Add support for int64, uint64, and int8

.github/workflows/pythonpackage.yml

@@ -13,46 +13,20 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: [3.7, 3.8, 3.9]
-        gdal: ["3.2.2", "3.3.0", "3.4.3", "3.5"]
+        python-version: [3.8, 3.9, "3.10", "3.11"]
+        gdal: ["3.2.2", "3.3.0", "3.4.3", "3.5", "3.6", "3.7"]
         os: [ubuntu-latest, windows-latest, macos-latest]
-
-        include:
-          - python-version: "3.10"
-            gdal: "3.4.3"
-            os: ubuntu-latest
-
-          - python-version: "3.10"
-            gdal: "3.4.3"
-            os: windows-latest
-
-          - python-version: "3.10"
-            gdal: "3.4.3"
-            os: macos-latest
-
-          - python-version: "3.10"
-            gdal: "3.5"
-            os: ubuntu-latest
-
-          - python-version: "3.10"
-            gdal: "3.5"
-            os: windows-latest
-
-          - python-version: "3.10"
-            gdal: "3.5"
-            os: macos-latest
-
-          - python-version: "3.11"
-            gdal: "3.5"
-            os: ubuntu-latest
-
-          - python-version: "3.11"
-            gdal: "3.5"
-            os: windows-latest
-
-          - python-version: "3.11"
-            gdal: "3.5"
-            os: macos-latest
+        exclude:
+          - gdal: "3.2.2"
+            python-version: 3.10
+          - gdal: "3.2.2"
+            python-version: 3.11
+          - gdal: "3.3.0"
+            python-version: 3.10
+          - gdal: "3.3.0"
+            python-version: 3.11
+          - gdal: "3.4.3"
+            python-version: 3.11
 
     steps:
       - uses: actions/checkout@v3

HISTORY.rst

@@ -15,6 +15,10 @@ Unreleased Changes
   from the input vector.
 * Added a new function, ``pygeoprocessing.align_bbox``, which pads a bounding
   box to align with the grid of a given geotransform.
+* Added support for int64 and uint64 (GDAL 3.5+)
+  https://github.com/natcap/pygeoprocessing/issues/352
+* Added support for signed bytes (GDAL 3.7+)
+  https://github.com/natcap/pygeoprocessing/issues/329
 
 2.4.1 (2023-09-05)
 ------------------

pyproject.toml

@@ -13,8 +13,7 @@ build-backend = "setuptools.build_meta"
 
 [tool.pytest.ini_options]
 # Raise warnings to exceptions.
-filterwarnings = 'error'
-
+filterwarnings = ["error", "default::DeprecationWarning", "default::FutureWarning"]
 
 [tool.setuptools_scm]
 version_scheme = "post-release"

src/pygeoprocessing/geoprocessing.py

@@ -26,6 +26,7 @@
 import shapely.prepared
 import shapely.wkb
 from osgeo import gdal
+from osgeo import gdal_array
 from osgeo import gdalconst
 from osgeo import ogr
 from osgeo import osr
@@ -40,19 +41,7 @@
 if sys.version_info >= (3, 8):
     import multiprocessing.shared_memory
 
-NUMPY_TO_GDAL_TYPE = {
-    numpy.dtype(bool): gdal.GDT_Byte,
-    numpy.dtype(numpy.int8): gdal.GDT_Byte,
-    numpy.dtype(numpy.uint8): gdal.GDT_Byte,
-    numpy.dtype(numpy.int16): gdal.GDT_Int16,
-    numpy.dtype(numpy.int32): gdal.GDT_Int32,
-    numpy.dtype(numpy.uint16): gdal.GDT_UInt16,
-    numpy.dtype(numpy.uint32): gdal.GDT_UInt32,
-    numpy.dtype(numpy.float32): gdal.GDT_Float32,
-    numpy.dtype(numpy.float64): gdal.GDT_Float64,
-    numpy.dtype(numpy.csingle): gdal.GDT_CFloat32,
-    numpy.dtype(numpy.complex64): gdal.GDT_CFloat64,
-}
+GDAL_VERSION = tuple(int(_) for _ in gdal.__version__.split('.'))
 
 
 class ReclassificationMissingValuesError(Exception):
@@ -86,18 +75,6 @@ def __init__(self, missing_values, raster_path, value_map):
 _LOGGING_PERIOD = 5.0  # min 5.0 seconds per update log message for the module
 _LARGEST_ITERBLOCK = 2**16  # largest block for iterblocks to read in cells
 
