def plot(c):
r = resource()
r.trYReverse = c.reverseY
r.trXReverse = c.reverseX
r.trXLog = c.XlogAxis
r.trYLog = c.YlogAxis
#
#Line styles
r.xyLineColors = lineColors
r.xyLineThicknesses = lineThickness
#Plot title
r.tiMainString = c.PlotTitle
#Axis labels (ToDo: add defaults)
#X and Y axis labels
r.tiXAxisString = c.Xlabel
r.tiYAxisString = c.Ylabel
if c.switchXY:
r.tiXAxisString, r.tiYAxisString = r.tiYAxisString, r.tiXAxisString
# Legends, for multicurve plot
legends = []
for id in c.listVariables():
if not id == c.Xid:
if len(c.label[id]) > 0:
legends.append(c.label[id])
else:
legends.append(id)
#ToDo: Add option to skip legends
#Legends are redundant if there's only one curve
if len(legends) > 1:
r.pmLegendDisplayMode = "Always"
r.xyExplicitLegendLabels = legends
#
#Suppress line drawing and just plot symbol for scatter plot curves
r.xyMarkers = plotSymbols
r.xyMarkerColors = lineColors
r.xyMarkerSizeF = .01
r.xyMarkLineModes = []
for id in c.listVariables():
if not id == c.Xid:
if c.scatter[id]:
r.xyMarkLineModes.append('Markers')
else:
r.xyMarkLineModes.append('Lines')
#
w = Ngl.open_wks('x11', 'Climate Workbook')
if c.switchXY:
plot = Ngl.xy(w, c.Y(), c.X(), r)
else:
plot = Ngl.xy(w, c.X(), c.Y(), r)
#
#Now draw the plot
r.nglDraw = True
Ngl.panel(w, [plot], [1, 1], r)
return plotObj(w, plot) #So that user can delete window or save plot
def contour(A, **kwargs):
#The following allows an expert user to pass
#Ngl options directly to the plotter.
#ToDo: Note that
#options explicitly specified later will over-ride
#what the user specified. This should be fixed,
#by checking for things already specified. We should
#also allow for using this resource to specify a color
#map.
if 'resource' in kwargs.keys():
r = kwargs['resource']
else:
r = Dummy()
#
r.cnFillOn = True #Uses color fill
# Set axes if they have been specified
# as keyword arguments
if 'x' in kwargs.keys():
r.sfXArray = kwargs['x']
if 'y' in kwargs.keys():
r.sfYArray = kwargs['y']
#
# Now create the plot
rw = Dummy()
#Set the color map
if 'colors' in kwargs.keys():
if (kwargs['colors'] == 'gray') or (kwargs['colors'] == 'grey'):
#Set the default greyscale
rw.wkColorMap = 'gsdtol'
else:
rw.wkColorMap = kwargs['colors']
else:
#Default rainbow color table
rw.wkColorMap = "temp1"
w = Ngl.open_wks('x11', 'Climate Workbook', rw)
r.nglDraw = False
r.nglFrame = False
plot = Ngl.contour(w, A, r)
#Now draw the plot
r.nglDraw = True
Ngl.panel(w, [plot], [1, 1], r)
return plotObj(w, plot, rw) #So user can delete or save plot
colors00 = Ngl.read_colormap_file("MPL_RdBu")
ncolors00 = colors00.shape[0]
colors0 = colors00[np.linspace(2,
ncolors00 - 1,
int((res.cnMaxLevelValF - res.cnMinLevelValF) /
res.cnLevelSpacingF),
dtype=int), :]
grey_color = np.expand_dims(np.array([0.85, 0.85, 0.85, 1]), axis=0)
colors = np.append(grey_color, colors0[::-1, :], axis=0)
res.cnFillPalette = colors #'BlWhRe' #'MPL_YlOrRd' #-- choose color map
plot = []
title = 'CESM all forcing vs all forcing without ' + sf + ' effect ~C~FWI >= p' + str(
pxx) + ' risk ratio'
for pp in range(5, nperiods, 1):
for vv in range(0, n_vars, 1):
print('period ' + str(pp + 1))
# res.tiMainString = var[vv]+' '+str(pyear0[pp])+'-'+str(pyear1[pp])
res.tiMainString = ''
riskratio_cyc, lon_cyc = Ngl.add_cyclic(
riskratio_ens_agree_masked[vv, pp, :, :], lon)
res.sfXArray = lon_cyc
p = Ngl.contour_map(wks, riskratio_cyc, res)
plot.append(p)
Ngl.panel(wks, plot, [n_vars, 1], pres)
#Ngl.text_ndc(wks,title,0.5,0.92,txres)
Ngl.frame(wks)
Ngl.delete_wks(wks)
def draw_clubb_bgt(ptype, cseason, ncases, cases, casenames, nsite, lats, lons,
filepath, filepathobs, casedir, varis, vname, cscale,
chscale, pname):
# ncases, the number of models
# cases, the name of models
# casename, the name of cases
# filepath, model output filepath
# filepathobs, filepath for observational data
# inptrs = [ncases]
if not os.path.exists(casedir):
os.mkdir(casedir)
_Font = 25
interp = 2
extrap = False
mkres = Ngl.Resources()
mkres.gsMarkerIndex = 2
mkres.gsMarkerColor = "Red"
mkres.gsMarkerSizeF = 15.
infiles = ["" for x in range(ncases)]
ncdfs = ["" for x in range(ncases)]
nregions = nsite
nvaris = len(varis)
plotbgt = ["" for x in range(nsite * ncases)]
alphas = [
'a) ', 'b) ', 'c) ', 'd) ', 'e) ', 'f) ', 'g) ', 'h) ', 'i) ', 'j) ',
'k) ', 'l) ', 'm) ', 'n) ', 'o) ', 'p) ', 'q) ', 'r) ', 's) ', 't) ',
'u) ', 'v) ', 'w) ', 'x) ', 'y) ', 'z) '
]
for ire in range(0, nsite):
for im in range(0, ncases):
if not os.path.exists(casedir + '/' + str(lons[ire]) + 'E_' +
str(lats[ire]) + 'N'):
os.mkdir(casedir + '/' + str(lons[ire]) + 'E_' +
str(lats[ire]) + 'N')
plotname = casedir + '/' + str(lons[ire]) + 'E_' + str(
lats[ire]) + 'N/' + pname + '_' + casenames[im] + "_" + str(
lons[ire]) + "E_" + str(lats[ire]) + "N_" + cseason
plotbgt[im +
ncases * ire] = pname + '_' + casenames[im] + "_" + str(
lons[ire]) + "E_" + str(lats[ire]) + "N_" + cseason
wks = Ngl.open_wks(ptype, plotname)
Ngl.define_colormap(wks, "radar")
plot = []
res = Ngl.Resources()
res.nglDraw = False
res.nglFrame = False
res.nglScale = False
# res.vpWidthF = 0.40 # set width and height
# res.vpHeightF = 0.40
# res.vpXF = 0.04
# res.vpYF = 0.30
res.nglMaximize = False
if (lats[ire] > 0 and lons[ire] < 230):
res.trYMinF = 400.
res.trYMaxF = 1000.
else:
res.trYMinF = 700.
res.trYMaxF = 1000.
res.tiMainFont = _Font
res.tmYLLabelFont = _Font
res.tmXBLabelFont = _Font
res.tiYAxisFont = _Font
res.tiXAxisFont = _Font
res.tmXBLabelFontHeightF = 0.02
res.tmXBLabelFontThicknessF = 1.0
res.xyMarkLineMode = "MarkLines"
res.xyLineThicknesses = [
3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3., 2., 2., 2., 2, 2, 2, 2, 2, 2,
2
]
res.xyLineColors = np.arange(1, 16, 4)
res.xyDashPatterns = np.arange(0, 24, 1)
res.xyMarkers = np.arange(16, 40, 1)
res.xyMarkerSizeF = 0.005
res.xyMarkerColors = np.arange(1, 16, 4)
res.pmLegendDisplayMode = "NEVER"
res.pmLegendSide = "top" # Change location of
res.pmLegendParallelPosF = 0.75 # move units right
res.pmLegendOrthogonalPosF = -0.65 # more neg = down
res.pmLegendWidthF = 0.05 # Change width and
res.pmLegendHeightF = 0.06 # height of legend.
res.lgLabelFontHeightF = 0.03 # change font height
res.lgLabelFontThicknessF = 1.
# res.lgBoxMinorExtentF = 0.5
res.lgPerimOn = False
res.tiYAxisString = "Pressure [hPa]"
res.tmYLLabelFontHeightF = 0.02
res.trYReverse = True
res1 = Ngl.Resources()
res1 = res
pres = Ngl.Resources()
# pres.gsnPaperOrientation= "Landscape"
# pres.wkPaperWidthF = 20 # in inches
# pres.wkPaperHeightF = 28 # in inches
pres.nglMaximize = False
# pres.vpWidthF = 0.40 # set width and height
# pres.vpHeightF = 0.40
pres.nglFrame = False
pres.txFont = _Font
pres.nglPanelYWhiteSpacePercent = 5
pres.nglPanelXWhiteSpacePercent = 3
pres.nglPanelTop = .9
# pres.nglPanelBottom=0.3
# pres.nglPanelLeft= 0.2
# pres.nglPanelRight= 0.95
pres.nglPanelFigureStrings = alphas
pres.nglPanelFigureStringsJust = 'Topleft'
pres.nglPanelFigureStringsFontHeightF = 0.015
for iv in range(0, nvaris):
if (varis[iv] == "rtp2" or varis[iv] == "thlp2"):
budget_ends = ["_ta", "_tp", "_dp1"]
budget_name = [
'~F10~turb adv', '~F10~turb prod', '~F10~dissipation'
]
nterms = len(budget_ends)
if (varis[iv] == "wprtp"):
budget_ends = [
"_bt", "_ma", "_ta", "_tp", "_ac", "_bp", "_pr1",
"_pr2", "_pr3", "_dp1", "_mfl", "_cl", "_sicl", "_pd",
"_forcing"
]
budget_name = budget_ends
nterms = len(budget_ends)
if (varis[iv] == "wpthlp"):
budget_ends = ["_tp", "_bp", "_pr1"]
budget_name = [
'~F10~turb prod', '~F10~buoy+pres', '~F10~ret to iso'
]
nterms = len(budget_ends)
if (varis[iv] == "rtpthlp"):
budget_ends = [
"_bt", "_ma", "_ta", "_tp1", "_tp2", "_dp1", "_dp2",
"_cl", "_sf", "_forcing"
]
budget_name = budget_ends
nterms = len(budget_ends)
if (varis[iv] == "wp2"):
budget_ends = ["_ta", "_bp", "_pr1", "_dp1", "_dp2"]
budget_name = budget_ends
nterms = len(budget_ends)
if (varis[iv] == "wp3"):
budget_ends = [
"_ta", "_tp", "_bp1", "_bp2", "_pr1", "_pr2", "_dp1"
]
budget_name = budget_ends
nterms = len(budget_ends)
if (varis[iv] == "up2" or varis[iv] == "vp2"):
budget_ends = [
"_bt", "_ma", "_ta", "_tp", "_dp1", "_dp2", "_pr1",
"_pr2", "_cl", "_pd", "_sf"
]
budget_name = budget_ends
nterms = len(budget_ends)
if (varis[iv] == "um" or varis[iv] == "vm"):
budget_ends = ["_bt", "_ma", "_ta", "_gf", "_f"]
budget_name = budget_ends
nterms = len(budget_ends)
if (varis[iv] == "thlm" or varis[iv] == "rtm"):
budget_ends = ["_bt", "_ma", "_ta", "_cl", "_mc"]
budget_name = budget_ends
nterms = len(budget_ends)
if (varis[iv] == 'tau_no_N2_zm'):
budget_ends = ['tau_no_N2_zm', 'bkgnd', 'sfc', 'shear']
budget_name = [
'~F8~t~N~~F25~~B~noN2~N~', '~F8~t~N~~F25~~B~bkgnd~N~',
'~F8~t~N~~F25~~B~shear~N~', '~F8~t~N~~F25~~B~shear~N~'
]
nterms = len(budget_ends)
if (varis[iv] == 'tau_xp2_zm'):
budget_ends = ['tau_xp2_zm', 'tau_no_N2_zm']
budget_name = [
'~F8~t~N~~F25~~B~x`~S~2~N~~N~',
'~F8~t~N~~F25~~B~noN2~N~'
]
nterms = len(budget_ends)
if (varis[iv] == 'tau_wp2_zm'):
budget_ends = ['tau_wp2_zm', 'tau_no_N2_zm', 'bvpos']
budget_name = [
'~F8~t~N~~F25~~B~w`~S~2~N~~N~',
'~F8~t~N~~F25~~B~noN2~N~', '~F8~t~N~~F25~~B~bv~N~'
]
nterms = len(budget_ends)
if (varis[iv] == 'tau_wpxp_zm'):
budget_ends = [
'tau_wpxp_zm', 'tau_no_N2_zm', 'bvpos', 'clear'
]
budget_name = [
'~F8~t~N~~F25~~B~w`x`~N~', '~F8~t~N~~F25~~B~noN2~N~',
'~F8~t~N~~F25~~B~bv~N~', '~F8~t~N~~F25~~B~clr~N~'
]
nterms = len(budget_ends)
if (varis[iv] == 'tau_wp3_zm'):
budget_ends = [
'tau_wp3_zm', 'tau_no_N2_zm', 'bvpos', 'clear'
]
budget_name = [
'~F8~t~N~~F25~~B~w`~S~3~N~~N~',
'~F8~t~N~~F25~~B~noN2~N~', '~F8~t~N~~F25~~B~bv~N~',
'~F8~t~N~~F25~~B~clr~N~'
]
nterms = len(budget_ends)
ncdfs[im] = './data/' + cases[im] + '_site_location.nc'
infiles[im] = filepath[im] + cases[im] + '/' + cases[
im] + '_' + cseason + '_climo.nc'
inptrs = Dataset(infiles[im], 'r') # pointer to file1
lat = inptrs.variables['lat'][:]
nlat = len(lat)
lon = inptrs.variables['lon'][:]
nlon = len(lon)
ilev = inptrs.variables['ilev'][:]
nilev = len(ilev)
ncdf = Dataset(ncdfs[im], 'r')
n = ncdf.variables['n'][:]
idx_cols = ncdf.variables['idx_cols'][:, :]
ncdf.close()
A_field = np.zeros((nterms, nilev), np.float32)
for it in range(0, nterms):
for subc in range(0, n[ire]):
npoint = idx_cols[ire, n[subc] - 1] - 1
varis_bgt = varis[iv] + budget_ends[it]
tmp0 = inptrs.variables[varis[iv]][0, :, npoint]
theunits0 = "~F25~" + inptrs.variables[varis[iv]].units
if (varis[iv] == 'wpthlp'
and budget_ends[it] == '_bp'):
tmp = inptrs.variables[varis_bgt][
0, :, npoint] + inptrs.variables['wpthlp_pr3'][
0, :, npoint]
else:
tmp = inptrs.variables[varis_bgt][0, :, npoint]
theunits = str(
chscale[iv]) + "~F25~" + inptrs.variables[
varis[iv] + '_bt'].units
if (varis[iv] == "wprtp" or varis[iv] == "thlp2"):
tmp[0:10] = 0.0
tmp0[0:10] = 0.0
txres = Ngl.Resources()
txres.txFontHeightF = 0.02
txres.txFont = _Font
tmp = tmp * cscale[iv]
A_field[it, :] = (A_field[it, :] +
tmp[:] / n[ire]).astype(np.float32)
inptrs.close()
res.tiXAxisString = vname[iv] + ' Unit= ' + theunits
if (varis[iv] == "wpthlp" or varis[iv] == "thlp2"
or varis[iv] == "wp3" or varis[iv] == "wp2"):
res1.tiXAxisString = vname[iv] + ' Unit= ' + theunits0
p0 = Ngl.xy(wks, tmp0, ilev, res1)
plot.append(p0)
if (varis[iv] == 'wpthlp'):
if (lons[ire] < 230):
res.trXMinF = -1.
res.trXMaxF = 1.
Common_functions.create_legend(wks, budget_name, 0.013,
np.arange(1, 16, 4),
0.77, 0.85 - iv * 0.45)
else:
res.trXMinF = -0.4
res.trXMaxF = 0.4
Common_functions.create_legend(wks, budget_name, 0.013,
np.arange(1, 16, 4),
0.77, 0.85 - iv * 0.45)
if (varis[iv] == 'thlp2'):
if (lons[ire] < 230):
res.trXMinF = -2.8
res.trXMaxF = 2.8
Common_functions.create_legend(wks, budget_name, 0.013,
np.arange(1, 16, 4),
0.77, 0.85 - iv * 0.45)
else:
res.trXMinF = -1.
res.trXMaxF = 1.
Common_functions.create_legend(wks, budget_name, 0.013,
np.arange(1, 16, 4),
0.77, 0.85 - iv * 0.45)
res.tiXAxisString = vname[iv] + ' Unit= ' + theunits
p = Ngl.xy(wks, A_field, ilev, res)
plot.append(p)
del (res.trXMaxF)
del (res.trXMinF)
xp = np.mod(iv, 2)
yp = int(iv / 2)
Ngl.panel(wks, plot[:], [nvaris, 2], pres)
txres = Ngl.Resources()
txres.txFont = _Font
txres.txFontHeightF = 0.02
Ngl.text_ndc(
wks, casenames[im] + " BUDGET at " + str(lons[ire]) + "E," +
str(lats[ire]) + "N", 0.5, 0.91, txres)
Ngl.frame(wks)
Ngl.destroy(wks)
return (plotbgt)
def plot_power(Pow, symmetry=("symm"), source="", var1="", plotpath="./", flim=0.5, nWavePlt=20, cmin=0.05, cmax=0.55,
cspc=0.05, plotxy=[1, 1], N=[1, 2]):
dims = Pow.shape
nplot = dims[0]
FillMode = "AreaFill"
# text labels
abc = list(string.ascii_lowercase)
# plot resources
wkstype = "png"
wks = ngl.open_wks(wkstype, plotpath + "SpaceTimePower_" + source + var1)
plots = []
# coherence2 plot resources
res = coh_resources(cmin, cmax, cspc, FillMode, flim, nWavePlt)
# phase arrow resources
resA = phase_resources(flim, nWavePlt)
# dispersion curve resources
dcres = ngl.Resources()
dcres.gsLineThicknessF = 2.0
dcres.gsLineDashPattern = 0
# text box resources
txres = ngl.Resources()
txres.txPerimOn = True
txres.txFontHeightF = 0.013
txres.txBackgroundFillColor = "Background"
# panel plot resources
resP = panel_resources(nplot, abc)
# plot contours and phase arrows
pp = 0
while pp < nplot:
if nplot == 1:
coh2 = Pow
else:
coh2 = Pow[pp, :, :]
if len(symmetry) == nplot:
Symmetry = symmetry[pp]
else:
Symmetry = symmetry
res.tiMainString = source + " log10( Power(" + var1 + ")) " + Symmetry
plot = ngl.contour(wks, coh2, res)
(matsuno_names, textlabels, textlocsX, textlocsY) = text_labels(Symmetry)
nlabel = len(textlocsX)
# generate matsuno mode dispersion curves
if Symmetry == "midlat":
He = [3000, 7000, 10000]
matsuno_modes = mp.matsuno_modes_wk_bg(he=He, n=N, latitude=0., max_wn=nWavePlt, n_wn=500, u=25)
else:
He = [12, 25, 50]
matsuno_modes = mp.matsuno_modes_wk(he=He, n=N, latitude=0., max_wn=nWavePlt, n_wn=500)
# add polylines for dispersion curves
for he in matsuno_modes:
df = matsuno_modes[he]
wn = df.index.values
for wavename in df:
for matsuno_name in matsuno_names:
if wavename == (matsuno_name + str(he) + "m)"):
wave = df[wavename].values
wnwave = wn[~np.isnan(wave)]
wave = wave[~np.isnan(wave)]
ngl.add_polyline(wks, plot, wnwave, wave, dcres)
# add text boxes
ll = 0
while ll < nlabel:
ngl.add_text(wks, plot, textlabels[ll], textlocsX[ll], textlocsY[ll], txres)
ll += 1
plots.append(plot)
pp += 1
# panel plots
ngl.panel(wks, plots, plotxy, resP)
ngl.delete_wks(wks)
#ngl.end()
return
res.cnMinLevelValF = -0.1#0.45#-0.1 #-- contour min. value
res.cnMaxLevelValF = 2.0#1.5#2.0 #-- contour max. value
res.cnLevelSpacingF = 0.1#0.05#0.1 #-- contour interval
colors00 = Ngl.read_colormap_file("MPL_RdBu")
ncolors00= colors00.shape[0]
colors0 = colors00[np.linspace(2,ncolors00-1,int((res.cnMaxLevelValF-res.cnMinLevelValF)/res.cnLevelSpacingF),dtype=int),:]
grey_color = np.expand_dims(np.array([0.85, 0.85, 0.85, 1]), axis=0)
colors = np.append(grey_color,colors0[::-1,:],axis=0)
res.cnFillPalette = colors#'BlWhRe' #'MPL_YlOrRd' #-- choose color map
plot = []
title = 'CESM all forcing vs '+sf+' foricng~C~FWI >= p'+str(pxx)+' risk ratio'
for pp in range(2,nperiods,1):
print('period '+str(pp+1))
res.tiMainString = str(pyear0[pp])+'-'+str(pyear1[pp])
riskratio_cyc, lon_cyc = Ngl.add_cyclic(riskratio_ens_agree_masked[pp,:,:], lon)
res.sfXArray = lon_cyc
p = Ngl.contour_map(wks,riskratio_cyc,res)
if pp==(nperiods-1):
for rr in range(0,n_reg,1):
poly_y = [df_reg['reg_N'][rr],df_reg['reg_S'][rr],df_reg['reg_S'][rr],df_reg['reg_N'][rr],df_reg['reg_N'][rr]]
poly_x = [df_reg['reg_E'][rr],df_reg['reg_E'][rr],df_reg['reg_W'][rr],df_reg['reg_W'][rr],df_reg['reg_E'][rr]]
poly_reg = Ngl.add_polygon(wks,p,poly_x,poly_y,gsres)
plot.append(p)
Ngl.panel(wks,plot,[4,1],pres)
Ngl.text_ndc(wks,title,0.5,0.92,txres)
Ngl.frame(wks)
Ngl.delete_wks(wks)
def large_scale_prf (ptype,cseason, ncases, cases, casenames, nsite, lats, lons, filepath, filepathobs, casedir):
# ncases, the number of models
# cases, the name of models
# casename, the name of cases
# filepath, model output filepath
# filepathobs, filepath for observational data
# inptrs = [ncases]
if not os.path.exists(casedir):
os.mkdir(casedir)
_Font = 25
interp = 2
extrap = False
mkres = Ngl.Resources()
mkres.gsMarkerIndex = 2
mkres.gsMarkerColor = 'Red'
mkres.gsMarkerSizeF = 15.
