a189e488e495404c1fb2f38acae085287ab08be101039861ae8cb469 | Python | 9,421 | 238 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created in March 2024
@author: Thomas Bonald <bonald@enst.fr>
@author: Ahmed Zaiou <ahmed.zaiou@capgemini.com>
"""
from typing import Union, Optional
import numpy as np
from scipy import sparse
from sknetwork.clustering import Louvain
from sknetwork.clustering.louvai... |
bcfe2dd091287dc538f0269cba29a720bf6dd3cd81cdfa73aabe952f2b3de339 | Python | 9,422 | 296 | from dataclasses import dataclass
from time import perf_counter
from itertools import repeat
from typing import Union
import jax
import jax.numpy as jnp
import plotly.io as pio
from pypdf import PdfReader
jax.config.update("jax_enable_x64", True)
pio.templates.default = "plotly_white"
# https://github.com/plotly/plot... |
9e6027f72bdb0885cd8a879ccfaec9d2e87666a536733f15abb87ae3baa90e5a | Python | 9,423 | 219 | """Utilities for parsing "Galaxy Flavored Markdown".
See markdown_util.py for loading objects and interacting with the rest of Galaxy.
This file is meant to be relatively self contained and just used to "parse" and validate
Galaxy Markdown. Keeping things isolated to allow re-use of these utilities in other
projects (... |
f419c6a7e1a23cd1218145d4b04f69950c4579bae59ab317be2eee3f92d1eeee | Python | 9,423 | 290 | from __future__ import annotations
from types import SimpleNamespace
import pandas as pd
import panel as pn
import pytest
from bokeh.document import Document
from larvaworld.portal.datasets import (
EndpointDataFrameTable,
LarvaDatasetTablesWidget,
StepDataFrameTable,
)
@pytest.fixture
def step_datafra... |
37376d4a9fb5e581bd0aed4942b20868312ec4fcae4bf25397163c30e65e0c04 | Python | 9,424 | 219 | import functools
import os
import shutil
from typing import (
Any,
)
from galaxy import exceptions
from galaxy.files.models import (
AnyRemoteEntry,
BaseFileSourceConfiguration,
BaseFileSourceTemplateConfiguration,
FilesSourceRuntimeContext,
RemoteDirectory,
RemoteFile,
)
from galaxy.util.c... |
63c3834a71b52e7c0dae2ecc9dc378ad26558d75d388f4fad7728dc8457fd213 | Python | 9,425 | 245 | # coding=utf-8
# Copyright 2024 The Google Research Authors.
#
# 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 applicab... |
64080c596ccfed1a8fc957136284d07ffd6c52856d7528bb294acebf06511f82 | Python | 9,425 | 261 | # SOURCE: vendored from pykt-team/pykt-toolkit @ main
# (pykt/models/atdkt.py + the ut_mask helper it imports from pykt/models/utils.py)
#
# AT-DKT (Auxiliary Task Deep Knowledge Tracing): an LSTM-based knowledge-tracing model
# (interaction embedding -> LSTM -> sigmoid output head) augmented, in its "predcurc"/
# "pre... |
ea999c2118af5917f530baeee6e61fb268d42963bbbebff760ab4c7d7f67b218 | Python | 9,426 | 235 | # -*- coding: utf-8 -*-
from __future__ import print_function, division
import os
import os.path
import json
import subprocess
import shutil
import sys
import glob
from global_config import *
generatingMultiViewImage = not generatingThicknessViewImage
# generatingMultiViewImage to eval/repeat MVCNN is deprecated
usin... |
17a288d4da63a12e1967ef059aefc5a8a35b67948ca27a3dba556cd1609098dd | Python | 9,429 | 264 | # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... |
e95eec7b30f6d460316fe3d3344c9a72cced96ade403c8830519cf2c3483436c | Python | 9,429 | 278 | """
Dataproviders that iterate over lines from their sources.
