def print_cape_for_timestamp(wrf_data, timestamp, filepath):
slp = pressure_lib.get_sea_level_pressure(wrf_data)
cinfo = getvar(wrf_data, "cape_2d", missing=0.0)
cape = cinfo[0, :, :].fillna(0)
lat, lon = latlon_coords(slp)
lat_normal = to_np(lat)
lon_normal = to_np(lon)
# rain sum
cape_res = get_pyngl(cinfo)
cape_res.nglDraw = False # don't draw plot
cape_res.nglFrame = False # don't advance frame
cape_res.cnFillOn = True # turn on contour fill
cape_res.cnLinesOn = False # turn off contour lines
cape_res.cnLineLabelsOn = False # turn off line labels
cape_res.cnFillMode = "RasterFill" # These two resources
cape_res.cnLevelSelectionMode = "ExplicitLevels"
cape_res.cnFillColors = numpy.array([ [255,255,255], [ 0,255, 0], [ 0,128, 0], \
[240,230,140], [255,255, 0], [255,140, 0], \
[255, 0, 0], [139, 0, 0], [186, 85,211],\
[153, 50,204], [139, 0,139], ],'f') / 255.
cape_res.cnLevels = numpy.array(
[.1, 500, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500])
cape_res = geography_lib.initialize_geography(cape_res, "gray50")
cape_res.lbTitleString = "Convective available potential energy [CAPE] in (J/kg)"
cape_res.lbOrientation = "horizontal"
cape_res.lbTitleFontHeightF = 0.015
cape_res.lbLabelFontHeightF = 0.015
cape_res.tiMainString = "Thunderstorm probability (%s)" % timestamp.strftime(
"%b %d %Y %HUTC")
cape_res.trGridType = "TriangularMesh" # can speed up plotting.
cape_res.tfDoNDCOverlay = True # required for native projection
# pressure
p_res = pressure_lib.get_pressure_resource(lat_normal, lon_normal)
wk_res = Ngl.Resources()
wk_res.wkWidth = 2500
wk_res.wkHeight = 2500
output_path = "%scape_%s" % (filepath, timestamp.strftime("%Y_%m_%d_%H"))
wks_comp = Ngl.open_wks("png", output_path, wk_res)
# creating plots for the measurands
capeplot = Ngl.contour_map(wks_comp, cape, cape_res)
pplot = Ngl.contour(wks_comp, slp, p_res)
Ngl.overlay(capeplot, pplot)
Ngl.maximize_plot(wks_comp, capeplot)
Ngl.draw(capeplot)
Ngl.frame(wks_comp)
Ngl.delete_wks(wks_comp) # delete currently used workstation
def get_3h_rainsum(previous_data, current_data, timestamp, filepath):
slp = pressure_lib.get_sea_level_pressure(current_data)
previous_sum, rain_con = get_cumulated_rain_sum(previous_data)
current_sum, rain_con = get_cumulated_rain_sum(current_data)
rain_sum = current_sum - previous_sum
lat, lon = latlon_coords(rain_con)
lat_normal = to_np(lat)
lon_normal = to_np(lon)
# rain sum
rr_res = initialize_rain_resource(rain_con)
rr_res.lbTitleString = "3h rainsum in (mm)"
rr_res.lbOrientation = "horizontal"
rr_res.lbTitleFontHeightF = 0.015
rr_res.lbLabelFontHeightF = 0.015
rr_res.tiMainString = "3h rainsum (%s)" % timestamp.strftime(
"%b %d %Y %HUTC")
rr_res.trGridType = "TriangularMesh" # can speed up plotting.
