sharey=True)
# plot timeseries with unit conversion
cloudTopOutliersColors = Colorful.getIndyColorList(
len(cloudTopOutliers))
for ind, case in enumerate(caseCollection):
for emulInd, emul in enumerate(cloudTopOutliers):
try:
simulation = simulationCollection[case][emul]
except KeyError:
continue
dataset = simulation.getTSDataset()
muuttuja = dataset["zc"][1:] / (
simulationDataFrames[case].loc[emul]["pblh_m"])
muuttuja.plot(
ax=fig2.getAxes(True)[ind],
color=cloudTopOutliersColors[emulInd],
label=simulationCollection[case][emul].getLabel())
xmax = 3.5
ymax = 2.5
for ind, case in enumerate(caseCollection):
PlotTweak.setAnnotation(fig2.getAxes(True)[ind],
annotationCollection[case],
xPosition=1.5,
yPosition=ymax - 0.25)
PlotTweak.setXLim(fig2.getAxes(True)[ind], 0, xmax)
PlotTweak.setYLim(fig2.getAxes(True)[ind], 0, ymax)
#fig2.getAxes(True)[ind].plot( [0,xmax], [0, ymax], 'k-', alpha=0.75, zorder=0)
def plot4Sets(caseCollection,
simulationCollection,
annotationCollection,
simulationDataFrames,
figurefolder,
figurename,
ncVariable,
designVariable,
conversionNC=1.0,
conversionDesign=1.0,
xmax=1000,
ymax=1000,
xAxisLabel=None,
xAxisUnit=None,
yAxisLabel=None,
yAxisUnit=None,
keisseja=10000,
yPositionCorrection=100,
outlierParameter=0.2):
relativeChangeDict = Data.emptyDictionaryWithKeys(caseCollection)
print(" ")
print(figurename)
# create figure object
fig = Figure(figurefolder,
figurename,
ncols=2,
nrows=2,
sharex=True,
sharey=True)
# plot timeseries with unit conversion
maks = 0
mini = 0
for ind, case in enumerate(caseCollection):
for emul in list(simulationCollection[case])[:keisseja]:
dataset = simulationCollection[case][emul].getTSDataset()
muuttuja = dataset[ncVariable]
alku = simulationDataFrames[case].loc[emul][
designVariable] * conversionDesign
loppu = muuttuja.sel(
time=slice(2.5, 3.5)).mean().values * conversionNC
relChangeParam = loppu / alku
relativeChangeDict[case][emul] = relChangeParam
if relChangeParam > 1 + outlierParameter:
color = Colorful.getDistinctColorList("red")
zorderParam = 10
elif relChangeParam < 1 - outlierParameter:
color = Colorful.getDistinctColorList("blue")
zorderParam = 9
else:
color = "white"
zorderParam = 6
maks = max(relChangeParam, maks)
mini = min(relChangeParam, mini)
fig.getAxes(True)[ind].plot(alku,
loppu,
marker="o",
markerfacecolor=color,
markeredgecolor="black",
markeredgewidth=0.2,
markersize=6,
alpha=0.5,
zorder=zorderParam)
def figureUpdraftTimeseries(self):
packing = 7
yend = 1.5
aeroAnalysis = SimulationDataAnalysis(self.simulation, "S_Nabb",
"AeroB")
cloudAnalysis = SimulationDataAnalysis(self.simulation, "S_Ncbb",
"CloudB")
iceAnalysis = SimulationDataAnalysis(self.simulation, "S_Nibb", "IceB")
aeroAnalysis.renameAUXCoordSizeBinB()
cloudAnalysis.renameAUXCoordSizeBinB()
iceAnalysis.renameAUXCoordSizeBinB()
if packing < 7:
aeroAnalysis.packFilteredAUXVariablewithSizeBinCoords(packing)
cloudAnalysis.packFilteredAUXVariablewithSizeBinCoords(packing)
iceAnalysis.packFilteredAUXVariablewithSizeBinCoords(packing)
aero = aeroAnalysis.simulation.AUXDatasets["AeroB"]["S_Nabb"]
cloud = cloudAnalysis.simulation.AUXDatasets["CloudB"]["S_Ncbb"]
ice = iceAnalysis.simulation.AUXDatasets["IceB"]["S_Nibb"]
updraft = self.simulation.AUXDatasets["Updraft"]["w"]
updraft = updraft.rename({"ym": "yt"})
updraft.yt.values = updraft.yt.values - 25.
