def test_generator():
# Test Data
plot1 = PlotData('test1.csv', 1, 'GC Commit', 'MB', None, 600, 1200,
'line')
plot2 = PlotData('test2.csv', 1, 'GC CMS Pause', 'seconds', None, 600,
1200, 'line')
plot3 = PlotData('test3.csv', 1, 'GC Promo', 'bps', None, 600, 1200,
'line')
plot4 = PlotData('test4.csv', 1, 'GC Promo', 'bps', None, 600, 1200,
'line')
plot5 = PlotData('test5.csv', 1, 'GC Promo', 'bps', None, 600, 1200,
'line')
yield plot, [plot1], 'test1', 'single plot with all valid csv', True
yield plot, [plot1, plot2], 'test2', 'dual plot with all valid csv', True
yield plot, [plot1, plot2,
plot3], 'test3', 'multi plot with all valid csv', True
yield plot, [plot4], 'test4', 'single plot with 1 empty csv', False
yield plot, [plot4, plot1], 'test5', 'dual plot with 1 empty csv', True
yield plot, [plot1, plot4,
plot3], 'test6', 'multi plot with 1 empty csv', True
yield plot, [plot5], 'test7', 'single plot with 1 non-existent csv', False
yield plot, [plot5,
plot1], 'test8', 'dual plot with 1 non-existent csv', True
yield plot, [plot1, plot5,
plot3], 'test9', 'multi plot with 1 non-existent csv', True
def nway_plotting(crossplots, metrics, output_directory, resource_path):
listlen = len(crossplots)
if listlen == 0:
return ''
i = 0
correlated_plots = []
#GC.appstop,all GC.alloc,GC.alloc-rate GC.promo,GC.gen0t,GC.gen0sys
while i < listlen:
plot = crossplots[i]
vals = plot.split(',')
i += 1
if not 'all' in vals:
plot_data = []
for val in vals:
csv_file = get_default_csv(output_directory, val)
plot_data.append(PlotData(input_csv=csv_file, csv_column=1, series_name=sanitize_string(val), y_label=sanitize_string(val), precision=None, graph_height=500, graph_width=1200, graph_type='line'))
png_name = get_merged_plot_link_name(vals)
graphed, div_file = Metric.graphing_modules['matplotlib'].graph_data(plot_data, output_directory, resource_path, png_name)
if graphed:
correlated_plots.append(div_file)
else:
vals.remove('all')
for metric in metrics:
for csv in metric.csv_files:
csv_filename = csv.split('/')[-1]
metric_name = '.'.join(csv_filename.split('.')[0:-1])
if metric_name in vals:
continue
new_val = []
new_val.extend(vals)
new_val.append(metric_name)
new_val_str = ','.join(new_val)
crossplots.append(new_val_str)
listlen += 1
return correlated_plots