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88b0546ded885d4dc7f5a78d7f9ffc16b1bf323a430eeb34ad8b6491a431ef63
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from __future__ import annotations __version__ = "0.41.2"
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BATCH_DIM = 0 FEAT_DIM = 1 SPATIAL_DIM = 2 TEMPORAL_DIM = 3
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Python
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from .edtf import EDTF from .localmedia import LocalMedia
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from Pose_multi_mmpose import Pose_multi_mmpose as Pose_cid
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Python
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from player import * from task import * from volume import *
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"""Shared MorphoGlia data contracts and core structures."""
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Python
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from .vanhateren import VanHateren from . import preprocess
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SLEEPEDFX_CHANNEL_LIST = [ 'FPZ-CZ', 'PZ-OZ' # *PSG.edf ]
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from ._modules import Module from ._modules import ConvBlock
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from .io import * from .image import * from .tiles import *
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from .app import main if __name__ == "__main__": main()
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from .flatten import flatten from .tracers import const_graph
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from .core import PhilipsPhysioLog, CouldNotFindThresholdError
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"""Package version.""" VERSION = "0.2" __version__ = VERSION
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VERSION = (1, 0, 0) __version__ = '.'.join(map(str, VERSION))
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from torch.optim import Adam from .radam import RiemannianAdam
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VERSION = (0, 3, 0) __version__ = ".".join(map(str, VERSION))
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class NoAuth: def auth(self): return {"email": ""}
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from .sim_clr import SimCLRTrainer from .byol import BYOLTrainer
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from .pdfam_gau_module import * from .pdfam_gmm_module import *
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VERSION = (1, 0, 10) __version__ = '.'.join(map(str, VERSION))
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# This file is protected via CODEOWNERS __version__ = "1.26.16"
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from .hadamardproduct import HadamardProduct as HadamardProduct
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from .filter import grouped_filter __all__ = ["grouped_filter"]
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from .oxford_pet import OxfordPetDataset, SimpleOxfordPetDataset
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from __future__ import unicode_literals TOMBO_VERSION = '1.5.1'
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from .dnn import Classifier, Feature_Extractor, Task_Classifier
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from .feature_extraction import * from .feature_reduction import *
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from Pose_multi_mmpose import Pose_multi_mmpose as Pose_multi_cid
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from .bcgan import * from .bgan import * from .eegfusenet import *
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from Pose_multi_mmpose import Pose_multi_mmpose as Pose_multi_dekr
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from .sepresidualblock import SepResidualBlock as SepResidualBlock
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from .src.measure_trigger import measure_trigger as measure_trigger
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import setuptools if __name__ == "__main__": setuptools.setup()
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from .ffn import FusedFeedForwardNetwork as FusedFeedForwardNetwork
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from .design import PrecomputedLutFunction as PrecomputedLutFunction
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from .eeg_signal import EEGSignalIO from .meta_info import MetaInfoIO
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options = None # test for dc0c8aa60b5960d240b0dcea270efa1e5a314a2c
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from primer.preprocess.rank_inverse_transformation import gaussianize
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__author__ = 'martinez' from .variables import * from .utils import *
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"""Connectome-derived dynamics coupled to a frozen language model."""
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def test_generate_description(): pass class TestMain(): pass
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"""Git-backed version detection and update for the RegTools repo."""
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from .io_inference import * from .models import * from .utils import *
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from .clean_segmentation import * from .io import * from .edit import *
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from ._guide_rna import GuideAssignment __all__ = ["GuideAssignment"]
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import matplotlib as mpl; mpl.use('qt5agg') from pylab import *; ion()
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from .model import BOLDModel from .timeIntegration import simulateBOLD
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__version__ = '1.0.11' import warnings warnings.filterwarnings("ignore")
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from .tcga_case import TCGA_Case from .tcga_project import TCGA_Project
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from . import _version __version__ = _version.get_versions()['version']
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from ._fpndecoder import FPNDecoder from ._unetdecoder import UNetDecoder
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from .frechet import frechet_mean from .manifolds import Poincare, Lorentz
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from .src.binary_filter import binary_filter __all__ = ["binary_filter"]
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# __init__.py from .predict_multi import * from .ImageUtilities import *
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# Copyright Jonathan Hartley 2013. BSD 3-Clause license, see LICENSE file.
