593 lines
16 KiB
Julia
593 lines
16 KiB
Julia
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module plotting
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using StatsPlots, Plots, DataFrames, Statistics, Dates
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export plotEverything, plotBars, plotAllDistributions
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function plotEverything(df1, df2, settings, memory)
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println("Data is being plotted.")
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dateString = Dates.format(Dates.now(), "yyyy-mm-dd_HH.MM.SS")
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memory.focus = ""
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memory.yTicks = ((0-240):60:2000) #change for case
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memory.xRotation = 90.0
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memory.xLabel = "stations"
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memory.yLabel = ""
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memory.color = [:chartreuse :yellow2 :lightskyblue :purple]
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memory.linewidth = 0
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memory.barwidth = 0.7
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memory.tickSize = 13
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memory.guidefontsize = 20
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memory.legendSize = 13
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memory.titleSize = 23
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memory.legendPosition = :outerright
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if settings.approach == "registration points"
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memory.yLabel = "deviation in seconds"
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memory.focus = "Line " * settings.analyzedLine
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memory.size = (2000, 1300)
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memory.direction1 =
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settings.stationDict[df1.station[length(df1.station)]]
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memory.direction2 =
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settings.stationDict[df2.station[length(df2.station)]]
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if settings.timePeriod[1] != "no" &&
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settings.timePeriod[1] != "match day" &&
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settings.timePeriod[1] != "rush hour" &&
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settings.analyzedLine != "11"
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memory.title =
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memory.focus *
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" - Direction " *
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memory.direction1 *
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" - " *
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settings.timePeriod[1] *
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"/ " *
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settings.timePeriod[2] *
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" - " *
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settings.quantile[1] *
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" %-Quantile"
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p1 = plotBarsDays(df1, settings, memory)
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memory.title =
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memory.focus *
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" - Direction " *
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memory.direction2 *
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" - " *
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settings.timePeriod[1] *
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"/ " *
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settings.timePeriod[2] *
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" - " *
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settings.quantile[1] *
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" %-Quantile"
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p2 = plotBarsDays(df2, settings, memory)
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elseif settings.timePeriod[1] == "match day" &&
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settings.analyzedLine != "11"
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memory.size = (900, 750)
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memory.title =
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memory.focus *
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" - Direction " *
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memory.direction1 *
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" - Match Day - " *
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settings.quantile[1] *
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" %-Quantile"
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p1 = plotBarsGameOrRushHour(df1, settings, memory)
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memory.title =
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memory.focus *
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" - Direction " *
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memory.direction2 *
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" - Match Day - " *
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settings.quantile[1] *
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" %-Quantile"
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p2 = plotBarsGameOrRushHour(df2, settings, memory)
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elseif settings.timePeriod[1] == "rush hour" &&
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settings.analyzedLine != "11"
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memory.title =
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memory.focus *
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" - Direction " *
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memory.direction1 *
