def test_filetype_keywords():
kws = {'poissonize': True}
format = DD.filetype_keywords(kws)
assert format == 'singfel'
kws = {'woo': True}
format = DD.filetype_keywords(kws)
assert format == 'UNKNOWN'
def test_write_emc_h5_multi(tmp_path):
h5_file = './testFiles/singfel-multi.h5'
out_path = tmp_path / "h5_multi.emc"
DiffrData = DD.read(h5_file, poissonize=False)
DiffrData.multiply(1e9)
assert isinstance(DiffrData, DiffractionData) is True
DD.write(out_path, DiffrData, 'emc')
def test_writeUnsupported():
input_arr = np.random.rand(10, 10)
data = DiffractionData(arrary=input_arr)
with pytest.raises(UnknownFileTypeError) as excinfo:
DD.write("filename", data, format='blabla')
print(excinfo.value)
assert "Unsupported format" in str(excinfo.value)
def saveH5(self, format='emc'):
"""Save noised diffraction data as a HDF5 file
:param format: What format to save the data in.
:type format: str
"""
DD.write(self.output_path, self.data, format)
def test_filetype_content():
h5_file = './testFiles/singfel.h5'
format = DD.filetype_content(h5_file)
assert format == 'singfel'
md_file = './testFiles/README.md'
format = DD.filetype_content(md_file)
assert format == 'UNKNOWN'
def test_filetype():
h5_file = './testFiles/singfel.h5'
format = DD.filetype(h5_file)
assert format == 'singfel'
try:
md_file = './testFiles/README.md'
format = DD.filetype(md_file)
except UnknownFileTypeError:
assert True
def test_addGaussianNoise(tmp_path):
h5_file = './testFiles/singfel-multi.h5'
data = DD.read(h5_file)
xcs = np.array([-1.845, 56.825, 114.623])
fwhms = np.array([20.687, 26.771, 29.232])
hist_params = DD.histogramParams(xcs, fwhms)
data.addGaussianNoise(hist_params.mu, hist_params.sigs_popt)
out_path = tmp_path / "fitting.png"
fn = str(out_path)
hist_params.plotFitting(fn)
assert out_path.is_file() is True
def test_multiply():
h5_file = './testFiles/singfel-multi.h5'
dd = DD.read(h5_file, poissonize=False)
orig = dd.array
val_orig = np.max(orig[0])
dd.multiply(0)
multi = dd.array
assert np.max(orig[0]) == val_orig
assert np.max(multi[0]) == 0
assert np.max(multi[2]) == 0
def backengine(self):
""" Method to do the actual calculation."""
diffr_data = DD.read(self.input_path, self.parameters.index,
**self.parameters.read_args)
diffr_data.addGaussianNoise(self.parameters.mu,
self.parameters.sigs_popt)
diffr_data.multiply(1 / self.parameters.mu)
for i in tqdm(range(len(diffr_data.array))):
diffr_data.array[i] = np.round(diffr_data.array[i])
diffr_data.array[diffr_data.array < 0] = 0
diffr_data.setArrayDataType('i4')
self._set_data(diffr_data)
return 0
def test_read():
h5_file = './testFiles/singfel.h5'
DiffrData = DD.read(h5_file)
assert isinstance(DiffrData, DD.DiffractionData) is True
def test_file_not_exists():
h5_file = './testFiles/xx.h5'
with pytest.raises(FileNotFoundError):
DD.read(h5_file)
def test_listFormats():
DD.listFormats()
def test_unexpected_read_argument(tmp_path):
diffr_path = './testFiles/singfel-multi.h5'
with pytest.raises(TypeError) as excinfo:
DD.read(diffr_path, pattern_shape=[81, 81])
assert "got an unexpected keyword argument" in str(excinfo.value)
def test_read_emc_h5_multi():
h5_file = './testFiles/h5_multi.emc'
DiffrData = DD.read(h5_file, pattern_shape=[81, 81])
DiffrData.plotPattern(1)
assert len(DiffrData.array) == 13
def test_addBeamStop():
h5_file = './testFiles/singfel-multi.h5'
data = DD.read(h5_file)
data.addBeamStop(3)
def test_read_emc_h5_single():
h5_file = './testFiles/h5.emc'
DiffrData = DD.read(h5_file, pattern_shape=[81, 81])
DiffrData.plotPattern(0)
with pytest.raises(IndexError):
DiffrData.plotPattern(1)
def test_plotPattern():
h5_file = './testFiles/singfel-multi.h5'
data = DD.read(h5_file, poissonize=False)
data.plotPattern(idx=0, logscale=True)
def test_print_format_keys():
DD.listFormats()
def test_write_EMC_ini(tmp_path):
h5_file = './testFiles/singfel-multi.h5'
out_path = tmp_path / "config.ini"
# out_path = 'config.ini'
dd = DD.read(h5_file)
dd.writeEmcIni(str(out_path))
def test_savePattern(tmp_path):
h5_file = './testFiles/singfel-multi.h5'
dd = DD.read(h5_file, poissonize=False)
out_path = tmp_path / "test.png"
dd.plotPattern(idx=0, logscale=True, fn_png=str(out_path))
assert out_path.is_file() is True
def test_readSingFEL():
h5_file = './testFiles/singfel-multi.h5'
data = DD.read(h5_file)
assert len(data.array) == 13
def test_saveHistogram(tmp_path):
h5_file = './testFiles/singfel-multi.h5'
dd = DD.read(h5_file, poissonize=False)
out_path = tmp_path / "test.png"
dd.plotHistogram(fn_png=str(out_path))
assert out_path.is_file() is True
def test_plotStatistics():
h5_file = './testFiles/singfel-multi.h5'
dd = DD.read(h5_file, poissonize=False)
if __name__ == "__main__":
dd.plotHistogram()
def test_photon_statistics():
h5_file = './testFiles/singfel-multi.h5'
dd = DD.read(h5_file, poissonize=False)
pprint(dd.photon_statistics)
def test_pattern_total():
h5_file = './testFiles/singfel-multi.h5'
dd = DD.read(h5_file)
assert dd.pattern_total == 13
def test_data_simplebeam():
h5_file = './testFiles/singfel-multi.h5'
dd = DD.read(h5_file)
assert pytest.approx(dd.beam.attrs['wavelength'], 0.1) == 2.5
assert pytest.approx(dd.beam.wavelength, 0.1) == 2.5
print(dd.beam)
def test_write_multi(tmp_path):
diffr_path = './testFiles/singfel-multi.h5'
out_path = tmp_path / "t.emc"
diffr = DD.read(diffr_path)
EMC.write(str(out_path), diffr)
def test_readAutoRewriteSingFEL(tmp_path):
h5_file = './testFiles/singfel-multi.h5'
data = DD.read(h5_file)
ofn = tmp_path / 'rewrite_singfel.h5'
DD.write(str(ofn), data, 'singfel')
DD.read(str(ofn))