"""
import collections
import logging
import re
from . import base
log = logging.getLogger(__name__)
_TODO = """
line offsets (skip to some place in a file) needs to work more efficiently than simply iterating till we're there
capture tell() when pro... |
02fc51b82a633410ccf672ae8d32c4e030b9d252e7b8458be7fdb7eddb78f1ce | Python | 9,430 | 278 | import copy
import typing
from typing import List
import numpy as np
import pytest
import torch
import torch.nn.functional as F
from torch import Tensor, nn
from lightly.loss import DINOLoss
from lightly.models.modules.center import Center
from lightly.models.utils import deactivate_requires_grad
class OriginalDINO... |
4652251123e1ebf696bbf6fe835b79a763ec19341620888fd93dbc52f05bc1e6 | Python | 9,430 | 266 | import io
import av
from torch.utils.data import Dataset as TorchDataset, ConcatDataset, WeightedRandomSampler
import torch
import numpy as np
import h5py
import os
from datasets.helpers.audiodatasets import PreprocessDataset, get_roll_func
# specify AudioSet location in 'dataset_dir'
# 3 files have to be located the... |
f895843601bfeea87b94ca605206e9018b0a360b01b6c7765842374bb3a7f8d0 | Python | 9,430 | 266 | #!/usr/bin/env python3
"""
File: plot_cf_per_pic2.py
Created: 2022/05/10
Last Changed:
Author: M.Vochteloo
Copyright (C) 2020 University Medical Center Groningen.
A copy of the BSD 3-Clause "New" or "Revised" License can be found in the
LICENSE file in the root directory of this source tree.
"""
... |
a4fbd3dca212d0f0845dfa05a32cf4d30110b9a4b8410fbda84817667a9fe968 | Python | 9,431 | 271 | from typing import Any, Dict
import torch
from torch.nn import ReLU
from torch_geometric.nn import GATv2Conv, MessagePassing, global_add_pool
from .base_funcs import *
class GATEncoder(torch.nn.Module):
"""
Encoder layer to obtain the global state of each input graph.
The global state will be
"""
... |
2b388af40c7af910422de5fa7f56139ef64d10dfee0574f04cbeb5d2c3a43e1e | Python | 9,432 | 226 | """Artifact-registry contract tests (testing MEMO build rows A1/A2).
The registry is the ONE authority for real-model artifacts: closed row
schema, pinned revisions and per-blob digests, never-count enforcement for
R0 rows, the exact-key cache digest, the byte-budget cap formula, and the
consumes-never-constructs rule... |
cfcc01b9354918a039b23165e2956ca738105f3480346e0323794f384ee8794b | Python | 9,433 | 262 | # SOURCE: vendored from https://github.com/hlxin/tinnet @ master (c80f5d12d304)
# (tinnet/band_center.py's ConvLayer + CrystalGraphConvNet)
#
# TinNet (Lin, Wang, Cao, Xin, "Automated Discovery of Adsorbate-Metal
# Interaction Descriptors from Machine Learning with Physics-Informed
# Priors", Nature Communications 2024... |
c7203015bce032766ba555be0e5c0207c5dca3cbf76a73b92398396197f18a66 | Python | 9,435 | 268 | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import argparse
import xlsxwriter
from models import GraphConv, AE, LP
from utils import *
from sklearn.metrics import roc_curve, auc, roc_auc_score, precision_score, recall_score, f1_score, accuracy_score
parser = argparse.Argument... |
146d417547877fdc50d4c75d4a443818605a10f7c2ff6f2eb88cad7db1d4c859 | Python | 9,437 | 201 | class Model():
def __init__(self, model_name, input_shape, model_type):
self.model_name = model_name
self.model_type = model_type
if len(input_shape) == 4:
input_shape.append(input_shape.pop(1)) # change BCHW to BHWC
self.input_shape = tuple(input_shape)
self... |
ba80a267a99cee92039dacc2d23febce225ecd84286351fe7cae3059a4b5713b | Python | 9,438 | 208 | # Copyright (c) ByteDance, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
from timm.models.layers import DropPath
_cur_active: torch.Tensor = None #... |
0ce2682a9d15c7d2eb8736abd14ebc982efad1d7f4a7d9f022d6534a44634d82 | Python | 9,439 | 252 | """Tests for OSM(complete_relations=True): completing the member set of relations
that straddle a bounding box, so their geometries are correct (not cut at the box
edge). Uses the real bundled Helsinki extract and the downloadable history file."""
