def main(simulationDataFrameCSVFile):
simulationDataFrame = pandas.read_csv(simulationDataFrameCSVFile)
# set simulation data as dictionary
simulationCollection = InputSimulation.getSimulationCollection(
simulationDataFrame)
if False:
fig1 = Figure("/home/aholaj/Nextcloud/kuvatesti", "Prognostic")
cloudTicks = Plot.getTicks(0, 1000, 250)
logaritmicLevels = Plot.getLogaritmicTicks(-17, -9, includeFives=True)
ax, im = Plot.getTimeseriesOfProfile(
fig1.getAxes(),
simulationCollection["Prognostic_48h"],
"P_cDUa",
title="",
yticks=cloudTicks,
timeEndH=33.05,
levels=logaritmicLevels,
useColorBar=False,
showXaxisLabels=False,
showXLabel=False)
fig1.save()
if False:
# create figure object
fig2 = Figure("/home/aholaj/Nextcloud/kuvatesti", "LWP")
# load ts-datasets and change their time coordinates to hours
for k in [
"Prognostic_48h", "ICE4_24h", "Prognostic_2",
"Prognostic_Aero", "Prognostic_2_Aero"
]:
simulationCollection[k].getTSDataset()
simulationCollection[k].setTimeCoordToHours()
# plot timeseries with unit conversion
Plot.getTimeseries(fig2.getAxes(), [
simulationCollection["Prognostic_48h"],
simulationCollection["ICE4_24h"],
simulationCollection["Prognostic_Aero"],
simulationCollection["Prognostic_2"],
simulationCollection["Prognostic_2_Aero"]
],
"lwp_bar",
conversionFactor=1000.)
end = 32
# set xticks
ticks = PlotTweak.setXticks(fig2.getAxes(), end=end, interval=0.5)
# set xlabels
shownLabelsBoolean = PlotTweak.setXLabels(fig2.getAxes(),
ticks,
end=end,
interval=4)
# set xtick sizes
PlotTweak.setXTickSizes(fig2.getAxes(),
shownLabelsBoolean,
minorFontSize=8)
# limit x-axes
PlotTweak.setXLim(fig2.getAxes(), end=end)
PlotTweak.setYLim(fig2.getAxes(), end=60)
# set annotation for figure
PlotTweak.setAnnotation(fig2.getAxes(),
"a) Liquid water path",
xPosition=2,
yPosition=30)
Plot.getVerticalLine(fig2.getAxes(), 2)
# set axes labels
PlotTweak.setXaxisLabel(fig2.getAxes(), "LWP", "g\ m^{-2}")
PlotTweak.setYaxisLabel(fig2.getAxes(), "Time", "h")
PlotTweak.useLegend(fig2.getAxes())
PlotTweak.setTightLayot(fig2.getFig())
fig2.save()
if True:
# create figure object
fig2 = Figure("/home/aholaj/Nextcloud/kuvatesti", "Nc_ic")
# load ts-datasets and change their time coordinates to hours
sensitive = [
"ICE0_8h", "ICE1_24h", "ICE2_24h", "ICE3_24h", "ICE3_8h",
"ICE4_24h", "ICE5_8h", "ICE6_8h", "Prognostic_48h"
]
for k in sensitive:
simulationCollection[k].getTSDataset()
simulationCollection[k].setTimeCoordToHours()
# plot timeseries with unit conversion
Plot.getTimeseries(fig2.getAxes(),
simulationCollection[k],
"Nc_ic",
conversionFactor=1e-6)
end = 32
# set xticks
ticks = PlotTweak.setXticks(fig2.getAxes(), end=end, interval=0.5)
# set xlabels
shownLabelsBoolean = PlotTweak.setXLabels(fig2.getAxes(),
ticks,
end=end,
interval=4)
# set xtick sizes
PlotTweak.setXTickSizes(fig2.getAxes(),
shownLabelsBoolean,
minorFontSize=8)
# limit x-axes
PlotTweak.setXLim(fig2.getAxes(), end=end)
#PlotTweak.setYLim(fig2.getAxes(), end = 60)
# set annotation for figure
PlotTweak.setAnnotation(fig2.getAxes(),
"a) Nc_ic",
xPosition=2,
yPosition=155)
Plot.getVerticalLine(fig2.getAxes(), 2)
# set axes labels
PlotTweak.setYaxisLabel(fig2.getAxes(), "In-cloud\ CDNC", "mg^{-1}")
PlotTweak.setXaxisLabel(fig2.getAxes(), "Time", "h")
PlotTweak.useLegend(fig2.getAxes())
PlotTweak.setTightLayot(fig2.getFig())
fig2.save(file_extension=".png")
if True:
# create figure object
fig3 = Figure("/home/aholaj/Nextcloud/kuvatesti", "IWP")
# load ts-datasets and change their time coordinates to hours
for k in [
"Prognostic_48h", "ICE4_24h", "Prognostic_2",
"Prognostic_Aero", "Prognostic_2_Aero"
]:
simulationCollection[k].getTSDataset()
#simulationCollection[k].setTimeCoordToHours()
# plot timeseries with unit conversion
Plot.getTimeseries(fig3.getAxes(), [
simulationCollection["Prognostic_48h"],
simulationCollection["ICE4_24h"],
simulationCollection["Prognostic_Aero"],
simulationCollection["Prognostic_2"],
simulationCollection["Prognostic_2_Aero"]
],
"iwp_bar",
conversionFactor=1000.)
end = 32
# set xticks
ticks = PlotTweak.setXticks(fig3.getAxes(), end=end, interval=0.5)
# set xlabels
shownLabelsBoolean = PlotTweak.setXLabels(fig3.getAxes(),
ticks,
end=end,
interval=4)
# set xtick sizes
PlotTweak.setXTickSizes(fig3.getAxes(),
shownLabelsBoolean,
minorFontSize=8)
# limit x-axes
PlotTweak.setXLim(fig3.getAxes(), end=end)
PlotTweak.setYLim(fig3.getAxes(), end=60)
# set annotation for figure
PlotTweak.setAnnotation(fig3.getAxes(),
"b) Ice water path",
xPosition=2,
yPosition=30)
Plot.getVerticalLine(fig3.getAxes(), 2)
# set axes labels
PlotTweak.setXaxisLabel(fig3.getAxes(), "IWP", "g\ m^{-2}")
PlotTweak.setYaxisLabel(fig3.getAxes(), "Time", "h")
PlotTweak.useLegend(fig3.getAxes())
PlotTweak.setTightLayot(fig3.getFig())
fig3.save()
if False:
# create figure object
fig2 = Figure("/home/aholaj/Nextcloud/kuvatesti",
"fourWinds",
ncols=2,
nrows=2,
style="seaborn-paper")
# load ts-datasets and change their time coordinates to hours
for k in ["ICE0_8h", "ICE1_8h"]:
simulationCollection[k].getTSDataset()
simulationCollection[k].getPSDataset()
simulationCollection[k].setTimeCoordToHours()
# plot timeseries with unit conversion
Plot.getTimeseries(fig2.getAxes()[0, 0],
simulationCollection["ICE0_8h"],
"lwp_bar",
conversionFactor=1000.)
Plot.getVerticalLine(fig2.getAxes()[0, 0], 2)
if True:
PlotTweak.setSuperWrapper(
fig2.getAxes()[0, 0],
xstart=0,
xend=8,
xtickinterval=0.5,
xlabelinterval=2,
xticks=None,
xShownLabels=None,
xTickMajorFontSize=
3.5, # matplotlib.rcParams["xtick.major.size"],
yTickMajorFontSize=
3.5, #matplotlib.rcParams["ytick.major.size"],
ystart=0,
yend=60,
ytickinterval=2,
ylabelinterval=10,
yticks=None,
yShownLabels=None,
annotationText=None,
annotationXPosition=2,
annotationYPosition=30,
xlabel="Time",
xunit="h",
ylabel="LWP",
yunit="g\ m^{-2}",
useBold=True)
PlotTweak.hideYTickLabels(fig2.getAxes()[0, 0])
PlotTweak.setAxesOff(fig2.getAxes()[0, 1])
PlotTweak.setLegendSimulation(
fig2.getAxes()[0, 1],
[simulationCollection["ICE0_8h"], simulationCollection["ICE1_8h"]])
ax, im, levels = Plot.getTimeseriesOfProfile(
fig2.getAxes()[1, 1],
simulationCollection["ICE0_8h"],
"P_RH",
levels=None,
useLogaritmic=False,
colors=None)
PlotTweak.setAxesOff(fig2.getAxes()[1, 0])
cax = matplotlib.pyplot.axes([0.05, 0.25, 0.3, 0.03])
Plot.getColorBar(im, cax, levels)
#Plot.getContourLine(fig2.getAxes()[1,1],"ICE0_8h", color = 'black' , value = 100)
fig2.save()
def figure5(self):
fig = Figure(self.figurefolder,"figure5", ncols = 2, nrows = 2, wspace=0.1, bottom = 0.14, left=0.15, top=0.98)
simulation = "Prognostic_48h"
self.simulationCollection[simulation].getPSDataset()
self.simulationCollection[simulation].getTSDataset()
self.simulationCollection[simulation].setTimeCoordToHours()
logaritmicLevels = PlotTweak.getLogaritmicTicks(-17,-9, includeFives = True)
end = 1000
yPositionFrac = 0.9
xPosition = 0.5
orange = Colorful.getDistinctColorList("orange")
annotation = ["a) Dust in aerosols", "b) Dust in cloud droplets", "c) Dust in ice crystals"]
for ind, muuttuja in enumerate(["P_cDUa", "P_cDUc", "P_cDUi"]):
ax = fig.getAxes(ind)
data = self.simulationCollection[simulation].getPSDataset()[muuttuja]
data.values = numpy.log10(data.values)
im = data.plot.contourf("time","zt", ax = ax, levels=logaritmicLevels, add_colorbar = False)
self.simulationCollection[simulation].getTSDataset()["zb"].plot(ax = ax,
color = orange,
linewidth = self.simulationCollection[simulation].getLineWidth())
ax = Plot.getContourLine(ax, self.simulationCollection[simulation], "P_RHi", 100)
PlotTweak.setAnnotation(ax, annotation[ind], xPosition=xPosition, yPosition= yPositionFrac*end)
end = 1000
PlotTweak.setYLim(ax, end = end)
ticks = PlotTweak.setYticks(ax, end = end, interval = 100)
shownLabelsBoolean = PlotTweak.setYLabels(ax, ticks, end = end, interval = 200)
PlotTweak.setYTickSizes(ax, shownLabelsBoolean)
for i in range(3):
ax = fig.getAxes(i)
end = 33.05
PlotTweak.setXLim(ax, end = end)
Plot.getVerticalLine(ax, 2)
if i in [1,2]:
PlotTweak.setXaxisLabel(ax,"Time", "h")
else:
PlotTweak.setXaxisLabel(ax,"")
PlotTweak.hideXTickLabels(ax)
if i == 1:
PlotTweak.hideYTickLabels(ax)
if i in [0,2]:
PlotTweak.setYaxisLabel(ax,"Height", "m")
else:
PlotTweak.setYaxisLabel(ax,"")
PlotTweak.hideYTickLabels(ax)
ticks = PlotTweak.setXticks(ax, end = end, interval = 1)
shownLabelsBoolean = PlotTweak.setXLabels(ax, ticks, end = end, interval = 4)
PlotTweak.setXTickSizes(ax, shownLabelsBoolean)
# empty space
ax = fig.getAxes(3)
ax.axis("off")
legend_elements = [Patch(facecolor="black",
label='RH over ice 100%'),
Patch(facecolor=orange,
label='Cloud base')]
ax.legend(handles=legend_elements, loc=(0.07,-0.02), frameon = True, framealpha = 1.0)
cax = matplotlib.pyplot.axes([0.6, 0.4, 0.33, 0.03])
Plot.getColorBar(im,cax,logaritmicLevels)
shownLabelsBoolean = Data.getMaskedList(logaritmicLevels, numpy.arange(-11,-19,-1))
PlotTweak.hideLabels(cax.xaxis, shownLabelsBoolean)
PlotTweak.setXTickSizes(cax, shownLabelsBoolean)
PlotTweak.setXaxisLabel(cax, "", unit="kg\ kg^{-1}")
###
fig.save()
