Commit 67940376 authored by Daniel Seybold's avatar Daniel Seybold

minor fix to availability phases plot, now storing as well dataframes of phases

parent 70c1ca71
Pipeline #53767 passed with stage
in 45 minutes and 20 seconds
......@@ -130,7 +130,7 @@ def plot_availability_timeseries(inputPath, df,workloadPhase):
#recovery avg
recoveryAvg = calculate_phase_average(extractedTimeseriesData,df.loc[index,'RecoveryDBMSStart'],df.loc[index,'RecoveryDBMSEnd'])
plt.hlines(y=unhealthyAvg, xmin=df.loc[index,'RecoveryDBMSStart'], xmax=df.loc[index,'RecoveryDBMSEnd'], color='orange', linestyles='dashed', zorder=3, label='recovery avg.')
plt.hlines(y=recoveryAvg, xmin=df.loc[index,'RecoveryDBMSStart'], xmax=df.loc[index,'RecoveryDBMSEnd'], color='orange', linestyles='dashed', zorder=3, label='recovery avg.')
#healthy avg
if (index + 1) == len(df.index):
healtyAvg = calculate_phase_average(extractedTimeseriesData,df.loc[index,'RecoveryDBMSEnd'],evaluationEnd)
......@@ -148,6 +148,10 @@ def plot_availability_timeseries(inputPath, df,workloadPhase):
print("saving throughput plot to disk: " + outputFile)
plt.savefig(outputFile)
outputDataframe = inputPath + plotting_config.TIMESERiES_FOLDER + "phases-dataframe"
print("saving phases dataframe to disk: " + outputDataframe)
df.to_pickle(outputDataframe)
def plot_throughput_timeseries(inputPath, scaleOutStart, scaleOutEnd):
......
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