def do_action(args, pair):
"""
I need to generate appropriate content here.
"""
(x, y) = pair
fig = plt.figure()
ax = fig.add_subplot(111)
Graph.scatter(ax, x, y, 'b', label="just a dumb scatter plot")
plt.xlabel('x')
plt.ylabel(r'y')
plt.title('x versus y')
if args.plot == None:
plt.show()
else:
plt.savefig(args.plot)
def do_xcorr(mds, plot=None, ybound=None, hilite="open"):
if mds.CPU is None:
print "mds.do_xcorr(): Error - There is no CPU utilization data for %s" % mds.name
return
if mds.MDS is None:
print "mds.do_xcorr(): Error - There is no data for %s" % mds.name
return
if ybound is None:
ybound = mds.MDS.getMax()
fig = plt.figure()
ax = fig.add_subplot(111)
Graph.scatter(ax, mds.CPU.Values, mds.MDS.Values, 'b', label="mds ops")
if not hilite is None:
n = 0
op_index = None
for op in mds.Ops:
#print "mds.do_xcorr(): Debug - op name = %s, hilite = %s" % (op.name, hilite)
if ((op.Values is None) or (op.Steps is None) or
(op.Steps.steps() == 0) or (op.Stats is None)):
continue
if op.name == hilite:
op_index = n
n += 1
if n > 0:
# mds.x is teh result of a generalized linear regression apporioning
# the fraction of CPU utilization to each operation. x[n] is the
# final category, of "no operation".
if mds.x is None:
mds.attribute()
if (not op_index is None) and (mds.x[op_index] != 0.0):
slope = (100 - mds.x[n])/(100*mds.x[op_index])
model_x = np.array(range(101))
model_y = mds.x[n]/100.0 + slope*model_x
#print "hilite = %s, op_index = %d, y(0) = %f, y(1) = %f" % (hilite, op_index, model_y[0], model_y[99])
ax.plot(model_x, model_y, "r-", label=hilite)
else:
print "mds.do_xcorr(): Warning - No ops with data for regression"
ax.set_xbound(lower = 0, upper = 100)
ax.set_ybound(lower = 0, upper = ybound)
ax.legend()
plt.title("%s activity vs %%CPU" % mds.name)
ax.set_xlabel(r"$\%$ CPU")
ax.set_ylabel(r"$ops/sec$")
if plot is None:
plt.show()
else:
plt.savefig(plot)
plt.cla()
def do_xcorr(B, mode=None, plot=None, ybound=None, scale=1024*1024):
"""
The scatter plot of the aggregate I/O rates versus average CPU utilization
is less illumination than the composite of all the individual OSS scatter
plots. I don't call on this one, but it is still here and available.
"""
if not ((mode == 'Read') or (mode == 'Write') or (mode == 'Both') or (mode is None)):
print "bulk.do_xcorr: Error - Unrecognized mode %s" % mode
return
if B.CPU is None:
print "bulk.do_xcorr(): Error - There is no CPU utilization data for %s" % B.name
return
if ((B.Read is None) or (B.Write is None) or (B.bulk is None)):
print "bulk.do_xcorr(): Error - There is no data"
return(None)
if ybound is None:
if mode == 'Read':
ymax = B.Read.getMax()/scale
elif mode == 'Write':
ymax = B.Write.getMax()/scale
elif mode == 'Both':
ymax = B.bulk.getMax()/scale
else:
readMax = B.Read.getMax()/scale
writeMax = B.Write.getMax()/scale
if readMax > writeMax:
ymax = readMax
else:
ymax = writeMax
ybound = ymax
fig = plt.figure()
ax = fig.add_subplot(111)
if (mode is None) or (mode == 'Read'):
Graph.scatter(ax, B.CPU.Values, B.Read.Values/scale, 'r', label="read")
if (mode is None) or (mode == 'Write'):
Graph.scatter(ax, B.CPU.Values, B.Write.Values/scale, 'b', label="write")
if mode == 'Both':
Graph.scatter(ax, B.CPU.Values, B.bulk.Values/scale, 'b', label="read+write")
ax.set_xbound(lower = 0, upper = 100)
ax.set_ybound(lower = 0, upper = ybound)
ax.legend()
dayStr = time.strftime("%Y-%m-%d", time.localtime(B.begin.sie))
plt.title("%s bulk %s activity vs %%CPU" % (dayStr, B.name))
ax.set_xlabel(r"$\%$ CPU")
ax.set_ylabel(r"$MB/sec$")
if plot is None:
plt.show()
else:
plt.savefig(plot)
def do_composite_xcorr(B, mode=None, plot=None, ybound=None, scale=1024.0*1024.0):
if ybound is None:
ymax = 0.0
for oss in B.OSSs:
if mode == 'Read':
ossMax = oss.Read.getMax()/scale
elif mode == 'Write':
ossMax = oss.Write.getMax()/scale
elif mode == 'Both':
ossMax = oss.OSS.getMax()/scale
else:
readMax = oss.Read.getMax()/scale
writeMax = oss.Write.getMax()/scale
if readMax > writeMax:
ossMax = readMax
else:
ossMax = writeMax
