本文介绍了给定r,theta和z值的Python极坐标直方图的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我有一个数据帧,该数据帧由特定磁强计站随时间的测量结果组成,其列对应于:
- 它的纬度(我认为是半径)
- 它的方位角
- 在特定时间测量的数量
我想知道一种将这个数据框绘制为测量变量的极坐标直方图的方法:即像这样:
我查看了 physt
中的特殊直方图,但这允许我只输入 x,y 值,我对此感到非常困惑.
有人可以帮忙吗?
解决方案
使用
I have a dataframe consisting of measurements from a particular magnetometer station over time, with columns corresponding to:
- its latitude (which I think of as a radius)
- its azimuthal angle
- a measured quantity at this specific time
I was wondering of a way to plot this dataframe as a polar histogram for the measured variable: ie something like this:
I have looked at the special histogram in physt
but this allows me to only put in x,y values and I'm quite confused by it all.
Could anybody help?
解决方案
Calculating a histogram is easily done with numpy.histogram2d
. Plotting the resulting 2D array can be done with matplotlib's pcolormesh
.
import numpy as np; np.random.seed(42)
import matplotlib.pyplot as plt
# two input arrays
azimut = np.random.rand(3000)*2*np.pi
radius = np.random.rayleigh(29, size=3000)
# define binning
rbins = np.linspace(0,radius.max(), 30)
abins = np.linspace(0,2*np.pi, 60)
#calculate histogram
hist, _, _ = np.histogram2d(azimut, radius, bins=(abins, rbins))
A, R = np.meshgrid(abins, rbins)
# plot
fig, ax = plt.subplots(subplot_kw=dict(projection="polar"))
pc = ax.pcolormesh(A, R, hist.T, cmap="magma_r")
fig.colorbar(pc)
plt.show()
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