Source code for easistrain.func_lattice_d_spacing_param

import os
import pyFAI
import numpy
import h5py




def lattice_param(root_data, h5file, poni_file, h, k, l):
    ai = pyFAI.load(poni_file)  # loading the poni file (integration geometry)
    wlgth = (ai.wavelength) * 10**10  # the wavelength in angstrom
    with h5py.File(
        os.path.join(root_data, "Results" + "_" + h5file), "a"
    ) as fh5_save:  ### Create the file in which will be saved the results (integration, ...)
        with h5py.File(
            os.path.join(root_data, "Results" + "_" + h5file), "r"
        ) as r_h5file:  ### Read the h5 file
            r_groups_scan = list(
                r_h5file.keys()
            )  # getting the list of all the names of the scans in the h5 file
            for iscan in range(numpy.shape(r_groups_scan)[0]):  # Iteration on the scans
                print(
                    "#*#*#*#*#*# Processing of the scan: "
                    + r_groups_scan[iscan]
                    + " #*#*#*#*#*#*"
                )
                r_groups_images = list(
                    r_h5file[
                        r_groups_scan[iscan]
                        + "/fitting_HKL="
                        + "("
                        + str(h)
                        + str(k)
                        + str(l)
                        + ")_cleaned"
                    ].keys()
                )  # getting the list images in a scan
                save1 = fh5_save[r_groups_scan[iscan]].create_group(
                    "latt_param_d_spacing_" + "(" + str(h) + str(k) + str(l) + ")"
                )  # Creating of the group where the results will be saved
                for nimg in range(
                    numpy.shape(r_groups_images)[0]
                ):  # Iteration on the images in a scan
                    print(
                        "#*#*#*#*#*# Processing of the image: "
                        + r_groups_images[nimg]
                        + " #*#*#*#*#*#*"
                    )
                    print(
                        "######### Calculation of lattice parameter and d-spacing started ############"
                    )
                    img_save1 = save1.create_group(
                        r_groups_images[nimg]
                    )  # creates a group 'image+nb' for each image
                    tth_pos = r_h5file[
                        r_groups_scan[iscan]
                        + "/fitting_HKL="
                        + "("
                        + str(h)
                        + str(k)
                        + str(l)
                        + ")_cleaned/"
                        + r_groups_images[nimg]
                        + "/tth_position_cleaned"
                    ]  # read tth_positions dataset matrix
                    chi_cleaned = r_h5file[
                        r_groups_scan[iscan]
                        + "/fitting_HKL="
                        + "("
                        + str(h)
                        + str(k)
                        + str(l)
                        + ")_cleaned/"
                        + r_groups_images[nimg]
                        + "/chi_cleaned"
                    ]  # read tth_positions dataset matrix
                    a_matrix = numpy.zeros(
                        (numpy.shape(tth_pos)[0], 2), float
                    )  # matrix to stock the calculated lattice parameters
                    d_spacing_matrix = numpy.zeros(
                        (numpy.shape(tth_pos)[0], 2), float
                    )  # matrix to stock the calculated d_spacings
                    d_spacing_matrix[:, 0] = wlgth / (
                        2 * numpy.sin(numpy.radians(0.5 * tth_pos[:]))
                    )  # Calculation of the d_spacing
                    d_spacing_matrix[:, 1] = chi_cleaned[:]
                    a_matrix[:, 0] = d_spacing_matrix[:, 0] * numpy.sqrt(
                        (int(h) ** 2) + (int(k) ** 2) + (int(l) ** 2)
                    )  # Calculation of the lattice parameter
                    a_matrix[:, 1] = chi_cleaned[:]
                    a_mean = numpy.mean(
                        a_matrix[:, 0]
                    )  # Calculation o the mean lattice parameter value
                    a_std = numpy.std(
                        a_matrix[:, 0]
                    )  # Calculation of the std of the lattice parameter
                    d_mean = numpy.mean(
                        d_spacing_matrix[:, 0]
                    )  # Calculation of the mean d-spacing value
                    d_std = numpy.std(
                        d_spacing_matrix[:, 0]
                    )  # Calculation of the std of the d-spacing value
                    print(
                        "######### Calculation of lattice parameter and d-spacing completed ############"
                    )
                    img_save1.create_dataset(
                        "d_spacing", dtype="f", data=d_spacing_matrix
                    )
                    img_save1.create_dataset("d_spacing_mean", dtype="f", data=d_mean)
                    img_save1.create_dataset("d_spacing_std", dtype="f", data=d_std)
                    img_save1.create_dataset("latt_param", dtype="f", data=a_matrix)
                    img_save1.create_dataset("latt_param_mean", dtype="f", data=a_mean)
                    img_save1.create_dataset("latt_param_std", dtype="f", data=a_std)
                    print("######### data saved in h5 file ############")