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/******************************************************************************
*
* Project: GDAL Gridding API.
* Purpose: Implementation of GDAL scattered data gridder.
* Author: Andrey Kiselev, dron@ak4719.spb.edu
*
******************************************************************************
* Copyright (c) 2007, Andrey Kiselev <dron@ak4719.spb.edu>
* Copyright (c) 2009-2013, Even Rouault <even dot rouault at spatialys.com>
*
* SPDX-License-Identifier: MIT
****************************************************************************/
#include "cpl_port.h"
#include "gdalgrid.h"
#include "gdalgrid_priv.h"
#include <cfloat>
#include <climits>
#include <cmath>
#include <cstdlib>
#include <cstring>
#include <limits>
#include <map>
#include <utility>
#include <algorithm>
#include "cpl_conv.h"
#include "cpl_cpu_features.h"
#include "cpl_error.h"
#include "cpl_multiproc.h"
#include "cpl_progress.h"
#include "cpl_quad_tree.h"
#include "cpl_string.h"
#include "cpl_vsi.h"
#include "cpl_worker_thread_pool.h"
#include "gdal.h"
constexpr double TO_RADIANS = M_PI / 180.0;
/************************************************************************/
/* GDALGridGetPointBounds() */
/************************************************************************/
static void GDALGridGetPointBounds(const void *hFeature, CPLRectObj *pBounds)
{
const GDALGridPoint *psPoint = static_cast<const GDALGridPoint *>(hFeature);
GDALGridXYArrays *psXYArrays = psPoint->psXYArrays;
const int i = psPoint->i;
const double dfX = psXYArrays->padfX[i];
const double dfY = psXYArrays->padfY[i];
pBounds->minx = dfX;
pBounds->miny = dfY;
pBounds->maxx = dfX;
pBounds->maxy = dfY;
}
/************************************************************************/
/* GDALGridInverseDistanceToAPower() */
/************************************************************************/
/**
* Inverse distance to a power.
*
* The Inverse Distance to a Power gridding method is a weighted average
* interpolator. You should supply the input arrays with the scattered data
* values including coordinates of every data point and output grid geometry.
* The function will compute interpolated value for the given position in
* output grid.
*
* For every grid node the resulting value \f$Z\f$ will be calculated using
* formula:
*
* \f[
* Z=\frac{\sum_{i=1}^n{\frac{Z_i}{r_i^p}}}{\sum_{i=1}^n{\frac{1}{r_i^p}}}
* \f]
*
* where
* <ul>
* <li> \f$Z_i\f$ is a known value at point \f$i\f$,
* <li> \f$r_i\f$ is an Euclidean distance from the grid node
* to point \f$i\f$,
* <li> \f$p\f$ is a weighting power,
* <li> \f$n\f$ is a total number of points in search ellipse.
* </ul>
*
* In this method the weighting factor \f$w\f$ is
*
* \f[
* w=\frac{1}{r^p}
* \f]
*
* @param poOptionsIn Algorithm parameters. This should point to
* GDALGridInverseDistanceToAPowerOptions object.
* @param nPoints Number of elements in input arrays.
* @param padfX Input array of X coordinates.
* @param padfY Input array of Y coordinates.
* @param padfZ Input array of Z values.
* @param dfXPoint X coordinate of the point to compute.
* @param dfYPoint Y coordinate of the point to compute.
* @param pdfValue Pointer to variable where the computed grid node value
* will be returned.
* @param hExtraParamsIn extra parameters (unused)
*
* @return CE_None on success or CE_Failure if something goes wrong.
*/
CPLErr GDALGridInverseDistanceToAPower(const void *poOptionsIn, GUInt32 nPoints,
const double *padfX, const double *padfY,
const double *padfZ, double dfXPoint,
double dfYPoint, double *pdfValue,
CPL_UNUSED void *hExtraParamsIn)
{
// TODO: For optimization purposes pre-computed parameters should be moved
// out of this routine to the calling function.
const GDALGridInverseDistanceToAPowerOptions *const poOptions =
static_cast<const GDALGridInverseDistanceToAPowerOptions *>(
poOptionsIn);
// Pre-compute search ellipse parameters.
const double dfRadius1Square = poOptions->dfRadius1 * poOptions->dfRadius1;
const double dfRadius2Square = poOptions->dfRadius2 * poOptions->dfRadius2;
const double dfR12Square = dfRadius1Square * dfRadius2Square;
// Compute coefficients for coordinate system rotation.
const double dfAngle = TO_RADIANS * poOptions->dfAngle;
const bool bRotated = dfAngle != 0.0;
const double dfCoeff1 = bRotated ? cos(dfAngle) : 0.0;
const double dfCoeff2 = bRotated ? sin(dfAngle) : 0.0;
const double dfPowerDiv2 = poOptions->dfPower / 2;
const double dfSmoothing = poOptions->dfSmoothing;
const GUInt32 nMaxPoints = poOptions->nMaxPoints;
double dfNominator = 0.0;
double dfDenominator = 0.0;
GUInt32 n = 0;
for (GUInt32 i = 0; i < nPoints; i++)
{
double dfRX = padfX[i] - dfXPoint;
double dfRY = padfY[i] - dfYPoint;
const double dfR2 =
dfRX * dfRX + dfRY * dfRY + dfSmoothing * dfSmoothing;
if (bRotated)
{
const double dfRXRotated = dfRX * dfCoeff1 + dfRY * dfCoeff2;
const double dfRYRotated = dfRY * dfCoeff1 - dfRX * dfCoeff2;
dfRX = dfRXRotated;
dfRY = dfRYRotated;
}
// Is this point located inside the search ellipse?
if (dfRadius2Square * dfRX * dfRX + dfRadius1Square * dfRY * dfRY <=
dfR12Square)
{
// If the test point is close to the grid node, use the point
// value directly as a node value to avoid singularity.
if (dfR2 < 0.0000000000001)
{
*pdfValue = padfZ[i];
return CE_None;
}
const double dfW = pow(dfR2, dfPowerDiv2);
const double dfInvW = 1.0 / dfW;
dfNominator += dfInvW * padfZ[i];
dfDenominator += dfInvW;
n++;
if (nMaxPoints > 0 && n > nMaxPoints)
break;
}
}
if (n < poOptions->nMinPoints || dfDenominator == 0.0)
{
*pdfValue = poOptions->dfNoDataValue;
}
else
{
*pdfValue = dfNominator / dfDenominator;
}
return CE_None;
}
/************************************************************************/
/* GDALGridInverseDistanceToAPowerNearestNeighbor() */
/************************************************************************/
/**
* Inverse distance to a power with nearest neighbor search, ideal when
* max_points used.
*
* The Inverse Distance to a Power gridding method is a weighted average
* interpolator. You should supply the input arrays with the scattered data
* values including coordinates of every data point and output grid geometry.
* The function will compute interpolated value for the given position in
* output grid.
*
* For every grid node the resulting value \f$Z\f$ will be calculated using
* formula for nearest matches:
*
* \f[
* Z=\frac{\sum_{i=1}^n{\frac{Z_i}{r_i^p}}}{\sum_{i=1}^n{\frac{1}{r_i^p}}}
* \f]
*
* where
* <ul>
* <li> \f$Z_i\f$ is a known value at point \f$i\f$,
* <li> \f$r_i\f$ is an Euclidean distance from the grid node
* to point \f$i\f$ (with an optional smoothing parameter \f$s\f$),
* <li> \f$p\f$ is a weighting power,
* <li> \f$n\f$ is a total number of points in search ellipse.
* </ul>
*
* In this method the weighting factor \f$w\f$ is
*
* \f[
* w=\frac{1}{r^p}
* \f]
*
* @param poOptionsIn Algorithm parameters. This should point to
* GDALGridInverseDistanceToAPowerNearestNeighborOptions object.
* @param nPoints Number of elements in input arrays.
* @param padfX Input array of X coordinates.
* @param padfY Input array of Y coordinates.
* @param padfZ Input array of Z values.
* @param dfXPoint X coordinate of the point to compute.
* @param dfYPoint Y coordinate of the point to compute.
* @param pdfValue Pointer to variable where the computed grid node value
* will be returned.
* @param hExtraParamsIn extra parameters.
*
* @return CE_None on success or CE_Failure if something goes wrong.
*/
CPLErr GDALGridInverseDistanceToAPowerNearestNeighbor(
const void *poOptionsIn, GUInt32 nPoints, const double *padfX,
const double *padfY, const double *padfZ, double dfXPoint, double dfYPoint,
double *pdfValue, void *hExtraParamsIn)
{
CPL_IGNORE_RET_VAL(nPoints);
const GDALGridInverseDistanceToAPowerNearestNeighborOptions
*const poOptions = static_cast<
const GDALGridInverseDistanceToAPowerNearestNeighborOptions *>(
poOptionsIn);
const double dfRadius = poOptions->dfRadius;
const double dfSmoothing = poOptions->dfSmoothing;
const double dfSmoothing2 = dfSmoothing * dfSmoothing;
const GUInt32 nMaxPoints = poOptions->nMaxPoints;
GDALGridExtraParameters *psExtraParams =
static_cast<GDALGridExtraParameters *>(hExtraParamsIn);
const CPLQuadTree *phQuadTree = psExtraParams->hQuadTree;
CPLAssert(phQuadTree);
const double dfRPower2 = psExtraParams->dfRadiusPower2PreComp;
const double dfPowerDiv2 = psExtraParams->dfPowerDiv2PreComp;
std::multimap<double, double> oMapDistanceToZValues;
const double dfSearchRadius = dfRadius;
CPLRectObj sAoi;
sAoi.minx = dfXPoint - dfSearchRadius;
sAoi.miny = dfYPoint - dfSearchRadius;
sAoi.maxx = dfXPoint + dfSearchRadius;
sAoi.maxy = dfYPoint + dfSearchRadius;
int nFeatureCount = 0;
GDALGridPoint **papsPoints = reinterpret_cast<GDALGridPoint **>(
CPLQuadTreeSearch(phQuadTree, &sAoi, &nFeatureCount));
if (nFeatureCount != 0)
{
for (int k = 0; k < nFeatureCount; k++)
{
const int i = papsPoints[k]->i;
const double dfRX = padfX[i] - dfXPoint;
const double dfRY = padfY[i] - dfYPoint;
const double dfR2 = dfRX * dfRX + dfRY * dfRY;
// real distance + smoothing
const double dfRsmoothed2 = dfR2 + dfSmoothing2;
if (dfRsmoothed2 < 0.0000000000001)
{
*pdfValue = padfZ[i];
CPLFree(papsPoints);
return CE_None;
}
// is point within real distance?
if (dfR2 <= dfRPower2)
{
oMapDistanceToZValues.insert(
std::make_pair(dfRsmoothed2, padfZ[i]));
}
}
}
CPLFree(papsPoints);
double dfNominator = 0.0;
double dfDenominator = 0.0;
GUInt32 n = 0;
// Examine all "neighbors" within the radius (sorted by distance via the
// multimap), and use the closest n points based on distance until the max
// is reached.
for (std::multimap<double, double>::iterator oMapDistanceToZValuesIter =
oMapDistanceToZValues.begin();
oMapDistanceToZValuesIter != oMapDistanceToZValues.end();
++oMapDistanceToZValuesIter)
{
const double dfR2 = oMapDistanceToZValuesIter->first;
const double dfZ = oMapDistanceToZValuesIter->second;
const double dfW = pow(dfR2, dfPowerDiv2);
const double dfInvW = 1.0 / dfW;
dfNominator += dfInvW * dfZ;
dfDenominator += dfInvW;
n++;
if (nMaxPoints > 0 && n >= nMaxPoints)
{
break;
}
}
if (n < poOptions->nMinPoints || dfDenominator == 0.0)
{
*pdfValue = poOptions->dfNoDataValue;
}
else
{
*pdfValue = dfNominator / dfDenominator;
}
return CE_None;
}
/************************************************************************/
/* GDALGridInverseDistanceToAPowerNearestNeighborPerQuadrant() */
/************************************************************************/
/**
* Inverse distance to a power with nearest neighbor search, with a per-quadrant
* search logic.
*/
static CPLErr GDALGridInverseDistanceToAPowerNearestNeighborPerQuadrant(
const void *poOptionsIn, GUInt32 /*nPoints*/, const double *padfX,
const double *padfY, const double *padfZ, double dfXPoint, double dfYPoint,
double *pdfValue, void *hExtraParamsIn)
{
const GDALGridInverseDistanceToAPowerNearestNeighborOptions
*const poOptions = static_cast<
const GDALGridInverseDistanceToAPowerNearestNeighborOptions *>(
poOptionsIn);
const double dfRadius = poOptions->dfRadius;
const double dfSmoothing = poOptions->dfSmoothing;
const double dfSmoothing2 = dfSmoothing * dfSmoothing;
const GUInt32 nMaxPoints = poOptions->nMaxPoints;
const GUInt32 nMinPointsPerQuadrant = poOptions->nMinPointsPerQuadrant;
const GUInt32 nMaxPointsPerQuadrant = poOptions->nMaxPointsPerQuadrant;
GDALGridExtraParameters *psExtraParams =
static_cast<GDALGridExtraParameters *>(hExtraParamsIn);
const CPLQuadTree *phQuadTree = psExtraParams->hQuadTree;
CPLAssert(phQuadTree);
const double dfRPower2 = psExtraParams->dfRadiusPower2PreComp;
const double dfPowerDiv2 = psExtraParams->dfPowerDiv2PreComp;
std::multimap<double, double> oMapDistanceToZValuesPerQuadrant[4];
const double dfSearchRadius = dfRadius;
CPLRectObj sAoi;
sAoi.minx = dfXPoint - dfSearchRadius;
sAoi.miny = dfYPoint - dfSearchRadius;
sAoi.maxx = dfXPoint + dfSearchRadius;
sAoi.maxy = dfYPoint + dfSearchRadius;
int nFeatureCount = 0;
GDALGridPoint **papsPoints = reinterpret_cast<GDALGridPoint **>(
CPLQuadTreeSearch(phQuadTree, &sAoi, &nFeatureCount));
if (nFeatureCount != 0)
{
for (int k = 0; k < nFeatureCount; k++)
{
const int i = papsPoints[k]->i;
const double dfRX = padfX[i] - dfXPoint;
const double dfRY = padfY[i] - dfYPoint;
const double dfR2 = dfRX * dfRX + dfRY * dfRY;
// real distance + smoothing
const double dfRsmoothed2 = dfR2 + dfSmoothing2;
if (dfRsmoothed2 < 0.0000000000001)
{
*pdfValue = padfZ[i];
CPLFree(papsPoints);
return CE_None;
}
// is point within real distance?
if (dfR2 <= dfRPower2)
{
const int iQuadrant =
((dfRX >= 0) ? 1 : 0) | (((dfRY >= 0) ? 1 : 0) << 1);
oMapDistanceToZValuesPerQuadrant[iQuadrant].insert(
std::make_pair(dfRsmoothed2, padfZ[i]));
}
}
}
CPLFree(papsPoints);
std::multimap<double, double>::iterator aoIter[] = {
oMapDistanceToZValuesPerQuadrant[0].begin(),
oMapDistanceToZValuesPerQuadrant[1].begin(),
oMapDistanceToZValuesPerQuadrant[2].begin(),
oMapDistanceToZValuesPerQuadrant[3].begin(),
};
constexpr int ALL_QUADRANT_FLAGS = 1 + 2 + 4 + 8;
// Examine all "neighbors" within the radius (sorted by distance via the
// multimap), and use the closest n points based on distance until the max
// is reached.
// Do that by fetching the nearest point in quadrant 0, then the nearest
// point in quadrant 1, 2 and 3, and starting again with the next nearest
// point in quarant 0, etc.
int nQuadrantIterFinishedFlag = 0;
GUInt32 anPerQuadrant[4] = {0};
double dfNominator = 0.0;
double dfDenominator = 0.0;
GUInt32 n = 0;
for (int iQuadrant = 0; /* true */; iQuadrant = (iQuadrant + 1) % 4)
{
if (aoIter[iQuadrant] ==
oMapDistanceToZValuesPerQuadrant[iQuadrant].end() ||
(nMaxPointsPerQuadrant > 0 &&
anPerQuadrant[iQuadrant] >= nMaxPointsPerQuadrant))
{
nQuadrantIterFinishedFlag |= 1 << iQuadrant;
if (nQuadrantIterFinishedFlag == ALL_QUADRANT_FLAGS)
break;
continue;
}
const double dfR2 = aoIter[iQuadrant]->first;
const double dfZ = aoIter[iQuadrant]->second;
++aoIter[iQuadrant];
const double dfW = pow(dfR2, dfPowerDiv2);
const double dfInvW = 1.0 / dfW;
dfNominator += dfInvW * dfZ;
dfDenominator += dfInvW;
n++;
anPerQuadrant[iQuadrant]++;
if (nMaxPoints > 0 && n >= nMaxPoints)
{
break;
}
}
if (nMinPointsPerQuadrant > 0 &&
(anPerQuadrant[0] < nMinPointsPerQuadrant ||
anPerQuadrant[1] < nMinPointsPerQuadrant ||
anPerQuadrant[2] < nMinPointsPerQuadrant ||
anPerQuadrant[3] < nMinPointsPerQuadrant))
{
*pdfValue = poOptions->dfNoDataValue;
}
else if (n < poOptions->nMinPoints || dfDenominator == 0.0)
{
*pdfValue = poOptions->dfNoDataValue;
}
else
{
*pdfValue = dfNominator / dfDenominator;
}
return CE_None;
}
/************************************************************************/
/* GDALGridInverseDistanceToAPowerNoSearch() */
/************************************************************************/
/**
* Inverse distance to a power for whole data set.
*
* This is somewhat optimized version of the Inverse Distance to a Power
* method. It is used when the search ellips is not set. The algorithm and
* parameters are the same as in GDALGridInverseDistanceToAPower(), but this
* implementation works faster, because of no search.
