[skip ci] docs build of 7982119

Author: ci-doc-deploy-bot

_sources/content/mooreslaw-tutorial.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "60285612",
+   "id": "28579ae5",
    "metadata": {},
    "source": [
     "# Pairing Jupyter notebooks and MyST-NB\n",
@@ -76,7 +76,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "5fcc520d",
+   "id": "1407bc69",
    "metadata": {},
    "outputs": [
     {
@@ -94,7 +94,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0b4e68b7",
+   "id": "6771f87c",
    "metadata": {},
    "source": [
     "---\n",

_sources/content/pairing.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "fdc112c4",
+   "id": "9673d6bc",
    "metadata": {},
    "source": [
     "# Saving and sharing your NumPy arrays\n",
@@ -37,7 +37,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "c7ae53d5",
+   "id": "0e2a9177",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -46,7 +46,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "09dd946b",
+   "id": "c01382b6",
    "metadata": {},
    "source": [
     "In this tutorial, you will use the following Python, IPython magic, and NumPy functions:\n",
@@ -64,7 +64,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "61f3df28",
+   "id": "167ae9f7",
    "metadata": {},
    "source": [
     "---\n",
@@ -81,7 +81,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "c81eab4e",
+   "id": "cd8af1a9",
    "metadata": {},
    "outputs": [
     {
@@ -102,7 +102,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5f976311",
+   "id": "cccee03f",
    "metadata": {},
    "source": [
     "## Save your arrays with NumPy's [`savez`](https://numpy.org/doc/stable/reference/generated/numpy.savez.html?highlight=savez#numpy.savez)\n",
@@ -125,7 +125,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "c381abff",
+   "id": "4781a152",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -134,7 +134,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f9af5f9f",
+   "id": "2e8cb897",
    "metadata": {},
    "source": [
     "## Remove the saved arrays and load them back with NumPy's [`load`](https://numpy.org/doc/stable/reference/generated/numpy.load.html#numpy.load)\n",
@@ -159,7 +159,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "15c8f6a2",
+   "id": "2b41e261",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -169,7 +169,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "a046f647",
+   "id": "c7eb0914",
    "metadata": {},
    "outputs": [
     {
@@ -189,7 +189,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "de0069c2",
+   "id": "72ffe604",
    "metadata": {},
    "outputs": [
     {
@@ -209,7 +209,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "ab5816bc",
+   "id": "9b428875",
    "metadata": {},
    "outputs": [
     {
@@ -218,7 +218,7 @@
      "text": [
       "Variable   Type       Data/Info\n",
       "-------------------------------\n",
-      "load_xy    NpzFile    <numpy.lib.npyio.NpzFile <...>object at 0x7f9a9c87a070>\n",
+      "load_xy    NpzFile    <numpy.lib.npyio.NpzFile <...>object at 0x7f052bd01490>\n",
       "np         module     <module 'numpy' from '/ho<...>kages/numpy/__init__.py'>\n"
      ]
     }
@@ -229,7 +229,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "65da5074",
+   "id": "af7a2a4a",
    "metadata": {},
    "source": [
     "## Reassign the NpzFile arrays to `x` and `y`\n",
@@ -242,7 +242,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "14b49891",
+   "id": "f6894538",
    "metadata": {},
    "outputs": [
     {
@@ -263,7 +263,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1edd2089",
+   "id": "6a0470ef",
    "metadata": {},
    "source": [
     "## Success\n",
@@ -294,7 +294,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "65bfb76d",
+   "id": "4b03cbda",
    "metadata": {},
    "outputs": [
     {
@@ -323,7 +323,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c774045e",
+   "id": "0c7b011b",
    "metadata": {},
    "source": [
     "## Save the data to csv file using [`savetxt`](https://numpy.org/doc/stable/reference/generated/numpy.savetxt.html#numpy.savetxt)\n",
@@ -338,7 +338,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "4a695de3",
+   "id": "ab0b89e6",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -347,7 +347,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d4f418fa",
+   "id": "4212942d",
    "metadata": {},
    "source": [
     "Open the file, `x_y-squared.csv`, and you'll see the following:\n",
@@ -387,7 +387,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "676df1d2",
+   "id": "1a23e6ae",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -397,7 +397,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "aa15938d",
+   "id": "7a182136",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -409,7 +409,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "4d0ffe7c",
+   "id": "73b7abe9",
    "metadata": {},
    "outputs": [
     {
@@ -430,7 +430,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "87d9972b",
+   "id": "2175abc5",
    "metadata": {},
    "outputs": [
     {
@@ -451,7 +451,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2471f546",
+   "id": "cd780ec0",
    "metadata": {},
    "source": [
     "## Success, but remember your types\n",
@@ -462,7 +462,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "08e4f9d8",
+   "id": "989b2303",
    "metadata": {},
    "source": [
     "## Wrapping up\n",