我有以下两个列表：
latt=[42.0,41.978567980875397,41.96622693388357,41.963791391892457,...,41.972407378075879]
lont=[-66.706920989908909,-66.703116557977069,-66.707351643324543,...-66.718218142021925]
现在我想把它作为一条线来绘制，将这些“latt”和“lont”记录中的每10个分开作为一个周期，并赋予其独特的颜色。 我应该怎么做？
有几种不同的方法可以实现这一点。 "最佳"方法主要取决于您想绘制多少条线段。
如果您只需要绘制几条（例如10条）线段，则可以执行以下操作：
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()
如果你要绘制的图形有一百万条线段，那么使用该方法会非常缓慢。在这种情况下，可以使用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”颜色图中随机选择颜色。在这里查看调色板（gist_ncar大约在页面的2/3处）：http://matplotlib.org/examples/color/colormaps_reference.html
coll.set_array(np.random.random(xy.shape[0]))时指定了什么？
文档对此非常不清楚，可以参考此链接：https://matplotlib.org/api/cm_api.html#matplotlib.cm.ScalarMappable.set_array - J.A.Cado从这个示例复制：
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()
plt.plot(np.where(df["label"]==1, df["myvalue"], None), color="red", label="1")
plt.plot(np.where(df["label"]==0, df["myvalue"], None), color="blue", label="0")
plt.legend()
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)))
scatter完成这个任务。
scatterhttp://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.scatter - tacaswell