# -*- coding: utf-8 -*- # Copyright 2007-2023 The HyperSpy developers # # This file is part of RosettaSciIO. # # RosettaSciIO is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # RosettaSciIO is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with RosettaSciIO. If not, see . import os from pathlib import Path import pytest from rsciio.utils.tests import expected_is_binned hs = pytest.importorskip("hyperspy.api", reason="hyperspy not installed") imagecodecs = pytest.importorskip( "imagecodecs", reason="skipping test_phenom tests, requires imagecodecs" ) TEST_DATA_PATH = Path(__file__).parent / "data" / "phenom" ELID2VERSION0 = TEST_DATA_PATH / "Elid2Version0.elid" ELID2VERSION1 = TEST_DATA_PATH / "Elid2Version1.elid" ELID2VERSION2 = TEST_DATA_PATH / "Elid2Version2.elid" ELID2VERSION3 = TEST_DATA_PATH / "Elid2Version3.elid" ELID2VERSION4 = TEST_DATA_PATH / "Elid2Version4.elid" @pytest.mark.parametrize( ("pathname"), [ELID2VERSION0, ELID2VERSION1, ELID2VERSION2, ELID2VERSION3, ELID2VERSION4], ) def test_elid(pathname): s = hs.load(pathname) assert len(s) == 11 assert s[0].data.shape == (16, 20) assert s[0].axes_manager.as_dictionary() == { "axis-0": { "_type": "UniformDataAxis", "name": "y", "scale": 0.9757792598920122, "offset": 0.0, "size": 16, "units": "µm", "navigate": True, "is_binned": False, }, "axis-1": { "_type": "UniformDataAxis", "name": "x", "scale": 0.9757792598920122, "offset": 0.0, "size": 20, "units": "µm", "navigate": True, "is_binned": False, }, } assert ( s[0].metadata["Acquisition_instrument"]["SEM"]["Stage"]["x"] == -2.586744298575455 ) assert ( s[0].metadata["Acquisition_instrument"]["SEM"]["Stage"]["y"] == -0.7322168400784014 ) assert s[0].metadata["Acquisition_instrument"]["SEM"]["beam_energy"] == 15.0 assert ( s[0].metadata["Acquisition_instrument"]["SEM"]["microscope"] == "MVE027364-0026-L" ) assert s[0].metadata["General"]["date"] == "2019-08-07" assert s[0].metadata["General"]["original_filename"] == os.path.split(pathname)[1] assert s[0].metadata["General"]["time"] == "09:37:31" assert s[0].metadata["General"]["title"] == "Image 1" assert s[0].metadata["Signal"]["signal_type"] == "" assert s[0].original_metadata["acquisition"]["scan"]["dwellTime"]["value"] == "200" assert s[0].original_metadata["acquisition"]["scan"]["dwellTime"]["unit"] == "ns" assert ( s[0].original_metadata["acquisition"]["scan"]["fieldSize"] == 0.000019515585197840245 ) assert ( s[0].original_metadata["acquisition"]["scan"]["highVoltage"]["value"] == "-15" ) assert s[0].original_metadata["acquisition"]["scan"]["highVoltage"]["unit"] == "kV" assert s[0].original_metadata["pixelWidth"]["value"] == "975.7792598920121" assert s[0].original_metadata["pixelWidth"]["unit"] == "nm" assert s[0].original_metadata["pixelHeight"]["value"] == "975.7792598920121" assert s[0].original_metadata["pixelHeight"]["unit"] == "nm" assert s[0].original_metadata["samplePosition"]["x"] == "-0.002586744298575455" assert s[0].original_metadata["samplePosition"]["y"] == "-0.0007322168400784014" assert s[0].original_metadata["workingDistance"]["value"] == "8.141749999999993" assert s[0].original_metadata["workingDistance"]["unit"] == "mm" assert ( s[0].original_metadata["instrument"]["softwareVersion"] == "5.4.5.rc1.bb8fbe3.23039" ) assert s[0].original_metadata["instrument"]["type"] == "PhenomXL" assert s[0].original_metadata["instrument"]["uniqueID"] == "MVE027364-0026-L" assert s[1].metadata["General"]["title"] == "Image 1, Spot 1" assert s[1].data.shape == (2048,) assert s[1].axes_manager.as_dictionary() == { "axis-0": { "_type": "UniformDataAxis", "name": "Energy", "scale": 0.00988676802994421, "offset": -0.03634370080990722, "size": 2048, "units": "keV", "navigate": False, "is_binned": expected_is_binned(), } } assert s[1].data.tolist()[0:300] == [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 