def export_image(self, image_contents):
""" Write curves into a PNG image. """
if self.ydata:
# calculate and apply max range
all_ydata = []
map(all_ydata.extend, [ydata for ydata in self.ydata.values()])
plt.ylim(self.get_range(all_ydata))
# create plots for each series of data
for i, ((title, unit), ydata) in enumerate(self.ydata.items()):
# create X axis
xdata = [x for x in range(len(ydata))]
# get additional statistics
avg, rate, (a, b), dev = get_stats(ydata)
# plot the data
dataLine, = plt.plot(xdata, ydata, label=title)
plotColor = dataLine.get_color()
# plot the mean line
avg_data = [avg for _ in ydata]
meanLine, = plt.plot(xdata, avg_data, label='Mean: {:.2f}{}'.format(avg, unit), linestyle='--', color=plotColor)
if a is not None:
# plot the linear regression
plt.plot([xdata[0], xdata[-1]], [a * xdata[0] + b, a * xdata[-1] + b], linestyle=':', color=plotColor)
if dev is not None:
# plot the standard deviation
plt.fill_between(xdata, avg-dev, avg+dev, facecolor=plotColor, alpha=.3)
# create the legend
legend = plt.legend(handles=[dataLine, meanLine], loc=i+1, fontsize='small', fancybox=True, shadow=True)
# add the legend to the current axes
plt.gca().add_artist(legend)
# save image to internal memory buffer
plt.savefig(image_contents.new_image(), dpi=80, bbox_inches='tight', format='png')
# reset yData
self.ydata = {}
# close plot
plt.close()
def write_network_statistics(self, root, io_stats):
""" Rendering of the network statistics. """
if not HostAddressView.interface_stats:
# choose first interface name by default
address_stats = self.get_address_stats()
io_stats = address_stats.io
HostAddressView.interface_stats = next(iter(io_stats.keys()))
# display io statistics
flatten_io_stats = [(intf, lst) for intf, lsts in io_stats.items() for lst in lsts]
iterator = root.findmeld('intf_tr_mid').repeat(flatten_io_stats)
rowspan, shaded_tr = True, False
for tr_element, (intf, single_io_stats) in iterator:
selected_tr = False
# set interface cell rowspan
elt = tr_element.findmeld('intf_td_mid')
if rowspan:
elt.attrib['rowspan'] = "2"
# set interface name
elt = elt.findmeld('intf_a_mid')
if HostAddressView.interface_stats == intf:
selected_tr = True
elt.attrib['class'] = 'button off active'
else:
elt.attributes(href='{}?intf={}'.format(HostAddressView.page_name, intf))
elt.content(intf)
else:
if HostAddressView.interface_stats == intf:
selected_tr = True
elt.replace('')
# set interface direction
elt = tr_element.findmeld('intfrxtx_td_mid')
elt.content('Rx' if rowspan else 'Tx')
if len(single_io_stats) > 0:
avg, rate, (a, b), dev = get_stats(single_io_stats)
# set last value
elt = tr_element.findmeld('intfval_td_mid')
if rate is not None:
self.set_slope_class(elt, rate)
elt.content('{:.2f}'.format(single_io_stats[-1]))
# set mean value
elt = tr_element.findmeld('intfavg_td_mid')
elt.content('{:.2f}'.format(avg))
if a is not None:
# set slope of linear regression
elt = tr_element.findmeld('intfslope_td_mid')
elt.content('{:.2f}'.format(a))
if dev is not None:
# set standard deviation
elt = tr_element.findmeld('intfdev_td_mid')
elt.content('{:.2f}'.format(dev))
if selected_tr:
tr_element.attrib['class'] = 'selected'
elif shaded_tr:
tr_element.attrib['class'] = 'shaded'
if not rowspan:
shaded_tr = not shaded_tr
rowspan = not rowspan
def test_statistics(self):
""" Test the statistics function. """
from supvisors.utils import get_stats
ydata = [2, 3, 4, 5, 6]
avg, rate, (a, b), dev = get_stats(ydata)
self.assertAlmostEqual(4, avg)
self.assertAlmostEqual(20, rate)
self.assertAlmostEqual(1, a)
self.assertAlmostEqual(2, b)
self.assertAlmostEqual(math.sqrt(2), dev)
