python：如何用不同的颜色绘制一条线

Question

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，将每个10个'latt'和'lont'记录分开作为一个句点并给它一个独特的颜色。 我该怎么办？

Answer 1

有几种不同的方法可以做到这一点。 “最佳”方法主要取决于您想要绘制多少个线段。

如果您要绘制少数（例如10个）线段，那么只需执行以下操作：

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()

如果您正在绘制具有一百万个线段的内容，那么绘制起来会非常缓慢。在这种情况下，请使用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”coloramp中绘制随机颜色。看看这里的色彩图（gist_ncar大概是下降的2/3）：http://matplotlib.org/examples/color/colormaps_reference.html

Answer 2

从this example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()

Answer 3

请参阅答案here以生成“句点”，然后使用matplotlib scatter函数作为@tcaswell提及。使用plot.hold功能可以绘制每个周期，颜色会自动增加。

Answer 4

剔除@JoeKington的颜色选择，

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)))

您可以使用scatter执行此操作。

Answer 5

我一直在寻找一个简短的解决方案，如何使用 pyplots 线图来显示由标签特征着色的时间序列由于数据点的数量，不使用散点。

我想出了以下解决方法：

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()

缺点是您正在创建两个不同的线图，因此不会显示不同类之间的连接。就我而言，这没什么大不了的。它可能会帮助某人。