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#! /usr/bin/env python # -*- coding: utf-8 -*- from main import main main(revisions=["issue583-base", "issue583-v1"])
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from itertools import chain def flatten_params(params: list[list[int]]) -> list[int]: return list(chain(*params))
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#! /usr/bin/env python # -*- coding: utf-8 -*- from main import main main(revisions=["issue571-base", "issue571-v1"])
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import numpy as np import pytest @pytest.fixture def rng() -> np.random.Generator: return np.random.default_rng()
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#! /usr/bin/env python # -*- coding: utf-8 -*- from main import main main(revisions=["issue549-base", "issue549-v3"])
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""" Placeholder for saving/loading masks/labels (future work). Currently unused; included to match agreed structure. """
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from cog import BaseRunner, Path class Runner(BaseRunner): def run(self) -> Path: return Path("hello.webp")
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# flake8: noqa from .archs import * from .data import * from .models import * from .utils import * from .version import *
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#! /usr/bin/env python # -*- coding: utf-8 -*- from main import main main(revisions=["issue583-base-v2", "issue583-v3"])
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#! /usr/bin/env python # -*- coding: utf-8 -*- from main import main main(revisions=["issue583-base-v3", "issue583-v5"])
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from .cnn import MLP, ContrastiveLearningNetwork, VICRegNetwork from .mil import MIL_Classifier, TransformerMIL, AdditiveMIL
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import json def load_json(filename): with open(filename,'r+') as f: data_dic = json.load(f) return data_dic
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#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Wed Aug 12 18:58:11 2020 @author: usingh """ version="0.0.4"
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from cobolt.model.coboltmodel import CoboltModel from cobolt.model.cobolt import Cobolt __all__ = ['CoboltModel', 'Cobolt']
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from .src.linear import linear_array as linear_array from .src.linear import linear_array_pipelined as linear_array_pipelined
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__all__ = ["icdParser", "oboParser", "efoParser", "reflectParser", "snomedParser"]
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# This file exists to implement "lastdir" as a global variable available in all modules # lastdir = '' ssfont = '' monofont= ''
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import torch class HardSigmoid(torch.nn.Hardsigmoid): def __init__(self) -> None: super().__init__(inplace=False)
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from .classifier import ClassifierTrainer from .domain_adaption import * from .generative import * from .self_supervised import *
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import werkzeug class AuthException(werkzeug.exceptions.HTTPException): code = 401 description = "Please authenticate"
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from .wavelets import Morlet, Paul, DOG, Ricker, Marr, Mexican_hat from .transform import cwt, WaveletAnalysis, WaveletTransform
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import importlib.metadata from .util import E3FPWarning, E3FPDeprecationWarning __version__ = importlib.metadata.version("e3fp")
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from .CSDPSynapse import CSDPSynapse from .goodnessModCell import GoodnessModCell from .maskedErrorCell import MaskedErrorCell
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from src.conv_onet.models import decoder # Decoder dictionary decoder_dict = { 'nice': decoder.NICE, 'imap':decoder.MLP }
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from .flywire import * from .hemibrain import * from .malecns import * from .manc import * from .aedes import * from .banc import *
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from dotenv import load_dotenv import pathlib path_env = pathlib.Path(__file__).parent.joinpath('paths.env') load_dotenv(path_env)
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"""Provide the primary functions.""" if __name__ == "__main__": # Do something if this file is invoked on its own pass
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# -*- coding: utf-8 -*- import sys from niftymic.application.multiply import main if __name__ == "__main__": sys.exit(main())
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from .hmc import HMCDataset from .isruc import ISRUCDataset from .p2018 import P2018Dataset from .sleep_edfx import SleepEDFxDataset
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#! /usr/bin/env python # -*- coding: utf-8 -*- import common common.generate_experiments(common.generate_configs(["foobar.sas"]))
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# setup.py from setuptools import find_packages, setup setup( name="median", version="0.1", packages=find_packages(), )
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"""Design custom probes for VisiumHD/VisiumFFPE/Single Cell Gene Expression Flex""" __version__ = "0.1.0" from .gene2probe import *
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from .train_scHetG import train_scHetG from .utils import ZINBLoss,cluster_acc,calculate_metric,cl_crition,calculate_ber,louvain
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# Copyright (c) OpenMMLab. All rights reserved. from .DPA_TISR_3D import DPATISR_3D from .RCAN import RCAN3D __all__ = ['DPATISR_3D']
