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	diff --git a/inc/Lau1DCubicSpline.hh b/inc/Lau1DCubicSpline.hh
	index 4f8b1c4..0cc2f6e 100644
	--- a/inc/Lau1DCubicSpline.hh
	+++ b/inc/Lau1DCubicSpline.hh
	@@ -1,260 +1,261 @@

	/*
	Copyright 2015 University of Warwick

	Licensed 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

	Unless required by applicable law or agreed to in writing, software
	distributed under the License is distributed on an "AS IS" BASIS,
	WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	See the License for the specific language governing permissions and
	limitations under the License.
	*/

	/*
	Laura++ package authors:
	John Back
	Paul Harrison
	Thomas Latham
	*/

	/*! \file Lau1DCubicSpline.hh
	\brief File containing declaration of Lau1DCubicSpline class.
	*/

	/*! \class Lau1DCubicSpline
	\brief Class for defining a 1D cubic spline based on a set of knots.

	Class for defining a 1D cubic spline based on a set of knots.
	Interpolation between the knots is performed either by one of
	two types of cubic spline (standard or Akima) or by linear interpolation.
	The splines are defined by a piecewise cubic function which, between knots i and i+1, has the form

	f_i(x) = (1 - t)y_i + ty_i+1 + t(1 - t)(a(1 - t) + b*t)

	where t = (x - x_i)/(x_i+1 - x_i),
	a = k_i *(x_i+1 - x_i) - (y_i+1 - y_i),
	b = -k_i+1*(x_i+1 - x_i) + (y_i+1 - y_i)

	and k_i is (by construction) the first derivative at knot i.
	f(x) and f'(x) are continuous at the internal knots by construction.

	For the standard splines, f''(x) is required to be continuous
	at all internal knots placing n-2 constraints on the n parameters, k_i.
	The final two constraints are set by the boundary conditions.
	At each boundary, the function may be:

	(i) Clamped : f'(x) = C at the last knot
	(ii) Natural : f''(x) = 0 at the last knot
	(iii) Not a knot : f'''(x) continuous at the second last knot

	The algorithms used in these splines can be found on:
	http://en.wikipedia.org/wiki/Spline_interpolation#Algorithm_to_find_the_interpolating_cubic_spline
	http://en.wikipedia.org/wiki/Tridiagonal_matrix_algorithm

	For the Akima splines, the values of k_i are determined from the slopes of the four nearest segments (a_i-1, a_i, a_i+1 and a_i+2) as

	k_i = ( \| a_i+2 - a_i+1 \| a_i + \| a_i - a_i-1 \| a_i+1 ) / ( \| a_i+2 - a_i+1 \| + \| a_i - a_i-1 \| )

	and as

	k_i = ( a_i + a_i+1 ) / 2

	in the special case a_i-1 == a_i != a_i+1 == a_i+2.

	Boundary conditions are specified by the relations
	a_2 - a_1 = a_1 - a_0 = a_0 - a_-1 and
	a_n-1 - a_n-2 = a_n - a_n-1 = a_n+1 - a_n

	The algorithms used in these splines can be found in:
	J.ACM vol. 17 no. 4 pp 589-602
	*/

	#ifndef LAU_1DCUBICSPLINE
	#define LAU_1DCUBICSPLINE

	#include <vector>
	#include <array>

	#include "Rtypes.h"
	#include "TF1.h"
	#include "TFitResultPtr.h"

	#include "LauPrint.hh"

	class TH1;
	class LauAbsRValue;
	class LauParameter;

	class Lau1DCubicSpline final {

	public:
	//! Define the allowed interpolation types
	enum LauSplineType {
	StandardSpline, /!< standard cubic splines with f''(x) continuous at all internal knots /
	AkimaSpline, /!< Akima cubic splines with f'(x) at each knot defined locally by the positions of only five knots /
	LinearInterpolation /! Linear interpolation between each pair of knots /
	};

	//! Define the allowed boundary condition types
	/*!
	These are only supported by standard splines
	*/
	enum LauSplineBoundaryType {
	Clamped, /!< clamped boundary - f'(x) = C /
	Natural, /!< natural boundary - f''(x) = 0 /
	NotAKnot /!< 'not a knot' boundary - f'''(x) continuous at second last knot /
	};

