Added optika.sensors.E2VCCDAIAMaterial (#7)

Added `optika.sensors.E2VCCDAIAMaterial`
sun-data · Jan 15, 2024 · 97343a8 · 97343a8
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diff --git a/docs/refs.bib b/docs/refs.bib
@@ -98,3 +98,32 @@ @techreport{Moody2017
     year={2017},
     url={https://oro.open.ac.uk/49003/1/Moody%202017%20-%20SXRQE_WhitePaper.pdf},
 }
+@ARTICLE{Boerner2012,
+       author = {{Boerner}, Paul and {Edwards}, Christopher and {Lemen}, James and {Rausch}, Adam and {Schrijver}, Carolus and {Shine}, Richard and {Shing}, Lawrence and {Stern}, Robert and {Tarbell}, Theodore and {Title}, Alan and {Wolfson}, C. Jacob and {Soufli}, Regina and {Spiller}, Eberhard and {Gullikson}, Eric and {McKenzie}, David and {Windt}, David and {Golub}, Leon and {Podgorski}, William and {Testa}, Paola and {Weber}, Mark},
+        title = "{Initial Calibration of the Atmospheric Imaging Assembly (AIA) on the Solar Dynamics Observatory (SDO)}",
+      journal = {\solphys},
+     keywords = {Instrumentation, EUV, Soft X-ray, Chromosphere, Corona, Transition region},
+         year = 2012,
+        month = jan,
+       volume = {275},
+       number = {1-2},
+        pages = {41-66},
+          doi = {10.1007/s11207-011-9804-8},
+       adsurl = {https://ui.adsabs.harvard.edu/abs/2012SoPh..275...41B},
+      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
+}
+@ARTICLE{Lemen2012,
+       author = {{Lemen}, James R. and {Title}, Alan M. and {Akin}, David J. and {Boerner}, Paul F. and {Chou}, Catherine and {Drake}, Jerry F. and {Duncan}, Dexter W. and {Edwards}, Christopher G. and {Friedlaender}, Frank M. and {Heyman}, Gary F. and {Hurlburt}, Neal E. and {Katz}, Noah L. and {Kushner}, Gary D. and {Levay}, Michael and {Lindgren}, Russell W. and {Mathur}, Dnyanesh P. and {McFeaters}, Edward L. and {Mitchell}, Sarah and {Rehse}, Roger A. and {Schrijver}, Carolus J. and {Springer}, Larry A. and {Stern}, Robert A. and {Tarbell}, Theodore D. and {Wuelser}, Jean-Pierre and {Wolfson}, C. Jacob and {Yanari}, Carl and {Bookbinder}, Jay A. and {Cheimets}, Peter N. and {Caldwell}, David and {Deluca}, Edward E. and {Gates}, Richard and {Golub}, Leon and {Park}, Sang and {Podgorski}, William A. and {Bush}, Rock I. and {Scherrer}, Philip H. and {Gummin}, Mark A. and {Smith}, Peter and {Auker}, Gary and {Jerram}, Paul and {Pool}, Peter and {Soufli}, Regina and {Windt}, David L. and {Beardsley}, Sarah and {Clapp}, Matthew and {Lang}, James and {Waltham}, Nicholas},
+        title = "{The Atmospheric Imaging Assembly (AIA) on the Solar Dynamics Observatory (SDO)}",
+      journal = {\solphys},
+     keywords = {Solar corona, Solar instrumentation, Solar imaging, Extreme ultraviolet},
+         year = 2012,
+        month = jan,
+       volume = {275},
+       number = {1-2},
+        pages = {17-40},
+          doi = {10.1007/s11207-011-9776-8},
+       adsurl = {https://ui.adsabs.harvard.edu/abs/2012SoPh..275...17L},
+      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
+}
+
diff --git a/optika/sensors/_materials/__init__.py b/optika/sensors/_materials/__init__.py
@@ -1,2 +1,3 @@
 from ._materials import *
 from ._e2v_ccd97 import *
+from ._e2v_ccd_aia import *
diff --git a/optika/sensors/_materials/_e2v_ccd97/_e2v_ccd97.py b/optika/sensors/_materials/_e2v_ccd97/_e2v_ccd97.py
@@ -1,22 +1,19 @@
-import functools
 import pathlib
 import numpy as np
-import scipy.optimize
 import astropy.units as u
 import named_arrays as na
-from .._materials import quantum_efficiency_effective
-from .._materials import AbstractBackilluminatedCCDMaterial
+from .._materials import AbstractStern1994BackilluminatedCCDMaterial
 