import pytest
import shapely
from pyrosm import OSM, get_data
@pytest... |
1c8e0109f94a31417c7dc678b2b2a0ed5886d08f58fb967b88fdb0f63ea14752 | Python | 9,439 | 224 | """Extract DICOM images """
import os
from os.path import join as opj
import numpy as np
import pydicom
from scripts.utils.constants import IGNORE_SAMPLES_AT_DATES, MRI_ROOTDIR, MRI_IMG_DIR, DWMRI_IMG_DIR, T2STAR_DIRS
from scripts.utils.minor_utils import min_max_norm
class DICOMImageExtractor():
""""Extract DI... |
14bd134595486c9563cfa82c035cf18c0b3331ad7ec4d2f1ea4f8679a1357385 | Python | 9,441 | 304 | import sys
sys.path.append('..')
sys.path.append('../..')
import os
import datasets as dat
from analysis_lib import *
import numpy as np
from copy import deepcopy
# Analyze freeform task, and produce HTML file with model outputs.
# Compare human and machine samples.
def analyze_mapping(sample):
# augment with annota... |
e6ea3a59eacdff4e727f1fc9648c5e1a5f1ffb0b8243f00dc90747b9b345cd4b | Python | 9,445 | 315 | import numpy as np
np.random.seed(13)
# VOCABS -- for DNA/RNA only for now
DNA = ["A", "C", "G", "T"]
RNA = ["A", "C", "G", "U"]
COMPLEMENT_DNA = {"A": "T", "C": "G", "G": "C", "T": "A"}
COMPLEMENT_RNA = {"A": "U", "C": "G", "G": "C", "U": "A"}
# exact concise
def _get_vocab(vocab):
if vocab == "DNA":
re... |
6c5dcce45a9e28eab4f6d69ef18d7389a23dd489384754a032ca051def753c20 | Python | 9,446 | 253 | """A-RAGGED-DOCS: routed-MoE neutral-grouper regression (COORDINATE test).
Pins foldB D11 on a real routed mixture-of-experts architecture family: the
landed episode grouper keys on successive top-level calls of the declared
stepped module, never on pass-interior graph equality — a ragged interior
(experts absent from... |
b6a664a0446c4c2366da50a80d691ccf768229093b89786ca01e29e1c7eb4670 | Python | 9,447 | 270 | """Memcached and in-memory cache result backend."""
from kombu.utils.encoding import bytes_to_str, ensure_bytes
from kombu.utils.objects import cached_property
from celery.exceptions import ImproperlyConfigured
from celery.utils import deprecated
from celery.utils.functional import LRUCache
from celery.utils.log impor... |
0272f2a5bb2bf4425e95edfe79c94517b06a3938cad86a3b0089440d6bd4d71e | Python | 9,449 | 268 | """The layer map: one declared stratum per package/module (C01 item 1).
The ten-layer model (architecture memo 3.1). A module's layer resolves
module attribute first (``__tl_layer__`` in the module), then the most
specific row here. ``FACADE`` is a ROLE, not a layer: thin, lazy,
logic-free modules whose deferred upwar... |
5067ebc58f3ac12d110c814b5cd8e29c5e79710bf789e2c91a16c8dbfa4c98f7 | Python | 9,449 | 213 | import numpy as np
import pandas as pd
import os
import glob
import math
import json
import scipy
import scipy.stats
import pickle as pckl
from PIL import Image
import model_analysis_folders.all_model_info as all_model_info
from torchvision import transforms
from analysis_scripts.helpers_16_choice import force_16_c... |
7b9fabf2cc3d7f5f5ae3adf0ad177b5d852c1a9933258c63ce42de7859a2e1bf | Python | 9,449 | 244 | import unittest
import numpy as np
import pickle
from os.path import join, abspath
from spitfire import ChemicalMechanismSpec, Flamelet, FlameletSpec
def construct_adiabatic_flamelet(initialization, grid_type, diss_rate_form):
test_xml = abspath(join('tests', 'test_mechanisms', 'h2-burke.yaml'))
mechanism = C... |
82be70ef15510062137ac0a62b6cee6c6b626f8b5d0d27c90b00c3632ceb173d | Python | 9,450 | 290 | from __future__ import annotations
import sys
import pytest
np = pytest.importorskip("numpy")
eigen_tensor = pytest.importorskip("pybind11_tests.eigen_tensor")
submodules = [eigen_tensor.c_style, eigen_tensor.f_style]
try:
import eigen_tensor_avoid_stl_array as avoid
submodules += [avoid.c_style, avoid.f_st... |
9c2ddb542ebedfcf895e41d952f14985d6eb58f4f92b272ee5fe3c0481793676 | Python | 9,450 | 254 | """Parse-time hardening for runnable descriptors (grind b3-l1, R10 supplement B)."""