	//! Constructor
	/*!
	\param [in] xs the x-values of the knots
	\param [in] ys the y-values of the knots
	\param [in] type the type of spline (Standard, Akima, Linear)
	\param [in] leftBound the left-hand boundary condition
	\param [in] rightBound the right-hand boundary condition
	\param [in] dydx0 the gradient at the left-hand boundary of a clamped spline
	\param [in] dydxn the gradient at the right-hand boundary of a clamped spline
	*/
	Lau1DCubicSpline(const std::vector<Double_t>& xs, const std::vector<Double_t>& ys,
	LauSplineType type = Lau1DCubicSpline::StandardSpline,
	LauSplineBoundaryType leftBound = Lau1DCubicSpline::NotAKnot,
	LauSplineBoundaryType rightBound = Lau1DCubicSpline::NotAKnot,
	Double_t dydx0 = 0.0, Double_t dydxn = 0.0);

	//! Evaluate the function at given point
	/*!
	\param [in] x the x-coordinate
	\return the value of the spline at x
	*/
	Double_t evaluate(Double_t x) const;

	//! Update the y-values of the knots
	/*!
	\param [in] ys the y-values of the knots
	*/
	void updateYValues(const std::vector<Double_t>& ys);
	//! Update the y-values of the knots
	/*!
	\param [in] ys the y-values of the knots
	*/
	void updateYValues(const std::vector<LauParameter*>& ys);
	//! Update the y-values of the knots
	/*!
	\param [in] ys the y-values of the knots
	*/
	void updateYValues(const std::vector<LauAbsRValue*>& ys);

	//! Update the type of interpolation to perform
	/*!
	\param [in] type the type of interpolation
	*/
	void updateType(LauSplineType type);

	//! Update the boundary conditions for the spline
	/*!
	\param [in] leftBound the left-hand boundary condition
	\param [in] rightBound the right-hand boundary condition
	\param [in] dydx0 the gradient at the left-hand boundary of a clamped spline
	\param [in] dydxn the gradient at the right-hand boundary of a clamped spline
	*/
	void updateBoundaryConditions(LauSplineBoundaryType leftBound,
	LauSplineBoundaryType rightBound,
	Double_t dydx0 = 0.0,
	Double_t dydxn = 0.0);

	//! Get the number of knots
	std::size_t getnKnots() const {return nKnots_;}

	//! Get y values
	const std::vector<Double_t>& getYValues() const {return y_;}

	//! Get x values
	const std::vector<Double_t>& getXValues() const {return x_;}

	//! Get the coefficients of a given spline segment in the form a + bx + cx^2 + dx^3
	/*!
	\param [in] segIndex refers to the index of the knot at the left end of the segment (segIndex = 0 gets the coefficients of the the segment between x_0 and x_1)
	\param [in] normalise if true, the coefficients returned will be normalised by the integral of the complete spline (defaults to false)
	\return coefficients {a, b, c, d}
	*/
	std::array<Double_t,4> getCoefficients(const std::size_t segIndex, const bool normalise = false) const;

	//! Get the integral over all the spline segments
	Double_t integral() const;

	//! Make a TF1 showing the spline with its current knot values
	/*!
	\param [in] normalise whether or not you want the spline normalised
	\return 1D function object
	*/
	TF1* makeTF1(const bool normalise = false) const;

	//! Fit the the normalisation of the spline to a TH1
	/*!
	\param [in] hist the histogram to be fitted
	\param [in] printLevel the level of printout desired from fit
	\return a TF1 fit to the histogram
	*/
	TF1* normaliseToTH1(TH1* hist, LauOutputLevel printLevel = LauOutputLevel::Standard) const;

	//! Fit the spline to a TH1
	/*!
	\param [in] hist the histogram to be fitted
	\param [in] printLevel the level of printout desired from fit
	+ \param [in] doWL If true do a weighted likelihood fit, else chi2
	\return a shared-ownership smart pointer to the fit results
	*/
	- TFitResultPtr fitToTH1(TH1* hist, LauOutputLevel printLevel = LauOutputLevel::Standard);
	+ TFitResultPtr fitToTH1(TH1* hist, LauOutputLevel printLevel = LauOutputLevel::Standard, const bool doWL = false);

	private:
	//! Initialise the class
	void init();

	//! Calculate the first derivative at each knot
	void calcDerivatives();

	//! Calculate the first derivatives according to the standard method
	void calcDerivativesStandard();
	//! Calculate the first derivatives according to the Akima method
	void calcDerivativesAkima();

	//! The number of knots in the spline
	const std::size_t nKnots_;

	//! The x-value at each knot
	std::vector<Double_t> x_;
	//! The y-value at each knot
	std::vector<Double_t> y_;
	//! The first derivative at each knot
	std::vector<Double_t> dydx_;