*
* @see GDALGridInverseDistanceToAPower()
*/
CPLErr GDALGridInverseDistanceToAPowerNoSearch(
const void *poOptionsIn, GUInt32 nPoints, const double *padfX,
const double *padfY, const double *padfZ, double dfXPoint, double dfYPoint,
double *pdfValue, void * /* hExtraParamsIn */)
{
const GDALGridInverseDistanceToAPowerOptions *const poOptions =
static_cast<const GDALGridInverseDistanceToAPowerOptions *>(
poOptionsIn);
const double dfPowerDiv2 = poOptions->dfPower / 2.0;
const double dfSmoothing = poOptions->dfSmoothing;
const double dfSmoothing2 = dfSmoothing * dfSmoothing;
double dfNominator = 0.0;
double dfDenominator = 0.0;
const bool bPower2 = dfPowerDiv2 == 1.0;
GUInt32 i = 0; // Used after if.
if (bPower2)
{
if (dfSmoothing2 > 0)
{
for (i = 0; i < nPoints; i++)
{
const double dfRX = padfX[i] - dfXPoint;
const double dfRY = padfY[i] - dfYPoint;
const double dfR2 = dfRX * dfRX + dfRY * dfRY + dfSmoothing2;
const double dfInvR2 = 1.0 / dfR2;
dfNominator += dfInvR2 * padfZ[i];
dfDenominator += dfInvR2;
}
}
else
{
for (i = 0; i < nPoints; i++)
{
const double dfRX = padfX[i] - dfXPoint;
const double dfRY = padfY[i] - dfYPoint;
const double dfR2 = dfRX * dfRX + dfRY * dfRY;
// If the test point is close to the grid node, use the point
// value directly as a node value to avoid singularity.
if (dfR2 < 0.0000000000001)
{
break;
}
const double dfInvR2 = 1.0 / dfR2;
dfNominator += dfInvR2 * padfZ[i];
dfDenominator += dfInvR2;
}
}
}
else
{
for (i = 0; i < nPoints; i++)
{
const double dfRX = padfX[i] - dfXPoint;
const double dfRY = padfY[i] - dfYPoint;
const double dfR2 = dfRX * dfRX + dfRY * dfRY + dfSmoothing2;
// If the test point is close to the grid node, use the point
// value directly as a node value to avoid singularity.
if (dfR2 < 0.0000000000001)
{
break;
}
const double dfW = pow(dfR2, dfPowerDiv2);
const double dfInvW = 1.0 / dfW;
dfNominator += dfInvW * padfZ[i];
dfDenominator += dfInvW;
}
}
if (i != nPoints)
{
*pdfValue = padfZ[i];
}
else if (dfDenominator == 0.0)
{
*pdfValue = poOptions->dfNoDataValue;
}
else
{
*pdfValue = dfNominator / dfDenominator;
}
return CE_None;
}
/************************************************************************/
/* GDALGridMovingAverage() */
/************************************************************************/
/**
* Moving average.
*
* The Moving Average is a simple data averaging algorithm. It uses a moving
* window of elliptic form to search values and averages all data points
* within the window. Search ellipse can be rotated by specified angle, the
* center of ellipse located at the grid node. Also the minimum number of data
* points to average can be set, if there are not enough points in window, the
* grid node considered empty and will be filled with specified NODATA value.
*
* Mathematically it can be expressed with the formula:
*
* \f[
* Z=\frac{\sum_{i=1}^n{Z_i}}{n}
* \f]
*
* where
* <ul>
* <li> \f$Z\f$ is a resulting value at the grid node,
* <li> \f$Z_i\f$ is a known value at point \f$i\f$,
* <li> \f$n\f$ is a total number of points in search ellipse.
* </ul>
*
* @param poOptionsIn Algorithm parameters. This should point to
* GDALGridMovingAverageOptions object.
* @param nPoints Number of elements in input arrays.
* @param padfX Input array of X coordinates.
* @param padfY Input array of Y coordinates.
* @param padfZ Input array of Z values.
* @param dfXPoint X coordinate of the point to compute.
* @param dfYPoint Y coordinate of the point to compute.
* @param pdfValue Pointer to variable where the computed grid node value
* will be returned.
* @param hExtraParamsIn extra parameters (unused)
*
* @return CE_None on success or CE_Failure if something goes wrong.
*/
CPLErr GDALGridMovingAverage(const void *poOptionsIn, GUInt32 nPoints,
const double *padfX, const double *padfY,
const double *padfZ, double dfXPoint,
double dfYPoint, double *pdfValue,
CPL_UNUSED void *hExtraParamsIn)
{
// TODO: For optimization purposes pre-computed parameters should be moved
// out of this routine to the calling function.
const GDALGridMovingAverageOptions *const poOptions =
static_cast<const GDALGridMovingAverageOptions *>(poOptionsIn);
// Pre-compute search ellipse parameters.
const double dfRadius1Square = poOptions->dfRadius1 * poOptions->dfRadius1;
const double dfRadius2Square = poOptions->dfRadius2 * poOptions->dfRadius2;
const double dfSearchRadius =
std::max(poOptions->dfRadius1, poOptions->dfRadius2);
const double dfR12Square = dfRadius1Square * dfRadius2Square;
GDALGridExtraParameters *psExtraParams =
static_cast<GDALGridExtraParameters *>(hExtraParamsIn);
const CPLQuadTree *phQuadTree = psExtraParams->hQuadTree;
// Compute coefficients for coordinate system rotation.
const double dfAngle = TO_RADIANS * poOptions->dfAngle;
const bool bRotated = dfAngle != 0.0;
const double dfCoeff1 = bRotated ? cos(dfAngle) : 0.0;
const double dfCoeff2 = bRotated ? sin(dfAngle) : 0.0;
double dfAccumulator = 0.0;
GUInt32 n = 0; // Used after for.
if (phQuadTree != nullptr)
{
CPLRectObj sAoi;
sAoi.minx = dfXPoint - dfSearchRadius;
sAoi.miny = dfYPoint - dfSearchRadius;
sAoi.maxx = dfXPoint + dfSearchRadius;
sAoi.maxy = dfYPoint + dfSearchRadius;
int nFeatureCount = 0;
GDALGridPoint **papsPoints = reinterpret_cast<GDALGridPoint **>(
CPLQuadTreeSearch(phQuadTree, &sAoi, &nFeatureCount));
if (nFeatureCount != 0)
{
for (int k = 0; k < nFeatureCount; k++)
{
const int i = papsPoints[k]->i;
const double dfRX = padfX[i] - dfXPoint;
const double dfRY = padfY[i] - dfYPoint;
if (dfRadius2Square * dfRX * dfRX +
dfRadius1Square * dfRY * dfRY <=
dfR12Square)
{
dfAccumulator += padfZ[i];
n++;
}
}
}
CPLFree(papsPoints);
}
else
{
for (GUInt32 i = 0; i < nPoints; i++)
{
double dfRX = padfX[i] - dfXPoint;
double dfRY = padfY[i] - dfYPoint;
if (bRotated)
{
const double dfRXRotated = dfRX * dfCoeff1 + dfRY * dfCoeff2;
const double dfRYRotated = dfRY * dfCoeff1 - dfRX * dfCoeff2;
dfRX = dfRXRotated;
dfRY = dfRYRotated;
}
// Is this point located inside the search ellipse?
if (dfRadius2Square * dfRX * dfRX + dfRadius1Square * dfRY * dfRY <=
dfR12Square)
{
dfAccumulator += padfZ[i];
n++;
}
}
}
if (n < poOptions->nMinPoints || n == 0)
{
*pdfValue = poOptions->dfNoDataValue;
}
else
{
*pdfValue = dfAccumulator / n;
}
return CE_None;
}
/************************************************************************/
/* GDALGridMovingAveragePerQuadrant() */
/************************************************************************/
/**
* Moving average, with a per-quadrant search logic.
*/
static CPLErr GDALGridMovingAveragePerQuadrant(
const void *poOptionsIn, GUInt32 /*nPoints*/, const double *padfX,
const double *padfY, const double *padfZ, double dfXPoint, double dfYPoint,
double *pdfValue, void *hExtraParamsIn)
{
const GDALGridMovingAverageOptions *const poOptions =
static_cast<const GDALGridMovingAverageOptions *>(poOptionsIn);
const double dfRadius1Square = poOptions->dfRadius1 * poOptions->dfRadius1;
const double dfRadius2Square = poOptions->dfRadius2 * poOptions->dfRadius2;
const double dfR12Square = dfRadius1Square * dfRadius2Square;
const GUInt32 nMaxPoints = poOptions->nMaxPoints;
const GUInt32 nMinPointsPerQuadrant = poOptions->nMinPointsPerQuadrant;
const GUInt32 nMaxPointsPerQuadrant = poOptions->nMaxPointsPerQuadrant;
GDALGridExtraParameters *psExtraParams =
static_cast<GDALGridExtraParameters *>(hExtraParamsIn);
const CPLQuadTree *phQuadTree = psExtraParams->hQuadTree;
CPLAssert(phQuadTree);
std::multimap<double, double> oMapDistanceToZValuesPerQuadrant[4];
const double dfSearchRadius =
std::max(poOptions->dfRadius1, poOptions->dfRadius2);
CPLRectObj sAoi;
sAoi.minx = dfXPoint - dfSearchRadius;
sAoi.miny = dfYPoint - dfSearchRadius;
sAoi.maxx = dfXPoint + dfSearchRadius;
sAoi.maxy = dfYPoint + dfSearchRadius;
int nFeatureCount = 0;
GDALGridPoint **papsPoints = reinterpret_cast<GDALGridPoint **>(
CPLQuadTreeSearch(phQuadTree, &sAoi, &nFeatureCount));
if (nFeatureCount != 0)
{
for (int k = 0; k < nFeatureCount; k++)
{
const int i = papsPoints[k]->i;
const double dfRX = padfX[i] - dfXPoint;
const double dfRY = padfY[i] - dfYPoint;
const double dfRXSquare = dfRX * dfRX;
const double dfRYSquare = dfRY * dfRY;
if (dfRadius2Square * dfRXSquare + dfRadius1Square * dfRYSquare <=
dfR12Square)
{
const int iQuadrant =
((dfRX >= 0) ? 1 : 0) | (((dfRY >= 0) ? 1 : 0) << 1);
oMapDistanceToZValuesPerQuadrant[iQuadrant].insert(
std::make_pair(dfRXSquare + dfRYSquare, padfZ[i]));
}
}
}
CPLFree(papsPoints);
std::multimap<double, double>::iterator aoIter[] = {
oMapDistanceToZValuesPerQuadrant[0].begin(),
oMapDistanceToZValuesPerQuadrant[1].begin(),
oMapDistanceToZValuesPerQuadrant[2].begin(),
oMapDistanceToZValuesPerQuadrant[3].begin(),
};
constexpr int ALL_QUADRANT_FLAGS = 1 + 2 + 4 + 8;
// Examine all "neighbors" within the radius (sorted by distance via the
// multimap), and use the closest n points based on distance until the max
// is reached.
// Do that by fetching the nearest point in quadrant 0, then the nearest
// point in quadrant 1, 2 and 3, and starting again with the next nearest
// point in quarant 0, etc.
int nQuadrantIterFinishedFlag = 0;
GUInt32 anPerQuadrant[4] = {0};
double dfNominator = 0.0;
GUInt32 n = 0;
for (int iQuadrant = 0; /* true */; iQuadrant = (iQuadrant + 1) % 4)
{
if (aoIter[iQuadrant] ==
oMapDistanceToZValuesPerQuadrant[iQuadrant].end() ||
(nMaxPointsPerQuadrant > 0 &&
anPerQuadrant[iQuadrant] >= nMaxPointsPerQuadrant))
{
nQuadrantIterFinishedFlag |= 1 << iQuadrant;
if (nQuadrantIterFinishedFlag == ALL_QUADRANT_FLAGS)
break;
continue;
}
const double dfZ = aoIter[iQuadrant]->second;
++aoIter[iQuadrant];
dfNominator += dfZ;
n++;
anPerQuadrant[iQuadrant]++;
if (nMaxPoints > 0 && n >= nMaxPoints)
{
break;
}
}
if (nMinPointsPerQuadrant > 0 &&
(anPerQuadrant[0] < nMinPointsPerQuadrant ||
anPerQuadrant[1] < nMinPointsPerQuadrant ||
anPerQuadrant[2] < nMinPointsPerQuadrant ||
anPerQuadrant[3] < nMinPointsPerQuadrant))
{
*pdfValue = poOptions->dfNoDataValue;
}
else if (n < poOptions->nMinPoints || n == 0)
{
*pdfValue = poOptions->dfNoDataValue;
}
else
{
*pdfValue = dfNominator / n;
}
return CE_None;
}
/************************************************************************/
/* GDALGridNearestNeighbor() */
/************************************************************************/
/**
* Nearest neighbor.
*
* The Nearest Neighbor method doesn't perform any interpolation or smoothing,
* it just takes the value of nearest point found in grid node search ellipse
* and returns it as a result. If there are no points found, the specified
* NODATA value will be returned.
*
* @param poOptionsIn Algorithm parameters. This should point to
* GDALGridNearestNeighborOptions object.
* @param nPoints Number of elements in input arrays.
* @param padfX Input array of X coordinates.
* @param padfY Input array of Y coordinates.
* @param padfZ Input array of Z values.
* @param dfXPoint X coordinate of the point to compute.
* @param dfYPoint Y coordinate of the point to compute.
* @param pdfValue Pointer to variable where the computed grid node value
* will be returned.
* @param hExtraParamsIn extra parameters.
*
* @return CE_None on success or CE_Failure if something goes wrong.
*/
CPLErr GDALGridNearestNeighbor(const void *poOptionsIn, GUInt32 nPoints,
const double *padfX, const double *padfY,
const double *padfZ, double dfXPoint,
double dfYPoint, double *pdfValue,
void *hExtraParamsIn)
{
// TODO: For optimization purposes pre-computed parameters should be moved
// out of this routine to the calling function.
const GDALGridNearestNeighborOptions *const poOptions =
static_cast<const GDALGridNearestNeighborOptions *>(poOptionsIn);
// Pre-compute search ellipse parameters.
const double dfRadius1Square = poOptions->dfRadius1 * poOptions->dfRadius1;
const double dfRadius2Square = poOptions->dfRadius2 * poOptions->dfRadius2;
const double dfR12Square = dfRadius1Square * dfRadius2Square;
GDALGridExtraParameters *psExtraParams =
static_cast<GDALGridExtraParameters *>(hExtraParamsIn);
CPLQuadTree *hQuadTree = psExtraParams->hQuadTree;
// Compute coefficients for coordinate system rotation.
const double dfAngle = TO_RADIANS * poOptions->dfAngle;
const bool bRotated = dfAngle != 0.0;
const double dfCoeff1 = bRotated ? cos(dfAngle) : 0.0;
const double dfCoeff2 = bRotated ? sin(dfAngle) : 0.0;
// If the nearest point will not be found, its value remains as NODATA.
double dfNearestValue = poOptions->dfNoDataValue;
GUInt32 i = 0;
double dfSearchRadius = psExtraParams->dfInitialSearchRadius;
if (hQuadTree != nullptr)
{
if (poOptions->dfRadius1 > 0 || poOptions->dfRadius2 > 0)
dfSearchRadius =
std::max(poOptions->dfRadius1, poOptions->dfRadius2);
CPLRectObj sAoi;
while (dfSearchRadius > 0)
{
sAoi.minx = dfXPoint - dfSearchRadius;
sAoi.miny = dfYPoint - dfSearchRadius;
sAoi.maxx = dfXPoint + dfSearchRadius;
sAoi.maxy = dfYPoint + dfSearchRadius;
int nFeatureCount = 0;
GDALGridPoint **papsPoints = reinterpret_cast<GDALGridPoint **>(
CPLQuadTreeSearch(hQuadTree, &sAoi, &nFeatureCount));
if (nFeatureCount != 0)
{
// Nearest distance will be initialized with the distance to the
// first point in array.
double dfNearestRSquare = std::numeric_limits<double>::max();
for (int k = 0; k < nFeatureCount; k++)
{
const int idx = papsPoints[k]->i;
const double dfRX = padfX[idx] - dfXPoint;
const double dfRY = padfY[idx] - dfYPoint;
const double dfR2 = dfRX * dfRX + dfRY * dfRY;
if (dfR2 <= dfNearestRSquare)
{
dfNearestRSquare = dfR2;
dfNearestValue = padfZ[idx];
}
}
CPLFree(papsPoints);
break;
}
CPLFree(papsPoints);
if (poOptions->dfRadius1 > 0 || poOptions->dfRadius2 > 0)
break;
dfSearchRadius *= 2;
#if DEBUG_VERBOSE
CPLDebug("GDAL_GRID", "Increasing search radius to %.16g",
dfSearchRadius);
#endif
}
}
else
{
double dfNearestRSquare = std::numeric_limits<double>::max();
while (i < nPoints)
{
double dfRX = padfX[i] - dfXPoint;
double dfRY = padfY[i] - dfYPoint;
if (bRotated)
{
const double dfRXRotated = dfRX * dfCoeff1 + dfRY * dfCoeff2;
const double dfRYRotated = dfRY * dfCoeff1 - dfRX * dfCoeff2;
dfRX = dfRXRotated;
dfRY = dfRYRotated;
}
// Is this point located inside the search ellipse?
const double dfRXSquare = dfRX * dfRX;
const double dfRYSquare = dfRY * dfRY;
if (dfRadius2Square * dfRXSquare + dfRadius1Square * dfRYSquare <=
dfR12Square)
{
const double dfR2 = dfRXSquare + dfRYSquare;
if (dfR2 <= dfNearestRSquare)
{
dfNearestRSquare = dfR2;
dfNearestValue = padfZ[i];
}
}
i++;
}
}
*pdfValue = dfNearestValue;
return CE_None;
}
/************************************************************************/
/* GDALGridDataMetricMinimum() */
/************************************************************************/
/**
* Minimum data value (data metric).
*
* Minimum value found in grid node search ellipse. If there are no points
* found, the specified NODATA value will be returned.
*
* \f[
* Z=\min{(Z_1,Z_2,\ldots,Z_n)}
* \f]
*
* where
* <ul>
* <li> \f$Z\f$ is a resulting value at the grid node,
* <li> \f$Z_i\f$ is a known value at point \f$i\f$,
* <li> \f$n\f$ is a total number of points in search ellipse.
* </ul>
*
* @param poOptionsIn Algorithm parameters. This should point to
* GDALGridDataMetricsOptions object.
* @param nPoints Number of elements in input arrays.
* @param padfX Input array of X coordinates.
* @param padfY Input array of Y coordinates.
* @param padfZ Input array of Z values.
* @param dfXPoint X coordinate of the point to compute.
* @param dfYPoint Y coordinate of the point to compute.
* @param pdfValue Pointer to variable where the computed grid node value
* will be returned.
* @param hExtraParamsIn unused.
*
* @return CE_None on success or CE_Failure if something goes wrong.
