Calculate Data Seriesopnfv-7.0.stable.RC2

Adds the min, max and actual slope values to the
final report metrics so that end users do not
have to calculate these values.

Change-Id: Ic98ec5cbfcdf7447d2bffc46e9bd05e087c72965
JIRA: STORPERF-257
Signed-off-by: mbeierl <mark.beierl@dell.com>

6 files changed, 145 insertions, 6 deletions

diff --git a/ci/verify.sh b/ci/verify.sh
index aedbf26..40e94b6 100755
--- a/ci/verify.sh
+++ b/ci/verify.sh
@@ -22,7 +22,6 @@ pip install --upgrade setuptools
 pip install autoflake==1.2
 pip install autopep8==1.3.5
 pip install coverage==4.5.1
-#pip install cryptography
 pip install flake8==3.5.0
 pip install mock==2.0.0
 pip install nose==1.3.7
diff --git a/docker/storperf-master/storperf/utilities/data_handler.py b/docker/storperf-master/storperf/utilities/data_handler.py
index c7d70a7..cb662f5 100644
--- a/docker/storperf-master/storperf/utilities/data_handler.py
+++ b/docker/storperf-master/storperf/utilities/data_handler.py
@@ -59,6 +59,8 @@ class DataHandler(object):
 
                     metrics[metric][io_type]['series'] = series
                     metrics[metric][io_type]['steady_state'] = steady
+                    metrics[metric][io_type]['series_slope'] = \
+                        math.slope_series(series)
                     treated_data = DataTreatment.data_treatment(series)
 
                     metrics[metric][io_type]['slope'] = \
@@ -68,6 +70,11 @@ class DataHandler(object):
                     average = math.average(treated_data['average_data'])
                     metrics[metric][io_type]['average'] = average
 
+                    metrics[metric][io_type]['series_min'] = \
+                        math.min_series(treated_data['range_data'])
+                    metrics[metric][io_type]['series_max'] = \
+                        math.max_series(treated_data['range_data'])
+
                     metrics_key = '%s.%s.%s' % (workload, io_type, metric)
                     executor.metadata['details']['metrics'][metrics_key] = \
                         average
diff --git a/docker/storperf-master/storperf/utilities/math.py b/docker/storperf-master/storperf/utilities/math.py
index 8e04134..2e78c9d 100644
--- a/docker/storperf-master/storperf/utilities/math.py
+++ b/docker/storperf-master/storperf/utilities/math.py
@@ -8,6 +8,9 @@
 ##############################################################################
 import copy
 
+RANGE_DEVIATION = 0.20
+SLOPE_DEVIATION = 0.10
+
 
 def slope(data_series):
     """
@@ -114,3 +117,58 @@ def average(data_series):
         average = data_sum / float(m)
 
     return average
+
+
+def slope_series(data_series):
+    """
+    This function returns an adjusted series based on the average
+    for the supplied series and the slope of the series.
+    """
+
+    new_series = []
+    average_series = []
+    for l in data_series:
+        average_series.append(l[1])
+
+    avg = average(average_series)
+    slp = slope(data_series)
+
+    multiplier = float(len(data_series) + 1) / 2.0 - len(data_series)
+    for index, _ in data_series:
+        new_value = avg + (slp * multiplier)
+        new_series.append([index, new_value])
+        multiplier += 1
+
+    return new_series
+
+
+def min_series(data_series):
+    """
+    This function returns an copy of the series with only the
+    minimum allowed deviation as its values
+    """
+
+    new_series = []
+    avg = average(data_series)
+    low = avg - (avg * RANGE_DEVIATION)
+
+    for _ in data_series:
+        new_series.append(low)
+
+    return new_series
+
+
+def max_series(data_series):
+    """
+    This function returns an copy of the series with only the
+    maximum allowed deviation as its values
+    """
+
+    new_series = []
+    avg = average(data_series)
+    high = avg + (avg * RANGE_DEVIATION)
+
+    for _ in data_series:
+        new_series.append(high)
+
+    return new_series
diff --git a/docker/storperf-master/storperf/utilities/steady_state.py b/docker/storperf-master/storperf/utilities/steady_state.py
index 13f609d..23a74d7 100644
--- a/docker/storperf-master/storperf/utilities/steady_state.py
+++ b/docker/storperf-master/storperf/utilities/steady_state.py
@@ -9,7 +9,8 @@
 import logging
 
