diff --git a/tools_numpy.ipynb b/tools_numpy.ipynb
index 7b5c22e..3aaa689 100644
--- a/tools_numpy.ipynb
+++ b/tools_numpy.ipynb
@@ -36,7 +36,7 @@
   },
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+   "execution_count": 1,
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@@ -59,7 +59,7 @@
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@@ -75,7 +75,7 @@
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+   "execution_count": 3,
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@@ -100,7 +100,7 @@
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+   "execution_count": 4,
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@@ -110,7 +110,7 @@
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+   "execution_count": 5,
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@@ -119,7 +119,7 @@
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+   "execution_count": 6,
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@@ -128,7 +128,7 @@
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+   "execution_count": 7,
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@@ -145,7 +145,7 @@
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-   "execution_count": 9,
+   "execution_count": 8,
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@@ -162,7 +162,7 @@
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-   "execution_count": 10,
+   "execution_count": 9,
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@@ -181,7 +181,7 @@
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+   "execution_count": 10,
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@@ -198,7 +198,7 @@
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-   "execution_count": 12,
+   "execution_count": 11,
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    "source": [
@@ -215,7 +215,7 @@
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   {
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-   "execution_count": 13,
+   "execution_count": 12,
    "metadata": {
     "scrolled": true
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@@ -234,7 +234,7 @@
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   {
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-   "execution_count": 14,
+   "execution_count": 13,
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@@ -251,7 +251,7 @@
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-   "execution_count": 15,
+   "execution_count": 14,
    "metadata": {
     "scrolled": true
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@@ -269,7 +269,7 @@
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+   "execution_count": 15,
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@@ -285,7 +285,7 @@
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-   "execution_count": 17,
+   "execution_count": 16,
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@@ -301,7 +301,7 @@
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-   "execution_count": 18,
+   "execution_count": 17,
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    "source": [
@@ -320,7 +320,7 @@
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   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 18,
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    "source": [
@@ -338,7 +338,7 @@
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-   "execution_count": 20,
+   "execution_count": 19,
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@@ -354,7 +354,7 @@
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+   "execution_count": 20,
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@@ -370,7 +370,7 @@
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   {
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-   "execution_count": 22,
+   "execution_count": 21,
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@@ -404,12 +404,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
     "def my_function(z, y, x):\n",
-    "    return x * y + z\n",
+    "    return x + 10 * y + 100 * z\n",
     "\n",
     "np.fromfunction(my_function, (3, 2, 10))"
    ]
@@ -418,7 +418,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "NumPy first creates three `ndarrays` (one per dimension), each of shape `(2, 10)`. Each array has values equal to the coordinate along a specific axis. For example, all elements in the `z` array are equal to their z-coordinate:\n",
+    "NumPy first creates three `ndarrays` (one per dimension), each of shape `(3, 2, 10)`. Each array has values equal to the coordinate along a specific axis. For example, all elements in the `z` array are equal to their z-coordinate:\n",
     "\n",
     "    [[[ 0.  0.  0.  0.  0.  0.  0.  0.  0.  0.]\n",
     "      [ 0.  0.  0.  0.  0.  0.  0.  0.  0.  0.]]\n",
@@ -429,7 +429,7 @@
     "     [[ 2.  2.  2.  2.  2.  2.  2.  2.  2.  2.]\n",
     "      [ 2.  2.  2.  2.  2.  2.  2.  2.  2.  2.]]]\n",
     "\n",
-    "So the terms x, y and z in the expression `x * y + z` above are in fact `ndarray`s (we will discuss arithmetic operations on arrays below).  The point is that the function `my_function` is only called *once*, instead of once per element. This makes initialization very efficient."
+    "So the terms `x`, `y` and `z` in the expression `x + 10 * y + 100 * z` above are in fact `ndarray`s (we will discuss arithmetic operations on arrays below).  The point is that the function `my_function` is only called *once*, instead of once per element. This makes initialization very efficient."
    ]
   },
   {