dataset = xarray.merge([aero, cloud, ice, updraft])
aeroColor = Colorful.getDistinctColorList("red")
cloudColor = Colorful.getDistinctColorList("navy")
iceColor = Colorful.getDistinctColorList("cyan")
yticks = numpy.arange(0, 3.5 + 0.1, 0.5)
heightList = {
0: "Surface",
200: "",
400: "",
355: "Always below cloud base",
705: "Always in-cloud",
785: "At the beginning in-cloud, At end above cloud top",
850: "Always above cloud top"
}
for height in heightList:
realHeight = dataset.zt.sel(zt=height, method="nearest").item()
fig = Figure(self.figurefolder,
"figureUpdraft_z_" + "{0:.0f}".format(realHeight),
ncols=2,
nrows=packing,
figsize=[8, 16],
wspace=0.06,
left=0.05,
bottom=0.03,
top=0.96,
right=0.98)
print("figsize", fig.getFigSize())
datasetHeight = dataset.sel(zt=height, method="nearest")
for draftIndex in range(2):
if draftIndex == 0:
dataDraft = datasetHeight.where(
datasetHeight["w"] > self.draftLimit, drop=True)
draftType = "Up-draft"
else:
dataDraft = datasetHeight.where(
datasetHeight["w"] < -self.draftLimit, drop=True)
draftType = "Down-draft"
for bini in range(packing):
print("")
print("height", realHeight, draftType, "bini", bini)
axIndex = bini * 2 + draftIndex
ax = fig.getAxes(axIndex)
if dataDraft["w"].size == 0:
ax.axis("off")
continue
aeroHeight = dataDraft["S_Nabb"].mean(dim=["xt", "yt"],
skipna=True)
cloudHeight = dataDraft["S_Ncbb"].mean(dim=["xt", "yt"],
skipna=True)
iceHeight = dataDraft["S_Nibb"].mean(dim=["xt", "yt"],
skipna=True)
aeroBin = aeroHeight[:, bini]
cloudBin = cloudHeight[:, bini]
iceBin = iceHeight[:, bini]
totalBin = aeroBin + cloudBin + iceBin
aeroFrac = aeroBin / totalBin
cloudFrac = cloudBin / totalBin
iceFrac = iceBin / totalBin
pointZero = totalBin.sel(time=self.xstart,
method="nearest")
pointEnd = totalBin.sel(time=self.xend,
method="nearest").values
totalBinRelative = totalBin / pointZero
aeroFrac.plot(ax=ax, color=aeroColor)
cloudFrac.plot(ax=ax, color=cloudColor)
iceFrac.plot(ax=ax, color=iceColor)
totalBinRelative.plot(ax=ax, color="black")
bininame = str(bini + 1)
if True:
label = " ".join([
draftType, "Bin", bininame + ",", "Total",
r"$N_0$",
str(int(pointZero)) + ",", "\nMin", r"$N$",
str(int(pointEnd)), "$(kg^{-1})$"
])
facecolor = "black"
PlotTweak.setArtist(ax, {label: facecolor},
loc=(0.01, 0.74),
framealpha=0.8)
if axIndex == 0:
collectionOfLabelsColors = {
"Aerosol": aeroColor,
"Cloud": cloudColor,
"Ice": iceColor
}
PlotTweak.setArtist(ax,
collectionOfLabelsColors,
ncol=3,
loc=(0.75, 1.12))
##############
ax.set_title("")
PlotTweak.setXLim(ax, start=self.xstart, end=self.xend)
PlotTweak.setYLim(ax, end=yend)
PlotTweak.setYticks(ax, yticks)
yShownLabelsBoolean = PlotTweak.setYLabels(ax,
yticks,
end=3,
interval=1,
integer=True)
PlotTweak.setYTickSizes(ax, yShownLabelsBoolean)
xticks = PlotTweak.setXticks(ax,
start=self.xstart,
end=self.xend,
interval=1)
shownLabelsBoolean = PlotTweak.setXLabels(ax,
xticks,
end=self.xend,
interval=4)
PlotTweak.setXTickSizes(ax, shownLabelsBoolean)
PlotTweak.setYaxisLabel(ax, "")
if axIndex in [12, 13]:
PlotTweak.setXaxisLabel(ax, "Time", "h")
else:
PlotTweak.setXaxisLabel(ax, "")
PlotTweak.hideXTickLabels(ax)
if draftIndex == 1:
PlotTweak.hideYTickLabels(ax)
if axIndex == 0:
ax.text(0.5 * self.xend,
yticks[-1] + yticks[1] * 0.25,
PlotTweak.getUnitLabel(
"Height\ " + f"{realHeight:.0f}", "m") +
" " + heightList[height] + " limit: " +
f"{self.draftLimit:.0e}",
size=8)
# end bini for loop
# end draftIndex for loop
fig.save()
figObject.simulationCollection[k].setZorder(3)
for k in simulationList.getUCLALESSALSASimulations():
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],
def figureUpdraftProfile(self):
packing = 7
aeroAnalysis = SimulationDataAnalysis(self.simulation, "S_Nabb",
"AeroB")
cloudAnalysis = SimulationDataAnalysis(self.simulation, "S_Ncbb",
"CloudB")
iceAnalysis = SimulationDataAnalysis(self.simulation, "S_Nibb", "IceB")
aeroAnalysis.renameAUXCoordSizeBinB()
cloudAnalysis.renameAUXCoordSizeBinB()
iceAnalysis.renameAUXCoordSizeBinB()
if packing < 7:
aeroAnalysis.packFilteredAUXVariablewithSizeBinCoords(packing)
cloudAnalysis.packFilteredAUXVariablewithSizeBinCoords(packing)
iceAnalysis.packFilteredAUXVariablewithSizeBinCoords(packing)
aero = aeroAnalysis.simulation.AUXDatasets["AeroB"]["S_Nabb"]
cloud = cloudAnalysis.simulation.AUXDatasets["CloudB"]["S_Ncbb"]
ice = iceAnalysis.simulation.AUXDatasets["IceB"]["S_Nibb"]
updraft = self.simulation.AUXDatasets["Updraft"]["w"]
updraft = updraft.rename({"ym": "yt"})
if xarray.__version__ == "0.14.1":
updraft.yt.values = updraft.yt.values - 25.
