Move labels to bars in vertical graph.

xlap/analyse/latency.py

@@ -116,6 +116,33 @@ def _plot_controlflow_graph(df, hdb):
     #    print("\t_node__"+edge['Start'] + " -> _node__"+edge['End'] + "[label=\""+str(edge['Correlation'])+"\"];")
     print("}")
 
+
+# Taken from: http://composition.al/blog/2015/11/29/a-better-way-to-add-labels-to-bar-charts-with-matplotlib/
+def autolabel(rects, ax, labels):
+    # Get y-axis height to calculate label position from.
+    (y_bottom, y_top) = ax.get_ylim()
+    y_height = y_top - y_bottom
+
+    for i, rect in enumerate(rects):
+        height = rect.get_height()
+        color = "black"
+
+        # Fraction of axis height taken up by this rectangle
+        p_height = (height / y_height)
+
+        # If we can fit the label above the column, do that;
+        # otherwise, put it inside the column.
+        if p_height > 0.50: # arbitrary; 95% looked good to me.
+            label_position = 0.01
+            color = "white"
+        else:
+            label_position = height + (y_height * 0.01)
+
+        ax.text(rect.get_x() + rect.get_width()/2., label_position,
+                labels[i],
+                ha='center', va='bottom', rotation=90, color=color)
+
+
 def _plot_critical_regions(df,hdb):
     """
     plot regions, sorted by latency criticality
@@ -123,18 +150,22 @@ def _plot_critical_regions(df,hdb):
     for region in sorted(hdb, key = lambda x: -x['Correlation']):
         print("%-10f %10s -> %10s"%(region['Correlation'], region['Start'], region['End']), file=sys.stderr)
 
-    relevant = sorted([x for x in hdb if x['Correlation'] > 0], key = lambda x: -x['Correlation'])
+    relevant = sorted([x for x in hdb if x['Correlation'] > 0], key = lambda x: -x['Correlation'], reverse=True)
     x = np.arange(len(relevant))
-    bars = plt.bar(x, list(map(lambda x: x['Correlation'], relevant)))
+
+    correlations = list(map(lambda x: x['Correlation'], relevant))
+    ticks = list(map(lambda x: "%s-%s" % (x['Start'][:-2], x['End'][:-2]), relevant))
+    fig, ax = plt.subplots()
+    rects = ax.bar(x, correlations, align="center", tick_label="")
+    autolabel(rects, ax, ticks)
+
     # TODO: find a more elegant solution for the label text
-    plt.xticks(x, list(map(lambda x: "%s-%s"%(x['Start'][:-2], x['End'][:-2]) , relevant)), rotation=90)
     plt.tight_layout()
-    plt.savefig("latency-criticality.png")
+    plt.savefig("latency-criticality.pdf")
     plt.close()
 
 
 
-
 def analyse(df, config):
     hb = []
     for event1 in df: