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from celery import Celery app = Celery() @app.task def plugh(): """This task is in a different module!"""
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"""GluonCV-Torch pose estimation.""" from __future__ import absolute_import from .directpose_resnet_fpn import *
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from F01 import F01 class F04(F01): c1_norm = (0.002, 0.01) norm_thresh_a = 0.2 norm_thresh_b = 0.5
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from pl_bolts.transforms.self_supervised.ssl_transforms import Patchify, RandomTranslateWithReflect # noqa: F401
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"""Code generated from protocol buffers specifications. This is used for communication with the user interface."""
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from celery import Celery app = Celery(set_as_current=False) app.config_from_object("t.integration.worker_config")
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"""CenterNet""" # pylint: disable=wildcard-import from __future__ import absolute_import from .center_net import *
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IMAGENET_DEFAULT_MEAN = (0.485, 0.456, 0.406) IMAGENET_DEFAULT_STD = (0.229, 0.224, 0.225) DEFAULT_CROP_PCT = 0.875
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import sys sys.path.append('/workspace/Walk_Video_PyTorch/project/utils') from metrics import * from utils import *
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""" Contains scripts and supporting modules for creating the spliceai-GTEx and spliceai-Canonical/GTEx datasets. """
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"""Legacy FRC namespace. No-reference single-image FRC helpers were removed from the tracked API. """ __all__ = []
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"""Torch image classification estimator""" from .torch_image_classification import TorchImageClassificationEstimator
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from .pdbbind import PDBbind from .ligand_expo import LigandExpo from .chembl import ChEMBL from .enzyme import ENZYME
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from celery import Celery app = Celery(set_as_current=False) app.config_from_object("t.unit.bin.proj.daemon_config")
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from .xpu import xp from . import cluster, traces, regression, stats, visualize, util, spatial __version__ = '0.0.0.1'
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"""Transform and augmentation for instance level manipulations""" from .augmentation import * from .transform import *
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""" Principal and independent components """ from . import pca from . import ica from . import jpca from . import dmd
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""" Integration tests for ethoscope_node. Integration tests test component interactions and external dependencies. """
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# pylint: disable=wildcard-import """SiamRPN tracking""" from __future__ import absolute_import from .siam_net import *
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from torch.optim.lr_scheduler import ReduceLROnPlateau SCHEDULER_REGISTRY = {"reduce_lr_on_plateau": ReduceLROnPlateau}
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""" GNN-SubNet: Disease Subnetwork Detection with Explainable Graph Neural Networks. """ from GNNSubNet import GNNSubNet
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""" ST Spot Detector server WSGI compliant web server for the ST Spot Detector. """ from .app import APP as application
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import sys paths = [ '/workspace/' ] for path in paths: if path not in sys.path: sys.path.append(path)
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""" Portal apps for configuring and running simulations. """ from __future__ import annotations __all__: list[str] = []
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from . import architectures, datafusion, interpret, modules, utils, functional, logs, train from tlib import tutils, tgeo
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"""tracking dataset,include youtube-bb,VID,DET,COCO dataset""" from __future__ import absolute_import from .track import *
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import pointnet2_ops.pointnet2_modules import pointnet2_ops.pointnet2_utils from pointnet2_ops._version import __version__
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from dcCustom.models.tensorgraph.tensor_graph import TensorGraph, TFWrapper #from dcCustom.models.tensorgraph import models
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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.test import TestCase # Create your tests here.
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from sys import argv from msp import MSP msp = MSP() msp.file = __file__ msp.seed = int(argv[1]) msp.window = 800 msp.run()
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""" Contains functionality of the newer XML defined external display applications (not hardcoded into datatype classes). """
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"""Conditioner layers for autoregressive normalizing flows.""" from tfep.nn.conditioners.made import MADE, generate_degrees
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# flake8: noqa: F401 from .simple_image_view import SimpleImageView from .wait_cursor import ShowWaitCursor, show_wait_cursor
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from . import common from .BeattieModel import BeattieModel from .KempModel import KempModel from .WangModel import WangModel
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def ensure_dir(f): import os d = os.path.dirname(f) if not os.path.exists(d): os.makedirs(d) return f
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from neuron import h, gui def test_nothing(): assert h.get_foo() == 42.0 if __name__ == "__main__": test_nothing()
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#from distutils.command.config import config from . import df, geotif, kml, landcover, plotter, utils from tlib import tutils
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import sys, os def blockPrint(): sys.stdout = open(os.devnull, 'w') def enablePrint(): sys.stdout = sys.__stdout__
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"""Utilities sub-module.""" from .spectral import trim_spectrum, interpolate_spectrum, interpolate_spectra, subsample_spectra
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#from deepchem.hyper.grid_search import HyperparamOpt from dcCustom.hyper.gaussian_process import GaussianProcessHyperparamOpt
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from . import clg_ from . import gk_ from . import lkp_ from . import warps from . import imgreg from . import stackreg
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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.contrib import admin # Register your models here.
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from . import parcellation_levels from .project import ParcellationProject from .tree_helpers import * from .plotting import *
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from flask import Flask import os app = Flask(__name__, template_folder=__path__[0] + "/templates") import angorapy.monitor.app
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class UnprocessedBulletinException(Exception): """ Raised when a bulletin fails certain validity checks (ex. MH) """ pass
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#from . import geometries #from . import registration #from . import sorting #from . import pipeline #from . import pipeline_utils
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from . import auxseg, filter, image from .normalize import normalize_total, select_hvf_seurat from .transform import log1p, scale
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from .tool import CLITool, CLIOption, KeyValueOption, AbsolutePathOption, FlagOption from .launcher import Launcher, SRunLauncher
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""" Test fixtures for ethoscope device package. This module contains reusable test fixtures and utilities for device testing. """
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from .biss import BissClassifier from .utils import save_prediction, get_volume_share from .metrics import compute_dice_coefficient
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from .core.trajectorydataframe import TrajDataFrame from .core.flowdataframe import FlowDataFrame from .io.file import read, write
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from .anndata import merge_h5ad_into_adata, write_subset_h5ad __all__ = [ "merge_h5ad_into_adata", "write_subset_h5ad", ]
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import pytest from webserver import app @pytest.fixture def client(): test_client = app.test_client() return test_client
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# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved from cpa.api import API from cpa.plotting import CPAVisuals
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#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. """A More Flexible Video models."""
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from neuron import h def test_valence(): assert h.ion_charge("K_ion") == 222.0 if __name__ == "__main__": test_valence()
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from .parcellation_level import ParcellationLevel from .aibs_level import AibsLevel from .binary_split_level import BinarySplitLevel
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from . import stats from . import utils from .file_access import AurynBinaryStateFile, AurynBinarySpikeFile, AurynBinarySpikeView
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"""GluonCV-Torch model zoo""" from .model_zoo import get_model, get_model_list from .action_recognition import * from .pose import *
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from __future__ import annotations import numpy as np ak_dtypes = np.number | np.bytes_ | np.datetime64 | np.timedelta64 | np.bool_
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from pydantic.main import BaseModel class APIMessage(BaseModel): message: str class APIRequest(BaseModel): data: APIMessage
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from .threshold_based import * from .regression_based import * from . import utils from . import threshold_based __version__ = '0.6'
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sim_results_dir = 'sim_results' plots_dir = 'plots' # sim_results_dir = 'sim_results_NoRecurrence' # plots_dir = 'plots_NoRecurrence'
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""" Padding helpers for "same" padding based on: https://github.com/rwightman/pytorch-image-models/tree/master/timm/models/layers """
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from pyabf.abf2.section import Section class DataSection(Section): def __init__(self, fb): Section.__init__(self, fb, 236)
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from __future__ import print_function from __future__ import division from __future__ import unicode_literals import dcCustom.utils.save
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import sys import os module_path = os.path.abspath(os.path.join('..')) if module_path not in sys.path: sys.path.append(module_path)
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from pl_bolts.metrics.aggregation import accuracy, mean, precision_at_k __all__ = [ "accuracy", "mean", "precision_at_k", ]
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from galaxy.util.resources import resource_string def get_example(filename: str) -> str: return resource_string(__name__, filename)
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if __name__ == "__main__": import alphamap.gui import multiprocessing multiprocessing.freeze_support() alphamap.gui.run()
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from .mesh import construct_cells, construct_surface from .point_clouds import construct_pc from .voxel import voxelize_mesh, voxelize_pc
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# DO NOT EDIT # This file is generated by the updateplotlyjs and updateplotlyjsdev commands in commands.py __plotlyjs_version__ = "4.1.1"