*/
CPLErr GDALGridDataMetricMinimum(const void *poOptionsIn, GUInt32 nPoints,
const double *padfX, const double *padfY,
const double *padfZ, double dfXPoint,
double dfYPoint, double *pdfValue,
void *hExtraParamsIn)
{
// TODO: For optimization purposes pre-computed parameters should be moved
// out of this routine to the calling function.
const GDALGridDataMetricsOptions *const poOptions =
static_cast<const GDALGridDataMetricsOptions *>(poOptionsIn);
// Pre-compute search ellipse parameters.
const double dfRadius1Square = poOptions->dfRadius1 * poOptions->dfRadius1;
const double dfRadius2Square = poOptions->dfRadius2 * poOptions->dfRadius2;
const double dfSearchRadius =
std::max(poOptions->dfRadius1, poOptions->dfRadius2);
const double dfR12Square = dfRadius1Square * dfRadius2Square;
GDALGridExtraParameters *psExtraParams =
static_cast<GDALGridExtraParameters *>(hExtraParamsIn);
CPLQuadTree *phQuadTree = psExtraParams->hQuadTree;
// Compute coefficients for coordinate system rotation.
const double dfAngle = TO_RADIANS * poOptions->dfAngle;
const bool bRotated = dfAngle != 0.0;
const double dfCoeff1 = bRotated ? cos(dfAngle) : 0.0;
const double dfCoeff2 = bRotated ? sin(dfAngle) : 0.0;
double dfMinimumValue = std::numeric_limits<double>::max();
GUInt32 n = 0;
if (phQuadTree != nullptr)
{
CPLRectObj sAoi;
sAoi.minx = dfXPoint - dfSearchRadius;
sAoi.miny = dfYPoint - dfSearchRadius;
sAoi.maxx = dfXPoint + dfSearchRadius;
sAoi.maxy = dfYPoint + dfSearchRadius;
int nFeatureCount = 0;
GDALGridPoint **papsPoints = reinterpret_cast<GDALGridPoint **>(
CPLQuadTreeSearch(phQuadTree, &sAoi, &nFeatureCount));
if (nFeatureCount != 0)
{
for (int k = 0; k < nFeatureCount; k++)
{
const int i = papsPoints[k]->i;
const double dfRX = padfX[i] - dfXPoint;
const double dfRY = padfY[i] - dfYPoint;
if (dfRadius2Square * dfRX * dfRX +
dfRadius1Square * dfRY * dfRY <=
dfR12Square)
{
if (dfMinimumValue > padfZ[i])
dfMinimumValue = padfZ[i];
n++;
}
}
}
CPLFree(papsPoints);
}
else
{
GUInt32 i = 0;
while (i < nPoints)
{
double dfRX = padfX[i] - dfXPoint;
double dfRY = padfY[i] - dfYPoint;
if (bRotated)
{
const double dfRXRotated = dfRX * dfCoeff1 + dfRY * dfCoeff2;
const double dfRYRotated = dfRY * dfCoeff1 - dfRX * dfCoeff2;
dfRX = dfRXRotated;
dfRY = dfRYRotated;
}
// Is this point located inside the search ellipse?
if (dfRadius2Square * dfRX * dfRX + dfRadius1Square * dfRY * dfRY <=
dfR12Square)
{
if (dfMinimumValue > padfZ[i])
dfMinimumValue = padfZ[i];
n++;
}
i++;
}
}
if (n < poOptions->nMinPoints || n == 0)
{
*pdfValue = poOptions->dfNoDataValue;
}
else
{
*pdfValue = dfMinimumValue;
}
return CE_None;
}
/************************************************************************/
/* GDALGridDataMetricMinimumOrMaximumPerQuadrant() */
/************************************************************************/
/**
* Minimum or maximum data value (data metric), with a per-quadrant search
* logic.
*/
template <bool IS_MIN>
static CPLErr GDALGridDataMetricMinimumOrMaximumPerQuadrant(
const void *poOptionsIn, const double *padfX, const double *padfY,
const double *padfZ, double dfXPoint, double dfYPoint, double *pdfValue,
void *hExtraParamsIn)
{
const GDALGridDataMetricsOptions *const poOptions =
static_cast<const GDALGridDataMetricsOptions *>(poOptionsIn);
// Pre-compute search ellipse parameters.
const double dfRadius1Square = poOptions->dfRadius1 * poOptions->dfRadius1;
const double dfRadius2Square = poOptions->dfRadius2 * poOptions->dfRadius2;
const double dfSearchRadius =
std::max(poOptions->dfRadius1, poOptions->dfRadius2);
const double dfR12Square = dfRadius1Square * dfRadius2Square;
// const GUInt32 nMaxPoints = poOptions->nMaxPoints;
const GUInt32 nMinPointsPerQuadrant = poOptions->nMinPointsPerQuadrant;
const GUInt32 nMaxPointsPerQuadrant = poOptions->nMaxPointsPerQuadrant;
GDALGridExtraParameters *psExtraParams =
static_cast<GDALGridExtraParameters *>(hExtraParamsIn);
const CPLQuadTree *phQuadTree = psExtraParams->hQuadTree;
CPLAssert(phQuadTree);
CPLRectObj sAoi;
sAoi.minx = dfXPoint - dfSearchRadius;
sAoi.miny = dfYPoint - dfSearchRadius;
sAoi.maxx = dfXPoint + dfSearchRadius;
sAoi.maxy = dfYPoint + dfSearchRadius;
int nFeatureCount = 0;
GDALGridPoint **papsPoints = reinterpret_cast<GDALGridPoint **>(
CPLQuadTreeSearch(phQuadTree, &sAoi, &nFeatureCount));
std::multimap<double, double> oMapDistanceToZValuesPerQuadrant[4];
if (nFeatureCount != 0)
{
for (int k = 0; k < nFeatureCount; k++)
{
const int i = papsPoints[k]->i;
const double dfRX = padfX[i] - dfXPoint;
const double dfRY = padfY[i] - dfYPoint;
const double dfRXSquare = dfRX * dfRX;
const double dfRYSquare = dfRY * dfRY;
if (dfRadius2Square * dfRXSquare + dfRadius1Square * dfRYSquare <=
dfR12Square)
{
const int iQuadrant =
((dfRX >= 0) ? 1 : 0) | (((dfRY >= 0) ? 1 : 0) << 1);
oMapDistanceToZValuesPerQuadrant[iQuadrant].insert(
std::make_pair(dfRXSquare + dfRYSquare, padfZ[i]));
}
}
}
CPLFree(papsPoints);
std::multimap<double, double>::iterator aoIter[] = {
oMapDistanceToZValuesPerQuadrant[0].begin(),
oMapDistanceToZValuesPerQuadrant[1].begin(),
oMapDistanceToZValuesPerQuadrant[2].begin(),
oMapDistanceToZValuesPerQuadrant[3].begin(),
};
constexpr int ALL_QUADRANT_FLAGS = 1 + 2 + 4 + 8;
// Examine all "neighbors" within the radius (sorted by distance via the
// multimap), and use the closest n points based on distance until the max
// is reached.
// Do that by fetching the nearest point in quadrant 0, then the nearest
// point in quadrant 1, 2 and 3, and starting again with the next nearest
// point in quarant 0, etc.
int nQuadrantIterFinishedFlag = 0;
GUInt32 anPerQuadrant[4] = {0};
double dfExtremum = IS_MIN ? std::numeric_limits<double>::max()
: -std::numeric_limits<double>::max();
GUInt32 n = 0;
for (int iQuadrant = 0; /* true */; iQuadrant = (iQuadrant + 1) % 4)
{
if (aoIter[iQuadrant] ==
oMapDistanceToZValuesPerQuadrant[iQuadrant].end() ||
(nMaxPointsPerQuadrant > 0 &&
anPerQuadrant[iQuadrant] >= nMaxPointsPerQuadrant))
{
nQuadrantIterFinishedFlag |= 1 << iQuadrant;
if (nQuadrantIterFinishedFlag == ALL_QUADRANT_FLAGS)
break;
continue;
}
const double dfZ = aoIter[iQuadrant]->second;
++aoIter[iQuadrant];
if (IS_MIN)
{
if (dfExtremum > dfZ)
dfExtremum = dfZ;
}
else
{
if (dfExtremum < dfZ)
dfExtremum = dfZ;
}
n++;
anPerQuadrant[iQuadrant]++;
/*if( nMaxPoints > 0 && n >= nMaxPoints )
{
break;
}*/
}
if (nMinPointsPerQuadrant > 0 &&
(anPerQuadrant[0] < nMinPointsPerQuadrant ||
anPerQuadrant[1] < nMinPointsPerQuadrant ||
anPerQuadrant[2] < nMinPointsPerQuadrant ||
anPerQuadrant[3] < nMinPointsPerQuadrant))
{
*pdfValue = poOptions->dfNoDataValue;
}
else if (n < poOptions->nMinPoints || n == 0)
{
*pdfValue = poOptions->dfNoDataValue;
}
else
{
*pdfValue = dfExtremum;
}
return CE_None;
}
/************************************************************************/
/* GDALGridDataMetricMinimumPerQuadrant() */
/************************************************************************/
/**
* Minimum data value (data metric), with a per-quadrant search logic.
*/
static CPLErr GDALGridDataMetricMinimumPerQuadrant(
const void *poOptionsIn, GUInt32 /* nPoints */, const double *padfX,
const double *padfY, const double *padfZ, double dfXPoint, double dfYPoint,
double *pdfValue, void *hExtraParamsIn)
{
return GDALGridDataMetricMinimumOrMaximumPerQuadrant</*IS_MIN=*/true>(
poOptionsIn, padfX, padfY, padfZ, dfXPoint, dfYPoint, pdfValue,
hExtraParamsIn);
}
/************************************************************************/
/* GDALGridDataMetricMaximum() */
/************************************************************************/
/**
* Maximum data value (data metric).
*
* Maximum value found in grid node search ellipse. If there are no points
* found, the specified NODATA value will be returned.
*
* \f[
* Z=\max{(Z_1,Z_2,\ldots,Z_n)}
* \f]
*
* where
* <ul>
* <li> \f$Z\f$ is a resulting value at the grid node,
* <li> \f$Z_i\f$ is a known value at point \f$i\f$,
* <li> \f$n\f$ is a total number of points in search ellipse.
* </ul>
*
* @param poOptionsIn Algorithm parameters. This should point to
* GDALGridDataMetricsOptions object.
* @param nPoints Number of elements in input arrays.
* @param padfX Input array of X coordinates.
* @param padfY Input array of Y coordinates.
* @param padfZ Input array of Z values.
* @param dfXPoint X coordinate of the point to compute.
* @param dfYPoint Y coordinate of the point to compute.
* @param pdfValue Pointer to variable where the computed grid node value
* will be returned.
* @param hExtraParamsIn extra parameters (unused)
*
* @return CE_None on success or CE_Failure if something goes wrong.
*/
CPLErr GDALGridDataMetricMaximum(const void *poOptionsIn, GUInt32 nPoints,
const double *padfX, const double *padfY,
const double *padfZ, double dfXPoint,
double dfYPoint, double *pdfValue,
void *hExtraParamsIn)
{
// TODO: For optimization purposes pre-computed parameters should be moved
// out of this routine to the calling function.
const GDALGridDataMetricsOptions *const poOptions =
static_cast<const GDALGridDataMetricsOptions *>(poOptionsIn);
// Pre-compute search ellipse parameters.
const double dfRadius1Square = poOptions->dfRadius1 * poOptions->dfRadius1;
const double dfRadius2Square = poOptions->dfRadius2 * poOptions->dfRadius2;
const double dfSearchRadius =
std::max(poOptions->dfRadius1, poOptions->dfRadius2);
const double dfR12Square = dfRadius1Square * dfRadius2Square;
GDALGridExtraParameters *psExtraParams =
static_cast<GDALGridExtraParameters *>(hExtraParamsIn);
CPLQuadTree *phQuadTree = psExtraParams->hQuadTree;
// Compute coefficients for coordinate system rotation.
const double dfAngle = TO_RADIANS * poOptions->dfAngle;
const bool bRotated = dfAngle != 0.0;
const double dfCoeff1 = bRotated ? cos(dfAngle) : 0.0;
const double dfCoeff2 = bRotated ? sin(dfAngle) : 0.0;
double dfMaximumValue = -std::numeric_limits<double>::max();
GUInt32 n = 0;
if (phQuadTree != nullptr)
{
CPLRectObj sAoi;
sAoi.minx = dfXPoint - dfSearchRadius;
sAoi.miny = dfYPoint - dfSearchRadius;
sAoi.maxx = dfXPoint + dfSearchRadius;
sAoi.maxy = dfYPoint + dfSearchRadius;
int nFeatureCount = 0;
GDALGridPoint **papsPoints = reinterpret_cast<GDALGridPoint **>(
CPLQuadTreeSearch(phQuadTree, &sAoi, &nFeatureCount));
if (nFeatureCount != 0)
{
for (int k = 0; k < nFeatureCount; k++)
{
const int i = papsPoints[k]->i;
const double dfRX = padfX[i] - dfXPoint;
const double dfRY = padfY[i] - dfYPoint;
if (dfRadius2Square * dfRX * dfRX +
dfRadius1Square * dfRY * dfRY <=
dfR12Square)
{
if (dfMaximumValue < padfZ[i])
dfMaximumValue = padfZ[i];
n++;
}
}
}
CPLFree(papsPoints);
}
else
{
GUInt32 i = 0;
while (i < nPoints)
{
double dfRX = padfX[i] - dfXPoint;
double dfRY = padfY[i] - dfYPoint;
if (bRotated)
{
const double dfRXRotated = dfRX * dfCoeff1 + dfRY * dfCoeff2;
const double dfRYRotated = dfRY * dfCoeff1 - dfRX * dfCoeff2;
dfRX = dfRXRotated;
dfRY = dfRYRotated;
}
// Is this point located inside the search ellipse?
if (dfRadius2Square * dfRX * dfRX + dfRadius1Square * dfRY * dfRY <=
dfR12Square)
{
if (dfMaximumValue < padfZ[i])
dfMaximumValue = padfZ[i];
n++;
}
i++;
}
}
if (n < poOptions->nMinPoints || n == 0)
{
*pdfValue = poOptions->dfNoDataValue;
}
else
{
*pdfValue = dfMaximumValue;
}
return CE_None;
}
/************************************************************************/
/* GDALGridDataMetricMaximumPerQuadrant() */
/************************************************************************/
/**
* Maximum data value (data metric), with a per-quadrant search logic.
*/
static CPLErr GDALGridDataMetricMaximumPerQuadrant(
const void *poOptionsIn, GUInt32 /* nPoints */, const double *padfX,
const double *padfY, const double *padfZ, double dfXPoint, double dfYPoint,
double *pdfValue, void *hExtraParamsIn)
{
return GDALGridDataMetricMinimumOrMaximumPerQuadrant</*IS_MIN=*/false>(
poOptionsIn, padfX, padfY, padfZ, dfXPoint, dfYPoint, pdfValue,
hExtraParamsIn);
}
/************************************************************************/
/* GDALGridDataMetricRange() */
/************************************************************************/
/**
* Data range (data metric).
*
* A difference between the minimum and maximum values found in grid node
* search ellipse. If there are no points found, the specified NODATA
* value will be returned.
*
* \f[
* Z=\max{(Z_1,Z_2,\ldots,Z_n)}-\min{(Z_1,Z_2,\ldots,Z_n)}
* \f]
*
* where
* <ul>
* <li> \f$Z\f$ is a resulting value at the grid node,
* <li> \f$Z_i\f$ is a known value at point \f$i\f$,
* <li> \f$n\f$ is a total number of points in search ellipse.
* </ul>
*
* @param poOptionsIn Algorithm parameters. This should point to
* GDALGridDataMetricsOptions object.
* @param nPoints Number of elements in input arrays.
* @param padfX Input array of X coordinates.
* @param padfY Input array of Y coordinates.
* @param padfZ Input array of Z values.
* @param dfXPoint X coordinate of the point to compute.
* @param dfYPoint Y coordinate of the point to compute.
* @param pdfValue Pointer to variable where the computed grid node value
* will be returned.
* @param hExtraParamsIn extra parameters (unused)
*
* @return CE_None on success or CE_Failure if something goes wrong.
*/
CPLErr GDALGridDataMetricRange(const void *poOptionsIn, GUInt32 nPoints,
const double *padfX, const double *padfY,
const double *padfZ, double dfXPoint,
double dfYPoint, double *pdfValue,
void *hExtraParamsIn)
{
// TODO: For optimization purposes pre-computed parameters should be moved
// out of this routine to the calling function.
const GDALGridDataMetricsOptions *const poOptions =
static_cast<const GDALGridDataMetricsOptions *>(poOptionsIn);
// Pre-compute search ellipse parameters.
const double dfRadius1Square = poOptions->dfRadius1 * poOptions->dfRadius1;
const double dfRadius2Square = poOptions->dfRadius2 * poOptions->dfRadius2;
const double dfSearchRadius =
std::max(poOptions->dfRadius1, poOptions->dfRadius2);
const double dfR12Square = dfRadius1Square * dfRadius2Square;
GDALGridExtraParameters *psExtraParams =
static_cast<GDALGridExtraParameters *>(hExtraParamsIn);
CPLQuadTree *phQuadTree = psExtraParams->hQuadTree;
// Compute coefficients for coordinate system rotation.
const double dfAngle = TO_RADIANS * poOptions->dfAngle;
const bool bRotated = dfAngle != 0.0;
const double dfCoeff1 = bRotated ? cos(dfAngle) : 0.0;
const double dfCoeff2 = bRotated ? sin(dfAngle) : 0.0;
double dfMaximumValue = -std::numeric_limits<double>::max();
double dfMinimumValue = std::numeric_limits<double>::max();
GUInt32 n = 0;
if (phQuadTree != nullptr)
{
CPLRectObj sAoi;
sAoi.minx = dfXPoint - dfSearchRadius;
sAoi.miny = dfYPoint - dfSearchRadius;
sAoi.maxx = dfXPoint + dfSearchRadius;
sAoi.maxy = dfYPoint + dfSearchRadius;
int nFeatureCount = 0;
GDALGridPoint **papsPoints = reinterpret_cast<GDALGridPoint **>(
CPLQuadTreeSearch(phQuadTree, &sAoi, &nFeatureCount));
if (nFeatureCount != 0)
{
for (int k = 0; k < nFeatureCount; k++)
{
const int i = papsPoints[k]->i;
const double dfRX = padfX[i] - dfXPoint;
const double dfRY = padfY[i] - dfYPoint;
if (dfRadius2Square * dfRX * dfRX +
dfRadius1Square * dfRY * dfRY <=
dfR12Square)
{
if (dfMinimumValue > padfZ[i])
dfMinimumValue = padfZ[i];
if (dfMaximumValue < padfZ[i])
dfMaximumValue = padfZ[i];
n++;
}
}
}
CPLFree(papsPoints);
}
else
{
GUInt32 i = 0;
while (i < nPoints)
{
double dfRX = padfX[i] - dfXPoint;
double dfRY = padfY[i] - dfYPoint;
if (bRotated)
{
const double dfRXRotated = dfRX * dfCoeff1 + dfRY * dfCoeff2;
const double dfRYRotated = dfRY * dfCoeff1 - dfRX * dfCoeff2;
dfRX = dfRXRotated;
dfRY = dfRYRotated;
}
// Is this point located inside the search ellipse?
if (dfRadius2Square * dfRX * dfRX + dfRadius1Square * dfRY * dfRY <=
dfR12Square)
{
if (dfMinimumValue > padfZ[i])
dfMinimumValue = padfZ[i];
if (dfMaximumValue < padfZ[i])
dfMaximumValue = padfZ[i];
n++;
}
i++;
}
}
if (n < poOptions->nMinPoints || n == 0)
{
*pdfValue = poOptions->dfNoDataValue;
}
else
{
*pdfValue = dfMaximumValue - dfMinimumValue;
}
return CE_None;
}
/************************************************************************/
/* GDALGridDataMetricRangePerQuadrant() */
/************************************************************************/
/**
* Data range (data metric), with a per-quadrant search logic.
