def createDataSource(dset, withShape=False): dset_5d = H5pyDset5DWrapper(dset) src = ArraySource(dset_5d) if withShape: return src, dset_5d.shape else: return src
def _createArrayDataSource(source,withShape = False): #has to handle NumpyArray #check if the array is 5d, if not so embed it in a canonical way if len(source.shape) == 2: source = source.reshape( (1,) + source.shape + (1,1) ) elif len(source.shape) == 3 and source.shape[2] <= 4: source = source.reshape( (1,) + source.shape[0:2] + (1,) + (source.shape[2],) ) elif len(source.shape) == 3: source = source.reshape( (1,) + source.shape + (1,) ) elif len(source.shape) == 4: source = source.reshape( (1,) + source.shape ) src = ArraySource(source) if withShape: return src,source.shape else: return src
def setUp(self): import numpy as np from datasources import ArraySource self.raw = np.random.randint(0, 100, (10, 3, 3, 128, 3)) self.a = ArraySource(self.raw) self.ss = SliceSource(self.a, projectionAlongTZC)
import dask.array from datasources import ArraySource from in_memory_catalog import Catalog # Build Catalog of Catalogs. subcatalogs = {} for name, size, fruit, animal in zip( ["tiny", "small", "medium", "large"], [3, 100, 1000, 10_000], ["apple", "banana", "orange", "grape"], ["bird", "cat", "dog", "penguin"], ): subcatalogs[name] = Catalog( { k: ArraySource(v * dask.array.ones((size, size))) for k, v in zip(["ones", "twos", "threes"], [1, 2, 3]) }, metadata={ "fruit": fruit, "animal": animal }, ) catalog = Catalog(subcatalogs)