ix keepdims for min, max, argmin, argmax (#707)

v923z · Jan 26, 2025 · 20f7259 · 20f7259
1 parent be15d62
commit 20f7259
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diff --git a/code/numpy/numerical.c b/code/numpy/numerical.c
@@ -546,10 +546,6 @@ static mp_obj_t numerical_argmin_argmax_ndarray(ndarray_obj_t *ndarray, mp_obj_t
         }
 
         m_del(int32_t, strides, ULAB_MAX_DIMS);
-
-        if(results->len == 1) {
-            return mp_binary_get_val_array(results->dtype, results->array, 0);
-        }
         return ulab_tools_restore_dims(ndarray, results, keepdims, _shape_strides);
     }
     // we should never get to this point

diff --git a/code/ulab.c b/code/ulab.c
@@ -33,7 +33,7 @@
 #include "user/user.h"
 #include "utils/utils.h"
 
-#define ULAB_VERSION 6.7.2
+#define ULAB_VERSION 6.7.3
 #define xstr(s) str(s)
 #define str(s) #s
 

diff --git a/docs/manual/source/conf.py b/docs/manual/source/conf.py
@@ -27,7 +27,7 @@
 author = 'Zoltán Vörös'
 
 # The full version, including alpha/beta/rc tags
-release = '6.7.2'
+release = '6.7.3'
 
 
 # -- General configuration ---------------------------------------------------

diff --git a/docs/ulab-change-log.md b/docs/ulab-change-log.md
@@ -1,3 +1,9 @@
+Sun, 26 Jan 2025
+
+version 6.7.3
+
+    fix keepdims for min, max, argmin, argmax
+
 Sun, 19 Jan 2025
 
 version 6.7.2

diff --git a/docs/ulab-convert.ipynb b/docs/ulab-convert.ipynb
@@ -61,7 +61,7 @@
     "author = 'Zoltán Vörös'\n",
     "\n",
     "# The full version, including alpha/beta/rc tags\n",
-    "release = '6.7.2'\n",
+    "release = '6.7.3'\n",
     "\n",
     "\n",
     "# -- General configuration ---------------------------------------------------\n",
@@ -217,7 +217,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 2,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-09T06:27:21.647179Z",
@@ -258,7 +258,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 3,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-02-09T06:27:42.024028Z",

diff --git a/docs/ulab-numerical.ipynb b/docs/ulab-numerical.ipynb
@@ -50,7 +50,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 3,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2022-01-07T19:16:37.453883Z",
@@ -245,115 +245,11 @@
     "\n",
     "**WARNING:** Difference to `numpy`: the `out` keyword argument is not implemented.\n",
     "\n",
-    "These functions follow the same pattern, and work with generic iterables, and `ndarray`s. `min`, and `max` return the minimum or maximum of a sequence. If the input array is two-dimensional, the `axis` keyword argument can be supplied, in which case the minimum/maximum along the given axis will be returned. If `axis=None` (this is also the default value), the minimum/maximum of the flattened array will be determined.\n",
+    "These functions follow the same pattern, and work with generic iterables, and `ndarray`s. `min`, and `max` return the minimum or maximum of a sequence. If the input array is two-dimensional, the `axis` keyword argument can be supplied, in which case the minimum/maximum along the given axis will be returned. If `axis=None` (this is also the default value), the minimum/maximum of the flattened array will be determined. The functions also accept the `keepdims=True` or `keepdims=False` keyword argument. The latter case is the default, while the former keeps the dimensions (the number of axes) of the supplied array. \n",
     "\n",
     "`argmin/argmax` return the position (index) of the minimum/maximum in the sequence."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2020-10-17T21:26:22.507996Z",
-     "start_time": "2020-10-17T21:26:22.492543Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "array([1.0, 2.0, 3.0], dtype=float64)\n",
-      "array([], dtype=float64)\n",
-      "[] 0\n",
-      "array([1.0, 2.0, 3.0], dtype=float64)\n",
-      "array([], dtype=float64)\n",
-      "\n",
-      "\n"
-     ]
-    }
-   ],
-   "source": [
-    "%%micropython -unix 1\n",
-    "\n",
-    "from ulab import numpy as np\n",
-    "\n",
-    "a = np.array([1, 2, 3])\n",
-    "print(a)\n",
-    "print(a[-1:-1:-3])\n",
-    "try:\n",
-    "    sa = list(a[-1:-1:-3])\n",
-    "    la = len(sa)\n",
-    "except IndexError as e:\n",
-    "    sa = str(e)\n",
-    "    la = -1\n",
-    "    \n",
-    "print(sa, la)\n",
-    "\n",
-    "a[-1:-1:-3] = np.ones(0)\n",
-    "print(a)\n",
-    "\n",
-    "b = np.ones(0) + 1\n",
-    "print(b)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2020-10-17T21:54:49.123748Z",
-     "start_time": "2020-10-17T21:54:49.093819Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "array([], dtype=float64)\n",
-      "\n",
-      "\n"
-     ]
-    }
-   ],
-   "source": [
-    "%%micropython -unix 1\n",
-    "\n",
-    "from ulab import numpy as np\n",
-    "\n",
-    "a = np.array([1, 2, 3])\n",
-    "print(a[0:1:-3])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 81,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2020-10-17T20:59:58.285134Z",
-     "start_time": "2020-10-17T20:59:58.263605Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(0,)"
-      ]
-     },
-     "execution_count": 81,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a = np.array([1, 2, 3])\n",
-    "np.ones(0, dtype=uint8) / np.zeros(0, dtype=uint16)\n",
-    "np.ones(0).shape"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 10,
@@ -400,6 +296,43 @@
     "print('min of b (axis=1):', np.min(b, axis=1))"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "a: array([[0.0, 1.0, 2.0, 3.0],\n",
+      "       [4.0, 5.0, 6.0, 7.0],\n",
+      "       [8.0, 9.0, 10.0, 11.0]], dtype=float64)\n",
+      "\n",
+      "min of a (axis=1):\n",
+      " array([[0.0],\n",
+      "       [4.0],\n",
+      "       [8.0]], dtype=float64)\n",
+      "\n",
+      "min of a (axis=0):\n",
+      " array([[0.0, 1.0, 2.0, 3.0]], dtype=float64)\n",
+      "\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%micropython -unix 1\n",
+    "\n",
+    "from ulab import numpy as np\n",
+    "\n",
+    "a = np.array(range(12)).reshape((3, 4))\n",
+    "\n",
+    "print('a:', a)\n",
+    "print('\\nmin of a (axis=1):\\n', np.min(a, axis=1, keepdims=True))\n",
+    "print('\\nmin of a (axis=0):\\n', np.min(a, axis=0, keepdims=True))"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},