figObject.simulationCollection[k].setLineWidth(
matplotlib.rcParams["lines.linewidth"] * 1.5)
figObject.simulationCollection[k].setColor(
Colorful.getDistinctColorList("green"))
figObject.simulationCollection["RadDamp"].setColor(
Colorful.getDistinctColorList("red"))
lwpYlimit = 60
iwpYlimit = 21
yPositionFrac = 0.91
# figA
ax = fig.getAxes(0)
for k in simulationList.getIce0Simulations():
Plot.getTimeseries(ax,
figObject.simulationCollection[k],
"lwp_bar",
conversionFactor=1000.)
PlotTweak.setAnnotation(ax,
"a) ICE0 liquid water path",
xPosition=0.2,
yPosition=lwpYlimit * yPositionFrac)
# figB
ax = fig.getAxes(2)
for k in simulationList.getIce1Simulations():
Plot.getTimeseries(ax,
figObject.simulationCollection[k],
"lwp_bar",
conversionFactor=1000.)
PlotTweak.setAnnotation(ax,
"b) ICE1 liquid water path",
def figure2(self):
# create figure object
fig = Figure(self.figurefolder,"figure2", ncols = 2, nrows = 3)
simulationList = Figure2SimulationList()
for k in simulationList.getAllSimulations():
try:
self.simulationCollection[k].getTSDataset()
self.simulationCollection[k].setTimeCoordToHours()
except FileNotFoundError:
if "ovchinnikov" in str(self.simulationCollection[k].getFolder()).lower():
print("Ovchinnikov data is not available. Continue with existing simulations")
continue
else:
print("{0} data missing from {1}, make sure you have set your \
folder and environment variables correctly".format(k, self.simulationCollection[k].getFolder()))
if self.simulationCollection[k].getLabel() == "BULK":
self.simulationCollection[k].setZorder(1)
elif self.simulationCollection[k].getLabel() == "BIN":
self.simulationCollection[k].setZorder(2)
else:
self.simulationCollection[k].setZorder(3)
for k in simulationList.getUCLALESSALSASimulations():
self.simulationCollection[k].setLineWidth(matplotlib.rcParams["lines.linewidth"]*1.5)
self.simulationCollection[k].setColor(Colorful.getDistinctColorList("green"))
lwpYlimit = 60
iwpYlimit = 21
yPositionFrac = 0.91
# figA
ax = fig.getAxes(0)
for k in simulationList.getIce0Simulations():
Plot.getTimeseries(ax,
self.simulationCollection[k],
"lwp_bar", conversionFactor=1000.)
PlotTweak.setAnnotation(ax, "a) ICE0 liquid water path", xPosition=0.2, yPosition= lwpYlimit*yPositionFrac)
# figB
ax = fig.getAxes(2)
for k in simulationList.getIce1Simulations():
Plot.getTimeseries(ax,
self.simulationCollection[k],
"lwp_bar", conversionFactor=1000.)
PlotTweak.setAnnotation(ax, "b) ICE1 liquid water path", xPosition=0.2, yPosition= lwpYlimit*yPositionFrac)
# figC
ax = fig.getAxes(3)
for k in simulationList.getIce1Simulations():
Plot.getTimeseries(ax,
self.simulationCollection[k],
"iwp_bar", conversionFactor=1000.)
PlotTweak.setAnnotation(ax, "c) ICE1 ice water path", xPosition=0.2, yPosition= iwpYlimit*yPositionFrac)
# figD
ax = fig.getAxes(4)
for k in simulationList.getIce4Simulations():
Plot.getTimeseries(ax,
self.simulationCollection[k],
"lwp_bar", conversionFactor=1000.)
PlotTweak.setAnnotation(ax, "d) ICE4 liquid water path", xPosition=0.2, yPosition= lwpYlimit*yPositionFrac)
# figE
ax = fig.getAxes(5)
for k in simulationList.getIce4Simulations():
Plot.getTimeseries(ax,
self.simulationCollection[k],
"iwp_bar", conversionFactor=1000.)
