Source code for epdfsuite.calibration

from pymatgen.core import Structure
from pymatgen.analysis.diffraction.xrd import XRDCalculator
from .filereader import load_data
import fabio
import os
import sys



def build_calibration_data_from_cif(
    cif_file,
    wavelength,
    n_peaks=15,
    two_theta_range=(0, 2)
):
    """
    Generate a list of diffraction peaks from a CIF structure file.

    Uses pymatgen's XRD calculator to compute the simulated diffraction
    pattern, then exports the d-spacings to a text file (``distances.txt``)
    for use by pyFAI-calib2.

    Parameters
    ----------
    cif_file : str
        Path to the CIF structure file.
    wavelength : float
        Electron (or X-ray) wavelength in Å.
    n_peaks : int, optional
        Maximum number of peaks to return. Default is 15.
    two_theta_range : tuple of float, optional
        Angular range in degrees ``(2θ_min, 2θ_max)`` used to filter peaks.
        Default is ``(0, 2)``.

    Returns
    -------
    peaks : list of dict
        Each element contains:

        - ``'hkl'``: Miller indices
        - ``'d'``: d-spacing in Å
        - ``'two_theta'``: Bragg angle in degrees
        - ``'intensity'``: relative intensity
    """

    # Lecture de la structure
    structure = Structure.from_file(cif_file)

    # Calculateur XRD
    xrd = XRDCalculator(wavelength=wavelength)

    pattern = xrd.get_pattern(structure, two_theta_range=two_theta_range)

    peaks = []
    for i in range(min(n_peaks, len(pattern.x))):
        peaks.append({
            "hkl": pattern.hkls[i][0]["hkl"],
            "d": pattern.d_hkls[i],
            "two_theta": pattern.x[i],
            "intensity": pattern.y[i]
        })

    line2write=''
    for p in peaks:
        line2write += str(p['d'])+'\n'
    with open('./distances.txt','w') as f:
        f.write(line2write)
    return peaks





def perform_geometric_calibration(
        cif_file: str,
        image_file: str,
        mtf_file: str = None):
    """
    Perform geometric calibration of electron diffraction data using pyFAI-calib2.

    Exports the image as a temporary EDF file, optionally applies MTF
    deconvolution, computes calibrant d-spacings from the CIF, prints
    the instrument settings to enter in pyFAI-calib2, and launches the
    calibration GUI.

    Parameters
    ----------
    cif_file : str
        Path to the CIF structure file of the calibrant.
    image_file : str
        Path to the DM4 image file of the calibrant diffraction pattern.
    mtf_file : str, optional
        Path to the MTF file. If provided, Wiener deconvolution is applied
        to the image before calibration.
    """
    
    # load data and metadata
    detector_info, raw_image = load_data(image_file)
    if mtf_file is not None:
        # apply MTF deconvolution to raw image
        from .utilities import deconvolve_mtf_2d
        raw_image = deconvolve_mtf_2d(raw_image, mtf_file)
    # Define output EDF file name
    edffile = image_file.replace('.dm4', '.edf')

    # Create EDF image and save
    edf_image = fabio.edfimage.EdfImage(data=raw_image, header=detector_info)
    edf_image.write(edffile)

    # Create distance files for use in pyFAI-calib2
    peaks = build_calibration_data_from_cif(
        cif_file,
        wavelength=detector_info['wavelength'],  
        n_peaks=10)
    
    print("=" * 70)
    print('EXPERIMENT SETTINGS TO INPUT IN PYFAI-CALIB2:')
    print('='*70)
    print(f'Camera description={detector_info["description"]}')
    print(f'pixel_size_x={detector_info["pixel_size"]}X{detector_info["pixel_size"]}')  # in µmeters
    print(f'image dimension={detector_info["image_width"]}X{detector_info["image_height"]}') # in pixels 
    print(f'Electron wavelength={detector_info["wavelength"]} Å')

    print('=' * 70 )
    print('Launching pyFAI-calib2')
    os.system(f'"{sys.executable}" -m pyFAI.app.calib2 -c ./distances.txt {edffile}')
    
    # Clean up distance file and edf file
    os.remove(edffile)
    os.remove('./distances.txt')





def get_calibration_parameters(poni_file: str):
    """
    Extract calibration parameters from a PONI file generated by pyFAI-calib2.

    Parameters
    ----------
    poni_file : str
        Path to the PONI file produced after calibration.

    Returns
    -------
    calibration_params : dict
        Dictionary containing the following keys (when present in the file):

        - ``'distance'``: sample-to-detector distance (m)
        - ``'poni1'``, ``'poni2'``: point of normal incidence coordinates (m)
        - ``'rot1'``, ``'rot2'``, ``'rot3'``: detector rotation angles (rad)
        - ``'wavelength'``: wavelength (m)
        - ``'pixel1'``, ``'pixel2'``: pixel sizes (m)
        - ``'max_shape'``: detector shape in pixels
    """
    import json
    calibration_params = {}
    if not os.path.exists(poni_file):
        raise FileNotFoundError(f"Fichier PONI non trouvé: {poni_file}")

    with open(poni_file, 'r') as f:
        lines = f.readlines()

    for line in lines:
        if line.startswith('Distance:'):
            calibration_params['distance'] = float(line.split(':')[1].strip())
        elif line.startswith('Poni1:'):
            calibration_params['poni1'] = float(line.split(':')[1].strip())
        elif line.startswith('Poni2:'):
            calibration_params['poni2'] = float(line.split(':')[1].strip())
        elif line.startswith('Rot1:'):
            calibration_params['rot1'] = float(line.split(':')[1].strip())
        elif line.startswith('Rot2:'):
            calibration_params['rot2'] = float(line.split(':')[1].strip())
        elif line.startswith('Rot3:'):
            calibration_params['rot3'] = float(line.split(':')[1].strip())
        elif line.startswith('Wavelength:'):
            calibration_params['wavelength'] = float(line.split(':')[1].strip())
        elif line.startswith('Detector_config:'):
            config_str = line.split(':', 1)[1].strip()
            config = json.loads(config_str)
            calibration_params['pixel1'] = config.get('pixel1', None)
            calibration_params['pixel2'] = config.get('pixel2', None)
            calibration_params['max_shape'] = config.get('max_shape', None)

    return calibration_params