Fix encoding/decoding of F-ordered numpy arrays

Closes #63

mcbackend/__init__.py

@@ -20,4 +20,4 @@
     pass
 
 
-__version__ = "0.2.3"
+__version__ = "0.2.4"

mcbackend/npproto/utils.py

@@ -18,6 +18,7 @@ def ndarray_from_numpy(arr: numpy.ndarray) -> Ndarray:
         dtype=dt,
         data=bytes(arr.data),
         strides=list(arr.strides),
+        order="CF"[arr.flags.f_contiguous],
     )
 
 
@@ -38,4 +39,12 @@ def ndarray_to_numpy(nda: Ndarray) -> numpy.ndarray:
             dtype=numpy.dtype(nda.dtype),
             strides=nda.strides,
         )
+    # The code that reads the bytes(arr.data) always results in C-ordered data.
+    # Passing `to the `np.ndarray(order=...)` call has no effect.
+    # This is where below workaround comes into play:
+    # It reshapes arrays that were originally in Fortran order.
+    # F-ordered arrays that were encoded with mcbackend < 0.2.4 default
+    # to `nda.order == ""` and there is nothing we can do for these.
+    if nda.order == "F":
+        arr = arr.T.reshape(arr.shape)
     return arr

mcbackend/test_npproto.py

@@ -31,3 +31,15 @@ def test_conversion(self, arr: numpy.ndarray):
         result = utils.ndarray_to_numpy(dec)
         numpy.testing.assert_array_equal(result, arr)
         pass
+
+    @pytest.mark.parametrize("shape", [(5,), (2, 3), (2, 3, 5), (5, 2, 1, 7)])
+    @pytest.mark.parametrize("order", "CF")
+    def test_byteorders(self, shape, order):
+        arr = numpy.arange(numpy.prod(shape)).reshape(shape, order=order)
+
+        nda = utils.ndarray_from_numpy(arr)
+        assert nda.order == "CF"[arr.flags.f_contiguous]
+
+        dec = utils.ndarray_to_numpy(nda)
+        numpy.testing.assert_array_equal(arr, dec)
+        pass

protobufs/npproto/ndarray.proto

@@ -9,4 +9,5 @@ message ndarray {
     string dtype = 2;
     repeated int64 shape = 3;
     repeated int64 strides = 4;
+    string order = 5;
 }