def test_preprocess_add_array():
def pre(arr):
return np.stack((arr, arr / 10))
size = (64, 64)
sdg = SpatialDataGenerator()
sdg.source = 'data/small.tif'
sdg.indexes = 1
sdg.width, sdg.height = size
df = sdg.regular_grid(*size)
sdg.add_preprocess_callback('pre', pre)
arr = next(sdg.flow_from_dataframe(df))
assert len(arr.shape) == 4
assert arr.shape[0] == min(sdg.batch_size, len(df))
assert arr.shape[1] == 2
assert arr.shape[-2] == size[0] and arr.shape[-1] == size[1]
def test_preprocess_modify_array():
def pre(arr, maxval):
return arr / maxval
size = (64, 64)
sdg = SpatialDataGenerator()
sdg.source = 'data/small.tif'
sdg.indexes = 1
sdg.width, sdg.height = size
df = sdg.regular_grid(*size)
df['max'] = [a.max() for a in sdg.flow_from_dataframe(df, batch_size=1)]
sdg.add_preprocess_callback('normalize', pre, df['max'].max())
arr = next(sdg.flow_from_dataframe(df))
assert len(arr.shape) == 3
assert arr.shape[0] == min(sdg.batch_size, len(df))
assert arr.shape[-2] == size[0] and arr.shape[-1] == size[1]
assert arr.max() <= 1.0
