def test_add_stimulus_presentations(nwbfile, stimulus_presentations_behavior,
                                    stimulus_timestamps, roundtrip,
                                    roundtripper,
                                    stimulus_templates: StimulusTemplate):
    nwb.add_stimulus_timestamps(nwbfile, stimulus_timestamps)
    nwb.add_stimulus_presentations(nwbfile, stimulus_presentations_behavior)
    nwb.add_stimulus_template(nwbfile=nwbfile,
                              stimulus_template=stimulus_templates)

    # Add index for this template to NWB in-memory object:
    nwb_template = nwbfile.stimulus_template[stimulus_templates.image_set_name]
    compare = (stimulus_presentations_behavior['image_set'] ==
               nwb_template.name)
    curr_stimulus_index = stimulus_presentations_behavior[compare]
    nwb.add_stimulus_index(nwbfile, curr_stimulus_index, nwb_template)

    if roundtrip:
        obt = roundtripper(nwbfile, BehaviorNwbApi)
    else:
        obt = BehaviorNwbApi.from_nwbfile(nwbfile)

    expected = stimulus_presentations_behavior.copy()
    expected['is_change'] = [False, True, True, True, True]

    obtained = obt.get_stimulus_presentations()

    pd.testing.assert_frame_equal(expected[sorted(expected.columns)],
                                  obtained[sorted(obtained.columns)],
                                  check_dtype=False)
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def test_add_stimulus_templates(nwbfile, stimulus_templates, roundtrip, roundtripper):
    for key, val in stimulus_templates.items():
        nwb.add_stimulus_template(nwbfile, val, key)

    if roundtrip:
        obt = roundtripper(nwbfile, BehaviorOphysNwbApi)
    else:
        obt = BehaviorOphysNwbApi.from_nwbfile(nwbfile)

    stimulus_templates_obt = obt.get_stimulus_templates()
    for key in set(stimulus_templates.keys()).union(set(stimulus_templates_obt.keys())):
        np.testing.assert_array_almost_equal(stimulus_templates[key], stimulus_templates_obt[key])
Exemple #3
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    def _add_stimulus_templates(nwbfile: NWBFile,
                                stimulus_templates: StimulusTemplate,
                                stimulus_presentations: pd.DataFrame):
        nwb.add_stimulus_template(nwbfile=nwbfile,
                                  stimulus_template=stimulus_templates)

        # Add index for this template to NWB in-memory object:
        nwb_template = nwbfile.stimulus_template[
            stimulus_templates.image_set_name]
        stimulus_index = stimulus_presentations[
            stimulus_presentations['image_set'] == nwb_template.name]
        nwb.add_stimulus_index(nwbfile, stimulus_index, nwb_template)

        return nwbfile
def test_add_stimulus_templates(nwbfile, behavior_stimuli_data_fixture,
                                roundtrip, roundtripper):
    stimulus_templates = get_stimulus_templates(behavior_stimuli_data_fixture,
                                                grating_images_dict={})

    nwb.add_stimulus_template(nwbfile, stimulus_templates)

    if roundtrip:
        obt = roundtripper(nwbfile, BehaviorNwbApi)
    else:
        obt = BehaviorNwbApi.from_nwbfile(nwbfile)

    stimulus_templates_obt = obt.get_stimulus_templates()

    assert stimulus_templates_obt == stimulus_templates
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def test_add_stimulus_presentations(nwbfile, stimulus_presentations_behavior, stimulus_timestamps, roundtrip, roundtripper, stimulus_templates):
    nwb.add_stimulus_timestamps(nwbfile, stimulus_timestamps)
    nwb.add_stimulus_presentations(nwbfile, stimulus_presentations_behavior)
    for key, val in stimulus_templates.items():
        nwb.add_stimulus_template(nwbfile, val, key)

