add function for fast computation

Author: yucongalicechen

src/diffpy/labpdfproc/fast_cve.py

@@ -2,8 +2,56 @@
 import pandas as pd
 from scipy.interpolate import interp1d
 
+from diffpy.utils.scattering_objects.diffraction_objects import Diffraction_object
+
 TTH_GRID = np.arange(1, 180.1, 0.1)
 MUD_LIST = [0.5, 1, 2, 3, 4, 5, 6]
 INVERSE_CVE_DATA = np.loadtxt("data/inverse_cve.xy")
 COEFFICIENT_LIST = pd.read_csv("data/coefficient_list.csv", header=None)
 INTERPOLATION_FUNCTIONS = [interp1d(MUD_LIST, coefficients, kind="quadratic") for coefficients in COEFFICIENT_LIST]
+
+
+def fast_compute_cve(diffraction_data, mud, wavelength):
+    """
+    use precomputed datasets to compute the cve for given diffraction data, mud and wavelength
+
+    Parameters
+    ----------
+    diffraction_data Diffraction_object
+      the diffraction pattern
+    mud float
+      the mu*D of the diffraction object, where D is the diameter of the circle
+    wavelength float
+      the wavelength of the diffraction object
+
+    Returns
+    -------
+    the diffraction object with cve curves
+    """
+
+    coefficient_a, coefficient_b, coefficient_c, coefficient_d, coefficient_e = [
+        interpolation_function(mud) for interpolation_function in INTERPOLATION_FUNCTIONS
+    ]
+    inverse_cve = (
+        coefficient_a * INVERSE_CVE_DATA**4
+        + coefficient_b * INVERSE_CVE_DATA**3
+        + coefficient_c * INVERSE_CVE_DATA**2
+        + coefficient_d * INVERSE_CVE_DATA**1
+        + coefficient_e
+    )
+    cve = 1 / np.array(inverse_cve)
+
+    orig_grid = diffraction_data.on_tth[0]
+    newcve = np.interp(orig_grid, TTH_GRID, cve)
+    abdo = Diffraction_object(wavelength=wavelength)
+    abdo.insert_scattering_quantity(
+        orig_grid,
+        newcve,
+        "tth",
+        metadata=diffraction_data.metadata,
+        name=f"absorption correction, cve, for {diffraction_data.name}",
+        wavelength=diffraction_data.wavelength,
+        scat_quantity="cve",
+    )
+
+    return abdo