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Diffstat (limited to 'storperf/utilities/steady_state.py')
| -rw-r--r-- | storperf/utilities/steady_state.py | 45 |
1 files changed, 45 insertions, 0 deletions
diff --git a/storperf/utilities/steady_state.py b/storperf/utilities/steady_state.py new file mode 100644 index 0000000..8bfcb93 --- /dev/null +++ b/storperf/utilities/steady_state.py @@ -0,0 +1,45 @@ +############################################################################## +# Copyright (c) 2016 CENGN and others. +# +# All rights reserved. This program and the accompanying materials +# are made available under the terms of the Apache License, Version 2.0 +# which accompanies this distribution, and is available at +# http://www.apache.org/licenses/LICENSE-2.0 +############################################################################## +from storperf.utilities import data_treatment as DataTreatment +from storperf.utilities import math as math + + +def steady_state(data_series): + """ + This function seeks to detect steady state given on a measurement + window given the data series of that measurement window following + the pattern : [[x1,y1], [x2,y2], ..., [xm,ym]]. m represents the number + of points recorded in the measurement window, x which represents the + time, and y which represents the Volume performance variable being + tested e.g. IOPS, latency... + The function returns a boolean describing wether or not steady state + has been reached with the data that is passed to it. + """ + + # Pre conditioning the data to match the algorithms + treated_data = DataTreatment.data_treatment(data_series) + + # Calculating useful values invoking dedicated functions + slope_value = math.slope(treated_data['slope_data']) + range_value = math.range_value(treated_data['range_data']) + average_value = math.average(treated_data['average_data']) + + if (slope_value is not None and range_value is not None and + average_value is not None): + # Verification of the Steady State conditions following the SNIA + # definition + range_condition = range_value < 0.20 * abs(average_value) + slope_condition = slope_value < 0.10 * abs(average_value) + + steady_state = range_condition and slope_condition + + else: + steady_state = False + + return steady_state |