def cn_sym_min_max(x, res, ncontours=15, outside=True, aboutZero=True):
'''Adjust the contour level configuration of a plot resource to give nice
contour levels symmetric about zero. The contour levels are computed with
NGL.nice_cntr_levels().
cn_sym_min_max(x, res, ncontours=15, outside=True, aboutZero=True)
x : data used in the contour plot.
res : Resource object that will be updated accordingly.
outside : Whether the maxima is outside or inside the contour range. Will
be passed to NGL.nice_cntr_levels().
aboutZero : Whether the contour levels will be centered about Zero. Will be
passed to NGL.nice_cntr_levels().
'''
min_x = np.min(x)
max_x = np.max(x)
if min_x == max_x:
min_x, max_x = -1., 1.
min_out, max_out, step_size = ngl.nice_cntr_levels(min_x, max_x,
outside=outside,
max_steps=ncontours,
aboutZero=aboutZero)
newres = {"cnLevelSelectionMode": "ManualLevels",
"cnMinLevelValF": min_out,
"cnMaxLevelValF": max_out,
"cnLevelSpacingF": (max_out - min_out) / step_size}
res.__dict__.update(newres)
data = Ngl.generate_2d_array([nlat,nlon], 10, 19, 0., 100.) lat = Ngl.fspan(minlat,maxlat,nlat) lon = Ngl.fspan(minlon,maxlon,nlon) return data,lat,lon #---------------------------------------------------------------------- # Main code #---------------------------------------------------------------------- #---Generate dummy data data,lat1d,lon1d = gen_dummy_data() #---Get nice contour levels cmin,cmax,cint = Ngl.nice_cntr_levels(numpy.min(data),numpy.max(data)) #---Start the graphics wks_type = "png" wks = Ngl.open_wks (wks_type,"shapefile3") #---Define some graphical resources res = Ngl.Resources() res.nglFrame = False res.nglDraw = False #---Scalar field resources res.sfXArray = lon1d res.sfYArray = lat1d
# Add some named colors. This is no longer needed in PyNGL 1.5.0
#forest_green = numpy.array([ 34, 139, 34])/255.
#navy_blue = numpy.array([ 0, 0, 128])/255.
#brown = numpy.array([165, 42, 42])/255.
#ig = Ngl.new_color(wks,forest_green[0],forest_green[1],forest_green[2])
#ib = Ngl.new_color(wks,navy_blue[0], navy_blue[1], navy_blue[2])
#ir = Ngl.new_color(wks,brown[0], brown[1], brown[2])
# Generate some dummy data.
cmin = -19.23
cmax = 16.81
data = Ngl.generate_2d_array([100, 100], 10, 10, cmin, cmax)
nice_min, nice_max, nice_spc = Ngl.nice_cntr_levels(cmin, cmax, cint=3)
# Read in color map so we can subset it
cmap = Ngl.read_colormap_file("nrl_sirkes")
# Set up resources for a contour plot.
cnres = Ngl.Resources()
cnres.nglMaximize = True # Maximize plot in frame
cnres.nglDraw = False # Don't draw plot
cnres.nglFrame = False # Don't advance the frame
cnres.cnFillOn = True # Turn on contour fill
cnres.cnFillPalette = cmap[:-3, :]
import numpy, Ngl, sys
print "Testing Ngl.nice_cntr_levels code....."
print "--------------------------------------------------"
print "Testing CINT = 0.0, outside = False / returnLevels = False"
print "Ngl.nice_cntr_levels(-23.1, 70.7, outside=False)"
answer = (-20.0, 70.0, 9.0)
answer_is = Ngl.nice_cntr_levels(-23.1, 70.7, outside=False)
if (answer_is == answer):
print "...SUCCESSFUL..."
else:
print "...UNSUCCESSFUL..."
print "answer_is", answer_is
print "answer", answer
print "--------------------------------------------------"
print "Testing CINT = 0.0, outside = True / returnLevels = False"
print "Ngl.nice_cntr_levels(-23.1, 70.7, outside=True)"
answer = (-30.0, 80.0, 11.0)
answer_is = Ngl.nice_cntr_levels(-23.1, 70.7, outside=True)
if (answer_is == answer):
print "...SUCCESSFUL..."
else:
print "...UNSUCCESSFUL..."
print "answer_is", answer_is
print "answer", answer
print "--------------------------------------------------"
print "Testing cint = 0.0, outside = False / returnLevels = True"
print "Ngl.nice_cntr_levels(-23.1, 70.7, outside=False, returnLevels=True)"
answer1 = (-20.0, 70.0, 9.0)
