59 lines
1.5 KiB
Python
59 lines
1.5 KiB
Python
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import matplotlib
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from matplotlib.lines import Line2D
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class DynamicSeries:
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""" AutomaticTimeSeries handles drawing a line in an efficient way
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onto a matplotlib canvas. """
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def __init__(self, fig, ax):
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self.fig = fig
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self.ax = ax
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# Line associated with the figure used to draw the next line.
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self.dummyLine = ax.plot([0],[0], animated=True)[0]
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# Bitmap of previous background
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self._bg = None
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# Redraw time series on reveal.
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fig.canvas.mpl_connect("draw_event", self.on_draw)
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self.x_ax = []
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self.y_ax = []
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self.current_x_lims = 10
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def insert(self, x, y):
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self.x_ax.append([x])
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self.y_ax.append([y])
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if len(self.x_ax) == 1:
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return None
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prev_x = self.x_ax[-1]
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prev_y = self.y_ax[-1]
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self.dummyLine.set_data([(prev_x, prev_y), (x, y)])
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if self._bg is not None:
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self.fig.canvas.restore_region(self._bg)
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self.fig.draw_artist(self.dummyLine)
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self.fig.canvas.blit(self.fig.bbox)
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self.fig.canvas.flush_events()
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self._bg = self.fig.canvas.copy_from_bbox(self.fig.bbox)
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def on_invalidated(self):
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""" Redraw the entire canvas on invalidation. """
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self.ax.clear()
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self.ax.set_xlim(0, self.current_x_lims)
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self.ax.plot(self.x_ax, self.y_ax, color="blue")
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def on_draw(self, event):
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self.on_invalidated()
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import matplotlib.pyplot as plt
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fig, ax = plt.subplots()
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fig.show()
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ats = AutomaticTimeSeries(fig, ax)
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