transfer_matrix.py

""" This module serves as interface between solcore structures (junctions, layers,
materials...) and the transfer matrix package developed by Steven Byrnes and included in
the PyPi repository.

"""
import numpy as np
import solcore

from warnings import warn
from collections.abc import Hashable

from solcore.interpolate import interp1d
from solcore.structure import ToStructure
from solcore.absorption_calculator import tmm_core_vec as tmm
from functools import lru_cache, wraps

degree = np.pi / 180


def np_cache(function):
    """This function was taken from
    https://stackoverflow.com/questions/52331944/cache-decorator-for-numpy-arrays/52332109#52332109 # noqa: E501

    Creates a cacheable version of a function which takes a 1D numpy array as input, by
    using a wrapping function which converts the array to a tuple. It returns a
    function which returns the same output as the input function, but can be cached,
    avoiding a bottleneck when optical constants in a material are looked up repeatedly.

    If the input argument is hashable already - eg. a single float number - then the
    function is not chached and is returned "as is".

    :param: function: the function of which a cacheable version is to be created
    :return: wrapper: the cacheable version of the function"""

    @lru_cache()
    def cached_wrapper(hashable_array):
        array = np.array(hashable_array)
        return function(array)

    @wraps(function)
    def wrapper(array):
        if isinstance(array, Hashable):
            return function(array)
        else:
            return cached_wrapper(tuple(array))

    # copy lru_cache attributes over too
    wrapper.cache_info = cached_wrapper.cache_info
    wrapper.cache_clear = cached_wrapper.cache_clear

    return wrapper


class OptiStack(object):
    """Class that contains an optical structure: a sequence of layers with a thickness
    and a complex refractive index.

    It serves as an intermediate step between solcore layers and materials and the
    stack of thicknesses and n and k values necessary to run calculations involving TMM.
    When creating an OptiStack object, the thicknesses of all the layers forming the
    Solcore structure and the optical data of the materials of the layers are extracted
    and arranged in such a way they can be easily and fastly read by the TMM functions.

    In addition to a solcore structure with Layers, it can also take a list where each
    element represent a layer written as a list and contains the layer thickness and
    the dielectrical model, the raw n and k data as a function
    of wavelengths, or a whole Device structure as the type used in the PDD model.

    In summary, this class acepts:

        - A solcore structure with layers
        - A list where each element is [thickness, DielectricModel]
        - A list where each element is [thickness, wavelength, n, k]
        - A list mixing the above:
            [ [thickness, DielectricModel],
              [thickness, wavelength, n, k],
              solcore.Layer,
              solcore.Layer ]

    This allows for maximum flexibility when creating the optical model, allowing to
    construct the stack with experimental data, modelled data and known material
    properties from the database.

    Yet anther way of defining the layers mixes experimental data with a DielectricModel
    within the same layer but in spectrally distinct regions. The syntaxis for the
    layer is:

    layer = [thickness, wavelength, n, k, DielectricModel, mixing]

    where mixing is a list containing three elements:
    [the mixing point (nm), the mixing width (nm),  zero or one]
    depending if the mixing function should be increasing with the wavelength or
    decreasing. If increasing (zero), the Dielectric model will be used at long
    wavelengths and the experimental data at short wavelengths. If decreasing (one)
    the oposite is done. The mixing point and mixing width control how smooth is the
    transition between one and the other type of data.

    Extra layers such as he semi-infinite, air-like first and last medium, and a back
    highly absorbing layer are included at runtime to fulfill the requirements of the
    TMM solver or to solve some of its limitations.
    """

    def __init__(
        self,
        structure=(),
        no_back_reflection=False,
        substrate=None,
        incidence=None,
        **kwargs,
    ):
        """Class constructor. It takes a Solcore structure and extract the thickness
        and optical data from the Layers and the materials. Option is given to
        indicate if the reflection from the back of the structure must be suppressed,
        useful for ellipsometry calculations. This is done by creating an artificial
        highly absorbing but not reflecting layer just at the back.

        Alternatively, it can take simply a list of [thickness, DielectricModel] or
        [thickness, wavelength, n, k] for each layer accounting for the refractive
        index of the layers. The three options can be mixed for maximum flexibility.