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" - Rush Hour - " *
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settings.quantile[1] *
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" %-Quantile"
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p1 = plotBarsGameOrRushHour(df1, settings, memory)
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memory.title =
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memory.focus *
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" - Direction " *
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memory.direction2 *
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" - Rush Hour - " *
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settings.quantile[1] *
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" % Quantile"
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p2 = plotBarsGameOrRushHour(df2, settings, memory)
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elseif settings.timePeriod[1] == "no" #no extra settings
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memory.title = memory.focus * " - Direction " * memory.direction1
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p1 = plotBarsMultQuant(df1, settings, memory)
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memory.title = memory.focus * " - Direction " * memory.direction2
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p2 = plotBarsMultQuant(df2, settings, memory)
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memory.title = memory.focus * " - Distribution"
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#plotDistributionInSec(df1, df2, settings, memory)
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plotDistributionInMin(df1, df2, settings, memory)
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if length(settings.allLines) == length(memory.distributionMin)
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#plotAllDistributions(settings, memory)
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#memory.title = "Distribution S-Bahn Stuttgart - 'new' quantiles"
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memory.title = "Distribution S-Bahn Stuttgart - 'danish' quantiles"
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p3 = plotAllDistributions(settings, memory)
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settings.allLines = ["1", "2", "3", "4", "5", "6", "60"]
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pop!(memory.distributionMin)
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memory.title = ""
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p4 = plotAllDistributions(settings, memory)
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all = plot(p3, p4, layout = (2, 1), legend = :bottomright)
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savefig(
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all,
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settings.outputFilePath *
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"\\Plots\\all_Lines" *
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"_" *
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dateString *
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".pdf",
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)
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end
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end
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dateString = Dates.format(Dates.now(), "yyyy-mm-dd_HH.MM.SS")
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all = plot(p1, p2, layout = (2, 1), legend = memory.legendPosition)
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savefig(
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all,
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settings.outputFilePath *
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"\\Plots\\" *
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memory.focus *
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" " *
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settings.approach *
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"_" *
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dateString *
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".pdf",
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)
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elseif settings.approach == "between registration points"
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myTitle1 = ""
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myTitle2 = ""
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memory.yLabel = "deviation - median (seconds)"
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memory.size = (900, 750)
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memory.focus = "Line " * settings.analyzedLine
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memory.direction1 = settings.stationDict[df1.point2[length(df1.point2)]]
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memory.direction2 = settings.stationDict[df2.point2[length(df2.point2)]]
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memory.title = memory.focus * " - Direction " * memory.direction1
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p1 = plotBarsLineSection(df1, settings, memory)
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memory.title = memory.focus * " - Direction " * memory.direction2
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p2 = plotBarsLineSection(df2, settings, memory)
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all = plot(p1, p2, layout = (2, 1), legend = false, size = (800, 600))
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dateString = Dates.format(Dates.now(), "yyyy-mm-dd_HH.MM.SS")
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savefig(
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all,
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settings.outputFilePath *
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"\\Plots\\" *
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memory.focus *
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" " *
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settings.approach *
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"_" *
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dateString *
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".pdf",