-_GDAL_TYPE_TO_NUMPY_LOOKUP = {
-    gdal.GDT_Byte: numpy.uint8,
-    gdal.GDT_Int16: numpy.int16,
-    gdal.GDT_Int32: numpy.int32,
-    gdal.GDT_UInt16: numpy.uint16,
-    gdal.GDT_UInt32: numpy.uint32,
-    gdal.GDT_Float32: numpy.float32,
-    gdal.GDT_Float64: numpy.float64,
-    gdal.GDT_CFloat32: numpy.csingle,
-    gdal.GDT_CFloat64: numpy.complex64,
-}
-
 _GDAL_WARP_ALGORITHMS = []
 for _warp_algo in (_attrname for _attrname in dir(gdalconst)
                    if _attrname.startswith('GRA_')):
@@ -772,8 +749,8 @@ def raster_map(op, rasters, target_path, target_nodata=None, target_dtype=None,
                 f'the target dtype {target_dtype}')
 
     driver, options = raster_driver_creation_tuple
-    if target_dtype == numpy.int8 and 'PIXELTYPE=SIGNEDBYTE' not in options:
-        options += ('PIXELTYPE=SIGNEDBYTE',)
+    gdal_type, type_creation_options = _numpy_to_gdal_type(target_dtype)
+    options = list(options) + type_creation_options
 
     def apply_op(*arrays):
         """Apply the function ``op`` to the input arrays.
@@ -802,7 +779,7 @@ def apply_op(*arrays):
         [(path, 1) for path in rasters],  # assume the first band
         apply_op,
         target_path,
-        NUMPY_TO_GDAL_TYPE[numpy.dtype(target_dtype)],
+        gdal_type,
         target_nodata,
         raster_driver_creation_tuple=(driver, options))
 
@@ -1221,19 +1198,8 @@ def new_raster_from_base(
     driver = gdal.GetDriverByName(raster_driver_creation_tuple[0])
 
     local_raster_creation_options = list(raster_driver_creation_tuple[1])
-    # PIXELTYPE is sometimes used to define signed vs. unsigned bytes and
-    # the only place that is stored is in the IMAGE_STRUCTURE metadata
-    # copy it over if it exists and it not already defined by the input
-    # creation options. It's okay to get this info from the first band since
-    # all bands have the same datatype
+    numpy_dtype = _gdal_to_numpy_type(datatype, local_raster_creation_options)
     base_band = base_raster.GetRasterBand(1)
-    metadata = base_band.GetMetadata('IMAGE_STRUCTURE')
-    if 'PIXELTYPE' in metadata and not any(
-            ['PIXELTYPE' in option for option in
-             local_raster_creation_options]):
-        local_raster_creation_options.append(
-            'PIXELTYPE=' + metadata['PIXELTYPE'])
-
     block_size = base_band.GetBlockSize()
     # It's not clear how or IF we can determine if the output should be
     # striped or tiled.  Here we leave it up to the default inputs or if its
@@ -1283,7 +1249,6 @@ def new_raster_from_base(
     timed_logger = TimedLoggingAdapter(_LOGGING_PERIOD)
     pixels_processed = 0
     n_pixels = n_cols * n_rows
-    numpy_dtype = _GDAL_TYPE_TO_NUMPY_LOOKUP[datatype]
     if fill_value_list is not None:
         for index, fill_value in enumerate(fill_value_list):
             if fill_value is None:
@@ -2167,15 +2132,9 @@ def get_raster_info(raster_path):
 
     # datatype is the same for the whole raster, but is associated with band
     band = raster.GetRasterBand(1)
-    band_datatype = band.DataType
-    raster_properties['datatype'] = band_datatype
-    raster_properties['numpy_type'] = (
-        _GDAL_TYPE_TO_NUMPY_LOOKUP[band_datatype])
-    # this part checks to see if the byte is signed or not
-    if band_datatype == gdal.GDT_Byte:
-        metadata = band.GetMetadata('IMAGE_STRUCTURE')
-        if 'PIXELTYPE' in metadata and metadata['PIXELTYPE'] == 'SIGNEDBYTE':
-            raster_properties['numpy_type'] = numpy.int8
+    raster_properties['datatype'] = band.DataType
+    raster_properties['numpy_type'] = _gdal_to_numpy_type(
+        band.DataType, band.GetMetadata('IMAGE_STRUCTURE'))
     band = None
     raster = None
     return raster_properties
@@ -2413,11 +2372,14 @@ def reclassify_raster(
     keys = sorted(numpy.array(list(value_map_copy.keys())))
     values = numpy.array([value_map_copy[x] for x in keys])
 
