def test_mask_bits(self):
t = Tile(42 * np.ones((4, 4), 'uint16'), CellType.uint16())
# with a varitey of known values
mask = Tile(
np.array([[1, 1, 2720, 2720], [1, 6816, 6816, 2756],
[2720, 2720, 6900, 2720], [2720, 6900, 6816, 1]]),
CellType('uint16raw'))
df = self.spark.createDataFrame([Row(t=t, mask=mask)])
# removes fill value 1
mask_fill_df = df.select(
rf_mask_by_bit('t', 'mask', 0, True).alias('mbb'))
mask_fill_tile = mask_fill_df.first()['mbb']
self.assertTrue(mask_fill_tile.cell_type.has_no_data())
self.assertTrue(
mask_fill_df.select(rf_data_cells('mbb')).first()[0], 16 - 4)
# mask out 6816, 6900
mask_med_hi_cir = df.withColumn('mask_cir_mh',
rf_mask_by_bits('t', 'mask', 11, 2, [2, 3])) \
.first()['mask_cir_mh'].cells
self.assertEqual(mask_med_hi_cir.mask.sum(), 5)
def test_mask_and_deser(self):
# duplicates much of test_mask_bits but
t = Tile(42 * np.ones((4, 4), 'uint16'), CellType.uint16())
# with a varitey of known values
mask = Tile(
np.array([[1, 1, 2720, 2720], [1, 6816, 6816, 2756],
[2720, 2720, 6900, 2720], [2720, 6900, 6816, 1]]),
CellType('uint16raw'))
df = self.spark.createDataFrame([Row(t=t, mask=mask)])
# removes fill value 1
mask_fill_df = df.select(
rf_mask_by_bit('t', 'mask', 0, True).alias('mbb'))
mask_fill_tile = mask_fill_df.first()['mbb']
self.assertTrue(mask_fill_tile.cell_type.has_no_data())
# Unsure why this fails. mask_fill_tile.cells is all 42 unmasked.
self.assertEqual(
mask_fill_tile.cells.mask.sum(), 4,
f'Expected {16 - 4} data values but got the masked tile:'
f'{mask_fill_tile}')