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from .deform_conv import DeformConv, _DeformConv, DeformConvPack from .deform_conv import DeformConv_d, _DeformConv, DeformConvPack_d
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"""Allow running as ``python -m regtools.ccf_boundary_editor``.""" from regtools.ccf_boundary_editor.launch import main main()
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from .map_to_surface import * from .max_t import * from .max_r import * from .addNetColors import * from .addNetColors_Seaborn import *
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# -*- coding: utf-8 -*- import sys from niftymic.application.nifti2dicom import main if __name__ == "__main__": sys.exit(main())
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from common.backend import * from common.tracetype import * from common.frontendhelpers import * from common.agentmatrixinit import *
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import serial import serial.tools.list_ports print('\n') for p in serial.tools.list_ports.comports(): print(p.__dict__) print('\n')
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"""Allow running as `python -m regtools.geometry_registration`.""" from regtools.geometry_registration.launch import main main()
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# -*- coding: utf-8 -*- __all__ = ['all_utils', 'resnet_10_chan', 'train_for_epoch', 'training', 'validate', 'dataloader', 'screening']
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__all__ = ["convolution", "lowering_pass_conv"] from .convolution import convolution from .lowering_pass_conv import lowering_pass_conv
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from .checkpoint import * from .log import * from .parser import * from .util import * from .dataloading import * from .trainer import *
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from .cutoff import * from .embedding import * from .equivalent import * from .radial import * from .readout import * from .base import *
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from .layer import BatchNormedLinear as BatchNormedLinear from .layer import Linear as Linear __all__ = ["BatchNormedLinear", "Linear"]
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__all__ = ("tomllib",) import sys if sys.version_info >= (3, 11): import tomllib else: from pip._vendor import tomli as tomllib
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# -*- coding: utf-8 -*- import sys from niftymic.application.register_image import main if __name__ == "__main__": sys.exit(main())
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from PyQt5.QtGui import QFont font1 = QFont() font1.setPointSize(9) font1.setBold(False) cbFont = QFont() cbFont.setPointSize(7)
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from .arjun_vit import ArjunViT from .simple_vit import SimpleViT from .vanilla_transformer import VanillaTransformer from .vit import ViT
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import torch GPU_IDX = 2 DEVICE = torch.device(f"cuda:{GPU_IDX}" if torch.cuda.is_available() else "cpu") torch.cuda.set_device(DEVICE)
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# -*- coding: utf-8 -*- import sys from nsol.application.show_parameter_study import main if __name__ == "__main__": sys.exit(main())
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# Format-specific loaders for volume_io - each module exposes a single # ``_load_*`` function consumed by ``volume_io._dispatch_loader``.
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#%% import jax import jax.numpy as jnp #%% a = jnp.zeros([100, 100]) print(jax.devices('gpu')) b = a * a * a * a #%% print(b.devices())
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from typing import Protocol class NodeConstraintFn[PN, P](Protocol): def __call__(self, pattern_node: PN, graph_node: P) -> bool: ...
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# Neuroglancer viewer - view OME-Zarr volumes, NIfTI, TIFFs, and # precomputed point annotations in a self-hosted Neuroglancer instance.
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# SPDX-FileCopyrightText: 2024 Sergiu Deitsch <sergiu.deitsch@gmail.com> # # SPDX-License-Identifier: Apache-2.0 __version__ = '1.0.0.post1'
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""" OXASL: ASL processing pipeline This module is only for compatibility with the Quantipihyse widget """ from oxasl.pipeline import oxasl
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from .base import ManifoldParameter from .euclidean import Euclidean from .hyperboloid import Hyperboloid from .poincare import PoincareBall
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# -*- coding: utf-8 -*- import sys from niftymic.application.correct_bias_field import main if __name__ == "__main__": sys.exit(main())
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# -*- coding: utf-8 -*- import sys from niftymic.application.reconstruct_volume import main if __name__ == "__main__": sys.exit(main())
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import os from pathlib import Path codes = ["4ozs", "8H1B", "1BNA", "8U8W"] data_dir = Path(os.path.abspath(Path(__file__).parent / "data"))
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#!/usr/bin/env python """ MoCHI commandline tool """ import sys, os from pymochi import main if __name__ == "__main__": main.main()
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__version__ = "1.0.2" __all__ = [ "get_predictions", "MolNexTRSingleton", ] from .molnextr import get_predictions, MolNexTRSingleton
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# -*- coding: utf-8 -*- import sys from niftymic.application.segment_fetal_brains import main if __name__ == "__main__": sys.exit(main())
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# TODO: # Do a huge calculation with trivial primitive computations # and lots of diamonds and get a benchmark per-node time and # memory cost.
