{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "%config InlineBackend.figure_formats = ['svg']\n", "import oscovida as ov" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "text/markdown": [ "[Execute this notebook with Binder](https://mybinder.org/v2/gh/oscovida/binder/master?filepath=ipynb/tutorial-overview-plot_time_step.ipynb)" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ov.display_binder_link(\"tutorial-overview-plot_time_step.ipynb\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Total cumulative numbers\n", "\n", "The first graph returned by the `overview` function (see the [overview](tutorial-overview-graphs.nbdata.html)\n", "and the explanation of the [observables](tutorial-observables.nbdata.html))\n", "shows the cumulative numbers for COVID cases and deaths. Here we show how it is created internally." ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Firstly, we import the plotting framework and some special functions:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "from matplotlib.ticker import ScalarFormatter, FuncFormatter, FixedLocator\n", "from matplotlib.dates import DateFormatter, MONDAY, WeekdayLocator" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "We will need an empty Matplotlib graph object to pass onto the plotting functions." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "image/svg+xml": [ "\n", "\n", "\n", "\n" ], "text/plain": [ "

" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig1, ax1 = plt.subplots();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's add some data to our empty graph" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "country = \"Iran\"\n", "weeks = 30\n", "cases, deaths = ov.get_country_data(country)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we populate the empty plot we have with the data. We call the ploting function twice with two different series of data:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "image/svg+xml": [ "\n", "\n", "\n", "\n" ], "text/plain": [ "

" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ov.plot_time_step(ax=ax1, series=cases) # add cases to the graph\n", "ov.plot_time_step(ax=ax1, series=deaths) # add deaths to the graph\n", "ax1.set_title(\"Total numbers, log scale\")\n", "ax1.legend()\n", "ax1\n", "fig1" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Additionaly, one may turn off the logarithmic scale with `logscale=False` and pick another line style:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/svg+xml": [ "\n", "\n", "\n", "\n" ], "text/plain": [ "

" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig2, ax2 = plt.subplots();\n", "ov.plot_time_step(ax=ax2, series=cases, style='*', logscale=False) # add cases to the graph\n", "ov.plot_time_step(ax=ax2, series=deaths, style='--', logscale=False) # add deaths to the graph\n", "ax2.set_title(\"Total numbers, linear scale\")\n", "ax2.legend();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Other tutorials\n", "\n", "You can find [more tutorials here](tag-tutorial.html)." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.7" } }, "nbformat": 4, "nbformat_minor": 4 }