Python 使用条件着色添加水平线
我使用Python 使用条件着色添加水平线,python,matplotlib,Python,Matplotlib,我使用matplotlib.pyplot制作了一个contourf绘图。现在我想要一条水平线（或者类似于ax.vspan的东西也可以），在y=0处使用条件着色。我会告诉你我有什么，我想得到什么。我想用一个数组，比如说landsurface，表示陆地、海洋或冰。此数组填充有1（陆地）、2（海洋）或3（冰），并具有len（locs）（因此x轴） # 1 when near min, 2 when near 0, 3 when near max z = np.where(y<-0.5, 1, n
matplotlib.pyplotcontourfax.vspany=0landsurface123len（locs）# 1 when near min, 2 when near 0, 3 when near max
z = np.where(y<-0.5, 1, np.where(y<+0.5, 2, 3))
col_d = {1:(0.4, 0.4, 1.0, 1), # blue, near min
2:(0.4, 1.0, 0.4, 1), # green, near zero
3:(1.0, 0.4, 0.4, 1)} # red, near max
# prepare the list of colors
colors = [col_d[n] for n in z]
# 1 when near min, 2 when near 0, 3 when near max
z = np.where(y<-0.5, 1, np.where(y<+0.5, 2, 3))
col_d = {1:(0.4, 0.4, 1.0, 1), # blue, near min
2:(0.4, 1.0, 0.4, 1), # green, near zero
3:(1.0, 0.4, 0.4, 1)} # red, near max
# prepare the list of colors
colors = [col_d[n] for n in z]
plt.figure（）
ax=plt.axs（）
clev=np.arange（0,50,5）
plt.contourf（locs、高度、表面高度、var、clev、extend='max'）
plt.xlabel（'位置'）
plt.ylabel（'地平面以上高度[m]”）
cbar=plt.colorbar（）
cbar.ax.set_ylabel（'o3混合比[ppb]”）
plt.show（）
# 1 when near min, 2 when near 0, 3 when near max
z = np.where(y<-0.5, 1, np.where(y<+0.5, 2, 3))
col_d = {1:(0.4, 0.4, 1.0, 1), # blue, near min
2:(0.4, 1.0, 0.4, 1), # green, near zero
3:(1.0, 0.4, 0.4, 1)} # red, near max
# prepare the list of colors
colors = [col_d[n] for n in z]
# 1 when near min, 2 when near 0, 3 when near max
z = np.where(y<-0.5, 1, np.where(y<+0.5, 2, 3))
col_d = {1:(0.4, 0.4, 1.0, 1), # blue, near min
2:(0.4, 1.0, 0.4, 1), # green, near zero
3:(1.0, 0.4, 0.4, 1)} # red, near max
# prepare the list of colors
colors = [col_d[n] for n in z]
# 1 when near min, 2 when near 0, 3 when near max
z = np.where(y<-0.5, 1, np.where(y<+0.5, 2, 3))
col_d = {1:(0.4, 0.4, 1.0, 1), # blue, near min
2:(0.4, 1.0, 0.4, 1), # green, near zero
3:(1.0, 0.4, 0.4, 1)} # red, near max
# prepare the list of colors
colors = [col_d[n] for n in z]
# 1 when near min, 2 when near 0, 3 when near max
z = np.where(y<-0.5, 1, np.where(y<+0.5, 2, 3))
col_d = {1:(0.4, 0.4, 1.0, 1), # blue, near min
2:(0.4, 1.0, 0.4, 1), # green, near zero
3:(1.0, 0.4, 0.4, 1)} # red, near max
# prepare the list of colors
colors = [col_d[n] for n in z]
非常感谢 我建议添加一个带有适当
范围的imshow（）
，例如：
# 1 when near min, 2 when near 0, 3 when near max
z = np.where(y<-0.5, 1, np.where(y<+0.5, 2, 3))
col_d = {1:(0.4, 0.4, 1.0, 1), # blue, near min
2:(0.4, 1.0, 0.4, 1), # green, near zero
3:(1.0, 0.4, 0.4, 1)} # red, near max
# prepare the list of colors
colors = [col_d[n] for n in z]
将numpy导入为np
将matplotlib.pyplot作为plt导入
将matplotlib.colorbar导入为colorbar
将matplotlib.colors导入为颜色
###生成一些数据
np.随机种子（196801）
净现值=50
x=np.随机.均匀（0，1，npts）
y=np.随机.均匀（0，1，npts）
十、 Y=np.meshgrid（X，Y）
z=x*np.exp（-x**2-Y**2）*100
###为每个地块创建三种不同颜色的彩色地图
landmass_cmap=colors.ListedColormap（[“b”、“r”、“g”]））
x_land=np.linspace（0,1，len（x））##这应该缩放到您的“位置”
##生成一些带有概率的假地块类型（0、1或2）
y_land=np.随机选择（3，len（x），p=[0.1,0.6,0.3]）
打印（y_land）
图=plt.图（）
ax=plt.axs（）
clev=np.arange（0,50,5）
##调整陆块的“高度”
x0，x1=0,1
y0，y1=0，0.05##y1是陆地的“高度”
