BUG: Store numeric and character archives transposed for MATLAB compa…

…tibility. (#39)

scripts/make_test_data.py

@@ -6,7 +6,7 @@
 from sdafile import SDAFile
 
 
-EXAMPLE_A1 = np.zeros(5, dtype=np.float64)
+EXAMPLE_A1 = np.zeros((5, 1), dtype=np.float64)
 
 EXAMPLE_A2 = np.empty((4, 3), dtype=np.complex128)
 EXAMPLE_A2.real = 0
@@ -16,6 +16,10 @@
 
 EXAMPLE_A4 = np.nan
 
+EXAMPLE_B = True
+
+EXAMPLE_C = 'Here is some text'
+
 
 def make_example_data(filename):
 
@@ -27,12 +31,11 @@ def make_example_data(filename):
 
     sda_file.insert("example A3", EXAMPLE_A3, "5x5 sparse matrix")
 
-    sda_file.insert("example A4", np.nan, "Empty array")
+    sda_file.insert("example A4", EXAMPLE_A4, "Empty array")
 
-    sda_file.insert("example B", True, "Logical scalar")
+    sda_file.insert("example B", EXAMPLE_B, "Logical scalar")
 
-    data = np.array(list('Here is some text'), 'S1').reshape(-1, 1)
-    sda_file.insert("example C", data, "Some text")
+    sda_file.insert("example C", EXAMPLE_C, "Some text")
 
     desc = "Cell array combining examples A1 and A2"
     sda_file.insert("example E", [EXAMPLE_A1, EXAMPLE_A2], desc)

sdafile/extract.py

@@ -85,6 +85,8 @@ def extract_character(data):
         'S1' dtype.
 
     """
+    # Matlab stores the transpose of 2D arrays. This must be unapplied here.
+    data = data.T
     if data.ndim == 2 and data.shape[0] == 1:
         data = data.tobytes().decode('ascii')
     else:
@@ -163,7 +165,8 @@ def extract_numeric(data):
         The input data
 
     """
-    return reduce_array(data)
+    # Matlab stores the transpose of 2D arrays. This must be unapplied here.
+    return reduce_array(data.T)
 
 
 def extract_sparse(data):

sdafile/tests/test_compatibility.py

@@ -8,7 +8,7 @@
 from sdafile.testing import data_path
 
 
-EXAMPLE_A1 = np.zeros(5, dtype=np.float64)
+EXAMPLE_A1 = np.zeros((5, 1), dtype=np.float64)
 
 EXAMPLE_A2 = np.empty((4, 3), dtype=np.complex128)
 EXAMPLE_A2.real = 0
@@ -71,8 +71,8 @@ def test_example_B(self):
     def test_example_C(self):
         """ Some text """
         label = 'example C'
-        expected = np.array(list('Here is some text'), 'S1').reshape(-1, 1)
-        self.assertArray(label, expected)
+        expected = 'Here is some text'
+        self.assertScalar(label, expected)
 
     def test_example_D(self):
         """ Handle to the sine function """

sdafile/tests/test_utils.py

@@ -65,7 +65,10 @@ def test_unnest(self):
     def test_coerce_character(self):
         coerced = coerce_character(string.printable)
         self.assertEqual(coerced.dtype, np.dtype(np.uint8))
-        expected = np.array([[ord(c) for c in string.printable]], np.uint8)
+        expected = np.array(
+            [ord(c) for c in string.printable], 
+            np.uint8
+        ).reshape(-1, 1)
         assert_array_equal(coerced, expected)
 
     def test_coerce_simple(self):
@@ -119,14 +122,10 @@ def test_coerce_logical(self):
         assert_array_equal(coerced, [[1, 0, 1, 1]])
 
     def test_coerce_numeric(self):
-        for data, typ in TEST_SCALARS:
+        for data, typ in TEST_SCALARS + TEST_ARRAYS:
             if typ == 'numeric':
-                self.assertEqual(coerce_numeric(data), data)
-
-        for data, typ in TEST_ARRAYS:
-            if typ == 'numeric' and isinstance(data, np.ndarray):
                 coerced = coerce_numeric(data)
-                assert_array_equal(coerced, np.atleast_2d(data))
+                assert_array_equal(coerced, np.atleast_2d(data).T)
 
     def test_coerce_sparse(self):
         row = np.array([3, 4, 5, 6])

sdafile/utils.py

@@ -137,7 +137,9 @@ def coerce_character(data):
         data = data.view(np.uint8)
     else:
         data = np.frombuffer(data.encode('ascii'), np.uint8)
-    return np.atleast_2d(data)
+
+    # Matlab stores the transpose of 2D arrays. This must be applied here.
+    return np.atleast_2d(data).T
 
 
 def coerce_complex(data):
@@ -214,7 +216,8 @@ def coerce_numeric(data):
         The data with at least 2 dimensions
 
     """
-    return np.atleast_2d(data)
+    # Matlab stores the transpose of 2D arrays. This must be unapplied here.
+    return np.atleast_2d(data).T
 
 
 def coerce_sparse(data):