Added esis.flights.f1.optics.gratings.rulings.ruling_measurement(). (…

…#6)

esis/flights/f1/optics/gratings/rulings/_rulings.py

@@ -1,9 +1,12 @@
-import named_arrays as na
+import numpy as np
 import astropy.units as u
+import named_arrays as na
 import optika
+from esis.flights.f1.optics import gratings
 
 __all__ = [
     "ruling_design",
+    "ruling_measurement",
 ]
 
 
@@ -13,6 +16,11 @@ def ruling_design(
     """
     The as-designed rulings for the ESIS diffraction gratings.
 
+    Parameters
+    ----------
+    num_distribution
+        The number of Monte Carlo samples to draw when computing uncertainties.
+
     Examples
     --------
 
@@ -87,10 +95,143 @@ def ruling_design(
         depth=na.UniformUncertainScalarArray(
             nominal=15 * u.nm,
             width=2 * u.nm,
+            num_distribution=num_distribution,
         ),
         ratio_duty=na.UniformUncertainScalarArray(
             nominal=0.5,
             width=0.1,
+            num_distribution=num_distribution,
         ),
         diffraction_order=1,
     )
+
+
+def ruling_measurement(
+    num_distribution: int = 11,
+):
+    """
+    A model of the rulings where the efficiency has been calculated using the
+    ratio of the total efficiency of the gratings to the efficiency of the
+    multilayer coatings.
+
+    The total efficiency of the gratings is given by
+    :func:`esis.flights.f1.optics.gratings.efficiencies.efficiency_vs_wavelength()`,
+    and the efficiency of the multilayer coating is given by
+    :func:`esis.flights.f1.optics.gratings.materials.multilayer_fit()`.
+
+    Parameters
+    ----------
+    num_distribution
+        The number of Monte Carlo samples to draw when computing uncertainties.
+
+    Examples
+    --------
+
+    Compare the as-designed efficiency of the rulings to the measured efficiency
+    of the rulings.
+
+    .. jupyter-execute::
+
+        import numpy as np
+        import matplotlib.pyplot as plt
+        import astropy.units as u
+        import astropy.visualization
+        import named_arrays as na
+        import optika
+        from esis.flights.f1.optics import gratings
+
+        # Define an array of wavelengths with which to sample the efficiency
+        wavelength = na.geomspace(500, 700, axis="wavelength", num=1001) * u.AA
+
+        # Define the incidence angle to be the same as the Horiba technical proposal
+        angle = 1.3 * u.deg
+
+        # Define the incident rays from the wavelength array
+        rays = optika.rays.RayVectorArray(
+            wavelength=wavelength,
+            position=0 * u.mm,
+            direction=na.Cartesian3dVectorArray(
+                x=np.sin(angle),
+                y=0,
+                z=np.cos(angle),
+            ),
+        )
+
+        # Define the surface normal
+        normal = na.Cartesian3dVectorArray(0, 0, -1)
+
+        # Initialize the ESIS diffraction grating ruling model
+        ruling_design = gratings.rulings.ruling_design(num_distribution=0)
+        ruling_measurement = gratings.rulings.ruling_measurement(num_distribution=0)
+
+        # Compute the efficiency of the grating rulings
+        efficiency_design = ruling_design.efficiency(
+            rays=rays,
+            normal=normal,
+        )
+        efficiency_measurement = ruling_measurement.efficiency(
+            rays=rays,
+            normal=normal,
+        )
+
+        # Plot the efficiency vs wavelength
+        fig, ax = plt.subplots(constrained_layout=True)
+        na.plt.plot(
+            wavelength,
+            efficiency_design,
+            ax=ax,
+            color="tab:blue",
+            label="design",
+        );
+        na.plt.plot(
+            wavelength,
+            efficiency_measurement,
+            ax=ax,
+            color="tab:orange",
+            label="measurement",
+        );
+        ax.set_xlabel(f"wavelength ({wavelength.unit:latex_inline})");
+        ax.set_ylabel("efficiency");
+        ax.legend();
+    """
+
+    design = ruling_design(num_distribution=num_distribution)
+
+    density = na.UniformUncertainScalarArray(
+        nominal=2585.5 / u.mm,
+        width=1 / u.mm,
+        num_distribution=num_distribution,
+    )
+
+    spacing = design.spacing
+    spacing.coefficients[0] = 1 / density
+
+    efficiency_total = gratings.efficiencies.efficiency_vs_wavelength()
+
+    wavelength = efficiency_total.inputs.wavelength
+    angle = efficiency_total.inputs.direction
+
+    coating = gratings.materials.multilayer_fit()
+
+    efficiency_coating = coating.efficiency(
+        rays=optika.rays.RayVectorArray(
+            wavelength=wavelength,
+            direction=na.Cartesian3dVectorArray(
+                x=np.sin(angle),
+                y=0,
+                z=np.cos(angle),
+            ),
+        ),
+        normal=na.Cartesian3dVectorArray(0, 0, -1),
+    )
+
+    efficiency_rulings = na.FunctionArray(
+        inputs=efficiency_total.inputs,
+        outputs=efficiency_total.outputs / efficiency_coating,
+    )
+
+    return optika.rulings.MeasuredRulings(
+        spacing=spacing,
+        diffraction_order=design.diffraction_order,
+        efficiency_measured=efficiency_rulings,
+    )

esis/flights/f1/optics/gratings/rulings/_rulings_test.py

@@ -5,3 +5,8 @@
 def test_ruling_design():
     r = esis.flights.f1.optics.gratings.rulings.ruling_design()
     assert isinstance(r, optika.rulings.AbstractRulings)
+
+
+def test_ruling_measurement():
+    r = esis.flights.f1.optics.gratings.rulings.ruling_measurement()
+    assert isinstance(r, optika.rulings.AbstractRulings)