Change all paths

Changes the paths of all source code so that it exists under the dockerfile location
for each container.  This way we can use COPY instead of git clone, as well as use the
existing JJB.

Change-Id: I883b2957d89659c164fff0a1ebc4d677c534796d
JIRA: STORPERF-188
Signed-off-by: mbeierl <mark.beierl@dell.com>

1 files changed, 0 insertions, 54 deletions

diff --git a/storperf/utilities/steady_state.py b/storperf/utilities/steady_state.py
deleted file mode 100644
index 13f609d..0000000
--- a/storperf/utilities/steady_state.py
+++ /dev/null
@@ -1,54 +0,0 @@
-##############################################################################
-# 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
-##############################################################################
-import logging
-
-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.
-    """
-
-    logger = logging.getLogger('storperf.utilities.steady_state')
-
-    # 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 = abs(range_value) <= 0.20 * abs(average_value)
-        slope_condition = abs(slope_value) <= 0.10 * abs(average_value)
-
-        steady_state = range_condition and slope_condition
-
-        logger.debug("Range %s <= %s?" % (abs(range_value),
-                                          (0.20 * abs(average_value))))
-        logger.debug("Slope %s <= %s?" % (abs(slope_value),
-                                          (0.10 * abs(average_value))))
-        logger.debug("Steady State? %s" % steady_state)
-    else:
-        steady_state = False
-
-    return steady_state