def test_statistics(self):
""" Test the statistics function. """
from supvisors.utils import get_stats
ydata = [2, 3, 4, 5, 6]
avg, rate, (a, b), dev = get_stats(ydata)
self.assertAlmostEqual(4, avg)
self.assertAlmostEqual(20, rate)
self.assertAlmostEqual(1, a)
self.assertAlmostEqual(2, b)
self.assertAlmostEqual(math.sqrt(2), dev)
def write_memory_statistics(self, root, mem_stats):
""" Rendering of the memory statistics. """
if len(mem_stats) > 0:
# get additional statistics
avg, rate, (a, b), dev = get_stats(mem_stats)
# set last value
elt = root.findmeld('memval_td_mid')
if rate is not None:
self.set_slope_class(elt, rate)
elt.content('{:.2f}'.format(mem_stats[-1]))
# set mean value
elt = root.findmeld('memavg_td_mid')
elt.content('{:.2f}'.format(avg))
if a is not None:
# set slope of linear regression
elt = root.findmeld('memslope_td_mid')
elt.content('{:.2f}'.format(a))
if dev is not None:
# set standard deviation
elt = root.findmeld('memdev_td_mid')
elt.content('{:.2f}'.format(dev))
def write_processor_statistics(self, root, cpu_stats):
""" Rendering of the processor statistics. """
iterator = root.findmeld('cpu_tr_mid').repeat(cpu_stats)
shaded_tr = False
for idx, (tr_element, single_cpu_stats) in enumerate(iterator):
selected_tr = False
# set CPU id
elt = tr_element.findmeld('cpunum_a_mid')
if HostAddressView.cpu_id_stats == idx:
selected_tr = True
elt.attrib['class'] = 'button off active'
else:
elt.attributes(href='{}?idx={}'.format(HostAddressView.page_name, idx))
elt.content('cpu#{}'.format(idx-1 if idx > 0 else 'all'))
if len(single_cpu_stats) > 0:
avg, rate, (a, b), dev = get_stats(single_cpu_stats)
# set last value with instant slope
elt = tr_element.findmeld('cpuval_td_mid')
if rate is not None:
self.set_slope_class(elt, rate)
elt.content('{:.2f}'.format(single_cpu_stats[-1]))
# set mean value
elt = tr_element.findmeld('cpuavg_td_mid')
elt.content('{:.2f}'.format(avg))
if a is not None:
# set slope of linear regression
elt = tr_element.findmeld('cpuslope_td_mid')
elt.content('{:.2f}'.format(a))
if dev is not None:
# set standard deviation
elt = tr_element.findmeld('cpudev_td_mid')
elt.content('{:.2f}'.format(dev))
if selected_tr:
tr_element.attrib['class'] = 'selected'
elif shaded_tr:
tr_element.attrib['class'] = 'shaded'
shaded_tr = not shaded_tr
def write_process_statistics(self, root):
""" Display detailed statistics about the selected process. """
stats_elt = root.findmeld('pstats_div_mid')
# get data from statistics module iaw period selection
if ViewHandler.namespec_stats:
nbcores, proc_stats = self.get_process_stats(
ViewHandler.namespec_stats)
if proc_stats and (len(proc_stats[0]) > 0 or \
len(proc_stats[1]) > 0):
# set titles
elt = stats_elt.findmeld('process_h_mid')
elt.content(ViewHandler.namespec_stats)
# set CPU statistics
if len(proc_stats[0]) > 0:
avg, rate, (a, b), dev = get_stats(proc_stats[0])
# print last CPU value of process
elt = stats_elt.findmeld('pcpuval_td_mid')
if rate is not None:
self.set_slope_class(elt, rate)
cpuvalue = proc_stats[0][-1]
if not self.supvisors.options.stats_irix_mode:
cpuvalue /= nbcores
elt.content('{:.2f}%'.format(cpuvalue))
# set mean value
elt = stats_elt.findmeld('pcpuavg_td_mid')
elt.content('{:.2f}'.format(avg))
if a is not None:
# set slope value between last 2 values
elt = stats_elt.findmeld('pcpuslope_td_mid')
elt.content('{:.2f}'.format(a))
if dev is not None:
# set standard deviation
elt = stats_elt.findmeld('pcpudev_td_mid')
elt.content('{:.2f}'.format(dev))
# set MEM statistics
if len(proc_stats[1]) > 0:
avg, rate, (a, b), dev = get_stats(proc_stats[1])
