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-rw-r--r--numpy/core/src/multiarray/iterators.c4
-rw-r--r--numpy/core/src/multiarray/mapping.c150
-rw-r--r--numpy/core/src/multiarray/na_singleton.c34
-rw-r--r--numpy/core/src/multiarray/na_singleton.h8
-rw-r--r--numpy/core/src/multiarray/shape.c3
-rw-r--r--numpy/core/tests/test_maskna.py85
6 files changed, 255 insertions, 29 deletions
diff --git a/numpy/core/src/multiarray/iterators.c b/numpy/core/src/multiarray/iterators.c
index f59cdb7d1..45fc40366 100644
--- a/numpy/core/src/multiarray/iterators.c
+++ b/numpy/core/src/multiarray/iterators.c
@@ -105,6 +105,8 @@ parse_index(PyArrayObject *self, PyObject *op,
PyObject *op1 = NULL;
int is_slice;
+ printf("parsing index...\n");
+
if (PySlice_Check(op) || op == Py_Ellipsis || op == Py_None) {
n = 1;
op1 = op;
@@ -173,6 +175,7 @@ parse_index(PyArrayObject *self, PyObject *op,
}
}
else {
+ printf("index %d %d %d\n", (int)start, (int)n_steps, (int)step_size);
if (nd_old >= PyArray_NDIM(self)) {
PyErr_SetString(PyExc_IndexError, "too many indices");
return -1;
@@ -209,6 +212,7 @@ parse_index(PyArrayObject *self, PyObject *op,
}
*out_offset = offset;
if (out_maskna_offset != NULL) {
+ printf ("maskna offset %d\n", (int)maskna_offset);
*out_maskna_offset = maskna_offset;
}
return nd_new;
diff --git a/numpy/core/src/multiarray/mapping.c b/numpy/core/src/multiarray/mapping.c
index 0477b633e..4608c2604 100644
--- a/numpy/core/src/multiarray/mapping.c
+++ b/numpy/core/src/multiarray/mapping.c
@@ -89,8 +89,8 @@ array_big_item(PyArrayObject *self, npy_intp i)
fa->maskna_data = PyArray_MASKNA_DATA(self) +
i * PyArray_MASKNA_STRIDES(self)[0];
if (fa->nd > 0) {
- memcpy(fa->maskna_strides, &(PyArray_MASKNA_STRIDES(self)[1]),
- (fa->nd - 1) * sizeof(npy_intp));
+ memcpy(fa->maskna_strides, PyArray_MASKNA_STRIDES(self)+1,
+ fa->nd * sizeof(npy_intp));
}
fa->flags |= NPY_ARRAY_MASKNA;
}
@@ -1392,12 +1392,7 @@ array_ass_sub_simple(PyArrayObject *self, PyObject *index, PyObject *op)
tmp = (PyArrayObject *)tmp0;
}
- if (PyArray_ISOBJECT(self) && (PyArray_NDIM(tmp) == 0)) {
- ret = PyArray_DESCR(tmp)->f->setitem(op, PyArray_DATA(tmp), tmp);
- }
- else {
- ret = PyArray_CopyObject(tmp, op);
- }
+ ret = PyArray_CopyObject(tmp, op);
Py_DECREF(tmp);
return ret;
}
@@ -1521,7 +1516,7 @@ array_ass_sub(PyArrayObject *self, PyObject *index, PyObject *op)
(PyArray_DIMS((PyArrayObject *)index)==0) &&
PyArray_ISBOOL((PyArrayObject *)index))) {
if (PyObject_IsTrue(index)) {
- return PyArray_DESCR(self)->f->setitem(op, PyArray_DATA(self), self);
+ return PyArray_CopyObject(self, op);
}
else { /* don't do anything */
return 0;
@@ -1532,25 +1527,66 @@ array_ass_sub(PyArrayObject *self, PyObject *index, PyObject *op)
}
/* Integer-tuple */
- if (PyTuple_Check(index) && (PyTuple_GET_SIZE(index) == PyArray_NDIM(self))
- && (_tuple_of_integers(index, vals, PyArray_NDIM(self)) >= 0)) {
- int i;
- char *item;
-