*/
static CPLErr GDALGridDataMetricRangePerQuadrant(
const void *poOptionsIn, GUInt32 /* nPoints */, const double *padfX,
const double *padfY, const double *padfZ, double dfXPoint, double dfYPoint,
double *pdfValue, void *hExtraParamsIn)
{
const GDALGridDataMetricsOptions *const poOptions =
static_cast<const GDALGridDataMetricsOptions *>(poOptionsIn);
// Pre-compute search ellipse parameters.
const double dfRadius1Square = poOptions->dfRadius1 * poOptions->dfRadius1;
const double dfRadius2Square = poOptions->dfRadius2 * poOptions->dfRadius2;
const double dfSearchRadius =
std::max(poOptions->dfRadius1, poOptions->dfRadius2);
const double dfR12Square = dfRadius1Square * dfRadius2Square;
// const GUInt32 nMaxPoints = poOptions->nMaxPoints;
const GUInt32 nMinPointsPerQuadrant = poOptions->nMinPointsPerQuadrant;
const GUInt32 nMaxPointsPerQuadrant = poOptions->nMaxPointsPerQuadrant;
GDALGridExtraParameters *psExtraParams =
static_cast<GDALGridExtraParameters *>(hExtraParamsIn);
const CPLQuadTree *phQuadTree = psExtraParams->hQuadTree;
CPLAssert(phQuadTree);
CPLRectObj sAoi;
sAoi.minx = dfXPoint - dfSearchRadius;
sAoi.miny = dfYPoint - dfSearchRadius;
sAoi.maxx = dfXPoint + dfSearchRadius;
sAoi.maxy = dfYPoint + dfSearchRadius;
int nFeatureCount = 0;
GDALGridPoint **papsPoints = reinterpret_cast<GDALGridPoint **>(
CPLQuadTreeSearch(phQuadTree, &sAoi, &nFeatureCount));
std::multimap<double, double> oMapDistanceToZValuesPerQuadrant[4];
if (nFeatureCount != 0)
{
for (int k = 0; k < nFeatureCount; k++)
{
const int i = papsPoints[k]->i;
const double dfRX = padfX[i] - dfXPoint;
const double dfRY = padfY[i] - dfYPoint;
const double dfRXSquare = dfRX * dfRX;
const double dfRYSquare = dfRY * dfRY;
if (dfRadius2Square * dfRXSquare + dfRadius1Square * dfRYSquare <=
dfR12Square)
{
const int iQuadrant =
((dfRX >= 0) ? 1 : 0) | (((dfRY >= 0) ? 1 : 0) << 1);
oMapDistanceToZValuesPerQuadrant[iQuadrant].insert(
std::make_pair(dfRXSquare + dfRYSquare, padfZ[i]));
}
}
}
CPLFree(papsPoints);
std::multimap<double, double>::iterator aoIter[] = {
oMapDistanceToZValuesPerQuadrant[0].begin(),
oMapDistanceToZValuesPerQuadrant[1].begin(),
oMapDistanceToZValuesPerQuadrant[2].begin(),
oMapDistanceToZValuesPerQuadrant[3].begin(),
};
constexpr int ALL_QUADRANT_FLAGS = 1 + 2 + 4 + 8;
// Examine all "neighbors" within the radius (sorted by distance via the
// multimap), and use the closest n points based on distance until the max
// is reached.
// Do that by fetching the nearest point in quadrant 0, then the nearest
// point in quadrant 1, 2 and 3, and starting again with the next nearest
// point in quarant 0, etc.
int nQuadrantIterFinishedFlag = 0;
GUInt32 anPerQuadrant[4] = {0};
double dfMaximumValue = -std::numeric_limits<double>::max();
double dfMinimumValue = std::numeric_limits<double>::max();
GUInt32 n = 0;
for (int iQuadrant = 0; /* true */; iQuadrant = (iQuadrant + 1) % 4)
{
if (aoIter[iQuadrant] ==
oMapDistanceToZValuesPerQuadrant[iQuadrant].end() ||
(nMaxPointsPerQuadrant > 0 &&
anPerQuadrant[iQuadrant] >= nMaxPointsPerQuadrant))
{
nQuadrantIterFinishedFlag |= 1 << iQuadrant;
if (nQuadrantIterFinishedFlag == ALL_QUADRANT_FLAGS)
break;
continue;
}
const double dfZ = aoIter[iQuadrant]->second;
++aoIter[iQuadrant];
if (dfMinimumValue > dfZ)
dfMinimumValue = dfZ;
if (dfMaximumValue < dfZ)
dfMaximumValue = dfZ;
n++;
anPerQuadrant[iQuadrant]++;
/*if( nMaxPoints > 0 && n >= nMaxPoints )
{
break;
}*/
}
if (nMinPointsPerQuadrant > 0 &&
(anPerQuadrant[0] < nMinPointsPerQuadrant ||
anPerQuadrant[1] < nMinPointsPerQuadrant ||
anPerQuadrant[2] < nMinPointsPerQuadrant ||
anPerQuadrant[3] < nMinPointsPerQuadrant))
{
*pdfValue = poOptions->dfNoDataValue;
}
else if (n < poOptions->nMinPoints || n == 0)
{
*pdfValue = poOptions->dfNoDataValue;
}
else
{
*pdfValue = dfMaximumValue - dfMinimumValue;
}
return CE_None;
}
/************************************************************************/
/* GDALGridDataMetricCount() */
/************************************************************************/
/**
* Number of data points (data metric).
*
* A number of data points found in grid node search ellipse.
*
* \f[
* Z=n
* \f]
*
* where
* <ul>
* <li> \f$Z\f$ is a resulting value at the grid node,
* <li> \f$n\f$ is a total number of points in search ellipse.
* </ul>
*
* @param poOptionsIn Algorithm parameters. This should point to
* GDALGridDataMetricsOptions object.
* @param nPoints Number of elements in input arrays.
* @param padfX Input array of X coordinates.
* @param padfY Input array of Y coordinates.
* @param padfZ Input array of Z values.
* @param dfXPoint X coordinate of the point to compute.
* @param dfYPoint Y coordinate of the point to compute.
* @param pdfValue Pointer to variable where the computed grid node value
* will be returned.
* @param hExtraParamsIn extra parameters (unused)
*
* @return CE_None on success or CE_Failure if something goes wrong.
*/
CPLErr GDALGridDataMetricCount(const void *poOptionsIn, GUInt32 nPoints,
const double *padfX, const double *padfY,
CPL_UNUSED const double *padfZ, double dfXPoint,
double dfYPoint, double *pdfValue,
void *hExtraParamsIn)
{
// TODO: For optimization purposes pre-computed parameters should be moved
// out of this routine to the calling function.
const GDALGridDataMetricsOptions *const poOptions =
static_cast<const GDALGridDataMetricsOptions *>(poOptionsIn);
// Pre-compute search ellipse parameters.
const double dfRadius1Square = poOptions->dfRadius1 * poOptions->dfRadius1;
const double dfRadius2Square = poOptions->dfRadius2 * poOptions->dfRadius2;
const double dfSearchRadius =
std::max(poOptions->dfRadius1, poOptions->dfRadius2);
const double dfR12Square = dfRadius1Square * dfRadius2Square;
GDALGridExtraParameters *psExtraParams =
static_cast<GDALGridExtraParameters *>(hExtraParamsIn);
CPLQuadTree *phQuadTree = psExtraParams->hQuadTree;
// Compute coefficients for coordinate system rotation.
const double dfAngle = TO_RADIANS * poOptions->dfAngle;
const bool bRotated = dfAngle != 0.0;
const double dfCoeff1 = bRotated ? cos(dfAngle) : 0.0;
const double dfCoeff2 = bRotated ? sin(dfAngle) : 0.0;
GUInt32 n = 0;
if (phQuadTree != nullptr)
{
CPLRectObj sAoi;
sAoi.minx = dfXPoint - dfSearchRadius;
sAoi.miny = dfYPoint - dfSearchRadius;
sAoi.maxx = dfXPoint + dfSearchRadius;
sAoi.maxy = dfYPoint + dfSearchRadius;
int nFeatureCount = 0;
GDALGridPoint **papsPoints = reinterpret_cast<GDALGridPoint **>(
CPLQuadTreeSearch(phQuadTree, &sAoi, &nFeatureCount));
if (nFeatureCount != 0)
{
for (int k = 0; k < nFeatureCount; k++)
{
const int i = papsPoints[k]->i;
const double dfRX = padfX[i] - dfXPoint;
const double dfRY = padfY[i] - dfYPoint;
if (dfRadius2Square * dfRX * dfRX +
dfRadius1Square * dfRY * dfRY <=
dfR12Square)
{
n++;
}
}
}
CPLFree(papsPoints);
}
else
{
GUInt32 i = 0;
while (i < nPoints)
{
double dfRX = padfX[i] - dfXPoint;
double dfRY = padfY[i] - dfYPoint;
if (bRotated)
{
const double dfRXRotated = dfRX * dfCoeff1 + dfRY * dfCoeff2;
const double dfRYRotated = dfRY * dfCoeff1 - dfRX * dfCoeff2;
dfRX = dfRXRotated;
dfRY = dfRYRotated;
}
// Is this point located inside the search ellipse?
if (dfRadius2Square * dfRX * dfRX + dfRadius1Square * dfRY * dfRY <=
dfR12Square)
{
n++;
}
i++;
}
}
if (n < poOptions->nMinPoints)
{
*pdfValue = poOptions->dfNoDataValue;
}
else
{
*pdfValue = static_cast<double>(n);
}
return CE_None;
}
/************************************************************************/
/* GDALGridDataMetricCountPerQuadrant() */
/************************************************************************/
/**
* Number of data points (data metric), with a per-quadrant search logic.
*/
static CPLErr GDALGridDataMetricCountPerQuadrant(
const void *poOptionsIn, GUInt32 /* nPoints */, const double *padfX,
const double *padfY, const double *padfZ, double dfXPoint, double dfYPoint,
double *pdfValue, void *hExtraParamsIn)
{
const GDALGridDataMetricsOptions *const poOptions =
static_cast<const GDALGridDataMetricsOptions *>(poOptionsIn);
// Pre-compute search ellipse parameters.
const double dfRadius1Square = poOptions->dfRadius1 * poOptions->dfRadius1;
const double dfRadius2Square = poOptions->dfRadius2 * poOptions->dfRadius2;
const double dfSearchRadius =
std::max(poOptions->dfRadius1, poOptions->dfRadius2);
const double dfR12Square = dfRadius1Square * dfRadius2Square;
// const GUInt32 nMaxPoints = poOptions->nMaxPoints;
const GUInt32 nMinPointsPerQuadrant = poOptions->nMinPointsPerQuadrant;
const GUInt32 nMaxPointsPerQuadrant = poOptions->nMaxPointsPerQuadrant;
GDALGridExtraParameters *psExtraParams =
static_cast<GDALGridExtraParameters *>(hExtraParamsIn);
const CPLQuadTree *phQuadTree = psExtraParams->hQuadTree;
CPLAssert(phQuadTree);
CPLRectObj sAoi;
sAoi.minx = dfXPoint - dfSearchRadius;
sAoi.miny = dfYPoint - dfSearchRadius;
sAoi.maxx = dfXPoint + dfSearchRadius;
sAoi.maxy = dfYPoint + dfSearchRadius;
int nFeatureCount = 0;
GDALGridPoint **papsPoints = reinterpret_cast<GDALGridPoint **>(
CPLQuadTreeSearch(phQuadTree, &sAoi, &nFeatureCount));
std::multimap<double, double> oMapDistanceToZValuesPerQuadrant[4];
if (nFeatureCount != 0)
{
for (int k = 0; k < nFeatureCount; k++)
{
const int i = papsPoints[k]->i;
const double dfRX = padfX[i] - dfXPoint;
const double dfRY = padfY[i] - dfYPoint;
const double dfRXSquare = dfRX * dfRX;
const double dfRYSquare = dfRY * dfRY;
if (dfRadius2Square * dfRXSquare + dfRadius1Square * dfRYSquare <=
dfR12Square)
{
const int iQuadrant =
((dfRX >= 0) ? 1 : 0) | (((dfRY >= 0) ? 1 : 0) << 1);
oMapDistanceToZValuesPerQuadrant[iQuadrant].insert(
std::make_pair(dfRXSquare + dfRYSquare, padfZ[i]));
}
}
}
CPLFree(papsPoints);
std::multimap<double, double>::iterator aoIter[] = {
oMapDistanceToZValuesPerQuadrant[0].begin(),
oMapDistanceToZValuesPerQuadrant[1].begin(),
oMapDistanceToZValuesPerQuadrant[2].begin(),
oMapDistanceToZValuesPerQuadrant[3].begin(),
};
constexpr int ALL_QUADRANT_FLAGS = 1 + 2 + 4 + 8;
// Examine all "neighbors" within the radius (sorted by distance via the
// multimap), and use the closest n points based on distance until the max
// is reached.
// Do that by fetching the nearest point in quadrant 0, then the nearest
// point in quadrant 1, 2 and 3, and starting again with the next nearest
// point in quarant 0, etc.
int nQuadrantIterFinishedFlag = 0;
GUInt32 anPerQuadrant[4] = {0};
GUInt32 n = 0;
for (int iQuadrant = 0; /* true */; iQuadrant = (iQuadrant + 1) % 4)
{
if (aoIter[iQuadrant] ==
oMapDistanceToZValuesPerQuadrant[iQuadrant].end() ||
(nMaxPointsPerQuadrant > 0 &&
anPerQuadrant[iQuadrant] >= nMaxPointsPerQuadrant))
{
nQuadrantIterFinishedFlag |= 1 << iQuadrant;
if (nQuadrantIterFinishedFlag == ALL_QUADRANT_FLAGS)
break;
continue;
}
++aoIter[iQuadrant];
n++;
anPerQuadrant[iQuadrant]++;
/*if( nMaxPoints > 0 && n >= nMaxPoints )
{
break;
}*/
}
if (nMinPointsPerQuadrant > 0 &&
(anPerQuadrant[0] < nMinPointsPerQuadrant ||
anPerQuadrant[1] < nMinPointsPerQuadrant ||
anPerQuadrant[2] < nMinPointsPerQuadrant ||
anPerQuadrant[3] < nMinPointsPerQuadrant))
{
*pdfValue = poOptions->dfNoDataValue;
}
else if (n < poOptions->nMinPoints)
{
*pdfValue = poOptions->dfNoDataValue;
}
else
{
*pdfValue = static_cast<double>(n);
}
return CE_None;
}
/************************************************************************/
/* GDALGridDataMetricAverageDistance() */
/************************************************************************/
/**
* Average distance (data metric).
*
* An average distance between the grid node (center of the search ellipse)
* and all of the data points found in grid node search ellipse. If there are
* no points found, the specified NODATA value will be returned.
*
* \f[
* Z=\frac{\sum_{i = 1}^n r_i}{n}
* \f]
*
* where
* <ul>
* <li> \f$Z\f$ is a resulting value at the grid node,
* <li> \f$r_i\f$ is an Euclidean distance from the grid node
* to point \f$i\f$,
* <li> \f$n\f$ is a total number of points in search ellipse.
* </ul>
*
* @param poOptionsIn Algorithm parameters. This should point to
* GDALGridDataMetricsOptions object.
* @param nPoints Number of elements in input arrays.
* @param padfX Input array of X coordinates.
* @param padfY Input array of Y coordinates.
* @param padfZ Input array of Z values (unused)
* @param dfXPoint X coordinate of the point to compute.
* @param dfYPoint Y coordinate of the point to compute.
* @param pdfValue Pointer to variable where the computed grid node value
* will be returned.
* @param hExtraParamsIn extra parameters (unused)
*
* @return CE_None on success or CE_Failure if something goes wrong.
*/
CPLErr GDALGridDataMetricAverageDistance(const void *poOptionsIn,
GUInt32 nPoints, const double *padfX,
const double *padfY,
CPL_UNUSED const double *padfZ,
double dfXPoint, double dfYPoint,
double *pdfValue, void *hExtraParamsIn)
{
// TODO: For optimization purposes pre-computed parameters should be moved
// out of this routine to the calling function.
const GDALGridDataMetricsOptions *const poOptions =
static_cast<const GDALGridDataMetricsOptions *>(poOptionsIn);
// Pre-compute search ellipse parameters.
const double dfRadius1Square = poOptions->dfRadius1 * poOptions->dfRadius1;
const double dfRadius2Square = poOptions->dfRadius2 * poOptions->dfRadius2;
const double dfSearchRadius =
std::max(poOptions->dfRadius1, poOptions->dfRadius2);
const double dfR12Square = dfRadius1Square * dfRadius2Square;
GDALGridExtraParameters *psExtraParams =
static_cast<GDALGridExtraParameters *>(hExtraParamsIn);
CPLQuadTree *phQuadTree = psExtraParams->hQuadTree;
// Compute coefficients for coordinate system rotation.
const double dfAngle = TO_RADIANS * poOptions->dfAngle;
const bool bRotated = dfAngle != 0.0;
const double dfCoeff1 = bRotated ? cos(dfAngle) : 0.0;
const double dfCoeff2 = bRotated ? sin(dfAngle) : 0.0;
double dfAccumulator = 0.0;
GUInt32 n = 0;
if (phQuadTree != nullptr)
{
CPLRectObj sAoi;
sAoi.minx = dfXPoint - dfSearchRadius;
sAoi.miny = dfYPoint - dfSearchRadius;
sAoi.maxx = dfXPoint + dfSearchRadius;
sAoi.maxy = dfYPoint + dfSearchRadius;
int nFeatureCount = 0;
GDALGridPoint **papsPoints = reinterpret_cast<GDALGridPoint **>(
CPLQuadTreeSearch(phQuadTree, &sAoi, &nFeatureCount));
if (nFeatureCount != 0)
{
for (int k = 0; k < nFeatureCount; k++)
{
const int i = papsPoints[k]->i;
const double dfRX = padfX[i] - dfXPoint;
const double dfRY = padfY[i] - dfYPoint;
if (dfRadius2Square * dfRX * dfRX +
dfRadius1Square * dfRY * dfRY <=
dfR12Square)
{
dfAccumulator += sqrt(dfRX * dfRX + dfRY * dfRY);
n++;
}
}
}
CPLFree(papsPoints);
}
else
{
GUInt32 i = 0;
while (i < nPoints)
{
double dfRX = padfX[i] - dfXPoint;
double dfRY = padfY[i] - dfYPoint;
if (bRotated)
{
const double dfRXRotated = dfRX * dfCoeff1 + dfRY * dfCoeff2;
const double dfRYRotated = dfRY * dfCoeff1 - dfRX * dfCoeff2;
dfRX = dfRXRotated;
dfRY = dfRYRotated;
}
// Is this point located inside the search ellipse?
if (dfRadius2Square * dfRX * dfRX + dfRadius1Square * dfRY * dfRY <=
dfR12Square)
{
dfAccumulator += sqrt(dfRX * dfRX + dfRY * dfRY);
n++;
}
i++;
}
}
if (n < poOptions->nMinPoints || n == 0)
{
*pdfValue = poOptions->dfNoDataValue;
}
else
{
*pdfValue = dfAccumulator / n;
}
return CE_None;
}
/************************************************************************/
/* GDALGridDataMetricAverageDistancePerQuadrant() */
/************************************************************************/
/**
* Average distance (data metric), with a per-quadrant search logic.
