python - 在 matplotlibs 交互模式下编辑 python 变量

标签 python matplotlib plot

我实际上正在开发一个小型数据编辑器来平滑一些测量。因此我想在交互模式下使用 matplotlib,如下示例: Poly_editor example from matplotlib...

"""
This is an example to show how to build cross-GUI applications using
matplotlib event handling to interact with objects on the canvas

"""
import numpy as np
from matplotlib.lines import Line2D
from matplotlib.artist import Artist
from matplotlib.mlab import dist_point_to_segment


class PolygonInteractor(object):
    """
    An polygon editor.

    Key-bindings

      't' toggle vertex markers on and off.  When vertex markers are on,
          you can move them, delete them

      'd' delete the vertex under point

      'i' insert a vertex at point.  You must be within epsilon of the
          line connecting two existing vertices

    """

    showverts = True
    epsilon = 5  # max pixel distance to count as a vertex hit

    def __init__(self, ax, poly):
        if poly.figure is None:
            raise RuntimeError('You must first add the polygon to a figure         or canvas before defining the interactor')
        self.ax = ax
        canvas = poly.figure.canvas
        self.poly = poly

        x, y = zip(*self.poly.xy)
        self.line = Line2D(x, y, marker='o', markerfacecolor='r', animated=True)
        self.ax.add_line(self.line)
        #self._update_line(poly)

        cid = self.poly.add_callback(self.poly_changed)
        self._ind = None  # the active vert

        canvas.mpl_connect('draw_event', self.draw_callback)
        canvas.mpl_connect('button_press_event', self.button_press_callback)
        canvas.mpl_connect('key_press_event', self.key_press_callback)
        canvas.mpl_connect('button_release_event', self.button_release_callback)
        canvas.mpl_connect('motion_notify_event', self.motion_notify_callback)
        self.canvas = canvas

    def draw_callback(self, event):
        self.background = self.canvas.copy_from_bbox(self.ax.bbox)
        self.ax.draw_artist(self.poly)
        self.ax.draw_artist(self.line)
        self.canvas.blit(self.ax.bbox)

    def poly_changed(self, poly):
        'this method is called whenever the polygon object is called'
        # only copy the artist props to the line (except visibility)
        vis = self.line.get_visible()
        Artist.update_from(self.line, poly)
        self.line.set_visible(vis)  # don't use the poly visibility state

    def get_ind_under_point(self, event):
        'get the index of the vertex under point if within epsilon tolerance'

        # display coords
        xy = np.asarray(self.poly.xy)
        xyt = self.poly.get_transform().transform(xy)
        xt, yt = xyt[:, 0], xyt[:, 1]
        d = np.sqrt((xt - event.x)**2 + (yt - event.y)**2)
        indseq = np.nonzero(np.equal(d, np.amin(d)))[0]
        ind = indseq[0]

        if d[ind] >= self.epsilon:
            ind = None

        return ind

    def button_press_callback(self, event):
        'whenever a mouse button is pressed'
        if not self.showverts:
            return
        if event.inaxes is None:
            return
        if event.button != 1:
            return
        self._ind = self.get_ind_under_point(event)

    def button_release_callback(self, event):
        'whenever a mouse button is released'
        if not self.showverts:
            return
        if event.button != 1:
            return
        self._ind = None

    def key_press_callback(self, event):
        'whenever a key is pressed'
        if not event.inaxes:
            return
        if event.key == 't':
            self.showverts = not self.showverts
            self.line.set_visible(self.showverts)
            if not self.showverts:
                self._ind = None
        elif event.key == 'd':
            ind = self.get_ind_under_point(event)
            if ind is not None:
                self.poly.xy = [tup for i, tup in enumerate(self.poly.xy) if i != ind]
                self.line.set_data(zip(*self.poly.xy))
        elif event.key == 'i':
            xys = self.poly.get_transform().transform(self.poly.xy)
            p = event.x, event.y  # display coords
            for i in range(len(xys) - 1):
                s0 = xys[i]
                s1 = xys[i + 1]
                d = dist_point_to_segment(p, s0, s1)
                if d <= self.epsilon:
                    self.poly.xy = np.array(
                        list(self.poly.xy[:i]) +
                        [(event.xdata, event.ydata)] +
                        list(self.poly.xy[i:]))
                    self.line.set_data(zip(*self.poly.xy))
                    break

        self.canvas.draw()

    def motion_notify_callback(self, event):
        'on mouse movement'
        if not self.showverts:
            return
        if self._ind is None:
            return
        if event.inaxes is None:
            return
        if event.button != 1:
            return
        x, y = event.xdata, event.ydata

        self.poly.xy[self._ind] = x, y
        if self._ind == 0:
            self.poly.xy[-1] = x, y
        elif self._ind == len(self.poly.xy) - 1:
            self.poly.xy[0] = x, y
        self.line.set_data(zip(*self.poly.xy))

        self.canvas.restore_region(self.background)
        self.ax.draw_artist(self.poly)
        self.ax.draw_artist(self.line)
        self.canvas.blit(self.ax.bbox)


if __name__ == '__main__':
    import matplotlib.pyplot as plt
    from matplotlib.patches import Polygon

    theta = np.arange(0, 2*np.pi, 0.1)
    r = 1.5

    xs = r*np.cos(theta)
    ys = r*np.sin(theta)

    poly = Polygon(list(zip(xs, ys)), animated=True)

    fig, ax = plt.subplots()
    ax.add_patch(poly)
    p = PolygonInteractor(ax, poly)

    #ax.add_line(p.line)
    ax.set_title('Click and drag a point to move it')
    ax.set_xlim((-2, 2))
    ax.set_ylim((-2, 2))
    plt.show()

为了简单起见,我现在想要手动编辑显示的多边形,并在关闭窗口后,应存储顶点的新 xy 值用于进一步计算。

我现在的问题是,plt.show() 之后的代码立即执行。 plt.show(blocked=True) 不适用于交互模式。 plt.show() 甚至可以从代码中排除,但它仍然有效,因为绘图似乎都是在 PolygonInteractor 类中完成的...

有人对如何“真正”编辑图中的数据有建议吗?

最佳答案

该问题并非专用于 matplotlib,而是专用于 Spyder。 当在实际的 Ipython 控制台中执行时,matplot-windows 似乎是单独运行的,并且 plt.show() 之后的代码立即执行。

将控制台选项设置为“在新的专用 Python 控制台中执行”为我解决了这个问题。

关于python - 在 matplotlibs 交互模式下编辑 python 变量,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/41963456/

相关文章:

python - 派斯帕克 2 : KMeans The input data is not directly cached

python - Matplotlib 动画多行和文本

python - matplotlib 将刻度与刻度末端对齐

r - 如何使用 ggplot2 给图形编号

Matlab 将 defaultTextInterpreter 设置为 LaTeX

python - PyCharm - 如何暂停所有线程

python - 更改spark中的时间戳TZ

r - 在 par(fig) 之后,不写入边距中的文本

python - 高维结构化 numpy 数据类型上的 numba 类型错误

python - Matplotlib:检查网格是否打开?