X-Git-Url: https://gerrit.simantics.org/r/gitweb?a=blobdiff_plain;f=bundles%2Forg.simantics.spreadsheet.graph%2Fsrc%2Forg%2Fsimantics%2Fspreadsheet%2Fgraph%2Fformula%2FLinestFormulaFunction.java;fp=bundles%2Forg.simantics.spreadsheet.graph%2Fsrc%2Forg%2Fsimantics%2Fspreadsheet%2Fgraph%2Fformula%2FLinestFormulaFunction.java;h=dd037e9eaae010927dee651aadca7a5474d19014;hb=0ae2b770234dfc3cbb18bd38f324125cf0faca07;hp=dc15b99b1dcf03634dbd2f37b1ca6fecf5c049fb;hpb=24e2b34260f219f0d1644ca7a138894980e25b14;p=simantics%2Fplatform.git

diff --git a/bundles/org.simantics.spreadsheet.graph/src/org/simantics/spreadsheet/graph/formula/LinestFormulaFunction.java b/bundles/org.simantics.spreadsheet.graph/src/org/simantics/spreadsheet/graph/formula/LinestFormulaFunction.java
index dc15b99b1..dd037e9ea 100644
--- a/bundles/org.simantics.spreadsheet.graph/src/org/simantics/spreadsheet/graph/formula/LinestFormulaFunction.java
+++ b/bundles/org.simantics.spreadsheet.graph/src/org/simantics/spreadsheet/graph/formula/LinestFormulaFunction.java
@@ -1,77 +1,77 @@
-package org.simantics.spreadsheet.graph.formula;
-
-import org.apache.commons.math3.stat.regression.OLSMultipleLinearRegression;
-import org.simantics.spreadsheet.graph.CellFormulaFunction;
-import org.simantics.spreadsheet.graph.CellValueVisitor;
-import org.simantics.spreadsheet.graph.SpreadsheetGraphUtils;
-import org.simantics.spreadsheet.graph.SpreadsheetMatrix;
-import org.simantics.spreadsheet.graph.parser.ast.AstArgList;
-
-public class LinestFormulaFunction implements CellFormulaFunction<SpreadsheetMatrix> {
-
-    @Override
-    public SpreadsheetMatrix evaluate(CellValueVisitor visitor, AstArgList args) {
-        if (args.values.size() != 4)
-            throw new IllegalStateException();
-
-        Object ys = args.values.get(0).accept(visitor);
-        Object xs = args.values.get(1).accept(visitor);
-
-        if (xs instanceof SpreadsheetMatrix) {
-
-            OLSMultipleLinearRegression reg = new OLSMultipleLinearRegression();
-
-            SpreadsheetMatrix xsm = (SpreadsheetMatrix) xs;
-            SpreadsheetMatrix ysm = (SpreadsheetMatrix) ys;
-
-            if (xsm.getWidth() > 1) {
-
-                double y[] = new double[ysm.values.length];
-                double x[][] = new double[ysm.values.length][xsm.getWidth()];
-
-                for (int i = 0; i < ysm.values.length; i++) {
-                    y[i] = SpreadsheetGraphUtils.asNumber(ysm.values[i]);
-                    for (int j = 0; j < xsm.getWidth(); j++) {
-                        x[i][j] = SpreadsheetGraphUtils.asNumber(xsm.get(i, j));
-                    }
-                }
-
-                reg.newSampleData(y, x);
-
-                int width = xsm.getWidth() + 1;
-                SpreadsheetMatrix result = new SpreadsheetMatrix(width, 5);
-                double[] pars = reg.estimateRegressionParameters();
-                for (int i = 0; i < width; i++)
-                    result.set(0, width - i - 1, pars[i]);
-                double[] errs = reg.estimateRegressionParametersStandardErrors();
-                for (int i = 0; i < width; i++)
-                    result.set(1, width - i - 1, errs[i]);
-
-                double sstotal = reg.calculateTotalSumOfSquares();
-                double ssresid = reg.calculateResidualSumOfSquares();
-                double ssreg = sstotal - ssresid;
-                double F = 0;
-                double r2 = ssreg / sstotal;
-                double sey = reg.estimateRegressionStandardError();
-                double df = width;
-
-                result.set(2, 0, r2);
