def add_polymarker(wks, plot, xd, yd, index, size, thick, color):
"""https://www.ncl.ucar.edu/Document/Functions/Built-in/NhlNewMarker.shtml"""
poly_res = Ngl.Resources()
poly_res.gsMarkerIndex = index #4 # choose circle as polymarker
poly_res.gsMarkerSizeF = size # select size to avoid streaking
poly_res.gsMarkerThicknessF = thick #30.0
#poly_res.gsMarkerOpacityF = 0.3
poly_res.gsMarkerColor = color #purple4 # choose color
return Ngl.add_polymarker(wks, plot, xd, yd, poly_res)
def add_trajectories(wks,map,filename,cmap):
#---Open the netCDF file containing the salinity data for the trajectories.
ncfile = Nio.open_file(filename)
traj = [1,10,53,67,80] # choose which trajectories to plot
pres = Ngl.Resources() # polyline resources
pres.gsLineThicknessF = 5.0 # line thickness
mres = Ngl.Resources() # marker resources
mres.gsMarkerSizeF = 17.0 # marker size
mres.gsMarkerColor = "black" # marker color
mres.gsMarkerIndex = 15 # circle with an X
mres.gsMarkerThicknessF = 2.0 # thicker marker outlines
#
# Loop through the chosen trajectories.
#
sdata = ncfile.variables["sdata"]
sid = []
for i in range(len(traj)):
lat = sdata[2,:,traj[i]] # extract lat from whole array
lon = sdata[1,:,traj[i]] # extract lon from whole array
sst = sdata[8,:,traj[i]]
#
# Map the salinity values between 34.55 and 34.85 into color
# indices between 0 and 9 and draw polylines, with those
# colors, between adjacent lat/lon values.
#
for j in range(len(lat)-2):
sval = 0.5*(sst[j]+sst[j+1])
cindex = nint(30.*(sval-34.55))
pres.gsLineColor = cmap[cindex]
sid.append(Ngl.add_polyline(wks,map,[lon[j],lon[j+1]],[lat[j],lat[j+1]],pres))
#---Draw a polymarker at the beginning of each trajectory.
sid.append(Ngl.add_polymarker(wks,map,[lon[0]],[lat[0]],mres))
return
def add_masked_grid(wks,plot,lat,lon,mask): # # Create 2D arrays of lat/lon so we can draw markers outside the # masked area # nlat = len(lat) nlon = len(lon) lat2d = numpy.tile(lat,nlon) lat2d = numpy.reshape(lat2d,[nlon,nlat]) lat2d = numpy.transpose(lat2d) lon2d = numpy.tile(lon,nlat) lon2d = numpy.reshape(lon2d,[nlat,nlon]) lat1d_mask = ma.ravel(ma.masked_where(mask==0,lat2d)) lon1d_mask = ma.ravel(ma.masked_where(mask==0,lon2d)) mkres = Ngl.Resources() mkres.gsMarkerIndex = 16 # filled dot mkres.gsMarkerSizeF = 0.003 mkres.gsMarkerColor = "purple" return Ngl.add_polymarker(wks,plot,lon1d_mask,lat1d_mask,mkres)
# # Transpose the array so we can plot it, because Natgrid returns it # as an X x Y array, rather than Y x X which PyNGL expects. # zt = numpy.transpose(zo) contour = Ngl.contour(wks,zt,resources) # # Add some polymarkers showing the original locations of the X,Y points. # poly_res = Ngl.Resources() poly_res.gsMarkerIndex = 16 poly_res.gsMarkerSizeF = 0.015 Ngl.add_polymarker(wks,contour,x,y,poly_res) Ngl.draw(contour) Ngl.frame(wks) # # Now turn on RasterFill for the contours and compare. # resources.tiMainString = "Interpolation to a 2D grid (RasterFill)" resources.cnFillMode = 'RasterFill' contour = Ngl.contour(wks,zt,resources) # # Draw polymarkers again. #
#-- add polygon and polyline to map
gon_2 = Ngl.add_polygon(wks, map, x, y, pres)
plres.gsLineColor = "darkorange" #-- set line color
box_2 = Ngl.add_polyline(wks, map, x, y, plres)
#----------------------------------------------------------------
#-- polymarker resources
#----------------------------------------------------------------
pmres = Ngl.Resources()
pmres.gsMarkerColor = "blue" #-- marker color
