def _dtype_from_value(value):
if isinstance(value, float):
return np.dtype("float32")
elif value >= 0:
return utils.get_uint_dtype(value)
else:
return utils.get_int_dtype(value)
def process(data, bins, right):
if data is None or "values" not in data:
return data
values = data["values"]
dtype = utils.get_uint_dtype(len(bins) + 2)
fillvalue = utils.get_dtype_max(dtype)
result_values = np.digitize(values, bins, right).astype(dtype)
result_values[values == data["no_data_value"]] = fillvalue
return {"values": result_values, "no_data_value": fillvalue}
def dtype(self):
# with 254 bin edges, we have 255 bins, and we need 256 possible values
# to include no_data
return utils.get_uint_dtype(len(self.bins) + 2)
def test_get_uint_dtype(self):
self.assertRaises(ValueError, utils.get_uint_dtype, -1)
for dtype in ["u1", "u2", "u4", "u8"]:
hi = np.iinfo(dtype).max
self.assertEqual(utils.get_uint_dtype(hi - 1), dtype)