def plot(tr_unit_prof_df, info_df, unit_info_df, pilot_info_df, sid):
print "Plotting %s ..." % sid
labels = []
# Legend info
info = info_df.loc[sid]
mpi = get_mpi(unit_info_df, sid)
#mpi = True
# For this call assume that there is only one pilot per session
lms = get_lm(unit_info_df, pilot_info_df, sid, mpi)
assert len(lms) == 1
launch_method = lms.values()[0]
# For this call assume that there is only one pilot per session
spawners = get_spawners(unit_info_df, pilot_info_df, sid)
assert len(spawners) == 1
spawner = spawners.values()[0]
# For this call assume that there is only one pilot per session
resources = get_resources(unit_info_df, pilot_info_df, sid)
assert len(resources) == 1
resource_label = resources.values()[0]
# Get only the entries for this session
uf = unit_info_df[unit_info_df['sid'] == sid]
result = pd.value_counts(uf['state'].values, sort=False)
print result
ax = result.plot(kind='pie', autopct='%.2f%%')
ax.set_aspect('equal')
print info
#mp.pyplot.legend(labels, loc='upper left', fontsize=5)
mp.pyplot.title("%s (%s)\n"
"%d CUs of %d core(s) with a %ds payload on a %d core pilot on %s.\n"
"%d sub-agent(s) with %d ExecWorker(s) each. All times are per CU.\n"
"RP: %s - RS: %s - RU: %s"
% (sid, time.strftime("%a, %d %b %Y %H:%M:%S +0000", time.gmtime(info['created'])),
info['metadata.cu_count'], info['metadata.cu_cores'], info['metadata.cu_runtime'], info['metadata.pilot_cores'], resource_label,
info['metadata.num_sub_agents'], info['metadata.num_exec_instances_per_sub_agent'],
info['metadata.radical_stack.rp'], info['metadata.radical_stack.rs'], info['metadata.radical_stack.ru']
), fontsize=8)
mp.pyplot.savefig('%s_plot_states.pdf' % sid)
mp.pyplot.close()
def plot(tr_unit_prof_df, info_df, unit_info_df, pilot_info_df, sid):
print "Plotting %s ..." % sid
labels = []
# Legend info
info = info_df.loc[sid]
mpi = get_mpi(unit_info_df, sid)
#mpi = True
# For this call assume that there is only one pilot per session
lms = get_lm(unit_info_df, pilot_info_df, sid, mpi)
assert len(lms) == 1
launch_method = lms.values()[0]
# For this call assume that there is only one pilot per session
spawners = get_spawners(unit_info_df, pilot_info_df, sid)
assert len(spawners) == 1
spawner = spawners.values()[0]
# For this call assume that there is only one pilot per session
resources = get_resources(unit_info_df, pilot_info_df, sid)
assert len(resources) == 1
resource_label = resources.values()[0]
# Get only the entries for this session
uf = unit_info_df[unit_info_df['sid'] == sid]
# Get only the entries for this session
tuf = tr_unit_prof_df[tr_unit_prof_df['sid'] == sid]
result = pd.value_counts(tuf['aec_complete'].notnull(), sort=False)
# result = pd.value_counts(uf['state'].values, sort=False)
print result
# Only take completed CUs into account
#tuf = tuf[tuf['Done'].notnull()]
#print tuf['aec_after_exec']
#print tuf['aec_complete']
#print 'c:', c
ax = result.plot(kind='pie', autopct='%.2f%%')
ax.set_aspect('equal')
print info
#mp.pyplot.legend(labels, loc='upper left', fontsize=5)
mp.pyplot.title(
"%s (%s)\n"
"%d CUs of %d core(s) with a %ds payload on a %d core pilot on %s.\n"
"%d sub-agent(s) with %d ExecWorker(s) each. All times are per CU.\n"
"RP: %s - RS: %s - RU: %s" %
(sid,
time.strftime("%a, %d %b %Y %H:%M:%S +0000",