*/
static CPLErr GDALGridDataMetricAverageDistancePerQuadrant(
const void *poOptionsIn, GUInt32 /* nPoints */, const double *padfX,
const double *padfY, const double *padfZ, double dfXPoint, double dfYPoint,
double *pdfValue, void *hExtraParamsIn)
{
const GDALGridDataMetricsOptions *const poOptions =
static_cast<const GDALGridDataMetricsOptions *>(poOptionsIn);
// Pre-compute search ellipse parameters.
const double dfRadius1Square = poOptions->dfRadius1 * poOptions->dfRadius1;
const double dfRadius2Square = poOptions->dfRadius2 * poOptions->dfRadius2;
const double dfSearchRadius =
std::max(poOptions->dfRadius1, poOptions->dfRadius2);
const double dfR12Square = dfRadius1Square * dfRadius2Square;
// const GUInt32 nMaxPoints = poOptions->nMaxPoints;
const GUInt32 nMinPointsPerQuadrant = poOptions->nMinPointsPerQuadrant;
const GUInt32 nMaxPointsPerQuadrant = poOptions->nMaxPointsPerQuadrant;
GDALGridExtraParameters *psExtraParams =
static_cast<GDALGridExtraParameters *>(hExtraParamsIn);
const CPLQuadTree *phQuadTree = psExtraParams->hQuadTree;
CPLAssert(phQuadTree);
CPLRectObj sAoi;
sAoi.minx = dfXPoint - dfSearchRadius;
sAoi.miny = dfYPoint - dfSearchRadius;
sAoi.maxx = dfXPoint + dfSearchRadius;
sAoi.maxy = dfYPoint + dfSearchRadius;
int nFeatureCount = 0;
GDALGridPoint **papsPoints = reinterpret_cast<GDALGridPoint **>(
CPLQuadTreeSearch(phQuadTree, &sAoi, &nFeatureCount));
std::multimap<double, double> oMapDistanceToZValuesPerQuadrant[4];
if (nFeatureCount != 0)
{
for (int k = 0; k < nFeatureCount; k++)
{
const int i = papsPoints[k]->i;
const double dfRX = padfX[i] - dfXPoint;
const double dfRY = padfY[i] - dfYPoint;
const double dfRXSquare = dfRX * dfRX;
const double dfRYSquare = dfRY * dfRY;
if (dfRadius2Square * dfRXSquare + dfRadius1Square * dfRYSquare <=
dfR12Square)
{
const int iQuadrant =
((dfRX >= 0) ? 1 : 0) | (((dfRY >= 0) ? 1 : 0) << 1);
oMapDistanceToZValuesPerQuadrant[iQuadrant].insert(
std::make_pair(dfRXSquare + dfRYSquare, padfZ[i]));
}
}
}
CPLFree(papsPoints);
std::multimap<double, double>::iterator aoIter[] = {
oMapDistanceToZValuesPerQuadrant[0].begin(),
oMapDistanceToZValuesPerQuadrant[1].begin(),
oMapDistanceToZValuesPerQuadrant[2].begin(),
oMapDistanceToZValuesPerQuadrant[3].begin(),
};
constexpr int ALL_QUADRANT_FLAGS = 1 + 2 + 4 + 8;
// Examine all "neighbors" within the radius (sorted by distance via the
// multimap), and use the closest n points based on distance until the max
// is reached.
// Do that by fetching the nearest point in quadrant 0, then the nearest
// point in quadrant 1, 2 and 3, and starting again with the next nearest
// point in quarant 0, etc.
int nQuadrantIterFinishedFlag = 0;
GUInt32 anPerQuadrant[4] = {0};
GUInt32 n = 0;
double dfAccumulator = 0;
for (int iQuadrant = 0; /* true */; iQuadrant = (iQuadrant + 1) % 4)
{
if (aoIter[iQuadrant] ==
oMapDistanceToZValuesPerQuadrant[iQuadrant].end() ||
(nMaxPointsPerQuadrant > 0 &&
anPerQuadrant[iQuadrant] >= nMaxPointsPerQuadrant))
{
nQuadrantIterFinishedFlag |= 1 << iQuadrant;
if (nQuadrantIterFinishedFlag == ALL_QUADRANT_FLAGS)
break;
continue;
}
dfAccumulator += sqrt(aoIter[iQuadrant]->first);
++aoIter[iQuadrant];
n++;
anPerQuadrant[iQuadrant]++;
/*if( nMaxPoints > 0 && n >= nMaxPoints )
{
break;
}*/
}
if (nMinPointsPerQuadrant > 0 &&
(anPerQuadrant[0] < nMinPointsPerQuadrant ||
anPerQuadrant[1] < nMinPointsPerQuadrant ||
anPerQuadrant[2] < nMinPointsPerQuadrant ||
anPerQuadrant[3] < nMinPointsPerQuadrant))
{
*pdfValue = poOptions->dfNoDataValue;
}
else if (n < poOptions->nMinPoints || n == 0)
{
*pdfValue = poOptions->dfNoDataValue;
}
else
{
*pdfValue = dfAccumulator / n;
}
return CE_None;
}
/************************************************************************/
/* GDALGridDataMetricAverageDistancePts() */
/************************************************************************/
/**
* Average distance between points (data metric).
*
* An average distance between the data points found in grid node search
* ellipse. The distance between each pair of points within ellipse is
* calculated and average of all distances is set as a grid node value. If
* there are no points found, the specified NODATA value will be returned.
*
* \f[
* Z=\frac{\sum_{i = 1}^{n-1}\sum_{j=i+1}^{n}
r_{ij}}{\left(n-1\right)\,n-\frac{n+{\left(n-1\right)}^{2}-1}{2}}
* \f]
*
* where
* <ul>
* <li> \f$Z\f$ is a resulting value at the grid node,
* <li> \f$r_{ij}\f$ is an Euclidean distance between points
* \f$i\f$ and \f$j\f$,
* <li> \f$n\f$ is a total number of points in search ellipse.
* </ul>
*
* @param poOptionsIn Algorithm parameters. This should point to
* GDALGridDataMetricsOptions object.
* @param nPoints Number of elements in input arrays.
* @param padfX Input array of X coordinates.
* @param padfY Input array of Y coordinates.
* @param padfZ Input array of Z values (unused)
* @param dfXPoint X coordinate of the point to compute.
* @param dfYPoint Y coordinate of the point to compute.
* @param pdfValue Pointer to variable where the computed grid node value
* will be returned.
* @param hExtraParamsIn extra parameters (unused)
*
* @return CE_None on success or CE_Failure if something goes wrong.
*/
CPLErr GDALGridDataMetricAverageDistancePts(
const void *poOptionsIn, GUInt32 nPoints, const double *padfX,
const double *padfY, CPL_UNUSED const double *padfZ, double dfXPoint,
double dfYPoint, double *pdfValue, void *hExtraParamsIn)
{
// TODO: For optimization purposes pre-computed parameters should be moved
// out of this routine to the calling function.
const GDALGridDataMetricsOptions *const poOptions =
static_cast<const GDALGridDataMetricsOptions *>(poOptionsIn);
// Pre-compute search ellipse parameters.
const double dfRadius1Square = poOptions->dfRadius1 * poOptions->dfRadius1;
const double dfRadius2Square = poOptions->dfRadius2 * poOptions->dfRadius2;
const double dfSearchRadius =
std::max(poOptions->dfRadius1, poOptions->dfRadius2);
const double dfR12Square = dfRadius1Square * dfRadius2Square;
GDALGridExtraParameters *psExtraParams =
static_cast<GDALGridExtraParameters *>(hExtraParamsIn);
CPLQuadTree *phQuadTree = psExtraParams->hQuadTree;
// Compute coefficients for coordinate system rotation.
const double dfAngle = TO_RADIANS * poOptions->dfAngle;
const bool bRotated = dfAngle != 0.0;
const double dfCoeff1 = bRotated ? cos(dfAngle) : 0.0;
const double dfCoeff2 = bRotated ? sin(dfAngle) : 0.0;
double dfAccumulator = 0.0;
GUInt32 n = 0;
if (phQuadTree != nullptr)
{
CPLRectObj sAoi;
sAoi.minx = dfXPoint - dfSearchRadius;
sAoi.miny = dfYPoint - dfSearchRadius;
sAoi.maxx = dfXPoint + dfSearchRadius;
sAoi.maxy = dfYPoint + dfSearchRadius;
int nFeatureCount = 0;
GDALGridPoint **papsPoints = reinterpret_cast<GDALGridPoint **>(
CPLQuadTreeSearch(phQuadTree, &sAoi, &nFeatureCount));
if (nFeatureCount != 0)
{
for (int k = 0; k < nFeatureCount - 1; k++)
{
const int i = papsPoints[k]->i;
const double dfRX1 = padfX[i] - dfXPoint;
const double dfRY1 = padfY[i] - dfYPoint;
if (dfRadius2Square * dfRX1 * dfRX1 +
dfRadius1Square * dfRY1 * dfRY1 <=
dfR12Square)
{
for (int j = k; j < nFeatureCount; j++)
// Search all the remaining points within the ellipse and
// compute distances between them and the first point.
{
const int ji = papsPoints[j]->i;
double dfRX2 = padfX[ji] - dfXPoint;
double dfRY2 = padfY[ji] - dfYPoint;
if (dfRadius2Square * dfRX2 * dfRX2 +
dfRadius1Square * dfRY2 * dfRY2 <=
dfR12Square)
{
const double dfRX = padfX[ji] - padfX[i];
const double dfRY = padfY[ji] - padfY[i];
dfAccumulator += sqrt(dfRX * dfRX + dfRY * dfRY);
n++;
}
}
}
}
}
CPLFree(papsPoints);
}
else
{
GUInt32 i = 0;
while (i < nPoints - 1)
{
double dfRX1 = padfX[i] - dfXPoint;
double dfRY1 = padfY[i] - dfYPoint;
if (bRotated)
{
const double dfRXRotated = dfRX1 * dfCoeff1 + dfRY1 * dfCoeff2;
const double dfRYRotated = dfRY1 * dfCoeff1 - dfRX1 * dfCoeff2;
dfRX1 = dfRXRotated;
dfRY1 = dfRYRotated;
}
// Is this point located inside the search ellipse?
if (dfRadius2Square * dfRX1 * dfRX1 +
dfRadius1Square * dfRY1 * dfRY1 <=
dfR12Square)
{
// Search all the remaining points within the ellipse and
// compute distances between them and the first point.
for (GUInt32 j = i + 1; j < nPoints; j++)
{
double dfRX2 = padfX[j] - dfXPoint;
double dfRY2 = padfY[j] - dfYPoint;
if (bRotated)
{
const double dfRXRotated =
dfRX2 * dfCoeff1 + dfRY2 * dfCoeff2;
const double dfRYRotated =
dfRY2 * dfCoeff1 - dfRX2 * dfCoeff2;
dfRX2 = dfRXRotated;
dfRY2 = dfRYRotated;
}
if (dfRadius2Square * dfRX2 * dfRX2 +
dfRadius1Square * dfRY2 * dfRY2 <=
dfR12Square)
{
const double dfRX = padfX[j] - padfX[i];
const double dfRY = padfY[j] - padfY[i];
dfAccumulator += sqrt(dfRX * dfRX + dfRY * dfRY);
n++;
}
}
}
i++;
}
}
// Search for the first point within the search ellipse.
if (n < poOptions->nMinPoints || n == 0)
{
*pdfValue = poOptions->dfNoDataValue;
}
else
{
*pdfValue = dfAccumulator / n;
}
return CE_None;
}
/************************************************************************/
/* GDALGridLinear() */
/************************************************************************/
/**
* Linear interpolation
*
* The Linear method performs linear interpolation by finding in which triangle
* of a Delaunay triangulation the point is, and by doing interpolation from
* its barycentric coordinates within the triangle.
* If the point is not in any triangle, depending on the radius, the
* algorithm will use the value of the nearest point (radius != 0),
* or the nodata value (radius == 0)
*
* @param poOptionsIn Algorithm parameters. This should point to
* GDALGridLinearOptions object.
* @param nPoints Number of elements in input arrays.
* @param padfX Input array of X coordinates.
* @param padfY Input array of Y coordinates.
* @param padfZ Input array of Z values.
* @param dfXPoint X coordinate of the point to compute.
* @param dfYPoint Y coordinate of the point to compute.
* @param pdfValue Pointer to variable where the computed grid node value
* will be returned.
* @param hExtraParams extra parameters
*
* @return CE_None on success or CE_Failure if something goes wrong.
*
*/
CPLErr GDALGridLinear(const void *poOptionsIn, GUInt32 nPoints,
const double *padfX, const double *padfY,
const double *padfZ, double dfXPoint, double dfYPoint,
double *pdfValue, void *hExtraParams)
{
GDALGridExtraParameters *psExtraParams =
static_cast<GDALGridExtraParameters *>(hExtraParams);
GDALTriangulation *psTriangulation = psExtraParams->psTriangulation;
int nOutputFacetIdx = -1;
const bool bRet = CPL_TO_BOOL(GDALTriangulationFindFacetDirected(
psTriangulation, psExtraParams->nInitialFacetIdx, dfXPoint, dfYPoint,
&nOutputFacetIdx));
if (bRet)
{
CPLAssert(nOutputFacetIdx >= 0);
// Reuse output facet idx as next initial index since we proceed line by
// line.
psExtraParams->nInitialFacetIdx = nOutputFacetIdx;
double lambda1 = 0.0;
double lambda2 = 0.0;
double lambda3 = 0.0;
GDALTriangulationComputeBarycentricCoordinates(
psTriangulation, nOutputFacetIdx, dfXPoint, dfYPoint, &lambda1,
&lambda2, &lambda3);
const int i1 =
psTriangulation->pasFacets[nOutputFacetIdx].anVertexIdx[0];
const int i2 =
psTriangulation->pasFacets[nOutputFacetIdx].anVertexIdx[1];
const int i3 =
psTriangulation->pasFacets[nOutputFacetIdx].anVertexIdx[2];
*pdfValue =
lambda1 * padfZ[i1] + lambda2 * padfZ[i2] + lambda3 * padfZ[i3];
}
else
{
if (nOutputFacetIdx >= 0)
{
// Also reuse this failed output facet, when valid, as seed for
// next search.
psExtraParams->nInitialFacetIdx = nOutputFacetIdx;
}
const GDALGridLinearOptions *const poOptions =
static_cast<const GDALGridLinearOptions *>(poOptionsIn);
const double dfRadius = poOptions->dfRadius;
if (dfRadius == 0.0)
{
*pdfValue = poOptions->dfNoDataValue;
}
else
{
GDALGridNearestNeighborOptions sNeighbourOptions;
sNeighbourOptions.nSizeOfStructure = sizeof(sNeighbourOptions);
sNeighbourOptions.dfRadius1 =
dfRadius < 0.0 || dfRadius >= std::numeric_limits<double>::max()
? 0.0
: dfRadius;
sNeighbourOptions.dfRadius2 =
dfRadius < 0.0 || dfRadius >= std::numeric_limits<double>::max()
? 0.0
: dfRadius;
sNeighbourOptions.dfAngle = 0.0;
sNeighbourOptions.dfNoDataValue = poOptions->dfNoDataValue;
return GDALGridNearestNeighbor(&sNeighbourOptions, nPoints, padfX,
padfY, padfZ, dfXPoint, dfYPoint,
pdfValue, hExtraParams);
}
}
return CE_None;
}
/************************************************************************/
/* GDALGridJob */
/************************************************************************/
typedef struct _GDALGridJob GDALGridJob;
struct _GDALGridJob
{
GUInt32 nYStart;
GByte *pabyData;
GUInt32 nYStep;
GUInt32 nXSize;
GUInt32 nYSize;
double dfXMin;
double dfYMin;
double dfDeltaX;
double dfDeltaY;
GUInt32 nPoints;
const double *padfX;
const double *padfY;
const double *padfZ;
const void *poOptions;
GDALGridFunction pfnGDALGridMethod;
GDALGridExtraParameters *psExtraParameters;
int (*pfnProgress)(GDALGridJob *psJob);
GDALDataType eType;
int *pnCounter;
int nCounterSingleThreaded;
volatile int *pbStop;
CPLCond *hCond;
CPLMutex *hCondMutex;
GDALProgressFunc pfnRealProgress;
void *pRealProgressArg;
};
/************************************************************************/
/* GDALGridProgressMultiThread() */
/************************************************************************/
// Return TRUE if the computation must be interrupted.
static int GDALGridProgressMultiThread(GDALGridJob *psJob)
{
CPLAcquireMutex(psJob->hCondMutex, 1.0);
++(*psJob->pnCounter);
CPLCondSignal(psJob->hCond);
const int bStop = *psJob->pbStop;
CPLReleaseMutex(psJob->hCondMutex);
return bStop;
}
/************************************************************************/
/* GDALGridProgressMonoThread() */
/************************************************************************/
// Return TRUE if the computation must be interrupted.
static int GDALGridProgressMonoThread(GDALGridJob *psJob)
{
const int nCounter = ++(psJob->nCounterSingleThreaded);
if (!psJob->pfnRealProgress(nCounter / static_cast<double>(psJob->nYSize),
"", psJob->pRealProgressArg))
{
CPLError(CE_Failure, CPLE_UserInterrupt, "User terminated");
*psJob->pbStop = TRUE;
return TRUE;
}
return FALSE;
}
/************************************************************************/
/* GDALGridJobProcess() */
/************************************************************************/
static void GDALGridJobProcess(void *user_data)
{
GDALGridJob *const psJob = static_cast<GDALGridJob *>(user_data);
int (*pfnProgress)(GDALGridJob * psJob) = psJob->pfnProgress;
const GUInt32 nXSize = psJob->nXSize;
/* -------------------------------------------------------------------- */
/* Allocate a buffer of scanline size, fill it with gridded values */
/* and use GDALCopyWords() to copy values into output data array with */
/* appropriate data type conversion. */
/* -------------------------------------------------------------------- */
double *padfValues =
static_cast<double *>(VSI_MALLOC2_VERBOSE(sizeof(double), nXSize));
if (padfValues == nullptr)
{
*(psJob->pbStop) = TRUE;
if (pfnProgress != nullptr)
pfnProgress(psJob); // To notify the main thread.
return;
}
const GUInt32 nYStart = psJob->nYStart;
const GUInt32 nYStep = psJob->nYStep;
GByte *pabyData = psJob->pabyData;
const GUInt32 nYSize = psJob->nYSize;
const double dfXMin = psJob->dfXMin;
const double dfYMin = psJob->dfYMin;
const double dfDeltaX = psJob->dfDeltaX;
const double dfDeltaY = psJob->dfDeltaY;
const GUInt32 nPoints = psJob->nPoints;
const double *padfX = psJob->padfX;
const double *padfY = psJob->padfY;
const double *padfZ = psJob->padfZ;
const void *poOptions = psJob->poOptions;
GDALGridFunction pfnGDALGridMethod = psJob->pfnGDALGridMethod;
// Have a local copy of sExtraParameters since we want to modify
// nInitialFacetIdx.