if ossMax > ymax:
ymax = ossMax
ybound = ymax
if ybound <= 0.0:
print "bulk.do_composite_xcorr(): Warning - Failed to determine y-scale"
return
fig = plt.figure()
ax = fig.add_subplot(111)
handles = None
labels = None
for oss in B.OSSs:
if (mode is None) or (mode == 'Read'):
Graph.scatter(ax, oss.CPU.Values, oss.Read.Values/scale, 'r', label='read')
if (mode is None) or (mode == 'Write'):
Graph.scatter(ax, oss.CPU.Values, oss.Write.Values/scale, 'b', label='write')
if mode == 'Both':
Graph.scatter(ax, oss.CPU.Values, oss.OSS.Values/scale, 'b', label='read+write')
if (handles is None) and (labels is None):
(handles, labels) = ax.get_legend_handles_labels()
plt.legend(handles, labels)
ax.set_xbound(lower = 0, upper = 100)
ax.set_ybound(lower = 0, upper = ybound)
dayStr = time.strftime("%Y-%m-%d", time.localtime(B.begin.sie))
plt.title("%s Composite %s OSS activity vs %%CPU" % (dayStr, B.name))
ax.set_xlabel(r"$\%$ CPU")
ax.set_ylabel(r"$MB/sec$")
if plot is None:
plt.show()
else:
plt.savefig(plot)
def do_xcorr(bulk, mode, plot, ymax=None, scale=1024*1024):
"""
"""
if not ((mode == 'Read') or (mode == 'Write') or (mode == 'Both') or (mode == None)):
print "bulk_quick.do_xcorr: Error - Unrecognized mode %s" % mode
return
if bulk.CPU == None:
print "bulk_quick.do_xcorr(): Error - There is no CPU utilization data for %s" % bulk.name
return
if ((bulk.Read == None) or (bulk.Write == None) or (bulk.Bulk == None)):
print "bulk_quick.do_xcorr(): Error - There is no data"
return(None)
if ymax == None:
if mode == 'Read':
ymax = bulk.Read.getMax()/scale
elif mode == 'Write':
ymax = bulk.Write.getMax()/scale
elif mode == 'Both':
ymax = bulk.Bulk.getMax()/scale
else:
readMax = bulk.Read.getMax()/scale
writeMax = bulk.Write.getMax()/scale
if readMax > writeMax:
ymax = readMax
else:
ymax = writeMax
fig = plt.figure()
ax = fig.add_subplot(111)
if (mode == None) or (mode == 'Read'):
Graph.scatter(ax, bulk.CPU.Values, bulk.Read.Values/scale, 'r', label="read")
if (mode == None) or (mode == 'Write'):
Graph.scatter(ax, bulk.CPU.Values, bulk.Write.Values/scale, 'b', label="write")
if mode == 'Both':
Graph.scatter(ax, bulk.CPU.Values, bulk.Bulk.Values/scale, 'b', label="read+write")
ax.set_xbound(lower = 0, upper = 100)
ax.set_ybound(lower = 0, upper = ymax)
ax.legend()
dayStr = time.strftime("%Y-%m-%d", time.localtime(bulk.begin.sie))
plt.title("%s Bulk %s activity vs \%CPU" % (dayStr, bulk.name))
ax.set_xlabel(r"$\%$ CPU")
ax.set_ylabel(r"$MB/sec$")
if plot == None:
plt.show()
else:
plt.savefig(plot)
def do_xcorr(oss, mode=None, plot=None, ybound=None, scale=1024.0*1024.0):
if not ((mode == 'Read') or (mode == 'Write') or (mode == 'Both') or (mode is None)):
print "oss.do_xcorr: Error - Unrecognized mode %s" % mode
return
if oss.CPU is None:
print "oss.do_xcorr(): Error - There is no CPU utilization data for %s" % oss.name
return
if ((oss.Read is None) or (oss.Write is None) or (oss.OSS is None)):
print "oss.do_xcorr(): Error - There is no data"
return(None)
if ybound is None:
if mode == 'Read':
ymax = oss.Read.getMax()/scale
elif mode == 'Write':
ymax = oss.Write.getMax()/scale
elif mode == 'Both':
ymax = oss.OSS.getMax()/scale
else:
readMax = oss.Read.getMax()/scale
writeMax = oss.Write.getMax()/scale
if readMax > writeMax:
ymax = readMax
else:
ymax = writeMax
ybound = ymax
fig = plt.figure()
ax = fig.add_subplot(111)
if (mode is None) or (mode == 'Read'):
Graph.scatter(ax, oss.CPU.Values, oss.Read.Values/scale, 'r', label="read")
if (mode is None) or (mode == 'Write'):
Graph.scatter(ax, oss.CPU.Values, oss.Write.Values/scale, 'b', label="write")
if mode == 'Both':
Graph.scatter(ax, oss.CPU.Values, oss.OSS.Values/scale, 'b', label="read+write")
ax.set_xbound(lower = 0, upper = 100)
ax.set_ybound(lower = 0, upper = ybound)
ax.legend()
dayStr = time.strftime("%Y-%m-%d", time.localtime(oss.begin.sie))
plt.title("%s OSS %s activity vs %%CPU" % (dayStr, oss.name))
ax.set_xlabel(r"$\%$ CPU")
ax.set_ylabel(r"$MB/sec$")
if plot is None:
plt.show()
else:
plt.savefig(plot)