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from imodelsx import explain_dataset_iprompt, get_add_two_numbers_dataset, AugGAMClassifier def test_auggam(): m = AugGAMClassifier()
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from .label import run_label_transfer, run_rctd, run_single_r __all__ = [ "run_label_transfer", "run_rctd", "run_single_r", ]
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# stlearn/tl/__init__.py from . import cache, cci, clustering, label __all__ = [ "cache", "cci", "clustering", "label", ]
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import pytest from llspy.libcudawrapper import cudaLib requires_cuda = pytest.mark.skipif(not cudaLib, reason="Cannot test without CUDA")
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# -*- coding: utf-8 -*- # @Author : Yue Liu # @Email : yueliu19990731@163.com # @Time : 2022/9/21 0:29 import os __version__ = '1.0.0'
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"""regression module""" from sknetwork.regression.base import BaseRegressor from sknetwork.regression.diffusion import Diffusion, Dirichlet
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#!/usr/bin/env python """Package entry point.""" from stlearn.app import main if __name__ == "__main__": # pragma: no cover main()
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from pathlib import Path Path('debug_celeba').mkdir(exist_ok=True) Path('results').mkdir(exist_ok=True) Path('figures').mkdir(exist_ok=True)
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from .gaussian_process import morphofield_gp from .sparsevfc import cell_directions, morphofield_sparsevfc from .trajectory import morphopath
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from pl_bolts.models.detection.components.torchvision_backbones import create_torchvision_backbone __all__ = ["create_torchvision_backbone"]
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from infoclientLib import InfoClient ic = InfoClient('localhost', 15002, 'localhost', 15003) ic.add('roi-weightedave', 'active') ic.start()
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# pysam versioning information __version__ = "0.24.1" __samtools_version__ = "1.24" __bcftools_version__ = "1.24" __htslib_version__ = "1.24"
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# -*- coding: utf-8 -*- # @Author: gviejo # @Date: 2022-01-17 13:49:58 # @Last Modified by: Alxec # @Last Modified time: 2025-12-04 16:04:00
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"""BdPy data package. This package is a part of BdPy. """ from .bdata import BData from .utils import concat_dataset, vstack, metadata_equal
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from config import Config from flask_socketio import SocketIO def create_socket(): return SocketIO(message_queue=Config.CELERY_BROKER_URL)
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# pylint: disable=wildcard-import """YOLO Object Detection""" from __future__ import absolute_import from .darknet import * from .yolo3 import *
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from .__version__ import __version__ from .neighbors import * from .categorization import * from .DEanalysis import * from .visualization import *
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import sys sys.path.append('algo') sys.path.append('utils') sys.path.append('simulations') sys.path.append('out') sys.path.append('figures')
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import numpy as np import sys sys.setrecursionlimit(10000) _dtype_ = np.float64 _maxshape_ = 1e9 __all__ = ['_dtype_', '_maxshape_']
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# For backwards compatibility as memory_bank module was previously in loss module. from lightly.models.modules.memory_bank import MemoryBankModule
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"""Data sub-module.""" from .stores import (ModelModes, ModelSettings, ModelChecks, SpectrumMetaData, FitResults, SimParams)
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from .evaluator import Evaluator from .conf_ensemble_model_evaluator import ConfEnsembleModelEvaluator from .ranker_evaluator import RankerEvaluator
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from .metric import kmeans, louvain, calculate_metric from .read import setup_seed, sample, read_data from .utils import ZINBLoss, calculate_metric
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from .two_alt_choice import * from .lights import * from .place_pref_24hr import PlacePrefExp24hr from .three_ac_matching import ThreeACMatchingExp
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from sys import argv from msp import MSP from msp_fly import fly_am msp = MSP() msp.file = __file__ msp.seed = int(argv[1]) fly_am(msp) msp.run()
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from .detector import GroupFreeDetector from .loss_helper import get_loss from .ap_helper import APCalculator, parse_predictions, parse_groundtruths
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event_serializer = "pickle" result_serializer = "pickle" accept_content = ["pickle", "json"] worker_redirect_stdouts = False worker_log_color = False
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# flake8: noqa: F401 from .composite import StructureComposite from .composite_stack import StructureCompositeStack from .layer import StructureLayer