rr_res.tfDoNDCOverlay = True # required for native projection
# pressure
p_res = pressure_lib.get_pressure_resource(lat_normal, lon_normal)
wk_res = Ngl.Resources()
wk_res.wkWidth = 2500
wk_res.wkHeight = 2500
output_path = "%srain_3h_%s" % (filepath,
timestamp.strftime("%Y_%m_%d_%H"))
wks_comp = Ngl.open_wks("png", output_path, wk_res)
# creating plots for the measurands
rrplot = Ngl.contour_map(wks_comp, rain_sum, rr_res)
pplot = Ngl.contour(wks_comp, slp, p_res)
Ngl.overlay(rrplot, pplot)
Ngl.maximize_plot(wks_comp, rrplot)
Ngl.draw(rrplot)
Ngl.frame(wks_comp)
Ngl.delete_wks(wks_comp) # delete currently used workstation
#-- draw polygons polyg = Ngl.add_polygon(wks1,map,x1d,y1d,pgres) #-- add polygons to map #-- labelbar resources lbres = Ngl.Resources() lbres.vpWidthF = 0.85 #-- labelbar width lbres.vpHeightF = 0.15 #-- labelbar height lbres.lbOrientation = "Horizontal" #-- labelbar orientation lbres.lbFillPattern = "SolidFill" #-- labelbar box fill style lbres.lbMonoFillPattern = 21 #-- labelbar box fill pattern lbres.lbMonoFillColor = False #-- use multiple colors lbres.lbFillColors = colors #-- set color array lbres.lbLabelFontHeightF = 0.014 #-- labelbar label font size lbres.lbLabelAlignment = "InteriorEdges" #-- draw labels between boxes #-- add labelbar to workstation lb = Ngl.labelbar_ndc(wks1,nlevels,labels,0.1,0.2,lbres) #-- maximize and draw the plot, and advance the frame Ngl.maximize_plot(wks1, map) Ngl.draw(map) Ngl.frame(wks1) #-- get wallclock time t2 = time.time() print "Wallclock time: %0.3f seconds" % (t2-t1) print "" Ngl.end()
res.mpNationalLineThicknessF = 1.5 res.mpGeophysicalLineColor = "gray40" res.mpGeophysicalLineThicknessF = 1.5 res.cnMonoLineColor = True res.cnLevelSelectionMode = "ManualLevels" res.cnMinLevelValF = 1000.0 res.cnMaxLevelValF = 6000.0 res.cnLevelSpacingF = 250.0 res.cnLineThicknessF = 2.5 # create PWAT plot for analysis data MD_plot = ngl.contour_map(wks,MD,res) ngl.maximize_plot(wks, MD_plot) ngl.draw(MD_plot) ngl.frame(wks) ngl.destroy(wks) del res del MD #del CIN ################################################################################################### # open forecast file f_fili = "GFS_forecast_%s_%s.nc" % (init_dt[:8], init_dt[8:10]) forecast = nio.open_file(diri+f_fili)
res.mpNationalLineThicknessF = 1.5 res.mpGeophysicalLineColor = "gray40" res.mpGeophysicalLineThicknessF = 1.5 res.cnMonoLineColor = True res.cnLevelSelectionMode = "ManualLevels" res.cnMinLevelValF = 0.0 res.cnMaxLevelValF = 65.0 res.cnLevelSpacingF = 2.5 res.cnLineThicknessF = 2.5 # create PWAT plot for analysis data PWAT_plot = ngl.contour_map(wks, PWAT, res) ngl.maximize_plot(wks, PWAT_plot) ngl.draw(PWAT_plot) ngl.frame(wks) ngl.destroy(wks) del res del PWAT #del CIN ################################################################################################### # open forecast file f_fili = "GFS_forecast_%s_%s.nc" % (init_dt[:8], init_dt[8:10]) forecast = nio.open_file(diri + f_fili)
vcres.vcRefAnnoFontHeightF = 0.005 vcres.vcLineArrowThicknessF = 2.0 # create vector plot for analysis data and overlay on colour contours level 1 uv_plot1 = ngl.vector(wks,u_1,v_1,vcres) # create vector plot for analysis data and overlay on colour contours level2 vcres.vcLineArrowColor = "Red" uv_plot2 = ngl.vector(wks,u_2,v_2,vcres) ngl.overlay(shear_plot,uv_plot1) ngl.overlay(shear_plot,uv_plot2) ngl.maximize_plot(wks, shear_plot) ngl.draw(shear_plot) ngl.frame(wks) ngl.destroy(wks) del res del vcres ################################################################################################### # open forecast file f_fili = "GFS_48h_forecast_%s_%s.nc" % (init_dt[:8], init_dt[8:10]) forecast = nio.open_file(diri+f_fili)
res.cnLineThicknessF = 5.0
res.cnLineColor = "steelblue1"
res.cnLevelSelectionMode = "ManualLevels"
res.cnMinLevelValF = -85.0
res.cnMaxLevelValF = 115.0
res.cnLevelSpacingF = 100.0
# plot ITD and overlay on colour contours
ws_plot2 = ngl.contour(wks, ws, res)
ngl.overlay(ws_plot, ws_plot2)
ngl.overlay(ws_plot, uv_plot)
ngl.maximize_plot(wks, ws_plot)
ngl.draw(ws_plot)
ngl.frame(wks)
ngl.destroy(wks)
del res
del vcres
###################################################################################################
# open forecast file
f_fili = "GFS_forecast_%s_%s.nc" % (init_dt[:8], init_dt[8:10])
forecast = nio.open_file(diri + f_fili)
# loop through forecast times
res.cnLineThicknessF = 2.5 res.cnInfoLabelOn = True res.cnInfoLabelString = "CIN Contours at -50, -100 and -250 J/Kg" res.cnInfoLabelOrthogonalPosF = -0.06 res.cnInfoLabelParallelPosF = 0.505 res.cnLevelSelectionMode = "ExplicitLevels" res.cnLevels = [-250.0, -100.0, -50.0] # plot CIN and overlay on colour contours CIN_plot = ngl.contour(wks,CIN,res) ngl.overlay(CAPE_plot,CIN_plot) ngl.maximize_plot(wks, CAPE_plot) ngl.draw(CAPE_plot) ngl.frame(wks) ngl.destroy(wks) del res del CAPE del CIN ################################################################################################### # open forecast file f_fili = "GFS_forecast_%s_%s.nc" % (init_dt[:8], init_dt[8:10]) forecast = nio.open_file(diri+f_fili)
res.mpGridAndLimbOn = True
res.pmTickMarkDisplayMode = "Never"
res.mpProjection = "CylindricalEquidistant"
res.mpLimitMode = "LatLon" # Limit the map view.
res.mpMinLonF = lontr
res.mpMaxLonF = lonbl
res.mpMinLatF = lattr
res.mpMaxLatF = latbl
res.mpOutlineBoundarySets = "AllBoundaries"
res.mpNationalLineColor = colour
res.mpNationalLineThicknessF = 2.0
res.mpGeophysicalLineColor = colour
res.mpGeophysicalLineThicknessF = 2.0
res.mpGridLatSpacingF = 5.0
res.mpGridLonSpacingF = 5.0
res.mpGridLineThicknessF = 2.0
res.cnMonoLineColor = True
map_plot = ngl.map(wks,res)
ngl.maximize_plot(wks, map_plot)
ngl.draw(map_plot)
ngl.frame(wks)
ngl.destroy(wks)
del res
os.system('mogrify -trim map_'+colour+'_'+region+'.png')
# os.system('mogrify -resize 1350x900 map_'+colour+'_'+region+'.png')
res.cnMonoLineColor = True max_cont = 0.0001 min_cont = -0.0001 res.cnLevelSelectionMode = "ManualLevels" res.cnMinLevelValF = min_cont res.cnMaxLevelValF = max_cont res.cnLevelSpacingF = (max_cont - min_cont) / 15.0 res.cnLineThicknessF = 2.5 # create convergence plot for analysis data conv_plot = ngl.contour_map(wks, conv, res) ngl.maximize_plot(wks, conv_plot) ngl.draw(conv_plot) ngl.frame(wks) ngl.destroy(wks) del res ################################################################################################### # open forecast file f_fili = "GFS_forecast_%s_%s.nc" % (init_dt[:8], init_dt[8:10]) forecast = nio.open_file(diri + f_fili) # loop through forecast times for i in range(0, len(fore)):