- for (i = 0; i < PyArray_NDIM(self); i++) {
- if (vals[i] < 0) {
- vals[i] += PyArray_DIMS(self)[i];
+ if (PyTuple_Check(index) &&
+ (PyTuple_GET_SIZE(index) == PyArray_NDIM(self)) &&
+ (_tuple_of_integers(index, vals, PyArray_NDIM(self)) >= 0)) {
+ int idim, ndim = PyArray_NDIM(self);
+ npy_intp *shape = PyArray_DIMS(self);
+ npy_intp *strides = PyArray_STRIDES(self);
+ char *item = PyArray_DATA(self);
+
+ if (!PyArray_HASMASKNA(self)) {
+ for (idim = 0; idim < ndim; idim++) {
+ npy_intp v = vals[idim];
+ if (v < 0) {
+ v += shape[idim];
+ }
+ if (v < 0 || v >= shape[idim]) {
+ PyErr_Format(PyExc_IndexError,
+ "index (%"INTP_FMT") out of range "\
+ "(0<=index<%"INTP_FMT") in dimension %d",
+ vals[idim], PyArray_DIMS(self)[idim], idim);
+ return -1;
+ }
+ else {
+ item += v * strides[idim];
+ }
}
- if ((vals[i] < 0) || (vals[i] >= PyArray_DIMS(self)[i])) {
- PyErr_Format(PyExc_IndexError,
- "index (%"INTP_FMT") out of range "\
- "(0<=index<%"INTP_FMT") in dimension %d",
- vals[i], PyArray_DIMS(self)[i], i);
- return -1;
+ return PyArray_DESCR(self)->f->setitem(op, item, self);
+ }
+ else {
+ char *maskna_item = PyArray_MASKNA_DATA(self);
+ npy_intp *maskna_strides = PyArray_MASKNA_STRIDES(self);
+ NpyNA *na;
+
+ for (idim = 0; idim < ndim; idim++) {
+ npy_intp v = vals[idim];
+ if (v < 0) {
+ v += shape[idim];
+ }
+ if (v < 0 || v >= shape[idim]) {
+ PyErr_Format(PyExc_IndexError,
+ "index (%"INTP_FMT") out of range "\
+ "(0<=index<%"INTP_FMT") in dimension %d",
+ vals[idim], PyArray_DIMS(self)[idim], idim);
+ return -1;
+ }
+ else {
+ item += v * strides[idim];
+ maskna_item += v * maskna_strides[idim];
+ }
+ }
+ na = NpyNA_FromObject(op, 1);
+ if (na == NULL) {
+ *maskna_item = 1;
+ return PyArray_DESCR(self)->f->setitem(op, item, self);
+ }
+ else {
+ *maskna_item = NpyNA_AsMaskValue(na);
+ Py_DECREF(na);
+ return 0;
}
}
- item = PyArray_GetPtr(self, vals);
- return PyArray_DESCR(self)->f->setitem(op, item, self);
}
PyErr_Clear();
@@ -1634,9 +1670,66 @@ array_subscript_nice(PyArrayObject *self, PyObject *op)
}
}
/* optimization for a tuple of integers */
- if (PyArray_NDIM(self) > 1 && PyTuple_Check(op) &&
- (PyTuple_GET_SIZE(op) == PyArray_NDIM(self))
- && (_tuple_of_integers(op, vals, PyArray_NDIM(self)) >= 0)) {
+ if (PyArray_NDIM(self) > 1 &&
+ PyTuple_Check(op) &&
+ (PyTuple_GET_SIZE(op) == PyArray_NDIM(self)) &&
+ (_tuple_of_integers(op, vals, PyArray_NDIM(self)) >= 0)) {
+ int idim, ndim = PyArray_NDIM(self);
+ npy_intp *shape = PyArray_DIMS(self);
+ npy_intp *strides = PyArray_STRIDES(self);
+ char *item = PyArray_DATA(self);
+
+ if (!PyArray_HASMASKNA(self)) {
+ for (idim = 0; idim < ndim; idim++) {
+ npy_intp v = vals[idim];
+ if (v < 0) {
+ v += shape[idim];
+ }
+ if (v < 0 || v >= shape[idim]) {
+ PyErr_Format(PyExc_IndexError,
+ "index (%"INTP_FMT") out of range "\
+ "(0<=index<%"INTP_FMT") in dimension %d",
+ vals[idim], PyArray_DIMS(self)[idim], idim);
+ return NULL;
+ }
+ else {
+ item += v * strides[idim];
+ }
+ }
+ return PyArray_Scalar(item, PyArray_DESCR(self), (PyObject *)self);
+ }
+ else {
+ char *maskna_item = PyArray_MASKNA_DATA(self);
+ npy_intp *maskna_strides = PyArray_MASKNA_STRIDES(self);
+
+ for (idim = 0; idim < ndim; idim++) {
+ npy_intp v = vals[idim];
+ if (v < 0) {
+ v += shape[idim];
+ }
+ if (v < 0 || v >= shape[idim]) {
+ PyErr_Format(PyExc_IndexError,
+ "index (%"INTP_FMT") out of range "\
+ "(0<=index<%"INTP_FMT") in dimension %d",
+ vals[idim], PyArray_DIMS(self)[idim], idim);
+ return NULL;
+ }
+ else {
+ item += v * strides[idim];
+ maskna_item += v * maskna_strides[idim];
+ }
+ }
+ if (NpyMaskValue_IsExposed((npy_mask)*maskna_item)) {
+ return PyArray_Scalar(item, PyArray_DESCR(self),
+ (PyObject *)self);
+ }
+ else {
+ return (PyObject *)NpyNA_FromDTypeAndMaskValue(
+ PyArray_DESCR(self), (npy_mask)*maskna_item);
+ }
+ }
+
+#if 0
int i;
char *item;
@@ -1654,6 +1747,7 @@ array_subscript_nice(PyArrayObject *self, PyObject *op)
}
item = PyArray_GetPtr(self, vals);
return PyArray_Scalar(item, PyArray_DESCR(self), (PyObject *)self);
+#endif
}
PyErr_Clear();
diff --git a/numpy/core/src/multiarray/na_singleton.c b/numpy/core/src/multiarray/na_singleton.c
index f3cb1ac16..dd59b5c69 100644
--- a/numpy/core/src/multiarray/na_singleton.c
+++ b/numpy/core/src/multiarray/na_singleton.c
@@ -434,6 +434,40 @@ NpyNA_FromObject(PyObject *obj, int suppress_error)
}
/*
+ * Converts a dtype reference and mask value into an NA.
+ * Doesn't steal the 'dtype' reference. Raises an error
+ * if 'maskvalue' represents an exposed mask.
+ */
+NPY_NO_EXPORT NpyNA *
+NpyNA_FromDTypeAndMaskValue(PyArray_Descr *dtype, npy_mask maskvalue)
+{
+ NpyNA_fields *fna;
+
+ if (dtype == NULL && maskvalue == 0) {
+ Py_INCREF(Npy_NA);
+ return (NpyNA *)Npy_NA;
+ }
+
+ if (NpyMaskValue_IsExposed(maskvalue)) {
+ PyErr_SetString(PyExc_ValueError,
+ "Cannot convert exposed mask value into NA");
+ return NULL;
+ }
+
+ fna = (NpyNA_fields *)na_new(&NpyNA_Type, NULL, NULL);
+ if (fna == NULL) {
+ return NULL;
+ }
+
+ fna->dtype = dtype;
+ Py_XINCREF(fna->dtype);
+
+ fna->payload = NpyMaskValue_GetPayload(maskvalue);
+
+ return (NpyNA *)fna;
+}
+
+/*
* Returns a mask value corresponding to the NA.
*/
NPY_NO_EXPORT npy_mask
diff --git a/numpy/core/src/multiarray/na_singleton.h b/numpy/core/src/multiarray/na_singleton.h
index b911c2364..069c457b6 100644
--- a/numpy/core/src/multiarray/na_singleton.h
+++ b/numpy/core/src/multiarray/na_singleton.h
@@ -49,6 +49,14 @@ NPY_NO_EXPORT NpyNA *
NpyNA_FromObject(PyObject *obj, int suppress_error);
/*
+ * Converts a dtype reference and mask value into an NA.
+ * Doesn't steal the 'dtype' reference. Raises an error
+ * if 'maskvalue' represents an exposed mask.
+ */
+NPY_NO_EXPORT NpyNA *
+NpyNA_FromDTypeAndMaskValue(PyArray_Descr *dtype, npy_mask maskvalue);
+
+/*
* Returns a mask value corresponding to the NA.