        :param structure: A list with one or more layers.
        :param no_back_reflection: If reflection from the back must be suppressed.
            Default=False.
        :param substrate: a semi-infinite transmission medium. Note that if
            no_back_reflection is set to True, adding a substrate won't make any
         difference.
        :param incidence: a semi-infinite incidence medium. Note that add things may
            happen if this material is absorbing
        """

        self.widths = []
        self.n_data = []
        self.k_data = []
        self.models = []
        self.layers = []
        self.substrate = substrate
        self.incidence = incidence

        self.num_layers = 0
        self.add_layers(structure)

        self.no_back_reflection = no_back_reflection

        if "no_back_reflexion" in kwargs:
            warn(
                "The no_back_reflexion warning is deprecated. "
                "Use no_back_reflection instead.",
                FutureWarning,
            )
            self.no_back_reflection = kwargs["no_back_reflexion"]

    def get_indices(self, wl):
        """Returns the complex refractive index of the stack.

        :param wl: Wavelength of the light in nm.
        :return: A list with the complex refractive index of each layer, including the
        semi-infinite front and back layers and, opionally, the back absorbing layer
        used to suppress back surface relfexion.
        """

        out = []
        wl_m = solcore.si(wl, "nm")

        if hasattr(self, "n_sub"):
            n1 = self.n_sub(wl_m) + self.k_sub(wl_m) * 1.0j
        else:
            if hasattr(wl, "size"):
                n1 = np.ones_like(wl, dtype=complex)
            else:
                n1 = 1

        # incidence medium!
        if hasattr(self, "n_sup"):
            n0 = self.n_sup(
                wl_m
            )  # + self.k_sup(wl_m)*1.0j ignore complex part for now to avoid errors
        else:
            if hasattr(wl, "size"):
                n0 = np.ones_like(wl, dtype=complex)
            else:
                n0 = 1

        for i in range(self.num_layers):
            out.append(self.n_data[i](wl_m) + self.k_data[i](wl_m) * 1.0j)

        # substrate irrelevant if no_back_reflection = True
        if self.no_back_reflection:
            return (
                [n0]
                + out
                + [self.n_data[-1](wl_m) + self._k_absorbing(wl_m) * 1.0j, n1]
            )  # look at last entry in stack,
            # make high;y absorbing layer based on it.

        else:
            return [n0] + out + [n1]

    def get_widths(self):
        """Returns the widths of the layers of the stack.

        :return: A list with the widths each layer, including the semi-infinite front
        and back layers and, opionally, the back absorbing layer used to suppress
        back surface relfection, defined as 1 mm thick.
        """

        if self.no_back_reflection:
            return [np.inf] + self.widths + [1e6, np.inf]
        else:
            return [np.inf] + self.widths + [np.inf]

    def _k_absorbing(self, wl):
        """k value of the back highly absorbing layer. It is the maximum between the
        bottom layer of the stack or a finite, small value that will absorb all light
        within the absorbing layer thickness.

        :param wl: Wavelength of the light in nm.
        :return: The k value at each wavelength.
        """
        return np.maximum(wl / 1e-3, self.k_data[-1](wl))

    @staticmethod
    def _k_dummy(wl):
        """Dummy k value to be used with the dielectric model, which produces the
        refractive index as a complex number.

        :param wl: Wavelength of the light in nm.
        :return: The k value at each wavelength... set to zero.
        """
        return 0.0

    def add_layers(self, layers):
        """Generic function to add layers to the OptiStack. Internally, it calls
        add_solcore_layer, add_modelled_layer or add_raw_nk_layer.

