#!/usr/bin/env python
"""
Illustrate some of the more advanced things that one can do with
contour labels.

See also contour_demo.py.
"""
import matplotlib
import numpy as np
import matplotlib.cm as cm
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt

matplotlib.rcParams['xtick.direction'] = 'out'
matplotlib.rcParams['ytick.direction'] = 'out'

##################################################
# Define our surface
##################################################
delta = 0.025
x = np.arange(-3.0, 3.0, delta)
y = np.arange(-2.0, 2.0, delta)
X, Y = np.meshgrid(x, y)
Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
# difference of Gaussians
Z = 10.0 * (Z2 - Z1)

##################################################
# Make contour labels using creative float classes
# Follows suggestion of Manuel Metz
##################################################
plt.figure()

# Basic contour plot
CS = plt.contour(X, Y, Z)

# Define a class that forces representation of float to look a certain way
# This remove trailing zero so '1.0' becomes '1'
class nf(float):
     def __repr__(self):
         str = '%.1f' % (self.__float__(),)
         if str[-1]=='0':
             return '%.0f' % self.__float__()
         else:
             return '%.1f' % self.__float__()

# Recast levels to new class
CS.levels = [nf(val) for val in CS.levels ]

# Label levels with specially formatted floats
plt.clabel(CS, CS.levels, inline=True, fmt='%r %%', fontsize=10)

##################################################
# Label contours with arbitrary strings using a
# dictionary
##################################################
plt.figure()

# Basic contour plot
CS = plt.contour(X, Y, Z)

fmt = {}
strs = [ 'first', 'second', 'third', 'fourth', 'fifth', 'sixth', 'seventh' ]
for l,s in zip( CS.levels, strs ):
    fmt[l] = s

# Label every other level using strings
plt.clabel(CS,CS.levels[::2],inline=True,fmt=fmt,fontsize=10)

##################################################
# Show the hole thing
##################################################
plt.show()