min_cont = -0.25 if float(lev_hPa) >=700: max_cont = 0.1 min_cont = -0.1 res.cnLevelSelectionMode = "ManualLevels" res.cnMinLevelValF = min_cont res.cnMaxLevelValF = max_cont res.cnLevelSpacingF = (max_cont-min_cont)/20.0 res.cnLineThicknessF = 2.5 # create pv plot for analysis data pv_plot = ngl.contour_map(wks,pv,res) ngl.maximize_plot(wks, pv_plot) ngl.draw(pv_plot) ngl.frame(wks) ngl.destroy(wks) del res ################################################################################################### # open forecast file f_fili = "GFS_forecast_%s_%s.nc" % (init_dt[:8], init_dt[8:10]) forecast = nio.open_file(diri+f_fili) # loop through forecast times for i in range(0, len(fore)):
if float(lev_hPa) >= 700:
max_cont = 305.0
min_cont = 265.0
lev_space = 2.0
res.cnLevelSelectionMode = "ManualLevels"
res.cnMinLevelValF = min_cont
res.cnMaxLevelValF = max_cont
res.cnLevelSpacingF = lev_space
res.cnLineThicknessF = 2.5
# create plot for analysis data
temp_plot = ngl.contour_map(wks, temp, res)
ngl.maximize_plot(wks, temp_plot)
ngl.draw(temp_plot)
ngl.frame(wks)
ngl.destroy(wks)
del res
###################################################################################################
# open forecast file
f_fili = "GFS_forecast_%s_%s.nc" % (init_dt[:8], init_dt[8:10])
forecast = nio.open_file(diri + f_fili)
# loop through forecast times
res.cnMonoLineColor = True max_cont = (2.0 * round(np.max(mslp / 2.0), 0)) + 10.0 min_cont = (2.0 * round(np.min(mslp / 2.0), 0)) - 10.0 res.cnLevelSelectionMode = "ManualLevels" res.cnMinLevelValF = min_cont res.cnMaxLevelValF = max_cont res.cnLevelSpacingF = 2. res.cnLineThicknessF = 2.5 # create plot for analysis data mslp_plot = ngl.contour_map(wks, mslp, res) ngl.maximize_plot(wks, mslp_plot) ngl.draw(mslp_plot) ngl.frame(wks) ngl.destroy(wks) del res ################################################################################################### # open forecast file f_fili = "GFS_forecast_%s_%s.nc" % (init_dt[:8], init_dt[8:10]) forecast = nio.open_file(diri + f_fili) # loop through forecast times
res.cnMonoLineColor = True max_cont = 0.00025 min_cont = -0.00025 res.cnLevelSelectionMode = "ManualLevels" res.cnMinLevelValF = min_cont res.cnMaxLevelValF = max_cont res.cnLevelSpacingF = 0.000025 res.cnLineThicknessF = 2.5 # create plot for analysis data vort_plot = ngl.contour_map(wks, vort, res) ngl.maximize_plot(wks, vort_plot) ngl.draw(vort_plot) ngl.frame(wks) ngl.destroy(wks) del res ################################################################################################### # open forecast file f_fili = "GFS_forecast_%s_%s.nc" % (init_dt[:8], init_dt[8:10]) forecast = nio.open_file(diri + f_fili) # loop through forecast times
res.cnMonoLineColor = True max_cont = (2.0 * round(np.max(geopot / 2.0), 0)) + 10.0 min_cont = (2.0 * round(np.min(geopot / 2.0), 0)) - 10.0 res.cnLevelSelectionMode = "ManualLevels" res.cnMinLevelValF = min_cont res.cnMaxLevelValF = max_cont res.cnLevelSpacingF = 2. res.cnLineThicknessF = 2.5 # create plot for analysis data geo_plot = ngl.contour_map(wks, geopot, res) ngl.maximize_plot(wks, geo_plot) ngl.draw(geo_plot) ngl.frame(wks) ngl.destroy(wks) del res ################################################################################################### # open forecast file f_fili = "GFS_forecast_%s_%s.nc" % (init_dt[:8], init_dt[8:10]) forecast = nio.open_file(diri + f_fili) # loop through forecast times
res.cnLineDashPattern = 11
res.cnLineThicknessF = 5.0
res.cnLineColor = "purple"
res.cnLevelSelectionMode = "ManualLevels"
res.cnMinLevelValF = -85.0
res.cnMaxLevelValF = 115.0
res.cnLevelSpacingF = 100.0
# plot ITD and overlay on colour contours
dp_plot2 = ngl.contour(wks, dewpoint, res)
ngl.overlay(dp_plot, dp_plot2)
ngl.maximize_plot(wks, dp_plot)
ngl.draw(dp_plot)