PlotTweak.setAnnotation(ax, "e) ICE4 ice water path", xPosition=0.2, yPosition= iwpYlimit*yPositionFrac)
for i in [0,2,4]: #LWP figures
ax = fig.getAxes(i)
end = lwpYlimit
PlotTweak.setYaxisLabel(ax,"LWP", "g\ m^{-2}")
PlotTweak.setYLim(ax, end = end)
ticks = PlotTweak.setYticks(ax, end = end, interval = 2)
shownLabelsBoolean = PlotTweak.setYLabels(ax, ticks, end = end, interval = 10)
PlotTweak.setYTickSizes(ax, shownLabelsBoolean)
for i in [1,3,5]: #IWP figures
ax = fig.getAxes(i)
PlotTweak.setYaxisLabel(ax,"IWP", "g\ m^{-2}")
end = iwpYlimit
PlotTweak.setYLim(ax, end = end)
ticks = PlotTweak.setYticks(ax, end = end, interval = 1)
shownLabelsBoolean = PlotTweak.setYLabels(ax, ticks, end = end, interval = 3)
PlotTweak.setYTickSizes(ax, shownLabelsBoolean)
for i in [0,2,3,4,5]: #all timeseries figures
ax = fig.getAxes(i)
end = 8
PlotTweak.setXLim(ax, end = end)
Plot.getVerticalLine(ax, 2)
if i in [4,5]:
PlotTweak.setXaxisLabel(ax,"Time", "h")
else:
PlotTweak.setXaxisLabel(ax,"")
PlotTweak.hideXTickLabels(ax)
ticks = PlotTweak.setXticks(ax, end = end, interval = 0.5, integer=False)
ticks = [int(k) for k in ticks]
shownLabelsBoolean = PlotTweak.setXLabels(ax, ticks, end = end, interval = 2)
PlotTweak.setXTickSizes(ax, shownLabelsBoolean)
# empty space
ax = fig.getAxes(1)
ax.axis("off")
legend_elements = [Patch(facecolor=self.simulationCollection["ICE0_8h"].getColor(),
label='UCLALES-SALSA'),
Patch(facecolor=self.simulationCollection["SAM-bin_ice0"].getColor(),
label='BIN'),
Patch(facecolor=self.simulationCollection["COSMO_ice0"].getColor(),
label='BULK')]
ax.legend(handles=legend_elements, loc='center', frameon = True, framealpha = 1.0)
fig.save()
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 figure4(self):
fig = Figure(self.figurefolder,"figure4", ncols = 2, nrows = 3, left=0.15, wspace=0.4)
simulationList = ["Prognostic_48h", "ICE4_24h"]
for k in simulationList:
self.simulationCollection[k].getTSDataset()
self.simulationCollection[k].getNCDataset()
self.simulationCollection[k].setTimeCoordToHours()
lwpYlimit = 60
iwpYlimit = 21
xPosition = 0.52
yPositionFrac = 0.91
# figA
ax = fig.getAxes(0)
for k in simulationList:
Plot.getTimeseries(ax,
self.simulationCollection[k],
"lwp_bar", conversionFactor=1000.)
end = lwpYlimit
PlotTweak.setAnnotation(ax, "a) Liquid water path", xPosition=xPosition, yPosition= yPositionFrac*end)
PlotTweak.setYaxisLabel(ax,"LWP", "g\ m^{-2}")
PlotTweak.setYLim(ax, end = end)
PlotTweak.setYLim(ax, end = end)
ticks = PlotTweak.setYticks(ax, end = end, interval = 2)
shownLabelsBoolean = PlotTweak.setYLabels(ax, ticks, end = end, interval = 10)
PlotTweak.setYTickSizes(ax, shownLabelsBoolean)
# figB
ax = fig.getAxes(1)
for k in simulationList:
Plot.getTimeseries(ax,
self.simulationCollection[k],
"iwp_bar", conversionFactor=1000.)
