# -*- 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 . from pathlib import Path import numpy as np import pytest from rsciio.utils.tests import assert_deep_almost_equal hs = pytest.importorskip("hyperspy.api", reason="hyperspy not installed") exspy = pytest.importorskip("exspy", reason="exspy not installed") TEST_DATA_PATH = Path(__file__).parent / "data" / "pantarhei" class TestLoadingPrzFiles: def test_metadata_prz_v5(self): md = { "General": {"title": "AD", "original_filename": "panta_rhei_sample_v5.prz"}, "Signal": {"signal_type": ""}, "Acquisition_instrument": { "TEM": { "beam_energy": 200.0, "acquisition_mode": "STEM", "magnification": 10000000, "camera_length": 0.02, } }, } am = { "axis-0": { "_type": "UniformDataAxis", "name": "Y", "units": "m", "navigate": False, "is_binned": False, "size": 16, "scale": 7.795828292907633e-09, "offset": 0.0, }, "axis-1": { "_type": "UniformDataAxis", "name": "X", "units": "m", "navigate": False, "is_binned": False, "size": 16, "scale": 7.795828292907633e-09, "offset": 0.0, }, } s = hs.load(TEST_DATA_PATH / "panta_rhei_sample_v5.prz") md_file = s.metadata.as_dictionary() md_file.pop("_HyperSpy") md_file["General"].pop("FileIO") assert_deep_almost_equal(md_file, md) assert_deep_almost_equal(s.axes_manager.as_dictionary(), am) assert s.data.shape == (16, 16) assert s.data.max() == 40571 assert s.data.min() == 36193 np.testing.assert_almost_equal(s.data.std(), 1025.115644550) def test_save_load_cycle(tmp_path): fname = tmp_path / "test_file.prz" s = hs.load(TEST_DATA_PATH / "panta_rhei_sample_v5.prz") s.save(fname) assert fname.is_file() s2 = hs.load(fname) np.testing.assert_allclose(s2.data, s.data) assert s2.metadata.Signal.signal_type == s.metadata.Signal.signal_type def test_save_load_cycle_new_signal_1D_nav1(tmp_path): fname = tmp_path / "test_file_new_signal_1D_nav1.prz" data = np.arange(20).reshape(2, 10) s = hs.signals.Signal1D(data) s.save(fname) assert fname.is_file() s2 = hs.load(fname) np.testing.assert_allclose(s2.data, s.data) assert isinstance(s2, s.__class__) def test_save_load_cycle_new_signal_1D_nav2(tmp_path): fname = tmp_path / "test_file_new_signal1D_nav2.prz" data = np.arange(100).reshape(2, 5, 10) s = hs.signals.Signal2D(data) s.save(fname) assert fname.is_file() s2 = hs.load(fname) np.testing.assert_allclose(s2.data, s.data) assert isinstance(s2, s.__class__) def test_save_load_cycle_new_signal_2D(tmp_path): fname = tmp_path / "test_file_new_signal2D.prz" data = np.arange(100).reshape(2, 5, 10) s = hs.signals.Signal2D(data) s.save(fname) assert fname.is_file() s2 = hs.load(fname) np.testing.assert_allclose(s2.data, s.data) assert isinstance(s2, s.__class__) def test_save_load_cycle_new_signal_EELS(tmp_path): fname = tmp_path / "test_file_new_signal2D.prz" data = np.arange(100).reshape(2, 5, 10) s = exspy.signals.EELSSpectrum(data) s.save(fname) assert fname.is_file() s2 = hs.load(fname) np.testing.assert_allclose(s2.data, s.data) assert isinstance(s2, s.__class__) def test_save_load_cycle_new_signal_EELS_aperture_out(tmp_path): fname = tmp_path / "test_file_new_signal2D_aperture_out.prz" data = np.arange(100).reshape(2, 5, 10) s = exspy.signals.EELSSpectrum(data) s.metadata.set_item("Acquisition_instrument.TEM.Detector.EELS.aperture", "Out") s.save(fname) assert fname.is_file() s2 = hs.load(fname) np.testing.assert_allclose(s2.data, s.data) assert isinstance(s2, s.__class__) assert s2.metadata.Acquisition_instrument.TEM.Detector.EELS.aperture == "Out" def test_metadata_STEM(tmp_path): fname = tmp_path / "test_file_new_signal_metadata_STEM.prz" data = np.arange(20).reshape(2, 10) s = exspy.signals.EELSSpectrum(data) # Set some metadata md = { "Acquisition_instrument": { "TEM": { "beam_energy": 200.0, "acquisition_mode": "STEM", "magnification": 500000, "camera_length": 200, "convergence_angle": 20, "Detector": { "EELS": {"collection_angle": 60, "aperture": 5}, }, }, }, } s.metadata.add_dictionary(md) s.metadata.General.add_dictionary({"date": "2022-07-08", "time": "16:00"}) s.save(fname) assert fname.is_file() s2 = hs.load(fname) np.testing.assert_allclose(s2.data, s.data) assert isinstance(s2, s.__class__) assert_deep_almost_equal( s2.metadata.Acquisition_instrument.as_dictionary(), s.metadata.Acquisition_instrument.as_dictionary(), ) def test_metadata_TEM(tmp_path): fname = tmp_path / "test_file_new_signal_metadata_TEM.prz" data = np.arange(20).reshape(2, 10) s = exspy.signals.EELSSpectrum(data) # Set some metadata md = { "Acquisition_instrument": { "TEM": { "beam_energy": 200.0, "acquisition_mode": "TEM", "magnification": 500000, "camera_length": 200, "Detector": { "EELS": {"collection_angle": 60, "aperture": 5}, }, }, }, } s.metadata.add_dictionary(md) s.metadata.General.add_dictionary({"date": "2022-07-08", "time": "16:00"}) s.save(fname) assert fname.is_file() s2 = hs.load(fname) np.testing.assert_allclose(s2.data, s.data) assert isinstance(s2, s.__class__) assert_deep_almost_equal( s2.metadata.Acquisition_instrument.as_dictionary(), s.metadata.Acquisition_instrument.as_dictionary(), )