else:
updraft = updraft.assign_coords(yt=(updraft.yt.values - 25.))
dataset = xarray.merge([aero, cloud, ice, updraft])
aeroColor = Colorful.getDistinctColorList("red")
cloudColor = Colorful.getDistinctColorList("navy")
iceColor = Colorful.getDistinctColorList("cyan")
totalColor = Colorful.getDistinctColorList("green")
xaxisend = 1.0
ystart = 400.
yend = 850.
loopedBins = range(packing)[1:3]
fig = Figure(self.figurefolder,
"figure8",
figsize=[4.724409448818897, 3],
ncols=2,
nrows=len(loopedBins),
wspace=0.06,
left=0.12,
bottom=0.12,
top=0.85,
right=0.98)
print("figsize", fig.getFigSize())
timeBegin = dataset.time.sel(time=self.xstart, method="nearest").item()
timeEnd = dataset.time.sel(time=self.xend, method="nearest").item()
datasetTime = dataset.sel(time=slice(timeBegin, timeEnd))
subFigureName = [chr(ord('a') + i) for i in range(packing * 2)]
for draftIndex in range(2):
if draftIndex == 0:
dataDraft = datasetTime.where(
datasetTime["w"] > self.draftLimit, drop=True)
draftType = "Up-draft"
else:
dataDraft = datasetTime.where(
datasetTime["w"] < -self.draftLimit, drop=True)
draftType = "Down-draft"
biniCounter = 0
for bini in loopedBins:
print("")
print(draftType, "timeBegin", timeBegin, "timeEnd", timeEnd)
axIndex = biniCounter * 2 + draftIndex
ax = fig.getAxes(axIndex)
if dataDraft["w"].size == 0:
ax.axis("off")
continue
aeroHeight = dataDraft["S_Nabb"].mean(dim=["xt", "yt", "time"],
skipna=True)
cloudHeight = dataDraft["S_Ncbb"].mean(
dim=["xt", "yt", "time"], skipna=True)
iceHeight = dataDraft["S_Nibb"].mean(dim=["xt", "yt", "time"],
skipna=True)
aeroBin = aeroHeight[bini, :]
cloudBin = cloudHeight[bini, :]
iceBin = iceHeight[bini, :]
totalBin = aeroBin + cloudBin + iceBin
aeroFrac = aeroBin / totalBin
cloudFrac = cloudBin / totalBin
iceFrac = iceBin / totalBin
pointMax = totalBin.max()
totalBinRelative = totalBin / pointMax.item()
totalBinRelative.plot(ax=ax, color=totalColor, y="zt")
cloudFrac.plot(ax=ax, color=cloudColor, y="zt")
aeroFrac.plot(ax=ax, color=aeroColor, y="zt")
iceFrac.plot(ax=ax, color=iceColor, y="zt")
if packing < 7:
if bini == (packing - 1):
bininame = str(bini + 1) + " - 7"
else:
bininame = str(bini + 1)
else:
bininame = str(bini + 1)
##############
ax.set_title("")
PlotTweak.setYLim(ax, start=ystart, end=yend)
yticks = PlotTweak.setYticks(ax,
start=ystart,
end=yend,
interval=50)
shownYLabelsBoolean = PlotTweak.setYLabels(ax,
yticks,
end=yend,
interval=100,
integer=False)
PlotTweak.setYTickSizes(ax, shownYLabelsBoolean)
PlotTweak.setXLim(ax, end=xaxisend)
xticks = PlotTweak.setXticks(ax,
end=xaxisend,
interval=0.1,
integer=False)
xTickLabels = copy.deepcopy(xticks)
for xtickInd, xtickValue in enumerate(xTickLabels):