	//! The 'a' coefficients used to determine the derivatives
	std::vector<Double_t> a_;
	//! The 'b' coefficients used to determine the derivatives
	std::vector<Double_t> b_;
	//! The 'c' coefficients used to determine the derivatives
	std::vector<Double_t> c_;
	//! The 'd' coefficients used to determine the derivatives
	std::vector<Double_t> d_;

	//! The type of interpolation to be performed
	LauSplineType type_;

	//! The left-hand boundary condition on the spline
	LauSplineBoundaryType leftBound_;
	//! The right-hand boundary condition on the spline
	LauSplineBoundaryType rightBound_;

	//! The gradient at the left boundary for a clamped spline
	Double_t dydx0_;
	//! The gradient at the right boundary for a clamped spline
	Double_t dydxn_;

	ClassDef(Lau1DCubicSpline, 0) // Class for defining a 1D cubic spline
	};

	#endif
	diff --git a/inc/LauSplineDecayTimeEfficiency.hh b/inc/LauSplineDecayTimeEfficiency.hh
	index 627991a..a0dbe57 100644
	--- a/inc/LauSplineDecayTimeEfficiency.hh
	+++ b/inc/LauSplineDecayTimeEfficiency.hh
	@@ -1,423 +1,424 @@

	/*
	Copyright 2021 University of Warwick

	Licensed 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

	Unless required by applicable law or agreed to in writing, software
	distributed under the License is distributed on an "AS IS" BASIS,
	WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	See the License for the specific language governing permissions and
	limitations under the License.
	*/

	/*
	Laura++ package authors:
	John Back
	Paul Harrison
	Thomas Latham
	*/

	/*! \file LauSplineDecayTimeEfficiency.hh
	\brief File containing declaration of LauSplineDecayTimeEfficiency class.
	*/

	/*! \class LauSplineDecayTimeEfficiency
	\brief Class for defining a spline-interpolated model for decay time efficiency
	*/

	#ifndef LAU_SPLINE_DECAYTIME_EFFICIENCY
	#define LAU_SPLINE_DECAYTIME_EFFICIENCY

	#include <array>
	#include <memory>
	#include <vector>

	#include "Rtypes.h"
	#include "TFitResult.h"
	#include "TMath.h"
	#include "TSystem.h"

	#include "Lau1DCubicSpline.hh"
	#include "LauAbsDecayTimeEfficiency.hh"
	#include "LauParameter.hh"

	class TH1;

	//! Defines the allowed orders of spline polynomials
	enum class LauSplineOrder : std::size_t {
	Cubic = 3, //!< 3rd order
	Sixth = 6 //!< 6th order
	};

	template <LauSplineOrder Order>
	class LauSplineDecayTimeEfficiency : public LauAbsDecayTimeEfficiency {
	public:
	//! Constructor for a Cubic spline
	/*!
	\param [in] prefix the prefix to use when forming the names of the knot parameters
	\param [in] effSpline the cubic spline to be used to represent the efficiency variation
	*/
	template <LauSplineOrder SpOrder = Order, typename std::enable_if_t<SpOrder == LauSplineOrder::Cubic,bool> = true>
	LauSplineDecayTimeEfficiency( const TString& prefix, std::unique_ptr<Lau1DCubicSpline> effSpline ) :
	prefix_{prefix},
	effSpline_{std::move(effSpline)}
	{
	this->initialSetup();
	}

	//! Constructor for a Sixth order spline
	/*!
	\param [in] prefix the prefix to use when forming the names of the knot parameters
	\param [in] effSpline the cubic spline being used to represent the efficiency variation in another channel
	\param [in] correctionSpline the cubic spline to be used to represent the correction to effSpline to obtain the efficiency variation for this channel
	*/
	template <LauSplineOrder SpOrder = Order, typename std::enable_if_t<SpOrder == LauSplineOrder::Sixth,bool> = true>
	LauSplineDecayTimeEfficiency( const TString& prefix, const LauSplineDecayTimeEfficiency<LauSplineOrder::Cubic>& effSpline, std::unique_ptr<Lau1DCubicSpline> correctionSpline ) :
	prefix_{prefix},
	effSpline_{std::move(correctionSpline)},
	otherSpline_{std::make_unique<LauSplineDecayTimeEfficiency<LauSplineOrder::Cubic>>(effSpline)}
	{
	this->initialSetup();
	}

