def allocate_measurement(self, grid: Grid, wavelength: float,
scan: AbstractScan) -> Measurement:
inner, outer, nbins_radial, nbins_azimuthal = self._get_bins(
grid.antialiased_sampling, wavelength)
shape = scan.shape
calibrations = scan.calibrations
if nbins_radial > 1:
shape += (nbins_radial, )
calibrations += (Calibration(offset=inner,
sampling=self._radial_steps,
units='mrad'), )
if nbins_azimuthal > 1:
shape += (nbins_azimuthal, )
calibrations += (Calibration(offset=0,
sampling=self._azimuthal_steps,
units='rad'), )
array = np.zeros(shape, dtype=np.float32)
measurement = Measurement(array, calibrations=calibrations)
if isinstance(self.save_file, str):
measurement = measurement.write(self.save_file)
return measurement
def calibrations(self) -> tuple:
return (Calibration(offset=0,
sampling=self.sampling[0],
units='Å',
name='x'),
Calibration(offset=0,
sampling=self.sampling[1],
units='Å',
name='y'))
def calibrations(self) -> tuple:
return (Calibration(offset=self.start[0],
sampling=self.sampling[0],
units='Å',
name='x',
endpoint=self.grid.endpoint[0]),
Calibration(offset=self.start[1],
sampling=self.sampling[1],
units='Å',
name='y',
endpoint=self.grid.endpoint[1]))
def allocate_measurement(self,
waves,
scan: AbstractScan = None) -> Measurement:
"""
Allocate a Measurement object or an hdf5 file.
Parameters
----------
waves : Waves object
An example of the
scan : Scan object
The scan object that will define the scan dimensions the measurement.
Returns
-------
Measurement object or str
The allocated measurement or path to hdf5 file with the measurement data.
"""
waves.grid.check_is_defined()
waves.accelerator.check_is_defined()
if scan is None:
shape = ()
calibrations = ()
else:
shape = scan.shape
calibrations = scan.calibrations
nbins_radial, nbins_azimuthal, inner, _ = self._get_bins(
min(waves.cutoff_scattering_angles))
if nbins_radial > 1:
shape += (nbins_radial, )
calibrations += (Calibration(offset=inner,
sampling=self._radial_steps,
units='mrad'), )
if nbins_azimuthal > 1:
shape += (nbins_azimuthal, )
calibrations += (Calibration(offset=0,
sampling=self._azimuthal_steps,
units='rad'), )
array = np.zeros(shape, dtype=np.float32)
measurement = Measurement(array, calibrations=calibrations)
if isinstance(self.save_file, str):
measurement = measurement.write(self.save_file)
return measurement
def profiles(self, max_semiangle: float = None, phi: float = 0.):
if max_semiangle is None:
if self._semiangle_cutoff == np.inf:
max_semiangle = 50
else:
max_semiangle = self._semiangle_cutoff * 1.6
alpha = np.linspace(0, max_semiangle / 1000., 500)
aberrations = self.evaluate_aberrations(alpha, phi)
aperture = self.evaluate_aperture(alpha)
temporal_envelope = self.evaluate_temporal_envelope(alpha)
spatial_envelope = self.evaluate_spatial_envelope(alpha, phi)
gaussian_envelope = self.evaluate_gaussian_envelope(alpha)
envelope = aperture * temporal_envelope * spatial_envelope * gaussian_envelope
calibration = Calibration(offset=0.,
sampling=(alpha[1] - alpha[0]) * 1000.,
units='mrad',
name='alpha')
profiles = {}
profiles['ctf'] = Measurement(aberrations.imag * envelope,
calibrations=[calibration],
name='CTF')
profiles['aperture'] = Measurement(aperture,
calibrations=[calibration],
name='Aperture')
profiles['temporal_envelope'] = Measurement(temporal_envelope,
calibrations=[calibration],
name='Temporal')
profiles['spatial_envelope'] = Measurement(spatial_envelope,
calibrations=[calibration],
name='Spatial')
profiles['gaussian_spread'] = Measurement(gaussian_envelope,
calibrations=[calibration],
name='Gaussian')
profiles['envelope'] = Measurement(envelope,
calibrations=[calibration],
name='Envelope')
return profiles
def calibrations(self) -> Tuple[Calibration]:
return Calibration(offset=0,
sampling=self.sampling[0],
units='Å',
name='x',
endpoint=self.grid.endpoint[0]),
