在matplotlib中注释数据范围

ari*_*ari 6 matplotlib

如何为一系列数据添加注释?例如,说从数据x = 5x = 10比一些截止时,我怎么可能表明,在图形上.如果我用手进行注释,我只需在范围上方绘制一个大括号,并在括号上方写下我的注释.

我见过的最接近的是使用arrowstyle='<->'connectionstyle='bar',用两条箭头指向数据的边缘,用一条线连接它们的尾部.但这并不是正确的事; 您为注释输入的文本将其中一个箭头下方而不是在条形上方.

这是我的尝试,以及它的结果:

annotate(' ', xy=(1,.5),  xycoords='data',
            xytext=(190, .5), textcoords='data',
            arrowprops=dict(arrowstyle="<->",
                            connectionstyle="bar",
                            ec="k",
                            shrinkA=5, shrinkB=5,
                            )
            )
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注释尝试

我尝试解决方案的另一个问题是注释括号的方形形状并没有真正表明我突出显示范围(不像,例如,大括号).但我想这只是在挑剔.

Joo*_*eey 8

如此答案中所述,您可以使用 sigmoidal 函数构造大括号。下面是在 x 轴正上方添加大括号的函数。只要图形宽度和高度不变化,它生成的大括号应该看起来相同,而不管轴的限制如何。

import numpy as np
import matplotlib.pyplot as plt

def draw_brace(ax, xspan, text):
    """Draws an annotated brace on the axes."""
    xmin, xmax = xspan
    xspan = xmax - xmin
    ax_xmin, ax_xmax = ax.get_xlim()
    xax_span = ax_xmax - ax_xmin
    ymin, ymax = ax.get_ylim()
    yspan = ymax - ymin
    resolution = int(xspan/xax_span*100)*2+1 # guaranteed uneven
    beta = 300./xax_span # the higher this is, the smaller the radius

    x = np.linspace(xmin, xmax, resolution)
    x_half = x[:resolution//2+1]
    y_half_brace = (1/(1.+np.exp(-beta*(x_half-x_half[0])))
                    + 1/(1.+np.exp(-beta*(x_half-x_half[-1]))))
    y = np.concatenate((y_half_brace, y_half_brace[-2::-1]))
    y = ymin + (.05*y - .01)*yspan # adjust vertical position

    ax.autoscale(False)
    ax.plot(x, y, color='black', lw=1)

    ax.text((xmax+xmin)/2., ymin+.07*yspan, text, ha='center', va='bottom')

ax = plt.gca()
ax.plot(range(10))
draw_brace(ax, (0, 8), 'large brace')
draw_brace(ax, (8, 9), 'small brace')
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输出:

在此处输入图片说明


tac*_*ell 6

您可以将其全部包装在一个函数中:

def add_range_annotation(ax, start, end, txt_str, y_height=.5, txt_kwargs=None, arrow_kwargs=None):
    """
    Adds horizontal arrow annotation with text in the middle

    Parameters
    ----------
    ax : matplotlib.Axes
        The axes to draw to

    start : float
        start of line

    end : float
        end of line

    txt_str : string
        The text to add

    y_height : float
        The height of the line

    txt_kwargs : dict or None
        Extra kwargs to pass to the text

    arrow_kwargs : dict or None
        Extra kwargs to pass to the annotate

    Returns
    -------
    tuple
        (annotation, text)
    """

    if txt_kwargs is None:
        txt_kwargs = {}
    if arrow_kwargs is None:
        # default to your arrowprops
        arrow_kwargs = {'arrowprops':dict(arrowstyle="<->",
                            connectionstyle="bar",
                            ec="k",
                            shrinkA=5, shrinkB=5,
                            )}

    trans = ax.get_xaxis_transform()

    ann = ax.annotate('', xy=(start, y_height),
                        xytext=(end, y_height),
                        transform=trans,
                        **arrow_kwargs)
    txt = ax.text((start + end) / 2,
                  y_height + .05,
                  txt_str,
                  **txt_kwargs)


    if plt.isinteractive():
        plt.draw()
    return ann, txt
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交替,

start, end = .6, .8
ax.axvspan(start, end, alpha=.2, color='r')
trans = ax.get_xaxis_transform()
ax.text((start + end) / 2, .5, 'test', transform=trans)
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guz*_*zey 5