from __future__ import annotations
import json
from pathlib import Path
import pytest
import torch
from torch import nn
import torchlens as tl
from torchlens._io.runnable_load import (
ContextFieldInvalidError,
_parse_rng_p... |
c2f4ca3a3cf9a4c6791feddc367a8a71be44708e323e0a6efc8222f3f93565eb | Python | 9,450 | 264 | import os
import json
import random
import itertools
import numpy as np
import torch
from collections import defaultdict
from src.data.tokenize import tokenize_pet_txt, tokenize_pet_mlm_txt
from src.utils.util import device
class GenericReader(object):
'''
GenericReader reads generic dataset
'''
def ... |
aed74d6857724d6792a86078ef44586495c428029fdd596d12dc478c3ae3ef25 | Python | 9,451 | 221 | from collections import Counter
import dgl
import numpy as np
def sigmoid(x: int):
""""
Compute sigmoid function by definition
"""
return 1/(1+np.exp(x))
def get_genes(graphs_nr: int, nodes_per_graph_nr: int, graph: dgl.DGLGraph):
"""
Compute the genes/features for all graphs
:param gra... |
6ef83815ea2dad5a6b007f62421b98cc9df743a0a51ca08e9fc9871ca71a8a17 | Python | 9,454 | 230 | import torch
import torch.nn as nn
import torch.nn.functional as F
import sys
sys.path.append("models/")
from .mlp import MLP
class GraphCNN(nn.Module):
def __init__(self, num_layers, num_mlp_layers, input_dim, hidden_dim, output_dim, final_dropout, learn_eps, graph_pooling_type, neighbor_pooling_type, device):
... |
d8104ee62f5943645971d59b47f3ad3c123342e41ec232efdfdac327661ce69b | Python | 9,454 | 263 | """Echo failure package: two tails, exact ordering, original exception wins.
Pins snoop memo test rows 5 and 7 (crash tails on both tiers, exact tail
order, exception identity preserved), the double-fault contract (a broken
sink never outranks the model's own error), interrupt handling, the
raise_on_nan composition (l... |
9b81d02cab43f25c34244dda29f774fb54ac402b1e1384b530972f7fb98f43d8 | Python | 9,456 | 252 | """tviz renderer Stage-0 deterministic checks (memo D3/D4/D13/D16/D21/section 7).
Emitter honesty rows that a deterministic check can prove and therefore
never consume judge budget: zero ``<image>`` elements in every numeric SVG,
PDF text extraction in order, disclosure lines rendered, pagination that
drops nothing, t... |
4c0b1323278c5f84bbce28ab11d3c86d4877f47061f5487872648e80e42905a9 | Python | 9,458 | 203 | # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... |
f63196f8b848ec11394f20b162000fb3def6e65eafb7961f52e645482cab21d0 | Python | 9,458 | 274 | import os
import math
import time
import datetime
from multiprocessing import Process
from multiprocessing import Queue
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import imageio
import torch
import torch.optim as optim
import torch.optim.lr_scheduler as lrs
class time... |
0c6752487a585278528bb2ca45755255a84bf590b3ffae533fa9b1cc136d8b48 | Python | 9,460 | 262 | """
Contract tests for data_conf.py configurations.
Tests configuration validation and contract adherence.
No I/O, pure validation logic testing.
