将鼠标悬停在词干图中的matplotlib中的某个点上时，是否可以显示标签? [英] Possible to make labels appear when hovering over a point in matplotlib in stem plot?

问题描述

我是matplotlib的新手，当鼠标悬停在该点上时，我希望用x，y代码标记茎图中的茎.当我搜索所有内容时都是为了散点图(将鼠标悬停在matplotlib中的某个点上时是否可能使标签出现?当前代码如下:

I am new to matplotlib and I am looking to label stems in a stem plot with x,y co-od when mouse hovers over that point. When I searched everything was meant for scatter plot (Possible to make labels appear when hovering over a point in matplotlib? present code is like this:

def plot_matching(mzs,ints,matching,scan_num):
fig=p1.gcf()
fig.canvas.set_window_title('MS/MS Viewer')
rel_ints=relative_intensity(ints)
p1.xlim(min(mzs)-100,max(mzs)+100)
p1.ylim(min(rel_ints),max(rel_ints)+5)
p1.title('Scan Number:'+scan_num)
p1.xlabel('m/z')
p1.ylabel('Relative intensity')
mzs_rel=zip(mzs,rel_ints)    
for x,y in mzs_rel:
    x1=[]
    y1=[]
    x1.append(x)
    y1.append(y)
    markerline, stemlines, baseline=p1.stem(x1,y1)
    p1.setp(markerline, 'Marker', '')
    for m in matching:
        if x==m[1] and y>3.0:
            p1.setp(stemlines, linewidth=2, color='r')
            p1.text(x,y,m[0],fontsize=12)
            break
        else:
            p1.setp(stemlines,linewidth=2, color='g')
return p1

散点图链接也将用于茎图吗?

Will the scatter plot link for stem plot too?

推荐答案

要制作悬停标签，您需要连接一个函数来处理motion_notify_events:

To make a hovering label, you need to hook up a function to handle motion_notify_events:

    plt.connect('motion_notify_event', some_function)

下面是一些代码，显示了一种实现方法.悬停标签行为是由

Below is some code showing one way to do it. The hovering label behavior is produced by

cursor = FollowDotCursor(ax, x, y)

其中ax是轴，x和y是坐标列表.由于提供了x和y，因此无论是绘制线图还是茎图或其他任何内容都没有关系.当鼠标移动到任何位置(xi, yi)时，标签就会显示.

where ax is the axis, x and y are lists of coordinates. Since you supply x and y, it does not matter if you are making a line plot or a stem plot or whatever. The labels appear when the mouse is moved near any point (xi, yi).

下面的代码使用scipy.spatial.cKDTree定位最近的点. 此处是此代码的较旧版本，不需要密码.

The code below uses scipy.spatial.cKDTree to locate the nearest point. Here is an older version of this code which does not require scipy.

import matplotlib.pyplot as plt
import scipy.spatial as spatial
import numpy as np
pi = np.pi
cos = np.cos

def fmt(x, y):
    return 'x: {x:0.2f}\ny: {y:0.2f}'.format(x=x, y=y)

class FollowDotCursor(object):
    """Display the x,y location of the nearest data point.
    https://stackoverflow.com/a/4674445/190597 (Joe Kington)
    https://stackoverflow.com/a/13306887/190597 (unutbu)
    https://stackoverflow.com/a/15454427/190597 (unutbu)
    """
    def __init__(self, ax, x, y, tolerance=5, formatter=fmt, offsets=(-20, 20)):
        try:
            x = np.asarray(x, dtype='float')
        except (TypeError, ValueError):
            x = np.asarray(mdates.date2num(x), dtype='float')
        y = np.asarray(y, dtype='float')
        mask = ~(np.isnan(x) | np.isnan(y))
        x = x[mask]
        y = y[mask]
        self._points = np.column_stack((x, y))
        self.offsets = offsets
        y = y[np.abs(y-y.mean()) <= 3*y.std()]
        self.scale = x.ptp()
        self.scale = y.ptp() / self.scale if self.scale else 1
        self.tree = spatial.cKDTree(self.scaled(self._points))
        self.formatter = formatter
        self.tolerance = tolerance
        self.ax = ax
        self.fig = ax.figure
        self.ax.xaxis.set_label_position('top')
        self.dot = ax.scatter(
            [x.min()], [y.min()], s=130, color='green', alpha=0.7)
        self.annotation = self.setup_annotation()
        plt.connect('motion_notify_event', self)

    def scaled(self, points):
        points = np.asarray(points)
        return points * (self.scale, 1)

    def __call__(self, event):
        ax = self.ax
        # event.inaxes is always the current axis. If you use twinx, ax could be
        # a different axis.
        if event.inaxes == ax:
            x, y = event.xdata, event.ydata
        elif event.inaxes is None:
            return
        else:
            inv = ax.transData.inverted()
            x, y = inv.transform([(event.x, event.y)]).ravel()
        annotation = self.annotation
        x, y = self.snap(x, y)
        annotation.xy = x, y
        annotation.set_text(self.formatter(x, y))
        self.dot.set_offsets(np.column_stack((x, y)))
        bbox = self.annotation.get_window_extent()
        self.fig.canvas.blit(bbox)
        self.fig.canvas.draw_idle()

    def setup_annotation(self):
        """Draw and hide the annotation box."""
        annotation = self.ax.annotate(
            '', xy=(0, 0), ha = 'right',
            xytext = self.offsets, textcoords = 'offset points', va = 'bottom',
            bbox = dict(
                boxstyle='round,pad=0.5', fc='yellow', alpha=0.75),
            arrowprops = dict(
                arrowstyle='->', connectionstyle='arc3,rad=0'))
        return annotation

    def snap(self, x, y):
        """Return the value in self.tree closest to x, y."""
        dist, idx = self.tree.query(self.scaled((x, y)), k=1, p=1)
        try:
            return self._points[idx]
        except IndexError:
            # IndexError: index out of bounds
            return self._points[0]

fig, ax = plt.subplots()
x = np.linspace(0.1, 2*pi, 10)
y = cos(x)
markerline, stemlines, baseline = ax.stem(x, y, '-.')
plt.setp(markerline, 'markerfacecolor', 'b')
plt.setp(baseline, 'color','r', 'linewidth', 2)
cursor = FollowDotCursor(ax, x, y, tolerance=20)
plt.show()

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