Moved optika.sensors.quantum_yield_ideal() to a different source file.

optika/sensors/__init__.py

@@ -1 +1,2 @@
+from ._materials import *
 from ._sensors import *

optika/sensors/_materials/__init__.py

@@ -0,0 +1 @@
+from ._materials import *

optika/sensors/_materials/_materials.py

@@ -0,0 +1,83 @@
+import numpy as np
+import astropy.units as u
+import named_arrays as na
+
+__all__ = [
+    "energy_bandgap",
+    "energy_electron_hole",
+    "quantum_yield_ideal",
+]
+
+energy_bandgap = 1.12 * u.eV
+"""the bandgap energy of silicon"""
+
+energy_electron_hole = 3.65 * u.eV
+"""
+the high-energy limit of the energy required to create an electron-hole pair
+in silicon at room temperature
+"""
+
+
+def quantum_yield_ideal(
+    wavelength: u.Quantity | na.AbstractScalar,
+) -> na.AbstractScalar:
+    r"""
+    Calculate the ideal quantum yield of a silicon detector for a given
+    wavelength.
+
+    Parameters
+    ----------
+    wavelength
+        the wavelength of the incident photons
+
+    Notes
+    -----
+    The quantum yield is the number of electron-hole pairs produced per photon.
+
+    The ideal quantum yield is given in :cite:t:`Janesick2001` as:
+
+    .. math::
+
+        \text{QY}(\epsilon) = \begin{cases}
+            0, & \epsilon < E_\text{g}\\
+            1, &  E_\text{g} \leq \epsilon < E_\text{e-h} \\
+            E_\text{e-h} / \epsilon, & E_\text{e-h} \leq \epsilon,
+        \end{cases},
+
+    where :math:`\epsilon` is the energy of the incident photon,
+    :math:`E_\text{g} = 1.12\;\text{eV}` is the bandgap energy of silicon,
+    and :math:`E_\text{e-h} = 3.65\;\text{eV}` is the energy required to
+    generate 1 electron-hole pair in silicon at room temperature.
+
+    Examples
+    --------
+
+    Plot the quantum yield vs wavelength
+
+    .. jupyter-execute::
+
+        import matplotlib.pyplot as plt
+        import astropy.units as u
+        import named_arrays as na
+        import optika
+
+        # Define an array of wavelengths
+        wavelength = na.geomspace(100, 100000, axis="wavelength", num=101) << u.AA
+
+        # Compute the quantum yield
+        qy = optika.sensors.quantum_yield_ideal(wavelength)
+
+        # Plot the quantum yield vs wavelength
+        fig, ax = plt.subplots()
+        na.plt.plot(wavelength, qy, ax=ax);
+        ax.set_xscale("log");
+        ax.set_xlabel(f"wavelength ({wavelength.unit:latex_inline})");
+        ax.set_ylabel("quantum yield");
+    """
+    energy = wavelength.to(u.eV, equivalencies=u.spectral())
+
+    result = energy / energy_electron_hole
+    result = np.where(energy > energy_electron_hole, result, 1)
+    result = np.where(energy > energy_bandgap, result, 0)
+
+    return result

optika/sensors/_materials/_materials_test.py

@@ -0,0 +1,20 @@
+import pytest
+import numpy as np
+import astropy.units as u
+import named_arrays as na
+import optika
+
+
+@pytest.mark.parametrize(
+    argnames="wavelength,result_expected",
+    argvalues=[
+        (1.0 * u.eV, 0),
+        (2.0 * u.eV, 1),
+        (2 * optika.sensors.energy_electron_hole, 2),
+    ],
+)
+def test_quantum_yield_ideal(
+    wavelength: u.Quantity | na.AbstractScalar, result_expected: na.AbstractScalar
+):
+    result = optika.sensors.quantum_yield_ideal(wavelength)
+    assert np.all(result == result_expected)

optika/sensors/_sensors.py

@@ -9,9 +9,6 @@
 import optika
 
 __all__ = [
-    "energy_bandgap",
-    "energy_electron_hole",
-    "quantum_yield_ideal",
     "quantum_efficiency_effective",
     "AbstractImagingSensor",
     "AbstractCCD",
@@ -21,81 +18,6 @@
 MaterialT = TypeVar("MaterialT", bound=optika.materials.AbstractMaterial)
 
 
-energy_bandgap = 1.12 * u.eV
-"""the bandgap energy of silicon"""
-
-energy_electron_hole = 3.65 * u.eV
-"""
-the high-energy limit of the energy required to create an electron-hole pair
-in silicon at room temperature
-"""
-
-
-def quantum_yield_ideal(
-    wavelength: u.Quantity | na.AbstractScalar,
-) -> na.AbstractScalar:
-    r"""
-    Calculate the ideal quantum yield of a silicon detector for a given
-    wavelength.
-
-    Parameters
-    ----------
-    wavelength
-        the wavelength of the incident photons
-
-    Notes
-    -----
-    The quantum yield is the number of electron-hole pairs produced per photon.
-
-    The ideal quantum yield is given in :cite:t:`Janesick2001` as:
-
-    .. math::
-
-        \text{QY}(\epsilon) = \begin{cases}
-            0, & \epsilon < E_\text{g}\\
-            1, &  E_\text{g} \leq \epsilon < E_\text{e-h} \\
-            E_\text{e-h} / \epsilon, & E_\text{e-h} \leq \epsilon,
-        \end{cases},
-
-    where :math:`\epsilon` is the energy of the incident photon,
-    :math:`E_\text{g} = 1.12\;\text{eV}` is the bandgap energy of silicon,
-    and :math:`E_\text{e-h} = 3.65\;\text{eV}` is the energy required to
-    generate 1 electron-hole pair in silicon at room temperature.
-
-    Examples
-    --------
-
-    Plot the quantum yield vs wavelength
-
-    .. jupyter-execute::
-
-        import matplotlib.pyplot as plt
-        import astropy.units as u
-        import named_arrays as na
-        import optika
-
-        # Define an array of wavelengths
-        wavelength = na.geomspace(100, 100000, axis="wavelength", num=101) << u.AA
-
-        # Compute the quantum yield
-        qy = optika.sensors.quantum_yield_ideal(wavelength)
-
-        # Plot the quantum yield vs wavelength
-        fig, ax = plt.subplots()
-        na.plt.plot(wavelength, qy, ax=ax);
-        ax.set_xscale("log");
-        ax.set_xlabel(f"wavelength ({wavelength.unit:latex_inline})");
-        ax.set_ylabel("quantum yield");
-    """
-    energy = wavelength.to(u.eV, equivalencies=u.spectral())
-
-    result = energy / energy_electron_hole
-    result = np.where(energy > energy_electron_hole, result, 1)
-    result = np.where(energy > energy_bandgap, result, 0)
-
-    return result
-
-
 def quantum_efficiency_effective(
     wavelength: u.Quantity | na.AbstractScalar,
     direction: na.AbstractCartesian3dVectorArray,

optika/sensors/_tests/test_sensors.py

@@ -5,21 +5,6 @@
 import optika
 
 
-@pytest.mark.parametrize(
-    argnames="wavelength,result_expected",
-    argvalues=[
-        (1.0 * u.eV, 0),
-        (2.0 * u.eV, 1),
-        (2 * optika.sensors.energy_electron_hole, 2),
-    ],
-)
-def test_quantum_yield_ideal(
-    wavelength: u.Quantity | na.AbstractScalar, result_expected: na.AbstractScalar
-):
-    result = optika.sensors.quantum_yield_ideal(wavelength)
-    assert np.all(result == result_expected)
-
-
 @pytest.mark.parametrize(
     argnames="wavelength",
     argvalues=[