[skip ci] docs build of 59f665b

Author: ci-doc-deploy-bot

Diff for: _sources/content/mooreslaw-tutorial.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "8b7449be",
+   "id": "68da2f2d",
    "metadata": {},
    "source": [
     "# Pairing Jupyter notebooks and MyST-NB\n",
@@ -76,7 +76,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "140f25ee",
+   "id": "b0523853",
    "metadata": {},
    "outputs": [
     {
@@ -94,7 +94,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1a9e3d80",
+   "id": "b925b771",
    "metadata": {},
    "source": [
     "---\n",

Diff for: _sources/content/pairing.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "0d083776",
+   "id": "54903fb4",
    "metadata": {},
    "source": [
     "# Saving and sharing your NumPy arrays\n",
@@ -37,7 +37,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "e0ce3763",
+   "id": "f66e7ed9",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -46,7 +46,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f78dfbdf",
+   "id": "dc9a702f",
    "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": "951b51f6",
+   "id": "6ed3f2a1",
    "metadata": {},
    "source": [
     "---\n",
@@ -81,7 +81,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "e194d284",
+   "id": "65265300",
    "metadata": {},
    "outputs": [
     {
@@ -102,7 +102,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "12e10b9d",
+   "id": "cf513df5",
    "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": "d66e1bfa",
+   "id": "455a0a7c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -134,7 +134,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "592adec0",
+   "id": "e979e17c",
    "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": "87ae7ee1",
+   "id": "ddd0b442",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -169,7 +169,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "477a8c38",
+   "id": "ffd90408",
    "metadata": {},
    "outputs": [
     {
@@ -189,7 +189,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "4f170091",
+   "id": "b67d8e5a",
    "metadata": {},
    "outputs": [
     {
@@ -209,7 +209,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "81d548d7",
+   "id": "f9ae8e13",
    "metadata": {},
    "outputs": [
     {
@@ -229,7 +229,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c5da62d3",
+   "id": "e617a9a2",
    "metadata": {},
    "source": [
     "## Reassign the NpzFile arrays to `x` and `y`\n",
@@ -242,7 +242,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "35389415",
+   "id": "da780446",
    "metadata": {},
    "outputs": [
     {
@@ -263,7 +263,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e502ec45",
+   "id": "687ae480",
    "metadata": {},
    "source": [
     "## Success\n",
@@ -294,7 +294,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "86c485ad",
+   "id": "683c8102",
    "metadata": {},
    "outputs": [
     {
@@ -323,7 +323,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "963d2c7a",
+   "id": "695874f8",
    "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": "a1cbd398",
+   "id": "0866e256",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -347,7 +347,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9e483b91",
+   "id": "13db97a8",
    "metadata": {},
    "source": [
     "Open the file, `x_y-squared.csv`, and you'll see the following:"
@@ -356,7 +356,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "7291d38b",
+   "id": "0ed04f8d",
    "metadata": {},
    "outputs": [
     {
@@ -382,7 +382,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a578c491",
+   "id": "382d9e36",
    "metadata": {},
    "source": [
     "## Our arrays as a csv file\n",
@@ -406,7 +406,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "dfdf8f25",
+   "id": "4e320f2e",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -416,7 +416,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "1f49c0d7",
+   "id": "433b88ce",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -426,7 +426,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "9f6e878d",
+   "id": "b16af0dc",
    "metadata": {},
    "outputs": [
     {
@@ -447,7 +447,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "82d695db",
+   "id": "9f5ed3f8",
    "metadata": {},
    "outputs": [
     {
@@ -468,7 +468,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8a3a6517",
+   "id": "1cf82f86",
    "metadata": {},
    "source": [
     "## Success, but remember your types\n",
@@ -479,7 +479,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "172bd130",
+   "id": "22cb4b04",
    "metadata": {},
    "source": [
     "## Wrapping up\n",