From acfec3e9af5d351df88a7d71786f11a12f7545d3 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Zolt=C3=A1n=20V=C3=B6r=C3=B6s?= <zvoros@gmail.com>
Date: Sat, 10 Feb 2024 20:46:34 +0100
Subject: [PATCH] fix reshape (#660)

---
 code/ndarray.c                | 18 +++++-------------
 code/ulab.c                   |  2 +-
 tests/2d/numpy/reshape.py     | 17 +++++++++++++++++
 tests/2d/numpy/reshape.py.exp | 35 +++++++++++++++++++++++++++++++++++
 4 files changed, 58 insertions(+), 14 deletions(-)
 create mode 100644 tests/2d/numpy/reshape.py
 create mode 100644 tests/2d/numpy/reshape.py.exp

diff --git a/code/ndarray.c b/code/ndarray.c
index ffd3d621..84ce8495 100644
--- a/code/ndarray.c
+++ b/code/ndarray.c
@@ -558,13 +558,9 @@ ndarray_obj_t *ndarray_new_dense_ndarray(uint8_t ndim, size_t *shape, uint8_t dt
 ndarray_obj_t *ndarray_new_ndarray_from_tuple(mp_obj_tuple_t *_shape, uint8_t dtype) {
     // creates a dense array from a tuple
     // the function should work in the general n-dimensional case
-    size_t *shape = m_new(size_t, ULAB_MAX_DIMS);
-    for(size_t i = 0; i < ULAB_MAX_DIMS; i++) {
-        if(i >= _shape->len) {
-            shape[ULAB_MAX_DIMS - 1 - i] = 0;
-        } else {
-            shape[ULAB_MAX_DIMS - 1 - i] = mp_obj_get_int(_shape->items[i]);
-        }
+    size_t *shape = m_new0(size_t, ULAB_MAX_DIMS);
+    for(size_t i = 0; i < _shape->len; i++) {
+        shape[ULAB_MAX_DIMS - 1 - i] = mp_obj_get_int(_shape->items[_shape->len - 1 - i]);
     }
     return ndarray_new_dense_ndarray(_shape->len, shape, dtype);
 }
@@ -2021,7 +2017,7 @@ mp_obj_t ndarray_reshape_core(mp_obj_t oin, mp_obj_t _shape, bool inplace) {
         mp_obj_t *items = m_new(mp_obj_t, 1);
         items[0] = _shape;
         shape = mp_obj_new_tuple(1, items);
-    } else {
+    } else { // at this point it's certain that _shape is a tuple
         shape = MP_OBJ_TO_PTR(_shape);
     }
 
@@ -2072,11 +2068,7 @@ mp_obj_t ndarray_reshape_core(mp_obj_t oin, mp_obj_t _shape, bool inplace) {
         if(inplace) {
             mp_raise_ValueError(MP_ERROR_TEXT("cannot assign new shape"));
         }
-        if(mp_obj_is_type(_shape, &mp_type_tuple)) {
-            ndarray = ndarray_new_ndarray_from_tuple(shape, source->dtype);
-        } else {
-            ndarray = ndarray_new_linear_array(source->len, source->dtype);
-        }
+        ndarray = ndarray_new_dense_ndarray(shape->len, new_shape, source->dtype);
         ndarray_copy_array(source, ndarray, 0);
     }
     return MP_OBJ_FROM_PTR(ndarray);
diff --git a/code/ulab.c b/code/ulab.c
index f55768bc..df73f7bb 100644
--- a/code/ulab.c
+++ b/code/ulab.c
@@ -33,7 +33,7 @@
 #include "user/user.h"
 #include "utils/utils.h"
 
-#define ULAB_VERSION 6.5.0
+#define ULAB_VERSION 6.5.1
 #define xstr(s) str(s)
 #define str(s) #s
 
diff --git a/tests/2d/numpy/reshape.py b/tests/2d/numpy/reshape.py
new file mode 100644
index 00000000..7f4add6a
--- /dev/null
+++ b/tests/2d/numpy/reshape.py
@@ -0,0 +1,17 @@
+try:
+    from ulab import numpy as np
+except ImportError:
+    import numpy as np
+
+dtypes = (np.uint8, np.int8, np.uint16, np.int16, np.float)
+
+for dtype in dtypes:
+    print()
+    print('=' * 50)
+    a = np.array(range(12), dtype=dtype).reshape((3, 4))
+    print(a)
+    b = a[0,:]
+    print(b.reshape((1,4)))
+    b = a[:,0]
+    print(b.reshape((1,3)))
+
diff --git a/tests/2d/numpy/reshape.py.exp b/tests/2d/numpy/reshape.py.exp
new file mode 100644
index 00000000..806a26c3
--- /dev/null
+++ b/tests/2d/numpy/reshape.py.exp
@@ -0,0 +1,35 @@
+
+==================================================
+array([[0, 1, 2, 3],
+       [4, 5, 6, 7],
+       [8, 9, 10, 11]], dtype=uint8)
+array([[0, 1, 2, 3]], dtype=uint8)
+array([[0, 4, 8]], dtype=uint8)
+
+==================================================
+array([[0, 1, 2, 3],
+       [4, 5, 6, 7],
+       [8, 9, 10, 11]], dtype=int8)
+array([[0, 1, 2, 3]], dtype=int8)
+array([[0, 4, 8]], dtype=int8)
+
+==================================================
+array([[0, 1, 2, 3],
+       [4, 5, 6, 7],
+       [8, 9, 10, 11]], dtype=uint16)
+array([[0, 1, 2, 3]], dtype=uint16)
+array([[0, 4, 8]], dtype=uint16)
+
+==================================================
+array([[0, 1, 2, 3],
+       [4, 5, 6, 7],
+       [8, 9, 10, 11]], dtype=int16)
+array([[0, 1, 2, 3]], dtype=int16)
+array([[0, 4, 8]], dtype=int16)
+
+==================================================
+array([[0.0, 1.0, 2.0, 3.0],
+       [4.0, 5.0, 6.0, 7.0],
+       [8.0, 9.0, 10.0, 11.0]], dtype=float64)
+array([[0.0, 1.0, 2.0, 3.0]], dtype=float64)
+array([[0.0, 4.0, 8.0]], dtype=float64)