| """ |
| ============ |
| Data browser |
| ============ |
| |
| Connecting data between multiple canvases. |
| |
| This example covers how to interact data with multiple canvases. This |
| lets you select and highlight a point on one axis, and generating the |
| data of that point on the other axis. |
| |
| .. note:: |
| This example exercises the interactive capabilities of Matplotlib, and this |
| will not appear in the static documentation. Please run this code on your |
| machine to see the interactivity. |
| |
| You can copy and paste individual parts, or download the entire example |
| using the link at the bottom of the page. |
| """ |
| import numpy as np |
|
|
|
|
| class PointBrowser: |
| """ |
| Click on a point to select and highlight it -- the data that |
| generated the point will be shown in the lower axes. Use the 'n' |
| and 'p' keys to browse through the next and previous points |
| """ |
|
|
| def __init__(self): |
| self.lastind = 0 |
|
|
| self.text = ax.text(0.05, 0.95, 'selected: none', |
| transform=ax.transAxes, va='top') |
| self.selected, = ax.plot([xs[0]], [ys[0]], 'o', ms=12, alpha=0.4, |
| color='yellow', visible=False) |
|
|
| def on_press(self, event): |
| if self.lastind is None: |
| return |
| if event.key not in ('n', 'p'): |
| return |
| if event.key == 'n': |
| inc = 1 |
| else: |
| inc = -1 |
|
|
| self.lastind += inc |
| self.lastind = np.clip(self.lastind, 0, len(xs) - 1) |
| self.update() |
|
|
| def on_pick(self, event): |
|
|
| if event.artist != line: |
| return True |
|
|
| N = len(event.ind) |
| if not N: |
| return True |
|
|
| |
| x = event.mouseevent.xdata |
| y = event.mouseevent.ydata |
|
|
| distances = np.hypot(x - xs[event.ind], y - ys[event.ind]) |
| indmin = distances.argmin() |
| dataind = event.ind[indmin] |
|
|
| self.lastind = dataind |
| self.update() |
|
|
| def update(self): |
| if self.lastind is None: |
| return |
|
|
| dataind = self.lastind |
|
|
| ax2.clear() |
| ax2.plot(X[dataind]) |
|
|
| ax2.text(0.05, 0.9, f'mu={xs[dataind]:1.3f}\nsigma={ys[dataind]:1.3f}', |
| transform=ax2.transAxes, va='top') |
| ax2.set_ylim(-0.5, 1.5) |
| self.selected.set_visible(True) |
| self.selected.set_data(xs[dataind], ys[dataind]) |
|
|
| self.text.set_text('selected: %d' % dataind) |
| fig.canvas.draw() |
|
|
|
|
| if __name__ == '__main__': |
| import matplotlib.pyplot as plt |
|
|
| |
| np.random.seed(19680801) |
|
|
| X = np.random.rand(100, 200) |
| xs = np.mean(X, axis=1) |
| ys = np.std(X, axis=1) |
|
|
| fig, (ax, ax2) = plt.subplots(2, 1) |
| ax.set_title('click on point to plot time series') |
| line, = ax.plot(xs, ys, 'o', picker=True, pickradius=5) |
|
|
| browser = PointBrowser() |
|
|
| fig.canvas.mpl_connect('pick_event', browser.on_pick) |
| fig.canvas.mpl_connect('key_press_event', browser.on_press) |
|
|
| plt.show() |
|
|
