python:如何用不同的颜色绘制一条线 [英] python: how to plot one line in different colors

问题描述

我有两个列表如下:

latt=[42.0,41.978567980875397,41.96622693388357,41.963791391892457,...,41.972407378075879]
lont=[-66.706920989908909,-66.703116557977069,-66.707351643324543,...-66.718218142021925]

现在我想将其绘制为一条线，将这些latt"和lont"记录中的每 10 个分隔为一个句点，并为其赋予独特的颜色.我该怎么办?

now I want to plot this as a line, separate each 10 of those 'latt' and 'lont' records as a period and give it a unique color. what should I do?

推荐答案

有几种不同的方法可以做到这一点.最佳"方法主要取决于您要绘制的线段数量.

There are several different ways to do this. The "best" approach will depend mostly on how many line segments you want to plot.

如果您只想绘制少量(例如 10 个)线段，那么只需执行以下操作:

If you're just going to be plotting a handful (e.g. 10) line segments, then just do something like:

import numpy as np
import matplotlib.pyplot as plt

def uniqueish_color():
    """There're better ways to generate unique colors, but this isn't awful."""
    return plt.cm.gist_ncar(np.random.random())

xy = (np.random.random((10, 2)) - 0.5).cumsum(axis=0)

fig, ax = plt.subplots()
for start, stop in zip(xy[:-1], xy[1:]):
    x, y = zip(start, stop)
    ax.plot(x, y, color=uniqueish_color())
plt.show()

但是，如果您要绘制具有一百万条线段的内容，绘制起来会非常缓慢.在这种情况下，请使用 LineCollection.例如

If you're plotting something with a million line segments, though, this will be terribly slow to draw. In that case, use a LineCollection. E.g.

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection

xy = (np.random.random((1000, 2)) - 0.5).cumsum(axis=0)

# Reshape things so that we have a sequence of:
# [[(x0,y0),(x1,y1)],[(x0,y0),(x1,y1)],...]
xy = xy.reshape(-1, 1, 2)
segments = np.hstack([xy[:-1], xy[1:]])

fig, ax = plt.subplots()
coll = LineCollection(segments, cmap=plt.cm.gist_ncar)
coll.set_array(np.random.random(xy.shape[0]))

ax.add_collection(coll)
ax.autoscale_view()

plt.show()

对于这两种情况，我们只是从gist_ncar"颜色放大器中随机绘制颜色.看看这里的颜色图(gist_ncar 大约是向下的 2/3):http://matplotlib.org/examples/color/colormaps_reference.html

For both of these cases, we're just drawing random colors from the "gist_ncar" coloramp. Have a look at the colormaps here (gist_ncar is about 2/3 of the way down): http://matplotlib.org/examples/color/colormaps_reference.html

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