/// <summary>
/// 拷贝构造函数。
/// </summary>
/// <param name="interpolationParameter">插值通用参数设置类。</param>
/// <exception cref="ArgumentNullException">插值通用参数设置类为 null 时抛出异常。</exception>
public InterpolationParameter(InterpolationParameter interpolationParameter)
{
if (interpolationParameter == null)
{
throw new ArgumentNullException("interpolationParameter");
}
if (interpolationParameter.Bounds != null)
{
this.Bounds = new Rectangle2D(interpolationParameter.Bounds);
}
this.ExpectedCount = interpolationParameter.ExpectedCount;
if (interpolationParameter.FilterQueryParameter != null)
{
this.FilterQueryParameter = new QueryParameter(interpolationParameter.FilterQueryParameter);
}
this.MaxPointCountForInterpolation = interpolationParameter.MaxPointCountForInterpolation;
this.MaxPointCountInNode = interpolationParameter.MaxPointCountInNode;
this.OutputDatasetName = interpolationParameter.OutputDatasetName;
this.OutputDatasourceName = interpolationParameter.OutputDatasourceName;
this.PixelFormat = interpolationParameter.PixelFormat;
this.Resolution = interpolationParameter.Resolution;
this.SearchMode = interpolationParameter.SearchMode;
this.SearchRadius = interpolationParameter.SearchRadius;
this.ZValueFieldName = interpolationParameter.ZValueFieldName;
this.ZValueScale = interpolationParameter.ZValueScale;
}
public ImageProcess(ImageIO sourceImage,
int targetWidth, int targetHeight,
Interpolation interpolation, double bicubicFactor = -0.5)
{
_imageParameter = new ImageParameter(sourceImage, null, sourceImage.Path, null);
sourceImage.LockBits();
_processOption = new ProcessOption(Transform.None, interpolation);
_distortionParameter = null;
_warpParameter = null;
_faceTransformation = null;
_interpolationParameter = new InterpolationParameter(targetWidth, targetHeight, bicubicFactor);
_processResult = new ProcessResult(this.InterpolationFunction(), null, null);
sourceImage.UnlockBits();
}
public ImageProcess(ImageIO sourceImage, ImageIO faceImage,
int targetWidth, int targetHeight,
Interpolation interpolation, double bicubicFactor = -0.5)
{
_imageParameter = new ImageParameter(sourceImage, faceImage, sourceImage.Path, faceImage.Path);
sourceImage.LockBits();
faceImage.LockBits();
_processOption = new ProcessOption(Transform.TPS, interpolation);
_distortionParameter = null;
_warpParameter = null;
_faceTransformation = new FaceTransformation(this.ImageParameter.SourcePath, this.ImageParameter.FacePath);
_interpolationParameter = new InterpolationParameter(targetWidth, targetHeight, bicubicFactor);
_processResult = new ProcessResult(this.InterpolationFunction(), this.FaceTransformation.Source_marked, this.FaceTransformation.Face_marked);
sourceImage.UnlockBits();
faceImage.UnlockBits();
}
public ImageProcess(ImageIO sourceImage,
double warpFactor, int warpCenter_x, int warpCenter_y,
int targetWidth, int targetHeight,
Interpolation interpolation, double bicubicFactor = -0.5)
{
_stretch = false;
_imageParameter = new ImageParameter(sourceImage, null, sourceImage.Path, null);
sourceImage.LockBits();
_processOption = new ProcessOption(Transform.Warp, interpolation);
_distortionParameter = null;
_warpParameter = new WarpParameter(sourceImage.Width * sourceImage.Height, warpFactor, warpCenter_x, warpCenter_y);
_faceTransformation = null;
_interpolationParameter = new InterpolationParameter(targetWidth, targetHeight, bicubicFactor);
_processResult = new ProcessResult(this.InterpolationFunction(), null, null);
sourceImage.UnlockBits();
}
public override void Deserialize(MoDeserializer archive)
{
var first = new InterpolationParameter();
var second = new InterpolationParameter();
first.X = archive.ReadByte();
second.X = archive.ReadByte();
first.Y = archive.ReadByte();
second.Y = archive.ReadByte();
X.First = first;
X.Second = second;
first.X = archive.ReadByte();
second.X = archive.ReadByte();
first.Y = archive.ReadByte();
second.Y = archive.ReadByte();
Y.First = first;
Y.Second = second;
first.X = archive.ReadByte();
second.X = archive.ReadByte();
first.Y = archive.ReadByte();
second.Y = archive.ReadByte();
Z.First = first;
Z.Second = second;
first.X = archive.ReadByte();
second.X = archive.ReadByte();
first.Y = archive.ReadByte();
second.Y = archive.ReadByte();
R.First = first;
R.Second = second;
first.X = archive.ReadByte();
second.X = archive.ReadByte();
first.Y = archive.ReadByte();
second.Y = archive.ReadByte();
D.First = first;
D.Second = second;
first.X = archive.ReadByte();
second.X = archive.ReadByte();
first.Y = archive.ReadByte();
second.Y = archive.ReadByte();
V.First = first;
