# Python等效于Matlab的Demcmap(提升/ – 适当的色彩映射)

cmap“terrain”看起来很棒但是颜色缩放不是基于零(即,如果比例为0-> 5000m,则0-> 1000m范围可能是蓝色阴影,你可以认为是海底-水平)

Matlab函数等效于：
`demcmap`

python底图包中可能实际上有一些内置功能,我不知道.

``````import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors

class FixPointNormalize(matplotlib.colors.Normalize):
"""
Inspired by https://stackoverflow.com/questions/20144529/shifted-colorbar-matplotlib
Subclassing Normalize to obtain a colormap with a fixpoint
somewhere in the middle of the colormap.

This may be useful for a `terrain` map, to set the "sea level"
to a color in the blue/turquise range.
"""
def __init__(self, vmin=None, vmax=None, sealevel=0, col_val = 0.21875, clip=False):
# sealevel is the fix point of the colormap (in data units)
self.sealevel = sealevel
# col_val is the color value in the range [0,1] that should represent the sealevel.
self.col_val = col_val
matplotlib.colors.Normalize.__init__(self, vmin, vmax, clip)

def __call__(self, value, clip=None):
x, y = [self.vmin, self.sealevel, self.vmax], [0, self.col_val, 1]

# Combine the lower and upper range of the terrain colormap with a gap in the middle
# to let the coastline appear more prominently.
# inspired by https://stackoverflow.com/questions/31051488/combining-two-matplotlib-colormaps
colors_undersea = plt.cm.terrain(np.linspace(0, 0.17, 56))
colors_land = plt.cm.terrain(np.linspace(0.25, 1, 200))
# combine them and build a new colormap
colors = np.vstack((colors_undersea, colors_land))
cut_terrain_map = matplotlib.colors.LinearSegmentedColormap.from_list('cut_terrain', colors)

# invent some data (height in meters relative to sea level)
data = np.linspace(-1000,2400,15**2).reshape((15,15))

# plot example data
fig, ax = plt.subplots(nrows = 2, ncols=3, figsize=(11,6) )
plt.subplots_adjust(left=0.08, right=0.95, bottom=0.05, top=0.92, hspace = 0.28, wspace = 0.15)

plt.figtext(.5, 0.95, "Using 'terrain' and FixedPointNormalize", ha="center", size=14)
norm = FixPointNormalize(sealevel=0, vmax=3400)
im = ax[0,0].imshow(data+1000, norm=norm, cmap=plt.cm.terrain)
fig.colorbar(im, ax=ax[0,0])

norm2 = FixPointNormalize(sealevel=0, vmax=3400)
im2 = ax[0,1].imshow(data, norm=norm2, cmap=plt.cm.terrain)
fig.colorbar(im2, ax=ax[0,1])

norm3 = FixPointNormalize(sealevel=0, vmax=0)
im3 = ax[0,2].imshow(data-2400.1, norm=norm3, cmap=plt.cm.terrain)
fig.colorbar(im3, ax=ax[0,2])

plt.figtext(.5, 0.46, "Using custom cut map and FixedPointNormalize (adding hard edge between land and sea)", ha="center", size=14)
norm4 = FixPointNormalize(sealevel=0, vmax=3400)
im4 = ax[1,0].imshow(data+1000, norm=norm4, cmap=cut_terrain_map)
fig.colorbar(im4, ax=ax[1,0])

norm5 = FixPointNormalize(sealevel=0, vmax=3400)
im5 = ax[1,1].imshow(data, norm=norm5, cmap=cut_terrain_map)
cbar = fig.colorbar(im5, ax=ax[1,1])

norm6 = FixPointNormalize(sealevel=0, vmax=0)
im6 = ax[1,2].imshow(data-2400.1, norm=norm6, cmap=cut_terrain_map)
fig.colorbar(im6, ax=ax[1,2])

for i, name in enumerate(["land only", "coast line", "sea only"]):
for j in range(2):
ax[j,i].text(0.96,0.96,name, ha="right", va="top", transform=ax[j,i].transAxes, color="w" )

plt.show()
``````

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