        :param layers: A list with the layers to add (even if it is just one layer)
            It can be one or more and it can be mixed, Solcore-based and modelled
            layers.
        :return: None
        """
        try:
            # If the input is a whole device structure, we get just the layers
            # information
            if type(layers) is dict:
                layers = ToStructure(layers)

            if self.substrate is not None:
                self.n_sub = self.substrate.n
                self.k_sub = self.substrate.k

            if self.incidence is not None:
                self.n_sup = self.incidence.n
                self.k_sup = self.incidence.k

            for layer in layers:
                self.layers.append(layer)
                if "Layer" in str(type(layer)):
                    self._add_solcore_layer(layer)
                elif "DielectricConstantModel" in str(type(layer[1])):
                    self._add_modelled_layer(layer)
                else:
                    self._add_raw_nk_layer(layer)

                self.num_layers += 1

        except Exception as err:
            print("Error when adding a new layer to the OptiStack. {}".format(err))

    def remove_layer(self, idx):
        """Removes layer with index idx from the OptiStack

        :param idx: Index of the layer to remove
        :return: None
        """
        if idx >= self.num_layers:
            print(
                "Error when removing layers. idx must be: 0 <= idx <= {}.".format(
                    self.num_layers - 1
                )
            )
            return

        self.widths.pop(idx)
        self.models.pop(idx)
        self.n_data.pop(idx)
        self.k_data.pop(idx)
        self.num_layers -= 1

    def swap_layers(self, idx1, idx2):
        """Swaps two layers in the OptiStack.

        :param idx1: The index of one of the layers.
        :param idx2: The index of the other.
        :return: None
        """
        if idx1 >= self.num_layers or idx2 >= self.num_layers:
            print(
                "Error when removing layers. idx must be: 0 <= idx1, idx2 <= {}.".
                format(self.num_layers - 1)
            )
            return

        self.widths[idx1], self.widths[idx2] = self.widths[idx2], self.widths[idx1]
        self.models[idx1], self.models[idx2] = self.models[idx2], self.models[idx1]
        self.n_data[idx1], self.n_data[idx2] = self.n_data[idx2], self.n_data[idx1]
        self.k_data[idx1], self.k_data[idx2] = self.k_data[idx2], self.k_data[idx1]

    def set_widths(self, widths):
        """Changes the widths of the layers in the stack.

        :param: widths: a list or array of widths, length equal to the number of layers
        :return: None"""

        if type(widths) is np.ndarray:
            widths = widths.tolist()

        assert len(widths) == self.num_layers, (
            "Error: The list of widths must have as many elements (now {}) as the "
            "number of layers (now {}).".format(len(widths), self.num_layers)
        )

        self.widths = widths

    def _add_solcore_layer(self, layer):
        """Adds a Solcore layer to the end (bottom) of the stack, extracting its
        thickness and n and k data.

        :param layer: The Solcore layer
        :return: None
        """
        self.widths.append(solcore.asUnit(layer.width, "nm"))
        self.models.append([])
        self.n_data.append(np_cache(layer.material.n))
        self.k_data.append(np_cache(layer.material.k))

    def _add_modelled_layer(self, layer):
        """Adds a layer to the end (bottom) of the stack. The layer must be defined as
        a list containing the layer thickness in nm and a dielectric model.

        :param layer: The new layer to add as [thickness, DielectricModel]
        :return: None
        """
        self.widths.append(layer[0])
        self.models.append(layer[1])
        self.n_data.append(np_cache(self.models[-1].n_and_k))
        self.k_data.append(np_cache(self._k_dummy))

    def _add_raw_nk_layer(self, layer):
        """Adds a layer to the end (bottom) of the stack. The layer must be defined as
        a list containing the layer thickness in nm, the wavelength, the n and the k
        data as array-like objects.

        :param layer: The new layer to add as [thickness, wavelength, n, k]
        :return: None
        """
        # We make sure that the wavelengths are increasing, reversing the arrays
        # otherwise.
        if layer[1][0] > layer[1][-1]:
            layer[1] = layer[1][::-1]
            layer[2] = layer[2][::-1]
            layer[3] = layer[3][::-1]

        self.widths.append(layer[0])

        if len(layer) >= 5:
            self.models.append(layer[4])
            c = solcore.si(layer[5][0], "nm")
            w = solcore.si(layer[5][1], "nm")
            d = layer[5][2]  # = 0 for increasing, =1 for decreasing

            def mix(x):
                out = 1 + np.exp(-(x - c) / w)
                out = d + (-1) ** d * 1 / out

