为Polar Scatter图数据点添加颜色 [英] Adding color to Polar Scatter plot data points
问题描述
我正在尝试使用Python绘制极坐标图，到目前为止，我已经取得了一些成功
I'm trying to make a polar plot with Python, of which I've been somewhat successful so far
极地散射图示例
我确实有一些我希望得到一些想法/建议的问题:
I did have a few questions for which I was hoping to get some ideas/suggestions:
- 是否可以将圆圈的颜色设置为特定值(例如，下面的示例代码中的"n")?如果可以，我可以设置特定的颜色范围吗?例如:0-30:红色； 31-40:黄色； 41-60:绿色
注意:请遵循中的示例在R 中的值上，我尝试了ax.scatter(ra,dec,c = ifelse(n < 30,’red','green'), pch = 19 )但没有成功=(
Note: following the examples from Plot with conditional colors based on values in R, I tried ax.scatter(ra,dec,c = ifelse(n < 30,’red','green'), pch = 19 ) without success =(
-
我怎样才能使数据圈大一点?
how can I make the data circles a little bit bigger?
我可以移动"90"标签，以便图形标题不重叠吗?我试过了:
x.set_rlabel_position(-22.5)，但出现错误("AttributeError:'PolarAxes'对象没有属性'set_rlabel_position'")
can I move the "90" label so that the graph title does not overlap? I tried:
x.set_rlabel_position(-22.5) but I get an error ("AttributeError: 'PolarAxes' object has no attribute 'set_rlabel_position'")
是否只能显示0,30和60高程标签?这些可以水平放置吗(例如:沿着0方位线)?
Is it possible to only show the 0,30, and 60 elevation labels? Can these be oriented horizontally (e.g.: along the 0 azimuth line)?
非常感谢！期待听到您的建议=)
Thank you so much! Looking forward to hearing your suggestions =)
import numpy
import matplotlib.pyplot as pyplot
dec = [10,20,30,40,50,60,70,80,90,80,70,60,50,40,30,20,10]
ra = [225,225,225,225,225,225,225,225,225,45,45,45,45,45,45,45,45]
n = [20,23,36,43,47,48,49,50,51,50,48,46,44,36,30,24,21]
ra = [x/180.0*3.141593 for x in ra]
fig = pyplot.figure()
ax = fig.add_axes([0.1,0.1,0.8,0.8],polar=True)
ax.set_ylim(0,90)
ax.set_yticks(numpy.arange(0,90,10))
ax.scatter(ra,dec,c ='r')
ax.set_title("Graph Title here", va='bottom')
pyplot.show()
推荐答案
1.为点着色
使用scatter的c自变量可以使点着色.因此，您可以为其提供n数组，并根据颜色图选择颜色.色彩图将由不同的颜色组成(红色31倍，黄色10倍，绿色20倍).
使用颜色图的优点是可以轻松使用颜色栏.
1. colorize points
Using the c argument of scatter allows to colorize the points. In thei caase you may supply the n array to it and let the color be chosen accoring to a colormap. The colormap would consist of the different colors (31 times red, 10 times yellow, 20 times green).
The advantage of using a colormap is that it allows to easily use a colorbar.
2.使用s参数可以使圆圈变大.
2. making circles bigger can be done using the s argument.
3.在标签和标题之间添加空间，最好使用set_title参数y将标题稍微向上移动.为了使标题不超出图的范围，我们可以使用subplots_adjust方法并将top缩小一些. (请注意，这仅在通过子图创建轴时有效.)
3. adding space between label and title This would best be done by moving the title a bit upwards, using the y argument to set_title. In order for the title not to go outside the figure, we can use the subplots_adjust method and make top a little smaller. (Note that this works only if the axes are created via subplots.)
4.仅显示某些滴答声可以通过设置来完成
勾号为ax.set_yticks([0,30,60])并沿ax.set_rlabel_position(0)完成ylabel沿水平线的定向. (请注意，set_rlabel_position从版本1.4开始可用，如果您使用的是较早的版本，请考虑更新).
4. Only show certain ticks can be accomplished by setting
the ticks as ax.set_yticks([0,30,60]) and orienting ylabels along a horizontal line is done by ax.set_rlabel_position(0). (Note that set_rlabel_position is available from version 1.4 on, if you have an earlier version, consider updating).
import numpy as np
import matplotlib.pyplot as plt # don't use pylab
import matplotlib.colors
import matplotlib.cm
dec = [10,20,30,40,50,60,70,80,90,80,70,60,50,40,30,20,10]
ra = [225,225,225,225,225,225,225,225,225,45,45,45,45,45,45,45,45]
n = [20,23,36,43,47,48,49,50,51,50,48,46,44,36,30,24,21]
ra = [x/180.0*np.pi for x in ra]
fig = plt.figure()
ax = fig.add_subplot(111,polar=True)
ax.set_ylim(0,90)
# 4. only show 0,30, 60 ticks
ax.set_yticks([0,30,60])
# 4. orient ylabels along horizontal line
ax.set_rlabel_position(0)
# 1. prepare cmap and norm
colors= ["red"] * 31 + ["gold"] * 10 + ["limegreen"] * 20
cmap=matplotlib.colors.ListedColormap(colors)
norm = matplotlib.colors.Normalize(vmin=0, vmax=60)
# 2. make circles bigger, using `s` argument
# 1. set different colors according to `n`
sc = ax.scatter(ra,dec,c =n, s=49, cmap=cmap, norm=norm, zorder=2)
# 1. make colorbar
cax = fig.add_axes([0.8,0.1,0.01,0.2])
fig.colorbar(sc, cax=cax, label="n", ticks=[0,30,40,60])
# 3. move title upwards, then adjust top spacing
ax.set_title("Graph Title here", va='bottom', y=1.1)
plt.subplots_adjust(top=0.8)
plt.show()
这篇关于为Polar Scatter图数据点添加颜色的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
