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Changeset 12792

Timestamp:

07/21/15 16:00:20 (9 years ago)

Author:

gkronber

Message:

#2435: updated some of the alglib calls (we should only use the external API whenever possible)

Location:

trunk/sources

Files:

-                      r12790
+                      r12792
       alglib.densesolverreport denseSolveRep;
       var res = alglib.trfac.spdmatrixcholesky(ref l, n, false);
+      var res = alglib.spdmatrixcholesky(ref l, n, false);
       if (!res) throw new ArgumentException("Matrix is not positive semidefinite");
 …
       // for stddev
       alglib.ablas.rmatrixlefttrsm(n, newN, l, 0, 0, false, false, 0, sWKs, 0, 0);
+      alglib.rmatrixlefttrsm(n, newN, l, 0, 0, false, false, 0, ref sWKs, 0, 0);
       for (int i = 0; i < newN; i++) {

-                      r12509
+                      r12792
     private LinearRegression(LinearRegression original, Cloner cloner)
       : base(original, cloner) {
+    }
     public LinearRegression()
 …
         throw new NotSupportedException("Linear regression does not support NaN or infinity values in the input dataset.");
       alglib.linearmodel lm = new alglib.linearmodel();
       alglib.lrreport ar = new alglib.lrreport();
+      alglib.linearmodel lm;
+      alglib.lrreport ar;
       int nRows = inputMatrix.GetLength(0);
       int nFeatures = inputMatrix.GetLength(1) - 1;
       double[] coefficients = new double[nFeatures + 1]; // last coefficient is for the constant
+      double[] coefficients;
       int retVal = 1;

-                      r12622
+                      r12792
         throw new NotSupportedException("Multinomial logit classification does not support NaN or infinity values in the input dataset.");
       alglib.logitmodel lm = new alglib.logitmodel();
       alglib.mnlreport rep = new alglib.mnlreport();
+      alglib.logitmodel lm;
+      alglib.mnlreport rep;
       int nRows = inputMatrix.GetLength(0);
       int nFeatures = inputMatrix.GetLength(1) - 1;

-                      r12504
+                      r12792
       alglib.linearmodel lm = new alglib.linearmodel();
       alglib.lrreport ar = new alglib.lrreport();
+      alglib.linearmodel lm;
+      alglib.lrreport ar;
       int nRows = inputMatrix.GetLength(0);
       int nFeatures = inputMatrix.GetLength(1) - 1;

Property svn:ignore

r12012	r12792
276	276	}
277	277	// wilcoxon signed rank test is used because the impact values of two variables in a single run are not independent
278		alglib.w~~sr.wilcoxonsignedranktest(z, z.Length, 0, ref bothTails, ref leftTail, ref~~ rightTail);
	278	alglib.wilcoxonsignedranktest(z, z.Length, 0, out bothTails, out leftTail, out rightTail);
279	279	matrix[row, numberOfRuns + 3] = Math.Round(bothTails, 4);
280	280	}

r12012	r12792
31	31	}
32	32
33		double[] correlations ~~= new double[values.Length]~~;
34		alglib.corr~~.corrr1dcircular(values, values.Length, values, values.Length, ref~~ correlations);
	33	double[] correlations;
	34	alglib.corrr1dcircular(values, values.Length, values, values.Length, out correlations);
35	35	return correlations;
36	36	}

r12012	r12792
41	41	var original = originalValues.ToArray();
42	42	var estimated = estimatedValues.ToArray();
43		rs = alglib.~~basestat.~~spearmancorr2(original, estimated, original.Length);
	43	rs = alglib.spearmancorr2(original, estimated, original.Length);
44	44	errorState = OnlineCalculatorError.None;
45	45	}

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