1 files changed, 100 insertions, 0 deletions
diff --git a/scripts/tracing/dma-api/plotting.py b/scripts/tracing/dma-api/plotting.py
new file mode 100644
index 000000000000..f3d69b6a36a4
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+++ b/scripts/tracing/dma-api/plotting.py
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+"""Ugly graph drawing tools"""
+import matplotlib.pyplot as plt
+import matplotlib.cm as cmap
+#import numpy as np
+from matplotlib import cbook
+
+# http://stackoverflow.com/questions/4652439/is-there-a-matplotlib-equivalent-of-matlabs-datacursormode
+class DataCursor(object):
+    """A simple data cursor widget that displays the x,y location of a
+    matplotlib artist when it is selected."""
+    def __init__(self, artists, tolerance=5, offsets=(-20, 20),
+                 template='x: %0.2f\ny: %0.2f', display_all=False):
+        """Create the data cursor and connect it to the relevant figure.
+        "artists" is the matplotlib artist or sequence of artists that will be
+            selected.
+        "tolerance" is the radius (in points) that the mouse click must be
+            within to select the artist.
+        "offsets" is a tuple of (x,y) offsets in points from the selected
+            point to the displayed annotation box
+        "template" is the format string to be used. Note: For compatibility
+            with older versions of python, this uses the old-style (%)
+            formatting specification.
+        "display_all" controls whether more than one annotation box will
+            be shown if there are multiple axes.  Only one will be shown
+            per-axis, regardless.
+        """
+        self.template = template
+        self.offsets = offsets
+        self.display_all = display_all
+        if not cbook.iterable(artists):
+            artists = [artists]
+        self.artists = artists
+        self.axes = tuple(set(art.axes for art in self.artists))
+        self.figures = tuple(set(ax.figure for ax in self.axes))
+
+        self.annotations = {}
+        for ax in self.axes:
+            self.annotations[ax] = self.annotate(ax)
+
+        for artist in self.artists:
+            artist.set_picker(tolerance)
+        for fig in self.figures:
+            fig.canvas.mpl_connect('pick_event', self)
+
+    def annotate(self, ax):
+        """Draws and hides the annotation box for the given axis "ax"."""
+        annotation = ax.annotate(self.template, xy=(0, 0), ha='right',
+                xytext=self.offsets, textcoords='offset points', va='bottom',
+                bbox=dict(boxstyle='round,pad=0.5', fc='yellow', alpha=0.5),
+                arrowprops=dict(arrowstyle='->', connectionstyle='arc3,rad=0')
+                )
+        annotation.set_visible(False)
+        return annotation
+
+    def __call__(self, event):
+        """Intended to be called through "mpl_connect"."""
+        # Rather than trying to interpolate, just display the clicked coords
+        # This will only be called if it's within "tolerance", anyway.
+        x, y = event.mouseevent.xdata, event.mouseevent.ydata
+        try:
+            annotation = self.annotations[event.artist.axes]
+        except KeyError:
+            return
+        if x is not None:
+            if not self.display_all:
+                # Hide any other annotation boxes...
+                for ann in self.annotations.values():
+                    ann.set_visible(False)
+            # Update the annotation in the current axis..
+            annotation.xy = x, y
+            annotation.set_text(self.template % (x, y))
+            annotation.set_visible(True)
+            event.canvas.draw()
+
+def plotseries(*serieslabels):
+    """Plot lists of series in separate axes, tie time axis together"""
+    global fig
+    fig, axes = plt.subplots(nrows=len(serieslabels), sharex=True)
+
+    for subplot, ax in zip(serieslabels, axes):
+        for ser, lab in zip(*subplot): # subplot = ([x], [y])
+            ax.step(ser[0], ser[1], label=lab, where="post")
+        ax.grid(True)
+        ax.legend()
+
+        (DataCursor(ax.lines))
+        plt.grid(True)
+    plt.show()
+
+
+
+def disp_pic(bitmap):
+    """Display the allocation bitmap. TODO."""
+    fig=plt.figure()
+    a=fig.add_subplot(1,1,1)
+    fig.clf()
+    implt=plt.imshow(bitmap, extent=(0, len(bitmap[0]), 0, len(bitmap)),
+            interpolation="nearest", cmap=cmap.gist_heat)
+    fig.canvas.draw()
+    plt.show()