pmres.gsMarkerIndex = 1 #-- use marker 1
pmres.gsMarkerSizeF = 0.03 #-- set size of marker
pmres.gsLineThicknessF = 8. #-- marker line thickness
#-- unique identifier name for polymarker drawing, here marker_1
marker_1 = Ngl.add_polymarker(wks, map, -100., 30., pmres)
#----------------------------------------------------------------
#-- draw all 16 marker on plot using unique identifier name and
#-- additional map attribute settings
#----------------------------------------------------------------
x = -160. #-- x-position of first marker
y = -80. #-- y-position of first marker
idstr = "poly"
for i in range(0, 16): #-- 16 different marker
pmres.gsMarkerIndex = i + 1
id = idstr + str(i) #-- result is poly0-poly15
#-- add marker to map
map.id = Ngl.add_polymarker(wks, map, x + (i * 20.), y + (i * 10.), pmres)
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
# # Add primitives to plot. They will be drawn in the order # they are added, so some primitives may cover other ones. # # Be sure to use unique variable names on the left-hand side # for the Ngl.add_polyxxxx routines. # prim1 = Ngl.add_polyline(wks, xy1, xx, ymidline, gsres) prim2 = Ngl.add_polygon(wks, xy1, xsquare, ysquare, gsres) prim3 = Ngl.add_polyline(wks, xy1, xx, ytopline, gsres) prim4 = Ngl.add_polyline(wks, xy1, xx, ybotline, gsres) gsres.gsLineColor = "Green" prim5 = Ngl.add_polyline(wks, xy1, x[26:37], y[26:37], gsres) prim6 = Ngl.add_polymarker(wks, xy1, xdots, ydots, gsres) # # New Y points for second XY plot. # y = numpy.cos(3.14159 * x / 32.) # Create second XY plot, but don't draw it yet. xy2 = Ngl.xy(wks, x, y, xyres) # # Add primitives to second plot. # gsres.gsLineColor = "Blue"
cfres.mpGridAndLimbOn = False # Turn off grid and limb lines. pmres.gsMarkerSizeF = 0.0015 pmres.gsMarkerThicknessF = 0.1 pmres.gsMarkerOpacityF = 1 txres = Ngl.Resources() txres.txJust = "BottomCenter" txres.txFontHeightF = 0.025 title = 'Time of emergegence of FWI>p95 frequency~C~1-sigma above all forcing '+str(pyear0[base_pp])+'-'+str(pyear1[base_pp]) diff_cyc, lon_cyc = Ngl.add_cyclic(toe_diff_median_masked,lon) cfres.sfXArray = lon_cyc cfres.tiMainString = sf_list[ss] plot = Ngl.contour_map(wks,diff_cyc,cfres) pmres.gsMarkerColor = colors[np.int(ncolors/4),:] pmres.gsMarkerIndex = 1 marker_all = Ngl.add_polymarker(wks,plot,lon_1d_all,lat_1d_all,pmres) pmres.gsMarkerColor = colors[np.int(ncolors/4)*3,:] pmres.gsMarkerIndex = 1 marker_sf = Ngl.add_polymarker(wks,plot,lon_1d_sf,lat_1d_sf,pmres) Ngl.draw(plot) Ngl.text_ndc(wks,title,0.5,0.87,txres) Ngl.frame(wks) Ngl.delete_wks(wks)
mkres = Ngl.Resources() mkres.gsMarkerIndex = 2 mkres.gsMarkerColor = "Brown" Ngl.polymarker(wks, map, lon, lat, mkres) Ngl.frame(wks) #-- second plot res.mpMinLatF = 22. res.mpMaxLatF = 60. res.mpMinLonF = -125. res.mpMaxLonF = -65. map = Ngl.map(wks, res) #-- create the map plot, don't draw #-- Now attach the markers to the plot and notice that you don't #-- see them until you draw the plot. #-- If you resize the plot, the markers will be resized accordingly. mkres.gsMarkerColor = "Blue" mkres.gsMarkerSizeF = 15. #-- increase marker sizes dum = Ngl.add_polymarker(wks, map, lon, lat, mkres) #-- draw map and advance the frame Ngl.draw(map) Ngl.frame(wks) Ngl.end()
