def generate(path, count=5, size=(64, 64), indexes=1):
sdg = SpatialDataGenerator('data/small.tif', indexes=indexes)
sdg.source = 'data/small.tif'
df = sdg.random_grid(*size, count=count, units='pixels')
return fc.flow_to_numpy(sdg, df, *size, path=path)
def test_flow_to_numpy():
size = (64, 64)
sdg = SpatialDataGenerator('data/small.tif', indexes=1)
sdg.source = 'data/small.tif'
df = sdg.random_grid(*size, count=5, units='pixels')
with TemporaryDirectory() as td:
tmpdir = Path(td)
filenames = fc.flow_to_numpy(sdg, df, *size, path=tmpdir)
assert isinstance(filenames, pd.Series)
for fname in filenames:
filepath = tmpdir / fname
assert filepath.exists()
arr = np.load(filepath)
assert len(arr.shape) == 4
assert arr.shape[0] == 1
assert arr.shape[1] == 1
assert arr.shape[2] == size[1] and arr.shape[3] == size[0]
def test_random_grid():
dg = SpatialDataGenerator()
dg.source = 'data/small.tif'
df = dg.random_grid(64, 64, 100)
assert len(df) == 100
def test_random_grid():
dg = SpatialDataGenerator()
dg.source = 'data/small.tif'
dg.width, dg.height = 64, 64
df = dg.random_grid(100)
assert len(df) == 100