if (xtickInd == 0) or (xtickValue == xTickLabels[-1]):
xTickLabels[xtickInd] = f"{xtickValue:.0f}"
else:
xTickLabels[xtickInd] = f"{xtickValue:.1f}"
xShownLabelsBoolean = PlotTweak.setXLabels(ax,
xticks,
end=xaxisend,
interval=0.2,
integer=False)
ax.set_xticklabels(xTickLabels)
PlotTweak.setXTickSizes(ax, xShownLabelsBoolean)
xlimits = ax.get_xlim()
ylimits = ax.get_ylim()
PlotTweak.setXaxisLabel(ax, "")
PlotTweak.setYaxisLabel(ax, "")
print("bini", biniCounter, "loopedBins -1",
len(loopedBins) - 1)
if (biniCounter != len(loopedBins) - 1):
PlotTweak.hideXTickLabels(ax)
if draftIndex == 0:
PlotTweak.setYaxisLabel(ax, "Height", "m")
if draftIndex == 1:
PlotTweak.hideYTickLabels(ax)
if axIndex == 0:
ax.text( 0.05*(xlimits[1]-xlimits[0]), (ylimits[1]-ylimits[0])*0.05+ylimits[1],
"Mean profile from " + PlotTweak.getUnitLabel(f"t_0={self.xstart}", "h")+\
" to " + PlotTweak.getUnitLabel(f"t_1={self.xend}", "h") +\
" limit: " + PlotTweak.getUnitLabel(f"{self.draftLimit:.1f}", "m\ s^{-1}")
, size=8)
if True:
label = " ".join([
subFigureName[axIndex] + ")", draftType, "Bin",
bininame
])
PlotTweak.setAnnotation(
ax,
label,
xPosition=0.05 * (xlimits[1] - xlimits[0]) +
xlimits[0],
yPosition=0.1 * (ylimits[1] - ylimits[0]) + ylimits[0])
if axIndex == 0:
collectionOfLabelsColors = {
"Aerosol": aeroColor,
"Cloud": cloudColor,
"Ice": iceColor,
"Total": totalColor
}
PlotTweak.setArtist(ax,
collectionOfLabelsColors,
ncol=4,
loc=(0.10, 1.19))
biniCounter += 1
# end bini for loop
# end draftIndex for loop
fig.save()
def figureUpdraftProfileLog(self):
packing = 4
aeroAnalysis = SimulationDataAnalysis(self.simulation, "S_Nabb",
"AeroB")
cloudAnalysis = SimulationDataAnalysis(self.simulation, "S_Ncbb",
"CloudB")
iceAnalysis = SimulationDataAnalysis(self.simulation, "S_Nibb", "IceB")
aeroAnalysis.renameAUXCoordSizeBinB()
cloudAnalysis.renameAUXCoordSizeBinB()
iceAnalysis.renameAUXCoordSizeBinB()
if packing < 7:
aeroAnalysis.packFilteredAUXVariablewithSizeBinCoords(packing)
cloudAnalysis.packFilteredAUXVariablewithSizeBinCoords(packing)
iceAnalysis.packFilteredAUXVariablewithSizeBinCoords(packing)
aero = aeroAnalysis.simulation.AUXDatasets["AeroB"]["S_Nabb"]
cloud = cloudAnalysis.simulation.AUXDatasets["CloudB"]["S_Ncbb"]
ice = iceAnalysis.simulation.AUXDatasets["IceB"]["S_Nibb"]
updraft = self.simulation.AUXDatasets["Updraft"]["w"]
updraft = updraft.rename({"ym": "yt"})
updraft.yt.values = updraft.yt.values - 25.
dataset = xarray.merge([aero, cloud, ice, updraft])
aeroColor = Colorful.getDistinctColorList("red")
cloudColor = Colorful.getDistinctColorList("navy")
iceColor = Colorful.getDistinctColorList("cyan")
ystart = 400.
yend = 850.