ngl.frame(wks)
ngl.destroy(wks)
del res
del dewpoint
###################################################################################################
# open forecast file
f_fili = "GFS_forecast_%s_%s.nc" % (init_dt[:8], init_dt[8:10])
forecast = nio.open_file(diri + f_fili)
# loop through forecast times
vcres.vcRefMagnitudeF = 30.0 # define vector ref mag
vcres.vcRefLengthF = 0.03 # define length of vec ref
vcres.vcMinFracLengthF = 0.3
vcres.vcMinDistanceF = 0.02
vcres.vcRefAnnoOrthogonalPosF = -0.20
vcres.vcRefAnnoFontHeightF = 0.005
vcres.vcLineArrowThicknessF = 2.0
# create vector plot for analysis data and overlay on colour contours
uv_plot1 = ngl.vector(wks, max_shear_u2_u1, max_shear_v2_v1, vcres)
# create vector plot for analysis data and overlay on colour contours level2
ngl.overlay(PRATE_plot, uv_plot1)
ngl.maximize_plot(wks, PRATE_plot)
ngl.draw(PRATE_plot)
ngl.frame(wks)
ngl.destroy(wks)
del res.mpProjection
del res.mpLimitMode
del res.mpMinLonF
del res.mpMaxLonF
del res.mpMinLatF
del res.mpMaxLatF
# del res.mpPerimOn
del res.mpOutlineBoundarySets
del res.mpNationalLineColor
del res.mpNationalLineThicknessF
vcres.vcFillArrowsOn = True vcres.vcRefMagnitudeF = 30.0 # define vector ref mag vcres.vcRefLengthF = 0.02 # define length of vec ref vcres.vcMinFracLengthF = 0.3 vcres.vcMinDistanceF = 0.02 vcres.vcRefAnnoOrthogonalPosF = -0.20 vcres.vcRefAnnoFontHeightF = 0.005 cnres.tiMainString = "Fully opaque filled vectors over filled contours" #---Draw fully opaque vectors uv_plot = Ngl.vector(wks,u,v,vcres) spd_plot = Ngl.contour_map(wks,spd,cnres) Ngl.overlay(spd_plot,uv_plot) Ngl.maximize_plot(wks, spd_plot) Ngl.draw(spd_plot) Ngl.frame(wks) #---This time make vectors partially transparent vcres.vcGlyphOpacityF = 0.3 cnres.tiMainString = "Partially transparent vectors over filled contours" uv_plot = Ngl.vector(wks,u,v,vcres) spd_plot = Ngl.contour_map(wks,spd,cnres) Ngl.overlay(spd_plot,uv_plot) Ngl.maximize_plot(wks, spd_plot) Ngl.draw(spd_plot) Ngl.frame(wks)
lbres.lbTitleOffsetF = 0.00 #---Create the labelbar labels = ["0","1","2","3"] lbid = Ngl.labelbar_ndc (wks,len(labels),labels,0.0,0.,lbres) # # Create some annotation resources indicating how we want to # attach the labelbar to the plot. The default is the center # of the plot. Below amOrthogonalPosF is set to move the # labelbar down and outside the plot. # amres = Ngl.Resources() amres.amOrthogonalPosF = 0.7 annoid = Ngl.add_annotation(plot,lbid,amres) txres = Ngl.Resources() txres.txFontHeightF = 0.01 txres.txJust = "TopRight" txres.txPerimOn = True txid = Ngl.add_text(wks,plot,flnm,res.mpMaxLonF,res.mpMaxLatF,txres) #---This will resize plot so it and the labelbar fit in the frame. Ngl.maximize_plot(wks, plot) #---Drawing the original map also draws the attached labelbar. Ngl.draw(plot) Ngl.frame(wks) Ngl.end()
def draw_gh_500hPa(sel_year, sel_month):
print("darwing 500hPa gh 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/',
'gh_500_*.grb')))
f_cli = xr.open_mfdataset(files_cli,
concat_dim="time",
combine="nested",
engine="cfgrib",
parallel=True)
h = f_cli["z"]
h = h.mean(dim="time")
h_cli = h / 98
lat = f_cli["latitude"].values
lon = f_cli["longitude"].values
file_cur = "/home/alley/work/Dong/mongo/seasonal_analysis/data/data/download_from_mongo/cur/gh_500_" + str(
sel_year) + str(sel_month).zfill(2) + ".grb"
# print(file_cur)
f_cur = xr.open_mfdataset(file_cur, engine="cfgrib", parallel=True)
h_cur = f_cur["z"] / 98
