matplotlib:如何根据一些变量改变数据点的颜色

I have 2 variables (x,y) that change with time (t). I want to plot x vs. t and color the ticks based on the value of y. e.g. for highest values of y the tick color is dark green, for lowest value is dark red, and for intermediate values the color will be scaled in between green and red.

我有两个变量(x,y)随时间变化(t)我想把x和t和颜色基于y的值例如蜱蜱虫颜色是深绿色的y值最高,最小值是深红色,中间值的颜色绿色和红色之间将缩放。

Can this be done with matplotlib in python?

在python中使用matplotlib可以做到这一点吗?

2 个解决方案

#1

This is what matplotlib.pyplot.scatter is for.

这就是matplotlib.pyplot。散射。

As a quick example:

作为一个快速的例子:

import matplotlib.pyplot as plt
import numpy as np

# Generate data...
t = np.linspace(0, 2 * np.pi, 20)
x = np.sin(t)
y = np.cos(t)

plt.scatter(t,x,c=y)
plt.show()

#2

If you want to plot lines instead of points, see this example, modified here to plot good/bad points representing a function as a black/red as appropriate:

如果你想要绘制直线，而不是点，请看这个例子，在这里修改为表示一个函数为黑色/红色的好/坏的点:

def plot(xx, yy, good):
    """Plot data

    Good parts are plotted as black, bad parts as red.

    Parameters
    ----------
    xx, yy : 1D arrays
        Data to plot.
    good : `numpy.ndarray`, boolean
        Boolean array indicating if point is good.
    """
    import numpy as np
    import matplotlib.pyplot as plt
    fig, ax = plt.subplots()
    from matplotlib.colors import from_levels_and_colors
    from matplotlib.collections import LineCollection
    cmap, norm = from_levels_and_colors([0.0, 0.5, 1.5], ['red', 'black'])
    points = np.array([xx, yy]).T.reshape(-1, 1, 2)
    segments = np.concatenate([points[:-1], points[1:]], axis=1)
    lines = LineCollection(segments, cmap=cmap, norm=norm)
    lines.set_array(good.astype(int))
    ax.add_collection(lines)
    plt.show()