                return out

            n_data = np_cache(
                lambda x: self.models[-1].n_and_k(x) * mix(x)
                + (1 - mix(x))
                * interp1d(
                    x=solcore.si(layer[1], "nm"), y=layer[2], fill_value=layer[2][-1]
                )(x)
            )
            k_data = np_cache(
                lambda x: interp1d(
                    x=solcore.si(layer[1], "nm"), y=layer[3], fill_value=layer[3][-1]
                )(x)
            )

            self.n_data.append(n_data)
            self.k_data.append(k_data)

        else:
            self.models.append([])
            self.n_data.append(
                np_cache(
                    interp1d(
                        x=solcore.si(layer[1], "nm"),
                        y=layer[2],
                        fill_value=layer[2][-1],
                    )
                )
            )
            self.k_data.append(
                np_cache(
                    interp1d(
                        x=solcore.si(layer[1], "nm"),
                        y=layer[3],
                        fill_value=layer[3][-1],
                    )
                )
            )


def calculate_rat(
    structure,
    wavelength,
    angle=0,
    pol="u",
    coherent=True,
    coherency_list=None,
    no_back_reflection=True,
    **kwargs,
):
    """Calculates the reflected, absorbed and transmitted intensity of the structure
    for the wavelengths and angles defined.

    :param structure: A solcore Structure object with layers and materials or a
        OptiStack object.
    :param wavelength: Wavelengths (in nm) in which calculate the data. An array.
    :param angle: Angle (in degrees) of the incident light.
        Default: 0 (normal incidence).
    :param pol: Polarisation of the light: 's', 'p' or 'u'. Default: 'u' (unpolarised).
    :param coherent: If the light is coherent or not. If not, a coherency list
        must be added.
    :param coherency_list: A list indicating in which layers light should be treated as
        coherent ('c') and in which incoherent ('i'). It needs as many elements as
        layers in the structure.
    :param no_back_reflection: If reflection from the back must be supressed.
        Default=True.
    :return: A dictionary with the R, A and T at the specified wavelengths and angle.
    """
    num_wl = len(wavelength)

    if "no_back_reflexion" in kwargs:
        warn(
            "The no_back_reflexion argument is deprecated. "
            "Use no_back_reflection instead.",
            FutureWarning,
        )
        no_back_reflection = kwargs["no_back_reflexion"]

    if "OptiStack" in str(type(structure)):
        stack = structure
        stack.no_back_reflection = no_back_reflection
    else:
        stack = OptiStack(structure, no_back_reflection=no_back_reflection)

    if not coherent:
        if coherency_list is not None:
            assert len(coherency_list) == stack.num_layers, (
                "Error: The coherency list must have as many elements (now {}) as the "
                "number of layers (now {}).".format(
                    len(coherency_list), stack.num_layers
                )
            )

            if stack.no_back_reflection:
                coherency_list = ["i"] + coherency_list + ["i", "i"]
            else:
                coherency_list = ["i"] + coherency_list + ["i"]

        else:
            raise Exception(
                "Error: For incoherent or partly incoherent calculations you must "
                "supply the coherency_list parameter with as many elements as the "
                "number of layers in the structure"
            )

    output = {
        "R": np.zeros(num_wl),
        "A": np.zeros(num_wl),
        "T": np.zeros(num_wl),
        "all_p": [],
        "all_s": [],
        "out": [],
        "out_s": [],
        "out_p": [],
        "A_per_layer_s": [],
        "A_per_layer_p": [],
    }