 from storperf.utilities import data_treatment as DataTreatment
-from storperf.utilities import math as math
+from storperf.utilities import math
+from storperf.utilities.math import RANGE_DEVIATION, SLOPE_DEVIATION
 
 
 def steady_state(data_series):
@@ -38,15 +39,19 @@ def steady_state(data_series):
             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)
+        range_condition = abs(range_value) <= RANGE_DEVIATION * \
+            abs(average_value)
+        slope_condition = abs(slope_value) <= SLOPE_DEVIATION * \
+            abs(average_value)
 
         steady_state = range_condition and slope_condition
 
         logger.debug("Range %s <= %s?" % (abs(range_value),
-                                          (0.20 * abs(average_value))))
+                                          (RANGE_DEVIATION *
+                                           abs(average_value))))
         logger.debug("Slope %s <= %s?" % (abs(slope_value),
-                                          (0.10 * abs(average_value))))
+                                          (SLOPE_DEVIATION *
+                                           abs(average_value))))
         logger.debug("Steady State? %s" % steady_state)
     else:
         steady_state = False
diff --git a/docker/storperf-master/tests/utilities_tests/math_range_test.py b/docker/storperf-master/tests/utilities_tests/math_range_test.py
index 90519e7..9208fb7 100644
--- a/docker/storperf-master/tests/utilities_tests/math_range_test.py
+++ b/docker/storperf-master/tests/utilities_tests/math_range_test.py
@@ -118,3 +118,25 @@ class MathRangeTest(unittest.TestCase):
             data_series.insert(randrange(len(data_series)), -18954.98)
             actual = Range.range_value(data_series)
             self.assertEqual(expected, actual)
+
+    def test_min_series(self):
+        expected = [427.7333333333333,
+                    427.7333333333333,
+                    427.7333333333333,
+                    427.7333333333333,
+                    427.7333333333333,
+                    427.7333333333333]
+        data_series = [5, 351, 847, 2, 1985, 18]
+        actual = Range.min_series(data_series)
+        self.assertEqual(expected, actual)
+
+    def test_max_series(self):
+        expected = [641.5999999999999,
+                    641.5999999999999,
+                    641.5999999999999,
+                    641.5999999999999,
+                    641.5999999999999,
+                    641.5999999999999]
+        data_series = [5, 351, 847, 2, 1985, 18]
+        actual = Range.max_series(data_series)
+        self.assertEqual(expected, actual)
diff --git a/docker/storperf-master/tests/utilities_tests/math_slope_series_test.py b/docker/storperf-master/tests/utilities_tests/math_slope_series_test.py
new file mode 100644
index 0000000..cfa6efe
--- /dev/null
+++ b/docker/storperf-master/tests/utilities_tests/math_slope_series_test.py
@@ -0,0 +1,48 @@
+##############################################################################
+# 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 unittest
+from storperf.utilities import math
+
+
+class MathSlopeSeriesTest(unittest.TestCase):
+
+    def setUp(self):
+        unittest.TestCase.setUp(self)
+        pass
+
+    def test_slope_empty_series(self):
+        expected = []
+        actual = math.slope_series([])
+        self.assertEqual(expected, actual)
+
+    def test_slope_integer_series(self):
+        expected = [[1, 4.9], [2, 6.3], [3, 7.7], [4, 9.1]]
+        actual = math.slope_series([[1, 6], [2, 5], [3, 7], [4, 10]])
+        self.assertEqual(expected, actual)
+
+    def test_slope_mix_series(self):
+        expected = [[1, 4.9], [2, 6.3], [3, 7.7], [4, 9.1]]
+        actual = math.slope_series([[1.0, 6], [2, 5.0], [3, 7], [4.0, 10]])
+        self.assertEqual(expected, actual)
+
+    def test_slope_0_in_y(self):
+        expected = [
+            [15.5, 0.8333333333333333],
+            [16.5, 0.3333333333333333],
+            [17.5, -0.16666666666666669]]
+        actual = math.slope_series([[15.5, 1], [16.5, 0], [17.5, 0]])
+        self.assertEqual(expected, actual)
+
+    def test_slope_gaps_in_x(self):
+        expected = [
+            [1, 1.3571428571428572],
+            [2, 2.0],
+            [4, 2.642857142857143]]
+        actual = math.slope_series([[1, 1], [2, 2], [4, 3]])
+        self.assertEqual(expected, actual)