esbo_ds/ESBO-ETC
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Method visibility improved

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This commit is contained in:
Lukas Klass 2020-05-20 09:12:08 +02:00
parent a197ccae1f
commit 4c5465321b
1 changed files with 11 additions and 11 deletions
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20
esbo_etc/classes/psf/Airy.py
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@ -72,7 +72,7 @@ class Airy(IPSF):
reduced_observation_angle = 1.028
if not np.isclose(obstruction, 0.0):
# Use obstructed airy disk
reduced_observation_angle = newton(lambda y: self.airy(np.pi * y, np.sqrt(obstruction)) - 0.5,
reduced_observation_angle = newton(lambda y: self.__airy(np.pi * y, np.sqrt(obstruction)) - 0.5,
reduced_observation_angle / 2) * 2
contained_energy = "fwhm"
elif contained_energy.lower() == "min":
@ -81,15 +81,15 @@ class Airy(IPSF):
contained_energy = 0.8377 * u.dimensionless_unscaled
if not np.isclose(obstruction, 0.0):
# Use obstructed airy disk
reduced_observation_angle = fmin(lambda y: self.airy(np.pi * y, np.sqrt(obstruction)),
reduced_observation_angle = fmin(lambda y: self.__airy(np.pi * y, np.sqrt(obstruction)),
reduced_observation_angle / 2, disp=False)[0] * 2
contained_energy = self.airy_int(np.pi * reduced_observation_angle / 2,
contained_energy = self.__airy_int(np.pi * reduced_observation_angle / 2,
np.sqrt(obstruction)) * u.dimensionless_unscaled
else:
# Calculate the width numerically from the integral of the airy disk
contained_energy = contained_energy / 100 * u.dimensionless_unscaled
reduced_observation_angle = 2 * bisect(
lambda y: self.airy_int(np.pi * y, np.sqrt(obstruction)) - contained_energy.value, 0, 100)
lambda y: self.__airy_int(np.pi * y, np.sqrt(obstruction)) - contained_energy.value, 0, 100)
if jitter_sigma is not None and (isinstance(contained_energy, u.Quantity) or isinstance(contained_energy, str)
and contained_energy.lower() == "fwhm"):
# Convert jitter to reduced observation angle in lambda / d_ap
@ -106,7 +106,7 @@ class Airy(IPSF):
# Calculate the corresponding x-coordinates of each grid element
x = np.arange(1, n_points + 1) * dx
# Calculate the psf from an airy disk for each element on the grid
psf = self.airy(np.pi * x, np.sqrt(obstruction))
psf = self.__airy(np.pi * x, np.sqrt(obstruction))
# Calculate the integral of the undisturbed airy disk in order to scale the result of the convolution
total = np.sum(psf * x) * dx * 2 * np.pi
# Mirror the PSF to the negative x-domain
@ -139,7 +139,7 @@ class Airy(IPSF):
return reduced_observation_angle * u.dimensionless_unscaled
@staticmethod
def airy(x: Union[float, np.ndarray], obstruction: float = None):
def __airy(x: Union[float, np.ndarray], obstruction: float = None) -> Union[float, np.ndarray]:
"""
Calculate function values of the airy disk
@ -177,7 +177,7 @@ class Airy(IPSF):
return res
@staticmethod
def airy_int(x: float, obstruction: float = None):
def __airy_int(x: float, obstruction: float = None) -> float:
"""
Calculate the integral of the airy disk from 0 to x.
@ -234,7 +234,7 @@ class Airy(IPSF):
# Calculate the new PSF-center indices of the reduced mask
psf_center_ind = [mask.psf_center_ind[0] - y_ind.min(), mask.psf_center_ind[1] - x_ind.min()]
# Oversample the reduced mask
mask_red_os = self.rebin(mask_red, self.__osf).view(PixelMask)
mask_red_os = self._rebin(mask_red, self.__osf).view(PixelMask)
# Calculate the new PSF-center indices of the reduced mask
psf_center_ind = [x * self.__osf for x in psf_center_ind]
@ -247,7 +247,7 @@ class Airy(IPSF):
0]) * reduced_observation_angle_pixel.value / self.__osf)
dist = np.sqrt(x_mesh ** 2 + y_mesh ** 2)
if jitter_sigma is None:
res = self.airy(dist * np.pi, np.sqrt(obstruction))
res = self.__airy(dist * np.pi, np.sqrt(obstruction))
else:
if self.__psf_jitter is None:
self.calcReducedObservationAngle("fwhm", jitter_sigma, obstruction)
@ -257,7 +257,7 @@ class Airy(IPSF):
fill_value="extrapolate")
res = psf_interp(dist)
res = self.rebin(res, 1 / self.__osf)
res = self._rebin(res, 1 / self.__osf)
res = (mask_red * res).view(np.ndarray)
# Integrate the reduced mask and divide by the indefinite integral to get relative intensities
res = res * (reduced_observation_angle_pixel.value / self.__osf) ** 2 / (4 / np.pi) * (1 - obstruction)