fix vectorize (#568)

Author: v923z

code/numpy/vector.c

@@ -759,12 +759,51 @@ static mp_obj_t vector_vectorized_function_call(mp_obj_t self_in, size_t n_args,
     if(mp_obj_is_type(args[0], &ulab_ndarray_type)) {
         ndarray_obj_t *source = MP_OBJ_TO_PTR(args[0]);
         COMPLEX_DTYPE_NOT_IMPLEMENTED(source->dtype)
+
         ndarray_obj_t *ndarray = ndarray_new_dense_ndarray(source->ndim, source->shape, self->otypes);
-        for(size_t i=0; i < source->len; i++) {
-            avalue[0] = mp_binary_get_val_array(source->dtype, source->array, i);
-            fvalue = MP_OBJ_TYPE_GET_SLOT(self->type, call)(self->fun, 1, 0, avalue);
-            ndarray_set_value(self->otypes, ndarray->array, i, fvalue);
-        }
+        uint8_t *sarray = (uint8_t *)source->array;
+        uint8_t *narray = (uint8_t *)ndarray->array;
+        
+        #if ULAB_MAX_DIMS > 3
+        size_t i = 0;
+        do {
+        #endif
+            #if ULAB_MAX_DIMS > 2
+            size_t j = 0;
+            do {
+            #endif
+                #if ULAB_MAX_DIMS > 1
+                size_t k = 0;
+                do {
+                #endif
+                    size_t l = 0;
+                    do {
+                        avalue[0] = mp_binary_get_val_array(source->dtype, sarray, 0);
+                        fvalue = MP_OBJ_TYPE_GET_SLOT(self->type, call)(self->fun, 1, 0, avalue);
+                        ndarray_set_value(self->otypes, narray, 0, fvalue);
+                        sarray += source->strides[ULAB_MAX_DIMS - 1];
+                        narray += ndarray->itemsize;
+                        l++;
+                    } while(l < source->shape[ULAB_MAX_DIMS - 1]);
+                #if ULAB_MAX_DIMS > 1
+                    sarray -= source->strides[ULAB_MAX_DIMS - 1] * source->shape[ULAB_MAX_DIMS - 1];
+                    sarray += source->strides[ULAB_MAX_DIMS - 2];
+                    k++;
+                } while(k < source->shape[ULAB_MAX_DIMS - 2]);
+                #endif /* ULAB_MAX_DIMS > 1 */
+            #if ULAB_MAX_DIMS > 2
+                sarray -= source->strides[ULAB_MAX_DIMS - 2] * source->shape[ULAB_MAX_DIMS - 2];
+                sarray += source->strides[ULAB_MAX_DIMS - 3];
+                j++;
+            } while(j < source->shape[ULAB_MAX_DIMS - 3]);
+            #endif /* ULAB_MAX_DIMS > 2 */
+        #if ULAB_MAX_DIMS > 3
+            sarray -= source->strides[ULAB_MAX_DIMS - 3] * source->shape[ULAB_MAX_DIMS - 3];
+            sarray += source->strides[ULAB_MAX_DIMS - 4];
+            i++;
+        } while(i < source->shape[ULAB_MAX_DIMS - 4]);
+        #endif /* ULAB_MAX_DIMS > 3 */
+        
         return MP_OBJ_FROM_PTR(ndarray);
     } else if(mp_obj_is_type(args[0], &mp_type_tuple) || mp_obj_is_type(args[0], &mp_type_list) ||
         mp_obj_is_type(args[0], &mp_type_range)) { // i.e., the input is a generic iterable

code/ulab.c

@@ -33,7 +33,7 @@
 #include "user/user.h"
 #include "utils/utils.h"
 
-#define ULAB_VERSION 6.0.1
+#define ULAB_VERSION 6.0.2
 #define xstr(s) str(s)
 #define str(s) #s
 

docs/ulab-change-log.md

@@ -1,3 +1,9 @@
+Tue, 3 Jan 2023
+
+version 6.0.2
+
+    fix vectorize
+
 Sat, 5 Nov 2022
 
 version 6.0.1

tests/2d/numpy/vectorize.py

@@ -0,0 +1,18 @@
+try:
+    from ulab import numpy as np
+except:
+    import numpy as np
+
+
+dtypes = (np.uint8, np.int8, np.uint16, np.int16, np.float)
+
+square = np.vectorize(lambda n: n*n)
+
+for dtype in dtypes:
+    a = np.array(range(9), dtype=dtype).reshape((3, 3))
+    print(a)
+    print(square(a))
+    
+    b = a[:,2]
+    print(square(b))
+    print()

tests/2d/numpy/vectorize.py.exp

@@ -0,0 +1,40 @@
+array([[0, 1, 2],
+       [3, 4, 5],
+       [6, 7, 8]], dtype=uint8)
+array([[0.0, 1.0, 4.0],
+       [9.0, 16.0, 25.0],
+       [36.0, 49.0, 64.0]], dtype=float64)
+array([4.0, 25.0, 64.0], dtype=float64)
+
+array([[0, 1, 2],
+       [3, 4, 5],
+       [6, 7, 8]], dtype=int8)
+array([[0.0, 1.0, 4.0],
+       [9.0, 16.0, 25.0],
+       [36.0, 49.0, 64.0]], dtype=float64)
+array([4.0, 25.0, 64.0], dtype=float64)
+
+array([[0, 1, 2],
+       [3, 4, 5],
+       [6, 7, 8]], dtype=uint16)
+array([[0.0, 1.0, 4.0],
+       [9.0, 16.0, 25.0],
+       [36.0, 49.0, 64.0]], dtype=float64)
+array([4.0, 25.0, 64.0], dtype=float64)
+
+array([[0, 1, 2],
+       [3, 4, 5],
+       [6, 7, 8]], dtype=int16)
+array([[0.0, 1.0, 4.0],
+       [9.0, 16.0, 25.0],
+       [36.0, 49.0, 64.0]], dtype=float64)
+array([4.0, 25.0, 64.0], dtype=float64)
+
+array([[0.0, 1.0, 2.0],
+       [3.0, 4.0, 5.0],
+       [6.0, 7.0, 8.0]], dtype=float64)
+array([[0.0, 1.0, 4.0],
+       [9.0, 16.0, 25.0],
+       [36.0, 49.0, 64.0]], dtype=float64)
+array([4.0, 25.0, 64.0], dtype=float64)
+