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_var_norm_value.m
    path of file: ./repos/AI-mag/src/ann_regression/ann_matlab/@AnnManager
    
    the code of the file until where you have to start completion: function vec_output = get_var_norm_value(vec_input, norm_param, scale_unscale)
% Apply a given normalization or denormalization to a vector.
%
%    Parameters:
%        vec_input (vector): vector with the input data
%        norm_param (struct): normalization data
%        scale_unscale (str): normalization or denormalization ('scale' or 'unscale')
%
%    Returns:
%        vec_output (vector): vector with the output data
%
%    (c) 2019-2020, ETH Zurich, Power Electronic Systems Laboratory, T. Guillod

switch scale_unscale

    
function vec_output = get_var_norm_value(vec_input, norm_param, scale_unscale)
% Apply a given normalization or denormalization to a vector.
%
%    Parameters:
%        vec_input (vector): vector with the input data
%        norm_param (struct): normalization data
%        scale_unscale (str): normalization or denormalization ('scale' or 'unscale')
%
%    Returns:
%        vec_output (vector): vector with the output data
%
%    (c) 2019-2020, ETH Zurich, Power Electronic Systems Laboratory, T. Guillod

switch scale_unscale
    case 'scale'
        vec_output = (vec_input-norm_param.offset)./norm_param.scale;
    case 'unscale'
        vec_output = vec_input.*norm_param.scale+norm_param.offset;
    otherwise
        error('invalid scaling / unscaling choice')
end