##确保您在这里和您的.tourtf（）中通过了明智的zorder
im=ax.imshow（y_land.reformate（-1，len（x）），cmap=landmass_cmap，zorder=2，extent=（x0，x1，y0，y1））
轮廓曲线图（x，y，z，clev，extend='max'，zorder=1）
ax.set_xlim（0,1）
ax.set_ylim（0,1）
ax.plot（）
ax.set_xlabel（'位置'）
ax.set_ylabel（'地平面以上的高度[m]”）
cbar=plt.colorbar（）
cbar.ax.set_ylabel（'o3混合比[ppb]”）
##为列出的颜色贴图添加颜色栏
cax=图添加_轴（[0.2,0.95,0.5,0.02]）#x位置，y位置，x宽度，y高度
界限=[0,1,2,3]
范数=颜色。边界范数（边界，陆块\u cmap.N）
cb2=色条、色条（cax，cmap=landmass\u cmap，
norm=norm，
边界=边界，
滴答声=[0.5,1.5,2.5]，
间距‘’，
方向（水平）
cb2.ax.set_xticklabels（[‘海’、‘陆’、‘冰’]））
plt.show（）
收益率：
# 1 when near min, 2 when near 0, 3 when near max
z = np.where(y<-0.5, 1, np.where(y<+0.5, 2, 3))
col_d = {1:(0.4, 0.4, 1.0, 1), # blue, near min
2:(0.4, 1.0, 0.4, 1), # green, near zero
3:(1.0, 0.4, 0.4, 1)} # red, near max
# prepare the list of colors
colors = [col_d[n] for n in z]
简介
# 1 when near min, 2 when near 0, 3 when near max
z = np.where(y<-0.5, 1, np.where(y<+0.5, 2, 3))
col_d = {1:(0.4, 0.4, 1.0, 1), # blue, near min
2:(0.4, 1.0, 0.4, 1), # green, near zero
3:(1.0, 0.4, 0.4, 1)} # red, near max
# prepare the list of colors
colors = [col_d[n] for n in z]
我要用一个新的
# 1 when near min, 2 when near 0, 3 when near max
z = np.where(y<-0.5, 1, np.where(y<+0.5, 2, 3))
col_d = {1:(0.4, 0.4, 1.0, 1), # blue, near min
2:(0.4, 1.0, 0.4, 1), # green, near zero
3:(1.0, 0.4, 0.4, 1)} # red, near max
# prepare the list of colors
colors = [col_d[n] for n in z]
因为我没有您的原始数据，所以我使用简单的正弦曲线伪造了一些数据，并在基线上绘制了对应于曲线的小、中、高值的颜色代码
# 1 when near min, 2 when near 0, 3 when near max
z = np.where(y<-0.5, 1, np.where(y<+0.5, 2, 3))
col_d = {1:(0.4, 0.4, 1.0, 1), # blue, near min
2:(0.4, 1.0, 0.4, 1), # green, near zero
3:(1.0, 0.4, 0.4, 1)} # red, near max
# prepare the list of colors
colors = [col_d[n] for n in z]
代码
通常，我们需要显式导入LineCollection
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.collections import LineCollection
# 1 when near min, 2 when near 0, 3 when near max
z = np.where(y<-0.5, 1, np.where(y<+0.5, 2, 3))
col_d = {1:(0.4, 0.4, 1.0, 1), # blue, near min
2:(0.4, 1.0, 0.4, 1), # green, near zero
3:(1.0, 0.4, 0.4, 1)} # red, near max
# prepare the list of colors
colors = [col_d[n] for n in z]
只是画一条正弦曲线（xr
从曲线值（对应于曲面类型）到LineCollection
颜色的颜色编码，请注意LineCollection
要求将颜色指定为RGBA元组，但我看到过使用颜色字符串的示例，呸
# 1 when near min, 2 when near 0, 3 when near max
z = np.where(y<-0.5, 1, np.where(y<+0.5, 2, 3))
col_d = {1:(0.4, 0.4, 1.0, 1), # blue, near min
2:(0.4, 1.0, 0.4, 1), # green, near zero
3:(1.0, 0.4, 0.4, 1)} # red, near max
# prepare the list of colors
colors = [col_d[n] for n in z]
最后，我们把一切都放在画布上
# 1 when near min, 2 when near 0, 3 when near max
z = np.where(y<-0.5, 1, np.where(y<+0.5, 2, 3))
col_d = {1:(0.4, 0.4, 1.0, 1), # blue, near min
2:(0.4, 1.0, 0.4, 1), # green, near zero
3:(1.0, 0.4, 0.4, 1)} # red, near max
# prepare the list of colors
colors = [col_d[n] for n in z]
# plot the function and the line collection
fig, ax = plt.subplots()
ax.plot(x,y)
ax.add_collection(lc)
请看，这很有魅力，谢谢。有没有办法删除垂直的灰色/白色线条，使线条集合看起来连续？对于垂直线条，请尝试使用抗锯齿=1
（或者是抗锯齿=0
？）-否则，您可以尝试在每个段末端的x坐标上添加一个非常小的ε。免责声明，我没有测试这两个想法。@Bollehenk我检查过，它是抗锯齿=0
…我编辑了答案，我还使用zorder=3
强制在前景中绘制颜色编码线。