<commit_before>"""."""

from copy import deepcopy as _dcopy
from collections import namedtuple as _namedtuple
import numpy as np

import pyaccel
from pymodels import bo, si


class OpticsCorr():
    """."""

    METHODS = _namedtuple('Methods', ['Additional', 'Proportional'])(0, 1)
    CORR_STATUS = _namedtuple('CorrStatus', ['Fail', 'Sucess'])(0, 1)
    CORR_METHODS = _namedtuple('CorrMethods', ['LOCO'])(0)

    def __init__(self, model, acc, dim='4d', knobs_list=None,
                 method=None, correction_method=None):
        """."""
        self.model = model
        self.acc = acc
        self.dim = dim
        self._corr_method = OpticsCorr.CORR_METHODS.LOCO
        self._method = OpticsCorr.METHODS.Proportional
        self.jacobian_matrix = []
        if self.acc == 'BO':
            self.fam_data = bo.families.get_family_data(self.model)
        elif self.acc == 'SI':
            self.fam_data = si.families.get_family_data(self.model)
        else:
            raise Exception('Set models: BO or SI')
        if knobs_list is None:
            self.knobs_idx = self.fam_data['QN']['index']
        else:
            self.knobs_idx = knobs_list
        self.bpm_idx = self._get_idx(self.fam_data['BPM']['index'])
        self.ch_idx = self._get_idx(self.fam_data['CH']['index'])
        self.cv_idx = self._get_idx(self.fam_data['CV']['index'])
        self.method = method
        self.corr_method = correction_method

    @property
    def method(self):
        """."""
        return self._method

    @method.setter
    def method(self, value):
        if value is None:
            return
        if isinstance(value, str):
            self._method = int(value in OpticsCorr.METHODS._fields[1])
        elif int(value) in OpticsCorr.METHODS:
            self._method = int(value)

    @property
    def method_str(self):
        """."""
        return OpticsCorr.METHODS._fields[self._method]

    @property
    def corr_method(self):
        """."""
        return self._corr_method

    @corr_method.setter
    def corr_method(self, value):
        if value is None:
            return
        if isinstance(value, str):
            self._corr_method = int(
                value in OpticsCorr.CORR_METHODS._fields[1])
        elif int(value) in OpticsCorr.CORR_METHODS:
            self._corr_method = int(value)

    @property
    def corr_method_str(self):
        """."""
        return OpticsCorr.CORR_METHODS._fields[self._corr_method]

    @staticmethod
    def _get_idx(indcs):
        return np.array([idx[0] for idx in indcs])

    def calc_jacobian_matrix(self, model=None):
        """Optics correction response matrix.

        Calculates the variation of Twiss functions and tune given the
        variation of integrated quadrupoles strength.
        """
        if model is None:
            model = self.model

        res0 = self._get_optics_vector(model)
        self.jacobian_matrix = np.zeros((res0.size, len(self.knobs_idx)))
        delta = 1e-6

        modcopy = model[:]
        for idx, nmag in enumerate(self.knobs_idx):
            dlt = delta/len(nmag)
            for seg in nmag:<commit_msg>OPTICS.BUG: workaround when there is only one correction method<commit_after>"""."""

from copy import deepcopy as _dcopy
from collections import namedtuple as _namedtuple
import numpy as np

import pyaccel
from pymodels import bo, si


class OpticsCorr():
    """."""

    METHODS = _namedtuple('Methods', ['Additional', 'Proportional'])(0, 1)
    CORR_STATUS = _namedtuple('CorrStatus', ['Fail', 'Sucess'])(0, 1)
    CORR_METHODS = _namedtuple('CorrMethods', ['LOCO'])(0)

    def __init__(self, model, acc, dim='4d', knobs_list=None,
                 method=None, correction_method=None):
        """."""
        self.model = model
        self.acc = acc
        self.dim = dim
        self._corr_method = OpticsCorr.CORR_METHODS.LOCO
        self._method = OpticsCorr.METHODS.Proportional
        self.jacobian_matrix = []
        if self.acc == 'BO':
            self.fam_data = bo.families.get_family_data(self.model)
        elif self.acc == 'SI':
            self.fam_data = si.families.get_family_data(self.model)
        else:
            raise Exception('Set models: BO or SI')
        if knobs_list is None:
            self.knobs_idx = self.fam_data['QN']['index']
        else:
            self.knobs_idx = knobs_list
        self.bpm_idx = self._get_idx(self.fam_data['BPM']['index'])
        self.ch_idx = self._get_idx(self.fam_data['CH']['index'])
        self.cv_idx = self._get_idx(self.fam_data['CV']['index'])
        self.method = method
        self.corr_method = correction_method

    @property
    def method(self):
        """."""
        return self._method

    @method.setter
    def method(self, value):
        if value is None:
            return
        if isinstance(value, str):
            self._method = int(value in OpticsCorr.METHODS._fields[1])
        elif int(value) in OpticsCorr.METHODS:
            self._method = int(value)

    @property
    def method_str(self):
        """."""
        return OpticsCorr.METHODS._fields[self._method]

    @property
    def corr_method(self):
        """."""
        return self._corr_method

    @corr_method.setter
    def corr_method(self, value):
        if value is None:
            return
        if isinstance(value, str):
            self._corr_method = int(
                value not in OpticsCorr.CORR_METHODS._fields[0])
        elif int(value) in OpticsCorr.CORR_METHODS:
            self._corr_method = int(value)

    @property
    def corr_method_str(self):
        """."""
        return OpticsCorr.CORR_METHODS._fields[self._corr_method]

    @staticmethod
    def _get_idx(indcs):
        return np.array([idx[0] for idx in indcs])

    def calc_jacobian_matrix(self, model=None):
        """Optics correction response matrix.

        Calculates the variation of Twiss functions and tune given the
        variation of integrated quadrupoles strength.
        """
        if model is None:
            model = self.model

        res0 = self._get_optics_vector(model)
        self.jacobian_matrix = np.zeros((res0.size, len(self.knobs_idx)))
        delta = 1e-6

        modcopy = model[:]
        for idx, nmag in enumerate(self.knobs_idx):
            dlt = delta/len(nmag)
            for seg in nmag:
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