我正在使用matplotlib.imshow
来获取2D数组的交互式显示。光标下的x / y坐标显示在窗口的左下角。是否也可以在光标下获取数组的值?
答案 0 :(得分:19)
您只需重新分配ax.format_coord
即可。请参阅文档中的this example。
(代码直接取自示例)
"""
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()
答案 1 :(得分:6)
我需要一些可以重复使用的东西,所以我通过一个类封装了解决方案:
#!/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
使用示例:
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()
特点: