[RFC,v2,6/6] kernel-shark: Add basic example demonstrating the NumPy interface

Commit Message

Yordan Karadzhov April 5, 2019, 10:14 a.m. UTC

The example script plots the distribution (histogram) of the pulseaudio
wake-up times and finds the biggest latency. The script also generates
a KernelShark session descriptor file (JSON). The session descriptor file
can be used by the KernelSherk GUI to open a session which will directly
visualize the largest wake-up latency.

Signed-off-by: Yordan Karadzhov <[e-mail]>
---
 kernel-shark/bin/sched_wakeup.py | 106 +++++++++++++++++++++++++++++++
 1 file changed, 106 insertions(+)
 create mode 100755 kernel-shark/bin/sched_wakeup.py

Patch

diff --git a/kernel-shark/bin/sched_wakeup.py b/kernel-shark/bin/sched_wakeup.py
new file mode 100755
index 0000000..8e2cfc1
--- /dev/null
+++ b/kernel-shark/bin/sched_wakeup.py
@@ -0,0 +1,106 @@ 
+#!/usr/bin/env python3
+
+""" The license to be determined !!!!
+"""
+
+import json
+import sys
+
+import matplotlib.pyplot as plt
+import scipy.stats as st
+import numpy as np
+
+import ksharkpy as ks
+
+fname = str(sys.argv[1])
+
+ks.open_file(fname)
+
+# We do not need the Process Ids of the records.
+# Do not load the "pid" data.
+data = ks.load_data(pid_data=False)
+
+tasks = ks.get_tasks()
+task_pid = tasks['pulseaudio']
+
+# Get the Event Ids of the sched_switch and sched_waking events.
+ss_eid = ks.event_id('sched', 'sched_switch')
+w_eid = ks.event_id('sched', 'sched_waking')
+
+# Gey the size of the data.
+i = data['offset'].size
+
+dt = []
+delta_max = i_ss_max = i_sw_max = 0
+
+while i > 0:
+    i = i - 1
+    if data['event'][i] == ss_eid:
+        next_pid = ks.read_event_field(offset=data['offset'][i],
+                                       event_id=ss_eid,
+                                       field='next_pid')
+
+        if next_pid == task_pid:
+            time_ss = data['time'][i]
+            index_ss = i
+
+            while i > 0:
+                i = i - 1
+                if (data['event'][i] == w_eid):
+                    waking_pid = ks.read_event_field(offset=data['offset'][i],
+                                                     event_id=w_eid,
+                                                     field='pid')
+
+                    if waking_pid == task_pid:
+                        delta = (time_ss - data['time'][i]) / 1000.
+                        # print(delta)
+                        dt.append(delta)
+                        if delta > delta_max:
+                            print('lat. max: ', delta)
+                            i_ss_max = index_ss
+                            i_sw_max = i
+                            delta_max = delta
+
+                        break
+
+desc = st.describe(np.array(dt))
+print(desc)
+
+fig, ax = plt.subplots(nrows=1, ncols=1)
+fig.set_figheight(6)
+fig.set_figwidth(7)
+
+rect = fig.patch
+rect.set_facecolor('white')
+
+ax.set_xlabel('latency [$\mu$s]')
+plt.yscale('log')
+ax.hist(dt, bins=(200), histtype='step')
+plt.show()
+
+sname = 'sched.json'
+ks.new_session(fname, sname)
+
+with open(sname, 'r+') as s:
+    session = json.load(s)
+    session['TaskPlots'] = [task_pid]
+    session['CPUPlots'] = [
+        int(data['cpu'][i_sw_max]),
+        int(data['cpu'][i_ss_max])]
+
+    delta = data['time'][i_ss_max] - data['time'][i_sw_max]
+    tmin = int(data['time'][i_sw_max] - delta)
+    tmax = int(data['time'][i_ss_max] + delta)
+    session['Model']['range'] = [tmin, tmax]
+
+    session['Markers']['markA']['isSet'] = True
+    session['Markers']['markA']['row'] = int(i_sw_max)
+
+    session['Markers']['markB']['isSet'] = True
+    session['Markers']['markB']['row'] = int(i_ss_max)
+
+    session['ViewTop'] = int(i_sw_max) - 5
+
+    ks.save_session(session, s)
+
+ks.close()