infiles = ['' for x in range(ncases)]
ncdfs = ['' for x in range(ncases)]
nregions = nsite
localnames=np.append('ERAI',casenames)
varis = [ 'CLOUD' , 'CLDLIQ', 'THETA','RELHUM']
varisobs = ['CC_ISBL', 'CLWC_ISBL', 'THETA','RELHUM' ]
alphas = ['a) ','b) ','c) ','d) ','e) ','f) ','g) ','h) ','i) ', 'j) ', 'k) ', 'l) ', 'm) ', 'n) ', 'o) ', 'p) ', 'q) ', 'r) ', 's) ', 't) ', 'u) ', 'v) ', 'w) ', 'x) ', 'y) ', 'z) ']
nvaris = len(varis)
cunits = ['%','g/kg','K', '%' ]
cscale = [100, 1000 , 1., 1 ]
cscaleobs = [100, 1000 , 1., 1, 1, 1000, 1,1,1,1,1,1,1]
obsdataset =['ERAI', 'ERAI', 'ERAI', 'ERAI', 'ERAI', 'ERAI', 'ERAI', 'ERAI','ERAI','ERAI']
plotlgs=['' for x in range(nsite)]
for ire in range (0, nsite):
if not os.path.exists(casedir+'/'+str(lons[ire])+'E_'+str(lats[ire])+'N'):
os.mkdir(casedir+'/'+str(lons[ire])+'E_'+str(lats[ire])+'N')
plotname = casedir+'/'+str(lons[ire])+'E_'+str(lats[ire])+'N/Largescale_'+str(lons[ire])+'E_'+str(lats[ire])+'N_'+cseason
plotlgs[ire] = 'Largescale_'+str(lons[ire])+'E_'+str(lats[ire])+'N_'+cseason
wks= Ngl.open_wks(ptype,plotname)
Ngl.define_colormap(wks,'GMT_paired')
plot = []
res = Ngl.Resources()
res.nglMaximize = False
res.nglDraw = False
res.nglFrame = False
res.lgPerimOn = False # no box around
res.vpWidthF = 0.30 # set width and height
res.vpHeightF = 0.30
res.tiYAxisString = "Pressure [hPa]"
if (lats[ire] > 0 and lons[ire]<230 ):
res.trYMinF = 400.
res.trYMaxF = 1000.
else:
res.trYMinF = 700.
res.trYMaxF = 1000.
res.tiMainFont = _Font
res.tmYLLabelFont = _Font
res.tmXBLabelFont = _Font
res.tiYAxisFont = _Font
res.tiXAxisFont = _Font
res.tmXBLabelFontHeightF = 0.01
res.tmXBLabelFontThicknessF = 1.0
res.xyMarkLineMode = 'Lines'
res.xyLineThicknesses = [3.0, 3.0, 3.0, 3.0, 3.0, 3.0,3.,3.,3.,3.,3,3,3,3,3,3,3]
res.xyDashPatterns = np.arange(0,24,1)
pres = Ngl.Resources()
pres.nglFrame = False
pres.txFont = _Font
pres.nglPanelYWhiteSpacePercent = 5
pres.nglPanelXWhiteSpacePercent = 5
# pres.nglPanelTop = 0.88
pres.wkPaperWidthF = 17 # in inches
pres.wkPaperHeightF = 28 # in inches
pres.nglMaximize = True
pres.nglPanelTop = 0.935
pres.nglPanelFigureStrings = alphas
pres.nglPanelFigureStringsJust = 'Topleft'
pres.nglPanelFigureStringsFontHeightF = 0.015
for iv in range (0, nvaris):
if(iv == nvaris-1):
res.pmLegendDisplayMode = 'NEVER'
res.xyExplicitLegendLabels = casenames[:]
res.pmLegendSide = 'top'
res.pmLegendParallelPosF = 0.6
res.pmLegendOrthogonalPosF = -0.5
res.pmLegendWidthF = 0.10
res.pmLegendHeightF = 0.10
res.lgLabelFontHeightF = .02
res.lgLabelFontThicknessF = 1.5
res.lgPerimOn = True
else:
res.pmLegendDisplayMode = 'NEVER'
if(obsdataset[iv] =='CCCM'):
if(cseason == 'ANN'):
fileobs = '/Users/guoz/databank/CLD/CCCm/cccm_cloudfraction_2007-'+cseason+'.nc'
else:
fileobs = '/Users/guoz/databank/CLD/CCCm/cccm_cloudfraction_2007-2010-'+cseason+'.nc'
inptrobs = Dataset(fileobs,'r')
latobs=inptrobs.variables['lat'][:]
latobs_idx = np.abs(latobs - lats[ire]).argmin()
lonobs=inptrobs.variables['lon'][:]
lonobs_idx = np.abs(lonobs - lons[ire]).argmin()
B=inptrobs.variables[varisobs[iv]][:,latobs_idx,lonobs_idx]
else:
if (varisobs[iv] =='PRECT'):
fileobs = filepathobs+'/GPCP_'+cseason+'_climo.nc'
else:
fileobs = filepathobs + obsdataset[iv]+'_'+cseason+'_climo.nc'
inptrobs = Dataset(fileobs,'r')
if (varisobs[iv] =='THETA'):
latobs=inptrobs.variables['lat'][:]
latobs_idx = np.abs(latobs - lats[ire]).argmin()
lonobs=inptrobs.variables['lon'][:]
lonobs_idx = np.abs(lonobs - lons[ire]).argmin()
B = inptrobs.variables['T'][0,:,latobs_idx,lonobs_idx]
pre1 = inptrobs.variables['lev'][:]
for il1 in range (0, len(pre1)):
B[il1] = B[il1]*(1000/pre1[il1])**0.286
else:
pre1 = inptrobs.variables['lev'][:]
latobs=inptrobs.variables['lat'][:]
latobs_idx = np.abs(latobs - lats[ire]).argmin()
lonobs=inptrobs.variables['lon'][:]
lonobs_idx = np.abs(lonobs - lons[ire]).argmin()
B = inptrobs.variables[varisobs[iv]][0,:,latobs_idx,lonobs_idx]
B[:]=B[:] * cscaleobs[iv]
for im in range (0,ncases):
ncdfs[im] = './data/'+cases[im]+'_site_location.nc'
infiles[im]= filepath[im]+cases[im]+'/'+cases[im]+'_'+cseason+'_climo.nc'
inptrs = Dataset(infiles[im],'r') # pointer to file1
lat=inptrs.variables['lat'][:]
nlat=len(lat)
lon=inptrs.variables['lon'][:]
nlon=len(lon)
lev=inptrs.variables['lev'][:]
nlev=len(lev)
ncdf= Dataset(ncdfs[im],'r')
n =ncdf.variables['n'][:]
idx_cols=ncdf.variables['idx_cols'][:,:]
ncdf.close()
if (im ==0 ):
A_field = np.zeros((ncases,nlev),np.float32)
for subc in range( 0, n[ire]):
npoint=idx_cols[ire,n[subc]-1]-1
if (varis[iv] == 'THETA'):
tmp = inptrs.variables['T'][0,:,npoint]
hyam =inptrs.variables['hyam'][:]
hybm =inptrs.variables['hybm'][:]
ps=inptrs.variables['PS'][0,npoint]
ps=ps
p0=inptrs.variables['P0']
pre = np.zeros((nlev),np.float32)
for il in range (0, nlev):
pre[il] = hyam[il]*p0 + hybm[il] * ps
tmp[il] = tmp[il] * (100000/pre[il])**0.286
theunits=str(cscale[iv])+inptrs.variables['T'].units
else:
tmp=inptrs.variables[varis[iv]][0,:,npoint]
theunits=str(cscale[iv])+inptrs.variables[varis[iv]].units
A_field[im,:] = (A_field[im,:]+tmp[:]/n[ire]).astype(np.float32 )
A_field[im,:] = A_field[im,:] *cscale[iv]
inptrs.close()
textres = Ngl.Resources()
textres.txFontHeightF = 0.02
textres.txFont = _Font
textres.txFontHeightF = 0.015
res.tiXAxisString = varis[iv]+ " Unit= " + cunits[iv]
res.trXMinF = min(np.min(A_field[0, :]),np.min(B))
res.trXMaxF = max(np.max(A_field[0, :]),np.max(B))
if(varis[iv] == 'CLOUD') :
if (lats[ire] >= 0 and lons[ire]<230):
res.trXMinF = 0.
res.trXMaxF = 50.
else:
res.trXMinF = 0.
res.trXMaxF = 100.
if(varis[iv] =='CLDLIQ') :
if (lats[ire] >= 0):
res.trXMinF = 0.
res.trXMaxF = 0.1
else:
res.trXMinF = 0.
res.trXMaxF = 0.1
if(varis[iv] =='RELHUM') :
res.trXMinF = 0.
res.trXMaxF = 100.
if(varis[iv] == 'THETA') :
if (lats[ire] >= 0 and lons[ire]<230 ):
res.trXMinF = 290.
res.trXMaxF = 340.
else:
res.trXMinF = 280
res.trXMaxF = 320
if(varis[iv] == 'T') :
res.trXMinF = 180
res.trXMaxF = 300
if(varis[iv] == 'U') :
res.trXMinF = -40
res.trXMaxF = 40
res.trYReverse = True
res.xyLineColors = np.arange(3,20,2)
res.xyMarkerColors = np.arange(2,20,2)
p = Ngl.xy(wks,A_field,lev,res)
res.trYReverse = False
res.xyLineColors = ['black']
pt = Ngl.xy(wks,B,pre1,res)
Ngl.overlay(p,pt)
plot.append(p)
Ngl.panel(wks,plot[:],[nvaris/2,2],pres)
txres = Ngl.Resources()
txres.txFontHeightF = 0.02
txres.txFont = _Font
Ngl.text_ndc(wks,'Large-scale VAR at '+ str(lons[ire])+'E,'+str(lats[ire])+'N',0.5,0.93,txres)
Common_functions.create_legend(wks,localnames,0.02,np.append('black',np.arange(3,20,2)),0.25,0.85)
Ngl.frame(wks)
Ngl.destroy(wks)
return plotlgs
res2.trXMinF = faxis[0] # Limits for X axis
res2.trXMaxF = faxis[-1]
res2.tiXAxisString = "~F25~Frequency (Hz)"
res2.tiYAxisString = "~F25~Power Spectrum"
leftname = "Period from ~F34~%~F25~ to {} seconds".format(1./faxis[-1])
res2.tiMainString = "Spectral Analysis (FFT)"+ \
"~C~~B~"+leftname
plot = []
plot.append(Ngl.xy(wks,t,sig,res))
plot.append(Ngl.xy(wks,faxis,PS,res2))
#wrf_tools.ngl_Strings(wks, plot[0], left=leftname, center="", right="")
panelres = Ngl.Resources()
Ngl.panel(wks,plot[0:1+1],[2,1],panelres)
#Ngl.draw(plot[0])
#Ngl.frame(wks)
Ngl.destroy(wks); del res, plot
Ngl.end()
end_time = cpu_time(); end_time = (end_time - start_time)/60.0
print(os.path.basename(__file__)+" has done!\nTime elapsed: {:.2f}".format(end_time), "mins.")
pres.nglFrame = False
pres.nglPanelLabelBar = True
# Calculate start Y position for first row of plots
height = 0.275 # we know this will be height of small plots
extra = 1.0 - (3 * height)
top = 1.0 - (extra / 2.) # 子图第一行所在的高度
# Draw a title before we draw plots
title = figData[3]['headLineTxt']
txres = Ngl.Resources()
txres.txJust = "BottomCenter"
txres.txFontHeightF = 0.02
Ngl.text_ndc(wks, title, 0.5, top + 0.01, txres)
# # Loop across plots and panel them on one page
# for n in range(0,1):
# # Define location in a unit square for each set of plots.
pres.nglPanelTop = top - (0 * height)
pres.nglPanelBottom = top - ((2 + 1) * height)
pres.nglPanelYWhiteSpacePercent = 3
Ngl.panel(wks, plots[0:7], [3, 2], pres)
# plot = Ngl.contour_map(wks, plotData, res)
# Ngl.draw(plot)
Ngl.frame(wks)
Ngl.destroy(wks)
# Ngl.end()
def large_scale_prf(ptype, cseason, ncases, cases, casenames, nsite, lats,
lons, filepath, filepathobs, casedir, dofv):
# ncases, the number of models
# cases, the name of models
# casename, the name of cases
# filepath, model output filepath
# filepathobs, filepath for observational data
# inptrs = [ncases]
if not os.path.exists(casedir):
os.mkdir(casedir)
_Font = 25
interp = 2
extrap = False
mkres = Ngl.Resources()
mkres.gsMarkerIndex = 2
mkres.gsMarkerColor = "Red"
mkres.gsMarkerSizeF = 15.
