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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_PCA_parameters(self, specimen, fit, tmin, tmax, coordinate_system, calculation_type):
 """ Uses pmag.domean to preform a line, line-with-origin, line-anchored, or plane least squared regression or a fisher mean on the measurement data of specimen in coordinate system between bounds tmin to tmax Parameters specimen : specimen with measurement data in self.Data fit : fit for which the regression or mean is being applied (used for calculating measurement index of tmin and tmax) tmin : lower bound of measurement data tmax : upper bound of measurement data coordinate_system : which coordinate system the measurement data should be in calculation_type : type of regression or mean to preform (options - DE-BFL:line,DE-BFL-A:line-anchored,DE-BFL-O:line-with- origin,DE-FM:fisher,DE-BFP:plane) Returns ------- mpars : a 2.5 data model dictionary type specimen record of the dec, inc, etc of the regression or mean """

        if tmin == '' or tmax == '':
            return
        beg_pca, end_pca = self.get_indices(fit, tmin, tmax, specimen)

        if coordinate_system == 'geographic' or coordinate_system == 'DA-DIR-GEO':
            block = self.Data[specimen]['zijdblock_geo']
        elif coordinate_system == 'tilt-corrected' or coordinate_system == 'DA-DIR-TILT':
            block = self.Data[specimen]['zijdblock_tilt']
        else:
            block = self.Data[specimen]['zijdblock']
        if block == []:
            print(("-E- no measurement data for specimen %s in coordinate system %s" %
                   (specimen, coordinate_system)))
            mpars = {}
        elif end_pca > beg_pca and end_pca - beg_pca > 1:

            try:
                # preformes regression
                mpars = pmag.domean(block, beg_pca, end_pca, calculation_type)
            except:
                print((block, beg_pca, end_pca, calculation_type,
                       specimen, fit.name, tmin, tmax, coordinate_system))
                return

            if 'specimen_direction_type' in mpars and mpars['specimen_direction_type'] == 'Error':
                print(("-E- no measurement data for specimen %s in coordinate system %s" %
                       (specimen, coordinate_system)))
                return {}
        else:
            mpars = {}
        for k in list(mpars.keys()):
            try:
                if math.isnan(float(mpars[k])):
                    mpars[k] = 0
            except:
                pass
        if "DE-BFL" in calculation_type and 'specimen_dang' not in list(mpars.keys()):
            mpars['specimen_dang'] = 0

        if 'best fit vector' in self.plane_display_box.GetValue():
            self.calculate_best_fit_vectors()

        return(mpars)