| # Copyright 2015-2016 ARM Limited |
| # |
| # Licensed under the Apache License, Version 2.0 (the "License"); |
| # you may not use this file except in compliance with the License. |
| # You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| # |
| |
| from bart.common import Utils |
| from bart.common.Analyzer import Analyzer |
| import unittest |
| import pandas as pd |
| import trappy |
| |
| |
| class TestCommonUtils(unittest.TestCase): |
| |
| def __init__(self, *args, **kwargs): |
| super(TestCommonUtils, self).__init__(*args, **kwargs) |
| |
| def test_interval_sum(self): |
| """Test Utils Function: interval_sum""" |
| |
| # A series with a non uniform index |
| # Refer to the example illustrations in the |
| # the interval sum docs-strings which explains |
| # the difference between step-post and ste-pre |
| # calculations |
| values = [0, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1] |
| index = [0, 1, 2, 3, 4, 5, 8, 9, 10, 11, 12] |
| series = pd.Series(values, index=index) |
| |
| self.assertEqual(Utils.interval_sum(series, 1, step="post"), 8) |
| self.assertEqual(Utils.interval_sum(series, 1, step="pre"), 7) |
| |
| # check left boundary |
| array = [1, 1, 0, 0] |
| series = pd.Series(array) |
| |
| self.assertEqual(Utils.interval_sum(series, 1, step="post"), 2) |
| self.assertEqual(Utils.interval_sum(series, 1, step="pre"), 1) |
| |
| # check right boundary |
| array = [0, 0, 1, 1] |
| series = pd.Series(array) |
| |
| self.assertEqual(Utils.interval_sum(series, 1, step="post"), 1) |
| self.assertEqual(Utils.interval_sum(series, 1, step="pre"), 2) |
| |
| array = [False, False, True, True, True, True, False, False] |
| series = pd.Series(array) |
| self.assertEqual(Utils.interval_sum(series), 4) |
| |
| def test_area_under_curve(self): |
| """Test Utils function: area_under_curve""" |
| |
| array = [0, 0, 2, 2, 2, 1, 1, 1] |
| series = pd.Series(array) |
| |
| # Area under curve post stepping |
| self.assertEqual( |
| Utils.area_under_curve( |
| series, |
| method="rect", |
| step="post"), |
| 8) |
| |
| # Area under curve pre stepping |
| self.assertEqual( |
| Utils.area_under_curve( |
| series, |
| method="rect", |
| step="pre"), |
| 9) |
| |
| array = [1] |
| series = pd.Series(array) |
| |
| # Area under curve post stepping, edge case |
| self.assertEqual( |
| Utils.area_under_curve( |
| series, |
| method="rect", |
| step="post"), |
| 0) |
| |
| # Area under curve pre stepping, edge case |
| self.assertEqual( |
| Utils.area_under_curve( |
| series, |
| method="rect", |
| step="pre"), |
| 0) |
| |
| |
| class TestAnalyzer(unittest.TestCase): |
| |
| def test_assert_statement_bool(self): |
| """Check that asssertStatement() works with a simple boolean case""" |
| |
| rolls_dfr = pd.DataFrame({"results": [1, 3, 2, 6, 2, 4]}) |
| trace = trappy.BareTrace() |
| trace.add_parsed_event("dice_rolls", rolls_dfr) |
| config = {"MAX_DICE_NUMBER": 6} |
| |
| t = Analyzer(trace, config) |
| statement = "numpy.max(dice_rolls:results) <= MAX_DICE_NUMBER" |
| self.assertTrue(t.assertStatement(statement, select=0)) |
| |
| def test_assert_statement_dataframe(self): |
| """assertStatement() works if the generated statement creates a pandas.DataFrame of bools""" |
| |
| rolls_dfr = pd.DataFrame({"results": [1, 3, 2, 6, 2, 4]}) |
| trace = trappy.BareTrace() |
| trace.add_parsed_event("dice_rolls", rolls_dfr) |
| config = {"MIN_DICE_NUMBER": 1, "MAX_DICE_NUMBER": 6} |
| t = Analyzer(trace, config) |
| |
| statement = "(dice_rolls:results <= MAX_DICE_NUMBER) & (dice_rolls:results >= MIN_DICE_NUMBER)" |
| self.assertTrue(t.assertStatement(statement)) |
| |
| statement = "dice_rolls:results == 3" |
| self.assertFalse(t.assertStatement(statement)) |