resources.nglFrame = False resources.nglDraw = False resources.mpOutlineBoundarySets = "GeophysicalAndUSStates" resources.mpLandFillColor = 16 resources.mpFillOn = True resources.sfXArray = lon resources.sfYArray = lat resources.cnFillPalette = "WhViBlGrYeOrRe" resources.cnLevelSelectionMode = "ExplicitLevels" resources.cnLevels = np.arange(1, 100, 10) resources.tiMainString = track_name + " maxwind " resources.lbTitleString = "Knots" #resources.lbTitlePosition = "Right" resources.lbLabelFontHeightF = 0.02 resources.lbTitleFontHeightF = 0.02 resources.cnFillMode = "RasterFill" mpid = Ngl.contour_map(wks, np.transpose(maxwind), resources) #mpid = Ngl.contour_map(wks, np.transpose(grid), resources) mkres = Ngl.Resources() mkres.gsMarkerIndex = 1 mkres.gsMarkerColor = "Black" mkres.gsMarkerSizeF = 15 dum = Ngl.add_polymarker(wks, mpid, lon_c, lat_c, mkres) Ngl.draw(mpid) Ngl.frame(wks) Ngl.end()
def plot_psiyr(wks,data,vx,vy,xlab='Latitude [deg N]',ylab = 'y',\
vsurf=[],hei=0.1,ylon=True,xon=False,lbar=False,flipy=False,\
vpx=0.15,vpy=0.8,lsmooth=False):
"""
Plots meridional overturning stream functions
Usage:
plot_psiyr(wks,data,vx,vy,xlab='Latitude',ylab='y',vsurf=np.array([]),\
hei=0.15,ylon=True,xon=True,lbar=True,flipy=False)
Input:
wks - Workstation ID
data - 2D matrix. Can be several matrices in a list
vx - Latitude vector
vy - y-vector. Can be several in a list
Optional:
xlab - Title for x-axis
ylab - Title for y-axis
vsurf - Vector of surface values to draw in
hei - Height of plot(s)
ylon - Turn on y labels on left side (else right)
xon - Turn on x labels on bottom
lbar - Turn on colorbar
Output:
None
"""
##
res = Ngl.Resources()
res.wkColorMap = 'ViBlGrWhYeOrRe'
Ngl.set_values(wks,res)
print ' Plotting overturning stream functions in (y,r) coordinates'
print lbar
if ( isinstance(data,list) ):
nplots = len(data)
else:
nplots = 1
data = [data]
vy = fill_blanks(vy,nplots)
ylab = fill_blanks(ylab,nplots)
vsurf = fill_blanks(vsurf,nplots)
ylon = fill_blanks(ylon,nplots)
xon = fill_blanks(xon,nplots)
lbar = fill_blanks(lbar,nplots)
lbar[0] = True
flipy = fill_blanks(flipy,nplots)
hei = max([0.8/(nplots+1),hei])
wth = min([0.7,hei * 4])
vpy = 0.9 - hei * np.arange(0,nplots+1)
##
## Color levels for y-r stream functions
##
colour_levels = np.arange(-190,210,20)
for jn in range(0,nplots):
zplot = data[jn]
res = Ngl.Resources()
res.nglMaximize = False
res.nglPaperOrientation = 'Portrait'
res.nglFrame = False
res.nglDraw = False
res.cnFillOn = True
res.cnLinesOn = True
res.cnLineLabelsOn = False
res.cnLineLabelDensityF = 2
res.cnLineLabelBackgroundColor = -1
res.cnLevelSelectionMode = 'ExplicitLevels'
res.cnLevels = colour_levels
res.sfXArray = vx
res.sfYArray = vy[jn]
res.vpXF = vpx
res.vpWidthF = wth
res.vpYF = vpy[jn]
res.vpHeightF = hei
##
## Axis
##
res.tiYAxisFontHeightF = 0.012
res.tiYAxisString = ylab[jn]
res.tiXAxisString = xlab
if( ylon[jn] == True ):
res.tiYAxisSide = 'Left'
res.tmYLLabelsOn = True
res.tmYRLabelsOn = False
res.tmYLLabelFontHeightF = 0.012
else:
res.tiYAxisSide = 'Right'
res.tmYLLabelsOn = False
res.tmYRLabelsOn = True
res.tmYRLabelFontHeightF = 0.012
if( xon[jn] == True ):
res.tiXAxisOn = True
res.tmXBLabelsOn = True
res.tiXAxisFontHeightF = 0.012
res.tmXBLabelFontHeightF = 0.012
else:
res.tiXAxisOn = False
res.tmXBLabelsOn = False
##
## Labelbar
##
if( lbar[jn] == True ):
res.lbTitleString = 'Sverdrup (10~S~9~N~kg/s)'
res.lbLabelFontHeightF = 0.012
res.lbTitleFontHeightF = 0.015
res.lbLabelBarOn = True
res.lbOrientation = 'Horizontal'
res.pmLabelBarSide = 'Top'
res.pmLabelBarDisplayMode = 'Always'
res.pmLabelBarWidthF = 0.65
res.pmLabelBarHeightF = 0.07
else:
