SF.net SVN: matplotlib:[8123] trunk/matplotlib/examples/api/sankey_demo.py

[<jd...@us...>]

Revision: 8123
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=8123&view=rev
Author:   jdh2358
Date:     2010-02-10 15:56:34 +0000 (Wed, 10 Feb 2010)

Log Message:
-----------
added Yannick Copin's sanke demo

Added Paths:
-----------
    trunk/matplotlib/examples/api/sankey_demo.py

Added: trunk/matplotlib/examples/api/sankey_demo.py
===================================================================
--- trunk/matplotlib/examples/api/sankey_demo.py	                        (rev 0)
+++ trunk/matplotlib/examples/api/sankey_demo.py	2010-02-10 15:56:34 UTC (rev 8123)
@@ -0,0 +1,105 @@
+#!/usr/bin/env python
+# Time-stamp: <2010-02-10 01:49:08 ycopin>
+
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.patches as mpatches
+from matplotlib.path import Path
+
+def sankey(ax, losses, labels=None,
+           dx=40, dy=10, angle=45, w=3, dip=10, offset=2, **kwargs):
+    """Draw a Sankey diagram.
+
+    losses: array of losses, should sum up to 100%
+    labels: loss labels (same length as losses),
+            or None (use default labels) or '' (no labels)
+    dx: horizontal elongation
+    dy: vertical elongation
+    angle: arrow angle [deg]
+    w: arrow shoulder
+    dip: input dip
+    offset: text offset
+    **kwargs: propagated to Patch (e.g. fill=False)
+
+    Return (patch,texts)."""
+
+    assert sum(losses)==100, "Input losses don't sum up to 100%"
+
+    def add_loss(loss, last=False):
+        h = (loss/2+w)*np.tan(angle/180.*np.pi) # Arrow tip height
+        move,(x,y) = path[-1]           # Use last point as reference
+        if last:                        # Final loss (horizontal)
+            path.extend([(Path.LINETO,[x+dx,y]),
+                         (Path.LINETO,[x+dx,y+w]),
+                         (Path.LINETO,[x+dx+h,y-loss/2]), # Tip
+                         (Path.LINETO,[x+dx,y-loss-w]),
+                         (Path.LINETO,[x+dx,y-loss])])
+            tips.append(path[-3][1])
+        else:                           # Intermediate loss (vertical)
+            path.extend([(Path.LINETO,[x+dx/2,y]),
+                        (Path.CURVE3,[x+dx,y]),
+                        (Path.CURVE3,[x+dx,y+dy]),
+                        (Path.LINETO,[x+dx-w,y+dy]),
+                        (Path.LINETO,[x+dx+loss/2,y+dy+h]), # Tip
+                        (Path.LINETO,[x+dx+loss+w,y+dy]),
+                        (Path.LINETO,[x+dx+loss,y+dy]),
+                        (Path.CURVE3,[x+dx+loss,y-loss]),
+                        (Path.CURVE3,[x+dx/2+loss,y-loss])])
+            tips.append(path[-5][1])
+
+    tips = []                           # Arrow tip positions
+    path = [(Path.MOVETO,[0,100])]      # 1st point
+    for i,loss in enumerate(losses):
+        add_loss(loss, last=(i==(len(losses)-1)))
+    path.extend([(Path.LINETO,[0,0]),
+                 (Path.LINETO,[dip,50]), # Dip
+                 (Path.CLOSEPOLY,[0,100])])
+    codes,verts = zip(*path)
+    verts = np.array(verts)
+
+    # Path patch
+    path = Path(verts,codes)
+    patch = mpatches.PathPatch(path, **kwargs)
+    ax.add_patch(patch)
+
+    # Labels
+    if labels=='':                      # No labels
+        pass
+    elif labels is None:                # Default labels
+        labels = [ '%2d%%' % loss for loss in losses ]
+    else:
+        assert len(labels)==len(losses)
+
+    texts = []
+    for i,label in enumerate(labels):
+        x,y = tips[i]                   # Label position
+        last = (i==(len(losses)-1))
+        if last:
+            t = ax.text(x+offset,y,label, ha='left', va='center')
+        else:
+            t = ax.text(x,y+offset,label, ha='center', va='bottom')
+        texts.append(t)
+
+    # Axes management
+    ax.set_xlim(verts[:,0].min()-10, verts[:,0].max()+40)
+    ax.set_ylim(verts[:,1].min()-10, verts[:,1].max()+20)
+    ax.set_aspect('equal', adjustable='datalim')
+    ax.set_xticks([])
+    ax.set_yticks([])
+
+    return patch,texts
+
+if __name__=='__main__':
+
+    losses = [10.,20.,5.,15.,10.,40.]
+    labels = ['First','Second','Third','Fourth','Fifth','Hurray!']
+    labels = [ s+'\n%d%%' % l for l,s in zip(losses,labels) ]
+
+    fig = plt.figure()
+    ax = fig.add_subplot(1,1,1)
+
+    patch,texts = sankey(ax, losses, labels, fc='g', alpha=0.2)
+    texts[1].set_color('r')
+    texts[-1].set_fontweight('bold')
+
+    plt.show()


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