time.gmtime(info['created'])),
info['metadata.cu_count'], info['metadata.cu_cores'],
info['metadata.cu_runtime'], info['metadata.pilot_cores'],
resource_label, info['metadata.num_sub_agents'],
info['metadata.num_exec_instances_per_sub_agent'],
info['metadata.radical_stack.rp'], info['metadata.radical_stack.rs'],
info['metadata.radical_stack.ru']),
fontsize=8)
mp.pyplot.savefig('%s_plot_states.pdf' % sid)
mp.pyplot.close()
def plot(tr_unit_prof_df, info_df, unit_info_df, pilot_info_df, sid):
print "Plotting %s ..." % sid
labels = []
# Legend info
info = info_df.loc[sid]
mpi = get_mpi(unit_info_df, sid)
#mpi = True
# For this call assume that there is only one pilot per session
lms = get_lm(unit_info_df, pilot_info_df, sid, mpi)
assert len(lms) == 1
launch_method = lms.values()[0]
# For this call assume that there is only one pilot per session
spawners = get_spawners(unit_info_df, pilot_info_df, sid)
assert len(spawners) == 1
spawner = spawners.values()[0]
#exit()
# For this call assume that there is only one pilot per session
resources = get_resources(unit_info_df, pilot_info_df, sid)
assert len(resources) == 1
resource_label = resources.values()[0]
# Get only the entries for this session
tuf = tr_unit_prof_df[tr_unit_prof_df['sid'] == sid]
tuf = tuf[tuf['Done'].notnull()]
# We sort the units based on the order ...
#tufs = tuf.sort('awo_get_u_pend') # they arrived at the agent
#tufs = tuf.sort('aec_work_u_pend') # they are picked up by an EW
tufs = tuf.sort('asc_put_u_pend') # they are scheduled
#tufs = tuf.sort('asc_get_u_pend') # the are picked up by the scheduler
ax = (tufs['asc_released'] - tufs['asc_allocated'] - info['metadata.cu_runtime']).plot(kind='line', color='red')
labels.append("Core Occupation overhead")
ax = (tufs['aec_after_exec'] - tufs['aec_after_cd'] - info['metadata.cu_runtime']).plot(kind='line', color='orange')
labels.append('%s LaunchMethod (%s)' % ('MPI' if mpi else 'Task', launch_method))
ax = (tufs['aec_start_script'] - tufs['aec_handover']).plot(kind='line', color='black')
labels.append("Spawner (%s)" % spawner)
(tufs['asc_get_u_pend'] - tufs['asic_put_u_pend']).plot(kind='line', color='blue')
labels.append("Scheduler Queue")
ax = (tufs['aec_work_u_pend'] - tufs['asc_put_u_pend']).plot(kind='line', color='green')
labels.append("ExecWorker Queue")
ax = (tufs['asc_released'] - tufs['aec_complete']).plot(kind='line', color='magenta')
labels.append("Postexec")
mp.pyplot.legend(labels, loc='upper left', fontsize=5)
mp.pyplot.title("%s (%s)\n"
"%d CUs of %d core(s) with a %ds payload on a %d core pilot on %s.\n"
"%d sub-agent(s) with %d ExecWorker(s) each. All times are per CU.\n"
"RP: %s - RS: %s - RU: %s"
% (sid, time.strftime("%a, %d %b %Y %H:%M:%S +0000", time.gmtime(info['created'])),
info['metadata.cu_count'], info['metadata.cu_cores'], info['metadata.cu_runtime'], info['metadata.pilot_cores'], resource_label,
info['metadata.num_sub_agents'], info['metadata.num_exec_instances_per_sub_agent'],
info['metadata.radical_stack.rp'], info['metadata.radical_stack.rs'], info['metadata.radical_stack.ru']
), fontsize=8)
mp.pyplot.xlabel("Compute Units (ordered by agent arrival)")
mp.pyplot.ylabel("Time (s)")
mp.pyplot.ylim(-0.01)
ax.get_xaxis().set_ticks([])
mp.pyplot.savefig('%s_plot1.pdf' % sid)
mp.pyplot.close()