Improve dtype conversion for C(++) code templating

src/calng/dssc_gpu.py

@@ -224,12 +224,8 @@ class DsscGpuRunner:
                 "pixels_y": self.pixels_y,
                 "data_memory_cells": self.memory_cells,
                 "constant_memory_cells": self.constant_memory_cells,
-                "input_data_dtype": utils.numpy_dtype_to_c_type_str[
-                    self.input_data_dtype
-                ],
-                "output_data_dtype": utils.numpy_dtype_to_c_type_str[
-                    self.output_data_dtype
-                ],
+                "input_data_dtype": utils.np_dtype_to_c_type(self.input_data_dtype),
+                "output_data_dtype": utils.np_dtype_to_c_type(self.output_data_dtype),
             }
         )
         self.source_module = cupy.RawModule(code=kernel_source)

src/calng/utils.py

@@ -4,22 +4,40 @@ import timeit
 
 import numpy as np
 
-numpy_dtype_to_c_type_str = {
-    np.uint16: "unsigned short",
-    np.uint32: "unsigned short",
-    np.float16: "half",  # warning: only in CUDA with special support
-    np.float32: "float",
-    np.float64: "double",
+_np_typechar_to_c_typestring = {
+    "?": "bool",
+    "B": "unsigned char",
+    "D": "double complex",
+    "F": "float complex",
+    "G": "long double complex",
+    "H": "unsigned short",
+    "I": "unsigned int",
+    "L": "unsigned long",
+    "Q": "unsigned long long",
+    "b": "char",
+    "d": "double",
+    "e": "half",  # warning: only in CUDA with special support
+    "f": "float",
+    "g": "long double",
+    "h": "short",
+    "i": "int",
+    "l": "long",
+    "q": "long long",
 }
 
 
+def np_dtype_to_c_type(dtype):
+    as_char = np.sctype2char(dtype)
+    return _np_typechar_to_c_typestring[as_char]
+
+
 def ceil_div(num, denom):
     return (num + denom - 1) // denom
 
 
 def shape_after_transpose(input_shape, transpose_pattern, squeeze=True):
     if squeeze:
-        input_shape = tuple(dim for dim in input_shape if dim>1)
+        input_shape = tuple(dim for dim in input_shape if dim > 1)
     if transpose_pattern is None:
         return input_shape
     return tuple(np.array(input_shape)[list(transpose_pattern)].tolist())

src/tests/test_utils.py

+import numpy as np
+
+from calng import utils
+
+def test_get_c_type():
+    assert utils.np_dtype_to_c_type(np.float16) == "half"
+    assert utils.np_dtype_to_c_type(np.float32) == "float"
+    assert utils.np_dtype_to_c_type(np.float64) == "double"
+
+    assert utils.np_dtype_to_c_type(np.uint8) == "unsigned char"
+    assert utils.np_dtype_to_c_type(np.uint16) == "unsigned short"
+    assert utils.np_dtype_to_c_type(np.uint32) in ("unsigned", "unsigned int")
+    assert utils.np_dtype_to_c_type(np.uint64) == "unsigned long"
+
+    assert utils.np_dtype_to_c_type(np.int8) == "char"
+    assert utils.np_dtype_to_c_type(np.int16) == "short"
+    assert utils.np_dtype_to_c_type(np.int32) == "int"
+    assert utils.np_dtype_to_c_type(np.int64) == "long"