res.lbLabelBarOn = False
##
## Flip y axis?
##
if( flipy[jn] == True ):
res.trYReverse = True
else:
res.trYReverse = False
## Smooth
if (lsmooth==True):
sigma = 2
order = 0
for ji in range(0,5):
ndimage.filters.gaussian_filter(zplot[:,:],sigma,order=order,\
output=zplot[:,:],\
mode='reflect', cval=0.0)
cont = Ngl.contour(wks,zplot,res)
##
## Also draw the surface values
##
if (vsurf[jn].shape[0] == vx.shape[0]):
lres = Ngl.Resources()
lres.gsLineThicknessF = 1.5
lres.gsLineColor = 'black'
lres.gsLineDashPattern = 1
line = Ngl.add_polyline(wks,cont,vx,vsurf[jn],lres)
else:
print ' Length of vx and vsurf do not agree '
## And show the max/min values
zmax = np.max( zplot.flatten() )
zmin = np.min( zplot.flatten() )
max_point = np.where(zplot == zmax)
min_point = np.where(zplot == zmin)
lmax = vx[max_point[1]][0]
ymax = vy[jn][max_point[0]][0]
print ' psimax = '+repr(zmax)
print ' at lat = '+repr(lmax)+', y = '+repr(ymax)
lmin = vx[min_point[1]][0]
ymin = vy[jn][min_point[0]][0]
print ' psimin = '+repr(zmin)
print ' at lat = '+repr(lmin)+', y = '+repr(ymin)
pres = Ngl.Resources()
pres.gsMarkerColor = 'black'
pres.gsMarkerThicknessF = 3.
mark = Ngl.add_polymarker(wks,cont,lmax,ymax,pres)
mark = Ngl.add_polymarker(wks,cont,lmin,ymin,pres)
Ngl.draw(cont)
#Ngl.frame(wks)
flux_label = ['LH flux [PW]',\
'DSE flux [PW]',\
'MSE flux [PW]',\
'Volume flux [m3/s]',
'Pressure flux [hPa]',\
'Sensible heat flux [PW]']
jj = 0
if(1):
vy2 = np.zeros((nplots,vx.shape[0]))
for jc in range(0,nplots):
zplot = data[jc][:,:]
chi = 0.5 * (vy[jc][1:] + vy[jc][:-1])
for jj in range(0,vx.shape[0]):
dpsi = zplot[1:,jj] - zplot[:-1,jj]
vy2[jc,jj] = np.sum(dpsi * chi)
vy2 = 10**(-3) * (-1) * vy2[:,:] # W->PW and change sign
linecolors = ['blue','red','black','green','yellow','purple']
del res
res = Ngl.Resources()
res.nglMaximize = False
res.nglPaperOrientation = 'Portrait'
res.nglFrame = False
res.nglDraw = True
res.xyLineColors = linecolors
#res.xyLineThicknesses = [2,2,2]
#res.xyLabelMode = 'Custom'
#res.xyExplicitLabels = ['LH','DSE','MSE']
#
#if( np.mod(jc,2) == 0):
# res.tiYAxisSide = 'Left'
# res.tmYLLabelsOn = True
# res.tmYRLabelsOn = False
#else:
# res.tiYAxisSide = 'Right'
# res.tmYLLabelsOn = False
# res.tmYRLabelsOn = True
#
#if( jc == icoord-1):
# res.tiXAxisOn = True
# res.tmXBLabelsOn = True
#else:
# res.tiXAxisOn = False
# res.tmXBLabelsOn = False
## Axis
res.tiXAxisString = 'Latitude'
res.tiYAxisString = '[PW]'
res.tiXAxisFontHeightF = 0.012
res.tiYAxisFontHeightF = 0.012
res.tmXBLabelFontHeightF = 0.012
res.tmYLLabelFontHeightF = 0.012
res.trYMaxF = 6.
res.trYMinF = -6.
res.vpXF = vpx
res.vpWidthF = wth
res.vpYF = vpy[-1]
res.vpHeightF = hei
cont = Ngl.xy(wks,vx,vy2[0:3],res)
Ngl.frame(wks)
# # Transpose the array so we can plot it, because Natgrid returns it # as an X x Y array, rather than Y x X which PyNGL expects. # zt = numpy.transpose(zo) contour = Ngl.contour(wks, zt, resources) # # Add some polymarkers showing the original locations of the X,Y points. # poly_res = Ngl.Resources() poly_res.gsMarkerIndex = 16 poly_res.gsMarkerSizeF = 0.015 Ngl.add_polymarker(wks, contour, x, y, poly_res) Ngl.draw(contour) Ngl.frame(wks) # # Now turn on RasterFill for the contours and compare. # resources.tiMainString = "Interpolation to a 2D grid (RasterFill)" resources.cnFillMode = 'RasterFill' contour = Ngl.contour(wks, zt, resources) # # Draw polymarkers again. # Ngl.add_polymarker(wks, contour, x, y, poly_res)
