pcolormesh_levels (1)

Example Python program pcolormesh_levels (1).py

Modules

import matplotlib.pyplot as plt
from matplotlib.colors import BoundaryNorm
from matplotlib.ticker import MaxNLocator
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import BoundaryNorm
from matplotlib.ticker import MaxNLocator
import numpy as np

Code

Python example

import matplotlib.pyplot as plt
from matplotlib.colors import BoundaryNorm
from matplotlib.ticker import MaxNLocator
import numpy as np
plt.rcParams['savefig.dpi']=100

# make these smaller to increase the resolution
dx, dy = 0.05, 0.05
y, x = np.mgrid[slice(1, 5 + dy, dy),
                slice(1, 5 + dx, dx)]
z = np.cos(x)**10 + np.sin(10 + y*x) * np.sin(x)
z = z[:-1, :-1]

levels = MaxNLocator(nbins=15).tick_values(z.min(), z.max())

# pick the desired colormap, sensible levels, and define a normalization
# instance which takes data values and translates those into levels.
cmap = plt.get_cmap('PuOr')
norm = BoundaryNorm(levels, ncolors=cmap.N, clip=True)

fig, (ax0, ax1) = plt.subplots(nrows=2,figsize=(5,7))

im = ax0.pcolormesh(x, y, z, cmap=cmap, norm=norm)
fig.colorbar(im, ax=ax0)
ax0.set_title('pcolormesh with levels')

# contours are *point* based plots, so convert our bound into point centers
cf = ax1.contourf(x[:-1, :-1] + dx/2.,
                  y[:-1, :-1] + dy/2., z, levels=levels,
                  cmap=cmap)
fig.colorbar(cf, ax=ax1)
ax1.set_title('contourf with levels')
fig.tight_layout()
#plt.savefig("pcolormesh_vs_contourf.png",bbox_inches = 'tight', pad_inches = 0)
plt.show()



#random z data 
import matplotlib.pyplot as plt
from matplotlib.colors import BoundaryNorm
from matplotlib.ticker import MaxNLocator
import numpy as np


# make these smaller to increase the resolution
dx, dy = 0.05, 0.05

y, x = np.mgrid[slice(1, 5 + dy, dy),
                slice(1, 5 + dx, dx)]
z = np.random.rand(x.shape[0],x.shape[1])
z = z[:-1, :-1]
levels = MaxNLocator(nbins=10).tick_values(z.min(), z.max())

cmap = plt.get_cmap('PuOr')
norm = BoundaryNorm(levels, ncolors=cmap.N, clip=True)

fig, (ax0, ax1) = plt.subplots(nrows=2,figsize=(5,7))

im = ax0.pcolormesh(x, y, z, cmap=cmap, norm=norm)
fig.colorbar(im, ax=ax0)
ax0.set_title('pcolormesh with levels')

cf = ax1.contourf(x[:-1, :-1] + dx/2.,
                  y[:-1, :-1] + dy/2., z, levels=levels,
                  cmap=cmap)
fig.colorbar(cf, ax=ax1)
ax1.set_title('contourf with levels')
fig.tight_layout()
#plt.savefig("pcolormesh_vs_contourf_ransu.png",bbox_inches = 'tight', pad_inches = 0)
plt.show()

Useful Links

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