h_ano = h_cur - h_cli
leftString = "500hPa Height & Anomaly for " + str(sel_month) + str(
sel_year)
rightString = "dagpm"
wks_type = 'png'
wks = Ngl.open_wks(
wks_type,
'/home/alley/work/Dong/mongo/seasonal_analysis/images/gh_500hPa_' +
str(sel_year) + str(sel_month).zfill(2) + '.png')
res = Ngl.Resources()
res.nglFrame = False
res.nglDraw = False
res.mpLimitMode = "LatLon"
res.mpMinLonF = 60
res.mpMaxLonF = 180
res.mpMinLatF = 0
res.mpMaxLatF = 60
plot_map = Ngl.map(wks, res)
fres = Ngl.Resources()
fres.nglFrame = False
fres.nglDraw = False
fres.cnFillOn = True
fres.sfXArray = lon
fres.sfYArray = lat
fres.lbOrientation = "Horizontal" # horizontal labelbar
fres.cnLinesOn = False
fres.cnLineLabelsOn = False
fres.cnLevelSelectionMode = "ExplicitLevels"
fres.cnFillPalette = "BlueDarkRed18"
fres.cnLevels = np.arange(-5, 6, 1)
plot_cn = Ngl.contour(wks, h_ano, fres)
cnres = Ngl.Resources()
cnres.nglDraw = False
cnres.nglFrame = False
cnres.cnFillOn = False
cnres.cnLinesOn = True
cnres.cnLineLabelsOn = True
cnres.cnInfoLabelOn = False
cnres.sfXArray = lon
cnres.sfYArray = lat
cnres.cnLevelSelectionMode = "ExplicitLevels"
cnres.cnLevels = np.arange(500, 600, 4)
cnres.cnLineColor = "black"
cnres.cnLineThicknessF = 5
plot2 = Ngl.contour(wks, h_cur, cnres)
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(plot_map)
Ngl.frame(wks)
Ngl.end()
print("Finish darwing 500hPa gh plot plot for " + str(sel_month).zfill(2) +
" " + str(sel_year))
bres.tmXBLabelFontHeightF = 0.015 # Make labels smaller. This
# will affect Y labels too.
#---Set the values and labels for the Y axis of blank plot.
bres.tmYLMode = "Explicit"
bres.tmYLValues = lat_values
bres.tmYLLabels = lat_labels
#---Align four corners of both plots, that is, don't do data transformation
bres.tfDoNDCOverlay = True
#---Create the blank plot.
blank = Ngl.blank_plot(wks,bres)
#---Draw blank plot for debugging purposes.
#Ngl.draw(blank)
#Ngl.frame(wks)
#---Overlay blank plot on existing map plot.
Ngl.overlay(map.base,blank)
#---Resize map so it fits within frame
Ngl.maximize_plot(wks, map)
#---Drawing the original map also draws the overlaid blank plot
Ngl.draw(map)
Ngl.frame(wks)
Ngl.end()
res.mpNationalLineThicknessF = 1.5 res.mpGeophysicalLineColor = "gray40" res.mpGeophysicalLineThicknessF = 1.5 res.cnMonoLineColor = True res.cnLevelSelectionMode = "ManualLevels" res.cnMinLevelValF = -20.0 res.cnMaxLevelValF = 40.0 res.cnLevelSpacingF = 2.0 res.cnLineThicknessF = 2.5 # create DPTMP2 plot for analysis data DPTMP2_plot = ngl.contour_map(wks, DPTMP2, res) ngl.maximize_plot(wks, DPTMP2_plot) ngl.draw(DPTMP2_plot) ngl.frame(wks) ngl.destroy(wks) del res del DPTMP2 #del CIN ################################################################################################### # open forecast file f_fili = "GFS_forecast_%s_%s.nc" % (init_dt[:8], init_dt[8:10]) forecast = nio.open_file(diri + f_fili)
res.cnMonoLineColor = True max_cont = 100.0 min_cont = 0.0 res.cnLevelSelectionMode = "ManualLevels" res.cnMinLevelValF = min_cont res.cnMaxLevelValF = max_cont res.cnLevelSpacingF = 2.5 res.cnLineThicknessF = 2.5 # create relative humidity plot for analysis data rh_plot = ngl.contour_map(wks, rh, res) ngl.maximize_plot(wks, rh_plot) ngl.draw(rh_plot) ngl.frame(wks) ngl.destroy(wks) del res ################################################################################################### # open forecast file f_fili = "GFS_forecast_%s_%s.nc" % (init_dt[:8], init_dt[8:10]) forecast = nio.open_file(diri + f_fili) # loop through forecast times