# print last MEM value of process
elt = stats_elt.findmeld('pmemval_td_mid')
if rate is not None:
self.set_slope_class(elt, rate)
elt.content('{:.2f}%'.format(proc_stats[1][-1]))
# set mean value
elt = stats_elt.findmeld('pmemavg_td_mid')
elt.content('{:.2f}'.format(avg))
if a is not None:
# set slope value between last 2 values
elt = stats_elt.findmeld('pmemslope_td_mid')
elt.content('{:.2f}'.format(a))
if dev is not None:
# set standard deviation
elt = stats_elt.findmeld('pmemdev_td_mid')
elt.content('{:.2f}'.format(dev))
# write CPU / Memory plots
try:
from supvisors.plot import StatisticsPlot
# build CPU image
cpu_img = StatisticsPlot()
cpu_img.add_plot('CPU', '%', proc_stats[0])
cpu_img.export_image(process_cpu_image)
# build Memory image
mem_img = StatisticsPlot()
mem_img.add_plot('MEM', '%', proc_stats[1])
mem_img.export_image(process_mem_image)
except ImportError:
self.logger.warn("matplotlib module not found")
else:
if ViewHandler.namespec_stats:
self.logger.warn(
'unselect Process Statistics for {}'.format(
ViewHandler.namespec_stats))
ViewHandler.namespec_stats = ''
# remove stats part if empty
if not ViewHandler.namespec_stats:
stats_elt.replace('')
def write_process_statistics(self, root):
""" Display detailed statistics about the selected process. """
stats_elt = root.findmeld('pstats_div_mid')
# get data from statistics module iaw period selection
if ViewHandler.namespec_stats:
nbcores, proc_stats = self.get_process_stats(
ViewHandler.namespec_stats)
if proc_stats and (len(proc_stats[0]) > 0 or \
len(proc_stats[1]) > 0):
# set titles
elt = stats_elt.findmeld('process_h_mid')
elt.content(ViewHandler.namespec_stats)
# set CPU statistics
if len(proc_stats[0]) > 0:
avg, rate, (a, b), dev = get_stats(proc_stats[0])
# print last CPU value of process
elt = stats_elt.findmeld('pcpuval_td_mid')
if rate is not None:
self.set_slope_class(elt, rate)
cpuvalue = proc_stats[0][-1]
if not self.supvisors.options.stats_irix_mode:
cpuvalue /= nbcores
elt.content('{:.2f}%'.format(cpuvalue))
# set mean value
elt = stats_elt.findmeld('pcpuavg_td_mid')
elt.content('{:.2f}'.format(avg))
if a is not None:
# set slope value between last 2 values
elt = stats_elt.findmeld('pcpuslope_td_mid')
elt.content('{:.2f}'.format(a))
if dev is not None:
# set standard deviation
elt = stats_elt.findmeld('pcpudev_td_mid')
elt.content('{:.2f}'.format(dev))
# set MEM statistics
if len(proc_stats[1]) > 0:
avg, rate, (a, b), dev = get_stats(proc_stats[1])
# print last MEM value of process
elt = stats_elt.findmeld('pmemval_td_mid')
if rate is not None:
self.set_slope_class(elt, rate)
elt.content('{:.2f}%'.format(proc_stats[1][-1]))
# set mean value
elt = stats_elt.findmeld('pmemavg_td_mid')
elt.content('{:.2f}'.format(avg))
if a is not None:
# set slope value between last 2 values
elt = stats_elt.findmeld('pmemslope_td_mid')
elt.content('{:.2f}'.format(a))
if dev is not None:
# set standard deviation
elt = stats_elt.findmeld('pmemdev_td_mid')
elt.content('{:.2f}'.format(dev))
# write CPU / Memory plots
try:
from supvisors.plot import StatisticsPlot
# build CPU image
cpu_img = StatisticsPlot()
cpu_img.add_plot('CPU', '%', proc_stats[0])
cpu_img.export_image(process_cpu_image)
# build Memory image
mem_img = StatisticsPlot()
mem_img.add_plot('MEM', '%', proc_stats[1])
mem_img.export_image(process_mem_image)
except ImportError:
self.logger.warn("matplotlib module not found")
else:
if ViewHandler.namespec_stats:
self.logger.warn('unselect Process Statistics for {}'
.format(ViewHandler.namespec_stats))
ViewHandler.namespec_stats = ''
# remove stats part if empty
if not ViewHandler.namespec_stats:
stats_elt.replace('')
