Python：使用Matplotlib动态绘制多个行列表的列表

Question

Looking to clean up some code I have that's currently very messy. The goal is to plot many lines on a single plot, but the data can be structured differently.

The data can be arranged in a few different ways..

lats[set][point]
lons[set][point]

or

lat2[collection][set][point]
lon2[collection][set][point]

or even just a regular list of xs, and ys,

Where I would plug the respective 'set' into plt.plot(x,y) as it is a list of xs or ys. I want to be able to have the as many lists deep as I need, depending on the data that I'm plotting. Currently I have a few complex checks that sort based on the type, the base of the code is below.

def plotter(xs,ys):
    for x,y in zip(xs,ys):
        if type(x[0]) in (list, tuple):
            plotter(x,y)
        else:
            plt.plot(x,y)

What starts getting complex is trying to incorporate styles for different depths of lists.

I've been trying to use the matplotlib.collections but I haven't quite figured out how to use it correctly. Any help would be appreciated

Answer 1

One solution is to generate all possible combinations of indices for the data arrays that contain the actual data. Below is some example code, which might seem convoluted but is mostly generating and plotting the data.

There are 3 data sets (as you suggested), that have the forms:

lat1 -> set of points

lat2 -> collection of sets of points

lat3 -> points

Here is the code:

import matplotlib.pyplot as plt
import numpy as np
import itertools

# First data type
lat1 = np.array([np.linspace(0,180,100) for i in range(5)])
lon1 = np.array([10+5*np.random.random(100) for i in range(5)])
# lat1.shape = (5,100)
# [set][point]


# Second data type
lat2 = np.array([np.linspace(0,180,100) for i in range(5*3)]).reshape((3,5,100))
lon2 = np.array([30+10*np.random.random(100) for i in range(5*3)]).reshape((3,5,100))
# lat2.shape = (3,5,100)
# [collection][set][point]


# Third data type
lat3 = np.linspace(0,180,100)
lon3 = 50+5*np.random.random(100)
# lat3.shape = (100,)
# [point]


def plotter(xs,ys,ax,**kwargs):
    # Get number of dimensions
    ndim = xs.ndim

    # Iterate over each dimension, generating all indices
    if ndim>1:
        indices = [np.arange(0,i,1) for i in xs.shape[:-1]]
        comb = list(itertools.product(*indices))
    else:
        # This is to deal with one dimensional data (i.e. just a list)
        comb = [slice(0, xs.shape[0])]

    for c in comb:
        xx = xs[c]
        yy = ys[c]
        ax.plot(xx, yy, **kwargs)

    return ax

fig = plt.figure()
ax = fig.add_subplot(111)
plotter(lat1, lon1, ax, c='r', label='Type 1')
plotter(lat2, lon2, ax, c='b', label='Type 2')
plotter(lat3, lon3, ax, c='g', label='Type 3')

box = ax.get_position()
ax.set_position([box.x0, box.y0, box.width * 0.8, box.height])
ax.legend(fontsize=8,bbox_to_anchor=(1,1))

ax.set_ylim(0,60)
ax.set_xlim(0,180)

fig.show()

Which gives the following figure: