獲取 matplotlib 圖上最近數據點的坐標

Question

我將matplotlib與NavigationToolbar2QT 。 工具欄顯示光標的位置。 但我希望光標捕捉到最近的數據點（當足夠接近時）或者只是顯示最近數據點的坐標。 可以以某種方式安排嗎？

Answer 1

如果您正在處理大量點，我建議您使用CKDtrees ：

import matplotlib.pyplot as plt
import numpy as np
import scipy.spatial

points = np.column_stack([np.random.rand(50), np.random.rand(50)])
fig, ax = plt.subplots()
coll = ax.scatter(points[:,0], points[:,1])
ckdtree = scipy.spatial.cKDTree(points)

我在這里重構了kpie's答案。 創建ckdtree ，您可以立即識別最近的點以及有關它們的各種信息，只需稍加努力：

def closest_point_distance(ckdtree, x, y):
    #returns distance to closest point
    return ckdtree.query([x, y])[0]

def closest_point_id(ckdtree, x, y):
    #returns index of closest point
    return ckdtree.query([x, y])[1]

def closest_point_coords(ckdtree, x, y):
    # returns coordinates of closest point
    return ckdtree.data[closest_point_id(ckdtree, x, y)]
    # ckdtree.data is the same as points

光標位置的交互式顯示。 如果您希望在導航工具欄上顯示最近點的坐標：

def val_shower(ckdtree):
    #formatter of coordinates displayed on Navigation Bar
    return lambda x, y: '[x = {}, y = {}]'.format(*closest_point_coords(ckdtree, x, y))

plt.gca().format_coord = val_shower(ckdtree)
plt.show()

使用事件。 如果你想要另一種交互性，你可以使用事件：

def onclick(event):
    if event.inaxes is not None:
        print(closest_point_coords(ckdtree, event.xdata, event.ydata))

fig.canvas.mpl_connect('motion_notify_event', onclick)
plt.show()

Answer 2

您可以mouse_move NavigationToolbar2QT並覆蓋mouse_move處理程序。 xdata和ydata屬性包含繪圖坐標中的當前鼠標位置。 在將事件傳遞給基類mouse_move處理程序之前，您可以將其捕捉到最近的數據點。

完整示例，突出顯示圖中最近的點作為獎勵：

import sys

import numpy as np

from matplotlib.backends.qt_compat import QtWidgets
from matplotlib.backends.backend_qt5agg import FigureCanvas, NavigationToolbar2QT
from matplotlib.figure import Figure


class Snapper:
    """Snaps to data points"""

    def __init__(self, data, callback):
        self.data = data
        self.callback = callback

    def snap(self, x, y):
        pos = np.array([x, y])
        distances = np.linalg.norm(self.data - pos, axis=1)
        dataidx = np.argmin(distances)
        datapos = self.data[dataidx,:]
        self.callback(datapos[0], datapos[1])
        return datapos


class SnappingNavigationToolbar(NavigationToolbar2QT):
    """Navigation toolbar with data snapping"""

    def __init__(self, canvas, parent, coordinates=True):
        super().__init__(canvas, parent, coordinates)
        self.snapper = None

    def set_snapper(self, snapper):
        self.snapper = snapper

    def mouse_move(self, event):
        if self.snapper and event.xdata and event.ydata:
            event.xdata, event.ydata = self.snapper.snap(event.xdata, event.ydata)
        super().mouse_move(event)


class Highlighter:
    def __init__(self, ax):
        self.ax = ax
        self.marker = None
        self.markerpos = None

    def draw(self, x, y):
        """draws a marker at plot position (x,y)"""
        if (x, y) != self.markerpos:
            if self.marker:
                self.marker.remove()
                del self.marker
            self.marker = self.ax.scatter(x, y, color='yellow')
            self.markerpos = (x, y)
            self.ax.figure.canvas.draw()


class ApplicationWindow(QtWidgets.QMainWindow):
    def __init__(self):
        super().__init__()
        self._main = QtWidgets.QWidget()
        self.setCentralWidget(self._main)
        layout = QtWidgets.QVBoxLayout(self._main)
        canvas = FigureCanvas(Figure(figsize=(5,3)))
        layout.addWidget(canvas)
        toolbar = SnappingNavigationToolbar(canvas, self)
        self.addToolBar(toolbar)

        data = np.random.randn(100, 2)
        ax = canvas.figure.subplots()
        ax.scatter(data[:,0], data[:,1])

        self.highlighter = Highlighter(ax)
        snapper = Snapper(data, self.highlighter.draw)
        toolbar.set_snapper(snapper)


if __name__ == "__main__":
    qapp = QtWidgets.QApplication(sys.argv)
    app = ApplicationWindow()
    app.show()
    qapp.exec_()

Answer 3

以下代碼將在您單擊時打印最靠近鼠標的點的坐標。

import matplotlib.pyplot as plt
import numpy as np
np.random.seed(19680801)
N = 50
x = np.random.rand(N)
y = np.random.rand(N)
fig,ax = plt.subplots()
plt.scatter(x, y)
points = list(zip(x,y))
def distance(a,b):
    return(sum([(k[0]-k[1])**2 for k in zip(a,b)])**0.5)
def onclick(event):
    dists = [distance([event.xdata, event.ydata],k) for k in points]
    print(points[dists.index(min(dists))])
fig.canvas.mpl_connect('button_press_event', onclick)
plt.show()

Answer 4

另一種可能性是使用已有的采摘支撐軸。 請參閱事件處理文檔中的這一部分。

吉姆