infiles = ["" for x in range(ncases)]
ncdfs = ["" for x in range(ncases)]
nregions = nsite
varis = [
"CLOUD", "OMEGA", "Q", "CLDLIQ", "THETA", "RELHUM", "U", "CLDICE", "T"
]
varisobs = [
"CC_ISBL", "OMEGA", "SHUM", "CLWC_ISBL", "THETA", "RELHUM", "U",
"CIWC_ISBL", "T"
]
nvaris = len(varis)
cunits = [
"%", "mba/day", "g/kg", "g/kg", "K", "%", "m/s", "g/kg", "m/s", "m/s",
"K", "m"
]
cscale = [100, 864, 1000, 1000, 1., 1, 1, 1000, 1, 1, 1, 1, 1, 1, 1]
cscaleobs = [100, 1, 1, 1000, 1., 1, 1, 1000, 1, 1, 1, 1, 1, 1, 1]
obsdataset = [
"ERAI", "ERAI", "ERAI", "ERAI", "ERAI", "ERAI", "ERAI", "ERAI", "ERAI",
"ERAI"
]
plotlgs = ["" for x in range(nsite)]
for ire in range(0, nsite):
if not os.path.exists(casedir + '/' + str(lons[ire]) + 'E_' +
str(lats[ire]) + 'N'):
os.mkdir(casedir + '/' + str(lons[ire]) + 'E_' + str(lats[ire]) +
'N')
plotname = casedir + '/' + str(lons[ire]) + 'E_' + str(
lats[ire]) + 'N/Largescale_' + str(lons[ire]) + "E_" + str(
lats[ire]) + "N_" + cseason
plotlgs[ire] = 'Largescale_' + str(lons[ire]) + "E_" + str(
lats[ire]) + "N_" + cseason
wks = Ngl.open_wks(ptype, plotname)
Ngl.define_colormap(wks, "GMT_paired")
plot = []
res = Ngl.Resources()
res.nglMaximize = False
res.nglDraw = False
res.nglFrame = False
res.lgPerimOn = False # no box around
res.vpWidthF = 0.30 # set width and height
res.vpHeightF = 0.30
res.tiYAxisString = "Pressure [hPa]"
res.tiMainFont = _Font
res.tmYLLabelFont = _Font
res.tmXBLabelFont = _Font
res.tiYAxisFont = _Font
res.tiXAxisFont = _Font
res.tmXBLabelFontHeightF = 0.01
res.tmXBLabelFontThicknessF = 1.0
res.xyMarkLineMode = 'Lines'
# res.tmXBLabelAngleF = 45
res.xyLineThicknesses = [
3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3., 3., 3., 3., 3, 3, 3, 3, 3, 3, 3
]
res.xyDashPatterns = np.arange(0, 24, 1)
pres = Ngl.Resources()
pres.nglFrame = False
pres.txString = "Large-scale VAR at" + str(lons[ire]) + "E," + str(
lats[ire]) + "N"
pres.txFont = _Font
pres.nglPanelYWhiteSpacePercent = 5
pres.nglPanelXWhiteSpacePercent = 5
pres.nglPanelTop = 0.88
pres.wkPaperWidthF = 17 # in inches
pres.wkPaperHeightF = 28 # in inches
pres.nglMaximize = True
pres.wkWidth = 10000
pres.wkHeight = 10000
for iv in range(0, nvaris):
if (iv == nvaris - 1):
res.pmLegendDisplayMode = "NEVER"
res.xyExplicitLegendLabels = casenames[:]
res.pmLegendSide = "top"
res.pmLegendParallelPosF = 0.6
res.pmLegendOrthogonalPosF = -0.5
res.pmLegendWidthF = 0.10
res.pmLegendHeightF = 0.10
res.lgLabelFontHeightF = .02
res.lgLabelFontThicknessF = 1.5
res.lgPerimOn = True
else:
res.pmLegendDisplayMode = "NEVER"
if (obsdataset[iv] == "CCCM"):
if (cseason == "ANN"):
fileobs = "/Users/guoz/databank/CLD/CCCm/cccm_cloudfraction_2007-" + cseason + ".nc"
else:
fileobs = "/Users/guoz/databank/CLD/CCCm/cccm_cloudfraction_2007-2010-" + cseason + ".nc"
inptrobs = Dataset(fileobs, 'r')
latobs = inptrobs.variables['lat'][:]
latobs_idx = np.abs(latobs - lats[ire]).argmin()
lonobs = inptrobs.variables['lon'][:]
lonobs_idx = np.abs(lonobs - lons[ire]).argmin()
B = inptrobs.variables[varisobs[iv]][:, latobs_idx, lonobs_idx]
else:
if (varisobs[iv] == "PRECT"):
fileobs = filepathobs + '/GPCP_' + cseason + '_climo.nc'
else:
fileobs = filepathobs + obsdataset[
iv] + '_' + cseason + '_climo.nc'
inptrobs = Dataset(fileobs, 'r')
if (varisobs[iv] == "THETA"):
latobs = inptrobs.variables['lat'][:]
latobs_idx = np.abs(latobs - lats[ire]).argmin()
lonobs = inptrobs.variables['lon'][:]
lonobs_idx = np.abs(lonobs - lons[ire]).argmin()
B = inptrobs.variables['T'][0, :, latobs_idx, lonobs_idx]
pre1 = inptrobs.variables['lev'][:]
for il1 in range(0, len(pre1)):
B[il1] = B[il1] * (1000 / pre1[il1])**0.286
else:
pre1 = inptrobs.variables['lev'][:]
latobs = inptrobs.variables['lat'][:]
latobs_idx = np.abs(latobs - lats[ire]).argmin()
lonobs = inptrobs.variables['lon'][:]
lonobs_idx = np.abs(lonobs - lons[ire]).argmin()
B = inptrobs.variables[varisobs[iv]][0, :, latobs_idx,
lonobs_idx]
B[:] = B[:] * cscaleobs[iv]
for im in range(0, ncases):
ncdfs[im] = './data/' + cases[im] + '_site_location.nc'
infiles[im] = filepath[im] + '/' + cases[
im] + '_' + cseason + '_climo.nc'
inptrs = Dataset(infiles[im], 'r') # pointer to file1
lat = inptrs.variables['lat'][:]
nlat = len(lat)
lon = inptrs.variables['lon'][:]
nlon = len(lon)
lev = inptrs.variables['lev'][:]
nlev = len(lev)
ncdf = Dataset(ncdfs[im], 'r')
n = ncdf.variables['n'][:]
idx_cols = ncdf.variables['idx_cols'][:, :]
if (dofv):
idx_lats = ncdf.variables['idx_coord_lat'][:, :]
idx_lons = ncdf.variables['idx_coord_lon'][:, :]
ncdf.close()
theunits = "[units]"
if (im == 0):
A_field = np.zeros((ncases, nlev), np.float32)
for subc in range(0, n[ire]):
npoint = idx_cols[ire, n[subc] - 1] - 1
if (dofv):
npointlat = idx_lats[ire, 0]
npointlon = idx_lons[ire, 0]
if (varis[iv] == 'THETA'):
if (dofv):
tmp = inptrs.variables['T'][0, :, npointlat,
npointlon]
else:
tmp = inptrs.variables['T'][0, :, npoint]
hyam = inptrs.variables['hyam'][:]
hybm = inptrs.variables['hybm'][:]
if (dofv):
ps = inptrs.variables['PS'][0, npointlat,
npointlon]
else:
ps = inptrs.variables['PS'][0, npoint]
ps = ps
p0 = 100000.0 #CAM uses a hard-coded p0
pre = np.zeros((nlev), np.float32)
for il in range(0, nlev):
pre[il] = hyam[il] * p0 + hybm[il] * ps
tmp[il] = tmp[il] * (100000 / pre[il])**0.286
theunits = str(
cscale[iv]) + "x" + inptrs.variables['T'].units
else:
if (dofv):
tmp = inptrs.variables[varis[iv]][0, :, npointlat,
npointlon]
else:
tmp = inptrs.variables[varis[iv]][0, :, npoint]
theunits = str(cscale[iv]) + "x" + inptrs.variables[
varis[iv]].units
##import pdb; pdb.set_trace()
A_field[im, :] = (A_field[im, :] + tmp[:] / n[ire]).astype(
np.float32)
A_field[im, :] = A_field[im, :] * cscale[iv]
inptrs.close()
res.tiMainString = varis[iv] + " " + theunits
res.trXMinF = min(np.min(A_field[0, :]), np.min(B))
res.trXMaxF = max(np.max(A_field[0, :]), np.max(B))
if (varis[iv] == "THETA"):
res.trXMinF = 270.
res.trXMaxF = 400.
if (varis[iv] == "CLOUD" or varis[iv] == "RELHUM"):
res.trXMinF = 0.
res.trXMaxF = 100.
if (varis[iv] == "T"):
res.trXMinF = 180
res.trXMaxF = 300
if (varis[iv] == "U"):
res.trXMinF = -40
res.trXMaxF = 40
res.trYReverse = True
res.xyLineColors = np.arange(3, 20, 2)
res.xyMarkerColors = np.arange(2, 20, 2)
p = Ngl.xy(wks, A_field, lev, res)
res.trYReverse = False
res.xyLineColors = ["black"]
pt = Ngl.xy(wks, B, pre1, res)
Ngl.overlay(p, pt)
plot.append(p)
Ngl.panel(wks, plot[:], [nvaris / 3, 3], pres)
txres = Ngl.Resources()
txres.txFontHeightF = 0.02
txres.txFont = _Font
Ngl.text_ndc(
wks, "Large-scale VAR at" + str(lons[ire]) + "E," +
str(lats[ire]) + "N", 0.5, 0.92 + ncases * 0.01, txres)
Common_functions.create_legend(wks, casenames, 0.02,
np.arange(3, 20,
2), 0.1, 0.89 + ncases * 0.01)
Ngl.frame(wks)
Ngl.destroy(wks)
return plotlgs
# Resources for panelling
pres = Ngl.Resources()
pres.nglFrame = False
pres.nglPanelLabelBar = True
# Calculate start Y position for first row of plots
height = 0.8 # we know this will be height of small plots
extra = 1.0 - (height)
top = 1.0 - (extra / 2.) #子图第一行所在的高度
# Draw a title before we draw plots
title = figData[3]['headLineTxt']
txres = Ngl.Resources()
txres.txJust = "BottomCenter"
txres.txFontHeightF = 0.02
Ngl.text_ndc(wks, title, 0.5, top + 0.01, txres)
# Define location in a unit square for each set of plots.
pres.nglPanelTop = top
pres.nglPanelBottom = top - height
Ngl.panel(wks, plots[0:nplots], [3, 1], pres)
# plot = Ngl.contour_map(wks, plotData, res)
# Ngl.draw(plot)
Ngl.frame(wks)
Ngl.destroy(wks)
# Ngl.end()
def draw_2D_plot(ptype, cseason, ncases, cases, casenames, nsite, lats, lons,
filepath, filepathobs, casedir):
# ncases, the number of models
# cases, the name of models
# casename, the name of cases
# filepath, model output filepath
# filepathobs, filepath for observational data
# inptrs = [ncases]
if not os.path.exists(casedir):
os.mkdir(casedir)
if not os.path.exists(casedir + '/2D'):
os.mkdir(casedir + '/2D')
_Font = 25
interp = 2
extrap = False
infiles = ['' for x in range(ncases)]
ncdfs = ['' for x in range(ncases)]
alpha = ['A', 'B', 'C', 'D', 'E', 'F']
cunits = ['']
varis = [
'SWCF', 'LWCF', 'PRECT', 'LHFLX', 'SHFLX', 'TMQ', 'PS', 'TS', 'U10',
'CLDTOT', 'CLDLOW', 'CLDHGH', 'TGCLDLWP'
]
varisobs = [
'SWCF', 'LWCF', 'PRECT', 'LHFLX', 'SHFLX', 'PREH2O', 'PS', 'TS', 'U10',
'CLDTOT_CAL', 'CLDTOT_CAL', 'CLDTOT_CAL', 'TGCLDLWP_OCEAN'
]
nvaris = len(varis)
cscale = [1, 1, 86400000, 1, 1, 1, 1, 1, 1, 100, 100, 100, 1000, 1, 1, 1]
cscaleobs = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
# cntrs = [[0 for col in range(11)] for row in range(nvaris)]
cntrs = np.zeros((nvaris, 11), np.float32)
obsdataset = [
'CERES-EBAF', 'CERES-EBAF', 'GPCP', 'ERAI', 'NCEP', 'ERAI', 'NCEP',
'ERAI', 'ERAI', 'CALIPSOCOSP', 'CALIPSOCOSP', 'CALIPSOCOSP', 'NVAP'
]
plot2d = ['' for x in range(nvaris)]
for iv in range(0, nvaris):
# make plot for each field
if (varis[iv] == 'CLDTOT' or varis[iv] == 'CLDLOW'
or varis[iv] == 'CLDHGH'):
cntrs[iv, :] = [2, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90]
if (varis[iv] == 'LWCF'):
cntrs[iv, :] = [1, 2, 5, 10, 15, 20, 25, 30, 35, 40, 45]
if (varis[iv] == 'SWCF' or varis[iv] == 'FLUT'):
cntrs[iv, :] = [
-40, -50, -60, -70, -80, -90, -100, -110, -120, -130, -140
]
if (varis[iv] == 'PRECT' or varis[iv] == 'QFLX'):
cntrs[iv, :] = [0.5, 1.5, 3, 4.5, 6, 7.5, 9, 10.5, 12, 13.5, 15]
if (varis[iv] == 'LHFLX'):
cntrs[iv, :] = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110]
if (varis[iv] == 'SHFLX'):
cntrs[iv, :] = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110]
if (varis[iv] == 'U10'):
cntrs[iv, :] = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
if (varis[iv] == 'TMQ'):
cntrs[iv, :] = [5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55]
if (varis[iv] == 'TGCLDLWP'):
cntrs[iv, :] = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110]
# Observational data
if (obsdataset[iv] == 'CCCM'):
if (cseason == 'ANN'):
fileobs = '/Users/guoz/databank/CLD/CCCm/cccm_cloudfraction_2007-' + cseason + '.nc'
else:
fileobs = '/Users/guoz/databank/CLD/CCCm/cccm_cloudfraction_2007-2010-' + cseason + '.nc'
else:
if (varisobs[iv] == 'PRECT'):
fileobs = filepathobs + '/GPCP_' + cseason + '_climo.nc'
else:
fileobs = filepathobs + obsdataset[
iv] + '_' + cseason + '_climo.nc'
# infiles[im]=filepath[im]+cases[im]+'/run/'+cases[im]+'_'+cseason+'_climo.nc'
inptrobs = Dataset(fileobs, 'r')
latobs = inptrobs.variables['lat'][:]
lonobs = inptrobs.variables['lon'][:]
if (varisobs[iv] == 'U10'):
B0 = inptrobs.variables[varisobs[iv]][0, :, :]
B1 = inptrobs.variables['V10'][0, :, :]
B = (B0 * B0 + B1 * B1)
B = B * cscaleobs[iv]
B = np.sqrt(B)
else:
B = inptrobs.variables[varisobs[iv]][0, :, :]
B = B * cscaleobs[iv]
#************************************************
# create plot
#************************************************
plotname = casedir + '/2D/Horizontal_' + varis[iv] + '_' + cseason
plot2d[iv] = 'Horizontal_' + varis[iv] + '_' + cseason
wks = Ngl.open_wks(ptype, plotname)
Ngl.define_colormap(wks, 'cmocean_thermal')
# Ngl.define_colormap(wks,'MPL_coolwarm')
# ngl_define_colormap(wks,'prcp_1')
plot = []
textres = Ngl.Resources()
textres.txFontHeightF = 0.02 # Size of title.
textres.txFont = _Font
Ngl.text_ndc(wks, varis[iv], 0.1, .97, textres)
pres = Ngl.Resources()
pres.nglMaximize = True
pres.nglPanelYWhiteSpacePercent = 5
pres.nglPanelXWhiteSpacePercent = 5
pres.nglPanelBottom = 0.20
pres.nglPanelTop = 0.9
pres.pmLabelBarWidthF = 0.8
pres.nglFrame = False
pres.nglPanelLabelBar = True # Turn on panel labelbar
pres.nglPanelLabelBarLabelFontHeightF = 0.015 # Labelbar font height
pres.nglPanelLabelBarHeightF = 0.0750 # Height of labelbar
pres.nglPanelLabelBarWidthF = 0.700 # Width of labelbar
pres.lbLabelFont = 'helvetica-bold' # Labelbar font
pres.nglPanelTop = 0.935
pres.nglPanelFigureStrings = alpha
pres.nglPanelFigureStringsJust = 'BottomRight'
res = Ngl.Resources()
res.nglDraw = False #-- don't draw plots
res.nglFrame = False
res.cnFillOn = True
res.cnFillMode = 'RasterFill'
res.cnLinesOn = False
res.nglMaximize = True
res.mpFillOn = True
res.mpCenterLonF = 180
res.tiMainFont = _Font
res.tiMainFontHeightF = 0.025
res.tiXAxisString = ''
res.tiXAxisFont = _Font
res.tiXAxisFontHeightF = 0.025
res.tiYAxisString = ''
res.tiYAxisFont = _Font
res.tiYAxisOffsetXF = 0.0
res.tiYAxisFontHeightF = 0.025
res.tmXBLabelFont = _Font
res.tmYLLabelFont = _Font
res.tiYAxisFont = _Font
res.vpWidthF = 0.80 # set width and height
res.vpHeightF = 0.40
res.vpXF = 0.04
res.vpYF = 0.30
res.cnInfoLabelOn = False
res.cnFillOn = True
res.cnLinesOn = False
res.cnLineLabelsOn = False
res.lbLabelBarOn = False
# res.vcRefMagnitudeF = 5.
# res.vcMinMagnitudeF = 1.
# res.vcRefLengthF = 0.04
# res.vcRefAnnoOn = True#False
# res.vcRefAnnoZone = 3
# res.vcRefAnnoFontHeightF = 0.02
# res.vcRefAnnoString2 =''
# res.vcRefAnnoOrthogonalPosF = -1.0
# res.vcRefAnnoArrowLineColor = 'blue' # change ref vector color
# res.vcRefAnnoArrowUseVecColor = False
# res.vcMinDistanceF = .05
# res.vcMinFracLengthF = .
# res.vcRefAnnoParallelPosF = 0.997
# res.vcFillArrowsOn = True
# res.vcLineArrowThicknessF = 3.0
# res.vcLineArrowHeadMinSizeF = 0.01
# res.vcLineArrowHeadMaxSizeF = 0.03
# res.vcGlyphStyle = 'CurlyVector' # turn on curley vectors
# res@vcGlyphStyle ='Fillarrow'
# res.vcMonoFillArrowFillColor = True
# res.vcMonoLineArrowColor = True
# res.vcLineArrowColor = 'green' # change vector color
# res.vcFillArrowEdgeColor ='white'
# res.vcPositionMode ='ArrowTail'
# res.vcFillArrowHeadInteriorXF =0.1
# res.vcFillArrowWidthF =0.05 #default
# res.vcFillArrowMinFracWidthF =.5
# res.vcFillArrowHeadMinFracXF =.5
# res.vcFillArrowHeadMinFracYF =.5
# res.vcFillArrowEdgeThicknessF = 2.0
res.mpFillOn = False
res.cnLevelSelectionMode = 'ExplicitLevels'
res.cnLevels = cntrs[iv][:]
for im in range(0, ncases):
ncdfs[im] = './data/' + cases[im] + '_site_location.nc'
infiles[im] = filepath[im] + cases[im] + '/' + cases[
im] + '_' + cseason + '_climo.nc'
inptrs = Dataset(infiles[im], 'r') # pointer to file1
lat = inptrs.variables['lat'][:]
nlat = len(lat)
lon = inptrs.variables['lon'][:]
nlon = len(lon)
area = inptrs.variables['area'][:]
area_wgt = np.zeros(nlat)
sits = np.linspace(0, nsite - 1, nsite)
ncdf = Dataset(ncdfs[im], 'r')
n = ncdf.variables['n'][:]
idx_cols = ncdf.variables['idx_cols'][:]
if (varis[iv] == 'PRECT'):
A = inptrs.variables['PRECC'][
0, :] + inptrs.variables['PRECL'][0, :]
else:
A = inptrs.variables[varis[iv]][0, :]
if (varis[iv] == 'FLUT'):
A = inptrs.variables['FLUT'][0, :] - inptrs.variables['FLNS'][
0, :]
else:
A = inptrs.variables[varis[iv]][0, :]
if (varis[iv] == 'U10'):
A = inptrs.variables['U10'][0, :] * inptrs.variables['U10'][
0, :]
A = np.sqrt(A)
else:
A = inptrs.variables[varis[iv]][0, :]
A_xy = A
A_xy = A_xy * cscale[iv]
ncdf.close()
inptrs.close()
if im == 0:
dsizes = len(A_xy)
field_xy = [[0 for col in range(dsizes)]
for row in range(ncases)]
field_xy[im][:] = A_xy
res.lbLabelBarOn = False
if (np.mod(im, 2) == 0):
res.tiYAxisOn = True
else:
res.tiYAxisOn = False
res.tiXAxisOn = False
res.sfXArray = lon
res.sfYArray = lat
res.mpLimitMode = 'LatLon'
res.mpMaxLonF = max(lon)
res.mpMinLonF = min(lon)
res.mpMinLatF = min(lat)
res.mpMaxLatF = max(lat)
res.tiMainString = 'GLB=' + str(
np.sum(A_xy[:] * area[:] / np.sum(area)))
textres.txFontHeightF = 0.015
Ngl.text_ndc(wks, alpha[im] + ' ' + casenames[im], 0.3,
.135 - im * 0.03, textres)
p = Ngl.contour_map(wks, A_xy, res)
plot.append(p)
# observation
# res.nglLeftString = obsdataset[iv]
# res@lbLabelBarOn = True
# res@lbOrientation = 'vertical' # vertical label bars
res.lbLabelFont = _Font
res.tiYAxisOn = True
res.tiXAxisOn = True
res.tiXAxisFont = _Font
rad = 4.0 * np.arctan(1.0) / 180.0
re = 6371220.0
rr = re * rad
dlon = abs(lonobs[2] - lonobs[1]) * rr
dx = dlon * np.cos(latobs * rad)
jlat = len(latobs)
dy = np.zeros(jlat, dtype=float)
# close enough
dy[0] = abs(lat[2] - lat[1]) * rr
dy[1:jlat - 2] = abs(lat[2:jlat - 1] - lat[0:jlat - 3]) * rr * 0.5
dy[jlat - 1] = abs(lat[jlat - 1] - lat[jlat - 2]) * rr
area_wgt = dx * dy #
is_SE = False
sum1 = 0
sum2 = 0
for j in range(0, jlat - 1):
for i in range(0, len(lonobs) - 1):
if (np.isnan(B[j][i]) != '--'):
sum1 = sum1 + area_wgt[j] * B[j][i]
sum2 = sum2 + area_wgt[j]
glb = sum1 / sum2
res.sfXArray = lonobs
res.sfYArray = latobs
res.mpLimitMode = 'LatLon'
res.mpMaxLonF = max(lonobs)
res.mpMinLonF = min(lonobs)
res.mpMinLatF = min(latobs)
res.mpMaxLatF = max(latobs)
res.tiMainString = 'GLB=' + str(glb)
p = Ngl.contour_map(wks, B, res)
if (iv == 0):
poly_res = Ngl.Resources()
poly_res.gsMarkerIndex = 16
poly_res.gsMarkerSizeF = 0.005
poly_res.gsMarkerColor = 'green'
dum = Ngl.add_polymarker(wks, p, lons, lats, poly_res)
plot.append(p)
if (np.mod(ncases + 1, 2) == 1):
Ngl.panel(wks, plot[:], [(ncases + 1) / 2 + 1, 2], pres)
else:
Ngl.panel(wks, plot[:], [(ncases + 1) / 2, 2], pres)
Ngl.frame(wks)
Ngl.destroy(wks)
# Ngl.end()
return plot2d
def draw_clm_plot (ptype,cseason, ncases, cases, casenames, nsite, lats, lons, filepath, filepathobs,casedir):
# ncases, the number of models
# cases, the name of models
# casename, the name of cases
# filepath, model output filepath
# filepathobs, filepath for observational data
# inptrs = [ncases]
if not os.path.exists(casedir):
os.mkdir(casedir)
if not os.path.exists(casedir+"/2D"):
os.mkdir(casedir+"/2D")
_Font = 25
interp = 2
extrap = False
mkres = Ngl.Resources()
mkres.gsMarkerIndex = 2
mkres.gsMarkerColor = "Red"
mkres.gsMarkerSizeF = 15.
infiles = ["" for x in range(ncases)]
ncdfs = ["" for x in range(ncases)]
varis = ["SOILWATER_10CM", "QBOT"]
varisobs = ["PRECT" ,"PRECT"]
alpha = ["A","B","C","D","E","F"]
nvaris = len(varis)
cunits = [""]
cscale = [1,1,1,86400000, 1, 1,1,100,100,1,1,1000,1,1,1,1]
cscaleobs = [1,1,1,1,1,1,1,1,1,1,1,1,1,1]
# cntrs = [[0 for col in range(11)] for row in range(nvaris)]
cntrs = np.zeros((nvaris,11),np.float32)
obsdataset= ["GPCP","GPCP", "NCEP", "ERAI", "CALIPSOCOSP","CALIPSOCOSP","NCEP","NCEP","NVAP"]
plotclm=["" for x in range(nvaris)]
for iv in range(0, nvaris):
# make plot for each field
if(varis[iv] == "SOILWATER_10CM" or varis[iv] == "QBOT" ):
cntrs[iv,:] = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
# Observational data
if(obsdataset[iv] =="CCCM"):
if(cseason == "ANN"):
fileobs = "/Users/guoz/databank/CLD/CCCm/cccm_cloudfraction_2007-"+cseason+".nc"
else:
fileobs = "/Users/guoz/databank/CLD/CCCm/cccm_cloudfraction_2007-2010-"+cseason+".nc"
else:
if (varisobs[iv] =="PRECT"):
fileobs = filepathobs+'/GPCP_'+cseason+'_climo.nc'
else:
fileobs = filepathobs + obsdataset[iv]+'_'+cseason+'_climo.nc'
# infiles[im]=filepath[im]+cases[im]+'/run/'+cases[im]+'_'+cseason+'_climo.nc'
inptrobs = Dataset(fileobs,'r')
latobs=inptrobs.variables['lat'][:]
lonobs=inptrobs.variables['lon'][:]
if (varisobs[iv] =="U10"):
B0=inptrobs.variables[varisobs[iv]][0,:,:]
B1=inptrobs.variables["V10"][0,:,:]
B=(B0*B0+B1*B1)
B=B * cscaleobs[iv]
B=np.sqrt(B)
else:
B=inptrobs.variables[varisobs[iv]][0,:,:]
B=B * cscaleobs[iv]
#************************************************
# create plot
#************************************************
plotname = casedir+'/2D/Land_'+varis[iv]+'_'+cseason
plotclm[iv] = 'Land_'+varis[iv]+'_'+cseason
wks= Ngl.open_wks(ptype,plotname)
Ngl.define_colormap(wks,"cmocean_thermal")
# ngl_define_colormap(wks,"prcp_1")
plot = []
textres = Ngl.Resources()
textres.txFontHeightF = 0.02 # Size of title.
textres.txFont = _Font
Ngl.text_ndc(wks,varis[iv],0.1,.97,textres)
pres = Ngl.Resources()
pres.nglMaximize = True
pres.nglPanelYWhiteSpacePercent = 5
pres.nglPanelXWhiteSpacePercent = 5
pres.nglPanelBottom = 0.20
pres.nglPanelTop = 0.9
pres.pmLabelBarWidthF = 0.8
pres.nglFrame = False
pres.nglPanelLabelBar = True # Turn on panel labelbar
pres.nglPanelLabelBarLabelFontHeightF = 0.015 # Labelbar font height
pres.nglPanelLabelBarHeightF = 0.0750 # Height of labelbar
pres.nglPanelLabelBarWidthF = 0.700 # Width of labelbar
pres.lbLabelFont = "helvetica-bold" # Labelbar font
pres.nglPanelTop = 0.935
pres.nglPanelFigureStrings = alpha
pres.nglPanelFigureStringsJust = "BottomRight"
res = Ngl.Resources()
res.nglDraw = False #-- don't draw plots
res.nglFrame = False
res.cnFillOn = True
res.cnFillMode = "RasterFill"
res.cnLinesOn = False
res.nglMaximize = True
res.mpFillOn = True
res.mpCenterLonF = 180
res.tiMainFont = _Font
res.tiMainFontHeightF = 0.025
res.tiXAxisString = ""
res.tiXAxisFont = _Font
res.tiXAxisFontHeightF = 0.025
res.tiYAxisString = ""
res.tiYAxisFont = _Font
res.tiYAxisOffsetXF = 0.0
res.tiYAxisFontHeightF = 0.025
res.tmXBLabelFont = _Font
res.tmYLLabelFont = _Font
res.tiYAxisFont = _Font
res.vpWidthF = 0.80 # set width and height
res.vpHeightF = 0.40
res.vpXF = 0.04
res.vpYF = 0.30
res.cnInfoLabelOn = False
res.cnFillOn = True
res.cnLinesOn = False
res.cnLineLabelsOn = False
res.lbLabelBarOn = False
res.mpFillOn = False
res.cnLevelSelectionMode = "ExplicitLevels"
res.cnLevels = cntrs[iv][:]
for im in range(0, ncases):
ncdfs[im] = './data/'+cases[im]+'_site_location.nc'
infiles[im]= filepath[im]+cases[im]+'/'+cases[im]+'_'+cseason+'_clm.nc'
inptrs = Dataset(infiles[im],'r') # pointer to file1
lat=inptrs.variables['lat'][:]
nlat=len(lat)
lon=inptrs.variables['lon'][:]
nlon=len(lon)
area=inptrs.variables['area'][:]
area_wgt = np.zeros(nlat)
sits=np.linspace(0,nsite-1,nsite)
ncdf= Dataset(ncdfs[im],'r')
n =ncdf.variables['n'][:]
idx_cols=ncdf.variables['idx_cols'][:]
if (varis[iv] == 'PRECT'):
A = inptrs.variables['PRECC'][0,:]+inptrs.variables['PRECL'][0,:]
else:
A = inptrs.variables[varis[iv]][0,:]
if (varis[iv] == 'FLUT'):
A = inptrs.variables['FLUT'][0,:]-inptrs.variables['FLNS'][0,:]
else:
A = inptrs.variables[varis[iv]][0,:]
if (varis[iv] == 'U10'):
A = inptrs.variables['U10'][0,:]*inptrs.variables['U10'][0,:]
A = np.sqrt(A)
else:
A = inptrs.variables[varis[iv]][0,:]
A_xy=A
A_xy = A_xy * cscale[iv]
ncdf.close()
inptrs.close()
if im == 0 :
dsizes = len(A_xy)
field_xy = [[0 for col in range(dsizes)] for row in range(ncases)]
field_xy[im][:] = A_xy
res.lbLabelBarOn = False
if(np.mod(im,2)==0):
res.tiYAxisOn = True
else:
res.tiYAxisOn = False
res.tiXAxisOn = False
res.sfXArray = lon
res.sfYArray = lat
res.mpLimitMode = "LatLon"
res.mpMaxLonF = max(lon)
res.mpMinLonF = min(lon)
res.mpMinLatF = min(lat)
res.mpMaxLatF = max(lat)
res.tiMainString = "GLB="+str(np.sum(A_xy[:]*area[:]/np.sum(area)))
textres.txFontHeightF = 0.015
Ngl.text_ndc(wks,alpha[im]+" "+ casenames[im],0.3,.135-im*0.03,textres)
# varM = A_xy
# for ix in range(0, nlon-1):
# if ( np.isnan(A_xy[ix]) or not np.isfinite(A_xy[ix])):
# varM[ix]=0.0
p = Ngl.contour_map(wks,A_xy,res)
plot.append(p)
res.lbLabelFont = _Font
res.tiYAxisOn = True
res.tiXAxisOn = True
res.tiXAxisFont = _Font
rad = 4.0*np.arctan(1.0)/180.0
re = 6371220.0
rr = re*rad
dlon = abs(lonobs[2]-lonobs[1])*rr
dx = dlon* np.cos(latobs*rad)
jlat = len(latobs )
dy = np.zeros(jlat,dtype=float)
# close enough
dy[0] = abs(lat[2]-lat[1])*rr
dy[1:jlat-2] = abs(lat[2:jlat-1]-lat[0:jlat-3])*rr*0.5
dy[jlat-1] = abs(lat[jlat-1]-lat[jlat-2])*rr
area_wgt = dx*dy #
is_SE= False
sum1 = 0
sum2 = 0
for j in range(0, jlat-1):
for i in range(0, len(lonobs)-1):
if (np.isnan(B[j][i]) != "--"):
sum1= sum1+area_wgt[j]*B[j][i]
sum2= sum2+area_wgt[j]
glb=sum1/sum2
res.sfXArray = lonobs
res.sfYArray = latobs
res.mpLimitMode = "LatLon"
res.mpMaxLonF = max(lonobs)
res.mpMinLonF = min(lonobs)
res.mpMinLatF = min(latobs)
res.mpMaxLatF = max(latobs)
res.tiMainString = "GLB="+str(glb)
p =Ngl.contour_map(wks,B,res)
plot.append(p)
if(np.mod(ncases+1,2)==1):
Ngl.panel(wks,plot[:],[(ncases+1)/2+1,2],pres)
else:
Ngl.panel(wks,plot[:],[(ncases+1)/2,2],pres)
Ngl.frame(wks)
Ngl.destroy(wks)
# Ngl.end()
return plotclm
# directory. (The Ngl.pynglpath function is used to determine the
# directory.)
#
# Make sure the rangs database exists before we try to generate this frame.
#
rangs_dir = Ngl.pynglpath("rangs") # Location of RANGS dir.
if (os.path.exists(rangs_dir)):
nmap = 3
else:
nmap = 2
print("Sorry, you do not have the RANGS database installed.")
print("Will not generate the third frame of this example.")
plot = []
for i in range(nmap):
res.mpDataBaseVersion = map_res[i]
res.tiMainString = "Resolution = '" + map_res[i] + "'"
plot.append(Ngl.contour_map(wks, fsd, res)) # Create plot, but don't draw
#
# Set some panel resources: a common labelbar and title.
# "[1,3]" indicates 1 row, 3 columns.
#
panelres = Ngl.Resources()
panelres.txString = "Comparison of coastline resolutions"
panelres.nglPanelLabelBar = True # Common labelbar
Ngl.panel(wks, plot, [1, 3], panelres)
Ngl.end()
def silhs_prf (ptype,cseason, ncases, cases, casenames, nsite, lats, lons, filepath, filepathobs,casedir):
# ncases, the number of models
# cases, the name of models
# casename, the name of cases
# filepath, model output filepath
# filepathobs, filepath for observational data
# inptrs = [ncases]
if not os.path.exists(casedir):
os.mkdir(casedir)
_Font = 25
interp = 2
extrap = False
mkres = Ngl.Resources()
mkres.gsMarkerIndex = 2
mkres.gsMarkerColor = "Red"
mkres.gsMarkerSizeF = 15.
infiles = ["" for x in range(ncases)]
ncdfs = ["" for x in range(ncases)]
nregions = nsite
varis = [ "SILHS_CLUBB_PRECIP_FRAC","SILHS_CLUBB_ICE_SS_FRAC","HR","AWNC","AWNI","ADSNOW","ANSNOW","AQSNOW","RHW","QRS","QRL","AQRAIN" ]
nvaris = len(varis)
cunits = ["%","mba/day","g/kg","g/kg","K", "%", "m/s", "g/kg", "m/s", "m/s","K","m" ]
cscale = [1, 1, 1, 1, 1., 1, 1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1 ]
plotsilhs=["" for x in range(nsite)]
for ire in range (0, nsite):
if not os.path.exists(casedir+'/'+str(lons[ire])+'E_'+str(lats[ire])+'N'):
os.mkdir(casedir+'/'+str(lons[ire])+'E_'+str(lats[ire])+'N')
plotname = casedir+'/'+str(lons[ire])+'E_'+str(lats[ire])+'N/silhs_'+str(lons[ire])+"E_"+str(lats[ire])+"N_"+cseason
plotsilhs[ire] = 'CLUBB_standard_'+str(lons[ire])+"E_"+str(lats[ire])+"N_"+cseason
wks= Ngl.open_wks(ptype,plotname)
Ngl.define_colormap(wks,"GMT_paired")
plot = []
res = Ngl.Resources()
res.nglDraw = False
res.nglFrame = False
res.lgLabelFontHeightF = .012 # change font height
res.lgPerimOn = False # no box around
res.vpWidthF = 0.30 # set width and height
res.vpHeightF = 0.30
res.txFontHeightF = .01
#res.vpXF = 0.04
# res.vpYF = 0.30
res.tmYLLabelFont = _Font
res.tmXBLabelFont = _Font
res.tmXBLabelFontHeightF = 0.005
res.tmXBLabelFontThicknessF = 1.0
res.tmXBLabelAngleF = 45
res.xyMarkLineMode = "Lines"
res.xyLineThicknesses = [2.0, 2.0, 2.0, 2.0, 2.0, 2.0,2.,2.,2.,2.,2,2,2,2,2,2,2]
res.xyDashPatterns = np.arange(0,24,1)
# res.xyMarkers = np.arange(16,40,1)
# res.xyMarkerSizeF = 0.005
pres = Ngl.Resources()
pres.nglMaximize = True
pres.txString = str(lons[ire])+"E,"+str(lats[ire])+"N"
pres.txFont = _Font
pres.nglPanelYWhiteSpacePercent = 5
pres.nglPanelXWhiteSpacePercent = 5
pres.nglPanelTop = 0.93
txres = Ngl.Resources()
txres.txFontHeightF = 0.01
for iv in range (0, nvaris):
if(iv == nvaris-1):
res.pmLegendDisplayMode = "ALWAYS"
res.xyExplicitLegendLabels = casenames[:]
res.pmLegendSide = "top"
res.pmLegendParallelPosF = 0.6
res.pmLegendOrthogonalPosF = -0.5
res.pmLegendWidthF = 0.10
res.pmLegendHeightF = 0.10
res.lgLabelFontHeightF = .02
res.lgLabelFontThicknessF = 1.5
res.lgPerimOn = False
else:
res.pmLegendDisplayMode = "NEVER"
for im in range (0,ncases):
ncdfs[im] = './data/'+cases[im]+'_site_location.nc'
infiles[im]= filepath[im]+cases[im]+'/'+cases[im]+'_'+cseason+'_climo.nc'
inptrs = Dataset(infiles[im],'r') # pointer to file1
lat=inptrs.variables['lat'][:]
nlat=len(lat)
lon=inptrs.variables['lon'][:]
nlon=len(lon)
lev=inptrs.variables['ilev'][:]
nlev=len(lev)
ncdf= Dataset(ncdfs[im],'r')
n =ncdf.variables['n'][:]
idx_cols=ncdf.variables['idx_cols'][:,:]
ncdf.close()
if (im ==0):
A_field = np.zeros((ncases,nlev),np.float32)
for subc in range( 0, n[ire]):
npoint=idx_cols[ire,n[subc]-1]-1
if (varis[iv] == 'THETA'):
tmp = inptrs.variables['T'][0,:,npoint]
hyam =inptrs.variables['hyam'][:]
hybm =inptrs.variables['hybm'][:]
ps=inptrs.variables['PS'][0,npoint]
ps=ps
p0=inptrs.variables['P0']
pre = np.zeros((nlev),np.float32)
for il in range (0, nlev):
pre[il] = hyam[il]*p0 + hybm[il] * ps
tmp[il] = tmp[il] * (100000/pre[il])**0.286
theunits=str(cscale[iv])+inptrs.variables['T'].units
else:
tmp=inptrs.variables[varis[iv]][0,:,npoint]
theunits=str(cscale[iv])+inptrs.variables[varis[iv]].units
A_field[im,:] = (A_field[im,:]+tmp[:]/n[ire]).astype(np.float32 )
A_field[im,:] = A_field[im,:] *cscale[iv]
inptrs.close()
res.tiMainString = varis[iv]+" x"+theunits
res.trXMinF = min(np.min(A_field[0, :]))#,np.min(B))
res.trXMaxF = max(np.max(A_field[0, :]))#,np.max(B))
if(varis[iv] == "THETA"):
res.trXMinF = 280.
res.trXMaxF = 400.
if(varis[iv] == "CLOUD" or varis[iv] =="RELHUM") :
res.trXMinF = 0.
res.trXMaxF = 100.
if(varis[iv] == "T") :
res.trXMinF = 180
res.trXMaxF = 300
if(varis[iv] == "U") :
res.trXMinF = -40
res.trXMaxF = 40
res.trYReverse = True
res.xyLineColors = np.arange(2,20,1)
res.xyMarkerColors = np.arange(2,20,2)
p = Ngl.xy(wks,A_field,lev,res)
plot.append(p)
Ngl.panel(wks,plot[:],[nvaris/3,3],pres)
txres = Ngl.Resources()
txres.txFontHeightF = 0.020
Ngl.text_ndc(wks,"SILHS VAR at"+ str(lons[ire])+"E,"+str(lats[ire])+"N",0.5,0.05,txres)
Ngl.frame(wks)
Ngl.destroy(wks)
return plotsilhs
txres = Ngl.Resources()
txres.txJust = "BottomCenter"
txres.txFontHeightF = 0.02
Ngl.text_ndc(wks, title, 0.5, top + 0.01, txres)
# # Loop across plots and panel them on one page
# for n in range(0,1):
# # Define location in a unit square for each set of plots.
# add 子图序号
pres.tiMainFont = "Helvetica-Bold"
pres.nglPanelFigureStringsPerimOn = False
pres.nglPanelFigureStringsJust = "TopLeft"
# pres.nglPanelFigureStringsFont = "Helvetica-Bold"
pres.nglPanelFigureStringsOrthogonalPosF = -0.66
pres.nglPanelFigureStringsParallelPosF = -0.525
pres.nglPanelFigureStringsFontHeightF = 0.017
pres.nglPanelFigureStrings = figData[3]['seqNum']
pres.nglPanelTop = top - (0 * height) # leave room for title
pres.nglPanelBottom = top - (f_row * height)
pres.nglPanelYWhiteSpacePercent = 3
Ngl.panel(wks, plots[0:nplots + 1], [f_row, f_col], pres)
# plot = Ngl.contour_map(wks, plotData, res)
# Ngl.draw(plot)
Ngl.frame(wks)
Ngl.destroy(wks)
# Ngl.end()
def plotline(nlines,plotin,yearsin,nsep,title,Datatitle,figtitlein,colormap,xString,yString,unit):
wkres = Ngl.Resources()
wkres.wkColorMap = colormap
wks_type = "eps"
wks = Ngl.open_wks(wks_type,figtitlein,wkres)
res = Ngl.Resources()
plot = []
res.tiXAxisString = xString
res.tiYAxisString = yString
for iline in range(0,nlines):
yearsplot = yearsin[iline]
print yearsplot
# nyearsin = len(yearsplot)
# yearnums = range(0,nyearsin)
A = np.array(yearsplot)
regress = (np.zeros((5,nsep),np.float))
for ibin in range(0,nsep):
if ibin == 0:
if (plotdensity):
res.tiYAxisString = "frequency"
else:
res.tiYAxisString = "number of events"
else:
res.tiYAxisString = ""
linreg = plotin[iline][ibin][:]
print A.shape
print linreg.shape
regress[:,ibin] = stats.linregress(A,linreg)
if ibin == nsep -1:
res.tiMainString = '{:^80}'.format(' >' + '{:2.1g}'.format(tbound1[ibin]) + unit + '; p=' + '{:5.3f}'.format(regress[3,ibin]) + " ")
else:
res.tiMainString = '{:^80}'.format('{:2.1g}'.format(tbound1[ibin]) + '-' + '{:2.1g}'.format(tbound2[ibin]) + unit + '; p=' + '{:5.3f}'.format(regress[3,ibin]))
plot.append(Ngl.xy(wks,yearsplot,plotin[iline][ibin,:],res))
panelres = Ngl.Resources()
panelres.nglPanelLabelBar = True
panelres.nglPanelYWhiteSpacePercent = 8.
