python：如何绘制不同颜色的一条线
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] 现在我想把它画成一条线，把每一个“格”和“不”的logging分开一段时间，给它一个独特的颜色。 我该怎么办？
有几种不同的方法来做到这一点。 “最好”的方法将主要取决于你想要绘制多less条线段。
如果你只是要绘制一些（如10）线段，那么就做一些事情：
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()
如果你正在绘制一百万条线段，那么绘制速度将会非常缓慢。 在这种情况下，使用LineCollection 。 例如
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”coloramp绘制随机颜色。 看看这里的色彩地图（gist_ncar大概是下面的2/3）： http ://matplotlib.org/examples/color/colormaps_reference.html
从这个例子复制：
import numpy as np import matplotlib.pyplot as plt from matplotlib.collections import LineCollection from matplotlib.colors import ListedColormap, BoundaryNorm x = np.linspace(0, 3 * np.pi, 500) y = np.sin(x) z = np.cos(0.5 * (x[:-1] + x[1:])) # first derivative # Create a colormap for red, green and blue and a norm to color # f' < -0.5 red, f' > 0.5 blue, and the rest green cmap = ListedColormap(['r', 'g', 'b']) norm = BoundaryNorm([-1, -0.5, 0.5, 1], cmap.N) # Create a set of line segments so that we can color them individually # This creates the points as a N x 1 x 2 array so that we can stack points # together easily to get the segments. The segments array for line collection # needs to be numlines x points per line x 2 (x and y) points = np.array([x, y]).T.reshape(-1, 1, 2) segments = np.concatenate([points[:-1], points[1:]], axis=1) # Create the line collection object, setting the colormapping parameters. # Have to set the actual values used for colormapping separately. lc = LineCollection(segments, cmap=cmap, norm=norm) lc.set_array(z) lc.set_linewidth(3) fig1 = plt.figure() plt.gca().add_collection(lc) plt.xlim(x.min(), x.max()) plt.ylim(-1.1, 1.1) plt.show()
在@JoeKington的色彩select上，
import numpy as np import matplotlib.pyplot as plt def uniqueish_color(n): """There're better ways to generate unique colors, but this isn't awful.""" return plt.cm.gist_ncar(np.random.random(n)) plt.scatter(latt, lont, c=uniqueish_color(len(latt)))
你可以用scatter来做到这一点。
看到这里的答案生成“句点”，然后使用matplotlib分散函数作为@tcaswell提到。 使用plot.hold函数可以绘制每个周期，颜色将自动递增。
