Esempio n. 1
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def test_timestamps_as_data():
    hdr = DataBroker[-1]
    events = DataBroker.fetch_events(hdr)
    dm = DataMuxer.from_events(events)
    data_name = list(dm.sources.keys())
    for name in data_name:
        dm.include_timestamp_data(name)
        assert_true('{}_timestamp'.format(name) in dm._dataframe)
        dm.remove_timestamp_data(name)
        assert_false('{}_timestamp'.format(name) in dm._dataframe)
Esempio n. 2
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def test_attributes():
    hdr = DataBroker[-1]
    events = DataBroker.fetch_events(hdr)
    dm = DataMuxer.from_events(events)
    # merely testing that basic usage does not error
    for data_key in dm.sources.keys():
        getattr(dm, data_key)
        dm[data_key]
    properties = ['ncols', '_dataframe', 'col_info_by_ndim', 'sources',
                  'col_info', '_data', '_time', '_timestamps',
                  '_timestamps_as_data', '_known_events', '_known_descriptors',
                  '_stale']
    for prop in properties:
        getattr(dm, prop)
Esempio n. 3
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 def setUp(self):
     self.dm = DataMuxer.from_events(image_and_scalar.run())
Esempio n. 4
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 def setUp(self):
     self.dm = DataMuxer.from_events(multisource_event.run())
     self.sparse = 'Troom'
     self.dense = 'point_det'
     self.agg = np.mean
     self.interp = 'linear'
Esempio n. 5
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 def setUp(self):
     self.dm = DataMuxer.from_events(temperature_ramp.run())
     self.sparse = 'Tsam'
     self.dense = 'point_det'
     self.agg = np.mean
     self.interp = 'linear'
    ns.sort()

    # For each sample plot the intra sample temperature curve
    for i in ns:
        print(i)
        save_folder = '../S{}'.format(i)

        # Get the folder where the data is
        folder = '/mnt/bulk-data/research_data/USC_beamtime/APS_March_2016/S' \
                 + str(i) + '/temp_exp'

        # Get the run header assocaited with that folder
        hdr = db(run_folder=folder)[0]

        # Mux the data so that we have the correct Temp->data relationship
        dm = DataMuxer()
        dm.append_events(get_events(hdr))
        df = dm.to_sparse_dataframe()
        print(df.keys())
        binned = dm.bin_on('img', interpolation={'T': 'linear'})

        for plot_type in [
            'gr',
            'chi'
        ]:
            if plot_type is 'gr':
                # Only to the G(r)
                key_list = [f for f in os.listdir(folder) if
                            f.endswith('.gr') and not f.startswith('d')]
                # If we are working with G(r) files use these offset and read parameters
                offset = .1