我有一个线图和2个hlines,全部使用不同的颜色,我填充主线与hline颜色交叉的区域。除此之外,我还想在这些区域使用相同的颜色作为主线。简而言之,目前的输出:
我目前使用的相关代码:
lower, upper = 20, 80
self.indicatorPlot.axhline(lower, color="red")
self.indicatorPlot.axhline(upper, color="green")
self.indicatorPlot.plot(self.chartTimes, self.indicatorData, color="blue")
self.indicatorPlot.fill_between(self.chartTimes, self.indicatorData, lower, where=(self.indicatorData <= lower), facecolor="red", interpolate=True)
self.indicatorPlot.fill_between(self.chartTimes, self.indicatorData, upper, where=(self.indicatorData >= upper), facecolor="green", interpolate=True)
答案 0 :(得分:4)
原则上,您可以将绘图分为三部分,upper
以上的值,lower
以下的值和中间的值。在这个意义上,这个问题已经被提出并回答,例如
如果您的点密度足够高,那么这些解决方案的效果会很好,这样线条最终会接近阈值线。
如果你有较大的差距,他们可能不太适合。因此,我将在这里给出一个解决方案,它会插入间隙,使得线条完全在阈值线处结束。
import numpy as np; np.random.seed(43)
import matplotlib.pyplot as plt
t = np.linspace(0,100,301)
x = np.cumsum(np.random.randn(len(t)))
lower,upper = 0,8
fig, ax=plt.subplots()
ax.axhline(lower, color="crimson")
ax.axhline(upper, color="limegreen")
def insertzeros(t, x, zero=0):
ta = []
positive = (x-zero) > 0
ti = np.where(np.bitwise_xor(positive[1:], positive[:-1]))[0]
for i in ti:
y_ = np.sort(x[i:i+2])
z_ = t[i:i+2][np.argsort(x[i:i+2])]
t_ = np.interp(zero, y_, z_)
ta.append( t_ )
tnew = np.append( t, np.array(ta) )
xnew = np.append( x, np.ones(len(ta))*zero )
xnew = xnew[tnew.argsort()]
tnew = np.sort(tnew)
return tnew, xnew
t1,x1 = insertzeros(t,x, zero=lower)
t1,x1 = insertzeros(t1,x1, zero=upper)
xm = np.copy(x1)
xm[(x1 < lower) | (x1 > upper)] = np.nan
ax.plot(t1,xm, color="C0")
xl = np.copy(x1)
xl[(x1 > lower)] = np.nan
ax.plot(t1,xl, color="crimson")
#
xu = np.copy(x1)
xu[(xu < upper)] = np.nan
ax.plot(t1,xu, color="limegreen")
ax.fill_between(t, x, lower, where=(x <= lower), facecolor="crimson", interpolate=True, alpha=0.5)
ax.fill_between(t, x, upper, where=(x >= upper), facecolor="limegreen", interpolate=True, alpha=0.5)
plt.show()