import types
from typing import Optional, Tuple
import numpy as np
from numpy.typing import NDArray
try:
from ..absorption_calculator import (
calculate_absorption_profile_rcwa,
calculate_rat_rcwa,
)
reason_to_exclude = None
except ImportError:
reason_to_exclude = "An installation of S4 has not been found."
from ..registries import register_optics
from ..solar_cell import SolarCell
from ..state import State
from ..structure import Junction, Layer, TunnelJunction
rcwa_options = State()
rcwa_options.size = ((500, 500), (500, 500))
rcwa_options.orders = 4
rcwa_options.theta = 0
rcwa_options.phi = 0
rcwa_options.pol = "u"
rcwa_options.parallel = False
rcwa_options.n_jobs = -1
[docs]@register_optics(name="RCWA", reason_to_exclude=reason_to_exclude)
def solve_rcwa(
solar_cell: SolarCell,
wavelength: NDArray,
position: NDArray,
parallel: bool = False,
size: Tuple[int, int] = ((500, 500), (500, 500)),
orders: int = 4,
theta: float = 0,
phi: float = 0,
pol: str = "u",
n_jobs: int = -1,
rcwa_options: Optional[State] = None,
**kwargs
) -> None:
"""Calculates the RAT of a solar cell object using the RCWA solver.
The SolarCell object is updated with the wavelength, the calculated reflected,
transmitted and absorved ligth. Additionally, each a method to calculate the
absorved ligth per junction and the ligth absorved per later are also added to the
individual junctions.
Args:
solar_cell (SolarCell): A solar_cell object
wavelength (NDArray): Array of wavelegth at which the optics are calculated.
position (NDArray): Array of positions in the z direction to calculate the
absorption vs depth.
parallel (bool, optional): whether or not to execute calculation in parallel
(over wavelengths). Defaults to False.
size (Tuple[int, int], optional): a tuple of 2-D vectors in the format ((ux,
uy), (vx, vy)) giving the x and y components of the lattice unit vectors in
nm. Defaults to ((500, 500), (500, 500)).
orders (int, optional): number of orders to retain in the RCWA calculations.
Defaults to 4.
theta (float, optional): the polar incidence angle, in degrees, with 0 degrees
being normal incidence. Defaults to 0.
phi (float, optional): azimuthal incidence angle (in degrees). Defaults to 0.
pol (str, optional): the polarization of the light ('s', 'p' or 'u'). Defaults
to "u".
n_jobs (int, optional): the 'n_jobs' argument passed to Parallel from the joblib
package. If set to -1, all available CPUs are used, if set to 1 no parallel
computing is executed. The number of CPUs used is given by n_cpus + 1 +
n_jobs. Defaults to -1.
rcwa_options (Optional[State], optional): dictionary of options for S4. Defaults
to None. The list of possible entries and their values is:
* LatticeTruncation: 'Circular' or 'Parallelogramic' (default 'Circular')
* DiscretizedEpsilon: True or False (default False)
* DiscretizationResolution: integer (default value 8)
* PolarizationDecomposition: True or False (default False)
* PolarizationBasis: 'Default' or 'Normal' or 'Jones' (default 'Default')
* LanczosSmoothing: True or False (default False)
* SubpixelSmoothing: True or False (default False)
* ConserveMemory: True or False (default False)
* WeismannFormulation: True or False (default False)
Return:
None
"""
solar_cell.wavelength = wavelength
# We include the shadowing losses
initial = (1 - solar_cell.shading) if hasattr(solar_cell, "shading") else 1
# Now we calculate the absorbed and transmitted light. We first get all the relevant
# parameters from the objects
all_layers = []
n_layers_junction = []
for j, layer_object in enumerate(solar_cell):
# Attenuation due to absorption in the AR coatings or any layer in the front
# that is not part of the junction
if type(layer_object) is Layer:
all_layers.append(layer_object)
n_layers_junction.append(1)
# For each junction, and layer within the junction, we get the absorption
# coefficient and the layer width.
elif type(layer_object) in [TunnelJunction, Junction]:
n_layers_junction.append(len(layer_object))
for i, layer in enumerate(layer_object):
all_layers.append(layer)
# With all the information, we create the optical stack
stack = all_layers
position = position * 1e9
substrate = solar_cell.substrate
incidence = solar_cell.incidence
print("Calculating RAT...")
RAT = calculate_rat_rcwa(
stack,
size,
orders,
wavelength * 1e9,
incidence,
substrate,
theta=theta,
phi=phi,
pol=pol,
parallel=parallel,
user_options=rcwa_options,
)
print("Calculating absorption profile...")
out = calculate_absorption_profile_rcwa(
stack,
size,
orders,
wavelength * 1e9,
RAT["A_pol"],
dist=position,
theta=theta,
phi=phi,
pol=pol,
incidence=incidence,
substrate=substrate,
parallel=parallel,
n_jobs=n_jobs,
user_options=rcwa_options,
)
# With all this information, we are ready to calculate the differential absorption
# function
diff_absorption, _ = calculate_absorption_rcwa(out, initial)
layer = 0
A_per_layer = np.array(RAT["A_per_layer"].T)
# Each building block (layer or junction) needs to have access to the absorbed light
# in its region. We update each object with that information.
for j in range(len(solar_cell)):
solar_cell[j].diff_absorption = diff_absorption
solar_cell[j].absorbed = types.MethodType(absorbed, solar_cell[j])
solar_cell[j].layer_absorption = initial * np.sum(
A_per_layer[layer : (layer + n_layers_junction[j])], axis=0
)
layer = layer + n_layers_junction[j]
solar_cell.reflected = RAT["R"] * initial
solar_cell.absorbed = sum(
[solar_cell[x].layer_absorption for x in np.arange(len(solar_cell))]
)
solar_cell.transmitted = initial - solar_cell.reflected - solar_cell.absorbed
[docs]def absorbed(self, z):
out = self.diff_absorption(self.offset + z) * (z < self.width)
return out.T
[docs]def calculate_absorption_rcwa(tmm_out, initial=1):
all_z = tmm_out["position"] * 1e-9
all_abs = initial * tmm_out["absorption"] / 1e-9
def diff_absorption(z):
idx = all_z.searchsorted(z)
idx = np.where(idx <= len(all_z) - 1, idx, len(all_z) - 1)
idx = np.where(idx > 0, idx, 1)
try:
z1 = all_z[idx - 1]
z2 = all_z[idx]
f = np.divide(z - z1, z2 - z1,
out=np.zeros_like(z), where=np.abs(z2-z1) > 1e-12)
# this is to avoid divide by zero errors (|f| gets very large) when z1 = z2
out = (1-f) * all_abs[:, idx - 1] + f * all_abs[:, idx]
except IndexError:
out = all_abs[:, idx]
return out
all_absorbed = np.trapz(diff_absorption(all_z), all_z)
return diff_absorption, all_absorbed