 __all__ = [
     "E2VCCD97Material",
 ]
 
 
 class E2VCCD97Material(
-    AbstractBackilluminatedCCDMaterial,
+    AbstractStern1994BackilluminatedCCDMaterial,
 ):
     """
-    A model of the light-sensitive material of an e2v CCD90 sensor based on
+    A model of the light-sensitive material of an e2v CCD97 sensor based on
     measurements by :cite:t:`Moody2017`.
 
     Examples
@@ -96,6 +93,48 @@ class E2VCCD97Material(
     .. jupyter-execute::
 
         material_ccd97.cce_backsurface
+
+    Plot the effective quantum efficiency of the fit to this data vs. the fit
+    to the data in :class:`optika.sensors.E2VCCDAIAMaterial`
+
+    .. jupyter-execute::
+
+        material_ccd_aia = optika.sensors.E2VCCDAIAMaterial()
+
+        qe_fit_aia = material_ccd_aia.quantum_efficiency_effective(
+            rays=optika.rays.RayVectorArray(
+                wavelength=wavelength_fit,
+                direction=na.Cartesian3dVectorArray(0, 0, 1),
+            ),
+            normal=na.Cartesian3dVectorArray(0, 0, -1),
+        )
+
+        with astropy.visualization.quantity_support():
+            fig, ax = plt.subplots(constrained_layout=True)
+            na.plt.scatter(
+                wavelength_measured,
+                qe_measured,
+                label="Moody 2017 measured",
+            )
+            na.plt.plot(
+                wavelength_fit,
+                qe_fit,
+                label="Moody 2017 fit",
+            )
+            na.plt.scatter(
+                material_ccd_aia.quantum_efficiency_measured.inputs,
+                material_ccd_aia.quantum_efficiency_measured.outputs,
+                label="Boerner 2012 measured",
+            )
+            na.plt.plot(
+                wavelength_fit,
+                qe_fit_aia,
+                label="Boerner 2012 fit",
+            )
+            ax.set_xscale("log")
+            ax.set_xlabel(f"wavelength ({wavelength_fit.unit:latex_inline})")
+            ax.set_ylabel("quantum efficiency")
+            ax.legend()
     """
 
     @property
@@ -112,73 +151,3 @@ def quantum_efficiency_measured(self) -> na.FunctionArray:
             inputs=na.ScalarArray(wavelength, axes="wavelength"),
             outputs=na.ScalarArray(qe, axes="wavelength"),
         )
-
-    @functools.cached_property
-    def _quantum_efficiency_fit(self) -> dict[str, float | u.Quantity]:
-        qe_measured = self.quantum_efficiency_measured
-
-        unit_thickness_oxide = u.AA
-        unit_thickness_implant = u.AA
-        unit_thickness_substrate = u.um
-
-        def eqe_rms_difference(x: tuple[float, float, float, float]):
-            (
-                thickness_oxide,
-                thickness_implant,
-                thickness_substrate,
-                cce_backsurface,
-            ) = x
-            qe_fit = quantum_efficiency_effective(
-                wavelength=qe_measured.inputs,
-                direction=na.Cartesian3dVectorArray(0, 0, 1),
-                thickness_oxide=thickness_oxide << unit_thickness_oxide,
-                thickness_implant=thickness_implant << unit_thickness_implant,
-                thickness_substrate=thickness_substrate << unit_thickness_substrate,
-                cce_backsurface=cce_backsurface,
-            )
-
-            return np.sqrt(np.mean(np.square(qe_measured.outputs - qe_fit))).ndarray
-
-        thickness_oxide_guess = 50 * u.AA
-        thickness_implant_guess = 2317 * u.AA
-        thickness_substrate_guess = 7 * u.um
-        cce_backsurface_guess = 0.21
-
-        fit = scipy.optimize.minimize(
-            fun=eqe_rms_difference,
-            x0=[
-                thickness_oxide_guess.to_value(unit_thickness_oxide),
-                thickness_implant_guess.to_value(unit_thickness_implant),
-                thickness_substrate_guess.to_value(unit_thickness_substrate),
-                cce_backsurface_guess,
-            ],
-            method="nelder-mead",
-        )
-
-        thickness_oxide, thickness_implant, thickness_substrate, cce_backsurface = fit.x
-        thickness_oxide = thickness_oxide << unit_thickness_oxide
-        thickness_implant = thickness_implant << unit_thickness_implant
-        thickness_substrate = thickness_substrate << unit_thickness_substrate
-
-        return dict(
-            thickness_oxide=thickness_oxide,
-            thickness_implant=thickness_implant,
-            thickness_substrate=thickness_substrate,
-            cce_backsurface=cce_backsurface,
-        )
-
-    @property
-    def thickness_oxide(self) -> u.Quantity:
-        return self._quantum_efficiency_fit["thickness_oxide"]
-
-    @property
-    def thickness_implant(self) -> u.Quantity:
-        return self._quantum_efficiency_fit["thickness_implant"]
-
-    @property
-    def thickness_substrate(self) -> u.Quantity:
-        return self._quantum_efficiency_fit["thickness_substrate"]
-
-    @property
-    def cce_backsurface(self) -> float:
-        return self._quantum_efficiency_fit["cce_backsurface"]
diff --git a/optika/sensors/_materials/_e2v_ccd97/_e2v_ccd97_test.py b/optika/sensors/_materials/_e2v_ccd97/_e2v_ccd97_test.py
@@ -1,6 +1,6 @@
 import pytest
 import optika
-from .._materials_test import AbstractTestAbstractBackilluminatedCCDMaterial
+from .._materials_test import AbstractTestAbstractStern1994BackilluminatedCCDMaterial
 
