如果超过特定范围，是否可以更改绘图中的线条颜色？

Question

当值超过某个 y 值时，是否可以更改图中的线条颜色？例子：

 import numpy as np
import matplotlib.pyplot as plt
a = np.array([1,2,17,20,16,3,5,4])
plt.plt(a)

这个给出了以下内容：

我想可视化超过 y=15 的值。类似于下图：

或者像这样的东西（循环线型）： :

是否可以？

原文由 Mpizos Dimitris 发布，翻译遵循 CC BY-SA 4.0 许可协议

Answer 1

不幸的是，matplotlib 没有一个简单的选项来改变一条线的一部分的颜色。我们将不得不自己编写逻辑。诀窍是将线切割成线段的集合，然后为每条线段分配一种颜色，然后绘制它们。

 from matplotlib import pyplot as plt
from matplotlib.collections import LineCollection
import numpy as np

# The x and y data to plot
y = np.array([1,2,17,20,16,3,5,4])
x = np.arange(len(y))

# Threshold above which the line should be red
threshold = 15

# Create line segments: 1--2, 2--17, 17--20, 20--16, 16--3, etc.
segments_x = np.r_[x[0], x[1:-1].repeat(2), x[-1]].reshape(-1, 2)
segments_y = np.r_[y[0], y[1:-1].repeat(2), y[-1]].reshape(-1, 2)

# Assign colors to the line segments
linecolors = ['red' if y_[0] > threshold and y_[1] > threshold else 'blue'
              for y_ in segments_y]

# Stamp x,y coordinates of the segments into the proper format for the
# LineCollection
segments = [zip(x_, y_) for x_, y_ in zip(segments_x, segments_y)]

# Create figure
plt.figure()
ax = plt.axes()

# Add a collection of lines
ax.add_collection(LineCollection(segments, colors=linecolors))

# Set x and y limits... sadly this is not done automatically for line
# collections
ax.set_xlim(0, 8)
ax.set_ylim(0, 21)

你的第二个选择要容易得多。我们首先画线，然后在其上添加标记作为散点图：

 from matplotlib import pyplot as plt
import numpy as np

# The x and y data to plot
y = np.array([1,2,17,20,16,3,5,4])
x = np.arange(len(y))

# Threshold above which the markers should be red
threshold = 15

# Create figure
plt.figure()

# Plot the line
plt.plot(x, y, color='blue')

# Add below threshold markers
below_threshold = y < threshold
plt.scatter(x[below_threshold], y[below_threshold], color='green')

# Add above threshold markers
above_threshold = np.logical_not(below_threshold)
plt.scatter(x[above_threshold], y[above_threshold], color='red')

原文由 Marijn van Vliet 发布，翻译遵循 CC BY-SA 3.0 许可协议

Answer 2

定义一个辅助函数（这是一个基本的函数，可以添加更多的功能）。此代码是对文档中 此示例 的轻微重构。

 import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
from matplotlib.colors import ListedColormap, BoundaryNorm

def threshold_plot(ax, x, y, threshv, color, overcolor):
    """
    Helper function to plot points above a threshold in a different color

    Parameters
    ----------
    ax : Axes
        Axes to plot to
    x, y : array
        The x and y values

    threshv : float
        Plot using overcolor above this value

    color : color
        The color to use for the lower values

    overcolor: color
        The color to use for values over threshv

    """
    # 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([color, overcolor])
    norm = BoundaryNorm([np.min(y), threshv, np.max(y)], 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(y)

    ax.add_collection(lc)
    ax.set_xlim(np.min(x), np.max(x))
    ax.set_ylim(np.min(y)*1.1, np.max(y)*1.1)
    return lc

使用示例

fig, ax = plt.subplots()

x = np.linspace(0, 3 * np.pi, 500)
y = np.sin(x)

lc = threshold_plot(ax, x, y, .75, 'k', 'r')
ax.axhline(.75, color='k', ls='--')
lc.set_linewidth(3)

和输出

如果您只希望标记改变颜色，请使用相同的范数和 cmap 并将它们传递给散点图

cmap = ListedColormap([color, overcolor])
norm = BoundaryNorm([np.min(y), threshv, np.max(y)], cmap.N)
sc = ax.scatter(x, y, c=c, norm=norm, cmap=cmap)

原文由 tacaswell 发布，翻译遵循 CC BY-SA 3.0 许可协议