From: Neil Smith Date: Sat, 24 Feb 2018 22:34:46 +0000 (+0000) Subject: Cleared outputs, set some init cells X-Git-Url: https://git.njae.me.uk/?a=commitdiff_plain;ds=inline;p=ou-jupyter-r-demo.git Cleared outputs, set some init cells --- diff --git a/3dplot.ipynb b/3dplot.ipynb index 3494384..6f10a6c 100644 --- a/3dplot.ipynb +++ b/3dplot.ipynb @@ -1,25 +1,29 @@ { "cells": [ { - "cell_type": "code", - "execution_count": 1, + "cell_type": "markdown", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "── Attaching packages ─────────────────────────────────────── tidyverse 1.2.1 ──\n", - "✔ ggplot2 2.2.1 ✔ purrr 0.2.4\n", - "✔ tibble 1.4.2 ✔ dplyr 0.7.4\n", - "✔ tidyr 0.8.0 ✔ stringr 1.2.0\n", - "✔ readr 1.1.1 ✔ forcats 0.2.0\n", - "── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──\n", - "✖ dplyr::filter() masks stats::filter()\n", - "✖ dplyr::lag() masks stats::lag()\n" - ] - } - ], + "source": [ + "# 3d plots of regression surfaces" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "heading_collapsed": true + }, + "source": [ + "### Initialisation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "hidden": true, + "init_cell": true + }, + "outputs": [], "source": [ "library(tidyverse)\n", "# library(cowplot)\n", @@ -32,8 +36,11 @@ }, { "cell_type": "code", - "execution_count": 2, - "metadata": {}, + "execution_count": null, + "metadata": { + "hidden": true, + "init_cell": true + }, "outputs": [], "source": [ "source('plot_extensions.R')" @@ -41,16 +48,26 @@ }, { "cell_type": "code", - "execution_count": 3, - "metadata": {}, + "execution_count": null, + "metadata": { + "hidden": true, + "init_cell": true + }, "outputs": [], "source": [ "library(scatterplot3d)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Show plots" + ] + }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -59,7 +76,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -68,20 +85,9 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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rJa5kOhI718O/caeBBuPbVu297F3UQuap+10HVoyVlwN797K1neFrXJ2LDQOmLa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- "text/plain": [ - "plot without title" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "s3d <- scatterplot3d(x = rubber$hardness, y = rubber$strength, z = rubber$loss,\n", " xlab = 'Hardness', ylab = \"Strength\", zlab = \"Loss\",\n", @@ -92,7 +98,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -102,63 +108,9 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\n", - "
ventiloxygenoxy2
-0.9722499-1.607673 -1.213737
-1.0549252-1.592968 -1.210386
-1.0549252-1.534147 -1.195947
-1.0423986-1.531696 -1.195309
-1.0398933-1.490031 -1.184031
-1.0975155-1.447549 -1.171677
\n" - ], - "text/latex": [ - "\\begin{tabular}{r|lll}\n", - " ventil & oxygen & oxy2\\\\\n", - "\\hline\n", - "\t -0.9722499 & -1.607673 & -1.213737 \\\\\n", - "\t -1.0549252 & -1.592968 & -1.210386 \\\\\n", - "\t -1.0549252 & -1.534147 & -1.195947 \\\\\n", - "\t -1.0423986 & -1.531696 & -1.195309 \\\\\n", - "\t -1.0398933 & -1.490031 & -1.184031 \\\\\n", - "\t -1.0975155 & -1.447549 & -1.171677 \\\\\n", - "\\end{tabular}\n" - ], - "text/markdown": [ - "\n", - "ventil | oxygen | oxy2 | \n", - "|---|---|---|---|---|---|\n", - "| -0.9722499 | -1.607673 | -1.213737 | \n", - "| -1.0549252 | -1.592968 | -1.210386 | \n", - "| -1.0549252 | -1.534147 | -1.195947 | \n", - "| -1.0423986 | -1.531696 | -1.195309 | \n", - "| -1.0398933 | -1.490031 | -1.184031 | \n", - "| -1.0975155 | -1.447549 | -1.171677 | \n", - "\n", - "\n" - ], - "text/plain": [ - " ventil oxygen oxy2 \n", - "1 -0.9722499 -1.607673 -1.213737\n", - "2 -1.0549252 -1.592968 -1.210386\n", - "3 -1.0549252 -1.534147 -1.195947\n", - "4 -1.0423986 -1.531696 -1.195309\n", - "5 -1.0398933 -1.490031 -1.184031\n", - "6 -1.0975155 -1.447549 -1.171677" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "anaerobic.n <- data.frame(scale(anaerobic))\n", "head(anaerobic.n)" @@ -166,7 +118,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -175,20 +127,9 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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IFXJVGXsSAuRW1YlAxoomk1a4uBVUxqlqEALa8J4nFiv465+PfjLXCZWefQ9Rxz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", - "text/plain": [ - "plot without title" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "s3d <- with(anaerobic.n, scatterplot3d(x = oxygen, y = oxy2, z = ventil,\n", " xlab = 'Oxygen', ylab = \"Oxygen2\", zlab = \"Ventil\",\n", diff --git a/section5.1.ipynb b/section5.1.ipynb index 5a8ef2e..e24eb06 100644 --- a/section5.1.ipynb +++ b/section5.1.ipynb @@ -108,17 +108,6 @@ "# print(cbind(af,PctExp=afss/sum(afss)*100))" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# ggplot(rubber, aes(x=hardness, y=loss)) + \n", - "# geom_point() +\n", - "# stat_smooth(method = \"lm\", col = \"red\")" - ] - }, { "cell_type": "code", "execution_count": null, @@ -178,7 +167,9 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "hidden": true + }, "outputs": [], "source": [ "ggplotRegression(fit.s)" diff --git a/section5.1solutions.ipynb b/section5.1solutions.ipynb index 1858975..a4bb428 100644 --- a/section5.1solutions.ipynb +++ b/section5.1solutions.ipynb @@ -38,6 +38,7 @@ "cell_type": "code", "execution_count": null, "metadata": { + "hidden": true, "init_cell": true }, "outputs": [],