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)
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end
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end
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function plotAllDistributions(settings, memory)
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Plots.pyplot()
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y = Any[]
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x = Any[]
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for quantile in settings.quantile
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push!(y, parse(Int, quantile))
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end
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x = memory.distributionMin[1]
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#average september and october; source: DB
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a = [3, 6]
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b = [84.9, 95.8]
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tickX = (0:1:20)
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z = plot(
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a,
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b,
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label = "average deviation sept/ oct 2017",
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xlabel = "Deviation (min)",
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ylabel = "Quantile (%)",
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marker = true,
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legend = :bottomright,
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color = :red,
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xticks = tickX,
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size = (840, 600),
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)
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colors = [
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:gray71,
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:slateblue,
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:goldenrod,
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:darkcyan,
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:magenta4,
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:aqua,
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:deeppink,
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:tan4,
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]
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z = plot!(
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x,
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y,
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title = memory.title,
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label = "line " * settings.allLines[1],
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marker = true,
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color = colors[1],
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)
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for i = 2:length(memory.distributionMin)
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x = memory.distributionMin[i]
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colorN = colors[i]
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z = plot!(
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x,
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y,
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marker = true,
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color = colorN,
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label = "line " * settings.allLines[i],
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)
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end
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dateString = Dates.format(Dates.now(), "yyyy-mm-dd_HH.MM.SS")
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savefig(
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z,
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settings.outputFilePath *
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"\\Plots\\all_lines_deviation(min)_" *
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dateString *
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".pdf",
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)
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return z
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end
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function plotBarsMultQuant(df, settings, memory)
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pyplot()
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stations = Array{Int,1}()
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depOrArr = Array{String,1}()
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quantile = Array{Float64,1}()
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type = Array{String,1}()
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stationList = Any[]
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for index = 1:length(df.station)
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push!(stationList, df.station[index] * "_" * df.DepOrArr[index])
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for numberQuant = 1:length(settings.quantile)
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push!(stations, index)
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currentColumn = df[!, "quantile"*string(numberQuant)]
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push!(quantile, currentColumn[index])
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push!(type, settings.quantile[numberQuant] * "% quantile")
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end
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end
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df_new =
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DataFrame(station = (stations), quantile = (quantile), type = (type))
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memory.stationList = copy(stationList)
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x = plotBars(df_new, memory, settings)
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x = plot!(
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df.AverageDelay,
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linewidth = 3,
