--- a/flys-artifacts/src/main/java/de/intevation/flys/artifacts/model/fixings/FixCalculation.java	Sun Jul 22 09:49:56 2012 +0000
+++ b/flys-artifacts/src/main/java/de/intevation/flys/artifacts/model/fixings/FixCalculation.java	Sun Jul 22 10:38:30 2012 +0000
@@ -1,7 +1,11 @@
 package de.intevation.flys.artifacts.model.fixings;
 
+import de.intevation.artifacts.common.utils.StringUtils;
+
 import de.intevation.flys.artifacts.access.FixAccess;
 
+import de.intevation.flys.artifacts.math.fitting.Function;
+
 import de.intevation.flys.artifacts.model.Calculation;
 import de.intevation.flys.artifacts.model.FixingsColumn;
 import de.intevation.flys.artifacts.model.FixingsColumnFactory;
@@ -12,6 +16,10 @@
 import de.intevation.flys.artifacts.model.FixingsOverview.IdsFilter;
 
 import de.intevation.flys.artifacts.model.FixingsOverview;
+import de.intevation.flys.artifacts.model.Parameters;
+
+import de.intevation.flys.utils.DoubleUtil;
+import de.intevation.flys.utils.KMIndex;
 
 import java.util.ArrayList;
 import java.util.Date;
@@ -26,6 +34,44 @@
 {
     private static Logger log = Logger.getLogger(FixCalculation.class);
 
+    public static final double EPSILON = 1e-4;
+
+    public static final String [] STANDARD_COLUMNS = {
+        "km", "chi_sqr", "max_q", "std-dev"
+    };
+
+    protected static class FitResult {
+
+        protected Parameters      parameters;
+        protected KMIndex<QWD []> referenced;
+        protected KMIndex<QW []>  outliers;
+
+        public FitResult() {
+        }
+
+        public FitResult(
+            Parameters      parameters,
+            KMIndex<QWD []> referenced,
+            KMIndex<QW []>  outliers
+        ) {
+            this.parameters = parameters;
+            this.referenced = referenced;
+            this.outliers   = outliers;
+        }
+
+        public Parameters getParameters() {
+            return parameters;
+        }
+
+        public KMIndex<QWD []> getReferenced() {
+            return referenced;
+        }
+
+        public KMIndex<QW []> getOutliers() {
+            return outliers;
+        }
+    } // class FitResult
+
     /** Helper class to bundle the meta information of a column
      *  and the real data.
      */
@@ -208,5 +254,124 @@
 
         return columns;
     }
+
+    protected FitResult doFitting(FixingsOverview overview, Function func) {
+
+        boolean debug = log.isDebugEnabled();
+
+        final List<Column> eventColumns = getEventColumns(overview);
+
+        if (eventColumns.size() < 2) {
+            addProblem("fix.too.less.data.columns");
+            return null;
+        }
+
+        final double  [] qs = new double[eventColumns.size()];
+        final double  [] ws = new double[qs.length];
+        final boolean [] interpolated = new boolean[ws.length];
+
+        Fitting.QWDFactory qwdFactory = new Fitting.QWDFactory() {
+            @Override
+            public QWD create(double q, double w) {
+                // Check all the event columns for close match
+                // and take the description and the date from meta.
+                for (int i = 0; i < qs.length; ++i) {
+                    if (Math.abs(qs[i]-q) < EPSILON
+                    &&  Math.abs(ws[i]-w) < EPSILON) {
+                        Column column = eventColumns.get(i);
+                        return new QWD(
+                            qs[i], ws[i],
+                            column.getDescription(),
+                            column.getDate(),
+                            interpolated[i],
+                            0d);
+                    }
+                }
+                log.warn("cannot find column for (" + q + ", " + w + ")");
+                return new QWD(q, w);
+            }
+        };
+
+        Fitting fitting = new Fitting(func, qwdFactory, preprocessing);
+
+        String [] parameterNames = func.getParameterNames();
+
+        Parameters results =
+            new Parameters(
+                StringUtils.join(STANDARD_COLUMNS, parameterNames));
+
+        boolean invalid = false;
+
+        double [] kms = DoubleUtil.explode(from, to, step / 1000.0);
+
+        if (debug) {
+            log.debug("number of kms: " + kms.length);
+        }
+
+        KMIndex<QW []>  outliers   = new KMIndex<QW []>();
+        KMIndex<QWD []> referenced = new KMIndex<QWD []>(kms.length);
+
+        int kmIndex             = results.columnIndex("km");
+        int chiSqrIndex         = results.columnIndex("chi_sqr");
+        int maxQIndex           = results.columnIndex("max_q");
+        int stdDevIndex         = results.columnIndex("std-dev");
+        int [] parameterIndices = results.columnIndices(parameterNames);
+
+        int numFailed = 0;
+
+        for (int i = 0; i < kms.length; ++i) {
+            double km = kms[i];
+
+            // Fill Qs and Ws from event columns.
+            for (int j = 0; j < ws.length; ++j) {
+                interpolated[j] = !eventColumns.get(j).getQW(km, qs, ws, j);
+            }
+
+            fitting.reset();
+
+            if (!fitting.fit(qs, ws)) {
+                ++numFailed;
+                addProblem(km, "fix.fitting.failed");
+                continue;
+            }
+
+            referenced.add(km, fitting.referencedToArray());
+
+            if (fitting.hasOutliers()) {
+                outliers.add(km, fitting.outliersToArray());
+            }
+
+            int row = results.newRow();
+            double [] values = fitting.getParameters();
+
+            results.set(row, kmIndex, km);
+            results.set(row, chiSqrIndex, fitting.getChiSquare());
+            results.set(row, stdDevIndex, fitting.getStandardDeviation());
+            results.set(row, maxQIndex,   fitting.getMaxQ());
+            invalid |= results.set(row, parameterIndices, values);
+
+            if (debug) {
+                log.debug("km: "+km+" " + toString(parameterNames, values));
+            }
+        }
+
+        if (debug) {
+            log.debug("success: " + (kms.length - numFailed));
+            log.debug("failed: " + numFailed);
+        }
+
+        if (invalid) {
+            addProblem("fix.invalid.values");
+            results.removeNaNs();
+        }
+
+        outliers.sort();
+        referenced.sort();
+
+        return new FitResult(
+            results,
+            referenced,
+            outliers);
+    }
 }
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