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from Pose_detect_mmdetect import Pose_detect_mmdetect as Pose_detect_frcnn
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def test_example(): #placeholder test to appease linter assert True
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from .design import PrecomputedScalarFunction as PrecomputedScalarFunction
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__name__ = 'nsd_pressure' from . import model_opts from . import brain_data
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from . import Value_function, Decision_policy, Action_simulation, Evaluation
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from Pose_detect_mmdetect import Pose_detect_mmdetect as Pose_detect_rtmdet
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from .avgpooling1dflatten import AVGPooling1dFlatten as AVGPooling1dFlatten
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from .dataset import ProteinDataset from .utils import create_anns_dataframe
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from .aseutils import * from .generate_db import * from .convert_db import *
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import torch DEFAULT_DEVICE = 'cuda' DEFAULT_DTYPE = torch.float32 EPS = 1e-8
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from .resource_utils import find_project_root __all__ = ["find_project_root"]
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from .datasets import create_dataset from .dataloader import create_dataloader
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from .lap_spatial_only_module import * from .lap_spatial_param_module import *
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"""Vendored third-party code. Read-only — see SOURCE.txt for provenance."""
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from .utils import resize_padded from .process_ratings import create_label_files
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"""Legacy CLI entry point scripts (deprecated — prefer the ``hedpy`` CLI)."""
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from regtools.hub.launch import main if __name__ == "__main__": main()
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from .spherical_texture import SphericalTextureGenerator from .plotting import *
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__all__ = ['abstract_circuit', 'detailed_circuit', 'point_circuit', 'transform']
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#!/usr/bin/env python """Analysis code for the SAMPL and SAMPLing challenges."""
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from src.conv_onet import ( config, models ) __all__ = [ config, models ]
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from .base import Density from .grids import Grids __all__ = ["Density", "Grids"]
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# Any Python script in the scripts folder will be able to import from this module.
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from .sitk_tile import * from .sitk_point import * from .sitk_tile2volume import *
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from .binary import * from .select import * from .string import * from .fix import *
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from src.models.model_factory import get_classifier, get_regressor, get_regressor_v2
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"""The tensorlayer.cli module provides a command-line tool for some common tasks."""
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class IdsAggregator: def execute(self, adata): return adata.obs["index"]
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from .backbones import * from .modules import * from .plug_and_play import create_net
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"""__init__.py Initialises when agfusion module is loaded. """ __version__ = "1.5.0"
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"""MorphoGlia graphical user interface.""" from .app import main __all__ = ["main"]
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db = { 'host': '', 'user': '', 'password': '', 'database': '', 'port': 1 }
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import numpy as np from topaz.utils.picks import as_mask def test_as_mask(): pass
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from .actflowcalc import * from .actflowtest import * from .noiseceilingcalc import *
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from .random import * from .resize import * from .to import * from .contrastive import *
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""" Setup for Pyclamp """ from setuptools import setup setup(include_package_data=True)
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from .model_options import * from .feature_tools import * from .mapping_methods import *
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from setuptools import find_packages, setup setup(name="src", packages=find_packages())
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from .coreblock import UnlockDNACoreBlock __all__ = ( "UnlockDNACoreBlock", )
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from .model import * from .run import * from .run_with_timer import * from .util import *
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from .aalen_johansen import AalenJohansenMultiState __all__ = ["AalenJohansenMultiState"]
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# from .data import * # from .models import * # from .utils import * # from .train import *
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from .kernel import PW2AOkernel from .lcaodiag import LCAODiagKernel __version__ = '0.1.0'
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from topaz.model.utils import insize_from_outsize def test_insize_from_outsize(): pass