From 692c9ec9ab86e3f9d5df40f79fcec8e50e6b7965 Mon Sep 17 00:00:00 2001
From: Caroline Arnold <arnold@dkrz.de>
Date: Wed, 8 Mar 2023 08:03:53 +0100
Subject: [PATCH] revised visualization notebooks
---
.../visualization_with_Matplotlib_L1.ipynb | 20 ++++++++++---------
.../visualization_with_Matplotlib_L2.ipynb | 15 +++++++-------
2 files changed, 18 insertions(+), 17 deletions(-)
diff --git a/notebooks/visualization_with_Matplotlib_L1.ipynb b/notebooks/visualization_with_Matplotlib_L1.ipynb
index dfc3881..c203092 100644
--- a/notebooks/visualization_with_Matplotlib_L1.ipynb
+++ b/notebooks/visualization_with_Matplotlib_L1.ipynb
@@ -184,7 +184,7 @@
"\n",
" [<matplotlib.lines.Line2D at 0x10f402500>]\n",
" \n",
- "from above you can write it to a variable:"
+ "from above you can add a semicolon to the line or write the expression to a variable."
]
},
{
@@ -193,7 +193,7 @@
"metadata": {},
"outputs": [],
"source": [
- "yplot = plt.plot(y)"
+ "plt.plot(y);"
]
},
{
@@ -444,7 +444,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "Sometimes you want to overlay different components of your plots using transparency. In matplotlib this is achieved by setting the transparency parameter `alpha`. Here, `alpha=1.` corresponds to full **opacity**, and `alpha=0.` to **full transparency**. In the following plot, we draw a transparent line on top of a solid line:"
+ "Sometimes you want to overlay different components of your plots using transparency. In matplotlib this is achieved by setting the transparency parameter `alpha`. Here, `alpha=1.` corresponds to full **opacity**, and `alpha=0.` to **full transparency**. In the following plot, we draw a black transparent line on top of a solid red line:"
]
},
{
@@ -454,8 +454,8 @@
"outputs": [],
"source": [
"plt.grid()\n",
- "plt.plot(x, y, 'ko-', linewidth=2, alpha=0.2)\n",
- "plt.plot(x, [v**2/2 for v in y], 'rs:', linewidth=2)"
+ "plt.plot(x, [v**2/2 for v in y], 'rs:', linewidth=2)\n",
+ "plt.plot(x, y, 'ko-', linewidth=2, alpha=0.2)"
]
},
{
@@ -611,7 +611,9 @@
"In the next section we demonstrate how to use `pyplot.subplots` functionality to create two plots in one workspace.\n",
"\n",
"1. two plots in one row\n",
- "1. common title on top of the figure\n"
+ "1. common title on top of the figure\n",
+ "\n",
+ "Note that `axs` is now an array, and we access the individual axes by indexing it."
]
},
{
@@ -1183,9 +1185,9 @@
],
"metadata": {
"kernelspec": {
- "display_name": "cartopy",
+ "display_name": "CyGNSS Deployment",
"language": "python",
- "name": "cartopy"
+ "name": "cygnss-d"
},
"language_info": {
"codemirror_mode": {
@@ -1197,7 +1199,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.4"
+ "version": "3.9.13"
}
},
"nbformat": 4,
diff --git a/notebooks/visualization_with_Matplotlib_L2.ipynb b/notebooks/visualization_with_Matplotlib_L2.ipynb
index ec9eac9..cfb4099 100644
--- a/notebooks/visualization_with_Matplotlib_L2.ipynb
+++ b/notebooks/visualization_with_Matplotlib_L2.ipynb
@@ -128,7 +128,7 @@
"\n",
"## Add a legend <a class=\"anchor\" id=\"add-legend\"></a>\n",
"\n",
- "This looks quite nice, but a legend is still missing. Therefore, a **label** has to be added to each plot call and the `legend` fuction from pyplot is used to generate a legend box at the upper left part of the plot (default).\n",
+ "This looks quite nice, but a legend is still missing. Therefore, a **label** has to be added to each plot call and the `legend` fuction from pyplot is used to generate a legend box. By default, the legend is placed in a location where it does not overlap the plot, that can be changed by specifying the `loc` parameter.\n",
"\n",
"<br>"
]
@@ -151,7 +151,6 @@
"ax.plot(data.Jahr, data['Bayern'], color='darkorange', label='Bayern')\n",
"\n",
"legend = ax.legend()\n",
- "#legend = ax.legend(facecolor='lightgray')\n",
"#legend = ax.legend(loc='lower right', shadow=True, fontsize='small', \n",
"# facecolor='lightgray', edgecolor='black')\n",
"\n",
@@ -320,7 +319,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "Another way to create the plot:"
+ "Another way to create the axis in one line of code:"
]
},
{
@@ -577,7 +576,7 @@
" levels=15, transform=ccrs.PlateCarree())\n",
"\n",
"cbar = plt.colorbar(plt_cn, pad=0.08, shrink=0.55)\n",
- "cbar.set_label('$^o$ C', labelpad=15, y=.5, rotation=270)"
+ "cbar.set_label('Surface temperature $(^\\circ\\mathrm{C})$', labelpad=15, y=.5, rotation=90)"
]
},
{
@@ -699,7 +698,7 @@
" transform=ccrs.PlateCarree())\n",
"\n",
"cbar = plt.colorbar(vec, pad=0.07, shrink=0.55)\n",
- "cbar.set_label('Wind magnitude (m/s)', labelpad=15, y=.5, rotation=270)"
+ "cbar.set_label('Wind magnitude (m/s)', labelpad=15, y=.5, rotation=90)"
]
},
{
@@ -933,9 +932,9 @@
],
"metadata": {
"kernelspec": {
- "display_name": "cartopy",
+ "display_name": "ML (based on the latest module pytorch)",
"language": "python",
- "name": "cartopy"
+ "name": "ml-aim"
},
"language_info": {
"codemirror_mode": {
@@ -947,7 +946,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.4"
+ "version": "3.10.8"
}
},
"nbformat": 4,
--
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