Complete migration.

src/biocutils/_utils_combine.py

@@ -4,9 +4,8 @@ def _check_array_dimensions(x, active: int) -> bool:
         current = x[i].shape
         if len(first) != len(current):
             raise ValueError("inconsistent dimensions for combining arrays (expected " + str(len(first)) + ", got " + str(len(current)) + " for array " + str(i) + ")")
-
-        for j in enumerate(first):
-            if j != active and first[active] != current[active]:
+        for j in range(len(first)):
+            if j != active and first[j] != current[j]:
                 raise ValueError("inconsistent dimension extents for combining arrays on dimension " + str(active) + " (expected " + str(first[active]) + ", got " + str(current[active]) + " for array " + str(i) + ")")
 
 

src/biocutils/convert_to_dense.py

@@ -34,11 +34,11 @@ def _convert_sparse_to_dense(x):
         return x.todense()
 
     try:
-        convert_to_dense.register(sp.sparray, _convert_sparse_to_dense)
+        convert_to_dense.register(sp.spmatrix, _convert_sparse_to_dense)
     except Exception:
         pass
 
     try:
-        combine_rows.register(sp.spmatrix, _convert_sparse_to_dense)
+        convert_to_dense.register(sp.sparray, _convert_sparse_to_dense)
     except Exception:
         pass

tests/test_combine.py

@@ -23,12 +23,16 @@ def test_basic_list():
 def test_basic_mixed_dense_list():
     x = [1, 2, 3]
     y = [0.1, 0.2]
-    xd = np.array([1, 2, 3])
-
+    xd = np.array(x)
     zcomb = combine(xd, y)
 
     z = x + y
-
-    assert zcomb == z
-    assert isinstance(zcomb, list)
+    assert (zcomb == z).all()
     assert len(zcomb) == len(xd) + len(y)
+
+
+def test_basic_mixed_dense_array():
+    x = np.array([1, 2, 3, 4]).reshape((2,2))
+    y = np.array([4, 5, 6, 7]).reshape((2,2))
+    zcomb = combine(x, y)
+    assert zcomb.shape == (4, 2)

tests/test_combine_columns.py

@@ -36,6 +36,7 @@ def test_combine_columns_mixed():
     x = np.ones(shape=(num_rows, 10))
     y = sp.identity(num_rows)
 
+    print(x, y)
     z = combine_columns(x, y)
 
     assert isinstance(z, np.ndarray)

tests/test_combine_sequences.py

@@ -43,9 +43,7 @@ def test_basic_mixed_dense_list():
     zcomb = combine_sequences(xd, y)
 
     z = x + y
-
-    assert zcomb == z
-    assert isinstance(zcomb, list)
+    assert (zcomb == z).all()
     assert len(zcomb) == len(xd) + len(y)
 
 
@@ -57,34 +55,10 @@ def test_basic_mixed_tuple_list():
     zcomb = combine_sequences(xd, y, x)
 
     z = x + list(y) + x
-
-    assert zcomb == z
-    assert isinstance(zcomb, list)
+    assert (zcomb == z).all()
     assert len(zcomb) == 2 * len(xd) + len(y)
 
 
-def test_basic_sparse():
-    x = np.array([1, 2, 3])
-    y = np.array([0.1, 0.2])
-
-    sx = sp.csr_array(x)
-    sy = sp.csr_array(y)
-
-    z = combine_sequences(sx, sy)
-
-    assert isinstance(z, sp.spmatrix)
-    assert z.shape[1] == len(x) + len(y)
-
-    # mixed sparse arrays
-    sx = sp.csr_array(x)
-    sy = sp.coo_array(y)
-
-    z = combine_sequences(sx, sy)
-
-    assert isinstance(z, sp.spmatrix)
-    assert z.shape[1] == len(x) + len(y)
-
-
 def test_pandas_series():
     s1 = pd.Series(["a", "b"])
     s2 = pd.Series(["c", "d"])