def info(ff, pyngl_map=True, print_timeid=False):
''' domain information of WRF output '''
ts = getvar(ff, "times", timeidx=ALL_TIMES) #-1 isn't work
nt = np.int32(len(ts))
dtimes = []
#for t in ts:
# dtimes.append(str(t.values)[0:19])
dtimes = [str(t.values)[0:19] for t in ts]
#print("\033[44m{}\033[0m".format(dtimes[0]))
var = getvar(ff, "QCLOUD", timeidx=0) #Xarray
(nz, ny, nx) = var.shape #nz = np.int32(len(var[:,0,0]))
(lat, lon) = latlon_coords(var) # Get the latitude and longitude points
lat = to_np(lat)
lon = to_np(lon)
print(u'nt:{}'.format(nt)+'|nz:{}'.format(nz)+\
'|ny:{}'.format(ny)+'|nx:{} '.format(nx)+'.'*6+'Get Dimensions '+ \
'and coordinates(lat. & long.)')
if pyngl_map:
#Set some map options based on information in WRF output file
res = get_pyngl(var)
del var
res.tfDoNDCOverlay = True # required for native projection
print(
'pyngl_map = {}, Get WRF map-related resources'.format(pyngl_map))
else:
res = Ngl.Resources()
if print_timeid:
for i, dtime in enumerate(dtimes):
print('\033[95m({:02d}){}\033[0m'.format(i, dtime))
return nt, nz, ny, nx, dtimes, lat, lon, res
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 initialize_rain_resource(rain_con):
rr_res = get_pyngl(rain_con)
rr_res.nglDraw = False # don't draw plot
rr_res.nglFrame = False # don't advance frame
rr_res.cnFillOn = True # turn on contour fill
rr_res.cnLinesOn = False # turn off contour lines
rr_res.cnLineLabelsOn = False # turn off line labels
rr_res.cnFillMode = "RasterFill" # These two resources
rr_res.cnLevelSelectionMode = "ExplicitLevels"
rr_res.cnFillColors = numpy.array([ [255,255,255], [255,255,255], [152,251,152], \
[127,255, 0], [ 50,205, 50], [ 0,255, 0], \
[ 0,128, 0], [ 0,100, 0], [255,255, 0], \
[255,165, 0], [255, 69, 0], [139, 0,139], \
[ 0, 0, 255] ],'f') / 255.
rr_res.cnLevels = numpy.array( [ .1, .2, .4, .8, 1.6, 3.2, 6.4, \
12.8, 25.6, 51.2, 102.4, 204.8 ])
rr_res = geography_lib.initialize_geography(rr_res, "gray50")
return rr_res
"You do not have the necessary '{}' file to run this example.".format(
filename))
print("You need to supply your own WRF output file")
print("WRF output files usually have names like '{}'".format(filename))
sys.exit()
#---Read data
a = Nio.open_file(filename + ".nc") # Must add ".nc" suffix for Nio.open_file
tc = getvar(a, "tc")
#---Open file for graphics
wks_type = "png"
wks = Ngl.open_wks(wks_type, "wrf3")
# Set some map options based on information in WRF output file
res = get_pyngl(tc)
res.tfDoNDCOverlay = True # required for native projection
#---Contour options
res.cnFillOn = True # turn on contour fill
res.cnLinesOn = False # turn off contour lines
res.cnLineLabelsOn = False # turn off line labels
res.cnFillMode = "RasterFill" # These two resources
res.trGridType = "TriangularMesh" # can speed up plotting.
res.cnFillPalette = "ncl_default"
res.lbOrientation = "horizontal" # default is vertical
res.pmLabelBarHeightF = 0.08
res.pmLabelBarWidthF = 0.65
res.lbTitleString = "%s (%s)" % (tc.description, tc.units)
res.lbTitleFontHeightF = 0.015
print("No shapefile outlines will be added.")
ADD_SHAPE_OUTLINES = False
else:
ADD_SHAPE_OUTLINES = True
#---Read data
a = Nio.open_file("{}.nc".format(wrf_filename))
var_name = "slp" # "slp", "ter"
var = getvar(a, var_name)
#---Send graphics to PNG file
wks_type = "png"
wks = Ngl.open_wks(wks_type, "wrf2")
# Set some map options based on information in WRF output file
res = get_pyngl(var)
res.tfDoNDCOverlay = True # required for native projection
# Contour options
res.cnFillOn = True # turn on contour fill
res.cnLinesOn = False # turn off contour lines
res.cnLineLabelsOn = False # turn off line labels
if var_name == "ter":
#
# You may need to change these levels depending on your WRF output file.
# Try first running this script with these two lines commented out.
# This is for terrain
#
res.cnFillPalette = "OceanLakeLandSnow"
res.cnLevelSelectionMode = "ExplicitLevels"
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