Support passing data in numpy int8, int16, uint8 and uint16 dtypes to GMT (#1963)

Co-authored-by: Wei Ji <[email protected]>

Author: seisman

pygmt/clib/session.py

@@ -53,14 +53,18 @@
 REGISTRATIONS = ["GMT_GRID_PIXEL_REG", "GMT_GRID_NODE_REG"]
 
 DTYPES = {
-    np.float64: "GMT_DOUBLE",
-    np.float32: "GMT_FLOAT",
-    np.int64: "GMT_LONG",
+    np.int8: "GMT_CHAR",
+    np.int16: "GMT_SHORT",
     np.int32: "GMT_INT",
-    np.uint64: "GMT_ULONG",
+    np.int64: "GMT_LONG",
+    np.uint8: "GMT_UCHAR",
+    np.uint16: "GMT_USHORT",
     np.uint32: "GMT_UINT",
-    np.datetime64: "GMT_DATETIME",
+    np.uint64: "GMT_ULONG",
+    np.float32: "GMT_FLOAT",
+    np.float64: "GMT_DOUBLE",
     np.str_: "GMT_TEXT",
+    np.datetime64: "GMT_DATETIME",
 }
 
 
@@ -732,8 +736,8 @@ def put_vector(self, dataset, column, vector):
         The dataset must be created by :meth:`pygmt.clib.Session.create_data`
         first. Use ``family='GMT_IS_DATASET|GMT_VIA_VECTOR'``.
 
-        Not at all numpy dtypes are supported, only: float64, float32, int64,
-        int32, uint64, uint32, datetime64 and str\_.
+        Not all numpy dtypes are supported, only: int8, int16, int32, int64,
+        uint8, uint16, uint32, uint64, float32, float64, str\_ and datetime64.
 
         .. warning::
             The numpy array must be C contiguous in memory. If it comes from a
@@ -856,8 +860,8 @@ def put_matrix(self, dataset, matrix, pad=0):
         The dataset must be created by :meth:`pygmt.clib.Session.create_data`
         first. Use ``|GMT_VIA_MATRIX'`` in the family.
 
-        Not at all numpy dtypes are supported, only: float64, float32, int64,
-        int32, uint64, and uint32.
+        Not all numpy dtypes are supported, only: int8, int16, int32, int64,
+        uint8, uint16, uint32, uint64, float32 and float64.
 
         .. warning::
             The numpy array must be C contiguous in memory. Use

pygmt/tests/test_clib.py

@@ -36,6 +36,14 @@ def data():
     return np.loadtxt(POINTS_DATA)
 
 
+@pytest.fixture(scope="module", name="dtypes")
+def fixture_dtypes():
+    """
+    List of supported numpy dtypes.
+    """
+    return "int8 int16 int32 int64 uint8 uint16 uint32 uint64 float32 float64".split()
+
+
 @contextmanager
 def mock(session, func, returns=None, mock_func=None):
     """
@@ -339,11 +347,10 @@ def test_create_data_fails():
                 )
 
 
-def test_virtual_file():
+def test_virtual_file(dtypes):
     """
     Test passing in data via a virtual file with a Dataset.
     """
-    dtypes = "float32 float64 int32 int64 uint32 uint64".split()
     shape = (5, 3)
     for dtype in dtypes:
         with clib.Session() as lib:
@@ -497,11 +504,10 @@ def test_virtualfile_from_data_fail_non_valid_data(data):
             )
 
 
-def test_virtualfile_from_vectors():
+def test_virtualfile_from_vectors(dtypes):
     """
     Test the automation for transforming vectors to virtual file dataset.
     """
-    dtypes = "float32 float64 int32 int64 uint32 uint64".split()
     size = 10
     for dtype in dtypes:
         x = np.arange(size, dtype=dtype)
@@ -588,11 +594,10 @@ def test_virtualfile_from_vectors_diff_size():
                 print("This should have failed")
 
 
-def test_virtualfile_from_matrix():
+def test_virtualfile_from_matrix(dtypes):
     """
     Test transforming a matrix to virtual file dataset.
     """
-    dtypes = "float32 float64 int32 int64 uint32 uint64".split()
     shape = (7, 5)
     for dtype in dtypes:
         data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape)
@@ -606,11 +611,10 @@ def test_virtualfile_from_matrix():
             assert output == expected
 
 
-def test_virtualfile_from_matrix_slice():
+def test_virtualfile_from_matrix_slice(dtypes):
     """
     Test transforming a slice of a larger array to virtual file dataset.
     """
-    dtypes = "float32 float64 int32 int64 uint32 uint64".split()
     shape = (10, 6)
     for dtype in dtypes:
         full_data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape)
@@ -627,11 +631,10 @@ def test_virtualfile_from_matrix_slice():
             assert output == expected
 
 
-def test_virtualfile_from_vectors_pandas():
+def test_virtualfile_from_vectors_pandas(dtypes):
     """
     Pass vectors to a dataset using pandas Series.
     """
-    dtypes = "float32 float64 int32 int64 uint32 uint64".split()
     size = 13
     for dtype in dtypes:
         data = pd.DataFrame(

pygmt/tests/test_clib_put_matrix.py

@@ -11,11 +11,18 @@
 from pygmt.tests.test_clib import mock
 
 
-def test_put_matrix():
+@pytest.fixture(scope="module", name="dtypes")
+def fixture_dtypes():
+    """
+    List of supported numpy dtypes.
+    """
+    return "int8 int16 int32 int64 uint8 uint16 uint32 uint64 float32 float64".split()
+
+
+def test_put_matrix(dtypes):
     """
     Check that assigning a numpy 2d array to a dataset works.
     """
-    dtypes = "float32 float64 int32 int64 uint32 uint64".split()
     shape = (3, 4)
     for dtype in dtypes:
         with clib.Session() as lib:
@@ -57,11 +64,10 @@ def test_put_matrix_fails():
                 lib.put_matrix(dataset=None, matrix=np.empty((10, 2)), pad=0)
 
 
-def test_put_matrix_grid():
+def test_put_matrix_grid(dtypes):
     """
     Check that assigning a numpy 2d array to an ASCII and NetCDF grid works.
     """
-    dtypes = "float32 float64 int32 int64 uint32 uint64".split()
     wesn = [10, 15, 30, 40, 0, 0]
     inc = [1, 1]
     shape = ((wesn[3] - wesn[2]) // inc[1] + 1, (wesn[1] - wesn[0]) // inc[0] + 1)

pygmt/tests/test_clib_put_vector.py

@@ -12,11 +12,18 @@
 from pygmt.helpers import GMTTempFile
 
 
-def test_put_vector():
+@pytest.fixture(scope="module", name="dtypes")
+def fixture_dtypes():
+    """
+    List of supported numpy dtypes.
+    """
+    return "int8 int16 int32 int64 uint8 uint16 uint32 uint64 float32 float64".split()
+
+
+def test_put_vector(dtypes):
     """
     Check that assigning a numpy array to a dataset works.
     """
-    dtypes = "float32 float64 int32 int64 uint32 uint64".split()
     for dtype in dtypes:
         with clib.Session() as lib:
             dataset = lib.create_data(
@@ -50,13 +57,12 @@ def test_put_vector():
                 npt.assert_allclose(newz, z)
 
 
-def test_put_vector_mixed_dtypes():
+def test_put_vector_mixed_dtypes(dtypes):
     """
     Passing a numpy array of mixed dtypes to a dataset.
 
     See https://github.com/GenericMappingTools/pygmt/issues/255
     """
-    dtypes = "float32 float64 int32 int64 uint32 uint64".split()
     for dtypex, dtypey in itertools.permutations(dtypes, r=2):
         with clib.Session() as lib:
             dataset = lib.create_data(