o :ήc[ @s&ddlZddlmZ  d ddZdS) N)gaussian皙??c Cstj|}t|g|}t|}ttd||d}||||ft} d|tdd| D<t|d||dd}t |dd|} t || kS) aN Generate synthetic binary image with several rounded blob-like objects. Parameters ---------- length : int, optional Linear size of output image. blob_size_fraction : float, optional Typical linear size of blob, as a fraction of ``length``, should be smaller than 1. n_dim : int, optional Number of dimensions of output image. volume_fraction : float, default 0.5 Fraction of image pixels covered by the blobs (where the output is 1). Should be in [0, 1]. seed : {None, int, `numpy.random.Generator`}, optional If `seed` is None the `numpy.random.Generator` singleton is used. If `seed` is an int, a new ``Generator`` instance is used, seeded with `seed`. If `seed` is already a ``Generator`` instance then that instance is used. Returns ------- blobs : ndarray of bools Output binary image Examples -------- >>> from skimage import data >>> data.binary_blobs(length=5, blob_size_fraction=0.2) # doctest: +SKIP array([[ True, False, True, True, True], [ True, True, True, False, True], [False, True, False, True, True], [ True, False, False, True, True], [ True, False, False, False, True]]) >>> blobs = data.binary_blobs(length=256, blob_size_fraction=0.1) >>> # Finer structures >>> blobs = data.binary_blobs(length=256, blob_size_fraction=0.05) >>> # Blobs cover a smaller volume fraction of the image >>> blobs = data.binary_blobs(length=256, volume_fraction=0.3) g?css|]}|VqdS)N).0indicesrrA/tmp/pip-target-vg8gfxp4/lib/python/skimage/data/_binary_blobs.py ;szbinary_blobs..g?F)sigmapreserve_ranged) nprandom default_rngtuplezerosmaxintastyper percentile logical_not) lengthblob_size_fractionn_dimvolume_fractionseedrsshapemaskn_ptspoints thresholdrrr binary_blobss 0 r%)rrrrN)numpyr_shared.filtersrr%rrrr s