fig = Figure(self.figurefolder,
"figureProfileDraftsLog",
figsize=[4.724409448818897, 2.5],
ncols=2,
nrows=1,
wspace=0.06,
left=0.12,
bottom=0.12,
top=0.86,
right=0.98)
print("figsize", fig.getFigSize())
timeBegin = dataset.time.sel(time=self.xstart, method="nearest").item()
timeEnd = dataset.time.sel(time=self.xend, method="nearest").item()
datasetTime = dataset.sel(time=slice(timeBegin, timeEnd))
subFigureName = [chr(ord('a') + i) for i in range(packing * 2)]
loopedBins = range(packing)[1:2]
for draftIndex in range(2):
if draftIndex == 0:
dataDraft = datasetTime.where(
datasetTime["w"] > self.draftLimit, drop=True)
draftType = "Up-draft"
else:
dataDraft = datasetTime.where(
datasetTime["w"] < -self.draftLimit, drop=True)
draftType = "Down-draft"
biniCounter = 0
for bini in loopedBins:
print("")
print(draftType, "timeBegin", timeBegin, "timeEnd", timeEnd)
axIndex = biniCounter * 2 + draftIndex
biniCounter += 1
ax = fig.getAxes(axIndex)
if dataDraft["w"].size == 0:
ax.axis("off")
continue
aeroHeight = dataDraft["S_Nabb"].mean(dim=["xt", "yt", "time"],
skipna=True)
cloudHeight = dataDraft["S_Ncbb"].mean(
dim=["xt", "yt", "time"], skipna=True)
iceHeight = dataDraft["S_Nibb"].mean(dim=["xt", "yt", "time"],
skipna=True)
aeroBin = aeroHeight[bini, :]
cloudBin = cloudHeight[bini, :]
iceBin = iceHeight[bini, :]
aeroFrac = numpy.log10(aeroBin)
cloudFrac = numpy.log10(cloudBin)
iceFrac = numpy.log10(iceBin)
aeroFrac.plot(ax=ax, color=aeroColor, y="zt")
cloudFrac.plot(ax=ax, color=cloudColor, y="zt")
iceFrac.plot(ax=ax, color=iceColor, y="zt")
if packing < 7:
if bini == (packing - 1):
bininame = str(bini + 1) + " - 7"
else:
bininame = str(bini + 1)
else:
bininame = str(bini + 1)
##############
ax.set_title("")
PlotTweak.setYLim(ax, start=ystart, end=yend)
yticks = PlotTweak.setYticks(ax,
start=ystart,
end=yend,
interval=50)
shownYLabelsBoolean = PlotTweak.setYLabels(ax,
yticks,
end=yend,
interval=100,
integer=False)
PlotTweak.setYTickSizes(ax, shownYLabelsBoolean)
xlimits = ax.get_xlim()
ylimits = ax.get_ylim()
print("limits", xlimits, ylimits)
PlotTweak.setXaxisLabel(ax, "")
PlotTweak.setYaxisLabel(ax, "")
if draftIndex == 0:
PlotTweak.setYaxisLabel(ax, "Height", "m")
if draftIndex == 1:
PlotTweak.hideYTickLabels(ax)
if axIndex == 0:
ax.text( 0.1*(xlimits[1]-xlimits[0])+xlimits[0], (ylimits[1]-ylimits[0])*0.05+ylimits[1],
"Mean profile from " + PlotTweak.getUnitLabel(f"t_0={self.xstart}", "h")+\
" to " + PlotTweak.getUnitLabel(f"t_1={self.xend}", "h") +\
" limit: " + f"{self.draftLimit:.0e}" , size=8)
if True:
label = " ".join([
subFigureName[axIndex] + ")", draftType, "Bin",
bininame
])
PlotTweak.setAnnotation(
ax,
label,
xPosition=0.08 * (xlimits[1] - xlimits[0]) +
xlimits[0],
yPosition=0.08 * (ylimits[1] - ylimits[0]) +
ylimits[0])
if axIndex == 0:
collectionOfLabelsColors = {
"Aerosol": aeroColor,
"Cloud": cloudColor,
"Ice": iceColor
}
PlotTweak.setArtist(ax,
collectionOfLabelsColors,
ncol=3,
loc=(0.15, 1.19))
# end bini for loop
# end draftIndex for loop
fig.save()
def figureProfileExample(self):
fig = Figure(self.figurefolder,
"figureProfileExample",
figsize=[4.724409448818897, 4],
ncols=2,
nrows=1,
wspace=0.15,
bottom=0.13,
left=0.14)
print(fig.getFigSize())
colorList = [
Colorful.getDistinctColorList("red"),
Colorful.getDistinctColorList("blue")
]
variables = ["temperature", "water"]
tempRef = None
for ind, temp in enumerate(self.soundIN["temperature"].values):
if tempRef is None:
tempRef = temp
else:
if numpy.abs(tempRef - temp) > numpy.finfo(float).eps * 10:
pblhIND = ind - 1
break
pblh = self.soundIN["height"].iloc[pblhIND]
tpot_inv = self.design["tpot_inv"].iloc[self.designInd]
tpot_pbl = self.design["tpot_pbl"].iloc[self.designInd]
r_t = self.soundIN["water"].max()
