normalization.py 7.18 KB
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# coding: utf-8
# /*##########################################################################
#
# Copyright (c) 2016-2017 European Synchrotron Radiation Facility
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
#
# ###########################################################################*/

__authors__ = ["H. Payno"]
__license__ = "MIT"
__date__ = "06/11/2019"


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import functools
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import logging
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import multiprocessing

from PyMca5.PyMcaPhysics.xas.XASClass import XASClass

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from est.core.process.process import Process, Progress
from est.core.types import Spectrum, XASObject
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_logger = logging.getLogger(__name__)


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def process_spectr_norm(spectrum, configuration, overwrite=True, callbacks=None,
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                        output=None, output_dict=None):
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    """

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    :param spectrum: spectrum to process
    :type: :class:`.Spectrum`
    :param configuration: configuration of the pymca normalization
    :type: dict
    :param overwrite: False if we want to return a new Spectrum instance
    :type: bool
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    :param callbacks: callback to execute.
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    :param output: list to store the result, needed for pool processing
    :type: multiprocessing.manager.list
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    :param output_dict: key is input spectrum, value is index in the output
                        list.
    :type: dict
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    :return: processed spectrum
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    :rtype: tuple (configuration, spectrum)
    """
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    _logger.debug('start normalization on spectrum (%s, %s)' % (spectrum.x, spectrum.y))
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    if spectrum.energy is None or spectrum.mu is None:
        _logger.error('Energy and or Mu is/are not specified, unable to '
                      'compute exafs')
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        return None, None
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    pymca_xas = XASClass()
    pymca_xas.setSpectrum(energy=spectrum.energy,
                          mu=spectrum.mu)
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    if configuration is not None:
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        if 'e0' in configuration:
            configuration["E0Value"] = configuration['e0']
            configuration["E0Method"] = 'Manual'
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        pymca_xas.setConfiguration(configuration)
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    configuration = pymca_xas.getConfiguration()
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    try:
        res = pymca_xas.normalize()
        ddict = spectrum.to_dict()
        ddict.update(res)
        spectrum_ = Spectrum.from_dict(ddict)
    except (IndexError, ValueError) as e:
        _logger.error(e)
        return None, None
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    if callbacks:
        for callback in callbacks:
            callback()
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    def get_output(orignal_spec, res_spec):
        if overwrite:
            orignal_spec.update(res_spec)
            return orignal_spec
        else:
            return res_spec

    if output is not None:
        assert output_dict is not None
        output[output_dict[spectrum]] = get_output(spectrum, spectrum_)

    return configuration, get_output(spectrum, spectrum_)
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def pymca_normalization(xas_obj):
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    """
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    :param xas_obj: object containing the configuration and spectra to process
    :type: Union[XASObject, dict]. If is a dict, should contain configuration or
                                 spectra keys. Otherwise is simply the spectra
    :return: spectra dict
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    :rtype: dict
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    """
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    normalization_obj = PyMca_normalization()
    return normalization_obj.process(xas_obj=xas_obj)
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_USE_MULTIPROCESSING_POOL = False
# note: we cannot use multiprocessing pool with push workflow for now.


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class PyMca_normalization(Process):
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    def __init__(self):
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        Process.__init__(self, 'normalization')
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        self._advancement = Progress(self.name)
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    def setProperties(self, properties):
        if '_pymcaSettings' in properties:
            self._settings = properties['_pymcaSettings']

    def process(self, xas_obj):
        """

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        :param xas_obj: object containing the configuration and spectra to process
        :type: Union[XASObject, dict]. If is a dict, should contain configuration or
                                     spectra keys. Otherwise is simply the spectra
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        :return: updated XASObject
        :rtype: :class:`.XASObject`
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        """
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        _xas_obj = self.getXasObject(xas_obj)
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        if _xas_obj.energy is None:
            _logger.error('Energy not specified, unable to normalize spectra')
            return

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        if self._settings:
            _xas_obj.configuration['Normalization'] = self._settings

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        self._advancement.reset(max_=_xas_obj.n_spectrum)
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        self._advancement.startProcess()
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        self._pool_process(xas_obj=_xas_obj)
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        self._advancement.endProcess()
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        self.register_process(_xas_obj, data_keys=("NormalizedEnergy",
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                                                   "NormalizedMu",
                                                   "NormalizedSignal"))
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        return _xas_obj

    def _pool_process(self, xas_obj):
        """process normalization from a pool"""
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        assert isinstance(xas_obj, XASObject)
        if not _USE_MULTIPROCESSING_POOL:
            for spectrum in xas_obj.spectra:
                process_spectr_norm(spectrum=spectrum,
                                    configuration=xas_obj.configuration,
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                                    callbacks=self.callbacks,
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                                    overwrite=True)
        else:
            from multiprocessing import Manager
            manager = Manager()
            output_dict = {}
            res_list = manager.list()
            for i_spect, spect in enumerate(xas_obj.spectra):
                res_list.append(None)
                output_dict[spect] = i_spect

            with multiprocessing.Pool(5) as p:
                partial_ = functools.partial(process_spectr_norm,
                                             configuration=xas_obj.configuration,
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                                             callbacks=self.callbacks,
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                                             overwrite=False,
                                             output=res_list,
                                             output_dict=output_dict)
                p.map(partial_, xas_obj.spectra)

            # then update local spectrum
            for spectrum, res in zip(xas_obj.spectra, res_list):
                spectrum.update(res)

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    def definition(self):
        return "Normalization of the spectrum"

    def program_version(self):
        import PyMca5
        return PyMca5.version()

    def program_name(self):
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        return 'pymca_normalization'
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    __call__ = process