[skip ci] docs build of 89b0464

Author: ci-doc-deploy-bot

_sources/content/mooreslaw-tutorial.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "480c1f5b",
+   "id": "120adfd0",
    "metadata": {},
    "source": [
     "# Pairing Jupyter notebooks and MyST-NB\n",
@@ -76,7 +76,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "7db84729",
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    "metadata": {},
    "outputs": [
     {
@@ -94,7 +94,7 @@
   },
   {
    "cell_type": "markdown",
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+   "id": "099c887d",
    "metadata": {},
    "source": [
     "---\n",
@@ -286,7 +286,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.10.13"
   },
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    13,

_sources/content/pairing.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "90b77a04",
+   "id": "163b5a5f",
    "metadata": {},
    "source": [
     "# Saving and sharing your NumPy arrays\n",
@@ -37,7 +37,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "762ddaea",
+   "id": "e849a8f2",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -46,7 +46,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "34dd5581",
+   "id": "11cd18b7",
    "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": "e1da5249",
+   "id": "0d18085f",
    "metadata": {},
    "source": [
     "---\n",
@@ -81,7 +81,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "422ce751",
+   "id": "ccb9fce5",
    "metadata": {},
    "outputs": [
     {
@@ -102,7 +102,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "45db8770",
+   "id": "c60998b1",
    "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": "2abaf9de",
+   "id": "d6f4e89c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -134,7 +134,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3f7afe5a",
+   "id": "b29e24ae",
    "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": "abe5ab08",
+   "id": "de181ebb",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -169,7 +169,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "d26d2402",
+   "id": "98469ffe",
    "metadata": {},
    "outputs": [
     {
@@ -189,7 +189,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "be5fb2ee",
+   "id": "80a5bdec",
    "metadata": {},
    "outputs": [
     {
@@ -209,7 +209,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "6f1a5f77",
+   "id": "169d1671",
    "metadata": {},
    "outputs": [
     {
@@ -229,7 +229,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fbe68f87",
+   "id": "9b1683e5",
    "metadata": {},
    "source": [
     "## Reassign the NpzFile arrays to `x` and `y`\n",
@@ -242,7 +242,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "befd7ed1",
+   "id": "9afabe94",
    "metadata": {},
    "outputs": [
     {
@@ -263,7 +263,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2d39f49f",
+   "id": "33a6a2d7",
    "metadata": {},
    "source": [
     "## Success\n",
@@ -294,7 +294,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "6795690d",
+   "id": "3bd7312c",
    "metadata": {},
    "outputs": [
     {
@@ -323,7 +323,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a55ea3d2",
+   "id": "f7198db8",
    "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": "feb5553a",
+   "id": "571876da",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -347,7 +347,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a7f15da0",
+   "id": "14c1cd4e",
    "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": "87abe590",
+   "id": "48fdde24",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -397,7 +397,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "6d2fa410",
+   "id": "f1143eee",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -407,7 +407,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "2aa00056",
+   "id": "76353206",
    "metadata": {},
    "outputs": [
     {
@@ -428,7 +428,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "11eb708f",
+   "id": "ddd3623e",
    "metadata": {},
    "outputs": [
     {
@@ -449,7 +449,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "671aae8a",
+   "id": "65a731af",
    "metadata": {},
    "source": [
     "## Success, but remember your types\n",
@@ -460,7 +460,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "47c8b1aa",
+   "id": "2e3251a8",
    "metadata": {},
    "source": [
     "## Wrapping up\n",
@@ -495,7 +495,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.10.13"
   },
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    12,