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/*
 * JCufft - Java bindings for CUFFT, the NVIDIA CUDA FFT library,
 * to be used with JCuda
 *
 * Copyright (c) 2008-2013 Marco Hutter - http://www.jcuda.org
 *
 * 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.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
 * OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
 * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
 * HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
 * WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
 * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
 * OTHER DEALINGS IN THE SOFTWARE.
 */

package jcuda.fft;


/**
 * Compatibility flags for CUFFT. Original documentation: 

 * 

 * Certain R2C and C2R transforms go much more slowly when FFTW memory
 * layout and behaviour is required. The default is "best performance",
 * which means not-compatible-with-fftw. Use the cufftSetCompatibilityMode
 * API to enable exact FFTW-like behaviour.

 * 

 * These flags can be ORed together to select precise FFTW compatibility
 * behaviour. 
 */
public class cufftCompatibility
{
    /**
     * Disable any FFTW compatibility mode.
     * 
     * @deprecated as of CUDA 6.0RC
     */
    public static final int CUFFT_COMPATIBILITY_NATIVE          = 0x00;
    
    /**
     * Inserts extra padding between packed in-place transforms for
     * batched transforms with power-of-2 size. This is the default.
     */
    public static final int CUFFT_COMPATIBILITY_FFTW_PADDING    = 0x01;
    
    /**
     * Guarantees FFTW-compatible output for non-symmetric complex inputs
     * for transforms with power-of-2 size. This is only useful for
     * artificial (i.e. random) datasets as actual data will always be
     * symmetric if it has come from the real plane. If you don't
     * understand what this means, you probably don't have to use it.
     * 
     * @deprecated as of CUDA 6.5:  Asymmetric input is 
     * always treated as in FFTW.
     */
    public static final int CUFFT_COMPATIBILITY_FFTW_ASYMMETRIC = 0x02;

    /**
     * For convenience, enables all FFTW compatibility modes at once.
     */
    public static final int CUFFT_COMPATIBILITY_FFTW_ALL        = 0x03;

    /**
     * Returns the String identifying the given cufftCompatibility
     * 
     * @param m The cufftType
     * @return The String identifying the given cufftCompatibility
     */
    public static String stringFor(int m)
    {
        if (m == CUFFT_COMPATIBILITY_NATIVE)
        {
            return "CUFFT_COMPATIBILITY_NATIVE";
        }
        if ((m & CUFFT_COMPATIBILITY_FFTW_ALL) == CUFFT_COMPATIBILITY_FFTW_ALL)
        {
            return "CUFFT_COMPATIBILITY_FFTW_ALL";
        }
        StringBuilder sb = new StringBuilder();
        if ((m & CUFFT_COMPATIBILITY_FFTW_PADDING) != 0) 
        {
            sb.append("CUFFT_COMPATIBILITY_FFTW_PADDING ");
        }
        if ((m & CUFFT_COMPATIBILITY_FFTW_ASYMMETRIC) != 0) 
        {
            sb.append("CUFFT_COMPATIBILITY_FFTW_ASYMMETRIC ");
        }
        return sb.toString();
    }

    /**
     * Private constructor to prevent instantiation.
     */
    private cufftCompatibility()
    {
    }

}