GDALGridExtraParameters sExtraParameters = *psJob->psExtraParameters;
const GDALDataType eType = psJob->eType;
const int nDataTypeSize = GDALGetDataTypeSizeBytes(eType);
const int nLineSpace = nXSize * nDataTypeSize;
for (GUInt32 nYPoint = nYStart; nYPoint < nYSize; nYPoint += nYStep)
{
const double dfYPoint = dfYMin + (nYPoint + 0.5) * dfDeltaY;
for (GUInt32 nXPoint = 0; nXPoint < nXSize; nXPoint++)
{
const double dfXPoint = dfXMin + (nXPoint + 0.5) * dfDeltaX;
if ((*pfnGDALGridMethod)(poOptions, nPoints, padfX, padfY, padfZ,
dfXPoint, dfYPoint, padfValues + nXPoint,
&sExtraParameters) != CE_None)
{
CPLError(CE_Failure, CPLE_AppDefined,
"Gridding failed at X position %lu, Y position %lu",
static_cast<long unsigned int>(nXPoint),
static_cast<long unsigned int>(nYPoint));
*psJob->pbStop = TRUE;
if (pfnProgress != nullptr)
pfnProgress(psJob); // To notify the main thread.
break;
}
}
GDALCopyWords(padfValues, GDT_Float64, sizeof(double),
pabyData + nYPoint * nLineSpace, eType, nDataTypeSize,
nXSize);
if (*psJob->pbStop || (pfnProgress != nullptr && pfnProgress(psJob)))
break;
}
CPLFree(padfValues);
}
/************************************************************************/
/* GDALGridContextCreate() */
/************************************************************************/
struct GDALGridContext
{
GDALGridAlgorithm eAlgorithm;
void *poOptions;
GDALGridFunction pfnGDALGridMethod;
GUInt32 nPoints;
GDALGridPoint *pasGridPoints;
GDALGridXYArrays sXYArrays;
GDALGridExtraParameters sExtraParameters;
double *padfX;
double *padfY;
double *padfZ;
bool bFreePadfXYZArrays;
CPLWorkerThreadPool *poWorkerThreadPool;
};
static void GDALGridContextCreateQuadTree(GDALGridContext *psContext);
/**
* Creates a context to do regular gridding from the scattered data.
*
* This function takes the arrays of X and Y coordinates and corresponding Z
* values as input to prepare computation of regular grid (or call it a raster)
* from these scattered data.
*
* On Intel/AMD i386/x86_64 architectures, some
* gridding methods will be optimized with SSE instructions (provided GDAL
* has been compiled with such support, and it is available at runtime).
* Currently, only 'invdist' algorithm with default parameters has an optimized
* implementation.
* This can provide substantial speed-up, but sometimes at the expense of
* reduced floating point precision. This can be disabled by setting the
* GDAL_USE_SSE configuration option to NO.
* A further optimized version can use the AVX
* instruction set. This can be disabled by setting the GDAL_USE_AVX
* configuration option to NO.
*
* It is possible to set the GDAL_NUM_THREADS
* configuration option to parallelize the processing. The value to set is
* the number of worker threads, or ALL_CPUS to use all the cores/CPUs of the
* computer (default value).
*
* @param eAlgorithm Gridding method.
* @param poOptions Options to control chosen gridding method.
* @param nPoints Number of elements in input arrays.
* @param padfX Input array of X coordinates.
* @param padfY Input array of Y coordinates.
* @param padfZ Input array of Z values.
* @param bCallerWillKeepPointArraysAlive Whether the provided padfX, padfY,
* padfZ arrays will still be "alive" during the calls to
* GDALGridContextProcess(). Setting to TRUE prevent them from being
* duplicated in the context. If unsure, set to FALSE.
*
* @return the context (to be freed with GDALGridContextFree()) or NULL in case
* or error.
*
*/
GDALGridContext *GDALGridContextCreate(GDALGridAlgorithm eAlgorithm,
const void *poOptions, GUInt32 nPoints,
const double *padfX, const double *padfY,
const double *padfZ,
int bCallerWillKeepPointArraysAlive)
{
CPLAssert(poOptions);
CPLAssert(padfX);
CPLAssert(padfY);
CPLAssert(padfZ);
bool bCreateQuadTree = false;
const unsigned int nPointCountThreshold =
atoi(CPLGetConfigOption("GDAL_GRID_POINT_COUNT_THRESHOLD", "100"));
// Starting address aligned on 32-byte boundary for AVX.
float *pafXAligned = nullptr;
float *pafYAligned = nullptr;
float *pafZAligned = nullptr;
void *poOptionsNew = nullptr;
GDALGridFunction pfnGDALGridMethod = nullptr;
switch (eAlgorithm)
{
case GGA_InverseDistanceToAPower:
{
const auto poOptionsOld =
static_cast<const GDALGridInverseDistanceToAPowerOptions *>(
poOptions);
if (poOptionsOld->nSizeOfStructure != sizeof(*poOptionsOld))
{
CPLError(CE_Failure, CPLE_AppDefined,
"Wrong value of nSizeOfStructure member");
return nullptr;
}
poOptionsNew =
CPLMalloc(sizeof(GDALGridInverseDistanceToAPowerOptions));
memcpy(poOptionsNew, poOptions,
sizeof(GDALGridInverseDistanceToAPowerOptions));
const GDALGridInverseDistanceToAPowerOptions *const poPower =
static_cast<const GDALGridInverseDistanceToAPowerOptions *>(
poOptions);
if (poPower->dfRadius1 == 0.0 && poPower->dfRadius2 == 0.0)
{
const double dfPower = poPower->dfPower;
const double dfSmoothing = poPower->dfSmoothing;
pfnGDALGridMethod = GDALGridInverseDistanceToAPowerNoSearch;
if (dfPower == 2.0 && dfSmoothing == 0.0)
{
#ifdef HAVE_AVX_AT_COMPILE_TIME
if (CPLTestBool(
CPLGetConfigOption("GDAL_USE_AVX", "YES")) &&
CPLHaveRuntimeAVX())
{
pafXAligned = static_cast<float *>(
VSI_MALLOC_ALIGNED_AUTO_VERBOSE(sizeof(float) *
nPoints));
pafYAligned = static_cast<float *>(
VSI_MALLOC_ALIGNED_AUTO_VERBOSE(sizeof(float) *
nPoints));
pafZAligned = static_cast<float *>(
VSI_MALLOC_ALIGNED_AUTO_VERBOSE(sizeof(float) *
nPoints));
if (pafXAligned != nullptr && pafYAligned != nullptr &&
pafZAligned != nullptr)
{
CPLDebug("GDAL_GRID",
"Using AVX optimized version");
pfnGDALGridMethod =
GDALGridInverseDistanceToAPower2NoSmoothingNoSearchAVX;
for (GUInt32 i = 0; i < nPoints; i++)
{
pafXAligned[i] = static_cast<float>(padfX[i]);
pafYAligned[i] = static_cast<float>(padfY[i]);
pafZAligned[i] = static_cast<float>(padfZ[i]);
}
}
else
{
VSIFree(pafXAligned);
VSIFree(pafYAligned);
VSIFree(pafZAligned);
pafXAligned = nullptr;
pafYAligned = nullptr;
pafZAligned = nullptr;
}
}
#endif
#ifdef HAVE_SSE_AT_COMPILE_TIME
if (pafXAligned == nullptr &&
CPLTestBool(CPLGetConfigOption("GDAL_USE_SSE", "YES"))
#if !defined(USE_NEON_OPTIMIZATIONS)
&& CPLHaveRuntimeSSE()
#endif
)
{
pafXAligned = static_cast<float *>(
VSI_MALLOC_ALIGNED_AUTO_VERBOSE(sizeof(float) *
nPoints));
pafYAligned = static_cast<float *>(
VSI_MALLOC_ALIGNED_AUTO_VERBOSE(sizeof(float) *
nPoints));
pafZAligned = static_cast<float *>(
VSI_MALLOC_ALIGNED_AUTO_VERBOSE(sizeof(float) *
nPoints));
if (pafXAligned != nullptr && pafYAligned != nullptr &&
pafZAligned != nullptr)
{
CPLDebug("GDAL_GRID",
"Using SSE optimized version");
pfnGDALGridMethod =
GDALGridInverseDistanceToAPower2NoSmoothingNoSearchSSE;
for (GUInt32 i = 0; i < nPoints; i++)
{
pafXAligned[i] = static_cast<float>(padfX[i]);
pafYAligned[i] = static_cast<float>(padfY[i]);
pafZAligned[i] = static_cast<float>(padfZ[i]);
}
}
else
{
VSIFree(pafXAligned);
VSIFree(pafYAligned);
VSIFree(pafZAligned);
pafXAligned = nullptr;
pafYAligned = nullptr;
pafZAligned = nullptr;
}
}
#endif // HAVE_SSE_AT_COMPILE_TIME
}
}
else
{
pfnGDALGridMethod = GDALGridInverseDistanceToAPower;
}
break;
}
case GGA_InverseDistanceToAPowerNearestNeighbor:
{
const auto poOptionsOld = static_cast<
const GDALGridInverseDistanceToAPowerNearestNeighborOptions *>(
poOptions);
if (poOptionsOld->nSizeOfStructure != sizeof(*poOptionsOld))
{
CPLError(CE_Failure, CPLE_AppDefined,
"Wrong value of nSizeOfStructure member");
return nullptr;
}
poOptionsNew = CPLMalloc(
sizeof(GDALGridInverseDistanceToAPowerNearestNeighborOptions));
memcpy(
poOptionsNew, poOptions,
sizeof(GDALGridInverseDistanceToAPowerNearestNeighborOptions));
if (poOptionsOld->nMinPointsPerQuadrant != 0 ||
poOptionsOld->nMaxPointsPerQuadrant != 0)
{
pfnGDALGridMethod =
GDALGridInverseDistanceToAPowerNearestNeighborPerQuadrant;
}
else
{
pfnGDALGridMethod =
GDALGridInverseDistanceToAPowerNearestNeighbor;
}
bCreateQuadTree = true;
break;
}
case GGA_MovingAverage:
{
const auto poOptionsOld =
static_cast<const GDALGridMovingAverageOptions *>(poOptions);
if (poOptionsOld->nSizeOfStructure != sizeof(*poOptionsOld))
{
CPLError(CE_Failure, CPLE_AppDefined,
"Wrong value of nSizeOfStructure member");
return nullptr;
}
poOptionsNew = CPLMalloc(sizeof(GDALGridMovingAverageOptions));
memcpy(poOptionsNew, poOptions,
sizeof(GDALGridMovingAverageOptions));
if (poOptionsOld->nMinPointsPerQuadrant != 0 ||
poOptionsOld->nMaxPointsPerQuadrant != 0)
{
pfnGDALGridMethod = GDALGridMovingAveragePerQuadrant;
bCreateQuadTree = true;
}
else
{
pfnGDALGridMethod = GDALGridMovingAverage;
bCreateQuadTree = (nPoints > nPointCountThreshold &&
poOptionsOld->dfAngle == 0.0 &&
(poOptionsOld->dfRadius1 > 0.0 ||
poOptionsOld->dfRadius2 > 0.0));
}
break;
}
case GGA_NearestNeighbor:
{
const auto poOptionsOld =
static_cast<const GDALGridNearestNeighborOptions *>(poOptions);
if (poOptionsOld->nSizeOfStructure != sizeof(*poOptionsOld))
{
CPLError(CE_Failure, CPLE_AppDefined,
"Wrong value of nSizeOfStructure member");
return nullptr;
}
poOptionsNew = CPLMalloc(sizeof(GDALGridNearestNeighborOptions));
memcpy(poOptionsNew, poOptions,
sizeof(GDALGridNearestNeighborOptions));
pfnGDALGridMethod = GDALGridNearestNeighbor;
bCreateQuadTree = (nPoints > nPointCountThreshold &&
poOptionsOld->dfAngle == 0.0 &&
(poOptionsOld->dfRadius1 > 0.0 ||
poOptionsOld->dfRadius2 > 0.0));
break;
}
case GGA_MetricMinimum:
{
const auto poOptionsOld =
static_cast<const GDALGridDataMetricsOptions *>(poOptions);
if (poOptionsOld->nSizeOfStructure != sizeof(*poOptionsOld))
{
CPLError(CE_Failure, CPLE_AppDefined,
"Wrong value of nSizeOfStructure member");
return nullptr;
}
poOptionsNew = CPLMalloc(sizeof(GDALGridDataMetricsOptions));
memcpy(poOptionsNew, poOptions, sizeof(GDALGridDataMetricsOptions));
if (poOptionsOld->nMinPointsPerQuadrant != 0 ||
poOptionsOld->nMaxPointsPerQuadrant != 0)
{
pfnGDALGridMethod = GDALGridDataMetricMinimumPerQuadrant;
bCreateQuadTree = true;
}
else
{
pfnGDALGridMethod = GDALGridDataMetricMinimum;
bCreateQuadTree = (nPoints > nPointCountThreshold &&
poOptionsOld->dfAngle == 0.0 &&
(poOptionsOld->dfRadius1 > 0.0 ||
poOptionsOld->dfRadius2 > 0.0));
}
break;
}
case GGA_MetricMaximum:
{
const auto poOptionsOld =
static_cast<const GDALGridDataMetricsOptions *>(poOptions);
if (poOptionsOld->nSizeOfStructure != sizeof(*poOptionsOld))
{
CPLError(CE_Failure, CPLE_AppDefined,
"Wrong value of nSizeOfStructure member");
return nullptr;
}
poOptionsNew = CPLMalloc(sizeof(GDALGridDataMetricsOptions));
memcpy(poOptionsNew, poOptions, sizeof(GDALGridDataMetricsOptions));
if (poOptionsOld->nMinPointsPerQuadrant != 0 ||
poOptionsOld->nMaxPointsPerQuadrant != 0)
{
pfnGDALGridMethod = GDALGridDataMetricMaximumPerQuadrant;
bCreateQuadTree = true;
}
else
{
pfnGDALGridMethod = GDALGridDataMetricMaximum;
bCreateQuadTree = (nPoints > nPointCountThreshold &&
poOptionsOld->dfAngle == 0.0 &&
(poOptionsOld->dfRadius1 > 0.0 ||
poOptionsOld->dfRadius2 > 0.0));
}
break;
}
case GGA_MetricRange:
{
const auto poOptionsOld =
static_cast<const GDALGridDataMetricsOptions *>(poOptions);
if (poOptionsOld->nSizeOfStructure != sizeof(*poOptionsOld))
{
CPLError(CE_Failure, CPLE_AppDefined,
"Wrong value of nSizeOfStructure member");
return nullptr;
}
poOptionsNew = CPLMalloc(sizeof(GDALGridDataMetricsOptions));
memcpy(poOptionsNew, poOptions, sizeof(GDALGridDataMetricsOptions));
if (poOptionsOld->nMinPointsPerQuadrant != 0 ||
poOptionsOld->nMaxPointsPerQuadrant != 0)
{
pfnGDALGridMethod = GDALGridDataMetricRangePerQuadrant;
bCreateQuadTree = true;
}
else
{
pfnGDALGridMethod = GDALGridDataMetricRange;
bCreateQuadTree = (nPoints > nPointCountThreshold &&
poOptionsOld->dfAngle == 0.0 &&
(poOptionsOld->dfRadius1 > 0.0 ||
poOptionsOld->dfRadius2 > 0.0));
}
break;
}
case GGA_MetricCount:
{
const auto poOptionsOld =
static_cast<const GDALGridDataMetricsOptions *>(poOptions);
if (poOptionsOld->nSizeOfStructure != sizeof(*poOptionsOld))
{
CPLError(CE_Failure, CPLE_AppDefined,
"Wrong value of nSizeOfStructure member");
return nullptr;
}
poOptionsNew = CPLMalloc(sizeof(GDALGridDataMetricsOptions));
memcpy(poOptionsNew, poOptions, sizeof(GDALGridDataMetricsOptions));
if (poOptionsOld->nMinPointsPerQuadrant != 0 ||
poOptionsOld->nMaxPointsPerQuadrant != 0)
{
pfnGDALGridMethod = GDALGridDataMetricCountPerQuadrant;
bCreateQuadTree = true;
}
else
{
pfnGDALGridMethod = GDALGridDataMetricCount;
bCreateQuadTree = (nPoints > nPointCountThreshold &&
poOptionsOld->dfAngle == 0.0 &&
(poOptionsOld->dfRadius1 > 0.0 ||
poOptionsOld->dfRadius2 > 0.0));
}
break;
}
case GGA_MetricAverageDistance:
{
const auto poOptionsOld =
static_cast<const GDALGridDataMetricsOptions *>(poOptions);
if (poOptionsOld->nSizeOfStructure != sizeof(*poOptionsOld))
{
CPLError(CE_Failure, CPLE_AppDefined,
"Wrong value of nSizeOfStructure member");
return nullptr;
}
poOptionsNew = CPLMalloc(sizeof(GDALGridDataMetricsOptions));
memcpy(poOptionsNew, poOptions, sizeof(GDALGridDataMetricsOptions));
if (poOptionsOld->nMinPointsPerQuadrant != 0 ||
poOptionsOld->nMaxPointsPerQuadrant != 0)
{
pfnGDALGridMethod =
GDALGridDataMetricAverageDistancePerQuadrant;
bCreateQuadTree = true;
}
else
{
pfnGDALGridMethod = GDALGridDataMetricAverageDistance;
bCreateQuadTree = (nPoints > nPointCountThreshold &&
poOptionsOld->dfAngle == 0.0 &&
(poOptionsOld->dfRadius1 > 0.0 ||
poOptionsOld->dfRadius2 > 0.0));
}
break;
}
case GGA_MetricAverageDistancePts:
{
const auto poOptionsOld =
static_cast<const GDALGridDataMetricsOptions *>(poOptions);
if (poOptionsOld->nSizeOfStructure != sizeof(*poOptionsOld))
{
CPLError(CE_Failure, CPLE_AppDefined,
"Wrong value of nSizeOfStructure member");
return nullptr;
}
poOptionsNew = CPLMalloc(sizeof(GDALGridDataMetricsOptions));
memcpy(poOptionsNew, poOptions, sizeof(GDALGridDataMetricsOptions));
pfnGDALGridMethod = GDALGridDataMetricAverageDistancePts;
bCreateQuadTree = (nPoints > nPointCountThreshold &&
poOptionsOld->dfAngle == 0.0 &&
(poOptionsOld->dfRadius1 > 0.0 ||
poOptionsOld->dfRadius2 > 0.0));
break;
}
case GGA_Linear:
{
const auto poOptionsOld =
static_cast<const GDALGridLinearOptions *>(poOptions);
if (poOptionsOld->nSizeOfStructure != sizeof(*poOptionsOld))
{
CPLError(CE_Failure, CPLE_AppDefined,
"Wrong value of nSizeOfStructure member");
return nullptr;
}
poOptionsNew = CPLMalloc(sizeof(GDALGridLinearOptions));
memcpy(poOptionsNew, poOptions, sizeof(GDALGridLinearOptions));
pfnGDALGridMethod = GDALGridLinear;
break;
}
default:
CPLError(CE_Failure, CPLE_IllegalArg,
"GDAL does not support gridding method %d", eAlgorithm);
return nullptr;
}
if (pafXAligned == nullptr && !bCallerWillKeepPointArraysAlive)
{
double *padfXNew =
static_cast<double *>(VSI_MALLOC2_VERBOSE(nPoints, sizeof(double)));
double *padfYNew =
static_cast<double *>(VSI_MALLOC2_VERBOSE(nPoints, sizeof(double)));
double *padfZNew =
static_cast<double *>(VSI_MALLOC2_VERBOSE(nPoints, sizeof(double)));
if (padfXNew == nullptr || padfYNew == nullptr || padfZNew == nullptr)
{
VSIFree(padfXNew);
VSIFree(padfYNew);
VSIFree(padfZNew);
CPLFree(poOptionsNew);
return nullptr;
}
memcpy(padfXNew, padfX, nPoints * sizeof(double));
memcpy(padfYNew, padfY, nPoints * sizeof(double));
memcpy(padfZNew, padfZ, nPoints * sizeof(double));
padfX = padfXNew;
padfY = padfYNew;
padfZ = padfZNew;
}
GDALGridContext *psContext =
static_cast<GDALGridContext *>(CPLCalloc(1, sizeof(GDALGridContext)));
psContext->eAlgorithm = eAlgorithm;
psContext->poOptions = poOptionsNew;
psContext->pfnGDALGridMethod = pfnGDALGridMethod;