*/
NPY_NO_EXPORT npy_mask
diff --git a/numpy/core/src/multiarray/shape.c b/numpy/core/src/multiarray/shape.c
index 56c08304c..f9c079208 100644
--- a/numpy/core/src/multiarray/shape.c
+++ b/numpy/core/src/multiarray/shape.c
@@ -346,11 +346,12 @@ PyArray_Newshape(PyArrayObject *self, PyArray_Dims *newdims,
printf("building fortran strides\n"); fflush(stdout);
for (i = 0; i < ndim; ++i) {
fa->maskna_strides[i] = stride;
- printf("stride %d\n", stride);
+ printf("stride %d\n", (int)stride);
stride *= fa->dimensions[i];
}
}
else {
+ printf("building C strides\n"); fflush(stdout);
for (i = ndim; i >= 0; --i) {
fa->maskna_strides[i] = stride;
stride *= fa->dimensions[i];
diff --git a/numpy/core/tests/test_maskna.py b/numpy/core/tests/test_maskna.py
index dbd435c8c..d1d79c86a 100644
--- a/numpy/core/tests/test_maskna.py
+++ b/numpy/core/tests/test_maskna.py
@@ -120,6 +120,47 @@ def test_array_maskna_isna_1D():
# TODO: fancy indexing is next...
+def test_array_maskna_isna_2D():
+ a = np.zeros((3,4))
+
+ # With no mask, it returns all False
+ assert_equal(np.isna(a), False)
+ assert_equal(np.isna(a).shape, (3,4))
+
+ # With a mask but no NAs, it still returns all False
+ a.flags.maskna = True
+ assert_equal(np.isna(a), False)
+ assert_equal(np.isna(a).shape, (3,4))
+
+ # Checking isna of a single value
+ assert_equal(np.isna(a[1,2]), False)
+ # Assigning NA to a single value
+ a[1,2] = np.NA
+ assert_equal(np.isna(a), [[0,0,0,0],[0,0,1,0],[0,0,0,0]])
+ # Checking isna of a single value
+ assert_equal(np.isna(a[1,2]), True)
+
+ # Checking isna of a slice
+ assert_equal(np.isna(a[1:4,1:3]), [[0,1],[0,0]])
+ # Assigning NA to a slice
+ a[1:3,0:2] = np.NA
+ assert_equal(np.isna(a), [[0,0,0,0],[1,1,1,0],[1,1,0,0]])
+
+ # Checking isna of a strided slice
+ assert_equal(np.isna(a[1:,1:5:2]), [[1,0],[1,0]])
+ # Assigning NA to a strided slice
+ a[::2,::2] = np.NA
+ assert_equal(np.isna(a), [[1,0,1,0],[1,1,1,0],[1,1,1,0]])
+
+ # Checking isna of a boolean mask index
+ mask = np.array([[1,1,0,0],[0,1,0,1],[0,0,1,0]], dtype='?')
+ assert_equal(np.isna(a[mask]), [1,0,1,0,1])
+ # Assigning NA to a boolean masked index
+ a[mask] = np.NA
+ assert_equal(np.isna(a), [[1,1,1,0],[1,1,1,1],[1,1,1,0]])
+
+ # TODO: fancy indexing is next...
+
def test_array_maskna_view_function():
a = np.arange(10)
@@ -282,6 +323,50 @@ def test_array_maskna_view_NA_assignment_1D():
# TODO: fancy indexing is next...
+def test_array_maskna_view_NA_assignment_2D():
+ a = np.arange(6).reshape(2,3)
+ a_ref = a.copy()
+
+ # Make sure that assigning NA doesn't affect the original data
+ b = a.view(maskna=True)
+ b[...] = np.NA
+ assert_equal(np.isna(b), True)
+ assert_equal(a, a_ref)
+
+ b = a.view(maskna=True)
+ b[:] = np.NA
+ assert_equal(np.isna(b), True)
+ assert_equal(a, a_ref)
+
+ b = a.view(maskna=True)
+ b[0,:] = np.NA
+ assert_equal(np.isna(b[0]), True)
+ assert_equal(np.isna(b[1]), False)
+ assert_equal(a, a_ref)
+
+ b = a.view(maskna=True)
+ b[1:,1:3] = np.NA
+ assert_equal(np.isna(b), [[0,0,0],[0,1,1]])
+ assert_equal(a, a_ref)
+
+ b = a.view(maskna=True)
+ b[1,::2] = np.NA
+ assert_equal(np.isna(b), [[0,0,0],[1,0,1]])
+ assert_equal(a, a_ref)
+
+ b = a.view(maskna=True)
+ b[0,2] = np.NA
+ assert_equal(np.isna(b), [[0,0,1],[0,0,0]])
+ assert_equal(a, a_ref)
+
+ b = a.view(maskna=True)
+ mask = np.array([[1,0,1],[1,1,0]], dtype='?')
+ b[mask] = np.NA
+ assert_equal(np.isna(b), mask)
+ assert_equal(a, a_ref)
+
+ # TODO: fancy indexing is next...
+
def test_array_maskna_view_array_assignment_1D():
a = np.arange(5)
b = a.view(maskna=True)
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