我修改了Joooeey 的答案以允许更改大括号的垂直位置:

def draw_brace(ax, xspan, yy, text):
    """Draws an annotated brace on the axes."""
    xmin, xmax = xspan
    xspan = xmax - xmin
    ax_xmin, ax_xmax = ax.get_xlim()
    xax_span = ax_xmax - ax_xmin

    ymin, ymax = ax.get_ylim()
    yspan = ymax - ymin
    resolution = int(xspan/xax_span*100)*2+1 # guaranteed uneven
    beta = 300./xax_span # the higher this is, the smaller the radius

    x = np.linspace(xmin, xmax, resolution)
    x_half = x[:int(resolution/2)+1]
    y_half_brace = (1/(1.+np.exp(-beta*(x_half-x_half[0])))
                    + 1/(1.+np.exp(-beta*(x_half-x_half[-1]))))
    y = np.concatenate((y_half_brace, y_half_brace[-2::-1]))
    y = yy + (.05*y - .01)*yspan # adjust vertical position

    ax.autoscale(False)
    ax.plot(x, y, color='black', lw=1)

    ax.text((xmax+xmin)/2., yy+.07*yspan, text, ha='center', va='bottom')
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ax = plt.gca()
ax.plot(range(10))
draw_brace(ax, (0, 8), -0.5, 'large brace')
draw_brace(ax, (8, 9), 3, 'small brace')
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输出:

matplotlib 花括号

另请注意,在Joooeey 的回答中,行

x_half = x[:resolution/2+1]
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应该

x_half = x[:int(resolution/2)+1]
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否则,脚本在这里尝试用作索引的数字是一个浮点数。

最后,请注意,如果您将其移出边界,现在支架将不会显示。您需要添加参数clip_on=False,如下所示:

ax.plot(x, y, color='black', lw=1, clip_on=False)
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GB *_*gan 5

这是对guzeyjooeey 的答案的一个小修改,用于在轴外绘制花括号。

def draw_brace(ax, xspan, yy, text):
"""Draws an annotated brace outside the axes."""
    xmin, xmax = xspan
    xspan = xmax - xmin
    ax_xmin, ax_xmax = ax.get_xlim()
    xax_span = ax_xmax - ax_xmin

    ymin, ymax = ax.get_ylim()
    yspan = ymax - ymin
    resolution = int(xspan/xax_span*100)*2+1 # guaranteed uneven
    beta = 300./xax_span # the higher this is, the smaller the radius

    x = np.linspace(xmin, xmax, resolution)
    x_half = x[:int(resolution/2)+1]
    y_half_brace = (1/(1.+np.exp(-beta*(x_half-x_half[0])))
                + 1/(1.+np.exp(-beta*(x_half-x_half[-1]))))
    y = np.concatenate((y_half_brace, y_half_brace[-2::-1]))
    y = yy + (.05*y - .01)*yspan # adjust vertical position

    ax.autoscale(False)
    ax.plot(x, -y, color='black', lw=1, clip_on=False)

    ax.text((xmax+xmin)/2., -yy-.17*yspan, text, ha='center', va='bottom')

    
# Sample code
fmax = 1
fstart = -100
fend = 0
frise = 50
ffall = 20

def S(x):
   if x<=0:
       return 0
   elif x>=1:
       return 1
   else:
       return 1/(1+np.exp((1/(x-1))+(1/x)))

x = np.linspace(700,1000,500)
lam = [fmax*(S((i-880)/60)-S(((i-1000)/25)+1)) for i in x]
fig = plt.figure(1)
ax = fig.add_subplot(111)
plt.plot(x,lam)
plt.xlim([850,1000])
ax.set_aspect(50,adjustable='box')
plt.ylabel('$\lambda$')
plt.xlabel('$x$')
ax.xaxis.set_label_coords(0.5, -0.35)
draw_brace(ax, (900,950),0.2, 'rise')
draw_brace(ax, (980,1000),0.2, 'fall')
plt.text(822,0.95,'$(\lambda_{\mathrm{max}})$')
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样本输出