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linecolor = :blue,
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marker = true,
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label = "Average",
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)
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return x
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end
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function plotBarsDays(df, settings, memory)
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pyplot()
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stations = Array{Int,1}()
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depOrArr = Array{String,1}()
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quantile = Array{Float64,1}()
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type = Array{String,1}()
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stationList = Any[]
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for index = 1:length(df.station)
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push!(stationList, df.station[index] * "_" * df.DepOrArr[index])
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for day in settings.timePeriod
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push!(stations, index)
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currentColumn = df[!, "quantile"*settings.quantile[1]*"_"*day]
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push!(quantile, currentColumn[index])
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push!(type, day)
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end
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end
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df_new =
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DataFrame(station = (stations), quantile = (quantile), type = (type))
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memory.stationList = copy(stationList)
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x = plotBars(df_new, memory, settings)
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x = plot!(
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df[!, "average_"*settings.timePeriod[1]],
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linewidth = 3,
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linecolor = :orange,
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label = "Average Delay " * settings.timePeriod[1],
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)
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x = plot!(
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df[!, "average_"*settings.timePeriod[2]],
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linewidth = 3,
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linecolor = :blue,
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label = "Average Delay " * settings.timePeriod[2],
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)
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return x
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end
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function plotBarsLineSection(df, settings, memory)
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pyplot()
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x = bar(
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df.median,
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xticks = ([1:1:length(df.points);], df.points),
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yticks = ((0-270):30:210),
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legend = false,
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title = memory.title,
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ylabel = memory.yLabel,
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xlabel = memory.xLabel,
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size = (800, 300),
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bar_width = 1.0,
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xtickfontrotation = memory.xRotation,
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)
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return x
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end
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function plotDistributionInSec(df1, df2, settings, memory)
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mean1 = (mean(df1.quantile1) + mean(df2.quantile1)) / 2
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mean2 = (mean(df1.quantile2) + mean(df2.quantile2)) / 2
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mean3 = (mean(df1.quantile3) + mean(df2.quantile3)) / 2
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mean4 = (mean(df1.quantile4) + mean(df2.quantile4)) / 2
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pyplot()
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y = Any[]
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for quantile in settings.quantile
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push!(y, parse(Int, quantile))
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end
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x = [mean1, mean2, mean3, mean4]
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#Jahrendurschnitt Quelle: DB
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a = [3 * 60, 6 * 60]
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b = [84.9, 95.8]
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z = plot(
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a,
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b,
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title = memory.title,
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label = "average deviation september/october 2017",
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xlabel = "Deviation (sec)",
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ylabel = "Quantile",
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marker = true,
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legend = :bottomright,
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color = :red,
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)
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z = plot!(
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x,
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y,
