esbo_ds/ESBO-ETC
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Parse contained energy

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This commit is contained in:
Lukas Klass 2020-04-29 17:37:07 +02:00
parent 20234d284e
commit 37ba622407
1 changed files with 11 additions and 2 deletions
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13
esbo_etc/classes/psf/Zemax.py
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@ -6,6 +6,8 @@ from scipy.interpolate import RegularGridInterpolator
from scipy.integrate import nquad from scipy.integrate import nquad
from scipy.optimize import bisect from scipy.optimize import bisect
from .IPSF import IPSF from .IPSF import IPSF
from typing import Union
from ...lib.helpers import error
class Zemax(IPSF): class Zemax(IPSF):
@ -53,7 +55,7 @@ class Zemax(IPSF):
self.__center_point = [int(x) for x in self.__center_point = [int(x) for x in
re.findall("[0-9]+", list(filter(re.compile("Center point is: ").match, head))[0])] re.findall("[0-9]+", list(filter(re.compile("Center point is: ").match, head))[0])]
def calcReducedObservationAngle(self, contained_energy: float) -> u.Quantity: def calcReducedObservationAngle(self, contained_energy: Union[str, int, float, u.Quantity]) -> u.Quantity:
""" """
Calculate the reduced observation angle in lambda / d_ap for the given contained energy. Calculate the reduced observation angle in lambda / d_ap for the given contained energy.
@ -67,6 +69,13 @@ class Zemax(IPSF):
reduced_observation_angle: Quantity reduced_observation_angle: Quantity
The reduced observation angle in lambda / d_ap The reduced observation angle in lambda / d_ap
""" """
if type(contained_energy) == str:
try:
contained_energy = float(contained_energy) / 100.0 * u.dimensionless_unscaled
except ValueError:
error("Could not convert encircled energy to float.")
elif type(contained_energy) in [int, float]:
contained_energy = contained_energy * u.dimensionless_unscaled
# Create an linear interpolation function for the PSF and the corresponding grid coordinates # Create an linear interpolation function for the PSF and the corresponding grid coordinates
x_range = np.arange(-(self.__center_point[0] - 1), self.__psf.shape[0] - self.__center_point[0] + 1) x_range = np.arange(-(self.__center_point[0] - 1), self.__psf.shape[0] - self.__center_point[0] + 1)
y_range = np.arange(-(self.__center_point[1] - 1), self.__psf.shape[1] - self.__center_point[1] + 1) y_range = np.arange(-(self.__center_point[1] - 1), self.__psf.shape[1] - self.__center_point[1] + 1)
@ -80,7 +89,7 @@ class Zemax(IPSF):
# Find the radius of the circle containing the given percentage of energy. Therefore, the interpolation # Find the radius of the circle containing the given percentage of energy. Therefore, the interpolation
# function is numerically integrated within the radius. The Integration radius is optimized using bisection. # function is numerically integrated within the radius. The Integration radius is optimized using bisection.
try: try:
r = bisect(lambda r_c: contained_energy - r = bisect(lambda r_c: contained_energy.value -
nquad(lambda x, y: interp(np.array([y, x])), nquad(lambda x, y: interp(np.array([y, x])),
[lambda y: [-1 * np.sqrt(r_c ** 2 - y ** 2), np.sqrt(r_c ** 2 - y ** 2)], [lambda y: [-1 * np.sqrt(r_c ** 2 - y ** 2), np.sqrt(r_c ** 2 - y ** 2)],
[-r_c, r_c]], opts={"epsrel": 1e-1})[0] / total, 0, r_max, xtol=0.1) [-r_c, r_c]], opts={"epsrel": 1e-1})[0] / total, 0, r_max, xtol=0.1)