134 lines
4.9 KiB
Python
134 lines
4.9 KiB
Python
# Copyright (c) 2021-2025 The University of Texas Southwestern Medical Center.
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# All rights reserved.
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted for academic and research use only
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# (subject to the limitations in the disclaimer below)
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# provided that the following conditions are met:
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# * Redistributions of source code must retain the above copyright notice,
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# this list of conditions and the following disclaimer.
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# * Redistributions in binary form must reproduce the above copyright
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# notice, this list of conditions and the following disclaimer in the
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# documentation and/or other materials provided with the distribution.
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# * Neither the name of the copyright holders nor the names of its
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# contributors may be used to endorse or promote products derived from this
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# software without specific prior written permission.
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# NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY
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# THIS LICENSE. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND
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# CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
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# PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
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# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
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# BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
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# IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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# POSSIBILITY OF SUCH DAMAGE.
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# Standard library imports
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# Third party imports
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import pytest
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# local imports
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from navigate.model.features.feature_related_functions import (
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convert_str_to_feature_list,
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convert_feature_list_to_str,
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)
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from navigate.model.features.common_features import (
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PrepareNextChannel,
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LoopByCount,
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ZStackAcquisition,
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)
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@pytest.mark.parametrize(
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"feature_list_str, expected_list",
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[
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("", None),
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("[]", []),
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("[{'name': PrepareNextChannel}]", [{"name": PrepareNextChannel}]),
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("[{'name': NonExistFeature}]", None),
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(
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"[({'name': PrepareNextChannel}, {'name': LoopByCount})]",
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[({"name": PrepareNextChannel}, {"name": LoopByCount})],
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),
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(
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"[({'name': PrepareNextChannel}, {'name': LoopByCount, 'args': (3,)})]",
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[({"name": PrepareNextChannel}, {"name": LoopByCount, "args": (3,)})],
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),
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(
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"[({'name': PrepareNextChannel}, {'name': LoopByCount, 'args': 3})]",
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[({"name": PrepareNextChannel}, {"name": LoopByCount, "args": (3,)})],
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),
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(
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"[({'name': PrepareNextChannel}, {'name': LoopByCount, 'args': (3)})]",
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[({"name": PrepareNextChannel}, {"name": LoopByCount, "args": (3,)})],
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),
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(
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"[(({'name': PrepareNextChannel}, {'name': LoopByCount, 'args': (3)}))]",
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[({"name": PrepareNextChannel}, {"name": LoopByCount, "args": (3,)})],
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),
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(
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"[{'name': ZStackAcquisition, 'args': (True, False, 'zstack',)}]",
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[
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{
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"name": ZStackAcquisition,
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"args": (
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True,
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False,
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"zstack",
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),
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}
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],
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),
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],
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)
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def test_convert_str_to_feature_list(feature_list_str, expected_list):
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feature_list = convert_str_to_feature_list(feature_list_str)
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assert feature_list == expected_list
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@pytest.mark.parametrize(
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"feature_list, expected_str",
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[
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(None, "[]"),
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([], "[]"),
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([{"name": PrepareNextChannel}], '[{"name": PrepareNextChannel,},]'),
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(
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[({"name": PrepareNextChannel}, {"name": LoopByCount})],
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'[({"name": PrepareNextChannel,},{"name": LoopByCount,},),]',
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),
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(
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[({"name": PrepareNextChannel}, {"name": LoopByCount, "args": (3,)})],
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'[({"name": PrepareNextChannel,},{"name": LoopByCount,"args": (3,),},),]',
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),
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(
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[
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{
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"name": ZStackAcquisition,
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"args": (
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True,
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False,
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"zstack",
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),
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}
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],
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'[{"name": ZStackAcquisition,"args": (True,False,"zstack",),},]',
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),
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],
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)
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def test_convert_feature_list_to_str(feature_list, expected_str):
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feature_str = convert_feature_list_to_str(feature_list)
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assert feature_str == expected_str
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if feature_list:
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assert convert_str_to_feature_list(feature_str) == feature_list
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