104 lines
3.2 KiB
Python
104 lines
3.2 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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import pandas as pd
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import trappy
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from utils_tests import TestBART
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from bart.common.signal import SignalCompare
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import numpy as np
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class TestSignalCompare(TestBART):
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def __init__(self, *args, **kwargs):
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super(TestSignalCompare, self).__init__(*args, **kwargs)
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def test_conditional_compare(self):
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"""Test conditional_compare"""
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# Refer to the example in
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# bart.common.signal.SignalCompare.conditional_compare
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# doc-strings which explains the calculation for the
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# data set below
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A = [0, 0, 0, 3, 3, 0, 0, 0]
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B = [0, 0, 2, 2, 2, 2, 1, 1]
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trace = trappy.BareTrace()
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df = pd.DataFrame({"A": A, "B": B})
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trace.add_parsed_event("event", df)
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s = SignalCompare(trace, "event:A", "event:B")
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expected = (1.5, 2.0 / 7)
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self.assertEqual(
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s.conditional_compare(
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"event:A > event:B",
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method="rect"),
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expected)
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def test_get_overshoot(self):
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"""Test get_overshoot"""
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A = [0, 0, 0, 3, 3, 0, 0, 0]
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B = [0, 0, 2, 2, 2, 2, 1, 1]
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trace = trappy.BareTrace()
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df = pd.DataFrame({"A": A, "B": B})
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trace.add_parsed_event("event", df)
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s = SignalCompare(trace, "event:A", "event:B")
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expected = (1.5, 2.0 / 7)
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self.assertEqual(
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s.get_overshoot(method="rect"),
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expected)
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A = [0, 0, 0, 1, 1, 0, 0, 0]
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B = [0, 0, 2, 2, 2, 2, 1, 1]
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df = pd.DataFrame({"A": A, "B": B})
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trace.event.data_frame = df
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s = SignalCompare(trace, "event:A", "event:B")
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expected = (float("nan"), 0.0)
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result = s.get_overshoot(method="rect")
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self.assertTrue(np.isnan(result[0]))
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self.assertEqual(result[1], expected[1])
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def test_get_undershoot(self):
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"""Test get_undershoot"""
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A = [0, 0, 0, 1, 1, 1, 1, 1]
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B = [2, 2, 2, 2, 2, 2, 2, 2]
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trace = trappy.BareTrace()
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df = pd.DataFrame({"A": A, "B": B})
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trace.add_parsed_event("event", df)
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s = SignalCompare(trace, "event:A", "event:B")
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expected = (4.0 / 14.0, 1.0)
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self.assertEqual(
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s.get_undershoot(method="rect"),
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expected)
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A = [3, 3, 3, 3, 3, 3, 3, 3]
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B = [2, 2, 2, 2, 2, 2, 1, 1]
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df = pd.DataFrame({"A": A, "B": B})
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trace.event.data_frame = df
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s = SignalCompare(trace, "event:A", "event:B")
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expected = (float("nan"), 0.0)
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result = s.get_undershoot(method="rect")
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self.assertTrue(np.isnan(result[0]))
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self.assertEqual(result[1], expected[1])
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