	//! Destructor
	~LauSplineDecayTimeEfficiency() = default;
	//! Move constructor (default)
	LauSplineDecayTimeEfficiency(LauSplineDecayTimeEfficiency<Order>&& other) = default;
	//! Move assignment operator (default)
	LauSplineDecayTimeEfficiency& operator=(LauSplineDecayTimeEfficiency<Order>&& other) = default;
	//! Copy constructor (custom)
	LauSplineDecayTimeEfficiency(const LauSplineDecayTimeEfficiency<Order>& other);
	//! Copy assignment operator (deleted)
	LauSplineDecayTimeEfficiency& operator=(const LauSplineDecayTimeEfficiency<Order>& other) = delete;


	//! The number of coefficients of each spline segment
	static constexpr std::size_t nCoeffs { static_cast<std::underlying_type_t<LauSplineOrder>>(Order) + 1 };

	//! Retrieve the efficiency for a given value of the decay time
	/*!
	\param abscissa the value of the decay time
	\return the efficiency
	*/
	Double_t getEfficiency( const Double_t abscissa ) const override;

	//! Retrieve the parameters of the efficiency model so that they can be loaded into a fit
	/*!
	\return the parameters of the efficiency model
	*/
	std::vector<LauAbsRValue*> getParameters() override { return params_; }

	//! Initialise the parameter cache
	/*!
	Must be called prior to starting fitting or generation
	*/
	void initialise() override;

	//! Propagate any updates to parameters and recalculate information as neeeded
	/*!
	Should be called at each fit iteration
	*/
	void propagateParUpdates() override;

	//! Retrieve the number of segments in the spline
	std::size_t nSegments() const { return effSpline_->getnKnots() - 1; }

	//! Retrieve the positions of the spline knots
	const std::vector<Double_t>& knotPositions() const { return effSpline_->getXValues(); }

	//! Fix all knots
	void fixKnots();

	//! Float all knots
	void floatKnots();

	//! Fix or float a specific knot
	/*!
	\param knotIndex the index of the knot to fix/float
	\param fixed true if knot to be fixed, false if knot to be floated
	*/
	void fixKnot( const std::size_t knotIndex, const bool fixed );

	//! Retrieve the polynomial coefficients for the given spline segment
	/*!
	\param segmentIndex the index of the spline segment
	\return the polynomial coefficients
	*/
	std::array<Double_t,nCoeffs> getCoefficients( const std::size_t segmentIndex ) const;

	//! Retrieve whether any of the parameters are floating in the fit
	bool anythingFloating() const { return anyKnotFloating_; }

	//! Retrieve whether any of the parameters have changed in the latest fit iteration
	const bool& anythingChanged() const override { return anyKnotChanged_; }

	//! Fit our spline to a TH1
	/*!
	Useful to obtain reasonable starting values and uncertainties for the knot parameters

	\param [in] hist the histogram to be fit to
	\param [in] printLevel the level of printout desired from fit
	+ \param [in] doWL If true do a weighted likelihood fit, else chi2
	*/
	- void fitToTH1( TH1* hist, const LauOutputLevel printLevel = LauOutputLevel::Quiet );
	+ void fitToTH1( TH1* hist, const LauOutputLevel printLevel = LauOutputLevel::Quiet, const bool doWL = false );

	private:
	//! Perform the initial setup - shared by the various constructors
	void initialSetup( const LauSplineDecayTimeEfficiency<Order>* other = nullptr );

	//! Update the cached parameter values
	void updateParameterCache();

	//! The prefix for the parameter names
	const TString prefix_;

	//! The spline
	std::unique_ptr<Lau1DCubicSpline> effSpline_;

	//! The other spline
	std::unique_ptr<LauSplineDecayTimeEfficiency<LauSplineOrder::Cubic>> otherSpline_;

	//! The spline parameters
	std::vector<std::unique_ptr<LauParameter>> ownedParams_;

	//! The spline parameters (for giving access)
	std::vector<LauAbsRValue*> params_;

	//! The spline values
	std::vector<Double_t> values_;

	//! Are any of our knot parameters floating in the fit?
	bool ourKnotsFloating_{false};

	//! Are any of the other spline's knot parameters floating in the fit?
	bool otherKnotsFloating_{false};

	//! Are any of the knot parameters floating in the fit?
	bool anyKnotFloating_{false};

	//! Have any of our knot parameters changed in the latest fit iteration?
	bool ourKnotsChanged_{false};