panelres.nglPanelXWhiteSpacePercent = 0.0
panelres.nglPanelLabelBar = False # Turn on panel labelbar
panelres.nglPanelTop = 1.0
panelres.nglPanelBottom = 0.00
panelres.nglPanelLeft = 0.0
panelres.nglPanelRight = 1.0
panelres.nglPaperOrientation = "Portrait"
panelres.nglScale = False
panelres.nglMaximize = True
#txres = Ngl.Resources()
#txres.txFontHeightF = 0.012
#Ngl.text_ndc(wks,'Annual timeseries of global number of events of various scales from' + Datatitle,0.5,0.94,txres)
Ngl.panel(wks,plot,[nlines,float(nbounds)],panelres)
print 'panelled'
def plotmap(plotvars1,plotvars2,
plotmin1,plotmax1,plotmin2,plotmax2,
vartitle1,vartitle2,
title,
figtitle,
minlon,maxlon,minlat,maxlat,
FillValue,panellabels = [],
labelbarlabels = [],
labelbarlabels2 = []):
nplots = plotvars1.shape[0]
wkres = Ngl.Resources()
wkres.wkColorMap = "WhiteBlue"
wks_type = "eps"
wks = Ngl.open_wks(wks_type,figtitle,wkres)
# if lons start negative, shift everything over so there isn't a line down
# the middle of the Pacific
lons1 = plotvars1.lon.values
lons2 = plotvars2.lon.values
lats1 = plotvars1.lat.values
lats2 = plotvars2.lat.values
if lons1[0] < 0:
#nlonhalf1 = len(lons1)/2
#lonsnew1 = np.zeros(lons1.shape,np.float)
#lonsnew1[0:nlonhalf1] = lons1[nlonhalf1:nlons1]
#lonsnew1[nlonhalf1:nlons1] = lons1[0:nlonhalf1] + 360.0
lonsnew1 = shiftlonlons(lons1,len(lons1))
lonsnew2 = shiftlonlons(lons2,len(lons2))
for iplot in range(0,nplots):
plotvars1[iplot] = shiftlons(plotvars1[iplot],len(lons1))
plotvars2[iplot] = shiftlons(plotvars2[iplot],len(lons2))
else:
lonsnew1 = lons1
lonsnew2 = lons2
# initialize plotting resources
res1 = Ngl.Resources()
res1 = initcontourplot(res1,minlat,minlon,maxlat,maxlon,lats1,lonsnew1)
res1.sfMissingValueV = FillValue
res1.lbOrientation = "Vertical"
# including some font heights
res1.lbLabelFontHeightF = 0.01
res1.lbTitleFontHeightF = 0.01
res1.tiMainFontHeightF = 0.015
res1.lbTitlePosition = 'Bottom'
res1.lbBottomMarginF = 0.0
# initialize plotting resources
res2 = Ngl.Resources()
res2 = initcontourplot(res2,minlat,minlon,maxlat,maxlon,lats2,lonsnew2)
res2.sfMissingValueV = FillValue
res2.lbOrientation = "Vertical"
# including some font heights
res2.lbLabelFontHeightF = 0.01
res2.lbTitleFontHeightF = 0.01
res2.tiMainFontHeightF = 0.008
res2.lbTitlePosition = 'Bottom'
res2.lbBottomMarginF = 0.0
# turn off grid lines
res1.mpGridAndLimbOn = False
res2.mpGridAndLimbOn = False
# initialize plotting array
toplot = []
# fill plotting array
for iplot in range(0,nplots):
tempplot = plotvars1[iplot].values
tempplot[np.where(np.isnan(tempplot))] = FillValue
# update plot resources with correct lat/lon
res1.cnMinLevelValF = plotmin1[iplot]
res1.cnMaxLevelValF = plotmax1[iplot]
res1.cnLevelSpacingF = ((plotmax1[iplot]-plotmin1[iplot])/10.0)
res1.tiMainString = (vartitle1[iplot])
if panellabels != []:
res1.lbTitleString = labelbarlabels[iplot]
res1.tiYAxisString = panellabels[iplot] # Y axes label.
toplot.append(Ngl.contour_map(wks,tempplot,res1))
tempplot = plotvars2[iplot].values
tempplot[np.where(np.isnan(tempplot))] = FillValue
res2.cnMinLevelValF = plotmin2[iplot] # contour levels.
res2.cnMaxLevelValF = plotmax2[iplot]
res2.cnLevelSpacingF = ((plotmax2[iplot]-plotmin2[iplot])/10.0)
res2.tiMainString = vartitle2[iplot]
if panellabels != []:
res2.lbTitleString = labelbarlabels2[iplot]
res2.tiYAxisString = " " # so plots are the same
# size
toplot.append(Ngl.contour_map(wks,tempplot,res2))
textres = Ngl.Resources()
textres.txFontHeightF = 0.015
Ngl.text_ndc(wks,title,0.5,0.87,textres)
panelres = Ngl.Resources()
panelres.nglPanelLabelBar = True
panelres.nglPanelYWhiteSpacePercent = 0.
panelres.nglPanelXWhiteSpacePercent = 0.
panelres.nglPanelLabelBar = False # Turn on panel labelbar
if nplots > 5:
panelres.nglPanelTop = 0.8
panelres.nglPanelBottom = 0.15
else:
panelres.nglPanelTop = 0.95
panelres.nglPanelBottom = 0.01
panelres.nglPanelLeft = 0.01
panelres.nglPanelRight = 0.99
panelres.nglPanelFigureStrings = (
['a.','b.','c.','d.','e.','f.','g.','h.','i.','j.','k.','l.','m.','n.','o.','p.'])
panelres.nglPanelFigureStringsJust = "TopLeft"
panelres.nglPanelFigureStringsFontHeightF = 0.008
panelres.nglPanelFigureStringsParallelPosF = -0.55
panelres.nglPanelFigureStringsOrthogonalPosF = -0.7
panelres.nglPanelFigureStringsPerimOn = False # turn off boxes
#panelres.amJust = "TopLeft"
panelres.nglPaperOrientation = "Auto"
plot = Ngl.panel(wks,toplot,[nplots,2],panelres)
def clubb_skw_prf(ptype, cseason, ncases, cases, casenames, nsite, lats, lons,
filepath, filepathobs, casedir, dofv):
# ncases, the number of models
# cases, the name of models
# casename, the name of cases
# filepath, model output filepath
# filepathobs, filepath for observational data
# inptrs = [ncases]
if not os.path.exists(casedir):
os.mkdir(casedir)
_Font = 25
interp = 2
extrap = False
mkres = Ngl.Resources()
mkres.gsMarkerIndex = 2
mkres.gsMarkerColor = "Red"
mkres.gsMarkerSizeF = 15.
infiles = ["" for x in range(ncases)]
ncdfs = ["" for x in range(ncases)]
nregions = nsite
varis = [
"C6rt_Skw_fnc", "C11_Skw_fnc", "C1_Skw_fnc", "C7_Skw_fnc", "Lscale",
"Richardson_num", "Kh_zm", "tau_zm", "Skw_velocity"
]
varisobs = [
"CC_ISBL", "OMEGA", "SHUM", "CLWC_ISBL", "THETA", "RELHUM", "U",
"CIWC_ISBL", "T"
]
nvaris = len(varis)
cunits = [
"%", "mba/day", "g/kg", "g/kg", "K", "%", "m/s", "g/kg", "m/s", "m/s",
"K", "m"
]
cscale = [
1, 1, 1, 1, 1., 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1
]
cscaleobs = [100, 1, 1, 1000, 1., 1, 1, 1000, 1, 1, 1, 1, 1, 1, 1]
obsdataset = [
"ERAI", "ERAI", "ERAI", "ERAI", "ERAI", "ERAI", "ERAI", "ERAI", "ERAI",
"ERAI"
]
plotskw = ["" for x in range(nsite)]
for ire in range(0, nsite):
if not os.path.exists(casedir + '/' + str(lons[ire]) + 'E_' +
str(lats[ire]) + 'N'):
os.mkdir(casedir + '/' + str(lons[ire]) + 'E_' + str(lats[ire]) +
'N')
plotname = casedir + '/' + str(lons[ire]) + 'E_' + str(
lats[ire]) + 'N/CLUBB_skewfunc_' + str(lons[ire]) + "E_" + str(
lats[ire]) + "N_" + cseason
plotskw[ire] = 'CLUBB_skewfunc_' + str(lons[ire]) + "E_" + str(
lats[ire]) + "N_" + cseason
wks = Ngl.open_wks(ptype, plotname)
Ngl.define_colormap(wks, "GMT_paired")
plot = []
res = Ngl.Resources()
res.nglDraw = False
res.nglFrame = False
res.lgLabelFontHeightF = .012 # change font height
res.lgPerimOn = False # no box around
res.vpWidthF = 0.30 # set width and height
res.vpHeightF = 0.30
#res.vpXF = 0.04
# res.vpYF = 0.30
res.tmYLLabelFont = _Font
res.tmXBLabelFont = _Font
res.tmXBLabelFontHeightF = 0.01
res.tmXBLabelFontThicknessF = 1.0
# res.tmXBLabelAngleF = 45
res.xyMarkLineMode = "Lines"
res.xyLineThicknesses = [
3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3., 3., 3., 3., 3, 3, 3, 3, 3, 3, 3
]
res.xyDashPatterns = np.arange(0, 24, 1)
# res.xyMarkers = np.arange(16,40,1)
# res.xyMarkerSizeF = 0.005
pres = Ngl.Resources()
# pres.nglMaximize = True
pres.nglFrame = False
pres.txFont = _Font
pres.nglPanelYWhiteSpacePercent = 5
pres.nglPanelXWhiteSpacePercent = 5
pres.nglPanelTop = 0.88
pres.wkWidth = 2500
pres.wkHeight = 2500
for iv in range(0, nvaris):
if (iv == nvaris - 1):
res.pmLegendDisplayMode = "NEVER"
res.xyExplicitLegendLabels = casenames[:]
res.pmLegendSide = "top"
res.pmLegendParallelPosF = 0.6
res.pmLegendOrthogonalPosF = -0.5
res.pmLegendWidthF = 0.10
res.pmLegendHeightF = 0.10
res.lgLabelFontHeightF = .02
res.lgLabelFontThicknessF = 1.5
res.lgPerimOn = False
else:
res.pmLegendDisplayMode = "NEVER"
# if(obsdataset[iv] =="CCCM"):
# if(cseason == "ANN"):
# fileobs = "/Users/guoz/databank/CLD/CCCm/cccm_cloudfraction_2007-"+cseason+".nc"
# else:
# fileobs = "/Users/guoz/databank/CLD/CCCm/cccm_cloudfraction_2007-2010-"+cseason+".nc"
# inptrobs = Dataset(fileobs,'r')
# B=inptrobs.variables[varisobs[iv]][:,(lats[ire]),(lons[ire])]
# else:
# if (varisobs[iv] =="PRECT"):
# fileobs = filepathobs+'/GPCP_'+cseason+'_climo.nc'
# else:
# fileobs = filepathobs + obsdataset[iv]+'_'+cseason+'_climo.nc'
# inptrobs = Dataset(fileobs,'r')
# if (varisobs[iv] =="THETA"):
# B = inptrobs.variables['T'][0,:,(lats[ire]),(lons[ire])]
# pre1 = inptrobs.variables['lev'][:]
# for il1 in range (0, len(pre1)):
# B[il1] = B[il1]*(1000/pre1[il1])**0.286
# else:
# pre1 = inptrobs.variables['lev'][:]
# B = inptrobs.variables[varisobs[iv]][0,:,(lats[ire]),(lons[ire])]
#
# B[:]=B[:] * cscaleobs[iv]
for im in range(0, ncases):
ncdfs[im] = './data/' + cases[im] + '_site_location.nc'
infiles[im] = filepath[im] + '/' + cases[
im] + '_' + cseason + '_climo.nc'
inptrs = Dataset(infiles[im], 'r') # pointer to file1
lat = inptrs.variables['lat'][:]
nlat = len(lat)
lon = inptrs.variables['lon'][:]
nlon = len(lon)
lev = inptrs.variables['ilev'][:]
nlev = len(lev)
ncdf = Dataset(ncdfs[im], 'r')
n = ncdf.variables['n'][:]
idx_cols = ncdf.variables['idx_cols'][:, :]
if (dofv):
idx_lats = ncdf.variables['idx_coord_lat'][:, :]
idx_lons = ncdf.variables['idx_coord_lon'][:, :]
ncdf.close()
if (im == 0):
A_field = np.zeros((ncases, nlev), np.float32)
for subc in range(0, n[ire]):
npoint = idx_cols[ire, n[subc] - 1] - 1
if (dofv):
npointlat = idx_lats[ire, 0]
npointlon = idx_lons[ire, 0]
if (dofv):
tmp = inptrs.variables[varis[iv]][0, :, npointlat,
npointlon]
else:
tmp = inptrs.variables[varis[iv]][0, :, npoint]
theunits = str(
cscale[iv]) + inptrs.variables[varis[iv]].units
A_field[im, :] = (A_field[im, :] + tmp[:] / n[ire]).astype(
np.float32)
A_field[im, :] = A_field[im, :] * cscale[iv]
inptrs.close()
res.tiMainString = varis[iv] + " " + theunits
# res.trXMinF = min(np.min(A_field[0, :]))
# res.trXMaxF = max(np.max(A_field[0, :]))
res.trYReverse = True
res.xyLineColors = np.arange(3, 20, 2)
res.xyMarkerColors = np.arange(2, 20, 2)
p = Ngl.xy(wks, A_field, lev, res)
# res.trYReverse = False
# res.xyLineColors = ["black"]
# pt = Ngl.xy(wks,B,pre1,res)
# Ngl.overlay(p,pt)
plot.append(p)
pres.txString = "Skewness Functions at" + str(lons[ire]) + "E," + str(
lats[ire]) + "N"
txres = Ngl.Resources()
txres.txFontHeightF = 0.020
txres.txFont = _Font
Ngl.text_ndc(
wks, "Skewness Functions at" + str(lons[ire]) + "E," +
str(lats[ire]) + "N", 0.5, 0.92 + ncases * 0.01, txres)
Common_functions.create_legend(wks, casenames, 0.02,
np.arange(3, 20,
2), 0.1, 0.89 + ncases * 0.01)
Ngl.panel(wks, plot[:], [nvaris / 3, 3], pres)
Ngl.frame(wks)
Ngl.destroy(wks)
return plotskw
# Resources for panelling
pres = Ngl.Resources()
pres.nglFrame = False
pres.nglPanelLabelBar = True
# Calculate start Y position for first row of plots
height = 0.45 # we know this will be height of small plots
extra = 1.0 - (height)
top = 1.0 - (extra / 2.) # 子图第一行所在的高度
# Draw a title before we draw plots
title = figData[3]['headLineTxt']
txres = Ngl.Resources()
txres.txJust = "BottomCenter"
txres.txFontHeightF = 0.02
Ngl.text_ndc(wks, title, 0.5, top + 0.01, txres)
# Define location in a unit square for each set of plots.
pres.nglPanelTop = top
pres.nglPanelBottom = top - height
Ngl.panel(wks, plots[0:2], [1, 2], pres)
# plot = Ngl.contour_map(wks, plotData, res)
# Ngl.draw(plot)
Ngl.frame(wks)
Ngl.destroy(wks)
# Ngl.end()
def draw_clubb_tau(ptype, cseason, ncases, cases, casenames, nsite, lats, lons,
filepath, filepathobs, casedir, varis, vname, cscale,
chscale, pname):
# ncases, the number of models
# cases, the name of models
# casename, the name of cases
# filepath, model output filepath
# filepathobs, filepath for observational data
# inptrs = [ncases]
if not os.path.exists(casedir):
os.mkdir(casedir)
_Font = 25
interp = 2
extrap = False
mkres = Ngl.Resources()
mkres.gsMarkerIndex = 2
mkres.gsMarkerColor = "Red"
mkres.gsMarkerSizeF = 15.
infiles = ["" for x in range(ncases)]
ncdfs = ["" for x in range(ncases)]
nregions = nsite
nvaris = len(varis)
plottau = ["" for x in range(nsite * ncases)]
alphas = [
'a) ', 'b) ', 'c) ', 'd) ', 'e) ', 'f) ', 'g) ', 'h) ', 'i) ', 'j) ',
'k) ', 'l) ', 'm) ', 'n) ', 'o) ', 'p) ', 'q) ', 'r) ', 's) ', 't) ',
'u) ', 'v) ', 'w) ', 'x) ', 'y) ', 'z) '
]
for ire in range(0, nsite):
for im in range(0, ncases):
if not os.path.exists(casedir + '/' + str(lons[ire]) + 'E_' +
str(lats[ire]) + 'N'):
os.mkdir(casedir + '/' + str(lons[ire]) + 'E_' +
str(lats[ire]) + 'N')
plotname = casedir + '/' + str(lons[ire]) + 'E_' + str(
lats[ire]) + 'N/' + pname + '_' + casenames[im] + "_" + str(
lons[ire]) + "E_" + str(lats[ire]) + "N_" + cseason
plottau[im +
ncases * ire] = pname + '_' + casenames[im] + "_" + str(
lons[ire]) + "E_" + str(lats[ire]) + "N_" + cseason
wks = Ngl.open_wks(ptype, plotname)
Ngl.define_colormap(wks, "radar")
plot = []
res = Ngl.Resources()
res.nglMaximize = False
res.nglDraw = False
res.nglFrame = False
res.vpWidthF = 0.30 # set width and height
res.vpHeightF = 0.30
# if (lats[ire] > 0 and lons[ire]!=240 ):
# res.trYMinF = 400.
# res.trYMaxF = 1000.
# else:
res.trYMinF = 100.
res.trYMaxF = 1000.
res.tiMainFont = _Font
res.tmYLLabelFont = _Font
res.tmXBLabelFont = _Font
res.tiYAxisFont = _Font
res.tiXAxisFont = _Font
res.tmXBLabelFontHeightF = 0.01
res.tmXBLabelFontThicknessF = 1.0
res.xyMarkLineMode = "MarkLines"
res.xyLineThicknesses = [
3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3., 2., 2., 2., 2, 2, 2, 2, 2, 2,
2
]
res.xyDashPatterns = np.arange(0, 24, 1)
res.xyMarkers = np.arange(16, 40, 1)
res.xyMarkerSizeF = 0.005
res.pmLegendDisplayMode = "Never"
res.pmLegendSide = "top" # Change location of
res.pmLegendParallelPosF = 0.75 # move units right
res.pmLegendOrthogonalPosF = -0.65 # more neg = down
res.pmLegendWidthF = 0.1 # Change width and
res.pmLegendHeightF = 0.15 # height of legend.
res.lgLabelFontHeightF = .02 # change font height
res.lgLabelFontThicknessF = 1.
