[skip ci] docs build of 73ebebf

Author: ci-doc-deploy-bot

_sources/content/mooreslaw-tutorial.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "146cf52c",
+   "id": "72bc0890",
    "metadata": {},
    "source": [
     "# Pairing Jupyter notebooks and MyST-NB\n",
@@ -76,7 +76,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "75d41b08",
+   "id": "9682b56e",
    "metadata": {},
    "outputs": [
     {
@@ -94,7 +94,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "907bd079",
+   "id": "6ea339e8",
    "metadata": {},
    "source": [
     "---\n",

_sources/content/pairing.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "4091a3e6",
+   "id": "d7504fc5",
    "metadata": {},
    "source": [
     "# Saving and sharing your NumPy arrays\n",
@@ -37,7 +37,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "31841c8b",
+   "id": "bff95ad0",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -46,7 +46,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b15d4f09",
+   "id": "33057ab0",
    "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": "6f9bf914",
+   "id": "43472c11",
    "metadata": {},
    "source": [
     "---\n",
@@ -81,7 +81,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "b134082a",
+   "id": "a7da6711",
    "metadata": {},
    "outputs": [
     {
@@ -102,7 +102,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "428cec11",
+   "id": "d927bf64",
    "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": "b2308739",
+   "id": "e7b39454",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -134,7 +134,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d53d493f",
+   "id": "1847a5ff",
    "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": "44d24b57",
+   "id": "4de54641",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -169,7 +169,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "0a742c01",
+   "id": "766660b9",
    "metadata": {},
    "outputs": [
     {
@@ -189,7 +189,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "eddeea4c",
+   "id": "6f4b4f1b",
    "metadata": {},
    "outputs": [
     {
@@ -209,7 +209,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "35388419",
+   "id": "ebeebaa4",
    "metadata": {},
    "outputs": [
     {
@@ -218,7 +218,7 @@
      "text": [
       "Variable   Type       Data/Info\n",
       "-------------------------------\n",
-      "load_xy    NpzFile    <numpy.lib.npyio.NpzFile <...>object at 0x7f3a04e3f460>\n",
+      "load_xy    NpzFile    <numpy.lib.npyio.NpzFile <...>object at 0x7f6f0238a440>\n",
       "np         module     <module 'numpy' from '/ho<...>kages/numpy/__init__.py'>\n"
      ]
     }
@@ -229,7 +229,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "913cd63c",
+   "id": "b915a41f",
    "metadata": {},
    "source": [
     "## Reassign the NpzFile arrays to `x` and `y`\n",
@@ -242,7 +242,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "c8444c32",
+   "id": "a59a45c5",
    "metadata": {},
    "outputs": [
     {
@@ -263,7 +263,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4cf001eb",
+   "id": "866f2ebf",
    "metadata": {},
    "source": [
     "## Success\n",
@@ -294,7 +294,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "bfc26be1",
+   "id": "3c5cb4ee",
    "metadata": {},
    "outputs": [
     {
@@ -323,7 +323,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "99a90ab3",
+   "id": "e5da95fd",
    "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": "e2e52532",
+   "id": "51c47d21",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -347,7 +347,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9dacfd23",
+   "id": "010f4d30",
    "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": "e7c2443b",
+   "id": "34c5dd61",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -397,7 +397,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "43b798a2",
+   "id": "366fbd4a",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -407,7 +407,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "218acac1",
+   "id": "0da8b239",
    "metadata": {},
    "outputs": [
     {
@@ -428,7 +428,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "0b139917",
+   "id": "b2378de4",
    "metadata": {},
    "outputs": [
     {
@@ -449,7 +449,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "13a756e3",
+   "id": "5fd284d2",
    "metadata": {},
    "source": [
     "## Success, but remember your types\n",
@@ -460,7 +460,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2678af0b",
+   "id": "6b53b023",
    "metadata": {},
    "source": [
     "## Wrapping up\n",