psContext->nPoints = nPoints;
psContext->pasGridPoints = nullptr;
psContext->sXYArrays.padfX = padfX;
psContext->sXYArrays.padfY = padfY;
psContext->sExtraParameters.hQuadTree = nullptr;
psContext->sExtraParameters.dfInitialSearchRadius = 0.0;
psContext->sExtraParameters.pafX = pafXAligned;
psContext->sExtraParameters.pafY = pafYAligned;
psContext->sExtraParameters.pafZ = pafZAligned;
psContext->sExtraParameters.psTriangulation = nullptr;
psContext->sExtraParameters.nInitialFacetIdx = 0;
psContext->padfX = pafXAligned ? nullptr : const_cast<double *>(padfX);
psContext->padfY = pafXAligned ? nullptr : const_cast<double *>(padfY);
psContext->padfZ = pafXAligned ? nullptr : const_cast<double *>(padfZ);
psContext->bFreePadfXYZArrays =
pafXAligned ? false : !bCallerWillKeepPointArraysAlive;
/* -------------------------------------------------------------------- */
/* Create quadtree if requested and possible. */
/* -------------------------------------------------------------------- */
if (bCreateQuadTree)
{
GDALGridContextCreateQuadTree(psContext);
if (psContext->sExtraParameters.hQuadTree == nullptr &&
(eAlgorithm == GGA_InverseDistanceToAPowerNearestNeighbor ||
pfnGDALGridMethod == GDALGridMovingAveragePerQuadrant))
{
// shouldn't happen unless memory allocation failure occurs
GDALGridContextFree(psContext);
return nullptr;
}
}
/* -------------------------------------------------------------------- */
/* Pre-compute extra parameters in GDALGridExtraParameters */
/* -------------------------------------------------------------------- */
if (eAlgorithm == GGA_InverseDistanceToAPowerNearestNeighbor)
{
const double dfPower =
static_cast<
const GDALGridInverseDistanceToAPowerNearestNeighborOptions *>(
poOptions)
->dfPower;
psContext->sExtraParameters.dfPowerDiv2PreComp = dfPower / 2;
const double dfRadius =
static_cast<
const GDALGridInverseDistanceToAPowerNearestNeighborOptions *>(
poOptions)
->dfRadius;
psContext->sExtraParameters.dfRadiusPower2PreComp = pow(dfRadius, 2);
}
if (eAlgorithm == GGA_Linear)
{
psContext->sExtraParameters.psTriangulation =
GDALTriangulationCreateDelaunay(nPoints, padfX, padfY);
if (psContext->sExtraParameters.psTriangulation == nullptr)
{
GDALGridContextFree(psContext);
return nullptr;
}
GDALTriangulationComputeBarycentricCoefficients(
psContext->sExtraParameters.psTriangulation, padfX, padfY);
}
/* -------------------------------------------------------------------- */
/* Start thread pool. */
/* -------------------------------------------------------------------- */
const char *pszThreads = CPLGetConfigOption("GDAL_NUM_THREADS", "ALL_CPUS");
int nThreads = 0;
if (EQUAL(pszThreads, "ALL_CPUS"))
nThreads = CPLGetNumCPUs();
else
nThreads = atoi(pszThreads);
if (nThreads > 128)
nThreads = 128;
if (nThreads > 1)
{
psContext->poWorkerThreadPool = new CPLWorkerThreadPool();
if (!psContext->poWorkerThreadPool->Setup(nThreads, nullptr, nullptr))
{
delete psContext->poWorkerThreadPool;
psContext->poWorkerThreadPool = nullptr;
}
else
{
CPLDebug("GDAL_GRID", "Using %d threads", nThreads);
}
}
else
psContext->poWorkerThreadPool = nullptr;
return psContext;
}
/************************************************************************/
/* GDALGridContextCreateQuadTree() */
/************************************************************************/
void GDALGridContextCreateQuadTree(GDALGridContext *psContext)
{
const GUInt32 nPoints = psContext->nPoints;
psContext->pasGridPoints = static_cast<GDALGridPoint *>(
VSI_MALLOC2_VERBOSE(nPoints, sizeof(GDALGridPoint)));
if (psContext->pasGridPoints != nullptr)
{
const double *const padfX = psContext->padfX;
const double *const padfY = psContext->padfY;
// Determine point extents.
CPLRectObj sRect;
sRect.minx = padfX[0];
sRect.miny = padfY[0];
sRect.maxx = padfX[0];
sRect.maxy = padfY[0];
for (GUInt32 i = 1; i < nPoints; i++)
{
if (padfX[i] < sRect.minx)
sRect.minx = padfX[i];
if (padfY[i] < sRect.miny)
sRect.miny = padfY[i];
if (padfX[i] > sRect.maxx)
sRect.maxx = padfX[i];
if (padfY[i] > sRect.maxy)
sRect.maxy = padfY[i];
}
// Initial value for search radius is the typical dimension of a
// "pixel" of the point array (assuming rather uniform distribution).
psContext->sExtraParameters.dfInitialSearchRadius = sqrt(
(sRect.maxx - sRect.minx) * (sRect.maxy - sRect.miny) / nPoints);
psContext->sExtraParameters.hQuadTree =
CPLQuadTreeCreate(&sRect, GDALGridGetPointBounds);
for (GUInt32 i = 0; i < nPoints; i++)
{
psContext->pasGridPoints[i].psXYArrays = &(psContext->sXYArrays);
psContext->pasGridPoints[i].i = i;
CPLQuadTreeInsert(psContext->sExtraParameters.hQuadTree,
psContext->pasGridPoints + i);
}
}
}
/************************************************************************/
/* GDALGridContextFree() */
/************************************************************************/
/**
* Free a context used created by GDALGridContextCreate()
*
* @param psContext the context.
*
*/
void GDALGridContextFree(GDALGridContext *psContext)
{
if (psContext)
{
CPLFree(psContext->poOptions);
CPLFree(psContext->pasGridPoints);
if (psContext->sExtraParameters.hQuadTree != nullptr)
CPLQuadTreeDestroy(psContext->sExtraParameters.hQuadTree);
if (psContext->bFreePadfXYZArrays)
{
CPLFree(psContext->padfX);
CPLFree(psContext->padfY);
CPLFree(psContext->padfZ);
}
VSIFreeAligned(psContext->sExtraParameters.pafX);
VSIFreeAligned(psContext->sExtraParameters.pafY);
VSIFreeAligned(psContext->sExtraParameters.pafZ);
if (psContext->sExtraParameters.psTriangulation)
GDALTriangulationFree(psContext->sExtraParameters.psTriangulation);
delete psContext->poWorkerThreadPool;
CPLFree(psContext);
}
}
/************************************************************************/
/* GDALGridContextProcess() */
/************************************************************************/
/**
* Do the gridding of a window of a raster.
*
* This function takes the gridding context as input to prepare computation
* of regular grid (or call it a raster) from these scattered data.
* You should supply the extent of the output grid and allocate array
* sufficient to hold such a grid.
*
* @param psContext Gridding context.
* @param dfXMin Lowest X border of output grid.
* @param dfXMax Highest X border of output grid.
* @param dfYMin Lowest Y border of output grid.
* @param dfYMax Highest Y border of output grid.
* @param nXSize Number of columns in output grid.
* @param nYSize Number of rows in output grid.
* @param eType Data type of output array.
* @param pData Pointer to array where the computed grid will be stored.
* @param pfnProgress a GDALProgressFunc() compatible callback function for
* reporting progress or NULL.
* @param pProgressArg argument to be passed to pfnProgress. May be NULL.
*
* @return CE_None on success or CE_Failure if something goes wrong.
*
*/
CPLErr GDALGridContextProcess(GDALGridContext *psContext, double dfXMin,
double dfXMax, double dfYMin, double dfYMax,
GUInt32 nXSize, GUInt32 nYSize,
GDALDataType eType, void *pData,
GDALProgressFunc pfnProgress, void *pProgressArg)
{
CPLAssert(psContext);
CPLAssert(pData);
if (nXSize == 0 || nYSize == 0)
{
CPLError(CE_Failure, CPLE_IllegalArg,
"Output raster dimensions should have non-zero size.");
return CE_Failure;
}
const double dfDeltaX = (dfXMax - dfXMin) / nXSize;
const double dfDeltaY = (dfYMax - dfYMin) / nYSize;
// For linear, check if we will need to fallback to nearest neighbour
// by sampling along the edges. If all points on edges are within
// triangles, then interior points will also be.
if (psContext->eAlgorithm == GGA_Linear &&
psContext->sExtraParameters.hQuadTree == nullptr)
{
bool bNeedNearest = false;
int nStartLeft = 0;
int nStartRight = 0;
const double dfXPointMin = dfXMin + (0 + 0.5) * dfDeltaX;
const double dfXPointMax = dfXMin + (nXSize - 1 + 0.5) * dfDeltaX;
for (GUInt32 nYPoint = 0; !bNeedNearest && nYPoint < nYSize; nYPoint++)
{
const double dfYPoint = dfYMin + (nYPoint + 0.5) * dfDeltaY;
if (!GDALTriangulationFindFacetDirected(
psContext->sExtraParameters.psTriangulation, nStartLeft,
dfXPointMin, dfYPoint, &nStartLeft))
{
bNeedNearest = true;
}
if (!GDALTriangulationFindFacetDirected(
psContext->sExtraParameters.psTriangulation, nStartRight,
dfXPointMax, dfYPoint, &nStartRight))
{
bNeedNearest = true;
}
}
int nStartTop = 0;
int nStartBottom = 0;
const double dfYPointMin = dfYMin + (0 + 0.5) * dfDeltaY;
const double dfYPointMax = dfYMin + (nYSize - 1 + 0.5) * dfDeltaY;
for (GUInt32 nXPoint = 1; !bNeedNearest && nXPoint + 1 < nXSize;
nXPoint++)
{
const double dfXPoint = dfXMin + (nXPoint + 0.5) * dfDeltaX;
if (!GDALTriangulationFindFacetDirected(
psContext->sExtraParameters.psTriangulation, nStartTop,
dfXPoint, dfYPointMin, &nStartTop))
{
bNeedNearest = true;
}
if (!GDALTriangulationFindFacetDirected(
psContext->sExtraParameters.psTriangulation, nStartBottom,
dfXPoint, dfYPointMax, &nStartBottom))
{
bNeedNearest = true;
}
}
if (bNeedNearest)
{
CPLDebug("GDAL_GRID", "Will need nearest neighbour");
GDALGridContextCreateQuadTree(psContext);
}
}
int nCounter = 0;
volatile int bStop = FALSE;
GDALGridJob sJob;
sJob.nYStart = 0;
sJob.pabyData = static_cast<GByte *>(pData);
sJob.nYStep = 1;
sJob.nXSize = nXSize;
sJob.nYSize = nYSize;
sJob.dfXMin = dfXMin;
sJob.dfYMin = dfYMin;
sJob.dfDeltaX = dfDeltaX;
sJob.dfDeltaY = dfDeltaY;
sJob.nPoints = psContext->nPoints;
sJob.padfX = psContext->padfX;
sJob.padfY = psContext->padfY;
sJob.padfZ = psContext->padfZ;
sJob.poOptions = psContext->poOptions;
sJob.pfnGDALGridMethod = psContext->pfnGDALGridMethod;
sJob.psExtraParameters = &psContext->sExtraParameters;
sJob.pfnProgress = nullptr;
sJob.eType = eType;
sJob.pfnRealProgress = pfnProgress;
sJob.pRealProgressArg = pProgressArg;
sJob.nCounterSingleThreaded = 0;
sJob.pnCounter = &nCounter;
sJob.pbStop = &bStop;
sJob.hCond = nullptr;
sJob.hCondMutex = nullptr;
if (psContext->poWorkerThreadPool == nullptr)
{
if (sJob.pfnRealProgress != nullptr &&
sJob.pfnRealProgress != GDALDummyProgress)
{
sJob.pfnProgress = GDALGridProgressMonoThread;
}
GDALGridJobProcess(&sJob);
}
else
{
int nThreads = psContext->poWorkerThreadPool->GetThreadCount();
GDALGridJob *pasJobs = static_cast<GDALGridJob *>(
CPLMalloc(sizeof(GDALGridJob) * nThreads));
sJob.nYStep = nThreads;
sJob.hCondMutex = CPLCreateMutex(); /* and implicitly take the mutex */
sJob.hCond = CPLCreateCond();
sJob.pfnProgress = GDALGridProgressMultiThread;
/* --------------------------------------------------------------------
*/
/* Start threads. */
/* --------------------------------------------------------------------
*/
for (int i = 0; i < nThreads && !bStop; i++)
{
memcpy(&pasJobs[i], &sJob, sizeof(GDALGridJob));
pasJobs[i].nYStart = i;
psContext->poWorkerThreadPool->SubmitJob(GDALGridJobProcess,
&pasJobs[i]);
}
/* --------------------------------------------------------------------
*/
/* Report progress. */
/* --------------------------------------------------------------------
*/
while (*(sJob.pnCounter) < static_cast<int>(nYSize) && !bStop)
{
CPLCondWait(sJob.hCond, sJob.hCondMutex);
int nLocalCounter = *(sJob.pnCounter);
CPLReleaseMutex(sJob.hCondMutex);
if (pfnProgress != nullptr &&
!pfnProgress(nLocalCounter / static_cast<double>(nYSize), "",
pProgressArg))
{
CPLError(CE_Failure, CPLE_UserInterrupt, "User terminated");
bStop = TRUE;
}
CPLAcquireMutex(sJob.hCondMutex, 1.0);
}
// Release mutex before joining threads, otherwise they will dead-lock
// forever in GDALGridProgressMultiThread().
CPLReleaseMutex(sJob.hCondMutex);
/* --------------------------------------------------------------------
*/
/* Wait for all threads to complete and finish. */
/* --------------------------------------------------------------------
*/
psContext->poWorkerThreadPool->WaitCompletion();
CPLFree(pasJobs);
CPLDestroyCond(sJob.hCond);
CPLDestroyMutex(sJob.hCondMutex);
}
return bStop ? CE_Failure : CE_None;
}
/************************************************************************/
/* GDALGridCreate() */
/************************************************************************/
/**
* Create regular grid from the scattered data.
*
* This function takes the arrays of X and Y coordinates and corresponding Z
* values as input and computes regular grid (or call it a raster) from these
* scattered data. You should supply geometry and extent of the output grid
* and allocate array sufficient to hold such a grid.
*
* It is possible to set the GDAL_NUM_THREADS
* configuration option to parallelize the processing. The value to set is
* the number of worker threads, or ALL_CPUS to use all the cores/CPUs of the
* computer (default value).
*
* On Intel/AMD i386/x86_64 architectures, some
* gridding methods will be optimized with SSE instructions (provided GDAL
* has been compiled with such support, and it is available at runtime).
* Currently, only 'invdist' algorithm with default parameters has an optimized
* implementation.
* This can provide substantial speed-up, but sometimes at the expense of
* reduced floating point precision. This can be disabled by setting the
* GDAL_USE_SSE configuration option to NO.
* A further optimized version can use the AVX
* instruction set. This can be disabled by setting the GDAL_USE_AVX
* configuration option to NO.
*
* Note: it will be more efficient to use GDALGridContextCreate(),
* GDALGridContextProcess() and GDALGridContextFree() when doing repeated
* gridding operations with the same algorithm, parameters and points, and
* moving the window in the output grid.
*
* @param eAlgorithm Gridding method.
* @param poOptions Options to control chosen gridding method.
* @param nPoints Number of elements in input arrays.
* @param padfX Input array of X coordinates.
* @param padfY Input array of Y coordinates.
* @param padfZ Input array of Z values.
* @param dfXMin Lowest X border of output grid.
* @param dfXMax Highest X border of output grid.
* @param dfYMin Lowest Y border of output grid.
* @param dfYMax Highest Y border of output grid.
* @param nXSize Number of columns in output grid.
* @param nYSize Number of rows in output grid.
* @param eType Data type of output array.
* @param pData Pointer to array where the computed grid will be stored.
* @param pfnProgress a GDALProgressFunc() compatible callback function for
* reporting progress or NULL.
* @param pProgressArg argument to be passed to pfnProgress. May be NULL.
*
* @return CE_None on success or CE_Failure if something goes wrong.
*/
CPLErr GDALGridCreate(GDALGridAlgorithm eAlgorithm, const void *poOptions,
GUInt32 nPoints, const double *padfX, const double *padfY,
const double *padfZ, double dfXMin, double dfXMax,
double dfYMin, double dfYMax, GUInt32 nXSize,
GUInt32 nYSize, GDALDataType eType, void *pData,
GDALProgressFunc pfnProgress, void *pProgressArg)
{
GDALGridContext *psContext = GDALGridContextCreate(
eAlgorithm, poOptions, nPoints, padfX, padfY, padfZ, TRUE);
CPLErr eErr = CE_Failure;
if (psContext)
{
eErr = GDALGridContextProcess(psContext, dfXMin, dfXMax, dfYMin, dfYMax,
nXSize, nYSize, eType, pData, pfnProgress,
pProgressArg);
}
GDALGridContextFree(psContext);
return eErr;
}
/************************************************************************/
/* GDALGridParseAlgorithmAndOptions() */
/************************************************************************/
/** Translates mnemonic gridding algorithm names into GDALGridAlgorithm code,
* parse control parameters and assign defaults.