# res.lgBoxMinorExtentF = 0.2
res.lgPerimOn = True
res.tiYAxisString = "Pressure [hPa]"
res.trYReverse = True
pres = Ngl.Resources()
pres.nglFrame = False
pres.txFont = _Font
pres.nglPanelYWhiteSpacePercent = 5
pres.nglPanelXWhiteSpacePercent = 5
pres.nglPanelTop = 0.93
pres.txFont = _Font
pres.nglMaximize = False
pres.txFont = _Font
pres.nglPanelTop = 0.935
pres.nglPanelFigureStrings = alphas
pres.nglPanelFigureStringsJust = 'Topright'
pres.nglPanelFigureStringsFontHeightF = 0.015
for iv in range(0, nvaris):
if (varis[iv] == 'tau_no_N2_zm'):
budget_ends = ['tau_no_N2_zm', 'bkgnd', 'sfc', 'shear']
budget_name = [
'1/~F8~t~N~~F10~~B~noN2~N~',
'1/~F8~t~N~~F10~~B~bkgnd~N~',
'1/~F8~t~N~~F10~~B~surf~N~',
'1/~F8~t~N~~F10~~B~shear~N~'
]
nterms = len(budget_ends)
if (varis[iv] == 'tau_xp2_zm'):
budget_ends = ['tau_xp2_zm', 'tau_no_N2_zm']
budget_name = [
"1/~F8~t~N~~F10~~B~x'~S~2~N~~N~",
'1/~F8~t~N~~F10~~B~noN2~N~'
]
nterms = len(budget_ends)
if (varis[iv] == 'tau_wp2_zm'):
budget_ends = ['tau_wp2_zm', 'tau_no_N2_zm', 'bvpos']
budget_name = [
"1/~F8~t~N~~F10~~B~w'~S~2~N~~N~",
'1/~F8~t~N~~F10~~B~noN2~N~', '1/~F8~t~N~~F10~~B~bv~N~'
]
nterms = len(budget_ends)
if (varis[iv] == 'tau_wpxp_zm'):
budget_ends = [
'tau_wpxp_zm', 'tau_no_N2_zm', 'bvpos', 'clear'
]
budget_name = [
"1/~F8~t~N~~F10~~B~w'x'~N~",
"1/~F8~t~N~~F10~~B~noN2~N~", '1/~F8~t~N~~F10~~B~bv~N~',
'1/~F8~t~N~~F10~~B~clr~N~'
]
nterms = len(budget_ends)
if (varis[iv] == 'tau_wp3_zm'):
budget_ends = [
'tau_wpxp_zm', 'tau_no_N2_zm', 'bvpos', 'clear'
]
budget_name = [
"1/~F8~t~N~~F10~~B~w'x'~N~",
'1/~F8~t~N~~F10~~B~noN2~N~', '1/~F8~t~N~~F10~~B~bv~N~',
'1/~F8~t~N~~F10~~B~clr~N~'
]
nterms = len(budget_ends)
ncdfs[im] = './data/' + cases[im] + '_site_location.nc'
infiles[im] = filepath[im] + cases[im] + '/' + cases[
im] + '_' + cseason + '_climo.nc'
inptrs = Dataset(infiles[im], 'r') # pointer to file1
lat = inptrs.variables['lat'][:]
nlat = len(lat)
lon = inptrs.variables['lon'][:]
nlon = len(lon)
ilev = inptrs.variables['ilev'][:]
nilev = len(ilev)
ncdf = Dataset(ncdfs[im], 'r')
n = ncdf.variables['n'][:]
idx_cols = ncdf.variables['idx_cols'][:, :]
ncdf.close()
A_field = np.zeros((nterms, nilev), np.float32)
if (varis[iv] == 'tau_no_N2_zm' or varis[iv] == 'tau_wp2_zm'
or varis[iv] == 'tau_xp2_zm'
or varis[iv] == 'tau_wp3_zm'
or varis[iv] == 'tau_wpxp_zm'):
theunits = str(chscale[iv]) + '~F10~' + inptrs.variables[
varis[iv]].units + '~S~-1~N~'
else:
theunits = str(
chscale[iv]) + '~F10~' + inptrs.variables[varis[iv] +
'_bt'].units
res.tiXAxisString = '1/~F8~t~N~~F25~~B~' + vname[
iv] + "~N~ " + ' Unit= ' + theunits
res1 = Ngl.Resources()
res1 = res
for it in range(0, nterms):
for subc in range(0, n[ire]):
npoint = idx_cols[ire, n[subc] - 1] - 1
if (varis[iv] == 'tau_wp2_zm'
or varis[iv] == 'tau_xp2_zm'
or varis[iv] == 'tau_wp3_zm'
or varis[iv] == 'tau_wpxp_zm'
or varis[iv] == 'tau_no_N2_zm'):
varis_tau = budget_ends[it]
if ( varis_tau == 'bkgnd' or varis_tau == 'shear' \
or varis_tau == 'sfc' ):
tmp = inptrs.variables['invrs_tau_' +
varis_tau][0, :, npoint]
if (varis_tau == 'tau_no_N2_zm'):
tmp = inptrs.variables[varis_tau][0, :, npoint]
tmp = 1 / tmp
if (varis[iv] == 'tau_wp2_zm'):
if (varis_tau == 'tau_wp2_zm'):
tmp = inptrs.variables[varis_tau][0, :,
npoint]
tmp = 1 / tmp
if (varis_tau == 'bvpos'):
tmp0 = inptrs.variables['tau_wp2_zm'][
0, :, npoint]
tmp1 = inptrs.variables['tau_no_N2_zm'][
0, :, npoint]
tmp = tmp0
tmp = 1 / tmp0 - 1 / tmp1
if (varis[iv] == 'tau_zm'):
if (varis_tau == 'tau_zm'):
tmp = inptrs.variables[varis_tau][0, :,
npoint]
tmp = 1 / tmp
if (varis_tau == 'bvpos'):
tmp0 = inptrs.variables['tau_zm'][0, :,
npoint]
tmp1 = inptrs.variables['tau_no_N2_zm'][
0, :, npoint]
tmp = tmp0
tmp = 1 / tmp0 - 1 / tmp1
if (varis[iv] == 'tau_xp2_zm'):
if (varis_tau == 'tau_xp2_zm'):
tmp = inptrs.variables[varis_tau][0, :,
npoint]
tmp = 1 / tmp
if (varis_tau == 'Rich'):
tmp0 = inptrs.variables['tau_xp2_zm'][
0, :, npoint]
tmp1 = inptrs.variables['tau_no_N2_zm'][
0, :, npoint]
tmp = tmp0
tmp = 1 / tmp0 / (1 / tmp1) / 1000
if (varis[iv] == 'tau_wp3_zm'):
if (varis_tau == 'tau_wp3_zm'
or varis_tau == 'tau_wpxp_zm'):
tmp = inptrs.variables[varis_tau][0, :,
npoint]
tmp = 1 / tmp
tmp[0:10] = 0
if (varis_tau == 'bvpos'):
tmp0 = inptrs.variables['tau_wp2_zm'][
0, :, npoint]
tmp1 = inptrs.variables['tau_no_N2_zm'][
0, :, npoint]
tmp = tmp0
tmp = 1 / tmp0 - 1 / tmp1
if (varis_tau == 'clear'):
tmp0 = inptrs.variables['tau_wp3_zm'][
0, :, npoint]
tmp1 = inptrs.variables['tau_wp2_zm'][
0, :, npoint]
tmp = tmp0
tmp = 1 / tmp0 - 1 / tmp1
tmp[0:10] = 0
if (varis[iv] == 'tau_wpxp_zm'):
if (varis_tau == 'tau_wpxp_zm'
or varis_tau == 'tau_zm'):
tmp = inptrs.variables[varis_tau][0, :,
npoint]
tmp = 1 / tmp
if (varis_tau == 'bvpos'):
tmp0 = inptrs.variables['tau_zm'][0, :,
npoint]
tmp1 = inptrs.variables['tau_no_N2_zm'][
0, :, npoint]
tmp = tmp0
tmp = 2 / tmp0 - 1 / tmp1
if (varis_tau == 'clear'):
tmp0 = inptrs.variables['tau_wpxp_zm'][
0, :, npoint]
tmp1 = inptrs.variables['tau_zm'][0, :,
npoint]
tmp = tmp0
tmp = 1 / tmp0 / 5 - 2 / tmp1
else:
varis_tau = varis[iv] + budget_ends[it]
tmp0 = inptrs.variables[varis[iv]][0, :, npoint]
tmp = inptrs.variables[varis_tau][0, :, npoint]
tmp = tmp * cscale[iv]
A_field[it, :] = (A_field[it, :] +
tmp[:] / n[ire]).astype(np.float32)
inptrs.close()
res.pmLegendDisplayMode = "Never"
if (varis[iv] == 'tau_wp3_zm'):
res.trXMinF = 0
res.trXMaxF = 450
res.xyMarkerColors = [
'black', 'orange', 'purple', 'firebrick'
]
res.xyLineColors = [
'black', 'orange', 'purple', 'firebrick'
]
if (varis[iv] == 'tau_no_N2_zm'):
res.trXMinF = 0
res.trXMaxF = 20
res.xyMarkerColors = ['black', 'red', 'green', 'blue']
res.xyLineColors = ['black', 'red', 'green', 'blue']
if (varis[iv] == 'tau_wp2_zm'):
res.trXMinF = 0
res.trXMaxF = 12
res.xyMarkerColors = ['black', 'orange', 'purple']
res.xyLineColors = ['black', 'orange', 'purple']
if (varis[iv] == 'tau_xp2_zm'):
res.trXMinF = 0
res.trXMaxF = 35
res.xyMarkerColors = ['black', 'orange']
res.xyLineColors = ['black', 'orange']
p = Ngl.xy(wks, A_field, ilev, res)
plot.append(p)
xp = np.mod(iv, 2)
yp = int(iv / 2)
if (varis[iv] == 'tau_wp3_zm'):
res.trXMinF = 0
res.trXMaxF = 450
res.xyMarkerColors = [
'black', 'orange', 'purple', 'firebrick'
]
res.xyLineColors = [
'black', 'orange', 'purple', 'firebrick'
]
Common_functions.create_legend(
wks, budget_name[:], 0.02,
['black', 'orange', 'purple', 'firebrick'],
0.3 + xp * 0.5, 0.8 - yp * 0.5)
if (varis[iv] == 'tau_no_N2_zm'):
res.trXMinF = 0
res.trXMaxF = 20
res.xyMarkerColors = ['black', 'red', 'green', 'blue']
res.xyLineColors = ['black', 'red', 'green', 'blue']
Common_functions.create_legend(
wks, budget_name[:], 0.02,
['black', 'red', 'green', 'blue'], 0.3 + xp * 0.5,
0.8 - yp * 0.5)
if (varis[iv] == 'tau_wp2_zm'):
res.trXMinF = 0
res.trXMaxF = 12
res.xyMarkerColors = ['black', 'orange', 'purple']
res.xyLineColors = ['black', 'orange', 'purple']
Common_functions.create_legend(
wks, budget_name[:], 0.02,
['black', 'orange', 'purple'], 0.3 + xp * 0.5,
0.8 - yp * 0.5)
if (varis[iv] == 'tau_xp2_zm'):
res.trXMinF = 0
res.trXMaxF = 35
res.xyMarkerColors = ['black', 'orange']
res.xyLineColors = ['black', 'orange']
Common_functions.create_legend(wks, budget_name[:], 0.02,
['black', 'orange'],
0.3 + xp * 0.5,
0.8 - yp * 0.5)
Ngl.panel(wks, plot[:], [nvaris / 2, 2], pres)
txres = Ngl.Resources()
txres.txFont = _Font
txres.txFontHeightF = 0.020
Ngl.text_ndc(
wks, casenames[im] + " BUDGET at " + str(lons[ire]) + "E," +
str(lats[ire]) + "N", 0.5, 0.95, txres)
Ngl.frame(wks)
Ngl.destroy(wks)
return (plottau)
# # Slanted strings # txres.txJust = "BottomRight" txres.txAngleF = -45. text2b = Ngl.add_text(wks, xy2, "some slanted", 32., .5, txres) txres.txJust = "BottomLeft" txres.txAngleF = 45. text2b = Ngl.add_text(wks, xy2, "text strings", 32., .5, txres) # # Filled text box. # txres.txAngleF = 0. txres.txJust = "CenterLeft" txres.txPerimOn = True txres.txFontColor = "black" txres.txBackgroundFillColor = "gray75" text4 = Ngl.add_text(wks, xy1, "filled text box", 3., -1.0, txres) # # Now that our primitives have been added to both plots, panel them. # Note that by adding the primitives, they will get drawn when the # XY plots are drawn, and they will be automatically resized with # the plot. # Ngl.panel(wks, [xy1, xy2], [2, 1]) Ngl.end()
top = 1.0 - (extra / 2.)
# Draw a title before we draw plots
title = "Multiple panels on one page, 3 different colormaps"
txres = Ngl.Resources()
txres.txJust = "BottomCenter"
txres.txFontHeightF = 0.02
Ngl.text_ndc(wks, title, 0.5, top + 0.01, txres)
# Loop across plots and panel them on one page
for n in range(0, 3):
# Define location in a unit square for each set of plots.
pres.nglPanelTop = top - (n * height)
pres.nglPanelBottom = top - ((n + 1) * height)
Ngl.panel(wks, plots[n * 3:n * 3 + 3], [1, 3], pres)
Ngl.frame(wks)
Ngl.end()
#
# File:
# ngl09p.py
#
# Synopsis:
# Illustrates animation of contours over a map and using masked
# arrays.
#
# Category:
# Contours over maps
#
#
# Set some font heights to make them slightly bigger than the default.
# Turn off nglScale, because this resource wants to set the axes font
# heights for you.
#
resources.nglScale = False
resources.tiMainFontHeightF = 0.037
resources.lbLabelFontHeightF = 0.032
resources.tmXBLabelFontHeightF = 0.030
resources.tmYLLabelFontHeightF = 0.030
for i in range(0, nplots):
resources.tiMainString = "Temperature at time = {}".format(i)
plot.append(Ngl.contour(wks, temp[i, :, :], resources))
Ngl.panel(wks, plot[0:4], [2, 2]) # Draw 2 rows/2 columns of plots.
#
# Now add some extra white space around each plot.
#
panelres = Ngl.Resources()
panelres.nglPanelYWhiteSpacePercent = 5.
panelres.nglPanelXWhiteSpacePercent = 5.
Ngl.panel(wks, plot[0:4], [2, 2], panelres) # Draw 2 rows/2 columns of plots.
#
# This section will set resources for drawing contour plots over a map.
#
del resources.tiMainString # Don't set a main title.
def clubb_std_prf(ptype, cseason, ncases, cases, casenames, nsite, lats, lons,
filepath, filepathobs, casedir, varis, vname, cscale,
chscale, pname):
# ncases, the number of models
# cases, the name of models
# casename, the name of cases
# filepath, model output filepath
# filepathobs, filepath for observational data
# inptrs = [ncases]
if not os.path.exists(casedir):
os.mkdir(casedir)
_Font = 25
interp = 2
extrap = False
mkres = Ngl.Resources()
mkres.gsMarkerIndex = 2
mkres.gsMarkerColor = "Red"
mkres.gsMarkerSizeF = 15.
alphas = [
'a) ', 'b) ', 'c) ', 'd) ', 'e) ', 'f) ', 'g) ', 'h) ', 'i) ', 'j) ',
'k) ', 'l) ', 'm) ', 'n) ', 'o) ', 'p) ', 'q) ', 'r) ', 's) ', 't) ',
'u) ', 'v) ', 'w) ', 'x) ', 'y) ', 'z) '
]
infiles = ["" for x in range(ncases)]
ncdfs = ["" for x in range(ncases)]
nregions = nsite
nvaris = len(varis)
plotstd = ["" for x in range(nsite)]
for ire in range(0, nsite):
if not os.path.exists(casedir + '/' + str(lons[ire]) + 'E_' +
str(lats[ire]) + 'N'):
os.mkdir(casedir + '/' + str(lons[ire]) + 'E_' + str(lats[ire]) +
'N')
plotname = casedir + '/' + str(lons[ire]) + 'E_' + str(
lats[ire]) + 'N/' + pname + '_' + str(lons[ire]) + "E_" + str(
lats[ire]) + "N_" + cseason
plotstd[ire] = pname + '_' + str(lons[ire]) + "E_" + str(
lats[ire]) + "N_" + cseason
wks = Ngl.open_wks(ptype, plotname)
Ngl.define_colormap(wks, "GMT_paired")
plot = []
res = Ngl.Resources()
res.nglMaximize = False
if (lats[ire] > 0 and lons[ire] < 230):
res.trYMinF = 400.
res.trYMaxF = 1000.
else:
res.trYMinF = 700.
res.trYMaxF = 1000.
