[skip ci] docs build of 4fa0145

Author: ci-doc-deploy-bot

_sources/content/mooreslaw-tutorial.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "e1158bfe",
+   "id": "7b62a950",
    "metadata": {},
    "source": [
     "# Pairing Jupyter notebooks and MyST-NB\n",
@@ -76,7 +76,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "8f34ecb2",
+   "id": "a00292fc",
    "metadata": {},
    "outputs": [
     {
@@ -94,7 +94,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "08cd0e3f",
+   "id": "a5ea9750",
    "metadata": {},
    "source": [
     "---\n",

_sources/content/pairing.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "3b112ade",
+   "id": "2eb63384",
    "metadata": {},
    "source": [
     "# Saving and sharing your NumPy arrays\n",
@@ -37,7 +37,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "db89ee08",
+   "id": "966e0b26",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -46,7 +46,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a4bbe924",
+   "id": "097bc268",
    "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": "f28a3e8d",
+   "id": "fcbd1c99",
    "metadata": {},
    "source": [
     "---\n",
@@ -81,7 +81,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "303c39a8",
+   "id": "62e10f27",
    "metadata": {},
    "outputs": [
     {
@@ -102,7 +102,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "58e14b4a",
+   "id": "5cd08d99",
    "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": "7a0cc835",
+   "id": "7ef2d6d8",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -134,7 +134,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b94728f1",
+   "id": "71174464",
    "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": "05ebfb55",
+   "id": "4ac2b99b",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -169,7 +169,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "19ceeedb",
+   "id": "b788404e",
    "metadata": {},
    "outputs": [
     {
@@ -189,7 +189,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "77a32127",
+   "id": "a049ef75",
    "metadata": {},
    "outputs": [
     {
@@ -209,7 +209,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "9e31a82a",
+   "id": "9beac0a6",
    "metadata": {},
    "outputs": [
     {
@@ -218,7 +218,7 @@
      "text": [
       "Variable   Type       Data/Info\n",
       "-------------------------------\n",
-      "load_xy    NpzFile    <numpy.lib.npyio.NpzFile <...>object at 0x7fa36f0491f0>\n",
+      "load_xy    NpzFile    <numpy.lib.npyio.NpzFile <...>object at 0x7fd7e0165820>\n",
       "np         module     <module 'numpy' from '/ho<...>kages/numpy/__init__.py'>\n"
      ]
     }
@@ -229,7 +229,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f2e4a45a",
+   "id": "d5f9dc47",
    "metadata": {},
    "source": [
     "## Reassign the NpzFile arrays to `x` and `y`\n",
@@ -242,7 +242,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "4c927eaa",
+   "id": "532bd0ca",
    "metadata": {},
    "outputs": [
     {
@@ -263,7 +263,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "07e52076",
+   "id": "3252b27b",
    "metadata": {},
    "source": [
     "## Success\n",
@@ -294,7 +294,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "05e8b294",
+   "id": "cba541b8",
    "metadata": {},
    "outputs": [
     {
@@ -323,7 +323,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "abc44c4f",
+   "id": "e05d80a1",
    "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": "89bec31e",
+   "id": "d2021ed0",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -347,7 +347,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4e1778dd",
+   "id": "5b4a4311",
    "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": "1526656f",
+   "id": "8397700b",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -397,7 +397,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "2909a033",
+   "id": "eb105288",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -409,7 +409,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "c6a8f97e",
+   "id": "9572c696",
    "metadata": {},
    "outputs": [
     {
@@ -430,7 +430,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "cdf932b3",
+   "id": "75707ea3",
    "metadata": {},
    "outputs": [
     {
@@ -451,7 +451,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ea618eb4",
+   "id": "eeec280a",
    "metadata": {},
    "source": [
     "## Success, but remember your types\n",
@@ -462,7 +462,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7004594f",
+   "id": "3a868c61",
    "metadata": {},
    "source": [
     "## Wrapping up\n",