*/
CPLErr GDALGridParseAlgorithmAndOptions(const char *pszAlgorithm,
GDALGridAlgorithm *peAlgorithm,
void **ppOptions)
{
CPLAssert(pszAlgorithm);
CPLAssert(peAlgorithm);
CPLAssert(ppOptions);
*ppOptions = nullptr;
char **papszParams = CSLTokenizeString2(pszAlgorithm, ":", FALSE);
if (CSLCount(papszParams) < 1)
{
CSLDestroy(papszParams);
return CE_Failure;
}
if (EQUAL(papszParams[0], szAlgNameInvDist))
{
if (CSLFetchNameValue(papszParams, "min_points_per_quadrant") ||
CSLFetchNameValue(papszParams, "max_points_per_quadrant"))
{
// Remap invdist to invdistnn if per quadrant is required
if (CSLFetchNameValue(papszParams, "radius") == nullptr)
{
const double dfRadius1 =
CPLAtofM(CSLFetchNameValueDef(papszParams, "radius1", "1"));
const double dfRadius2 =
CPLAtofM(CSLFetchNameValueDef(papszParams, "radius2", "1"));
if (dfRadius1 != dfRadius2)
{
CPLError(CE_Failure, CPLE_NotSupported,
"radius1 != radius2 not supported when "
"min_points_per_quadrant and/or "
"max_points_per_quadrant is specified");
CSLDestroy(papszParams);
return CE_Failure;
}
}
if (CPLAtofM(CSLFetchNameValueDef(papszParams, "angle", "0")) != 0)
{
CPLError(CE_Failure, CPLE_NotSupported,
"angle != 0 not supported when "
"min_points_per_quadrant and/or "
"max_points_per_quadrant is specified");
CSLDestroy(papszParams);
return CE_Failure;
}
char **papszNewParams = CSLAddString(nullptr, "invdistnn");
if (CSLFetchNameValue(papszParams, "radius") == nullptr)
{
papszNewParams = CSLSetNameValue(
papszNewParams, "radius",
CSLFetchNameValueDef(papszParams, "radius1", "1"));
}
for (const char *pszItem :
{"radius", "power", "smoothing", "max_points", "min_points",
"nodata", "min_points_per_quadrant",
"max_points_per_quadrant"})
{
const char *pszValue = CSLFetchNameValue(papszParams, pszItem);
if (pszValue)
papszNewParams =
CSLSetNameValue(papszNewParams, pszItem, pszValue);
}
CSLDestroy(papszParams);
papszParams = papszNewParams;
*peAlgorithm = GGA_InverseDistanceToAPowerNearestNeighbor;
}
else
{
*peAlgorithm = GGA_InverseDistanceToAPower;
}
}
else if (EQUAL(papszParams[0], szAlgNameInvDistNearestNeighbor))
{
*peAlgorithm = GGA_InverseDistanceToAPowerNearestNeighbor;
}
else if (EQUAL(papszParams[0], szAlgNameAverage))
{
*peAlgorithm = GGA_MovingAverage;
}
else if (EQUAL(papszParams[0], szAlgNameNearest))
{
*peAlgorithm = GGA_NearestNeighbor;
}
else if (EQUAL(papszParams[0], szAlgNameMinimum))
{
*peAlgorithm = GGA_MetricMinimum;
}
else if (EQUAL(papszParams[0], szAlgNameMaximum))
{
*peAlgorithm = GGA_MetricMaximum;
}
else if (EQUAL(papszParams[0], szAlgNameRange))
{
*peAlgorithm = GGA_MetricRange;
}
else if (EQUAL(papszParams[0], szAlgNameCount))
{
*peAlgorithm = GGA_MetricCount;
}
else if (EQUAL(papszParams[0], szAlgNameAverageDistance))
{
*peAlgorithm = GGA_MetricAverageDistance;
}
else if (EQUAL(papszParams[0], szAlgNameAverageDistancePts))
{
*peAlgorithm = GGA_MetricAverageDistancePts;
}
else if (EQUAL(papszParams[0], szAlgNameLinear))
{
*peAlgorithm = GGA_Linear;
}
else
{
CPLError(CE_Failure, CPLE_IllegalArg,
"Unsupported gridding method \"%s\"", papszParams[0]);
CSLDestroy(papszParams);
return CE_Failure;
}
/* -------------------------------------------------------------------- */
/* Parse algorithm parameters and assign defaults. */
/* -------------------------------------------------------------------- */
const char *const *papszKnownOptions = nullptr;
switch (*peAlgorithm)
{
case GGA_InverseDistanceToAPower:
default:
{
*ppOptions =
CPLMalloc(sizeof(GDALGridInverseDistanceToAPowerOptions));
GDALGridInverseDistanceToAPowerOptions *const poPowerOpts =
static_cast<GDALGridInverseDistanceToAPowerOptions *>(
*ppOptions);
poPowerOpts->nSizeOfStructure = sizeof(*poPowerOpts);
const char *pszValue = CSLFetchNameValue(papszParams, "power");
poPowerOpts->dfPower = pszValue ? CPLAtofM(pszValue) : 2.0;
pszValue = CSLFetchNameValue(papszParams, "smoothing");
poPowerOpts->dfSmoothing = pszValue ? CPLAtofM(pszValue) : 0.0;
pszValue = CSLFetchNameValue(papszParams, "radius");
if (pszValue)
{
poPowerOpts->dfRadius1 = CPLAtofM(pszValue);
poPowerOpts->dfRadius2 = poPowerOpts->dfRadius1;
}
else
{
pszValue = CSLFetchNameValue(papszParams, "radius1");
poPowerOpts->dfRadius1 = pszValue ? CPLAtofM(pszValue) : 0.0;
pszValue = CSLFetchNameValue(papszParams, "radius2");
poPowerOpts->dfRadius2 = pszValue ? CPLAtofM(pszValue) : 0.0;
}
pszValue = CSLFetchNameValue(papszParams, "angle");
poPowerOpts->dfAngle = pszValue ? CPLAtofM(pszValue) : 0.0;
pszValue = CSLFetchNameValue(papszParams, "max_points");
poPowerOpts->nMaxPoints =
static_cast<GUInt32>(pszValue ? CPLAtofM(pszValue) : 0);
pszValue = CSLFetchNameValue(papszParams, "min_points");
poPowerOpts->nMinPoints =
static_cast<GUInt32>(pszValue ? CPLAtofM(pszValue) : 0);
pszValue = CSLFetchNameValue(papszParams, "nodata");
poPowerOpts->dfNoDataValue = pszValue ? CPLAtofM(pszValue) : 0.0;
static const char *const apszKnownOptions[] = {
"power", "smoothing", "radius", "radius1", "radius2",
"angle", "max_points", "min_points", "nodata", nullptr};
papszKnownOptions = apszKnownOptions;
break;
}
case GGA_InverseDistanceToAPowerNearestNeighbor:
{
*ppOptions = CPLMalloc(
sizeof(GDALGridInverseDistanceToAPowerNearestNeighborOptions));
GDALGridInverseDistanceToAPowerNearestNeighborOptions
*const poPowerOpts = static_cast<
GDALGridInverseDistanceToAPowerNearestNeighborOptions *>(
*ppOptions);
poPowerOpts->nSizeOfStructure = sizeof(*poPowerOpts);
const char *pszValue = CSLFetchNameValue(papszParams, "power");
poPowerOpts->dfPower = pszValue ? CPLAtofM(pszValue) : 2.0;
pszValue = CSLFetchNameValue(papszParams, "smoothing");
poPowerOpts->dfSmoothing = pszValue ? CPLAtofM(pszValue) : 0.0;
pszValue = CSLFetchNameValue(papszParams, "radius");
poPowerOpts->dfRadius = pszValue ? CPLAtofM(pszValue) : 1.0;
if (!(poPowerOpts->dfRadius > 0))
{
CPLError(CE_Failure, CPLE_IllegalArg,
"Radius value should be strictly positive");
CSLDestroy(papszParams);
return CE_Failure;
}
pszValue = CSLFetchNameValue(papszParams, "max_points");
poPowerOpts->nMaxPoints =
static_cast<GUInt32>(pszValue ? CPLAtofM(pszValue) : 12);
pszValue = CSLFetchNameValue(papszParams, "min_points");
poPowerOpts->nMinPoints =
static_cast<GUInt32>(pszValue ? CPLAtofM(pszValue) : 0);
pszValue = CSLFetchNameValue(papszParams, "nodata");
poPowerOpts->dfNoDataValue = pszValue ? CPLAtofM(pszValue) : 0.0;
pszValue =
CSLFetchNameValue(papszParams, "min_points_per_quadrant");
poPowerOpts->nMinPointsPerQuadrant =
static_cast<GUInt32>(pszValue ? CPLAtofM(pszValue) : 0);
pszValue =
CSLFetchNameValue(papszParams, "max_points_per_quadrant");
poPowerOpts->nMaxPointsPerQuadrant =
static_cast<GUInt32>(pszValue ? CPLAtofM(pszValue) : 0);
static const char *const apszKnownOptions[] = {
"power",
"smoothing",
"radius",
"max_points",
"min_points",
"nodata",
"min_points_per_quadrant",
"max_points_per_quadrant",
nullptr};
papszKnownOptions = apszKnownOptions;
break;
}
case GGA_MovingAverage:
{
*ppOptions = CPLMalloc(sizeof(GDALGridMovingAverageOptions));
GDALGridMovingAverageOptions *const poAverageOpts =
static_cast<GDALGridMovingAverageOptions *>(*ppOptions);
poAverageOpts->nSizeOfStructure = sizeof(*poAverageOpts);
const char *pszValue = CSLFetchNameValue(papszParams, "radius");
if (pszValue)
{
poAverageOpts->dfRadius1 = CPLAtofM(pszValue);
poAverageOpts->dfRadius2 = poAverageOpts->dfRadius1;
}
else
{
pszValue = CSLFetchNameValue(papszParams, "radius1");
poAverageOpts->dfRadius1 = pszValue ? CPLAtofM(pszValue) : 0.0;
pszValue = CSLFetchNameValue(papszParams, "radius2");
poAverageOpts->dfRadius2 = pszValue ? CPLAtofM(pszValue) : 0.0;
}
pszValue = CSLFetchNameValue(papszParams, "angle");
poAverageOpts->dfAngle = pszValue ? CPLAtofM(pszValue) : 0.0;
pszValue = CSLFetchNameValue(papszParams, "min_points");
poAverageOpts->nMinPoints =
static_cast<GUInt32>(pszValue ? CPLAtofM(pszValue) : 0);
pszValue = CSLFetchNameValue(papszParams, "max_points");
poAverageOpts->nMaxPoints =
static_cast<GUInt32>(pszValue ? CPLAtofM(pszValue) : 0);
pszValue = CSLFetchNameValue(papszParams, "nodata");
poAverageOpts->dfNoDataValue = pszValue ? CPLAtofM(pszValue) : 0.0;
pszValue =
CSLFetchNameValue(papszParams, "min_points_per_quadrant");
poAverageOpts->nMinPointsPerQuadrant =
static_cast<GUInt32>(pszValue ? CPLAtofM(pszValue) : 0);
pszValue =
CSLFetchNameValue(papszParams, "max_points_per_quadrant");
poAverageOpts->nMaxPointsPerQuadrant =
static_cast<GUInt32>(pszValue ? CPLAtofM(pszValue) : 0);
if (poAverageOpts->nMinPointsPerQuadrant != 0 ||
poAverageOpts->nMaxPointsPerQuadrant != 0)
{
if (!(poAverageOpts->dfRadius1 > 0) ||
!(poAverageOpts->dfRadius2 > 0))
{
CPLError(CE_Failure, CPLE_IllegalArg,
"Radius value should be strictly positive when "
"per quadrant parameters are specified");
CSLDestroy(papszParams);
return CE_Failure;
}
if (poAverageOpts->dfAngle != 0)
{
CPLError(CE_Failure, CPLE_NotSupported,
"angle != 0 not supported when "
"per quadrant parameters are specified");
CSLDestroy(papszParams);
return CE_Failure;
}
}
else if (poAverageOpts->nMaxPoints > 0)
{
CPLError(CE_Warning, CPLE_AppDefined,
"max_points is ignored unless one of "
"min_points_per_quadrant or max_points_per_quadrant "
"is >= 1");
}
static const char *const apszKnownOptions[] = {
"radius",
"radius1",
"radius2",
"angle",
"min_points",
"max_points",
"nodata",
"min_points_per_quadrant",
"max_points_per_quadrant",
nullptr};
papszKnownOptions = apszKnownOptions;
break;
}
case GGA_NearestNeighbor:
{
*ppOptions = CPLMalloc(sizeof(GDALGridNearestNeighborOptions));
GDALGridNearestNeighborOptions *const poNeighborOpts =
static_cast<GDALGridNearestNeighborOptions *>(*ppOptions);
poNeighborOpts->nSizeOfStructure = sizeof(*poNeighborOpts);
const char *pszValue = CSLFetchNameValue(papszParams, "radius");
if (pszValue)
{
poNeighborOpts->dfRadius1 = CPLAtofM(pszValue);
poNeighborOpts->dfRadius2 = poNeighborOpts->dfRadius1;
}
else
{
pszValue = CSLFetchNameValue(papszParams, "radius1");
poNeighborOpts->dfRadius1 = pszValue ? CPLAtofM(pszValue) : 0.0;
pszValue = CSLFetchNameValue(papszParams, "radius2");
poNeighborOpts->dfRadius2 = pszValue ? CPLAtofM(pszValue) : 0.0;
}
pszValue = CSLFetchNameValue(papszParams, "angle");
poNeighborOpts->dfAngle = pszValue ? CPLAtofM(pszValue) : 0.0;
pszValue = CSLFetchNameValue(papszParams, "nodata");
poNeighborOpts->dfNoDataValue = pszValue ? CPLAtofM(pszValue) : 0.0;
static const char *const apszKnownOptions[] = {
"radius", "radius1", "radius2", "angle", "nodata", nullptr};
papszKnownOptions = apszKnownOptions;
break;
}
case GGA_MetricMinimum:
case GGA_MetricMaximum:
case GGA_MetricRange:
case GGA_MetricCount:
case GGA_MetricAverageDistance:
case GGA_MetricAverageDistancePts:
{
*ppOptions = CPLMalloc(sizeof(GDALGridDataMetricsOptions));
GDALGridDataMetricsOptions *const poMetricsOptions =
static_cast<GDALGridDataMetricsOptions *>(*ppOptions);
poMetricsOptions->nSizeOfStructure = sizeof(*poMetricsOptions);
const char *pszValue = CSLFetchNameValue(papszParams, "radius");
if (pszValue)
{
poMetricsOptions->dfRadius1 = CPLAtofM(pszValue);
poMetricsOptions->dfRadius2 = poMetricsOptions->dfRadius1;
}
else
{
pszValue = CSLFetchNameValue(papszParams, "radius1");
poMetricsOptions->dfRadius1 =
pszValue ? CPLAtofM(pszValue) : 0.0;
pszValue = CSLFetchNameValue(papszParams, "radius2");
poMetricsOptions->dfRadius2 =
pszValue ? CPLAtofM(pszValue) : 0.0;
}
pszValue = CSLFetchNameValue(papszParams, "angle");
poMetricsOptions->dfAngle = pszValue ? CPLAtofM(pszValue) : 0.0;
pszValue = CSLFetchNameValue(papszParams, "min_points");
poMetricsOptions->nMinPoints = pszValue ? atoi(pszValue) : 0;
pszValue = CSLFetchNameValue(papszParams, "nodata");
poMetricsOptions->dfNoDataValue =
pszValue ? CPLAtofM(pszValue) : 0.0;
pszValue =
CSLFetchNameValue(papszParams, "min_points_per_quadrant");
poMetricsOptions->nMinPointsPerQuadrant =
static_cast<GUInt32>(pszValue ? CPLAtofM(pszValue) : 0);
pszValue =
CSLFetchNameValue(papszParams, "max_points_per_quadrant");
poMetricsOptions->nMaxPointsPerQuadrant =
static_cast<GUInt32>(pszValue ? CPLAtofM(pszValue) : 0);
if (poMetricsOptions->nMinPointsPerQuadrant != 0 ||
poMetricsOptions->nMaxPointsPerQuadrant != 0)
{
if (*peAlgorithm == GGA_MetricAverageDistancePts)
{
CPLError(CE_Failure, CPLE_NotSupported,
"Algorithm %s not supported when "
"per quadrant parameters are specified",
szAlgNameAverageDistancePts);
CSLDestroy(papszParams);
return CE_Failure;
}
if (!(poMetricsOptions->dfRadius1 > 0) ||
!(poMetricsOptions->dfRadius2 > 0))
{
CPLError(CE_Failure, CPLE_IllegalArg,
"Radius value should be strictly positive when "
"per quadrant parameters are specified");
CSLDestroy(papszParams);
return CE_Failure;
}
if (poMetricsOptions->dfAngle != 0)
{
CPLError(CE_Failure, CPLE_NotSupported,
"angle != 0 not supported when "
"per quadrant parameters are specified");
CSLDestroy(papszParams);
return CE_Failure;
}
}
static const char *const apszKnownOptions[] = {
"radius",
"radius1",
"radius2",
"angle",
"min_points",
"nodata",
"min_points_per_quadrant",
"max_points_per_quadrant",
nullptr};
papszKnownOptions = apszKnownOptions;
break;
}
case GGA_Linear:
{
*ppOptions = CPLMalloc(sizeof(GDALGridLinearOptions));
GDALGridLinearOptions *const poLinearOpts =
static_cast<GDALGridLinearOptions *>(*ppOptions);
poLinearOpts->nSizeOfStructure = sizeof(*poLinearOpts);
const char *pszValue = CSLFetchNameValue(papszParams, "radius");
poLinearOpts->dfRadius = pszValue ? CPLAtofM(pszValue) : -1.0;
pszValue = CSLFetchNameValue(papszParams, "nodata");
poLinearOpts->dfNoDataValue = pszValue ? CPLAtofM(pszValue) : 0.0;
static const char *const apszKnownOptions[] = {"radius", "nodata",
nullptr};
papszKnownOptions = apszKnownOptions;
break;
}
}
if (papszKnownOptions)
{
for (int i = 1; papszParams[i] != nullptr; ++i)
{
char *pszKey = nullptr;
CPL_IGNORE_RET_VAL(CPLParseNameValue(papszParams[i], &pszKey));
if (pszKey)
{
bool bKnownKey = false;
for (const char *const *papszKnownKeyIter = papszKnownOptions;
*papszKnownKeyIter; ++papszKnownKeyIter)
{
if (EQUAL(*papszKnownKeyIter, pszKey))
{
bKnownKey = true;
break;
}
}
if (!bKnownKey)
{
CPLError(CE_Warning, CPLE_AppDefined, "Option %s ignored",
pszKey);
}
}
CPLFree(pszKey);
}
}
CSLDestroy(papszParams);
return CE_None;
}
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