def testOutput(self):
graph = Graph()
data = numpy.random.random( (1,100,100,10,1) )
opProvider = OpArrayPiper(graph=graph)
opProvider.Input.setValue(data)
opSubRegion = OpSubRegion( graph=graph )
opSubRegion.Input.connect( opProvider.Output )
opSubRegion.Roi.setValue( ((0,20,30,5,0), (1,30,50,8,1)) )
subData = opSubRegion.Output( start=( 0,5,10,1,0 ), stop=( 1,10,20,3,1 ) ).wait()
assert (subData == data[0:1, 25:30, 40:50, 6:8, 0:1]).all()
def testOutput_masked(self):
graph = Graph()
data = numpy.random.random( (1,100,100,10,1) )
data = numpy.ma.masked_array(data,
mask=numpy.ma.getmaskarray(data),
fill_value=data.dtype.type(numpy.nan),
shrink=False
)
data[:, 25] = numpy.ma.masked
opProvider = OpArrayPiper(graph=graph)
opProvider.Input.setValue(data)
opSubRegion = OpSubRegion( graph=graph )
opSubRegion.Input.connect( opProvider.Output )
opSubRegion.Roi.setValue( ((0,20,30,5,0), (1,30,50,8,1)) )
subData = opSubRegion.Output( start=( 0,5,10,1,0 ), stop=( 1,10,20,3,1 ) ).wait()
assert (subData == data[0:1, 25:30, 40:50, 6:8, 0:1]).all()
assert (subData.mask == data.mask[0:1, 25:30, 40:50, 6:8, 0:1]).all()
assert ((subData.fill_value == data.fill_value) |
(numpy.isnan(subData.fill_value) & numpy.isnan(data.fill_value))).all()