vcres.vcMinFracLengthF = 0.3 vcres.vcMinDistanceF = 0.02 vcres.vcRefAnnoOrthogonalPosF = -0.20 vcres.vcRefAnnoFontHeightF = 0.005 vcres.vcLineArrowThicknessF = 2.0 # create vector plot for analysis data and overlay on colour contours level 1 uv_plot1 = ngl.vector(wks, max_shear_u2_u1, max_shear_v2_v1, vcres) PWAT_plot = ngl.contour(wks, PWAT, res) ngl.overlay(LI_plot, uv_plot1) ngl.overlay(LI_plot, PWAT_plot) ngl.maximize_plot(wks, LI_plot) ngl.draw(LI_plot) ngl.frame(wks) ngl.destroy(wks) del res del LI del PWAT del vcres del u1 del v1 del u2 del v2 del shear del max_shear del max_shear_u2_u1
res.mpMinLatF = lattr
res.mpMaxLatF = latbl
res.mpOutlineBoundarySets = "AllBoundaries"
res.mpNationalLineColor = -1
res.mpNationalLineThicknessF = 2.0
res.mpGeophysicalLineColor = -1
res.mpGeophysicalLineThicknessF = 2.0
res.mpGridLatSpacingF = 5.0
res.mpGridLonSpacingF = 5.0
res.mpGridLineThicknessF = 2.0
res.mpGridLineColor = colour
res.cnMonoLineColor = True
grid_plot = ngl.map(wks, res)
ngl.maximize_plot(wks, grid_plot)
ngl.draw(grid_plot)
ngl.frame(wks)
ngl.destroy(wks)
del res
os.system('mogrify -trim grid_' + colour + '_' + region + '.png')
# if region == "WA" or region == "unknownWA":
# os.system('mogrify -trim grid_'+colour+'_'+region+'.png')
# os.system('mogrify -resize 886x600 grid_'+colour+'_'+region+'.png')
# elif region == "EA" or region == "unknownEA":
# os.system('mogrify -trim grid_'+colour+'_'+region+'.png')
# os.system('mogrify -resize 600x733 grid_'+colour+'_'+region+'.png')
res.cnMonoLineColor = True max_cont = (2.0*round(np.max(theta/2.0),0))+10.0 min_cont = (2.0*round(np.min(theta/2.0),0))-10.0 res.cnLevelSelectionMode = "ManualLevels" res.cnMinLevelValF = 290.0 #min_cont res.cnMaxLevelValF = 355.0 #max_cont res.cnLevelSpacingF = 2.5 res.cnLineThicknessF = 2.5 # create plot for analysis data theta_plot = ngl.contour_map(wks,theta,res) ngl.maximize_plot(wks, theta_plot) ngl.draw(theta_plot) ngl.frame(wks) ngl.destroy(wks) del res ################################################################################################### # open forecast file f_fili = "GFS_forecast_%s_%s.nc" % (init_dt[:8], init_dt[8:10]) forecast = nio.open_file(diri+f_fili) # loop through forecast times
res.tiMainFontColor = "Navy" res.tiMainOffsetYF = 0.02 res.tiMainFontHeightF = 0.035 res.tiYAxisString = "Left Y axis string" res.stMonoLineColor = False # Use multiple colors for streamlines. res.stLineThicknessF = 2.0 # Twice as thick res.lbOrientation = "Horizontal" res.pmLabelBarOrthogonalPosF = -0.02 res.pmLabelBarHeightF = 0.1 res.pmLabelBarWidthF = 0.6 plot = Ngl.streamline_scalar(wks, u, v, spd, res) # Create streamline plot. txres = Ngl.Resources() # Text resources desired txres.txFontColor = "OrangeRed" subtitles(wks, plot, "Left string", "Center string", "Right string", txres) del txres.txFontColor # Go back to foreground color (black) txres.txFontHeightF = 0.029 right_axis(wks, plot, "Right Y axis string", txres) Ngl.maximize_plot(wks, plot) Ngl.draw(plot) # Drawing the plot will draw the three subtitles attached. Ngl.frame(wks) Ngl.end()