Target: data_conf.py: 40.62% → 70% (+118 lines)
"""
import pytest
from larvaworld.lib.reg.stored_confs import data_conf
@pytest.mark.fast
class TestDataConfContracts:
... |
689540851554f29bc07b78922e5115049252c1eee3990e5c5b5286edc0440899 | Python | 9,462 | 309 | """L6 stage-4b attribution-kit behavior and detachability gates."""
from __future__ import annotations
import ast
import re
from pathlib import Path
from typing import Any
import pytest
import torch
from _source_corpus import module_ast, package_files
from torch import Tensor, nn
import torchlens as tl
from torchle... |
4b1374ab00092b7377a147953de98ea1420ee0400400520a57723eabf3c0a676 | Python | 9,464 | 253 | """
Functions to create trial-based tensors and warp times
"""
import inspect
from functools import wraps
from numbers import Number
import numpy as np
from .. import core as nap
def _validate_warping_inputs(func):
@wraps(func)
def wrapper(*args, **kwargs):
# Validate each positional argument
... |
b8648b2fa45087bf698a9b74a058795d324af8e83e4f3a08abe5212f4c98c294 | Python | 9,465 | 203 | # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... |
7a22a40008f909946924684b90c638f7d8e8bff079d7b038880bf00310480f09 | Python | 9,470 | 216 | # coding: utf-8
# code adapted from MoleImg https://github.com/MoleImg/Attention_UNet/blob/master/AttResUNet.py
import tensorflow as tf
from tensorflow.keras.layers import *
from tensorflow.keras import backend as K
'''
Hyper-parameters
'''
# network structure
FILTER_SIZE = 3 # size of the convolutional filter
DOWN_S... |
05930d5d6c0c8acab88f6a6c547b92e81878a4f7fb3082b11faa88f396abe965 | Python | 9,472 | 197 | from __future__ import division
from psychrnn.tasks.task import Task
import numpy as np
class DelayedDiscrimination(Task):
"""Delayed discrimination task.
Following a fore period, the network receives an input, followed by a delay. After the delay the network receives a second input. The second input channe... |
b473208a758160bbf0522a6073a6afacb9f293c1ef05250df7ca2efa09832f6a | Python | 9,476 | 321 | # coding=utf-8
# Copyright 2025 The Google Research Authors.
#
# 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 applicab... |
97f7e43d0e98541646cf800d8c005b85112b6b6d50566f97fc828ca998286187 | Python | 9,479 | 160 | __doc__ = """
Compute single trial bias estimates.
In order to run this file, you will need to first run the "analysis*.py" scripts. This will
generate backup files in the folder sim_backup.
This code was adapted from Fründ, Wichmann, Macke (2014): Quantifying the effect of inter-trial dependence on perceptual decisio... |
fcb307317258fee99694492c270754e253346f764abafc885e048305542cf576 | Python | 9,481 | 210 | """
Théo Gauvrit
Mai 2020
Compute the detection of Upstate and Downstates from two datasets(WT,KO).
Each Up/Downstates parameters from every files will be returned in a dataframe.
A dataframe (Metrics) can be returned to have visual of the detection in the signal in a plot.
"""
import numpy as np
import math as math
f... |
b45b476653b82a05235b36398f0b1972dda5a1499ec5cdbabd5d14cd18038e8c | Python | 9,482 | 292 | from conftest import get_distances
import numpy as np
from numpy.testing import assert_array_almost_equal
from scipy.spatial.distance import euclidean, mahalanobis
import pytest
from pytest import approx
from pyriemann.utils.distance import (
distance_euclid,
distance_harmonic,
distance_kullback,
dista... |
6f87667fe8c96f2b3dd2b3d884e8a5986be7355c5e162c6efc182320a5365a0d | Python | 9,483 | 231 | """Power spectrum plotting functions.
Notes
-----
This file contains functions for plotting power spectra, that take in data directly.
"""
from inspect import isfunction
from itertools import repeat, cycle
import numpy as np
from specparam.modutils.dependencies import safe_import, check_dependency
from specparam.ut... |
3aad61f46db35d2b076de0c3df6402a7dee3d23c7dc5dc0911f82ce6d07f0cd3 | Python | 9,489 | 285 | """Steering a HF decoder block as a MODULE site, KV cache on, agrees with a forward hook.
