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