res.cnMonoLineColor = True max_cont = 0.00005 min_cont = -0.00005 res.cnLevelSelectionMode = "ManualLevels" res.cnMinLevelValF = min_cont res.cnMaxLevelValF = max_cont res.cnLevelSpacingF = (max_cont - min_cont) / 20.0 res.cnLineThicknessF = 2.5 # create divergence plot for analysis data div_plot = ngl.contour_map(wks, div, res) ngl.maximize_plot(wks, div_plot) ngl.draw(div_plot) ngl.frame(wks) ngl.destroy(wks) del res ################################################################################################### # open forecast file f_fili = "GFS_forecast_%s_%s.nc" % (init_dt[:8], init_dt[8:10]) forecast = nio.open_file(diri + f_fili) # loop through forecast times for i in range(0, len(fore)):
Ngl.overlay(map_plot,fill_contour_plot) Ngl.overlay(map_plot,line_contour_plot) Ngl.overlay(map_plot,vector_plot) # # Change the title. # srlist = Ngl.Resources() srlist.tiMainString = "vectors, line, and filled contours" Ngl.set_values(map_plot,srlist) # # Draw the map plot, which now contains the vectors and # filled/line contours. # Ngl.maximize_plot(wks,map_plot) # Maximize size of plot in frame. Ngl.draw(map_plot) Ngl.frame(wks) # # Change the title. # srlist.tiMainString = "line and filled contours" Ngl.set_values(map_plot,srlist) # # Remove the vector plot and redraw. We should now # just see the line contours and filled contours. # Ngl.remove_overlay(map_plot,vector_plot,0) Ngl.draw(map_plot)
def print_comp_for_timestamp(wrf_data, timestamp, filepath):
slp = pressure_lib.get_sea_level_pressure(wrf_data)
temperature = getvar(wrf_data,"tc")
u = get_latitude_wind(wrf_data)
v = get_longitude_wind(wrf_data)
lat, lon = latlon_coords(temperature)
lat_normal = to_np(lat)
lon_normal = to_np(lon)
# temperature
t_res = get_pyngl(temperature)
t_res.nglDraw = False # don't draw plot
t_res.nglFrame = False # don't advance frame
t_res.cnFillOn = True # turn on contour fill
t_res.cnLinesOn = False # turn off contour lines
t_res.cnLineLabelsOn = False # turn off line labels
t_res.cnFillMode = "RasterFill" # These two resources
t_res.cnFillPalette = "BlAqGrYeOrReVi200"
t_res.cnLevelSelectionMode = "ManualLevels"
t_res.cnMinLevelValF = -25.0 # min. temperature for composite
t_res.cnMaxLevelValF = 45.0 # max. temperature for composite
t_res.cnLevelSpacingF = 1 # increment
t_res = geography_lib.initialize_geography(t_res, "gray25")
t_res.lbTitleString = "%s in (%s)" % (temperature.description,temperature.units)
t_res.lbOrientation = "horizontal"
t_res.lbTitleFontHeightF = 0.015
t_res.lbLabelFontHeightF = 0.015
t_res.tiMainString = "Composite (%s)" % timestamp.strftime("%b %d %Y %HUTC")
t_res.trGridType = "TriangularMesh" # can speed up plotting.
t_res.tfDoNDCOverlay = True # required for native projection
# pressure
p_res = pressure_lib.get_pressure_resource(lat_normal, lon_normal)
# wind
uv_res = Ngl.Resources()
uv_res.nglDraw = False # don't draw plot
uv_res.nglFrame = False # don't advance frame
uv_res.vcFillArrowsOn = True
uv_res.vcRefMagnitudeF = 15.0
uv_res.vcRefLengthF = 0.03
uv_res.vcMinDistanceF = 0.02
uv_res.vcRefAnnoFontHeightF = 0.01
uv_res.vcRefAnnoString1 = "$VMG$ m/s"
uv_res.vcRefAnnoString2 = "ground windspeed (m/s) reference"
uv_res.vfXArray = lon_normal
uv_res.vfYArray = lat_normal
wk_res = Ngl.Resources()
wk_res.wkWidth = 2500
wk_res.wkHeight = 2500
output_path = "%scomp_%s" % (filepath, timestamp.strftime("%Y_%m_%d_%H"))
wks_comp = Ngl.open_wks("png", output_path, wk_res)
# creating plots for the measurands
tplot = Ngl.contour_map(wks_comp,temperature[0,:,:],t_res)
pplot = Ngl.contour(wks_comp,slp,p_res)
vector = Ngl.vector(wks_comp,u,v,uv_res)
Ngl.overlay(tplot, vector)
Ngl.overlay(tplot, pplot)
Ngl.maximize_plot(wks_comp, tplot)
Ngl.draw(tplot)
Ngl.frame(wks_comp)
Ngl.delete_wks(wks_comp) # delete currently used workstation
