Demo auto-generated version of skimage.filters

autogen_skimage_filters_init.py

def lazy_install(module_name, submodules, submod_attrs):
    """
    Defines gettr for lazy import via PEP 562
    https://www.python.org/dev/peps/pep-0562/
    """
    import sys
    import importlib
    import importlib.util
    all_funcs = []
    for mod, funcs in submod_attrs.items():
        all_funcs.extend(funcs)
    name_to_submod = {
        func: mod for mod, funcs in submod_attrs.items()
        for func in funcs
    }

    def require(fullname):
        if fullname in sys.modules:
            return sys.modules[fullname]

        spec = importlib.util.find_spec(fullname)
        try:
            module = importlib.util.module_from_spec(spec)
        except:
            raise ImportError(f'Could not lazy import module {fullname}') from None
        loader = importlib.util.LazyLoader(spec.loader)

        sys.modules[fullname] = module

        # Make module with proper locking and get it inserted into sys.modules.
        loader.exec_module(module)

        return module

    def __getattr__(name):
        if name in submodules:
            fullname = f'{module_name}.{name}'
            attr = require(fullname)
        elif name in name_to_submod:
            modname = name_to_submod[name]
            module = importlib.import_module(
                f'{module_name}.{modname}'
            )
            attr = getattr(module, name)
        else:
            raise AttributeError(f'No {module_name} attribute {name}')
        # Set module-level attribute so getattr is not called again
        globals()[name] = attr
        return attr
    return __getattr__

__getattr__ = lazy_install(
    __name__,
    submodules={
        'edges',
        'lpi_filter',
        'rank',
        'ridges',
        'setup',
        'tests',
        'thresholding',
    },
    submod_attrs={
        'edges': [
            'HFARID_WEIGHTS',
            'HPREWITT_WEIGHTS',
            'HSCHARR_WEIGHTS',
            'HSOBEL_WEIGHTS',
            'PREWITT_EDGE',
            'PREWITT_SMOOTH',
            'ROBERTS_ND_WEIGHTS',
            'ROBERTS_PD_WEIGHTS',
            'SCHARR_EDGE',
            'SCHARR_SMOOTH',
            'SOBEL_EDGE',
            'SOBEL_SMOOTH',
            'VFARID_WEIGHTS',
            'VPREWITT_WEIGHTS',
            'VSCHARR_WEIGHTS',
            'VSOBEL_WEIGHTS',
            'd1',
            'farid',
            'farid_h',
            'farid_v',
            'laplace',
            'p',
            'prewitt',
            'prewitt_h',
            'prewitt_v',
            'roberts',
            'roberts_neg_diag',
            'roberts_pos_diag',
            'scharr',
            'scharr_h',
            'scharr_v',
            'sobel',
            'sobel_h',
            'sobel_v',
        ],
        'lpi_filter': [
            'LPIFilter2D',
            'constrained_least_squares',
            'eps',
            'forward',
            'inverse',
            'wiener',
        ],
        'rank': [
            'autolevel',
            'autolevel_percentile',
            'bottomhat',
            'enhance_contrast',
            'enhance_contrast_percentile',
            'entropy',
            'equalize',
            'geometric_mean',
            'gradient',
            'gradient_percentile',
            'majority',
            'maximum',
            'mean',
            'mean_bilateral',
            'mean_percentile',
            'median',
            'minimum',
            'modal',
            'noise_filter',
            'otsu',
            'percentile',
            'pop',
            'pop_bilateral',
            'pop_percentile',
            'subtract_mean',
            'subtract_mean_percentile',
            'sum',
            'sum_bilateral',
            'sum_percentile',
            'threshold',
            'threshold_percentile',
            'tophat',
            'windowed_histogram',
        ],
        'ridges': [
            'compute_hessian_eigenvalues',
            'frangi',
            'hessian',
            'meijering',
            'sato',
        ],
        'setup': [
            'base_path',
            'configuration',
        ],
        'tests': [
            'setup',
            'teardown',
        ],
        'thresholding': [
            'apply_hysteresis_threshold',
            'threshold_isodata',
            'threshold_li',
            'threshold_local',
            'threshold_mean',
            'threshold_minimum',
            'threshold_multiotsu',
            'threshold_niblack',
            'threshold_otsu',
            'threshold_sauvola',
            'threshold_triangle',
            'threshold_yen',
            'try_all_threshold',
        ],
    },
)

def __dir__():
    return __all__

__all__ = ['HFARID_WEIGHTS', 'HPREWITT_WEIGHTS', 'HSCHARR_WEIGHTS',
           'HSOBEL_WEIGHTS', 'LPIFilter2D', 'PREWITT_EDGE', 'PREWITT_SMOOTH',
           'ROBERTS_ND_WEIGHTS', 'ROBERTS_PD_WEIGHTS', 'SCHARR_EDGE',
           'SCHARR_SMOOTH', 'SOBEL_EDGE', 'SOBEL_SMOOTH', 'VFARID_WEIGHTS',
           'VPREWITT_WEIGHTS', 'VSCHARR_WEIGHTS', 'VSOBEL_WEIGHTS',
           'apply_hysteresis_threshold', 'autolevel', 'autolevel_percentile',
           'base_path', 'bottomhat', 'compute_hessian_eigenvalues',
           'configuration', 'constrained_least_squares', 'd1', 'edges',
           'enhance_contrast', 'enhance_contrast_percentile', 'entropy', 'eps',
           'equalize', 'farid', 'farid_h', 'farid_v', 'forward', 'frangi',
           'geometric_mean', 'gradient', 'gradient_percentile', 'hessian',
           'inverse', 'laplace', 'lpi_filter', 'majority', 'maximum', 'mean',
           'mean_bilateral', 'mean_percentile', 'median', 'meijering',
           'minimum', 'modal', 'noise_filter', 'otsu', 'p', 'percentile',
           'pop', 'pop_bilateral', 'pop_percentile', 'prewitt', 'prewitt_h',
           'prewitt_v', 'rank', 'ridges', 'roberts', 'roberts_neg_diag',
           'roberts_pos_diag', 'sato', 'scharr', 'scharr_h', 'scharr_v',
           'setup', 'setup', 'sobel', 'sobel_h', 'sobel_v', 'subtract_mean',
           'subtract_mean_percentile', 'sum', 'sum_bilateral',
           'sum_percentile', 'teardown', 'tests', 'threshold',
           'threshold_isodata', 'threshold_li', 'threshold_local',
           'threshold_mean', 'threshold_minimum', 'threshold_multiotsu',
           'threshold_niblack', 'threshold_otsu', 'threshold_percentile',
           'threshold_sauvola', 'threshold_triangle', 'threshold_yen',
           'thresholding', 'tophat', 'try_all_threshold', 'wiener',
           'windowed_histogram']