res.nglDraw = False
res.nglFrame = False
res.lgLabelFontHeightF = .02 # change font height
res.lgPerimOn = False # no box around
res.vpWidthF = 0.30 # set width and height
res.vpHeightF = 0.30
res.vpXF = 0.04
res.vpYF = 0.30
res.tmYLLabelFont = _Font
res.tmXBLabelFont = _Font
res.tiYAxisFont = _Font
res.tiXAxisFont = _Font
res.tmXBLabelFontHeightF = 0.01
res.tmXBLabelFontThicknessF = 2.0
res.xyMarkLineMode = "Lines"
res.xyLineThicknesses = [
3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3., 3., 3., 3., 3, 3, 3, 3, 3, 3, 3
]
res.xyDashPatterns = np.arange(0, 24, 1)
# res.xyMarkers = np.arange(16,40,1)
# res.xyMarkerSizeF = 0.005
res.tiYAxisString = "Pressure [hPa]"
for iv in range(0, nvaris):
if (iv == nvaris - 1):
res.pmLegendDisplayMode = "NEVER"
res.xyExplicitLegendLabels = casenames[:]
res.pmLegendSide = "top"
res.pmLegendParallelPosF = 0.6
res.pmLegendOrthogonalPosF = -0.5
res.pmLegendWidthF = 0.10
res.pmLegendHeightF = 0.10
res.lgLabelFontHeightF = .02
res.lgLabelFontThicknessF = 1.5
res.lgPerimOn = True
else:
res.pmLegendDisplayMode = "NEVER"
# if(obsdataset[iv] =="CCCM"):
# if(cseason == "ANN"):
# fileobs = "/Users/guoz/databank/CLD/CCCm/cccm_cloudfraction_2007-"+cseason+".nc"
# else:
# fileobs = "/Users/guoz/databank/CLD/CCCm/cccm_cloudfraction_2007-2010-"+cseason+".nc"
# inptrobs = Dataset(fileobs,'r')
# B=inptrobs.variables[varisobs[iv]][:,(lats[ire]),(lons[ire])]
# else:
# if (varisobs[iv] =="PRECT"):
# fileobs = filepathobs+'/GPCP_'+cseason+'_climo.nc'
# else:
# fileobs = filepathobs + obsdataset[iv]+'_'+cseason+'_climo.nc'
# inptrobs = Dataset(fileobs,'r')
# if (varisobs[iv] =="THETA"):
# B = inptrobs.variables['T'][0,:,(lats[ire]),(lons[ire])]
# pre1 = inptrobs.variables['lev'][:]
# for il1 in range (0, len(pre1)):
# B[il1] = B[il1]*(1000/pre1[il1])**0.286
# else:
# pre1 = inptrobs.variables['lev'][:]
# B = inptrobs.variables[varisobs[iv]][0,:,(lats[ire]),(lons[ire])]
#
# B[:]=B[:] * cscaleobs[iv]
for im in range(0, ncases):
ncdfs[im] = './data/' + cases[im] + '_site_location.nc'
infiles[im] = filepath[im] + cases[im] + '/' + cases[
im] + '_' + cseason + '_climo.nc'
inptrs = Dataset(infiles[im], 'r') # pointer to file1
lat = inptrs.variables['lat'][:]
nlat = len(lat)
lon = inptrs.variables['lon'][:]
nlon = len(lon)
lev = inptrs.variables['ilev'][:]
nlev = len(lev)
ncdf = Dataset(ncdfs[im], 'r')
n = ncdf.variables['n'][:]
idx_cols = ncdf.variables['idx_cols'][:, :]
ncdf.close()
if (im == 0):
A_field = np.zeros((ncases, nlev), np.float32)
for subc in range(0, n[ire]):
npoint = idx_cols[ire, n[subc] - 1] - 1
if (varis[iv] == 'THETA'):
tmp = inptrs.variables['T'][0, :, npoint]
hyam = inptrs.variables['hyam'][:]
hybm = inptrs.variables['hybm'][:]
ps = inptrs.variables['PS'][0, npoint]
ps = ps
p0 = inptrs.variables['P0']
pre = np.zeros((nlev), np.float32)
for il in range(0, nlev):
pre[il] = hyam[il] * p0 + hybm[il] * ps
tmp[il] = tmp[il] * (100000 / pre[il])**0.286
theunits = str(
chscale[iv]) + inptrs.variables['T'].units
else:
tmp = inptrs.variables[varis[iv]][0, :, npoint]
# tmp2=inptrs.variables['C6rt_Skw_fnc'][0,:,npoint]
# tmp3=inptrs.variables['tau_zm'][0,:,npoint]
# tmp4=inptrs.variables['tau_wpxp_zm'][0,:,npoint]
theunits = str(
chscale[iv]) + inptrs.variables[varis[iv]].units
if (varis[iv] == 'tau_zm' or varis[iv] == 'tau_wp2_zm' \
or varis[iv] == 'tau_wp3_zm' or varis[iv] == 'tau_xp2_zm' \
or varis[iv] == 'tau_no_N2_zm' or varis[iv] == 'tau_wpxp_zm'):
tmp = 1 / tmp
tmp[0:10] = 0.0
theunits = str(chscale[iv]) + inptrs.variables[
varis[iv]].units + '^-1'
A_field[im, :] = (A_field[im, :] + tmp[:] / n[ire]).astype(
np.float32)
A_field[im, :] = A_field[im, :] * cscale[iv]
inptrs.close()
res.tiXAxisString = vname[iv] + " Unit= " + theunits
res.trYReverse = True
res.xyLineColors = np.arange(3, 20, 2)
res.xyMarkerColors = np.arange(2, 20, 2)
p = Ngl.xy(wks, A_field, lev, res)
plot.append(p)
pres = Ngl.Resources()
pres.nglFrame = False
pres.txFont = _Font
pres.nglMaximize = False
pres.txFont = _Font
# pres.nglPanelYWhiteSpacePercent = 5
# pres.nglPanelXWhiteSpacePercent = 5
# pres.wkPaperWidthF = 17 # in inches
# pres.wkPaperHeightF = 28 # in inches
pres.nglPanelTop = 0.935
pres.nglPanelFigureStrings = alphas
pres.nglPanelFigureStringsJust = 'Topleft'
pres.nglPanelFigureStringsFontHeightF = 0.015
pres.gsnPaperOrientation = "Landscape"
txres = Ngl.Resources()
txres.txFontHeightF = 0.02
txres.txFont = _Font
Ngl.text_ndc(
wks,
"CLUBB VAR at " + str(lons[ire]) + "E," + str(lats[ire]) + "N",
0.5, 0.75, txres)
Common_functions.create_legend(wks, casenames, 0.015,
np.arange(3, 20, 2), 0.3,
0.59 + ncases * 0.01)
Ngl.panel(wks, plot[:], [nvaris / 2, 2], pres)
Ngl.frame(wks)
Ngl.destroy(wks)
return plotstd
def draw_e3sm_bgt (ptype,cseason, ncases, cases, casenames, nsite, lats, lons, filepath, filepathobs,casedir,dpsc):
# ncases, the number of models
# cases, the name of models
# casename, the name of cases
# filepath, model output filepath
# filepathobs, filepath for observational data
# inptrs = [ncases]
if not os.path.exists(casedir):
os.mkdir(casedir)
_Font = 25
interp = 2
extrap = False
mkres = Ngl.Resources()
mkres.gsMarkerIndex = 2
mkres.gsMarkerColor = "Red"
mkres.gsMarkerSizeF = 15.
infiles = ["" for x in range(ncases)]
ncdfs = ["" for x in range(ncases)]
nregions = nsite
varis = [ "DCQ","DCCLDLIQ","DCCLDICE","PTEQ","PTTEND","DTCOND"]
nvaris = len(varis)
cscale = [1E8, 1E8, 1E8, 1E8, 1E4, 1E4]
chscale = ['1E-8', '1E-8', '1E-8', '1E-8', '1E-4', '1E-4']
plote3smbgt=["" for x in range(nsite*ncases)]
for ire in range (0, nsite):
for im in range (0,ncases):
if not os.path.exists(casedir+'/'+str(lons[ire])+'E_'+str(lats[ire])+'N'):
os.mkdir(casedir+'/'+str(lons[ire])+'E_'+str(lats[ire])+'N')
plotname = casedir+'/'+str(lons[ire])+'E_'+str(lats[ire])+'N/E3SM_Budgets_'+casenames[im]+"_"+str(lons[ire])+"E_"+str(lats[ire])+"N_"+cseason
plote3smbgt[im+ncases*ire] = 'E3SM_Budgets_'+casenames[im]+"_"+str(lons[ire])+"E_"+str(lats[ire])+"N_"+cseason
wks= Ngl.open_wks(ptype,plotname)
Ngl.define_colormap(wks,"radar")
plot = []
res = Ngl.Resources()
res.nglDraw = False
res.nglFrame = False
res.lgLabelFontHeightF = .012 # change font height
res.lgPerimOn = False # no box around
res.vpWidthF = 0.30 # set width and height
res.vpHeightF = 0.30
# res.txFontHeightF = .01
# res.vpXF = 0.04
# res.vpYF = 0.30
res.tmYLLabelFont = 12
res.tmXBLabelFont = 12
res.tmXBLabelFontHeightF = 0.01
res.tmXBLabelFontThicknessF = 1.0
res.xyMarkLineMode = "MarkLines"
res.xyLineThicknesses = [2.0, 2.0, 2.0, 2.0, 2.0, 2.0,2.,2.,2.,2.,2,2,2,2,2,2,2]
res.xyLineColors = np.arange(2,16,2)
res.xyDashPatterns = np.arange(0,24,1)
res.xyMarkers = np.arange(16,40,1)
res.xyMarkerSizeF = 0.005
res.xyMarkerColors = np.arange(2,16,2)
res.pmLegendDisplayMode = "ALWAYS"
res.pmLegendSide = "top" # Change location of
res.pmLegendParallelPosF = 0.6 # move units right
res.pmLegendOrthogonalPosF = -0.55 # more neg = down
res.pmLegendWidthF = 0.2 # Decrease width
res.pmLegendHeightF = 0.1 # Decrease height
res.lgBoxMinorExtentF = 0.1 # Shorten the legend lines
res.lgLabelFontHeightF = 0.015 # Change the font size
res.lgPerimOn = True
res.tiYAxisString = "PRESSURE"
res.trYReverse = True
pres = Ngl.Resources()
pres.nglMaximize = True
pres.wkWidth = 2000
pres.wkHeight = 2000
pres.nglFrame = False
pres.txFont = 12
pres.nglPanelYWhiteSpacePercent = 5
pres.nglPanelXWhiteSpacePercent = 5
pres.nglPanelTop = 0.93
for iv in range (0, nvaris):
if (varis[iv] == "DCQ" ):
if (dpsc[im] == "zm" ):
budget_ends = ["MPDQ", "RVMTEND_CLUBB","ZMDQ", "EVAPQZM"]
else:
budget_ends = ["MPDQ", "RVMTEND_CLUBB"]
nterms = len (budget_ends)
if (varis[iv] == "DTCOND" ):
if (dpsc[im] == "zm" ):
budget_ends = ["STEND_CLUBB", "MPDT", "DPDLFT","ZMDT", "EVAPTZM", "ZMMTT"]
else:
budget_ends = ["STEND_CLUBB", "MPDT", "DPDLFT"]
nterms = len (budget_ends)
if (varis[iv] == "PTTEND") :
budget_ends = ["DTCOND", "QRS", "QRL", "TTGW"]
nterms = len (budget_ends)
if (varis[iv] == "PTEQ") :
if (dpsc[im] == "zm" ):
budget_ends = ["MPDQ", "RVMTEND_CLUBB","ZMDQ", "EVAPQZM"]
else:
budget_ends = ["MPDQ", "RVMTEND_CLUBB"]
nterms = len (budget_ends)
if (varis[iv] == "DCCLDLIQ") :
if (dpsc[im] == "zm" ):
budget_ends = ["MPDLIQ", "RCMTEND_CLUBB", "DPDLFLIQ","ZMDLIQ"]
else:
budget_ends = ["MPDLIQ", "RCMTEND_CLUBB", "DPDLFLIQ"]
nterms = len (budget_ends)
if (varis[iv] == "DCCLDICE") :
if (dpsc[im] == "zm" ):
budget_ends = ["MPDICE", "RIMTEND_CLUBB", "DPDLFICE","ZMDICE"]
else:
budget_ends = ["MPDICE", "RIMTEND_CLUBB", "DPDLFICE"]
nterms = len (budget_ends)
ncdfs[im] = './data/'+cases[im]+'_site_location.nc'
infiles[im]= filepath[im]+cases[im]+'/'+cases[im]+'_'+cseason+'_climo.nc'
inptrs = Dataset(infiles[im],'r') # pointer to file1
lat=inptrs.variables['lat'][:]
nlat=len(lat)
lon=inptrs.variables['lon'][:]
nlon=len(lon)
ilev=inptrs.variables['lev'][:]
nilev=len(ilev)
ncdf= Dataset(ncdfs[im],'r')
n =ncdf.variables['n'][:]
idx_cols=ncdf.variables['idx_cols'][:,:]
ncdf.close()
A_field = np.zeros((nterms,nilev),np.float32)
theunits=str(chscale[iv])+"x"+inptrs.variables[varis[iv]].units
res.tiMainString = varis[iv]+" "+theunits
for it in range(0, nterms):
for subc in range( 0, n[ire]):
varis_bgt= budget_ends[it]
npoint=idx_cols[ire,n[subc]-1]-1
tmp=inptrs.variables[varis_bgt][0,:,npoint] #/n[ire]
tmp=tmp*cscale[iv]
if (varis_bgt == "MPDT" or varis_bgt == "STEND_CLUBB" ):
tmp=tmp/1004
A_field[it,:] = (A_field[it,:]+tmp[:]/n[ire]).astype(np.float32 )
inptrs.close()
res.xyExplicitLegendLabels = budget_ends[:]
p = Ngl.xy(wks,A_field,ilev,res)
plot.append(p)
xp=np.mod(iv,2)
yp=int(iv/2)
Ngl.panel(wks,plot[:],[nvaris/2,2],pres)
txres = Ngl.Resources()
txres.txFont = _Font
txres.txFontHeightF = 0.020
Ngl.text_ndc(wks,casenames[im]+" BUDGET at" +str(lons[ire])+"E,"+str(lats[ire])+"N",0.5,0.95,txres)
Ngl.frame(wks)
Ngl.destroy(wks)
return (plote3smbgt)
def draw_3D_plot(ptype, clevel, cseason, ncases, cases, casenames, nsite, lats,
lons, filepath, filepathobs, casedir):
# ncases, the number of models
# cases, the name of models
# casename, the name of cases
# filepath, model output filepath
# filepathobs, filepath for observational data
# inptrs = [ncases]
if not os.path.exists(casedir):
os.mkdir(casedir)
if not os.path.exists(casedir + "/2D"):
os.mkdir(casedir + "/2D")
_Font = 25
interp = 2
extrap = False
mkres = Ngl.Resources()
mkres.gsMarkerIndex = 2
mkres.gsMarkerColor = "Red"
mkres.gsMarkerSizeF = 15.
infiles = ["" for x in range(ncases)]
ncdfs = ["" for x in range(ncases)]
varis = ["T", "OMEGA", "Z3"]
varisobs = ["T", "OMEGA", "Z3"]
alpha = ["A", "B", "C", "D", "E", "F"]
nvaris = len(varis)
cunits = [""]
cscale = [1, 864, 1, 1, 1, 1]
cscaleobs = [1, 1, 1, 1, 0.04]
cntrs = np.zeros((nvaris, 11), np.float32)
obsdataset = ["ERAI", "ERAI", "ERAI", "ERAI", "ERAI"]
level = [
1000., 925., 850., 700., 600., 500., 400., 300., 250., 200., 150., 100.
]
plot3d = ["" for x in range(nvaris)]
for iv in range(0, nvaris):
# make plot for each field
# Observational data
if (obsdataset[iv] == "CCCM"):
if (cseason == "ANN"):
fileobs = "/Users/guoz/databank/CLD/CCCm/cccm_cloudfraction_2007-" + cseason + ".nc"
else:
fileobs = "/Users/guoz/databank/CLD/CCCm/cccm_cloudfraction_2007-2010-" + cseason + ".nc"
else:
if (varisobs[iv] == "PRECT"):
fileobs = filepathobs + '/GPCP_' + cseason + '_climo.nc'
else:
fileobs = filepathobs + obsdataset[
iv] + '_' + cseason + '_climo.nc'
inptrobs = Dataset(fileobs, 'r')
latobs = inptrobs.variables['lat'][:]
lonobs = inptrobs.variables['lon'][:]
levobs = inptrobs.variables['lev'][:]
levobs_idx = np.abs(levobs - clevel).argmin()
B = inptrobs.variables[varisobs[iv]][0, levobs_idx, :, :]
B = B * cscaleobs[iv]
# cntrs= np.arange(np.min(B),np.max(B),12)
if (varis[iv] == "OMEGA"):
cntrs[iv, :] = [-50, -40, -30, -20, -10, 0, 10, 20, 30, 40, 50]
if (varis[iv] == "Z3"):
if (clevel == 500):
cntrs[iv, :] = [
5300, 5400, 5500, 5600, 5700, 5800, 5900, 6000, 6100, 6200,
6300
]
else:
cntrs[iv, :] = [
300, 400, 500, 600, 700, 800, 900, 1000, 1100, 1200, 1300
]
if (varis[iv] == "T"):
if (clevel == 500):
cntrs[iv, :] = [
210, 220, 230, 240, 250, 260, 270, 280, 290, 300, 310
]
else:
cntrs[iv, :] = [
292, 294, 296, 298, 300, 302, 304, 306, 308, 310, 312
]
if (varis[iv] == "Q"):
if (clevel == 500):
cntrs[iv, :] = [
210, 220, 230, 240, 250, 260, 270, 280, 290, 300, 310
]
else:
cntrs[iv, :] = [
292, 294, 296, 298, 300, 302, 304, 306, 308, 310, 312
]
#************************************************
# create plot
#************************************************
plotname = casedir + '/2D/Horizontal_' + varis[
iv] + '_' + cseason + str(clevel)
plot3d[iv] = 'Horizontal_' + varis[iv] + '_' + cseason + str(clevel)
wks = Ngl.open_wks(ptype, plotname)
Ngl.define_colormap(wks, "amwg256")
plot = []
textres = Ngl.Resources()
textres.txFontHeightF = 0.02 # Size of title.
textres.txFont = _Font
Ngl.text_ndc(wks, varis[iv], 0.1, .97, textres)
pres = Ngl.Resources()
# pres.nglMaximize = True
pres.nglFrame = False
pres.nglPanelYWhiteSpacePercent = 5
pres.nglPanelXWhiteSpacePercent = 5
pres.nglPanelBottom = 0.2
pres.nglPanelTop = 0.9
pres.nglPanelLabelBar = True
pres.pmLabelBarWidthF = 0.8
pres.nglFrame = False
pres.nglPanelLabelBar = True # Turn on panel labelbar
pres.nglPanelLabelBarLabelFontHeightF = 0.015 # Labelbar font height
pres.nglPanelLabelBarHeightF = 0.0750 # Height of labelbar
pres.nglPanelLabelBarWidthF = 0.700 # Width of labelbar
pres.lbLabelFont = "helvetica-bold" # Labelbar font
pres.nglPanelTop = 0.93
pres.nglPanelFigureStrings = alpha
pres.nglPanelFigureStringsJust = "BottomRight"
res = Ngl.Resources()
res.nglDraw = False #-- don't draw plots
res.nglFrame = False
res.cnFillOn = True
res.cnFillMode = "RasterFill"
res.cnLinesOn = False
res.nglMaximize = True
res.mpFillOn = True
res.mpCenterLonF = 180
res.tiMainFont = _Font
res.tiMainFontHeightF = 0.025
res.tiXAxisString = ""
res.tiXAxisFont = _Font
res.tiXAxisFontHeightF = 0.025
res.tiYAxisString = ""
