复杂信息显示：Image 图片和3D 数据

使用Matplotlib时我们常常会遇到除函数图像信息以外的复杂信息显示的问题，本文以Image 和 3D 数据为例展示复杂信息的显示问题

1. 数据准备

import matplotlib.pyplot as plt
import numpy as np

# image data
a = np.array([0.313660827978, 0.365348418405, 0.423733120134,
              0.365348418405, 0.439599930621, 0.525083754405,
              0.423733120134, 0.525083754405, 0.651536351379]).reshape(3,3)

"""
for the value of "interpolation", check this:
http://matplotlib.org/examples/images_contours_and_fields/interpolation_methods.html
for the value of "origin"= ['upper', 'lower'], check this:
http://matplotlib.org/examples/pylab_examples/image_origin.html
"""

2. 显示 Image 图片

plt.imshow(a, interpolation='nearest', cmap='bone', origin='lower')
plt.colorbar(shrink=.92)

注：
1.plt.imshow(data, interpolation, cmap, origin)：图片显示函数
2.参数解释：

1.data：表示输入数据的来源
2.interpolation：默认为none ，表示图片插值方式(不太清楚)
3.camp：表示颜色地图，即图片的颜色对应方式，可自定义
4.origin：表示图片的显示方向

3. 坐标轴刻度显示

plt.xticks(())
plt.yticks(())
plt.show()

4. 3D 数据显示

4.1 数据准备

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

fig = plt.figure()
ax = Axes3D(fig)
# X, Y value
X = np.arange(-4, 4, 0.25)
Y = np.arange(-4, 4, 0.25)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X ** 2 + Y ** 2)
# height value
Z = np.sin(R)

4.2 显示3D数据

ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=plt.get_cmap('rainbow'))
"""
============= ================================================
        Argument      Description
        ============= ================================================
        *X*, *Y*, *Z* Data values as 2D arrays
        *rstride*     Array row stride (step size), defaults to 10
        *cstride*     Array column stride (step size), defaults to 10
        *color*       Color of the surface patches
        *cmap*        A colormap for the surface patches.
        *facecolors*  Face colors for the individual patches
        *norm*        An instance of Normalize to map values to colors
        *vmin*        Minimum value to map
        *vmax*        Maximum value to map
        *shade*       Whether to shade the facecolors
        ============= ================================================
"""

# I think this is different from plt12_contours
ax.contourf(X, Y, Z, zdir='z', offset=-2, cmap=plt.get_cmap('rainbow'))
"""
==========  ================================================
        Argument    Description
        ==========  ================================================
        *X*, *Y*,   Data values as numpy.arrays
        *Z*
        *zdir*      The direction to use: x, y or z (default)
        *offset*    If specified plot a projection of the filled contour
                    on this position in plane normal to zdir
        ==========  ================================================
"""

ax.set_zlim(-2, 2)

plt.show()