source: branches/HeuristicLab.Problems.GaussianProcessTuning/ILNumerics.2.14.4735.573/Functions/statistics/nanmean.cs @ 11194

///
///    This file is part of ILNumerics Community Edition.
///
///    ILNumerics Community Edition - high performance computing for applications.
///    Copyright (C) 2006 - 2012 Haymo Kutschbach, http://ilnumerics.net
///
///    ILNumerics Community Edition is free software: you can redistribute it and/or modify
///    it under the terms of the GNU General Public License version 3 as published by
///    the Free Software Foundation.
///
///    ILNumerics Community Edition is distributed in the hope that it will be useful,
///    but WITHOUT ANY WARRANTY; without even the implied warranty of
///    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
///    GNU General Public License for more details.
///
///    You should have received a copy of the GNU General Public License
///    along with ILNumerics Community Edition. See the file License.txt in the root
///    of your distribution package. If not, see <http://www.gnu.org/licenses/>.
///
///    In addition this software uses the following components and/or licenses: 
///
///    =================================================================================
///    The Open Toolkit Library License
///    
///    Copyright (c) 2006 - 2009 the Open Toolkit library.
///    
///    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.
///
///    =================================================================================
///    

using System;
using System.Collections.Generic;
using System.Text;
using ILNumerics.Storage;
using ILNumerics.Misc;
using ILNumerics.Exceptions;



namespace ILNumerics  {
  public partial class ILMath {

    /// <summary>
    /// Mean of array along specified dimension ignoring NaN values
    /// </summary>
    /// <param name="A">Input array</param>
        /// <param name="dim">[Optional] Index of the dimension to work along. If omitted operates along the first non singleton dimension (i.e. != 1).</param>
    /// <returns>Mean of non-NaN elements along specified dimension</returns>
    /// <remarks><para>The return array has the same shape as A, but the selected dimension is reduced 
    /// to length 1. If A is scalar, an scalar array will be returned. On empty input, the output will be empty.
    /// </para><para>If A contains an all NaN vector along the specified dimension the resulting value will by NaN
    /// (as the nansum of these elements is 0 divided by 0 elements)</para></remarks>
    public static ILRetArray<double> nanmean( ILInArray<double> A, int dim = -1) {
      using (ILScope.Enter(A)) {
        if (dim < 0)
          dim = A.Size.WorkingDimension();
        return nansum_internal(A, dim, true);
      }
    }

#region HYCALPER AUTO GENERATED CODE

    /// <summary>
    /// Mean of array along specified dimension ignoring NaN values
    /// </summary>
    /// <param name="A">Input array</param>
        /// <param name="dim">[Optional] Index of the dimension to work along. If omitted operates along the first non singleton dimension (i.e. != 1).</param>
    /// <returns>Mean of non-NaN elements along specified dimension</returns>
    /// <remarks><para>The return array has the same shape as A, but the selected dimension is reduced 
    /// to length 1. If A is scalar, an scalar array will be returned. On empty input, the output will be empty.
    /// </para><para>If A contains an all NaN vector along the specified dimension the resulting value will by NaN
    /// (as the nansum of these elements is 0 divided by 0 elements)</para></remarks>
    public static ILRetArray<fcomplex> nanmean( ILInArray<fcomplex> A, int dim = -1) {
      using (ILScope.Enter(A)) {
        if (dim < 0)
          dim = A.Size.WorkingDimension();
        return nansum_internal(A, dim, true);
      }
    }
    /// <summary>
    /// Mean of array along specified dimension ignoring NaN values
    /// </summary>
    /// <param name="A">Input array</param>
        /// <param name="dim">[Optional] Index of the dimension to work along. If omitted operates along the first non singleton dimension (i.e. != 1).</param>
    /// <returns>Mean of non-NaN elements along specified dimension</returns>
    /// <remarks><para>The return array has the same shape as A, but the selected dimension is reduced 
    /// to length 1. If A is scalar, an scalar array will be returned. On empty input, the output will be empty.
    /// </para><para>If A contains an all NaN vector along the specified dimension the resulting value will by NaN
    /// (as the nansum of these elements is 0 divided by 0 elements)</para></remarks>
    public static ILRetArray<float> nanmean( ILInArray<float> A, int dim = -1) {
      using (ILScope.Enter(A)) {
        if (dim < 0)
          dim = A.Size.WorkingDimension();
        return nansum_internal(A, dim, true);
      }
    }
    /// <summary>
    /// Mean of array along specified dimension ignoring NaN values
    /// </summary>
    /// <param name="A">Input array</param>
        /// <param name="dim">[Optional] Index of the dimension to work along. If omitted operates along the first non singleton dimension (i.e. != 1).</param>
    /// <returns>Mean of non-NaN elements along specified dimension</returns>
    /// <remarks><para>The return array has the same shape as A, but the selected dimension is reduced 
    /// to length 1. If A is scalar, an scalar array will be returned. On empty input, the output will be empty.
    /// </para><para>If A contains an all NaN vector along the specified dimension the resulting value will by NaN
    /// (as the nansum of these elements is 0 divided by 0 elements)</para></remarks>
    public static ILRetArray<complex> nanmean( ILInArray<complex> A, int dim = -1) {
      using (ILScope.Enter(A)) {
        if (dim < 0)
          dim = A.Size.WorkingDimension();
        return nansum_internal(A, dim, true);
      }
    }

#endregion HYCALPER AUTO GENERATED CODE
}
}