	//! Have any of the other spline's knot parameters changed in the latest fit iteration?
	bool otherKnotsChanged_{false};

	//! Have any of the knot parameters changed in the lastest fit iteration?
	bool anyKnotChanged_{false};

	ClassDefOverride(LauSplineDecayTimeEfficiency, 0)
	};

	templateClassImp(LauSplineDecayTimeEfficiency);

	template <LauSplineOrder Order>
	void LauSplineDecayTimeEfficiency<Order>::initialSetup( const LauSplineDecayTimeEfficiency<Order>* other )
	{
	if ( not effSpline_ ) {
	std::cerr<<"ERROR in LauSplineDecayTimeEfficiency::initialSetup : supplied efficiency spline pointer is null"<<std::endl;
	gSystem->Exit(EXIT_FAILURE);
	}

	if constexpr ( Order == LauSplineOrder::Sixth ) {
	std::vector<Double_t> ourKnots { effSpline_->getXValues() };
	std::vector<Double_t> otherKnots { otherSpline_->knotPositions() };

	if ( ourKnots != otherKnots ) {
	std::cerr<<"ERROR in LauSplineDecayTimeEfficiency<LauSplineOrder::Sixth>::initialSetup : mismatch in knot positions"<<std::endl;
	gSystem->Exit(EXIT_FAILURE);
	}

	// TODO - any other checks we need to do?
	}

	values_ = effSpline_->getYValues();

	const std::size_t nPars { values_.size() };
	ownedParams_.reserve( nPars );

	if ( other ) {
	for ( auto& ptr : other->ownedParams_ ) {
	// TODO - maybe need a way to give these a unique prefix?
	ownedParams_.emplace_back( ptr->createClone() );
	}
	} else {
	for( std::size_t index{0}; index < nPars; ++index ) {
	constexpr Double_t maxVal { (Order == LauSplineOrder::Cubic) ? 1.0 : 2.0 };
	ownedParams_.emplace_back( std::make_unique<LauParameter>( Form( "%s_knot_%lu", prefix_.Data(), index ), values_[index], 0.0, maxVal, kTRUE ) );
	}
	}

	if constexpr ( Order == LauSplineOrder::Sixth ) {
	params_ = otherSpline_->getParameters();
	params_.reserve( 2*nPars );
	} else {
	params_.reserve( nPars );
	}

	for ( auto& ptr : ownedParams_ ) {
	params_.push_back( ptr.get() );
	}
	}

	template <LauSplineOrder Order>
	LauSplineDecayTimeEfficiency<Order>::LauSplineDecayTimeEfficiency(const LauSplineDecayTimeEfficiency<Order>& other) :
	prefix_{ other.prefix_ },
	effSpline_{ std::make_unique<Lau1DCubicSpline>( * other.effSpline_ ) },
	otherSpline_{ other.otherSpline_ ? std::make_unique<LauSplineDecayTimeEfficiency<LauSplineOrder::Cubic>>( *other.otherSpline_ ) : nullptr }
	{
	this->initialSetup( &other );
	}

	template <LauSplineOrder Order>
	void LauSplineDecayTimeEfficiency<Order>::fixKnots()
	{
	for ( auto& ptr : ownedParams_ ) {
	ptr->fixed(true);
	}
	}

	template <LauSplineOrder Order>
	void LauSplineDecayTimeEfficiency<Order>::floatKnots()
	{
	for ( auto& ptr : ownedParams_ ) {
	ptr->fixed(false);
	}
	}

	template <LauSplineOrder Order>
	void LauSplineDecayTimeEfficiency<Order>::fixKnot( const std::size_t knotIndex, const bool fixed )
	{
	if ( knotIndex >= ownedParams_.size() ) {
	std::cerr<<"ERROR in LauSplineDecayTimeEfficiency::fixKnot : supplied knot index is out of range"<<std::endl;
	return;
	}
	ownedParams_[knotIndex]->fixed(fixed);
	}

	template <LauSplineOrder Order>
	Double_t LauSplineDecayTimeEfficiency<Order>::getEfficiency( const Double_t abscissa ) const
	{
	Double_t eff { effSpline_->evaluate( abscissa ) };
	if constexpr ( Order == LauSplineOrder::Sixth ) {
	eff *= otherSpline_->getEfficiency( abscissa );
	}
	return eff;
	}