The common steering case: ``tl.when(tl.module("model.layers.0"), tl.steer(v))`` on a causal
LM whose ``use_cache`` is on. A module site is not an ``in_module`` region, so the region
refusal for exits into returned cache tensors (... |
6861942bf311b71875b348e409d515cc435c735657ccb1cd5aadca962381caac | Python | 9,489 | 240 | import inspect
from functools import partial
from typing import Callable, Iterable, Optional
import torch
import torch.nn.functional as F
from timm.models import _manipulate
from timm.models.vision_transformer import Attention, Block, VisionTransformer
from torch import Tensor, jit
def _checkpoint_seq(blocks: Iterab... |
3759e196e7a0a6541c303200ca6e092bcdc30613f9f3f3d61a53c9810a60103b | Python | 9,490 | 231 | # Fixes for defective mne functions
from collections import defaultdict
from distutils.version import LooseVersion
import os.path as op
import numpy as np
from mne.surface import read_surface
from mne.utils import get_subjects_dir, logger, verbose
from mne.label import _get_annot_fname, _n_colors, _write_annot
import... |
3f9d040e2d5f14ec75204ae592b2d8b2f28322e5ddca58107bcf9492e681be08 | Python | 9,491 | 246 | # %%
import numpy as np
import os
import pandas as pd
import itertools
from globals import threshold_distance
path = "/Users/ivan/Documents/aaa_online_stuff/coding/python/phd/expt17_spots/data"
sessions = range(1, 5)
subjects = [3, 4, 6, 7, 8, 9, 10, 11]
def euclidean_distance(x, y):
return np.sqrt(np.sum((x - ... |
6f97464580ccb38d4cbbc60b4eff734bf708f9666ccef1702903c500cfa3dc16 | Python | 9,491 | 230 | from __future__ import absolute_import, division, print_function
from . import swigwrapper # pylint: disable=import-self
# This module is built with SWIG_PYTHON_STRICT_BYTE_CHAR so we must handle
# string encoding explicitly, here and throughout this file.
__version__ = swigwrapper.__version__.decode('utf-8')
# Hack... |
14cff40525bd61bcf7da5dc6a0c92546d3014162efb13df6c4aea55d5f4d9628 | Python | 9,495 | 306 | # %%
'''
Perform statistics and plots on connectivity results
'''
from nilearn import plotting
from numpy.ma import mask_rowcols
import pingouin as pg
import seaborn as sns
import h5py
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from bct.nbs import nbs_bct
import sys
sys.path.insert(0, '..'... |
9149f4f5ff852775248ffdfcc9c4c032bfdc5d49a1798fd4bf2b323321aa2b3b | Python | 9,495 | 180 | #!/usr/bin/env python
from __future__ import print_function, unicode_literals, absolute_import, division
import argparse
import sys
from pprint import pprint
import numpy as np
from tqdm import tqdm
from csbdeep.io import save_tiff_imagej_compatible
from csbdeep.utils import _raise, axes_check_and_normalize
from cs... |
32bb2fcef3798d5ba31d6107ea34a63d718e2ed2e959ceedc50178c0a2f9cefd | Python | 9,496 | 268 | from pathlib import Path
from typing import Any, Dict, List, Tuple, Union
from pytorch_lightning import Trainer
from pytorch_lightning.callbacks import DeviceStatsMonitor, LearningRateMonitor
from pytorch_lightning.loggers import TensorBoardLogger
from timm.data import create_transform
from timm.data.mixup import Mixu... |
a4c76a67b34810bdbd0ce3267f9945da51b65c48bb068fa40aa44e05f73e44bb | Python | 9,496 | 310 | import torch.nn as nn
from modular_splicing.utils.construct import construct
from modular_splicing.models.modules.lssi_in_model import both_lssi_model_types
from modular_splicing.models.motif_models.types import motif_model_types
from modular_splicing.models.local_splicepoint_model_residual_propagator import (
Ea... |
2f21f4d5a3ff27f9d8de963f729ae50265c8b133662f16fb75a99eaf7ec62fe4 | Python | 9,497 | 289 | #!/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... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.