q_inv = self.design["q_inv"].iloc[self.designInd]
t_grad = 0.3
invThi = tpot_inv / t_grad
print("pblh", pblh)
maxheight = Data.roundUp(self.soundIN["height"].max(), 100)
minTemp = Data.roundDown(self.soundIN["temperature"].min(), 1)
maxTemp = Data.roundUp(self.soundIN["temperature"].max(), 1)
minWater = 0
maxWaterAxes = Data.roundUp(self.soundIN["water"].max(), 1)
print("maxWater", self.soundIN["water"].max())
for ind in range(2):
ax = fig.getAxes(ind)
self.soundIN.plot(ax=ax,
x=variables[ind],
y="height",
color=colorList[ind],
legend=False,
linewidth=2)
ax.set_ylim([0, maxheight])
Plot.getHorizontalLine(ax, pblh)
if ind == 0:
PlotTweak.setXaxisLabel(ax, "\\theta_{L}", "K")
PlotTweak.setYaxisLabel(ax, "Altitude", "m")
xticks = PlotTweak.setXticks(ax,
start=minTemp,
end=maxTemp,
interval=1,
integer=True)
xShownLabelsBoolean = PlotTweak.setXLabels(ax,
xticks,
start=minTemp,
end=maxTemp,
interval=5,
integer=True)
PlotTweak.setXTickSizes(ax, xShownLabelsBoolean)
ax.set_xlim([minTemp, maxTemp])
xmin = ax.get_xlim()[0]
xmax = ax.get_xlim()[1]
ymin = ax.get_ylim()[0]
ymax = ax.get_ylim()[1]
k_rate = (ymax - ymin) / (xmax - xmin)
xPoint = (xmax - xmin) * 0.2 + xmin
yPoint = k_rate * (xPoint - tpot_pbl)
PlotTweak.setAnnotation(ax,
"(a) Temperature profile",
xPosition=(xmax - xmin) * 0.05 + xmin,
yPosition=(ymax - ymin) * 0.95 + ymin)
ax.axvline(tpot_pbl + tpot_inv,
color="k",
linestyle="--",
ymax=(pblh + invThi) / ymax)
# ax.arrow(xPoint, yPoint, tpot_pbl-xPoint, 0-yPoint,
# facecolor='black', shape = "full", linewidth = param, head_length = param*1.5*3., head_width = 3.*param, overhang = 0.1, head_starts_at_zero = True, length_includes_head = True)
ax.annotate(PlotTweak.getMathLabel("tpot_pbl"),
xy=(tpot_pbl, 0),
xytext=(xPoint, yPoint),
arrowprops=dict(facecolor='black',
arrowstyle="->",
linewidth=1.5),
horizontalalignment='left',
verticalalignment='bottom')
#ax.text((xPoint-tpot_pbl)*0.6 + tpot_pbl, (yPoint- ymin)*0.3 + ymin, PlotTweak.getMathLabel("tpot_pbl"))
arrowParam = 0.3
pblhArrowX = (xmax -
(tpot_pbl + tpot_inv)) * arrowParam + (tpot_pbl +
tpot_inv)
pblhArrowXText = (xmax -
(tpot_pbl + tpot_inv)) * arrowParam * 1.5 + (
tpot_pbl + tpot_inv)
ax.annotate("",
xy=(pblhArrowX, pblh),
xytext=(pblhArrowX, 0),
arrowprops=dict(arrowstyle="<->",
facecolor='black',
linewidth=1.5))
ax.text(pblhArrowXText, pblh * 0.43, "PBLH", rotation=90)
ax.text(tpot_pbl + tpot_inv * 0.40, pblh * 0.43,
PlotTweak.getMathLabel("tpot_inv"))
ax.annotate("",
xy=(tpot_pbl, pblh * 0.5),
xytext=(tpot_pbl + tpot_inv, pblh * 0.5),
arrowprops=dict(arrowstyle="<->",
facecolor='black',
linewidth=1.5))
else:
PlotTweak.setXaxisLabel(ax, "r_t", "g\ kg^{-1}")
PlotTweak.hideYTickLabels(ax)
xticks = numpy.arange(minWater, maxWaterAxes + 0.001, 1)
xlabels = [f"{t:.1f}" for t in xticks]
xShowList = Data.getMaskedList(xticks, xticks[0::4])
ax.set_xticks(xticks)
ax.set_xticklabels(xlabels)
PlotTweak.setXTickSizes(ax, xShowList)
PlotTweak.hideLabels(ax.xaxis, xShowList)
ax.set_xlim([minWater, maxWaterAxes])
xmin = ax.get_xlim()[0]
xmax = ax.get_xlim()[1]
ymin = ax.get_ylim()[0]
ymax = ax.get_ylim()[1]
PlotTweak.setAnnotation(ax,
"(b) Humidity profile",
xPosition=(xmax - xmin) * 0.17 + xmin,
yPosition=(ymax - ymin) * 0.95 + ymin)
ax.axvline(r_t - q_inv,
color="k",
linestyle="--",
ymax=(pblh + invThi) / ymax)
k_rate = (ymax - ymin) / (xmin - xmax)
xPoint = self.soundIN["water"].max() * .8
yPoint = k_rate * (xPoint - self.soundIN["water"].max())
ax.annotate(PlotTweak.getLatexLabel("r_t"),
xy=(self.soundIN["water"].max() * 0.99, 0),
xytext=(xPoint, yPoint),
arrowprops=dict(facecolor='black',
arrowstyle="->",
linewidth=1.5),
horizontalalignment='left',
verticalalignment='bottom')
ax.annotate("",