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# Copyright 2023 The Xron Authors. All Rights Reserved. # #This Source Code Form is subject to the terms of the GNU General Public License v3.0
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from .src.convolution import convolution from .src.lowering_pass_conv import lowering_pass_conv __all__ = ["convolution", "lowering_pass_conv"]
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from .logger import get_logger, setup_logging, SuppressShuffleWarning from .util import set_random_seed, config_add_subdict_key, override_n_genes
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# -*- coding: utf-8 -*- import sys from niftymic.application.rsfmri_estimate_motion import main if __name__ == "__main__": sys.exit(main())
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"""``python -m regtools.stitching`` -> launch the GUI.""" from regtools.stitching.launch import main if __name__ == "__main__": main()
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# only relative imports for the functionality to be accessible via spy.synthdata from .utils import * from .analog import * from .spikes import *
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from .blockV1_5 import * from .preact_block import * from .block_utils import * from .inverted_block import InvertedResidual, Conv2dNormActivation
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from .graph import Graph from .matching import MatchError, find_all_matches, match __all__ = ["match", "find_all_matches", "MatchError", "Graph"]
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from .base import Ensemble from .cellpack import CellPack from .star import StarFile __all__ = [ "Ensemble", "CellPack", "StarFile", ]
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# -*- coding: utf-8 -*- import sys from niftymic.application.multiply_stack_with_mask import main if __name__ == "__main__": sys.exit(main())
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"""More routines for operating on iterables, beyond itertools""" from .more import * # noqa from .recipes import * # noqa __version__ = '9.1.0'
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from . import base_module from . import distributions from . import unimodal from . import model from . import dataset_utils __version__ = "0.1.0"
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from .menu import register_templates_menu, unregister_templates_menu __all__ = [ "register_templates_menu", "unregister_templates_menu", ]
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from .amigos import * from .deap import * from .dreamer import * from .mahnob import * from .seed import * from .seed_iv import * from .mped import *
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"""Allow running as ``python -m regtools.manual_contour_registration``.""" from regtools.manual_contour_registration.launch import main main()
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from .annotation import create_anns_dataframe from .family_parser import get_families, assign_membership, get_hierachy from .data_manipulation import *
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import bl_ext.blender_org.molecularnodes as mn # type: ignore mol = mn.Molecule.fetch("4ozs") mol.add_style("cartoon", material="Ambient Occlusion")
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""" Global variables for the package """ __author__ = 'martinez' import numpy as np STR_PEAK_ID = 'peak_id' # Structs PK_COORDS = 'pk_coords'
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from mnp.utils.data_preparation import prepare_dockstring_scores prepare_dockstring_scores('plain', 'small') prepare_dockstring_scores('aug', 'small')
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import sys, os import pandas as pd import numpy as np try: inputfile = sys.argv[1] except: sys.exit("Please, give input file with count table")
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from .batch_normed_linear import BatchNormedLinear as BatchNormedLinear from .linear import Linear as Linear __all__ = ["BatchNormedLinear", "Linear"]
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from topaz.model.generative import ConvGenerator class ConvGenerator(): def test_init(self): pass def test_forward(self): pass
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from .base_transform import * from .any import * from .label import * from .numpy import * from .torch import * from .hooks import * from .graph import *
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from .identity_param_quantization import Identity from .quantized_optim import get_quantized_optimizer __all__ = ["get_quantized_optimizer", "Identity"]
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class Rom: def __init__(self, name: str, data_width: int, values: list[int]) -> None: self._name = name self._data_width = data_width
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"""Enhanced versions of the ASE Vasp calculator.""" from __future__ import annotations from quacc.calculators.vasp.vasp import Vasp __all__ = ["Vasp"]
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# -*- coding: utf-8 -*- import sys from niftymic.application.reconstruct_volume_from_slices import main if __name__ == "__main__": sys.exit(main())
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# Cell Analysis module for cell detection and region counting from .cell_counting import process_counts from .cell_detection import get_cell_locations
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import numpy as np import pandas as pd from topaz.utils.data.partition import stratify, kfold def test_stratify(): pass def test_kfold(): pass
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""" Output subpackage. GIF generation and matplotlib diagnostic visualization. """ from .gif import generate_axis_gif, generate_registration_gifs
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# -*- coding: utf-8 -*- from .model import VIDependencyModel from .parser import VIDependencyParser __all__ = ['VIDependencyModel', 'VIDependencyParser']
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from topaz.filters import AffineFilter,AffineDenoise,GaussianDenoise,InvGaussianFilter, gaussian_filter, inverse_filter class TestAffineFilter(): pass
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# -*- coding: utf-8 -*- from .nl import CellListNL from .basis import CutoffFunc, GaussianBasis, PolynomialBasis from .misc import AtomicOnehot, ANNOutput
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"""``python -m regtools.point_reorient`` -> launch the GUI.""" from regtools.point_reorient.launch import main if __name__ == "__main__": main()