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diff --git a/chart2/source/inc/RegressionCalculationHelper.hxx b/chart2/source/inc/RegressionCalculationHelper.hxx
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+++ b/chart2/source/inc/RegressionCalculationHelper.hxx
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+/* -*- Mode: C++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
+/*
+ * This file is part of the LibreOffice project.
+ *
+ * This Source Code Form is subject to the terms of the Mozilla Public
+ * License, v. 2.0. If a copy of the MPL was not distributed with this
+ * file, You can obtain one at http://mozilla.org/MPL/2.0/.
+ *
+ * This file incorporates work covered by the following license notice:
+ *
+ *   Licensed to the Apache Software Foundation (ASF) under one or more
+ *   contributor license agreements. See the NOTICE file distributed
+ *   with this work for additional information regarding copyright
+ *   ownership. The ASF licenses this file to you under the Apache
+ *   License, Version 2.0 (the "License"); you may not use this file
+ *   except in compliance with the License. You may obtain a copy of
+ *   the License at http://www.apache.org/licenses/LICENSE-2.0 .
+ */
+#pragma once
+
+#include <com/sun/star/uno/Sequence.hxx>
+
+#include <cmath>
+#include <utility>
+#include <vector>
+
+namespace chart::RegressionCalculationHelper
+{
+
+typedef std::pair< std::vector< double >, std::vector< double > > tDoubleVectorPair;
+
+/** takes the given x- and y-values and copies them into the resulting pair,
+    which contains x-values in the first element and the y-values in the second
+    one.  All tuples for which aPred is false are not copied.
+
+    <p>The function below provide a set of useful predicates that can be
+    used to pass as parameter aPred.</p>
+ */
+template< class Pred >
+tDoubleVectorPair
+    cleanup( const css::uno::Sequence< double > & rXValues,
+             const css::uno::Sequence< double > & rYValues,
+             Pred aPred )
+{
+    tDoubleVectorPair aResult;
+    sal_Int32 nSize = std::min( rXValues.getLength(), rYValues.getLength());
+    for( sal_Int32 i=0; i<nSize; ++i )
+    {
+        if( aPred( rXValues[i], rYValues[i] ))
+        {
+            aResult.first.push_back( rXValues[i] );
+            aResult.second.push_back( rYValues[i] );
+        }
+    }
+
+    return aResult;
+}
+
+class isValid
+{
+public:
+    bool operator()( double x, double y )
+    { return ! ( std::isnan( x ) ||
+                 std::isnan( y ) ||
+                 std::isinf( x ) ||
+                 std::isinf( y ) );
+    }
+};
+
+class isValidAndXPositive
+{
+public:
+    bool operator()( double x, double y )
+    { return ! ( std::isnan( x ) ||
+                 std::isnan( y ) ||
+                 std::isinf( x ) ||
+                 std::isinf( y ) ||
+                 x <= 0.0 );
+    }
+};
+
+class isValidAndYPositive
+{
+public:
+    bool operator()( double x, double y )
+    { return ! ( std::isnan( x ) ||
+                 std::isnan( y ) ||
+                 std::isinf( x ) ||
+                 std::isinf( y ) ||
+                 y <= 0.0 );
+    }
+};
+
+class isValidAndYNegative
+{
+public:
+    bool operator()( double x, double y )
+    { return ! ( std::isnan( x ) ||
+                 std::isnan( y ) ||
+                 std::isinf( x ) ||
+                 std::isinf( y ) ||
+                 y >= 0.0 );
+    }
+};
+
+class isValidAndBothPositive
+{
+public:
+    bool operator()( double x, double y )
+    { return ! ( std::isnan( x ) ||
+                 std::isnan( y ) ||
+                 std::isinf( x ) ||
+                 std::isinf( y ) ||
+                 x <= 0.0 ||
+                 y <= 0.0 );
+    }
+};
+
+class isValidAndXPositiveAndYNegative
+{
+public:
+    bool operator()( double x, double y )
+    { return ! ( std::isnan( x ) ||
+                 std::isnan( y ) ||
+                 std::isinf( x ) ||
+                 std::isinf( y ) ||
+                 x <= 0.0 ||
+                 y >= 0.0 );
+    }
+};
+
+} //  namespace chart::RegressionCalculationHelper
+
+/* vim:set shiftwidth=4 softtabstop=4 expandtab: */