15, 16, 19, 30, 52, 61, 98, 125, 145, 129, 114, 69, 45, 22, 14, 11, 18, 17, 30, 26, 29, 19, 16, 20, 26, 29, 35, 51, 59, 103, 139, 157, 209, 220, 179, 113, 99, 65, 49, 31, 36, 39, 42, 35, 48, 37, 55, 50, 45, 46, 49, 40, 49, 54, 35, 49, 57, 63, 71, 64, 75, 76, 92, 98, 83, 81, 94, 118, 120, 160, 215, 325, 363, 368, 429, 403, 376, 254, 204, 173, 136, 124, 102, 89, 97, 84, 83, 75, 83, 71, 85, 101, 81, 72, 87, 84, 90, 93, 84, 68, 93, 91, 82, 86, 112, 85, 84, 100, 110, 118, 132, 118, 125, 138, 128, 135, 143, 143, 136, 148, 227, 301, 538, 1077, 1946, 3319, 5108, 7249, 9032, 10755, 11441, 10804, 9219, 7245, 5335, 3568, 2213, 1455, 825, 543, 338, 283, 196, 160, 123, 104, 105, 92, 88, 109, 89, 88, 82, 95, 88, 91, 87, 108, 86, 85, 59, 77, 72, 58, 66, 69, 64, 76, 56, 67, 58, 60, 59, 71, 56, 57, 62, 50, 67, 59, 59, 52, 45, 60, 53, 57, 59, 39, 43, 55, 54, 40, 43, 37, 39, 41, 52, 39, 53, 41, 48, 40, 41, 45, 36, 45, 32, 40, 44, 43, 55, 50, 45, 59, 45, 44, 66, 52, 67, 74, 83, 90, 92, 114, 130, 131, 114, 100, 100, 106, 103, 84, 87, 77, 76, 82, 83, 78, 81, 63, 49, 54, 64, 45, 41, 40, 41, 38, 50, 39, 45, 44, 42, 44, 31, 36, 38, 37, 55, 40, 32, 34, 32, 34, 37, 27, 28, 45, 35, 24, 40, 22, 29, 33, 33, 44, 34, ] assert ( s[1].original_metadata["acquisition"]["scan"]["detectors"]["EDS"]["live_time"] == 5.7203385 ) assert ( s[1].original_metadata["acquisition"]["scan"]["detectors"]["EDS"]["real_time"] == 10.162500000000001 ) assert ( s[1].original_metadata["acquisition"]["scan"]["detectors"]["EDS"][ "fast_peaking_time" ] == 100e-9 ) assert ( s[1].original_metadata["acquisition"]["scan"]["detectors"]["EDS"][ "slow_peaking_time" ] == 11.2e-6 ) assert s[2].metadata["General"]["title"] == "Image 1, Region 2" assert s[2].data.shape == (2048,) assert s[2].axes_manager.as_dictionary() == { "axis-0": { "_type": "UniformDataAxis", "name": "Energy", "scale": 0.00988676802994421, "offset": -0.03634370080990722, "size": 2048, "units": "keV", "navigate": False, "is_binned": expected_is_binned(), } } assert ( s[2].original_metadata["acquisition"]["scan"]["detectors"]["EDS"]["live_time"] == 6.5802053 ) assert ( s[2].original_metadata["acquisition"]["scan"]["detectors"]["EDS"]["real_time"] == 10.177700000000003 ) assert s[3].metadata["General"]["title"] == "Image 1, Map 3" assert s[3].data.shape == (16, 16, 2048) assert s[3].axes_manager.as_dictionary() == { "axis-0": { "_type": "UniformDataAxis", "name": "y", "scale": 1.2197240748650153, "offset": 0.0, "size": 16, "units": "µm", "navigate": True, "is_binned": False, }, "axis-1": { "_type": "UniformDataAxis", "name": "x", "scale": 1.2197240748650153, "offset": 0.0, "size": 16, "units": "µm", "navigate": True, "is_binned": False, }, "axis-2": { "_type": "UniformDataAxis", "name": "X-ray energy", "scale": 0.00988676802994421, "offset": -0.03634370080990722, "size": 2048, "units": "keV", "navigate": False, "is_binned": expected_is_binned(), }, } assert ( s[3].original_metadata["acquisition"]["scan"]["detectors"]["EDS"]["live_time"] == 4.047052 ) assert ( s[3].original_metadata["acquisition"]["scan"]["detectors"]["EDS"]["real_time"] == 3.0005599999999997 ) assert s[4].metadata["General"]["title"] == "Image 1, Line 4" assert s[4].data.shape == (64, 2048) assert s[4].axes_manager.as_dictionary() == { "axis-0": { "_type": "UniformDataAxis", "name": "i", "scale": 1.0, "offset": 0.0, "size": 64, "units": "points", "navigate": True, "is_binned": False, }, "axis-1": { "_type": "UniformDataAxis", "name": "X-ray energy", "scale": 0.00988676802994421, "offset": -0.03634370080990722, "size": 2048, "units": "keV", "navigate": False, "is_binned": expected_is_binned(), }, } assert ( s[4].original_metadata["acquisition"]["scan"]["detectors"]["EDS"]["live_time"] == 5.504343599999998 ) assert ( s[4].original_metadata["acquisition"]["scan"]["detectors"]["EDS"]["real_time"] == 6.410299999999996 ) assert s[5].metadata["General"]["title"] == "Image 1, Map 6" assert s[5].data.shape == (16, 16, 2048) assert s[5].axes_manager.as_dictionary() == { "axis-0": { "_type": "UniformDataAxis", "name": "y", "scale": 1.2197240748650153, "offset": 0.0, "size": 16, "units": "µm", "navigate": True, "is_binned": False, }, "axis-1": { "_type": "UniformDataAxis", "name": "x", "scale": 1.2197240748650153, "offset": 0.0, "size": 16, "units": "µm", "navigate": True, "is_binned": False, }, "axis-2": { "_type": "UniformDataAxis", "name": "X-ray energy", "scale": 0.009886797201840245, "offset": -0.04478043655810262, "size": 2048, "units": "keV", "navigate": False, "is_binned": expected_is_binned(), }, } assert ( s[5].original_metadata["acquisition"]["scan"]["detectors"]["EDS"]["live_time"] == 4.5919591 ) assert ( s[5].original_metadata["acquisition"]["scan"]["detectors"]["EDS"]["real_time"] == 3.00056 ) assert s[6].metadata["General"]["title"] == "Image 1, Difference 3 - 6" assert s[6].data.shape == (2048,) assert s[6].axes_manager.as_dictionary() == { "axis-0": { "_type": "UniformDataAxis", "name": "Energy", "scale": 0.00988676802994421, "offset": -0.03634370080990722, "size": 2048, "units": "keV", "navigate": False, "is_binned": expected_is_binned(), } } assert s[7].metadata["General"]["title"] == "385test - spectrum" assert s[7].data.shape == (24, 32) assert s[7].axes_manager.as_dictionary() == { "axis-0": { "_type": "UniformDataAxis", "name": "y", "scale": 1.0, "offset": 0.0, "size": 24, "units": "points", "navigate": True, "is_binned": False, }, "axis-1": { "_type": "UniformDataAxis", "name": "x", "scale": 1.0, "offset": 0.0, "size": 32, "units": "points", "navigate": True, "is_binned": False, }, } assert "acquisition" not in s[7].original_metadata assert s[8].metadata["General"]["title"] == "385test - spectrum, MSA 1" assert s[8].data.shape == (2048,) assert s[8].axes_manager.as_dictionary() == { "axis-0": { "_type": "UniformDataAxis", "name": "Energy", "scale": 0.0098868, "offset": -0.0363437, "size": 2048, "units": "keV", "navigate": False, "is_binned": expected_is_binned(), } } assert ( s[8].original_metadata["acquisition"]["scan"]["detectors"]["EDS"]["live_time"] == 0.0 ) assert ( s[8].original_metadata["acquisition"]["scan"]["detectors"]["EDS"]["real_time"] == 5.066 ) assert s[9].metadata["General"]["title"] == "Image 1" assert s[9].data.shape == (35, 40) assert s[9].axes_manager.as_dictionary() == { "axis-0": { "_type": "UniformDataAxis", "name": "y", "scale": 0.8120422280865187, "offset": 0.0, "size": 35, "units": "µm", "navigate": True, "is_binned": False, }, "axis-1": { "_type": "UniformDataAxis", "name": "x", "scale": 0.8120422280865187, "offset": 0.0, "size": 40, "units": "µm", "navigate": True, "is_binned": False, }, } assert "EDS" not in s[9].original_metadata["acquisition"]["scan"]["detectors"] assert s[10].metadata["General"]["title"] == "Image 1, Map 1" assert s[10].data.shape == (16, 16, 2048) assert s[10].axes_manager.as_dictionary() == { "axis-0": { "_type": "UniformDataAxis", "name": "y", "scale": 2.0301055702162967, "offset": 0.0, "size": 16, "units": "µm", "navigate": True, "is_binned": False, }, "axis-1": { "_type": "UniformDataAxis", "name": "x", "scale": 2.0301055702162967, "offset": 0.0, "size": 16, "units": "µm", "navigate": True, "is_binned": False, }, "axis-2": { "_type": "UniformDataAxis", "name": "X-ray energy", "scale": 0.009886797201840245, "offset": -0.04478043655810262, "size": 2048, "units": "keV", "navigate": False, "is_binned": expected_is_binned(), }, } assert ( s[10].original_metadata["acquisition"]["scan"]["detectors"]["EDS"]["live_time"] == 4.821238 ) assert ( s[10].original_metadata["acquisition"]["scan"]["detectors"]["EDS"]["real_time"] == 3.0005600000000006 )