{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Plotting traces (collections)\n", "This Tutorial explains how to customize network plots in pandapower using plotly. Each pandapower network element can be translated into a plotly trace with all corresponding properties..." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import pandapower as pp\n", "import pandapower.networks as nw\n", "import pandapower.plotting.plotly as pplotly" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If you want to have full control over the layout of your plot, you can individually create and plot collections with the pandapower plotting module." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "net = nw.mv_oberrhein()\n", "\n", "lc = pplotly.create_line_trace(net,net.line.index, color='black')\n", "bc = pplotly.create_bus_trace(net,net.bus.index,size=10,color=\"orange\",\n", " infofunc=net.bus.name + '
' + net.bus.vn_kv.astype(str) + ' kV')\n", "\n", "pplotly.draw_traces(bc + lc, figsize=1, aspectratio=(8,6))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Order of ploting traces is as ordered in the `draw_traces` function. So, in order to plot buses in front of lines first lines and then buses need to be set in the input traces list:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "pplotly.draw_traces(lc + bc , figsize=1, aspectratio=(8,6))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Highligting\n", "Specific lines or buses can be highlighted by creating extra line collections in different colors.\n", "\n", "In this example, we plot lines that are longer than 2 km green and buses with a voltage below 0.98 pu red.\n", "\n", "First, we create a line collection for all lines in grey and a line collection for only the long lines in green:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "long_lines = net.line[net.line.length_km > 2.].index\n", "lc = pplotly.create_line_trace(net, net.line.index, color=\"grey\")\n", "lcl = pplotly.create_line_trace(net, long_lines, color=\"green\", width=2,\n", " infofunc = net.line.name[long_lines] + '
' + net.line.length_km[long_lines].astype(str) + ' km')\n", "\n", "low_voltage_buses = net.res_bus[net.res_bus.vm_pu < 0.98].index\n", "bc = pplotly.create_bus_trace(net, net.bus.index, size=10, color=\"blue\")\n", "bch = pplotly.create_bus_trace(net, low_voltage_buses, size=10, color=\"red\")\n", "\n", "pplotly.draw_traces(bc + bch + lc + lcl )" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "## Highlighting with the Topology Package\n", "Colors palette for plotly can be obtained using function `plotting.plotly.get_plotly_color_palette(n)` where argument `n` defines number of colors that will be returned in a list." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from pandapower.plotting.plotly import get_plotly_color_palette\n", "\n", "net = nw.mv_oberrhein()\n", "\n", "mg = pp.topology.create_nxgraph(net, nogobuses=set(net.trafo.lv_bus.values) | set(net.trafo.hv_bus.values))\n", "collections = []\n", "ai = 0\n", "islands = list(pp.topology.connected_components(mg)) # getting connected components of a graph\n", "colors = get_plotly_color_palette(len(islands)) # getting a color for each connected component\n", "for color, area in zip(colors, islands):\n", " collections += pplotly.create_bus_trace(net, area, size=5, color=color, trace_name='feeder {0}'.format(ai))\n", " ai += 1\n", "collections += pplotly.create_line_trace(net, net.line.index, color=\"grey\")\n", "collections += pplotly.create_bus_trace(net, net.ext_grid.bus.values, patch_type=\"square\", size=10,\n", " color=\"yellow\")\n", "pplotly.draw_traces(collections)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Collection on mapbox\n", "If network geo-data are not in lat/long form, there is a function `geo_data_to_latlong` which can be used to transform entire network geodata from a specific projection to lat/long:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "net = nw.mv_oberrhein()\n", "pplotly.geo_data_to_latlong(net, projection='epsg:31467') #transforming geodata to lat/long\n", "\n", "lc = pplotly.create_line_trace(net,net.line.index, color='purple')\n", "bc = pplotly.create_bus_trace(net,net.bus.index,size=10,color=\"orange\",\n", " infofunc=net.bus.name + '
' + net.bus.vn_kv.astype(str) + ' kV')\n", "\n", "pplotly.draw_traces(bc + lc, on_map = True, map_style='dark')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Colormaps\n", "Colormaps plots are available for plotly by setting `cmap=True` in create functions. By default line loading and bus voltage magnitudes will be used for coloring." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "net = nw.mv_oberrhein()\n", "bt = pplotly.create_bus_trace(net, cmap=True)\n", "lt = pplotly.create_line_trace(net, cmap=True)\n", "pplotly.draw_traces(lt + bt, showlegend=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Some customization is possible in regard to: limits, choosing a colormap, colorbar title, etc." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "lt = pplotly.create_line_trace(net, cmap='Blues', cmin=0, cmax=100, cbar_title = 'Line loading [%]')\n", "pplotly.draw_traces(lt, showlegend=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Alternatively, any other values can be used for colormaps, with also some customization in regard to limits, choosing a colormap, colorbar title, etc. An axample with coloring according to line length:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "lt = pplotly.create_line_trace(net, cmap_vals=net.line.length_km, cmap=True, cbar_title = 'Line length [km]')\n", "pplotly.draw_traces(lt, showlegend=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Customized hover-info\n", "Information that pop-ups when a bus or a line is pointed with mouse-cursor is called hover-info. By default it is set to bus/line name, but it can be customized by setting a list of strings to `infofunc` argument. A newline is defined using `
`. See a representative example hereafter (try getting hoverinfo by pointing a cursor above each bus):" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "bc = pplotly.create_bus_trace(net,[1,2,3,4,5],\n", " infofunc = net.bus.name + '
' +\n", " net.bus.vn_kv.astype(str) + ' kV' + '
' +\n", " 'this is one of the 5 buses...',\n", " size = 15)\n", "pplotly.draw_traces(bc)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "More tutorials about interactive plots using ploltly:\n", "* [built-in interactive plots](http://nbviewer.jupyter.org/github/e2nIEE/pandapower/blob/develop/tutorials/plotly_built-in.ipynb)\n", "* [interactive plots on maps](http://nbviewer.jupyter.org/github/e2nIEE/pandapower/blob/develop/tutorials/plotly_maps.ipynb)" ] } ], "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": "3.6.6" } }, "nbformat": 4, "nbformat_minor": 2 }