WIP: fixing reduce NA bug

3 files changed, 60 insertions, 11 deletions

diff --git a/doc/release/2.0.0-notes.rst b/doc/release/2.0.0-notes.rst
index 683f24eac..f36889d62 100644
--- a/doc/release/2.0.0-notes.rst
+++ b/doc/release/2.0.0-notes.rst
@@ -22,7 +22,8 @@ What works with NA:
     * All element-wise ufuncs.
     * UFunc.reduce methods, with a new skipna parameter.
     * Array methods:
-       + ndarray.clip,
+       + ndarray.clip
+       + ndarray.conjugate,
 
 What doesn't work with NA:
     * Fancy indexing, such as with lists and partial boolean masks.
@@ -30,7 +31,7 @@ What doesn't work with NA:
       that doesn't have an identity.
     * UFunc.accumulate, UFunc.reduceat.
     * np.logical_and, np.logical_or, np.all, and np.any don't satisfy the
-      rules NA | True == True, and NA & False == False yet.
+      rules NA | True == True and NA & False == False yet.
     * Array methods:
        + ndarray.argmax, ndarray.argmin,
 
diff --git a/numpy/core/src/multiarray/na_mask.c b/numpy/core/src/multiarray/na_mask.c
index e1644590f..bfc79a4eb 100644
--- a/numpy/core/src/multiarray/na_mask.c
+++ b/numpy/core/src/multiarray/na_mask.c
@@ -510,6 +510,21 @@ PyArray_ReduceMaskNAArray(int ndim, npy_intp *shape,
         return NPY_FAIL;
     }
 
+{
+    int i;
+    printf("Dump of raw iter:\n");
+    printf("ndim: %d\n", ndim);
+    printf("shape: ");
+    for (i = 0; i < ndim; ++i) printf("%d ", (int)shape[i]);
+    printf("\n");
+    printf("src_strides: ");
+    for (i = 0; i < ndim; ++i) printf("%d ", (int)src_strides_it[i]);
+    printf("\n");
+    printf("dst_strides: ");
+    for (i = 0; i < ndim; ++i) printf("%d ", (int)dst_strides_it[i]);
+    printf("\n");
+}
+
     /* Special case a reduction in the inner loop */
     if (dst_strides_it[0] == 0) {
         /* Special case a contiguous reduction in the inner loop */
@@ -543,10 +558,13 @@ PyArray_ReduceMaskNAArray(int ndim, npy_intp *shape,
         NPY_RAW_ITER_START(idim, ndim, coord, shape_it) {
             char *src_d = src_data, *dst_d = dst_data;
             for (i = 0; i < shape_it[0]; ++i) {
+printf("s%d/d%d>>", (int)*src_d, (int)*dst_d);
                 *dst_d &= *src_d;
+printf("d%d ", (int)*dst_d);
                 src_d += src_strides_it[0];
                 dst_d += dst_strides_it[0];
             }
+printf("\n");
         } NPY_RAW_ITER_TWO_NEXT(idim, ndim, coord, shape_it,
                                     src_data, src_strides_it,
                                     dst_data, dst_strides_it);
diff --git a/numpy/core/tests/test_maskna.py b/numpy/core/tests/test_maskna.py
index 1a5561c3b..879647a63 100644
--- a/numpy/core/tests/test_maskna.py
+++ b/numpy/core/tests/test_maskna.py
@@ -719,22 +719,52 @@ def check_ufunc_max_1D(max_func):
     a[...] = np.NA
     assert_raises(ValueError, max_func, a, skipna=True)
 
-def test_array_maskna_methods():
+def test_array_maskna_clip_method():
+    # ndarray.clip
     a = np.array([2, np.NA, 10, 4, np.NA, 7], maskna=True)
 
-    # ndarray.clip
     b = np.clip(a, 3, None)
-    print repr(b)
     assert_equal(np.isna(b), [0,1,0,0,1,0])
     assert_equal(b[~np.isna(b)], [3, 10, 4, 7])
 
-    b = np.clip(a, None, 6)
-    assert_equal(np.isna(b), [0,1,0,0,1,0])
-    assert_equal(b[~np.isna(b)], [2, 6, 4, 6])
+    res = np.clip(a, None, 6)
+    assert_equal(np.isna(res), [0,1,0,0,1,0])
+    assert_equal(res[~np.isna(res)], [2, 6, 4, 6])
 
-    b = np.clip(a, 4, 7)
-    assert_equal(np.isna(b), [0,1,0,0,1,0])
-    assert_equal(b[~np.isna(b)], [4, 7, 4, 7])
+    res = np.clip(a, 4, 7)
+    assert_equal(np.isna(res), [0,1,0,0,1,0])
+    assert_equal(res[~np.isna(res)], [4, 7, 4, 7])
+
+def test_array_maskna_max_min_methods():
+    # ndarray.max, ndarray.min
+    a = np.array([[2, np.NA, 10],
+                  [4, 8, 7],
+                  [12, 4, np.NA]], maskna=True)
+
+    res = a.max(axis=0)
+    print repr(res)
+    assert_equal(np.isna(res), [0,1,1])
+    assert_equal(res[~np.isna(res)], [12])
+
+    res = a.max(axis=-1)
+    assert_equal(np.isna(res), [1,0,1])
+    assert_equal(res[~np.isna(res)], [8])
+
+    res = a.min(axis=0)
+    assert_equal(np.isna(res), [0,1,1])
+    assert_equal(res[~np.isna(res)], [2])
+
+    res = a.min(axis=-1)
+    assert_equal(np.isna(res), [1,0,1])
+    assert_equal(res[~np.isna(res)], [4])
+
+def test_array_maskna_conjugate_method():
+    # ndarray.conjugate
+    a = np.array([1j, 2+4j, np.NA, 2-1.5j, np.NA], maskna=True)
+
+    b = a.conjugate()
+    assert_equal(np.isna(b), [0,0,1,0,1])
+    assert_equal(b[~np.isna(b)], [-1j, 2-4j, 2+1.5j])
 
 if __name__ == "__main__":
     run_module_suite()