CMSIS_5/CMSIS/DSP/Source/InterpolationFunctions/arm_linear_interp_f32.c

/* ----------------------------------------------------------------------
 * Project:      CMSIS DSP Library
 * Title:        arm_linear_interp_f32.c
 * Description:  Floating-point linear interpolation
 *
 * $Date:        23 April 2021
 * $Revision:    V1.9.0
 *
 * Target Processor: Cortex-M and Cortex-A cores
 * -------------------------------------------------------------------- */
/*
 * Copyright (C) 2010-2021 ARM Limited or its affiliates. All rights reserved.
 *
 * SPDX-License-Identifier: Apache-2.0
 *
 * Licensed under the Apache License, Version 2.0 (the License); you may
 * not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an AS IS BASIS, WITHOUT
 * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

#include "dsp/interpolation_functions.h"

/**
  @ingroup groupInterpolation
 */

/**
   * @defgroup LinearInterpolate Linear Interpolation
   *
   * Linear interpolation is a method of curve fitting using linear polynomials.
   * Linear interpolation works by effectively drawing a straight line between two neighboring samples and returning the appropriate point along that line
   *
   * \par
   * \image html LinearInterp.gif "Linear interpolation"
   *
   * \par
   * A  Linear Interpolate function calculates an output value(y), for the input(x)
   * using linear interpolation of the input values x0, x1( nearest input values) and the output values y0 and y1(nearest output values)
   *
   * \par Algorithm:
   * <pre>
   *       y = y0 + (x - x0) * ((y1 - y0)/(x1-x0))
   *       where x0, x1 are nearest values of input x
   *             y0, y1 are nearest values to output y
   * </pre>
   *
   * \par
   * This set of functions implements Linear interpolation process
   * for Q7, Q15, Q31, and floating-point data types.  The functions operate on a single
   * sample of data and each call to the function returns a single processed value.
   * <code>S</code> points to an instance of the Linear Interpolate function data structure.
   * <code>x</code> is the input sample value. The functions returns the output value.
   *
   * \par
   * if x is outside of the table boundary, Linear interpolation returns first value of the table
   * if x is below input range and returns last value of table if x is above range.
   */

/**
   * @addtogroup LinearInterpolate
   * @{
   */

  /**
   * @brief  Process function for the floating-point Linear Interpolation Function.
   * @param[in,out] S  is an instance of the floating-point Linear Interpolation structure
   * @param[in]     x  input sample to process
   * @return y processed output sample.
   *
   */
  float32_t arm_linear_interp_f32(
  arm_linear_interp_instance_f32 * S,
  float32_t x)
  {
    float32_t y;
    float32_t x0, x1;                            /* Nearest input values */
    float32_t y0, y1;                            /* Nearest output values */
    float32_t xSpacing = S->xSpacing;            /* spacing between input values */
    int32_t i;                                   /* Index variable */
    float32_t *pYData = S->pYData;               /* pointer to output table */

    /* Calculation of index */
    i = (int32_t) ((x - S->x1) / xSpacing);

    if (i < 0)
    {
      /* Iniatilize output for below specified range as least output value of table */
      y = pYData[0];
    }
    else if ((uint32_t)i >= (S->nValues - 1))
    {
      /* Iniatilize output for above specified range as last output value of table */
      y = pYData[S->nValues - 1];
    }
    else
    {
      /* Calculation of nearest input values */
      x0 = S->x1 +  i      * xSpacing;
      x1 = S->x1 + (i + 1) * xSpacing;

      /* Read of nearest output values */
      y0 = pYData[i];
      y1 = pYData[i + 1];

      /* Calculation of output */
      y = y0 + (x - x0) * ((y1 - y0) / (x1 - x0));

    }

    /* returns output value */
    return (y);
  }

  /**
   * @} end of LinearInterpolate group
   */