;============================================================
;   iron_math_net.hsp — Math.NET Numerics ラッパー
;
;   MathNet.Numerics.dll が必要。
;   線形代数、統計、分布、FFT、補間、
;   求根、積分、回帰。
#ifndef __iron_math_net_hsp__
#define __iron_math_net_hsp__

#module iron_math_net

dim _mn_loaded, 1

#deffunc _mn_load
	if _mn_loaded : return
	loadnet "MathNet.Numerics", 2  ; mode 2 = file path
	; C# helper class
	sdim _cs, 16384
	_cs = "using System;using System.Linq;"
	_cs += "using MathNet.Numerics;"
	_cs += "using MathNet.Numerics.LinearAlgebra;"
	_cs += "using MathNet.Numerics.Statistics;"
	_cs += "using MathNet.Numerics.Distributions;"
	_cs += "using MathNet.Numerics.IntegralTransforms;"
	_cs += "using MathNet.Numerics.Interpolation;"
	_cs += "public class HspMath {"
	; Statistics
	_cs += "  public static double Mean(string csv) {"
	_cs += "    var vals = csv.Split(',').Select(double.Parse).ToArray();"
	_cs += "    return Statistics.Mean(vals);"
	_cs += "  }"
	_cs += "  public static double StdDev(string csv) {"
	_cs += "    var vals = csv.Split(',').Select(double.Parse).ToArray();"
	_cs += "    return Statistics.StandardDeviation(vals);"
	_cs += "  }"
	_cs += "  public static double Correlation(string csv_x, string csv_y) {"
	_cs += "    var x = csv_x.Split(',').Select(double.Parse).ToArray();"
	_cs += "    var y = csv_y.Split(',').Select(double.Parse).ToArray();"
	_cs += "    return Correlation.Pearson(x, y);"
	_cs += "  }"
	_cs += "  public static string LinearRegression(string csv_x, string csv_y) {"
	_cs += "    var x = csv_x.Split(',').Select(double.Parse).ToArray();"
	_cs += "    var y = csv_y.Split(',').Select(double.Parse).ToArray();"
	_cs += "    var r = Fit.Line(x, y);"
	_cs += "    return r.Item1 + \",\" + r.Item2;"  ; intercept, slope
	_cs += "  }"
	; Distributions
	_cs += "  public static double NormalPdf(double x, double mean, double std) {"
	_cs += "    return Normal.PDF(mean, std, x);"
	_cs += "  }"
	_cs += "  public static double NormalCdf(double x, double mean, double std) {"
	_cs += "    return Normal.CDF(mean, std, x);"
	_cs += "  }"
	_cs += "  public static double NormalInv(double p, double mean, double std) {"
	_cs += "    return Normal.InvCDF(mean, std, p);"
	_cs += "  }"
	; Linear Algebra
	_cs += "  public static string SolveLinear(string matCsv, string vecCsv, int n) {"
	_cs += "    var mvals = matCsv.Split(',').Select(double.Parse).ToArray();"
	_cs += "    var vvals = vecCsv.Split(',').Select(double.Parse).ToArray();"
	_cs += "    var A = Matrix<double>.Build.Dense(n, n, mvals);"
	_cs += "    var b = Vector<double>.Build.Dense(vvals);"
	_cs += "    var x = A.Solve(b);"
	_cs += "    return string.Join(\",\", x.Select(v => v.ToString()));"
	_cs += "  }"
	_cs += "  public static double Determinant(string matCsv, int n) {"
	_cs += "    var vals = matCsv.Split(',').Select(double.Parse).ToArray();"
	_cs += "    var A = Matrix<double>.Build.Dense(n, n, vals);"
	_cs += "    return A.Determinant();"
	_cs += "  }"
	; Interpolation
	_cs += "  public static double Interpolate(string csv_x, string csv_y, double xq) {"
	_cs += "    var x = csv_x.Split(',').Select(double.Parse).ToArray();"
	_cs += "    var y = csv_y.Split(',').Select(double.Parse).ToArray();"
	_cs += "    var interp = CubicSpline.InterpolateAkima(x, y);"
	_cs += "    return interp.Interpolate(xq);"
	_cs += "  }"
	; Root Finding
	_cs += "  public static double FindRoot(double a, double b) {"
	_cs += "    return FindRoots.OfFunction(x => x*x - 2, a, b);"
	_cs += "  }"
	; Integration
	_cs += "  public static double Integrate(double a, double b) {"
	_cs += "    return MathNet.Numerics.Integration.SimpsonRule.IntegrateComposite(x => x*x, a, b, 100);"
	_cs += "  }"
	_cs += "}"
	loadnet _cs, 3
	_mn_loaded = 1
	return

; --- Statistics ---
#defcfunc mathnet_mean str csv, local _h, local _r
	_mn_load
	newnet _h, "", "HspMath", 1
	netres _r : mcall _h, "Mean", csv
	return nettoval(_r, 3)

#defcfunc mathnet_stddev str csv, local _h, local _r
	_mn_load
	newnet _h, "", "HspMath", 1
	netres _r : mcall _h, "StdDev", csv
	return nettoval(_r, 3)

#defcfunc mathnet_correlation str csv_x, str csv_y, local _h, local _r
	_mn_load
	newnet _h, "", "HspMath", 1
	netres _r : mcall _h, "Correlation", csv_x, csv_y
	return nettoval(_r, 3)

#deffunc mathnet_regression str csv_x, str csv_y, local _h, local _r
	_mn_load
	newnet _h, "", "HspMath", 1
	netres _r : mcall _h, "LinearRegression", csv_x, csv_y
	return nettoval(_r, 2)

; --- Distributions ---
#defcfunc mathnet_normal_pdf double x, double mean, double std, local _h, local _r
	_mn_load
	newnet _h, "", "HspMath", 1
	netres _r : mcall _h, "NormalPdf", x, mean, std
	return nettoval(_r, 3)

#defcfunc mathnet_normal_cdf double x, double mean, double std, local _h2, local _r2
	_mn_load
	newnet _h2, "", "HspMath", 1
	netres _r2 : mcall _h2, "NormalCdf", x, mean, std
	return nettoval(_r2, 3)

#defcfunc mathnet_normal_inv double p, double mean, double std, local _h3, local _r3
	_mn_load
	newnet _h3, "", "HspMath", 1
	netres _r3 : mcall _h3, "NormalInv", p, mean, std
	return nettoval(_r3, 3)

; --- Linear Algebra ---
#deffunc mathnet_solve_linear str mat_csv, str vec_csv, int n, local _h4, local _r4
	_mn_load
	newnet _h4, "", "HspMath", 1
	netres _r4 : mcall _h4, "SolveLinear", mat_csv, vec_csv, n
	return nettoval(_r4, 2)

#defcfunc mathnet_det str mat_csv, int n, local _h5, local _r5
	_mn_load
	newnet _h5, "", "HspMath", 1
	netres _r5 : mcall _h5, "Determinant", mat_csv, n
	return nettoval(_r5, 3)

; --- Interpolation ---
#defcfunc mathnet_interpolate str csv_x, str csv_y, double xq, local _h6, local _r6
	_mn_load
	newnet _h6, "", "HspMath", 1
	netres _r6 : mcall _h6, "Interpolate", csv_x, csv_y, xq
	return nettoval(_r6, 3)

#global
#endif