+    numpy_dtype = _gdal_to_numpy_type(
+        target_datatype, raster_driver_creation_tuple[1])
+
     def _map_dataset_to_value_op(original_values):
         """Convert a block of original values to the lookup values."""
         out_array = numpy.full(
             original_values.shape, target_nodata,
-            dtype=_GDAL_TYPE_TO_NUMPY_LOOKUP[target_datatype])
+            dtype=numpy_dtype)
         if nodata is None:
             valid_mask = numpy.full(original_values.shape, True)
         else:
@@ -2619,9 +2581,9 @@ def warp_raster(
     base_raster = gdal.OpenEx(base_raster_path, gdal.OF_RASTER)
 
     raster_creation_options = list(raster_driver_creation_tuple[1])
-    if (base_raster_info['numpy_type'] == numpy.int8 and
-            'PIXELTYPE' not in ' '.join(raster_creation_options)):
-        raster_creation_options.append('PIXELTYPE=SIGNEDBYTE')
+    _, type_creation_options = _numpy_to_gdal_type(
+        base_raster_info['numpy_type'])
+    raster_creation_options += type_creation_options
 
     if resample_method.lower() not in _GDAL_WARP_ALGORITHMS:
         raise ValueError(
@@ -3703,40 +3665,54 @@ def mask_op(base_array, mask_array):
     os.remove(mask_raster_path)
 
 
-def _gdal_to_numpy_type(band):
-    """Calculate the equivalent numpy datatype from a GDAL raster band type.
-
-    This function doesn't handle complex or unknown types.  If they are
-    passed in, this function will raise a ValueError.
+def _gdal_to_numpy_type(gdal_type, metadata):
+    """Calculate the equivalent numpy datatype from a GDAL type and metadata.
 
     Args:
-        band (gdal.Band): GDAL Band
+        gdal_type: GDAL.GDT_* data type code
+        metadata: mapping or list of strings to check for the existence of
+            the 'PIXELTYPE=SIGNEDBYTE' flag
 
-    Return:
-        numpy_datatype (numpy.dtype): equivalent of band.DataType
+    Returns:
+        numpy.dtype that is the equivalent of the input gdal type
 
+    Raises:
+        ValueError if an unsupported data type is entered
     """
-    # doesn't include GDT_Byte because that's a special case
-    base_gdal_type_to_numpy = {
-        gdal.GDT_Int16: numpy.int16,
-        gdal.GDT_Int32: numpy.int32,
-        gdal.GDT_UInt16: numpy.uint16,
-        gdal.GDT_UInt32: numpy.uint32,
-        gdal.GDT_Float32: numpy.float32,
-        gdal.GDT_Float64: numpy.float64,
-    }
+    if (GDAL_VERSION < (3, 7, 0) and gdal_type == gdal.GDT_Byte and
+        (('PIXELTYPE=SIGNEDBYTE' in metadata) or
+         ('PIXELTYPE' in metadata and metadata['PIXELTYPE'] == 'SIGNEDBYTE'))):
+            return numpy.int8
 
-    if band.DataType in base_gdal_type_to_numpy:
-        return base_gdal_type_to_numpy[band.DataType]
+    numpy_type = gdal_array.GDALTypeCodeToNumericTypeCode(gdal_type)
+    if numpy_type is None:
+        raise ValueError(f"Unsupported DataType: {gdal_type}")
+    return numpy_type
 
-    if band.DataType != gdal.GDT_Byte:
-        raise ValueError("Unsupported DataType: %s" % str(band.DataType))
 
