plotting

README.rst

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+=============
+DynamicSeries
+=============
+
+A class to plot a time series measured from an instrument.

dynamicseries.py

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