 
 @pytest.mark.parametrize(
@@ -10,6 +10,6 @@
     ],
 )
 class TestE2VCCD97Material(
-    AbstractTestAbstractBackilluminatedCCDMaterial,
+    AbstractTestAbstractStern1994BackilluminatedCCDMaterial,
 ):
     pass
diff --git a/optika/sensors/_materials/_e2v_ccd_aia/__init__.py b/optika/sensors/_materials/_e2v_ccd_aia/__init__.py
@@ -0,0 +1 @@
+from ._e2v_ccd_aia import *
diff --git a/optika/sensors/_materials/_e2v_ccd_aia/_e2v_ccd_aia.py b/optika/sensors/_materials/_e2v_ccd_aia/_e2v_ccd_aia.py
@@ -0,0 +1,123 @@
+import pathlib
+import numpy as np
+import astropy.units as u
+import named_arrays as na
+from .._materials import AbstractStern1994BackilluminatedCCDMaterial
+
+__all__ = [
+    "E2VCCDAIAMaterial",
+]
+
+
+class E2VCCDAIAMaterial(
+    AbstractStern1994BackilluminatedCCDMaterial,
+):
+    """
+    A model of the light-sensitive material of the custom e2v CCD sensors
+    on board the Atmospheric Imaging Assembly :cite:p:`Lemen2012` from
+    :cite:t:`Boerner2012`
+
+    Examples
+    --------
+
+    Plot the measured AIA CCD quantum efficiency vs the fitted
+    quantum efficiency calculated using the method of :cite:t:`Stern1994`.
+
+    .. jupyter-execute::
+
+        import matplotlib.pyplot as plt
+        import astropy.units as u
+        import astropy.visualization
+        import named_arrays as na
+        import optika
+
+        # Create a new instance of the e2v CCD97 light-sensitive material
+        material_ccd_aia = optika.sensors.E2VCCDAIAMaterial()
+
+        # Store the wavelengths at which the QE was measured
+        wavelength_measured = material_ccd_aia.quantum_efficiency_measured.inputs
+
+        # Store the QE measurements
+        qe_measured = material_ccd_aia.quantum_efficiency_measured.outputs
+
+        # Define a grid of wavelengths with which to evaluate the fitted QE
+        wavelength_fit = na.geomspace(10, 10000, axis="wavelength", num=1001) * u.AA
+
+        # Evaluate the fitted QE using the given wavelengths
+        qe_fit = material_ccd_aia.quantum_efficiency_effective(
+            rays=optika.rays.RayVectorArray(
+                wavelength=wavelength_fit,
+                direction=na.Cartesian3dVectorArray(0, 0, 1),
+            ),
+            normal=na.Cartesian3dVectorArray(0, 0, -1),
+        )
+
+        # Plot the measured QE vs the fitted QE
+        with astropy.visualization.quantity_support():
+            fig, ax = plt.subplots(constrained_layout=True)
+            na.plt.scatter(
+                wavelength_measured,
+                qe_measured,
+                label="measured",
+            )
+            na.plt.plot(
+                wavelength_fit,
+                qe_fit,
+                label="fit",
+            )
+            ax.set_xscale("log")
+            ax.set_xlabel(f"wavelength ({wavelength_fit.unit:latex_inline})")
+            ax.set_ylabel("quantum efficiency")
+            ax.legend()
+
+    The thickness of the oxide layer found by the fit is
+
+    .. jupyter-execute::
+
+        material_ccd_aia.thickness_oxide
+
+    The thickness of the implant layer found by the fit is
+
+    .. jupyter-execute::
+
+        material_ccd_aia.thickness_implant
+
+    The thickness of the substrate found by the fit is
+
+    .. jupyter-execute::
+
+        material_ccd_aia.thickness_substrate
+
+    And the differential charge collection efficiency at the backsurface
+    found by the fit is
+
+    .. jupyter-execute::
+
+        material_ccd_aia.cce_backsurface
+    """
+
+    @property
+    def quantum_efficiency_measured(self) -> na.FunctionArray:
+        directory = pathlib.Path(__file__).parent
+        (
+            wavelength_1,
+            qe_1,
+            wavelength_2,
+            qe_2,
+            wavelength_3,
+            qe_3,
+            wavelength_4,
+            qe_4,
+        ) = np.genfromtxt(
+            fname=directory / "e2v_ccd_aia_qe_boerner2012.csv",
+            skip_header=2,
+            delimiter=",",
+            unpack=True,
+        )
+        wavelength = (wavelength_1 + wavelength_2 + wavelength_3 + wavelength_4) / 4
+        wavelength = wavelength << u.AA
+        qe = (qe_1 + qe_2 + qe_3 + qe_4) / 4
+        return na.FunctionArray(
+            inputs=na.ScalarArray(wavelength, axes="wavelength"),
+            outputs=na.ScalarArray(qe, axes="wavelength"),
+        )
diff --git a/optika/sensors/_materials/_e2v_ccd_aia/_e2v_ccd_aia_test.py b/optika/sensors/_materials/_e2v_ccd_aia/_e2v_ccd_aia_test.py
@@ -0,0 +1,15 @@
+import pytest
+import optika
+from .._materials_test import AbstractTestAbstractStern1994BackilluminatedCCDMaterial
+
+
+@pytest.mark.parametrize(
+    argnames="a",
+    argvalues=[
+        optika.sensors.E2VCCDAIAMaterial(),
+    ],
+)
+class TestE2VCCD9AIAMaterial(
+    AbstractTestAbstractStern1994BackilluminatedCCDMaterial,
+):
+    pass
diff --git a/optika/sensors/_materials/_e2v_ccd_aia/e2v_ccd_aia_qe_boerner2012.csv b/optika/sensors/_materials/_e2v_ccd_aia/e2v_ccd_aia_qe_boerner2012.csv
@@ -0,0 +1,14 @@
+ATA1,,ATA2,,ATA3,,ATA4,
+X,Y,X,Y,X,Y,X,Y
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+1608.6131436149833,0.16073825503355677,1616.5984220000837,0.14060402684563744,1616.5984220000837,0.1627516778523488,1616.5984220000837,0.17281879194630856