Commit 87ed00ce authored by Andreas Schmidt's avatar Andreas Schmidt

Move labels to bars in vertical graph.

parent fbf30046
......@@ -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:
......
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