end = iwpYlimit
PlotTweak.setAnnotation(ax, "b) Ice water path", xPosition=xPosition, yPosition= yPositionFrac*end)
PlotTweak.setYaxisLabel(ax,"IWP", "g\ m^{-2}")
PlotTweak.setYLim(ax, end = end)
end = iwpYlimit
PlotTweak.setYLim(ax, end = end)
ticks = PlotTweak.setYticks(ax, end = end, interval = 1)
shownLabelsBoolean = PlotTweak.setYLabels(ax, ticks, end = end, interval = 3)
PlotTweak.setYTickSizes(ax, shownLabelsBoolean)
# figC
ax = fig.getAxes(2)
for k in simulationList:
self.simulationCollection[k].getNCDataset()["Ni_ii_vol"].plot(ax = ax,
color = self.simulationCollection[k].getColor(),
label = self.simulationCollection[k].getLabel(),
linewidth = self.simulationCollection[k].getLineWidth())
end = 5
PlotTweak.setAnnotation(ax, "c) Ice number \nconcentration", xPosition=xPosition, yPosition= 4)
PlotTweak.setYaxisLabel(ax,"N_{i}", "L^{-1}")
PlotTweak.setYLim(ax, end = end)
ticks = PlotTweak.setYticks(ax, end = end, interval = 0.2, integer=False)
shownLabelsBoolean = PlotTweak.setYLabels(ax, ticks, end = end, interval = 1)
PlotTweak.setYTickSizes(ax, shownLabelsBoolean)
# figD
ax = fig.getAxes(3)
for k in simulationList:
Plot.getTimeseries(ax,
self.simulationCollection[k],
"Nc_ic", conversionFactor=1e-6)
end = 170
PlotTweak.setAnnotation(ax, "d) In-cloud CDNC", xPosition=xPosition, yPosition= yPositionFrac*end)
PlotTweak.setYaxisLabel(ax,"CDNC", "mg^{-1}")
PlotTweak.setYLim(ax, end = end)
ticks = PlotTweak.setYticks(ax, end = end, interval = 10)
shownLabelsBoolean = PlotTweak.setYLabels(ax, ticks, end = end, interval = 50)
PlotTweak.setYTickSizes(ax, shownLabelsBoolean)
# figE
ax = fig.getAxes(4)
for k in simulationList:
for muuttuja in ["zb", "zc"]:
self.simulationCollection[k].getTSDataset()[muuttuja].where(self.simulationCollection[k].getTSDataset()[muuttuja] > 0).plot(ax = ax,
color = self.simulationCollection[k].getColor(),
label = self.simulationCollection[k].getLabel(),
linewidth = self.simulationCollection[k].getLineWidth())
end = 1000
PlotTweak.setAnnotation(ax, "e) Cloud top and base", xPosition=xPosition, yPosition= yPositionFrac*end)
PlotTweak.setYaxisLabel(ax,"Height", "m")
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(5):
ax = fig.getAxes(i)
end = 32
PlotTweak.setXLim(ax, end = end)
Plot.getVerticalLine(ax, 2)
Plot.getVerticalLine(ax, 24)
if i in [3,4]:
PlotTweak.setXaxisLabel(ax,"Time", "h")
else:
PlotTweak.setXaxisLabel(ax,"")
PlotTweak.hideXTickLabels(ax)
ticks = PlotTweak.setXticks(ax, end = end, interval = 0.5)
shownLabelsBoolean = PlotTweak.setXLabels(ax, ticks, end = end, interval = 4)
PlotTweak.setXTickSizes(ax, shownLabelsBoolean)
# empty space
ax = fig.getAxes(5)
ax.axis("off")
legend_elements = [Patch(facecolor=self.simulationCollection["Prognostic_48h"].getColor(),
label='Prognostic ice'),
Patch(facecolor=self.simulationCollection["ICE4_24h"].getColor(),
label='ICE4')]
ax.legend(handles=legend_elements, loc='center', frameon = True, framealpha = 1.0)
fig.save()