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marker = true,
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label = "Deviation Line" * settings.analyzedLine,
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)
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dateString = Dates.format(Dates.now(), "yyyy-mm-dd_HH.MM.SS")
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savefig(
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z,
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settings.outputFilePath *
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"\\Plots\\Line_" *
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settings.analyzedLine *
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"_Deviation(sec)_" *
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dateString *
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||
|
|
".pdf",
|
||
|
|
)
|
||
|
|
|
||
|
|
end
|
||
|
|
|
||
|
|
function plotDistributionInMin(df1, df2, settings, memory)
|
||
|
|
|
||
|
|
mean1 = (mean(df1.quantile1) + mean(df2.quantile1)) / 2 / 60
|
||
|
|
mean2 = (mean(df1.quantile2) + mean(df2.quantile2)) / 2 / 60
|
||
|
|
mean3 = (mean(df1.quantile3) + mean(df2.quantile3)) / 2 / 60
|
||
|
|
mean4 = (mean(df1.quantile4) + mean(df2.quantile4)) / 2 / 60
|
||
|
|
|
||
|
|
pyplot()
|
||
|
|
y = Any[]
|
||
|
|
for quantile in settings.quantile
|
||
|
|
push!(y, parse(Int, quantile))
|
||
|
|
end
|
||
|
|
x = [mean1, mean2, mean3, mean4]
|
||
|
|
push!(memory.distributionMin, x)
|
||
|
|
|
||
|
|
#Jahrendurschnitt Quelle: DB
|
||
|
|
a = [3, 6]
|
||
|
|
b = [84.9, 95.8]
|
||
|
|
|
||
|
|
z = plot(
|
||
|
|
a,
|
||
|
|
b,
|
||
|
|
title = memory.title,
|
||
|
|
label = "average deviation september/october 2017",
|
||
|
|
xlabel = "Deviation (min)",
|
||
|
|
ylabel = "Quantile",
|
||
|
|
marker = true,
|
||
|
|
legend = :bottomright,
|
||
|
|
color = :red,
|
||
|
|
)
|
||
|
|
|
||
|
|
z = plot!(
|
||
|
|
x,
|
||
|
|
y,
|
||
|
|
marker = true,
|
||
|
|
label = "Deviation " * memory.focus,
|
||
|
|
color = :blue,
|
||
|
|
)
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
dateString = Dates.format(Dates.now(), "yyyy-mm-dd_HH.MM.SS")
|
||
|
|
|
||
|
|
savefig(
|
||
|
|
z,
|
||
|
|
settings.outputFilePath *
|
||
|
|
"\\Plots\\" *
|
||
|
|
memory.title *
|
||
|
|
dateString *
|
||
|
|
".pdf",
|
||
|
|
)
|
||
|
|
|
||
|
|
end
|
||
|
|
|
||
|
|
function plotRailwayNetworkDistr(df1, df2, settings)
|
||
|
|
mean1 = (mean(df1.quantile1) + mean(df2.quantile1)) / 2 / 60
|
||
|
|
mean2 = (mean(df1.quantile2) + mean(df2.quantile2)) / 2 / 60
|
||
|
|
mean3 = (mean(df1.quantile3) + mean(df2.quantile3)) / 2 / 60
|
||
|
|
mean4 = (mean(df1.quantile4) + mean(df2.quantile4)) / 2 / 60
|
||
|
|
|
||
|
|
pyplot()
|
||
|
|
y = Any[]
|
||
|
|
for quantile in settings.quantile
|
||
|
|
push!(y, parse(Int, quantile))
|
||
|
|
end
|
||
|
|
x = [mean1, mean2, mean3, mean4]
|
||
|
|
|
||
|
|
z = plot(
|
||
|
|
x,
|
||
|
|
y,
|
||
|
|
title = settings.objectInFocus * " - Distribution",
|
||
|
|
label = "Deviation " * settings.objectInFocus,
|
||
|
|
xlabel = "Deviation (min)",
|
||
|
|
ylabel = "Quantile",
|
||
|
|
marker = true,
|
||
|
|
legend = :bottomright,
|
||
|
|
)
|
||
|
|
|
||
|
|
#Durchschnitt September und Oktober Quelle: DB
|
||
|
|
a = [3, 6]
|
||
|
|
b = [84.9, 95.8]
|
||
|
|
|
||
|
|
|
||
|
|
z = plot!(a, b, marker = true, label = "Average Deviation 2017")
|
||
|
|
|
||
|
|
|
||
|
|
dateString = Dates.format(Dates.now(), "yyyy-mm-dd_HH.MM.SS")
|
||
|
|
|
||
|
|
savefig(
|
||
|
|
z,
|
||
|
|
settings.outputFilePath *
|
||
|
|
"\\Plots\\" *
|
||
|
|
settings.objectInFocus *
|
||
|
|
"_Deviation(min)_" *
|
||
|
|
dateString *
|
||
|
|
".pdf",
|
||
|
|
)
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
end
|
||
|
|
|
||
|
|
function plotBarsGameOrRushHour(df, settings, memory)
|
||
|
|
|
||
|
|
|
||
|
|
pyplot()
|
||
|
|
|
||
|
|
stations = Array{Int,1}()
|
||
|
|
depOrArr = Array{String,1}()
|
||
|
|
quantile = Array{Float64,1}()
|
||
|
|
type = Array{String,1}()
|
||
|
|
|
||
|
|
stationList = Any[]
|
||
|
|
|
||
|
|
for index = 1:length(df.station)
|
||
|
|
push!(stationList, df.station[index] * "_" * df.DepOrArr[index])
|
||
|
|
for indicator in ["yes", "no"]
|
||
|
|
push!(stations, index)
|
||
|
|
currentColumn = df[!, "quantile"*settings.quantile[1]*"_"*indicator]
|
||
|
|
push!(quantile, currentColumn[index])
|
||
|
|
push!(type, indicator)
|
||
|
|
end
|
||
|
|
end
|
||
|
|
newType = Any[]
|
||
|
|
if settings.timePeriod[1] == "rush hour"
|
||
|
|
label1 = "Rush Hour"
|
||
|
|
label2 = "'Normal' Time"
|
||
|
|
elseif settings.timePeriod[1] == "match day"
|
||
|
|
label1 = "Match Day"
|
||
|
|
label2 = "'Normal' Day"
|
||
|
|
end
|
||
|
|
for x in type
|
||
|
|
if x == "yes"
|
||
|
|
push!(newType, label1)
|
||
|
|
else
|
||
|
|
push!(newType, label2)
|
||
|
|
end
|
||
|
|
end
|
||
|
|
|
||
|
|
df_new =
|
||
|
|
DataFrame(station = (stations), quantile = (quantile), type = (newType))
|
||
|
|
|
||
|
|
memory.size = (2000, 1000)
|
||
|
|
memory.stationList = copy(stationList)
|
||
|
|
|
||
|
|
x = plotBars(df_new, memory, settings)
|
||
|
|
|
||
|
|
x = plot!(
|
||
|
|
df[!, "average_yes"],
|
||
|
|
linewidth = 3,
|
||
|
|
linecolor = :orange,
|
||
|
|
label = "Average Delay " * label1,
|
||
|
|
)
|
||
|
|
x = plot!(
|
||
|
|
df[!, "average_no"],
|
||
|
|
linewidth = 3,
|
||
|
|
linecolor = :blue,
|
||
|
|
label = "Average Delay " * label2,
|
||
|
|
)
|
||
|
|
|
||
|
|
return x
|
||
|
|
|
||
|
|
end
|
||
|
|
|
||
|
|
function plotBars(df, memory, settings)
|
||
|
|
|
||
|
|
if settings.analyzedLine == "11" &&
|
||
|
|
memory.title == "Line 11 - Direction Herrenberg"
|
||
|
|
memory.yTicks = ((0-240):120:3000)
|
||
|
|
end
|
||
|
|
|
||
|
|
x = groupedbar(
|
||
|
|
df.quantile,
|
||
|
|
xticks = ([1:1:size(memory.stationList, 1);], memory.stationList),
|
||
|
|
yticks = memory.yTicks,
|
||
|
|
group = df.type,
|
||
|
|
ylabel = memory.yLabel,
|
||
|
|
xlabel = memory.xLabel,
|
||
|
|
title = memory.title,
|
||
|
|
size = memory.size,
|
||
|
|
bar_width = memory.barwidth,
|
||
|
|
linewidth = memory.linewidth,
|
||
|
|
tickfontsize = memory.tickSize,
|
||
|
|
legendfontsize = memory.legendSize,
|
||
|
|
guidefontsize = memory.guidefontsize,
|
||
|
|
titlefontsize = memory.titleSize,
|
||
|
|
xtickfontrotation = memory.xRotation,
|
||
|
|
legend = memory.legendPosition,
|
||
|
|
)
|
||
|
|
|
||
|
|
return x
|
||
|
|
|
||
|
|
end
|
||
|
|
|
||
|
|
end
|