matplotlib values under cursor [duplicate]

Answer 1

You simply need to re-assign ax.format_coord. See this example from the documentation.

(code lifted directly from example)

"""
Show how to modify the coordinate formatter to report the image "z"
value of the nearest pixel given x and y
"""
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm

X = 10*np.random.rand(5,3)

fig = plt.figure()
ax = fig.add_subplot(111)
ax.imshow(X, cmap=cm.jet, interpolation='nearest')

numrows, numcols = X.shape
def format_coord(x, y):
    col = int(x+0.5)
    row = int(y+0.5)
    if col>=0 and col<numcols and row>=0 and row<numrows:
        z = X[row,col]
        return 'x=%1.4f, y=%1.4f, z=%1.4f'%(x, y, z)
    else:
        return 'x=%1.4f, y=%1.4f'%(x, y)

ax.format_coord = format_coord
plt.show()

Answer 2

I needed something I could re-use, so I encapsulated the solution through a class:

#!/usr/bin/env python2
# -*- coding: utf-8 -*-

import numpy as np
class imshow_show_z:

    def __init__(self, ax, z, x, y):
        self.ax = ax
        self.x  = x
        self.y  = y
        self.z  = z
        self.dx = self.x[1] - self.x[0]
        self.dy = self.y[1] - self.y[0]
        self.numrows, self.numcols = self.z.shape
        self.ax.format_coord = self.format_coord
    def format_coord(self, x, y):
        col = int(x/self.dx+0.5)
        row = int(y/self.dy+0.5)
        #print "Nx, Nf = ", len(self.x), len(self.y), "    x, y =", x, y, "    dx, dy =", self.dx, self.dy, "    col, row =", col, row
        xyz_str = ''
        if ((col>=0) and (col<self.numcols) and (row>=0) and (row<self.numrows)):
            zij = self.z[row,col]
            #print "zij =", zij, '  |zij| =', abs(zij)
            if (np.iscomplex(zij)):
                amp = abs(zij)
                phs = np.angle(zij) / np.pi
                if (zij.imag >= 0.0):
                    signz = '+'
                else:
                    signz = '-'
                xyz_str = 'x=' + str('%.4g' % x) + ', y=' + str('%.4g' % y) + ',' \
                            + ' z=(' + str('%.4g' % zij.real) + signz + str('%.4g' % abs(zij.imag)) + 'j)' \
                            + '=' + str('%.4g' % amp) + r'*exp{' + str('%.4g' % phs) + u' π j})'
            else:
                xyz_str = 'x=' + str('%.4g' % x) + ', y=' + str('%.4g' % y) + ', z=' + str('%.4g' % zij)
        else:
            xyz_str = 'x=%1.4f, y=%1.4f'%(x, y)
        return xyz_str

def new_imshow(ax, x, y, z, *args, **kwargs):
    assert(len(x) == z.shape[1])
    assert(len(y) == z.shape[0])
    dx = x[1] - x[0]
    dy = y[1] - y[0]
    if (np.iscomplex(z).any()):
        zabs = abs(z)
    else:
        zabs = z
    # Use this to center pixel around (x,y) values
    extent = (x[0]-dx/2.0, x[-1]+dx/2.0, y[0]-dy/2.0, y[-1]+dy/2.0)
    # Use this to let (x,y) be the lower-left pixel location (upper-left when origin = 'lower' is not used)
    #extent = (x[0]-dx/2.0, x[-1]+dx/2.0, y[0]-dy/2.0, y[-1]+dy/2.0)
    im = ax.imshow(zabs, extent = extent, *args, **kwargs)
    imshow_show_z(ax, z, x, y)
    ax.set_xlim((x[0], x[-1]))
    ax.set_ylim((y[0], y[-1]))
    return im

Example usage:

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-5, 10, 100)
y = np.linspace(-2.0, 5, 51)
xx, yy = np.meshgrid(x, y)
Z = np.sin(xx**2 + yy**2) / (xx**2 + yy**2)

fig = plt.figure()
ax = fig.add_subplot(1,1,1)
im = new_imshow(ax, x, y, Z, aspect = 'auto', origin = 'lower', interpolation = 'nearest')
ax.set_xlabel('x')
ax.set_ylabel('y')

plt.show()

Features:

• Can show both floats and complex values. For complex, the real+imaginary parts and polar form are shown.
• Will set the extent for you, based on the x and y arrays. Note that the matplotlib example works only if you don't use the extent keyword.
• Pixels are centered around their (x,y) position instead of (x,y) being the lower (or upper) left location.