xy=(r_t - q_inv, pblh * 0.5),
xytext=(r_t, pblh * 0.5),
arrowprops=dict(arrowstyle="<->",
facecolor='black',
linewidth=1.5))
ax.text(r_t - q_inv * 0.60, pblh * 0.43,
PlotTweak.getMathLabel("q_inv"))
yticks = PlotTweak.setYticks(ax,
start=0,
end=maxheight,
interval=100,
integer=True)
yShownLabelsBoolean = PlotTweak.setYLabels(ax,
yticks,
start=0,
end=maxheight,
interval=500)
PlotTweak.setYTickSizes(ax, yShownLabelsBoolean)
# yTicks = numpy.arange(0, 0.51, 0.1)
# yTickLabels = [f"{t:.1f}" for t in yTicks]
#
# ax.set_yticklabels(yTickLabels)
# ax.set_ylim([0, 0.5])
# PlotTweak.setAnnotation(ax, self.annotationCollection[trainingSet], xPosition=ax.get_xlim()[1]*0.20, yPosition = ax.get_ylim()[1]*0.90)
# PlotTweak.setXaxisLabel(ax,"")
# fig.getAxes(0).legend(handles=PlotTweak.getPatches(legendLabelColors),
# title = "Global variance -based sensitivity for " + PlotTweak.getLatexLabel("w_{pos}", False),
# loc=(-0.2,-2.6),
# ncol = 4,
# fontsize = 8)
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 figure7(self):
fig = Figure(self.figurefolder,"figure7", ncols = 2, nrows = 2, hspace=0.43, bottom = 0.14, left=0.15, top=0.98, wspace = 0.1)
simulation = "Prognostic_48h"
self.simulationCollection[simulation].getPSDataset()
self.simulationCollection[simulation].setTimeCoordToHours()
end = 1000
yPositionFrac = 0.9
xPositionFrac = 0.02
annotation = ["a) Liquid water mixing ratio", "b) Ice mixing ratio", "c) Freezing rate"]
muuttujalista = ["P_rl", "P_ri", "nucl_ni"]
aika = [2,4,16,32]
colorlist = ['#a6cee3','#1f78b4','#b2df8a','#33a02c'] #['#a63603', '#e6550d', '#fd8d3c', '#fdae6b'] #['#1b9e77','#d95f02','#7570b3','#e7298a']
startList = [0, 0, -5]
endList = [0.2, 0.025,2.5]
xPositionList = []
for ind, muuttuja in enumerate(muuttujalista):
ax = fig.getAxes(ind)
data = self.simulationCollection[simulation].getPSDataset()[muuttuja]
xPositionList.append( numpy.abs(startList[ind]-endList[ind])*xPositionFrac + startList[ind])
if muuttuja == "nucl_ni":
data.values = numpy.log10(data.values)
else:
data.values = data.values*1e3
for aikaInd, aikapiste in enumerate(aika):
data.sel(time = aikapiste, method="nearest").plot( y="zt", ax = ax, color = colorlist[aikaInd])
end = 1000
for ind in range(3):
ax = fig.getAxes(ind)
ax.set_title("")
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)
PlotTweak.setAnnotation(ax, annotation[ind], xPosition= xPositionList[ind], yPosition= yPositionFrac*end)
###
ind = 0
ax = fig.getAxes(ind)
start = startList[ind]
end = endList[ind]
PlotTweak.setXLim(ax, start = ind, end = end)
PlotTweak.setXaxisLabel(ax,"", "g\ kg^{-1}")
PlotTweak.setYaxisLabel(ax,"Height", "m")
matplotlib.pyplot.setp(ax.get_xticklabels()[-1], visible=False)
###
ind = 1
ax = fig.getAxes(ind)
start = startList[ind]
end = endList[ind]
PlotTweak.setXLim(ax, start = start, end = end)
PlotTweak.setXaxisLabel(ax,"", "g\ kg^{-1}")
PlotTweak.setYaxisLabel(ax,"")
PlotTweak.hideYTickLabels(ax)
ticks = PlotTweak.setXticks(ax, end = end, interval = 0.005/2, integer=False)
shownLabelsBoolean = PlotTweak.setXLabels(ax, ticks, end = end, interval = 0.005, integer = False)
PlotTweak.setXTickSizes(ax, shownLabelsBoolean)
matplotlib.pyplot.setp(ax.get_xticklabels()[-1], visible=False)
###
ind = 2
ax = fig.getAxes(ind)
start = startList[ind]
end = endList[ind]
PlotTweak.setYaxisLabel(ax,"Height", "m")
PlotTweak.setXaxisLabel(ax,"", "m^{-3}\ s^{-1}")
PlotTweak.setXLim(ax, start = start, end = end)
xticksLog = numpy.arange(start, end + 0.1, 2.5)
xlabelsLog = [r"$10^{" + "{0:.1f}".format(elem) + "}$" for elem in xticksLog]
ax.set_xticks(xticksLog)
ax.set_xticklabels(xlabelsLog)
# empty space
ax = fig.getAxes(3)
ax.axis("off")
legend_elements = [Patch(facecolor=colorlist[0], label='2 (h)'),
