You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: get_parameter_mapping_for_condition.m
    path of file: ./repos/d2d/arFramework3/ThirdParty/strike-goldd/STRIKE-GOLDD/MEIGO64/MEIGO/PEtabMEIGO/parameter_mapping
    
    the code of the file until where you have to start completion: function [par_mapping, scale_mapping] = ...
    get_parameter_mapping_for_condition(condition_id, is_preeq, ...
    cur_measurement_df, sbml_model, condition_df, varargin)
    % Create dictionary of parameter value and parameter scale mappings 
    % from PEtab-problem to SBML parameters for the given condition.
    % 
    % Parameters:
    %   condition_id (string, char): 
    %       Condition ID for which to perform mapping.
    %   is_preeq (bool): 
    %       If "True", output parameters will not be mapped.
    %   cur_measurement_df (table): 
    %       Measurement sub-table for current condition
    %   condition_df (table):
    %       PEtab condition DataFrame.
    %   parameter_df *(table/[]):
    %       PEtab parameter DataFrame.

    
function [par_mapping, scale_mapping] = ...
    get_parameter_mapping_for_condition(condition_id, is_preeq, ...
    cur_measurement_df, sbml_model, condition_df, varargin)
    % Create dictionary of parameter value and parameter scale mappings 
    % from PEtab-problem to SBML parameters for the given condition.
    % 
    % Parameters:
    %   condition_id (string, char): 
    %       Condition ID for which to perform mapping.
    %   is_preeq (bool): 
    %       If "True", output parameters will not be mapped.
    %   cur_measurement_df (table): 
    %       Measurement sub-table for current condition
    %   condition_df (table):
    %       PEtab condition DataFrame.
    %   parameter_df *(table/[]):
    %       PEtab parameter DataFrame.
    %   sbml_model (Sbml):
    %       The sbml model with observables and noise specified according to
    %       the PEtab format used to retrieve simulation parameter IDs.     
    %   simulation_parameters *(Dict/[]):
    %       Model simulation parameter IDs mapped to parameter values (output
    %       of "sbml/get_model_parameters(.., with_values=True)").
    %       Optional, saves time if precomputed.
    %   warn_unmapped *(bool/[]):
    %       If "True", log warning regarding unmapped parameters.
    %     
    %   Returns:
    %       ([Dict, Dict])
    %           Tuple of two dictionaries. First dictionary mapping model 
    %           parameter IDs to mapped parameters IDs to be estimated or 
    %           to filled-in values in case of non-estimated parameters.
    %           Second dictionary mapping model parameter IDs to their 
    %           scale.
    %           NaN is used where no mapping exists.
    
    p = inputParser;
    addRequired(p, 'condition_id', @(x) isstring(x) || ischar(x));
    addRequired(p, 'is_preeq', @islogical);
    addRequired(p, 'cur_measurement_df', @istable);
    addRequired(p, 'sbml_model', @Sbml.isSbml);
    addRequired(p, 'condition_df', @istable);
    addParameter(p, 'parameter_df', table.empty(), @istable);
    addParameter(p, 'simulation_parameters', Dict.empty(), @Dict.isDict);
    addParameter(p, 'warn_unmapped', true, @islogical);
    addParameter(p, 'scaled_parameters', false, @islogical);
    
    parse(p, condition_id, is_preeq, cur_measurement_df, sbml_model, ...
        condition_df, varargin{:});
    
    condition_id = p.Results.condition_id;
    is_preeq = p.Results.is_preeq;
    cur_measurement_df = p.Results.cur_measurement_df;
    sbml_model = p.Results.sbml_model;
    condition_df = p.Results.condition_df;
    parameter_df = p.Results.parameter_df;
    simulation_parameters = p.Results.simulation_parameters;
    warn_unmapped = p.Results.warn_unmapped;
    scaled_parameters = p.Results.scaled_parameters;
    
    perform_mapping_checks(cur_measurement_df);
    
    if isempty_ext(simulation_parameters)
        simulation_parameters = get_model_parameters(sbml_model, true);
    end