-                result.set(2, 1, sey);
-                result.set(3, 0, F);
-                result.set(3, 1, df);
-                result.set(4, 0, ssreg);
-                result.set(4, 1, ssresid);
-                result.set(2,2, FormulaError2.NA.getString());
-                result.set(3,2, FormulaError2.NA.getString());
-                result.set(4,2, FormulaError2.NA.getString());
-                
-                return result;
-
-            }
-
-        }
-
-        return null;
-    }
-
-}
+package org.simantics.spreadsheet.graph.formula;
+
+import org.apache.commons.math3.stat.regression.OLSMultipleLinearRegression;
+import org.simantics.spreadsheet.graph.CellFormulaFunction;
+import org.simantics.spreadsheet.graph.CellValueVisitor;
+import org.simantics.spreadsheet.graph.SpreadsheetGraphUtils;
+import org.simantics.spreadsheet.graph.SpreadsheetMatrix;
+import org.simantics.spreadsheet.graph.parser.ast.AstArgList;
+
+public class LinestFormulaFunction implements CellFormulaFunction<SpreadsheetMatrix> {
+
+    @Override
+    public SpreadsheetMatrix evaluate(CellValueVisitor visitor, AstArgList args) {
+        if (args.values.size() != 4)
+            throw new IllegalStateException();
+
+        Object ys = args.values.get(0).accept(visitor);
+        Object xs = args.values.get(1).accept(visitor);
+
+        if (xs instanceof SpreadsheetMatrix) {
+
+            OLSMultipleLinearRegression reg = new OLSMultipleLinearRegression();
+
+            SpreadsheetMatrix xsm = (SpreadsheetMatrix) xs;
+            SpreadsheetMatrix ysm = (SpreadsheetMatrix) ys;
+
+            if (xsm.getWidth() > 1) {
+
+                double y[] = new double[ysm.values.length];
+                double x[][] = new double[ysm.values.length][xsm.getWidth()];
+
+                for (int i = 0; i < ysm.values.length; i++) {
+                    y[i] = SpreadsheetGraphUtils.asNumber(ysm.values[i]);
+                    for (int j = 0; j < xsm.getWidth(); j++) {
+                        x[i][j] = SpreadsheetGraphUtils.asNumber(xsm.get(i, j));
+                    }
+                }
+
+                reg.newSampleData(y, x);
+
+                int width = xsm.getWidth() + 1;
+                SpreadsheetMatrix result = new SpreadsheetMatrix(width, 5);
+                double[] pars = reg.estimateRegressionParameters();
+                for (int i = 0; i < width; i++)
+                    result.set(0, width - i - 1, pars[i]);
+                double[] errs = reg.estimateRegressionParametersStandardErrors();
+                for (int i = 0; i < width; i++)
+                    result.set(1, width - i - 1, errs[i]);
+
+                double sstotal = reg.calculateTotalSumOfSquares();
+                double ssresid = reg.calculateResidualSumOfSquares();
+                double ssreg = sstotal - ssresid;
+                double F = 0;
+                double r2 = ssreg / sstotal;
+                double sey = reg.estimateRegressionStandardError();
+                double df = width;
+
+                result.set(2, 0, r2);
+                result.set(2, 1, sey);
+                result.set(3, 0, F);
+                result.set(3, 1, df);
+                result.set(4, 0, ssreg);
+                result.set(4, 1, ssresid);
+                result.set(2,2, FormulaError2.NA.getString());
+                result.set(3,2, FormulaError2.NA.getString());
+                result.set(4,2, FormulaError2.NA.getString());
+                
+                return result;
+
+            }
+
+        }
+
+        return null;
+    }
+
+}