-    # band must be GDT_Byte type, check if it is signed/unsigned
-    metadata = band.GetMetadata('IMAGE_STRUCTURE')
-    if 'PIXELTYPE' in metadata and metadata['PIXELTYPE'] == 'SIGNEDBYTE':
-        return numpy.int8
-    return numpy.uint8
+def _numpy_to_gdal_type(numpy_type):
+    """Calculate the equivalent GDAL type and metadata from a numpy type.
+
+    Args:
+        numpy_type: numpy data type
+
+    Returns:
+        (gdal type, metadata) tuple. gdal type is a gdal.GDT_* type code.
+        metadata is an empty list in most cases, or ['PIXELTYPE=SIGNEDBYTE']
+        if needed to indicate a signed byte type.
+
+    Raises:
+        ValueError if an unsupported data type is entered
+    """
+    numpy_dtype = numpy.dtype(numpy_type)
+
+    if GDAL_VERSION < (3, 7, 0) and numpy_dtype == numpy.dtype(numpy.int8):
+        return gdal.GDT_Byte, ['PIXELTYPE=SIGNEDBYTE']
+
+    gdal_type = gdal_array.NumericTypeCodeToGDALTypeCode(numpy_dtype)
+    if gdal_type is None:
+        raise ValueError(f"Unsupported DataType: {numpy_type}")
+    return gdal_type, []
 
 
 def merge_bounding_box_list(bounding_box_list, bounding_box_mode):
@@ -4195,12 +4171,13 @@ def numpy_array_to_raster(
     Return:
         None
     """
-
-    raster_driver = gdal.GetDriverByName(raster_driver_creation_tuple[0])
+    driver_name, creation_options = raster_driver_creation_tuple
+    raster_driver = gdal.GetDriverByName(driver_name)
     ny, nx = base_array.shape
+    gdal_type, type_creation_options = _numpy_to_gdal_type(base_array.dtype)
     new_raster = raster_driver.Create(
-        target_path, nx, ny, 1, NUMPY_TO_GDAL_TYPE[base_array.dtype],
-        options=raster_driver_creation_tuple[1])
+        target_path, nx, ny, 1, gdal_type,
+        options=list(creation_options) + type_creation_options)
     if projection_wkt is not None:
         new_raster.SetProjection(projection_wkt)
     if origin is not None and pixel_size is not None:
@@ -4420,14 +4397,16 @@ def _mult_op(base_array, base_nodata, scale, datatype):
             scaled_raster_path = os.path.join(
                 workspace_dir,
                 f'scaled_{os.path.basename(base_stitch_raster_path)}')
+            gdal_type = _gdal_to_numpy_type(
+                target_band.DataType,
+                target_band.GetMetadata('IMAGE_STRUCTURE'))
             # multiply the pixels in the resampled raster by the ratio of
             # the pixel area in the wgs84 units divided by the area of the
             # original pixel
             raster_calculator(
                 [(base_stitch_raster_path, 1), (base_stitch_nodata, 'raw'),
                  m2_area_per_lat/base_pixel_area_m2,
-                 (_GDAL_TYPE_TO_NUMPY_LOOKUP[
-                     target_raster_info['datatype']], 'raw')], _mult_op,
+                 (gdal_type, 'raw')], _mult_op,
                 scaled_raster_path,
                 target_raster_info['datatype'], base_stitch_nodata)
 

src/pygeoprocessing/geoprocessing_core.pyx

@@ -656,22 +656,20 @@ def raster_band_percentile(
         will select the next element higher than the percentile cutoff).
 
     """
-    raster_type = pygeoprocessing.get_raster_info(
-        base_raster_path_band[0])['datatype']
-    if raster_type in (
-            gdal.GDT_Byte, gdal.GDT_Int16, gdal.GDT_UInt16, gdal.GDT_Int32,
-            gdal.GDT_UInt32):
+    numpy_type = pygeoprocessing.get_raster_info(
+        base_raster_path_band[0])['numpy_type']
+    if numpy.issubdtype(numpy_type, numpy.integer):
         return _raster_band_percentile_int(
             base_raster_path_band, working_sort_directory, percentile_list,
             heap_buffer_size, ffi_buffer_size)
-    elif raster_type in (gdal.GDT_Float32, gdal.GDT_Float64):
+    elif numpy.issubdtype(numpy_type, numpy.floating):
         return _raster_band_percentile_double(
             base_raster_path_band, working_sort_directory, percentile_list,
             heap_buffer_size, ffi_buffer_size)
     else:
         raise ValueError(
             'Cannot process raster type %s (not a known integer nor float '
-            'type)', raster_type)
+            'type)', numpy_type)
 
 
 def _raster_band_percentile_int(