res.tiYAxisFont = _Font
res.tiYAxisOffsetXF = 0.0
res.tiYAxisFontHeightF = 0.025
res.tmXBLabelFont = _Font
res.tmYLLabelFont = _Font
res.tiYAxisFont = _Font
# res.nglStringFont = _Font
# res.nglStringFontHeightF = 0.04
# res.nglRightString = ""#"Cloud Fraction"
# res.nglScalarContour = True
res.cnInfoLabelOn = False
res.cnFillOn = True
res.cnLinesOn = False
res.cnLineLabelsOn = False
res.lbLabelBarOn = False
# res.vcRefMagnitudeF = 5.
# res.vcMinMagnitudeF = 1.
# res.vcRefLengthF = 0.04
# res.vcRefAnnoOn = True#False
# res.vcRefAnnoZone = 3
# res.vcRefAnnoFontHeightF = 0.02
# res.vcRefAnnoString2 =""
# res.vcRefAnnoOrthogonalPosF = -1.0
# res.vcRefAnnoArrowLineColor = "blue" # change ref vector color
# res.vcRefAnnoArrowUseVecColor = False
# res.vcMinDistanceF = .05
# res.vcMinFracLengthF = .
# res.vcRefAnnoParallelPosF = 0.997
# res.vcFillArrowsOn = True
# res.vcLineArrowThicknessF = 3.0
# res.vcLineArrowHeadMinSizeF = 0.01
# res.vcLineArrowHeadMaxSizeF = 0.03
# res.vcGlyphStyle = "CurlyVector" # turn on curley vectors
# res@vcGlyphStyle ="Fillarrow"
# res.vcMonoFillArrowFillColor = True
# res.vcMonoLineArrowColor = True
# res.vcLineArrowColor = "green" # change vector color
# res.vcFillArrowEdgeColor ="white"
# res.vcPositionMode ="ArrowTail"
# res.vcFillArrowHeadInteriorXF =0.1
# res.vcFillArrowWidthF =0.05 #default
# res.vcFillArrowMinFracWidthF =.5
# res.vcFillArrowHeadMinFracXF =.5
# res.vcFillArrowHeadMinFracYF =.5
# res.vcFillArrowEdgeThicknessF = 2.0
res.mpFillOn = False
res.cnLevelSelectionMode = "ExplicitLevels"
res.cnLevels = cntrs[iv, :]
for im in range(0, ncases):
ncdfs[im] = './data/' + cases[im] + '_site_location.nc'
infiles[im] = filepath[im] + '/' + cases[
im] + '_' + cseason + '_climo.nc'
inptrs = Dataset(infiles[im], 'r') # pointer to file1
lat = inptrs.variables['lat'][:]
nlat = len(lat)
lon = inptrs.variables['lon'][:]
nlon = len(lon)
#area=inptrs.variables['area'][:]
lev = inptrs.variables['lev'][:]
lev_idx = np.abs(lev - clevel).argmin()
area_wgt = np.zeros(nlat)
# area_wgt[:] = gw[:]
sits = np.linspace(0, nsite - 1, nsite)
ncdf = Dataset(ncdfs[im], 'r')
n = ncdf.variables['n'][:]
idx_cols = ncdf.variables['idx_cols'][:]
A = inptrs.variables[varis[iv]][0, lev_idx, :]
A_xy = A
A_xy = A_xy * cscale[iv]
ncdf.close()
inptrs.close()
if im == 0:
dsizes = len(A_xy)
field_xy = [[0 for col in range(dsizes)]
for row in range(ncases)]
field_xy[im][:] = A_xy
res.lbLabelBarOn = False
if (np.mod(im, 2) == 0):
res.tiYAxisOn = True
else:
res.tiYAxisOn = False
res.tiXAxisOn = False
res.sfXArray = lon
res.sfYArray = lat
res.mpLimitMode = "LatLon"
res.mpMaxLonF = max(lon)
res.mpMinLonF = min(lon)
res.mpMinLatF = min(lat)
res.mpMaxLatF = max(lat)
#res.tiMainString = "GLB="+str(np.sum(A_xy[:]*area[:]/np.sum(area)))
res.tiMainString = "GLB="
textres.txFontHeightF = 0.015
Ngl.text_ndc(wks, alpha[im] + " " + casenames[im], 0.3,
.135 - im * 0.03, textres)
p = Ngl.contour_map(wks, A_xy, res)
plot.append(p)
# observation
# res.nglLeftString = obsdataset[iv]
# res@lbLabelBarOn = True
# res@lbOrientation = "vertical" # vertical label bars
res.lbLabelFont = _Font
res.tiYAxisOn = True
res.tiXAxisOn = True
res.tiXAxisFont = _Font
rad = 4.0 * np.arctan(1.0) / 180.0
re = 6371220.0
rr = re * rad
dlon = abs(lonobs[2] - lonobs[1]) * rr
dx = dlon * np.cos(latobs * rad)
jlat = len(latobs)
dy = np.zeros(jlat, dtype=float)
# close enough
dy[0] = abs(lat[2] - lat[1]) * rr
dy[1:jlat - 2] = abs(lat[2:jlat - 1] - lat[0:jlat - 3]) * rr * 0.5
dy[jlat - 1] = abs(lat[jlat - 1] - lat[jlat - 2]) * rr
area_wgt = dx * dy #
is_SE = False
sum1 = 0
sum2 = 0
for j in range(0, jlat - 1):
for i in range(0, len(lonobs) - 1):
if (np.isnan(B[j][i]) != "--"):
sum1 = sum1 + area_wgt[j] * B[j][i]
sum2 = sum2 + area_wgt[j]
res.sfXArray = lonobs
res.sfYArray = latobs
res.mpLimitMode = "LatLon"
res.mpMaxLonF = max(lonobs)
res.mpMinLonF = min(lonobs)
res.mpMinLatF = min(latobs)
res.mpMaxLatF = max(latobs)
res.tiMainString = "GLB=" + str(
sum1 / sum2) #Common_functions.area_avg(B, area_wgt,is_SE))
p = Ngl.contour_map(wks, B, res)
plot.append(p)
if (np.mod(ncases + 1, 2) == 1):
Ngl.panel(wks, plot[:], [(ncases + 1) / 2 + 1, 2], pres)
else:
Ngl.panel(wks, plot[:], [(ncases + 1) / 2, 2], pres)
Ngl.frame(wks)
Ngl.destroy(wks)
return plot3d
def rain_prf (ptype,cseason, ncases, cases, casenames, nsite, lats, lons, filepath, filepathobs,casedir,varis,cscale,chscale,pname):
# ncases, the number of models
# cases, the name of models
# casename, the name of cases
# filepath, model output filepath
# filepathobs, filepath for observational data
# inptrs = [ncases]
if not os.path.exists(casedir):
os.mkdir(casedir)
_Font = 25
interp = 2
extrap = False
mkres = Ngl.Resources()
mkres.gsMarkerIndex = 2
mkres.gsMarkerColor = 'Red'
mkres.gsMarkerSizeF = 15.
infiles = ['' for x in range(ncases)]
ncdfs = ['' for x in range(ncases)]
nregions = nsite
varisobs = ['CC_ISBL', 'OMEGA','SHUM','CLWC_ISBL', 'THETA','RELHUM','U','CIWC_ISBL','T' ]
nvaris = len(varis)
cunits = ['%','mba/day','g/kg','g/kg','K', '%', 'm/s', 'g/kg', 'm/s', 'm/s','K','m' ]
cscaleobs = [100, 1, 1, 1000 , 1., 1, 1, 1000, 1,1,1,1,1,1,1]
obsdataset =['ERAI', 'ERAI', 'ERAI', 'ERAI', 'ERAI', 'ERAI', 'ERAI', 'ERAI','ERAI','ERAI']
plotrain=['' for x in range(nsite)]
for ire in range (0, nsite):
if not os.path.exists(casedir+'/'+str(lons[ire])+'E_'+str(lats[ire])+'N'):
os.mkdir(casedir+'/'+str(lons[ire])+'E_'+str(lats[ire])+'N')
plotname = casedir+'/'+str(lons[ire])+'E_'+str(lats[ire])+'N/'+pname+'_'+str(lons[ire])+'E_'+str(lats[ire])+'N_'+cseason
plotrain[ire] = pname+'_'+str(lons[ire])+'E_'+str(lats[ire])+'N_'+cseason
wks= Ngl.open_wks(ptype,plotname)
Ngl.define_colormap(wks,'GMT_paired')
plot = []
res = Ngl.Resources()
res.nglDraw = False
res.nglFrame = False
res.lgLabelFontHeightF = .02 # change font height
res.lgPerimOn = False # no box around
res.vpWidthF = 0.30 # set width and height
res.vpHeightF = 0.30
#res.vpXF = 0.04
# res.vpYF = 0.30
res.tmYLLabelFont = _Font
res.tmXBLabelFont = _Font
res.tiMainFont = _Font
res.tmXBLabelFontHeightF = 0.015
res.tmXBLabelFontThicknessF = 1.0
# res.tmXBLabelAngleF = 45
res.xyMarkLineMode = 'Lines'
res.xyLineThicknesses = [3.0, 3.0, 3.0, 3.0, 3.0, 3.0,3.,3.,3.,3.,3,3,3,3,3,3,3]
res.xyDashPatterns = np.arange(0,24,1)
# res.xyMarkers = np.arange(16,40,1)
# res.xyMarkerSizeF = 0.005
pres = Ngl.Resources()
# pres.nglMaximize = True
pres.nglFrame = False
pres.txFont = _Font
pres.nglPanelYWhiteSpacePercent = 5
pres.nglPanelXWhiteSpacePercent = 5
pres.nglPanelTop = 0.88
pres.wkWidth = 2500
pres.wkHeight = 2500
for iv in range (0, nvaris):
if(iv == nvaris-1):
res.pmLegendDisplayMode = 'Never'
res.xyExplicitLegendLabels = casenames[:]
res.pmLegendSide = 'top'
res.pmLegendParallelPosF = 0.6
res.pmLegendOrthogonalPosF = -0.5
res.pmLegendWidthF = 0.10
res.pmLegendHeightF = 0.10
res.lgLabelFontHeightF = .02
res.lgLabelFontThicknessF = 1.5
res.lgPerimOn = False
else:
res.pmLegendDisplayMode = 'NEVER'
for im in range (0,ncases):
ncdfs[im] = './data/'+cases[im]+'_site_location.nc'
infiles[im]= filepath[im]+cases[im]+'/'+cases[im]+'_'+cseason+'_climo.nc'
inptrs = Dataset(infiles[im],'r') # pointer to file1
lat=inptrs.variables['lat'][:]
nlat=len(lat)
lon=inptrs.variables['lon'][:]
nlon=len(lon)
lev=inptrs.variables['lev'][:]
nlev=len(lev)
ncdf= Dataset(ncdfs[im],'r')
n =ncdf.variables['n'][:]
idx_cols=ncdf.variables['idx_cols'][:,:]
ncdf.close()
if (im ==0):
A_field = np.zeros((ncases,nlev),np.float32)
for subc in range( 0, n[ire]):
npoint=idx_cols[ire,n[subc]-1]-1
tmp=inptrs.variables[varis[iv]][0,:,npoint]
theunits=str(chscale[iv])+'x'+inptrs.variables[varis[iv]].units
A_field[im,:] = (A_field[im,:]+tmp[:]/n[ire]).astype(np.float32 )
A_field[im,:] = A_field[im,:] *cscale[iv]
inptrs.close()
res.tiMainString = varis[iv]+' '+theunits
# res.trXMinF = min(np.min(A_field[0, :]))
# res.trXMaxF = max(np.max(A_field[0, :]))
res.trYReverse = True
res.xyLineColors = np.arange(3,20,2)
res.xyMarkerColors = np.arange(2,20,2)
p = Ngl.xy(wks,A_field,lev,res)
# res.trYReverse = False
# res.xyLineColors = ['black']
# pt = Ngl.xy(wks,B,pre1,res)
# Ngl.overlay(p,pt)
plot.append(p)
pres.txString = pname+' at'+ str(lons[ire])+'E,'+str(lats[ire])+'N'
txres = Ngl.Resources()
txres.txFontHeightF = 0.020
txres.txFont = _Font
Ngl.text_ndc(wks,pname+' at'+ str(lons[ire])+'E,'+str(lats[ire])+'N',0.5,0.92+ncases*0.01,txres)
Common_functions.create_legend(wks,casenames,np.arange(3,20,2),0.1,0.89+ncases*0.01)
Ngl.panel(wks,plot[:],[nvaris/2,2],pres)
Ngl.frame(wks)
Ngl.destroy(wks)
return plotrain
def draw_uv(sel_year, sel_month):
print("darwing wind plot for " + str(sel_month).zfill(2) + " " +
str(sel_year))
files_cli = sorted(
glob.glob(
os.path.join(
'/home/alley/work/Dong/mongo/seasonal_analysis/data/data/download_from_mongo/cli',
'uv*.grb')))
f_cli = xr.open_mfdataset(files_cli,
concat_dim="time",
combine="nested",
engine="cfgrib",
parallel=True)
u_cli_850 = f_cli["u"][:, 0, :, :]
v_cli_850 = f_cli["v"][:, 0, :, :]
u_cli_850 = u_cli_850.mean(dim="time")
v_cli_850 = v_cli_850.mean(dim="time")
u_cli_200 = f_cli["u"][:, 1, :, :]
v_cli_200 = f_cli["v"][:, 1, :, :]
u_cli_200 = u_cli_200.mean(dim="time")
v_cli_200 = v_cli_200.mean(dim="time")
file_cur = "/home/alley/work/Dong/mongo/seasonal_analysis/data/data/download_from_mongo/cur/uv_850_200_" + str(
sel_year) + str(sel_month).zfill(2) + ".grb"
f_cur = xr.open_mfdataset(file_cur, engine="cfgrib", parallel=True)
u_cur_850 = f_cur["u"][0, :, :]
v_cur_850 = f_cur["v"][0, :, :]
u_cur_200 = f_cur["u"][1, :, :]
v_cur_200 = f_cur["v"][1, :, :]
lat = f_cur["latitude"].values
lon = f_cur["longitude"].values
# u_ano_850 = u_cur_850 - u_cli_850
# v_ano_850 = v_cur_850 - v_cli_850
leftString = "850hPa wind"
rightString = "m/s"
wks_type = 'png'
wks = Ngl.open_wks(
wks_type,
'/home/alley/work/Dong/mongo/seasonal_analysis/images/850_200_wind_' +
str(sel_year) + str(sel_month) + '.png')
res = Ngl.Resources()
res.nglFrame = False
res.nglDraw = False
res.mpLimitMode = "LatLon"
res.mpMinLonF = 60
res.mpMaxLonF = 180
res.mpMinLatF = -10
res.mpMaxLatF = 60
res.mpPerimOn = True #-- turn on map perimeter
res.mpFillOn = True #-- turn on map fill
res.mpLandFillColor = "gray" #-- change land color to gray
# resources.mpOceanFillColor = -1 # Change oceans and inland
# resources.mpInlandWaterFillColor = -1 # waters to transparent.
res.mpOceanFillColor = "transparent" #-- change color for oceans and inlandwater
res.mpInlandWaterFillColor = "transparent" #-- set ocean/inlandwater color to transparent
res.mpGridMaskMode = "MaskNotOcean" #-- draw grid over ocean, not land
res.vcMonoLineArrowColor = False #-- draw vectors in color
res.vcMinFracLengthF = 0.33 #-- increase length of vectors
res.vcMinMagnitudeF = 0.001 #-- increase length of vectors
res.vcRefLengthF = 0.045 #-- set reference vector length
res.vcRefMagnitudeF = 10.0 #-- set reference magnitude value
res.vcLineArrowThicknessF = 3 #-- make vector lines thicker (default: 1.0)
res.vcRefAnnoOn = False # 不显示reference vector
# res.vcLevelPalette = "ncl_default" #-- choose color map
res.pmLabelBarDisplayMode = "Never" #-- turn on a labelbar
res.lbOrientation = "Horizontal" #-- labelbar orientation
# res.lbLabelFontHeightF = 0.008 #-- labelbar label font size
# res.lbBoxMinorExtentF = 0.22 #-- decrease height of labelbar boxes
res.tiMainString = "850hPa wind field in " + str(sel_month).zfill(
2) + " " + str(sel_year)
# res.tiMainString = "850hPa wind"
res.vfXArray = lon[::15] #-- longitude values, subscript every 3rd value
res.vfYArray = lat[::15] #-- latitude values, subscript every 3rd value
wind_850_cur = Ngl.vector_map(
wks, u_cur_850[::15, ::15], v_cur_850[::15, ::15],
res) #-- draw a vector plot, subscript every 3rd value
res.tiMainString = "850hPa wind field for climate state"
wind_850_cli = Ngl.vector_map(
wks, u_cli_850[::15, ::15], v_cli_850[::15, ::15],
res) #-- draw a vector plot, subscript every 3rd value
res.tiMainString = "200hPa wind field in " + str(sel_month) + " " + str(
sel_year)
res.vfXArray = lon[::15] #-- longitude values, subscript every 3rd value
res.vfYArray = lat[::15] #-- latitude values, subscript every 3rd value
wind_200_cur = Ngl.vector_map(
wks, u_cur_200[::15, ::15], v_cur_200[::15, ::15],
res) #-- draw a vector plot, subscript every 3rd value
res.tiMainString = "200hPa wind field for climate state"
wind_200_cli = Ngl.vector_map(
wks, u_cli_200[::15, ::15], v_cli_200[::15, ::15],
res) #-- draw a vector plot, subscript every 3rd value
panelres = Ngl.Resources()
panelres.nglPanelLabelBar = True # Turn on panel labelbar
# panelres.nglPanelLabelBarLabelFontHeightF = 0.015 # Labelbar font height
# panelres.nglPanelLabelBarHeightF = 0.1750 # Height of labelbar
# panelres.nglPanelLabelBarWidthF = 0.700 # Width of labelbar
# panelres.lbLabelFont = "helvetica-bold" # Labelbar font
# panelres.nglPanelTop = 0.935
Ngl.panel(wks, [wind_200_cli, wind_200_cur, wind_850_cli, wind_850_cur],
[2, 2], panelres)
# panelres.nglPanelFigureStrings = ["A","B","C","D","E","F"]
# panelres.nglPanelFigureStringsJust = "BottomRight"
# vres = Ngl.Resources()
# vres.nglFrame = False
# vres.nglDraw = False
# vres.cnFillOn = True
# vres.sfXArray = lon
# vres.sfYArray = lat
# vres.lbOrientation = "Horizontal" # horizontal labelbar
# vres.cnLinesOn = False
# vres.cnLineLabelsOn = False
# vres.cnLevelSelectionMode = "ExplicitLevels"
# vres.cnFillPalette = "BlueDarkRed18"
# vres.cnLevels = np.arange(-5, 6, 1)
# plot_cn = Ngl.contour(wks, h_ano, vres)
# Ngl.overlay(plot_map, plot_cn)
# Ngl.overlay(plot_map, plot2)
# #
# txres = Ngl.Resources()
# txres.txFontHeightF = 0.024
# #
# Ngl.text_ndc(wks, leftString, 0.3, 0.83, txres)
# Ngl.text_ndc(wks, rightString, 0.85, 0.83, txres)
# #
# Ngl.maximize_plot(wks, plot_map)
# Ngl.draw(wind_850)
# Ngl.frame(wks)
Ngl.end()
print("Finish darwing wind plot for " + str(sel_month).zfill(2) + " " +
str(sel_year))
def cwrf_contour(fname, vname, days=None):
if not pth.exists(fname):
print_("You do not have the necessary '%s' file to run this script." %
fname)
sys.exit(1)
dset = Nio.open_file(fname + ".nc")
lat = dset.variables["XLAT"][0, :, :]
lon = dset.variables["XLONG"][0, :, :]
region, subm = re.split(os.sep, pth.dirname(fname))[-2:]
cur_date = get_date(dset.START_DATE)
dates = get_list_times(dset)
if days is None:
days = len(dates) / 10 * 10
elif days in ('30', '60', '90'):
days = int(days)
else:
print_("%s invalid, between 30, 60 and 90" % days)
sys.exit(1)
if vname == "RAINC":
vdat, base = get_rain_data(dset, cur_date.month - 1, days)
blon, blat = get_coordinates("rainc")
title = "Precipitacion Total"
unit = "mm"
levels = (30, 1200, 150)
blevels = [-300., -180., -90., -30., 30., 90., 180., 300.]
palete = 'WhBlGrYeRe'
bpalete = 'precip_diff_12lev'
elif vname == "T2":
vdat, base = get_temp_data(dset, cur_date.month - 1, days)
blon, blat = get_coordinates("t2ave")
title = "Temperatura Media a 2 m"
unit = "~S~o~N~C"
levels = (-5, 35, 5)
blevels = [-3, -2, -1, -0.3, 0.3, 1, 2, 3]
palete = 'MPL_coolwarm'
bpalete = 'temp_diff_18lev'
else:
print_("%s not supported" % vname)
sys.exit(1)
rbase = regrid((blon, blat), (lon, lat), base)
wks_type = "png"
wks_res = Ngl.Resources()
wks_res.wkHeight = 600
wks_res.wkWidth = 650
wks = Ngl.open_wks(
wks_type, DEFAULT_FILE_FORMAT %
(cur_date.year, cur_date.month, days, VARIABLES[vname]), wks_res)
panelres = Ngl.Resources()
panelres.nglMaximize = True
panelres.nglPanelBottom = 0.03
res = Ngl.Resources()
res.nglDraw = False
res.nglFrame = False
# Mapa
set_map(res, (np.min(lon), np.min(lat)), (np.max(lon), np.max(lat)))
#set_map(res, (REGIONS["SA"][0][0], REGIONS["SA"][0][1]),
# (REGIONS["SA"][1][0], REGIONS["SA"][1][1]))
set_labelbar(res, unit)
res.tiMainFontHeightF = 0.025
res.tiMainString = "Totales"
res.sfXArray = lon
res.sfYArray = lat
set_contour(res, levels, cnFillPalette=palete)
plot1 = Ngl.contour_map(wks, vdat, res)
#res.tmYLOn = False
#res.tmYROn = True
#res.tmYRLabelsOn = True
res.tiMainString = "Anomalias"
#res.sfXArray = blon
#res.sfYArray = blat
set_contour(res, blevels, cnFillPalette=bpalete)
plot2 = Ngl.contour_map(wks, vdat - rbase, res)
txres = Ngl.Resources()
txres.txFontHeightF = 0.03
Ngl.text_ndc(wks, title, 0.5, 0.97, txres)
txres.txFontHeightF = 0.02
last = days - 1
if days > 89:
last = days + 1
Ngl.text_ndc(
wks, "Promedio %d dias desde %s hasta %s" %
(days, dates[0].strftime("%d%b%Y"), dates[last].strftime("%d%b%Y")),
0.5, 0.91, txres)
txres.txFontHeightF = 0.015
y1 = 0.120
y2 = 0.090
if region == "PARAGUAY":
y1 = 0.190
y2 = 0.160
Ngl.text_ndc(wks, "CWRF-CAM-%s OLE~S~2~N~ (clima.pol.una.py) " % subm, 0.8,
y1, txres)
txres.txFontHeightF = 0.013
Ngl.text_ndc(
wks, "Proyecto 14-INV-054 / GUYRA Paraguay / Facultad "
"Politecnica", 0.75, y2, txres)
Ngl.panel(wks, [plot1, plot2], [1, 2], panelres)
Ngl.end()
