如何用不同颜色绘制一条线

Question

我有以下两个清单：

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，将每 10 个“latt”和“lont”记录分隔为一个句点，并赋予其独特的颜色。 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条线段。

如果您只想绘制少量（例如 10 条）线段，则只需执行以下操作：

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()

但是，如果您要绘制具有一百万条线段的内容，则绘制速度将非常慢。在这种情况下，请使用

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”颜色放大器中绘制随机颜色。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

Answer 2

复制自此示例：

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生成“句点”，然后使用@tcaswell提到的matplotlib scatter函数。使用 plot.hold 函数您可以绘制每个周期，颜色会自动增加。

Answer 4

抄袭@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

来完成此操作。

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而无需使用散点图。

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。就我的目的而言，这没什么大不了的。它可能对某人有帮助。

Answer 6

离开@AndreS的回答，

我做到了。

# Start with a default color (whatever your 'main' color will be)
plt.plot(data, color="blue")
# re-plot the line segments you want to be red
plt.plot(np.where(red==True, data, None), color="red")