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# -*- 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 <https://www.gnu.org/licenses/#GPL>.
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(),
)
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