[英]Custom Colorbar-like plot with matplotlib
我正在尋找一個像彩圖一樣的顏色條,如下所示:
但具有可控制的顏色,例如,我具有以下x和y數組:
x = [0,1,2,4,7,8]
y = [1,2,1,3,4,5]
然后,我將擁有一個如上圖所示的顏色條,但是當y = 1時,它將顯示為紅色,y = 2:綠色,y = 3:藍色,y = 4:黑色,等等。
這是我從matplotlib的圖庫中修改的python代碼:
from matplotlib import pyplot
import matplotlib as mpl
fig = pyplot.figure(figsize=(8,1))
ax2 = fig.add_axes([0.05, 0.25, 0.9, 0.5])
cmap = mpl.cm.Accent
norm = mpl.colors.Normalize(vmin=5, vmax=10)
bounds = [1, 2, 4, 7, 8]
norm = mpl.colors.BoundaryNorm(bounds, cmap.N)
cb2 = mpl.colorbar.ColorbarBase(ax2, cmap=cmap,
norm=norm,
boundaries=[0]+bounds+[13],
ticks=bounds, # optional
spacing='proportional',
orientation='horizontal')
修改您的代碼后,我設法獲得了與您描述的類似的東西。 在這種情況下,顏色列表是使用ListedColormap
生成的,我為y = 5添加了黃色。 重要的是要注意,在計算BoundaryNorm時,我使用的間隔包含了您為y描述的值。
from matplotlib import pyplot,colors
import matplotlib as mpl
fig = pyplot.figure(figsize=(8,1))
ax2 = fig.add_axes([0.05, 0.25, 0.9, 0.5])
cmap = colors.ListedColormap(['r', 'g', 'b', 'k','y'])
bounds = [0, 1, 2, 4, 7, 8, 13]
yVals = [ 1, 2, 1, 3, 4, 5]
cBounds = [i+0.5 for i in range(6)]
norm = mpl.colors.BoundaryNorm(cBounds, cmap.N)
cb2 = mpl.colorbar.ColorbarBase(ax2, cmap=cmap,
norm=norm,
values=yVals,
boundaries=bounds,
ticks=bounds[1:-1], # optional
spacing='proportional',
orientation='horizontal')
-編輯1月14日(MRCL)-
另外,您可以使用pcolormesh
繪制顏色圖,並使用顏色條作為圖例,例如下面的示例。
from pylab import *
from matplotlib import pyplot,colors
import matplotlib as mpl
fig = pyplot.figure(figsize=(8,1.5))
ax1 = fig.add_axes([0.05, 0.25, 0.82, 0.5])
cmap = colors.ListedColormap(['r', 'g', 'b', 'k','y'])
xBounds = array([0, 1, 2, 4, 7, 8, 13])
yBounds = array([0, 1])
Vals = array([[ 1, 2, 1, 3, 4, 5]])
cBounds = [i+0.5 for i in arange(amax(Vals)+1)]
norm = mpl.colors.BoundaryNorm(cBounds, cmap.N)
c = ax1.pcolormesh(xBounds,yBounds,Vals,cmap=cmap,norm=norm)
ax1.set_xticks(xBounds[1:-1])
ax1.set_yticks([])
ax1.set_xlim(xBounds[0],xBounds[-1])
ax1.set_ylim(yBounds[0],yBounds[-1])
ax2 = fig.add_axes([0.9, 0.25, 0.05, 0.5])
colorbar(c,cax=ax2,ticks=arange(amax(Vals))+1)
希望能幫助到你。
干杯
好吧,我在嘗試其他方式:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cmx
import matplotlib.colors as colors
close('all')
def ColorPlot(x,y):
figure()
jet = plt.get_cmap('jet')
cNorm = colors.Normalize(vmin=min(y), vmax=max(y))
scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet)
if len(x) == len(y):
x.insert(0,0)
for kk in range(len(x)-1):
colorVal = scalarMap.to_rgba(y[kk])
plt.axvspan(x[kk], x[kk+1], facecolor=colorVal,
alpha=0.5,label=colorVal)
plt.yticks([])
plt.xticks(x)
xlim([x[0],x[-1]])
plt.show()
x = [1,3,5,6,10,12]
y = [1,3,4,1,4,3]
ColorPlot(x,y)
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