        # Add index for this template to NWB in-memory object:
        nwb_template = nwbfile.stimulus_template[key]
        curr_stimulus_index = stimulus_presentations_behavior[stimulus_presentations_behavior['image_set'] == nwb_template.name]
        nwb.add_stimulus_index(nwbfile, curr_stimulus_index, nwb_template)

    if roundtrip:
        obt = roundtripper(nwbfile, BehaviorOphysNwbApi)
    else:
        obt = BehaviorOphysNwbApi.from_nwbfile(nwbfile)

    pd.testing.assert_frame_equal(stimulus_presentations_behavior, obt.get_stimulus_presentations(), check_dtype=False)
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    def save(self, session_object):

        nwbfile = NWBFile(
            session_description=str(session_object.metadata['session_type']),
            identifier=str(session_object.ophys_experiment_id),
            session_start_time=session_object.metadata['experiment_datetime'],
            file_create_date=pytz.utc.localize(datetime.datetime.now()))

        # Add stimulus_timestamps to NWB in-memory object:
        nwb.add_stimulus_timestamps(nwbfile,
                                    session_object.stimulus_timestamps)

        # Add running data to NWB in-memory object:
        unit_dict = {
            'v_sig': 'V',
            'v_in': 'V',
            'speed': 'cm/s',
            'timestamps': 's',
            'dx': 'cm'
        }
        nwb.add_running_data_df_to_nwbfile(nwbfile,
                                           session_object.running_data_df,
                                           unit_dict)

        # Add stimulus template data to NWB in-memory object:
        for name, image_data in session_object.stimulus_templates.items():
            nwb.add_stimulus_template(nwbfile, image_data, name)

            # Add index for this template to NWB in-memory object:
            nwb_template = nwbfile.stimulus_template[name]
            stimulus_index = session_object.stimulus_presentations[
                session_object.stimulus_presentations['image_set'] ==
                nwb_template.name]
            nwb.add_stimulus_index(nwbfile, stimulus_index, nwb_template)

        # Add stimulus presentations data to NWB in-memory object:
        nwb.add_stimulus_presentations(nwbfile,
                                       session_object.stimulus_presentations)

        # Add trials data to NWB in-memory object:
        nwb.add_trials(nwbfile, session_object.trials,
                       TRIAL_COLUMN_DESCRIPTION_DICT)

        # Add licks data to NWB in-memory object:
        if len(session_object.licks) > 0:
            nwb.add_licks(nwbfile, session_object.licks)

        # Add rewards data to NWB in-memory object:
        if len(session_object.rewards) > 0:
            nwb.add_rewards(nwbfile, session_object.rewards)

        # Add max_projection image data to NWB in-memory object:
        nwb.add_max_projection(nwbfile, session_object.max_projection)

        # Add average_image image data to NWB in-memory object:
        nwb.add_average_image(nwbfile, session_object.average_projection)

        # Add segmentation_mask_image image data to NWB in-memory object:
        nwb.add_segmentation_mask_image(nwbfile,
                                        session_object.segmentation_mask_image)

        # Add metadata to NWB in-memory object:
        nwb.add_metadata(nwbfile, session_object.metadata)

        # Add task parameters to NWB in-memory object:
        nwb.add_task_parameters(nwbfile, session_object.task_parameters)

        # Add roi metrics to NWB in-memory object:
        nwb.add_cell_specimen_table(nwbfile,
                                    session_object.cell_specimen_table)

        # Add dff to NWB in-memory object:
        nwb.add_dff_traces(nwbfile, session_object.dff_traces,
                           session_object.ophys_timestamps)

        # Add corrected_fluorescence to NWB in-memory object:
        nwb.add_corrected_fluorescence_traces(
            nwbfile, session_object.corrected_fluorescence_traces)

        # Add motion correction to NWB in-memory object:
        nwb.add_motion_correction(nwbfile, session_object.motion_correction)

        # Write the file:
        with NWBHDF5IO(self.path, 'w') as nwb_file_writer:
            nwb_file_writer.write(nwbfile)

        return nwbfile