Hello,
I want to plot two sets of masked data on a single plot and I can not
get exactly the kind of image I want to. I have tried pcolormesh and
contourf and both have problems. With contourf the inner data does not
look smooth and sometimes has a row of missing data around it, with
pcolormesh, on the other hand, I can not control the levels in the way I
want to.
So, as is in the documentation, contourf may have problems with masked
data, so I can skip that solution. But how do I achieve controlled color
levels as I can do with contourf, but using pcolormesh? Attached code
illustrates the images I get with two methods.
Best regards,
Andres
'''
Demonstrate use of a log color scale in contourf
'''
from matplotlib import pyplot as P
import numpy as np
from numpy import ma
from matplotlib import colors, ticker
from matplotlib.mlab import bivariate_normal
from matplotlib.ticker import LogLocator, LogFormatter
N = 100
x = np.linspace(-3.0, 3.0, N)
y = np.linspace(-2.0, 2.0, N)
X, Y = np.meshgrid(x, y)
# A low hump with a spike coming out of the top right.
# Needs to have z/colour axis on a log scale so we see both hump and spike.
# linear scale only shows the spike.
z = (bivariate_normal(X, Y, 0.1, 0.2, 1.0, 1.0)
+ 0.1 * bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0))
# Put in some negative values (lower left corner) to cause trouble with logs:
z[:5, :5] = -1
# The following is not strictly essential, but it will eliminate
# a warning. Comment it out to see the warning.
z = ma.masked_where(z<= 0, z)
# Automatic selection of levels works; setting the
# log locator tells contourf to use a log scale:
#cs = P.contourf(X, Y, z, locator=ticker.LogLocator())
# Alternatively, you can manually set the levels
# and the norm:
lev_exp = np.arange(np.floor(np.log10(z.min())-1),
np.ceil(np.log10(z.max())+1))
#levs = np.power(10, lev_exp)
levstr=[]
levs=[0.00001,0.00005,0.0001,0.0005,0.001,0.01,0.1,1,10]
for i in levs:
levstr.append(str('%1.5f' % i))
#print levs
zmask1=ma.masked_where(z.data<2,z)
zmask2=ma.masked_where(z.data>=2,z)
### To include all values of levels, not just the logarithms
l_f = LogFormatter(2,labelOnlyBase=False)
### USE pcolormesh
fig=P.figure()
P.title('w pcolormesh')
cs = P.pcolormesh(zmask1, levs=levs,cmap=P.cm.Blues, norm=colors.LogNorm())
P.colorbar(format=l_f)
cs = P.pcolormesh(zmask2, levs=levs,cmap=P.cm.Greens, norm=colors.LogNorm())
P.colorbar(format=l_f)
### USE contourf
fig=P.figure()
P.title('w contourf')
cs = P.contourf(zmask2,levs,cmap=P.cm.Greens, norm=colors.LogNorm())
P.colorbar(format=l_f)
cs = P.contourf(zmask1,levs, cmap=P.cm.Blues, norm=colors.LogNorm())
P.colorbar(format=l_f)
#cbar.ax.set_yticklabels(levstr)
P.show()
#P.savefig('test')
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