Patch(facecolor=colorlist[1], label='4 (h)'),
Patch(facecolor=colorlist[2], label='16 (h)'),
Patch(facecolor=colorlist[3], label='32 (h)')]
ax.legend(handles=legend_elements, loc="center", frameon = True, framealpha = 1.0)
fig.save()
def figure6(self):
packing = 4
xstart = 2.1
xend = 33.0
yend = 1.5
simulation = "Prognostic_48h"
simulCol = self.simulationCollection[simulation]
simulCol.getPSDataset()
simulCol.setTimeCoordToHours()
simulCol.sliceByTimePSDataset(xstart, xend)
fig = Figure(self.figurefolder,"figure6", ncols = 2, nrows = 2,
hspace=0.1, bottom = 0.10, left=0.05, top=0.93, wspace = 0.06, right=0.99, figsize = [12/2.54, 4])
aeroAnalysis = SimulationDataAnalysis( simulCol, "P_Nabb")
cloudAnalysis = SimulationDataAnalysis( simulCol, "P_Ncbb")
iceAnalysis = SimulationDataAnalysis( simulCol, "P_Nibb")
aeroAnalysis.filterPSVariableInCloud()
cloudAnalysis.filterPSVariableInCloud()
iceAnalysis.filterPSVariableInCloud()
aeroAnalysis.renamePSCoordSizeBinB()
cloudAnalysis.renamePSCoordSizeBinB()
iceAnalysis.renamePSCoordSizeBinB()
aeroAnalysis.packFilteredPSVariablewithSizeBinCoords(packing)
cloudAnalysis.packFilteredPSVariablewithSizeBinCoords(packing)
iceAnalysis.packFilteredPSVariablewithSizeBinCoords(packing)
aero = simulCol.getPSDataset()[aeroAnalysis.getFilteredPackedVariableName()]
cloud = simulCol.getPSDataset()[cloudAnalysis.getFilteredPackedVariableName()]
ice = simulCol.getPSDataset()[iceAnalysis.getFilteredPackedVariableName()]
total = aero + cloud + ice
aeroColor = Colorful.getDistinctColorList("red")
cloudColor = Colorful.getDistinctColorList("navy")
iceColor = Colorful.getDistinctColorList("cyan")
totalColor = Colorful.getDistinctColorList("green")
yticks = [0, 0.5, 1, 1.5]
figName = ["a)", "b)", "c)", "d)"]
for bini in range(packing):
ax = fig.getAxes(bini)
aeroBin = aero[:,bini]
cloudBin = cloud[:,bini]
iceBin = ice[:,bini]
totalBin = total[:,bini]
aeroFrac = aeroBin/totalBin
cloudFrac = cloudBin/totalBin
iceFrac = iceBin/totalBin
pointZero = totalBin.sel(time = xstart, method ="nearest")
pointEnd = totalBin.sel(time = xend, method ="nearest").values
totalBinRelative = totalBin / pointZero
totalBinRelative.plot(ax = ax, color = totalColor)
cloudFrac.plot(ax=ax, color = cloudColor)
aeroFrac.plot(ax=ax, color = aeroColor)
iceFrac.plot(ax=ax, color = iceColor)
if bini == (packing - 1):
bininame = str(bini + 1 ) + " - 7"
else:
bininame = str(bini +1)
if True:
label = " ".join([figName[bini], "Bin", bininame + ",", "Total", r"$N_0$", str(int(pointZero)) + ",", "\nMin", r"$N$", str(int(pointEnd)), "$(kg^{-1})$" ])
facecolor = totalColor
PlotTweak.setArtist(ax, {label:facecolor}, loc = (0.01, 0.74), framealpha = 0.8)
if bini == 0:
collectionOfLabelsColors = {"Aerosol": aeroColor, "Cloud": cloudColor, "Ice": iceColor}
PlotTweak.setArtist(ax, collectionOfLabelsColors, ncol = 3, loc = (0.47,1.02))
##############
ax.set_title("")
PlotTweak.setXLim(ax, start = xstart, end = xend)
PlotTweak.setYLim(ax, end = yend)
PlotTweak.setYticks(ax, yticks)
yShownLabelsBoolean = PlotTweak.setYLabels(ax, yticks, end = 1, interval = 1, integer=False)
PlotTweak.setYTickSizes(ax, yShownLabelsBoolean)
xticks = PlotTweak.setXticks(ax, start = xstart, end = xend, interval = 1)
shownLabelsBoolean = PlotTweak.setXLabels(ax, xticks, end = xend, interval = 4)
PlotTweak.setXTickSizes(ax, shownLabelsBoolean)
PlotTweak.setYaxisLabel(ax,"")
if bini in [2,3]:
PlotTweak.setXaxisLabel(ax,"Time", "h")
else:
PlotTweak.setXaxisLabel(ax,"")
PlotTweak.hideXTickLabels(ax)
if bini in [1,3]:
PlotTweak.hideYTickLabels(ax)
###########
fig.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()
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 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()