    if pol in "sp":
        if coherent:
            out = tmm.coh_tmm(
                pol,
                stack.get_indices(wavelength),
                stack.get_widths(),
                angle * degree,
                wavelength,
            )
            A_per_layer = tmm.absorp_in_each_layer(out)
            output["R"] = out["R"]
            output["A"] = 1 - out["R"] - out["T"]
            output["T"] = out["T"]
            output["A_per_layer"] = A_per_layer
            output["out"] = out
        else:
            out = tmm.inc_tmm(
                pol,
                stack.get_indices(wavelength),
                stack.get_widths(),
                coherency_list,
                angle * degree,
                wavelength,
            )
            A_per_layer = np.array(tmm.inc_absorp_in_each_layer(out))
            output["R"] = out["R"]
            output["A"] = 1 - out["R"] - out["T"]
            output["T"] = out["T"]
            output["A_per_layer"] = A_per_layer
            output["out"] = out
    else:
        if coherent:
            out_p = tmm.coh_tmm(
                "p",
                stack.get_indices(wavelength),
                stack.get_widths(),
                angle * degree,
                wavelength,
            )
            out_s = tmm.coh_tmm(
                "s",
                stack.get_indices(wavelength),
                stack.get_widths(),
                angle * degree,
                wavelength,
            )
            A_per_layer_p = tmm.absorp_in_each_layer(out_p)
            A_per_layer_s = tmm.absorp_in_each_layer(out_s)
            output["R"] = 0.5 * (out_p["R"] + out_s["R"])
            output["T"] = 0.5 * (out_p["T"] + out_s["T"])
            output["A"] = 1 - output["R"] - output["T"]
            output["A_per_layer"] = 0.5 * (A_per_layer_p + A_per_layer_s)

            output["out_s"] = out_s
            output["out_p"] = out_p
            output["A_per_layer_s"] = A_per_layer_s
            output["A_per_layer_p"] = A_per_layer_p

        else:
            out_p = tmm.inc_tmm(
                "p",
                stack.get_indices(wavelength),
                stack.get_widths(),
                coherency_list,
                angle * degree,
                wavelength,
            )
            out_s = tmm.inc_tmm(
                "s",
                stack.get_indices(wavelength),
                stack.get_widths(),
                coherency_list,
                angle * degree,
                wavelength,
            )

            A_per_layer_p = np.array(tmm.inc_absorp_in_each_layer(out_p))
            A_per_layer_s = np.array(tmm.inc_absorp_in_each_layer(out_s))

            output["R"] = 0.5 * (out_p["R"] + out_s["R"])
            output["T"] = 0.5 * (out_p["T"] + out_s["T"])
            output["A"] = 1 - output["R"] - output["T"]
            output["all_p"] = out_p["power_entering_list"]
            output["all_s"] = out_s["power_entering_list"]
            output["A_per_layer"] = 0.5 * (A_per_layer_p + A_per_layer_s)

            output["out_s"] = out_s
            output["out_p"] = out_p
            output["A_per_layer_s"] = A_per_layer_s
            output["A_per_layer_p"] = A_per_layer_p

    return output


def calculate_ellipsometry(
    structure, wavelength, angle, no_back_reflection=True, **kwargs
):
    """Calculates the ellipsometric parameters psi and delta. It can only deal with
    coherent light and the whole stack (including back surface) is considered,
    so caution must be taken when comparing the simulated results with experiments
    where the back surface is rough or layers are thick and coherent light propagation
    makes no sense.

    The optional argument no_back_reflection can be included to add an extra layer on
    the back absorbing all light that reaches that position without any reflection,
    to remove the reflection from the back surface.

    :param structure: A solcore structure with layers and materials.
    :param wavelength: Wavelengths (in nm) in which calculate the data. An array.
    :param angle: A tupple or list with the angles (in degrees) in which to calculate
        the data.
    :param no_back_reflection: If reflection from the back must be suppressed.
        Default=True.
    :return: A dictionary with psi and delta at the specified wavelengths and angles
        (2D arrays).
    """

    if "no_back_reflexion" in kwargs:
        warn(
            "The no_back_reflexion argument is deprecated. "
            "Use no_back_reflection instead.",
            FutureWarning,
        )
        no_back_reflection = kwargs["no_back_reflexion"]

    num_wl = len(wavelength)
    num_ang = len(angle)

    if "OptiStack" in str(type(structure)):
        stack = structure
        stack.no_back_reflection = no_back_reflection
    else:
        if hasattr(structure, "substrate"):
            substrate = structure.substrate
        else:
            substrate = None
        stack = OptiStack(
            structure, no_back_reflection=no_back_reflection, substrate=substrate
        )

    output = {"psi": np.zeros((num_wl, num_ang)), "Delta": np.zeros((num_wl, num_ang))}

    for i, ang in enumerate(angle):
        out = tmm.ellips(
            stack.get_indices(wavelength), stack.get_widths(), ang * degree, wavelength
        )
        output["psi"][:, i] = out["psi"] / degree

        # We revere the sign of Delta in order to use Woollam sign convention
        output["Delta"][:, i] = -out["Delta"] / degree

        output["Delta"][:, i] = np.where(
            output["Delta"][:, i] > 0, -output["Delta"][:, i], output["Delta"][:, i]
        )
        output["Delta"][:, i] = np.where(
            output["Delta"][:, i] < 180,
            180 - output["Delta"][:, i],
            output["Delta"][:, i],
        )

    return output


def calculate_absorption_profile(
    structure,
    wavelength,
    z_limit=None,
    steps_size=2,
    dist=None,
    no_back_reflection=True,
    angle=0,
    pol="u",
    coherent=True,
    coherency_list=None,
    zero_threshold=1e-6,
    RAT_out=None,
    **kwargs,
):
    """It calculates the absorbed energy density within the material.
    From the documentation:

    'In principle this has units of [power]/[volume], but we can express it as a
    multiple of incoming light power density on the material, which has units [
    power]/[area], so that absorbed energy density has units of 1/[length].'

    Integrating this absorption profile in the whole stack gives the same result that
    the absorption obtained with calculate_rat as long as the spatial mesh (controlled
    by steps_thinest_layer) is fine enough. If the structure is very thick and the
    mesh not thin enough, the calculation might diverge at short wavelengths.

    :param structure: A solcore structure with layers and materials.
    :param wavelength: Wavelengths in which calculate the data (in nm). An array
    :param z_limit: Maximum value in the z direction
    :param steps_size: if the dist is not specified, the step size in nm to use in the
        depth-dependent calculation
    :param dist: the positions (in nm) at which to calculate depth-dependent absorption
    :param no_back_reflection: whether to suppress reflections from the back interface
        (True) or not (False)
    :param angle: incidence of angle in degrees
    :param pol: polarization of incident light: 's', 'p' or 'u' (unpolarized)
    :param coherent: True if all the layers are to be treated coherently,
        False otherwise
    :param coherency_list: if coherent is False, a list of 'c' (coherent) or
        'i' (incoherent) for each layer
    :param zero_threshold: when the fraction of incident light absorbed in a layer is
        less than this value, the absorption profile is completely set to zero for
        both coherent and incoherent calculations. This is applied on a
        wavelength-by-wavelength basis and is intended to prevent errors where
        integrating a weak absorption profile in a layer over many
        points leads to calculated EQE > total absorption in that layer.
    :param RAT_out: output from calculate_rat for the same stack & options
    :return: A dictionary containing the positions (in nm) and a 2D array with the
        absorption in the structure as a function of the position and the wavelength.
    """

    if "no_back_reflexion" in kwargs:
        warn(
            "The no_back_reflexion warning is deprecated. "
            "Use no_back_reflection instead.",
            FutureWarning,
        )
        no_back_reflection = kwargs["no_back_reflexion"]

    if RAT_out is None:
        # R, A per layer, T not yet calculated, calculate now
        RAT_out = calculate_rat(
            structure,
            wavelength,
            angle,
            pol=pol,
            coherent=coherent,
            coherency_list=coherency_list,
            no_back_reflection=no_back_reflection,
        )

    num_wl = len(wavelength)

    if "OptiStack" in str(type(structure)):
        stack = structure
        stack.no_back_reflection = no_back_reflection
    else:
        stack = OptiStack(structure, no_back_reflection=no_back_reflection)

    if dist is None:
        if z_limit is None:
            z_limit = np.sum(np.array(stack.widths))
        dist = np.arange(0, z_limit, steps_size)

    if not coherent:
        if coherency_list is not None:
            if stack.no_back_reflection:
                coherency_list = ["i"] + coherency_list + ["i", "i"]
            else:
                coherency_list = ["i"] + coherency_list + ["i"]

        else:
            raise Exception(
                "Error: For incoherent or partly incoherent calculations you must "
                "supply the coherency_list parameter with as many elements as the "
                "number of layers in the structure"
            )

    output = {"position": dist, "absorption": np.zeros((num_wl, len(dist)))}

    layer, d_in_layer = tmm.find_in_structure_with_inf(stack.get_widths(), dist)

