rasterio.dtypes module

Mapping of GDAL to Numpy data types.

Since 0.13 we are not importing numpy here and data types are strings. Happily strings can be used throughout Numpy and so existing code will not break.

rasterio.dtypes.can_cast_dtype(values, dtype)

Test if values can be cast to dtype without loss of information.

Parameters:

• values (list-like) –

• dtype (numpy dtype or string) –

Returns:

True if values can be cast to data type.

Return type:

boolean

rasterio.dtypes.check_dtype(dt)

Check if dtype is a known dtype.

rasterio.dtypes.get_minimum_dtype(values)

Determine minimum type to represent values.

Uses range checking to determine the minimum integer or floating point data type required to represent values.

Parameters:

values (list-like) –

Return type:

rasterio dtype string

rasterio.dtypes.in_dtype_range(value, dtype)

Test if the value is within the dtype’s range of values, Nan, or Inf.

rasterio.dtypes.is_ndarray(array)

Check if array is a ndarray.

rasterio.dtypes.validate_dtype(values, valid_dtypes)

Test if dtype of values is one of valid_dtypes.

Parameters:

• values (list-like) –

• valid_dtypes (list-like) – list of valid dtype strings, e.g., (‘int16’, ‘int32’)

Returns:

True if dtype of values is one of valid_dtypes

Return type:

boolean