V.Second = second;
}
public override void Deserialize(MoDeserializer archive)
{
X = new Interpolation();
Y = new Interpolation();
Z = new Interpolation();
R = new Interpolation();
var x = new InterpolationParameter();
var y = new InterpolationParameter();
var z1 = new InterpolationParameter();
var r1 = new InterpolationParameter();
var z2 = new InterpolationParameter();
var r2 = new InterpolationParameter();
x.X = archive.ReadByte();
y.X = archive.ReadByte();
archive.ReadByte();
archive.ReadByte();
x.Y = archive.ReadByte();
y.Y = archive.ReadByte();
X.First = x;
Y.First = y;
z1.Y = archive.ReadByte();
r1.Y = archive.ReadByte();
x.X = archive.ReadByte();
y.X = archive.ReadByte();
z2.X = archive.ReadByte();
r2.X = archive.ReadByte();
x.Y = archive.ReadByte();
y.Y = archive.ReadByte();
z2.Y = archive.ReadByte();
r2.Y = archive.ReadByte();
archive.ReadByte();
z1.X = archive.ReadByte();
r1.X = archive.ReadByte();
X.Second = x;
Y.Second = y;
Z.First = z1;
Z.Second = z2;
R.First = r1;
R.Second = r2;
for (int i = 0; i < 64 - 19; i++)
{
archive.ReadByte();
}
}
/// <summary>
/// <para>用于对离散的点数据进行插值得到栅格数据集。插值分析可以将有限的采样点数据，通过插值对采样点周围的数值情况进行预测，
/// 从而掌握研究区域内数据的总体分布状况，而使采样的离散点不仅仅反映其所在位置的数值情况，而且可以反映区域的数值分布。</para>
/// </summary>
/// <param name="pointDataset">进行插值分析的点数据集名称，如SamplesP@Interpolation。</param>
/// <param name="parameter">插值参数对象。</param>
/// <returns>返回插值分析得到的栅格数据集。</returns>
/// <remarks>
/// <para>插值分析支持的算法类型：点密度、径向基函数、距离反比权值、普通克吕金、简单克吕金、泛克吕金共6种插值法。</para>
/// <para>(1)点密度（Density）插值法。插值分析时只需要将parameter参数定义为<see cref="InterpolationDensityParameter"/>类型，即可进行点密度插值法。</para>
/// <para>(2)径向基函数（Radial Basis Function）插值法。该方法假设变化是平滑的，它有两个特点：表面必须精确通过数据点；表面必须有最小曲率。该插值在创建有视觉要求的曲线和等高线方面有优势。插值分析时只需要将parameter参数定义为<see cref="InterpolationRBFParameter"/>类型，即可进行径向基函数插值法。</para>
/// <para>(3)距离反比权值（Inverse Distance Weighted）插值法。该方法通过计算附近区域离散点群的平均值来估算单元格的值，生成格网数据集。
/// 这是一种简单有效的数据内插方法，运算速度相对较快。距离离散中心越近的点，其估算值越受影响。插值分析时只需要将parameter参数定义为<see cref="InterpolationIDWParameter"/>类型，即可进行距离反比权值插值法。</para>
/// <para>(4)克吕金插值法。克吕金插值法又分成3种类型（参考<see cref="KrigingAlgorithmType"/>）：普通克吕金插值法；简单克吕金插值法；泛克吕金插值法。插值分析时需要将parameter参数定义为<see cref="InterpolationKrigingParameter"/>类型，并且在InterpolationKrigingParameter.Type参数中设置克吕金插值法的类型，即可进行克吕金插值法。</para>
/// </remarks>
/// <exception cref="ArgumentNullException">参数 parameter 为空时抛出异常。</exception>
/// <exception cref="SuperMap.Connector.Utility.ServiceException">服务端处理错误时抛出异常。</exception>
/// <example>
/// 以下示范代码演示如何进行插值分析操作。
/// <code>
/// using System;
/// using System.Collections.Generic;
/// using System.Text;
/// using SuperMap.Connector;
/// using SuperMap.Connector.Utility;
///
/// class Program
/// {
/// static void Main(string[] args)
/// {
/// //根据服务组件地址初始化一个SpatialAnalyst对象
/// SpatialAnalyst spatialAnalyst = new SpatialAnalyst("http://*****:*****@Interpolation",param);
/// Console.WriteLine("返回的数据集名称是：{0}", actualResult.Dataset);
/// Console.ReadLine();
/// }
/// }
/// </code>
/// </example>
public DatasetSpatialAnalystResult Interpolate(string pointDataset, InterpolationParameter parameter)
{
if (parameter == null)
{
throw new ArgumentNullException("parameter", Resources.ArgumentIsNotNull);
}
if (pointDataset == null)
{
throw new ArgumentNullException("pointDataset", Resources.ArgumentIsNotNull);
}
return _spatialAnalystProvier.Interpolate(pointDataset, parameter);
}
public void CalculateInterpolatedValueTest(InterpolationParameter first, InterpolationParameter second, float t, float y)
{
var interpolation = new Interpolation(first, second);
Assert.AreEqual(y, interpolation.GetInterpolatedValue(t), 1e-5);
}
public DatasetSpatialAnalystResult Interpolate(string pointDataset, InterpolationParameter parameter)
{
string baseUrl = "";
string resourceType = "";
System.Type parameterType = parameter.GetType();
switch (parameterType.Name)
{
case "InterpolationDensityParameter":
resourceType = "density";
break;
case "InterpolationIDWParameter":
resourceType = "idw";
break;
case "InterpolationRBFParameter":
resourceType = "rbf";
break;
case "InterpolationKrigingParameter":
resourceType = "kriging";
break;
default:
break;
}
baseUrl = string.Format("{0}/spatialanalyst/datasets/{1}/interpolation/{2}.json?returnContent=true", this._serviceUrl, HttpUtility.HtmlEncode(pointDataset), resourceType);
string json = string.Empty;
json = JsonConvert.SerializeObject(parameter);
string interpolateResult = SynchHttpRequest.GetRequestString(baseUrl, HttpRequestMethod.POST, json);
return JsonConvert.DeserializeObject<DatasetSpatialAnalystResult>(interpolateResult);
}