    if pol in "sp":
        if coherent:
            A_per_layer = RAT_out["A_per_layer"]
            no_abs_in_layer = np.where(A_per_layer[:-1, :] < zero_threshold)
            RAT_out["out"]["vw_list"][no_abs_in_layer[0], no_abs_in_layer[1], :] = 0

            data = tmm.position_resolved(layer, d_in_layer, RAT_out["out"])
            output["absorption"] = data["absor"]

        else:
            data = tmm.inc_position_resolved(
                layer,
                d_in_layer,
                RAT_out["out"],
                coherency_list,
                4 * np.pi * np.imag(stack.get_indices(wavelength)) / wavelength,
                zero_threshold,
            )
            output["absorption"] = data

    else:
        if coherent:
            A_per_layer_s = RAT_out["A_per_layer_s"]
            A_per_layer_p = RAT_out["A_per_layer_p"]
            no_abs_in_layer_s = np.where(A_per_layer_s[:-1, :] < zero_threshold)
            no_abs_in_layer_p = np.where(A_per_layer_p[:-1, :] < zero_threshold)
            RAT_out["out_s"]["vw_list"][
                no_abs_in_layer_s[0], no_abs_in_layer_s[1], :
            ] = 0
            RAT_out["out_p"]["vw_list"][
                no_abs_in_layer_p[0], no_abs_in_layer_p[1], :
            ] = 0

            data_s = tmm.position_resolved(layer, d_in_layer, RAT_out["out_s"])
            data_p = tmm.position_resolved(layer, d_in_layer, RAT_out["out_p"])

            output["absorption"] = 0.5 * (data_s["absor"] + data_p["absor"])

        else:

            data_s = tmm.inc_position_resolved(
                layer,
                d_in_layer,
                RAT_out["out_s"],
                coherency_list,
                4 * np.pi * np.imag(stack.get_indices(wavelength)) / wavelength,
                zero_threshold,
            )
            data_p = tmm.inc_position_resolved(
                layer,
                d_in_layer,
                RAT_out["out_p"],
                coherency_list,
                4 * np.pi * np.imag(stack.get_indices(wavelength)) / wavelength,
                zero_threshold,
            )

            output["absorption"] = 0.5 * (data_s + data_p)

    return output


if __name__ == "__main__":
    import matplotlib.pyplot as plt
    from solcore import material, si
    from solcore.structure import Layer, Structure

    GaAs = material("GaAs")(T=300)
    InGaAs = material("InGaAs")(T=300, In=0.1)

    my_structure = Structure(
        [
            Layer(si(3000, "nm"), material=InGaAs),
            Layer(si(30, "um"), material=GaAs),
        ]
    )

    wavelength = np.linspace(450, 1100, 300)

    out = calculate_rat(
        my_structure, wavelength, coherent=True, no_back_reflection=False
    )
    # #
    # plt.plot(wavelength, out['R'], 'b', label='Reflexion')
    # plt.plot(wavelength, out['A'], 'r', label='Absorption')
    # plt.plot(wavelength, out['T'], 'g', label='Transmission')
    # plt.legend()
    # plt.show()

    angles = [60, 65, 70]
    out = calculate_ellipsometry(my_structure, wavelength, angle=angles)
    #
    plt.plot(wavelength, out["psi"][:, 0], "b", label="psi")
    plt.plot(wavelength, out["Delta"][:, 0], "r", label="Delta")
    for i in range(1, len(angles)):
        plt.plot(wavelength, out["psi"][:, i], "b")
        plt.plot(wavelength, out["Delta"][:, i], "r")
    #
    # plt.legend()

    # out = calculate_absorption_profile_2(my_structure, wavelength, z_limit=3000)
    # # print(tuple(out['absorption'][0]))
    # # plt.plot(out['position'], out['absorption'][0])
    # A = np.zeros_like(wavelength)
    # #
    # for i, absorption in enumerate(out['absorption'][:]):
    #     A[i] = np.trapz(absorption, out['position'])
    # #
    # plt.plot(wavelength, A, 'k', label='Integrated Abs')

    #
    # plt.contourf(out['position'], wavelength, out['absorption'], 200)
    plt.legend()
    plt.show()