	template <LauSplineOrder Order>
	std::array<Double_t,LauSplineDecayTimeEfficiency<Order>::nCoeffs> LauSplineDecayTimeEfficiency<Order>::getCoefficients( const std::size_t segmentIndex ) const
	{
	if constexpr ( Order == LauSplineOrder::Cubic ) {
	return effSpline_->getCoefficients(segmentIndex);
	} else {
	std::array<Double_t,4> ourCoeffs { effSpline_->getCoefficients(segmentIndex) };
	std::array<Double_t,4> otherCoeffs { otherSpline_->getCoefficients(segmentIndex) };
	std::array<Double_t,nCoeffs> coeffs;
	coeffs[0] = ourCoeffs[0] * otherCoeffs[0];
	coeffs[1] = ourCoeffs[0] * otherCoeffs[1] + ourCoeffs[1] * otherCoeffs[0];
	coeffs[2] = ourCoeffs[0] * otherCoeffs[2] + ourCoeffs[1] * otherCoeffs[1] + ourCoeffs[2] * otherCoeffs[0];
	coeffs[3] = ourCoeffs[0] * otherCoeffs[3] + ourCoeffs[1] * otherCoeffs[2] + ourCoeffs[2] * otherCoeffs[1] + ourCoeffs[3] * otherCoeffs[0];
	coeffs[4] = ourCoeffs[1] * otherCoeffs[3] + ourCoeffs[2] * otherCoeffs[2] + ourCoeffs[3] * otherCoeffs[1];
	coeffs[5] = ourCoeffs[2] * otherCoeffs[3] + ourCoeffs[3] * otherCoeffs[2];
	coeffs[6] = ourCoeffs[3] * otherCoeffs[3];
	return coeffs;
	}
	}

	template <LauSplineOrder Order>
	void LauSplineDecayTimeEfficiency<Order>::initialise()
	{
	static auto isFixed = []( const std::unique_ptr<LauParameter>& par ){ return par->fixed(); };

	anyKnotFloating_ = ourKnotsFloating_ = not std::all_of( ownedParams_.begin(), ownedParams_.end(), isFixed );

	if constexpr ( Order == LauSplineOrder::Sixth ) {
	otherSpline_->initialise();
	otherKnotsFloating_ = otherSpline_->anythingFloating();
	anyKnotFloating_ \|= otherKnotsFloating_;
	}

	this->updateParameterCache();
	}

	template <LauSplineOrder Order>
	void LauSplineDecayTimeEfficiency<Order>::updateParameterCache()
	{
	static auto assignValue = []( const std::unique_ptr<LauParameter>& par ){ return par->unblindValue(); };

	// Update our local cache
	std::transform( ownedParams_.begin(), ownedParams_.end(), values_.begin(), assignValue );

	// Update the spline itself
	effSpline_->updateYValues( values_ );
	}

	template <LauSplineOrder Order>
	void LauSplineDecayTimeEfficiency<Order>::propagateParUpdates()
	{
	// If none of the parameters are floating there's nothing to do
	if ( not anyKnotFloating_ ) {
	return;
	}

	// Otherwise, determine which of the floating parameters have changed (if any) and act accordingly

	if ( ourKnotsFloating_ ) {
	static auto checkEquality = []( const std::unique_ptr<LauParameter>& par, const Double_t cacheVal ){ return par->unblindValue() == cacheVal; };

	anyKnotChanged_ = ourKnotsChanged_ = not std::equal( ownedParams_.begin(), ownedParams_.end(), values_.begin(), checkEquality);

	// Update the acceptance spline if any of the knot values have changed
	if ( ourKnotsChanged_ ) {
	this->updateParameterCache();
	}
	}

	if constexpr ( Order == LauSplineOrder::Sixth ) {
	if ( otherKnotsFloating_ ) {
	otherSpline_->propagateParUpdates();
	otherKnotsChanged_ = otherSpline_->anythingChanged();
	anyKnotChanged_ \|= otherKnotsChanged_;
	}
	}
	}

	template <LauSplineOrder Order>
	-void LauSplineDecayTimeEfficiency<Order>::fitToTH1( TH1* hist, const LauOutputLevel printLevel )
	+void LauSplineDecayTimeEfficiency<Order>::fitToTH1( TH1* hist, const LauOutputLevel printLevel, const bool doWL )
	{
	std::cout << "INFO in LauSplineDecayTimeEfficiency::fitToTH1 : fitting " << prefix_ << " spline to supplied histogram \"" << hist->GetName() << "\"\n";
	std::cout << " : to obtain initial estimates of parameter values and errors" << std::endl;

	- TFitResultPtr fitResult { effSpline_->fitToTH1( hist, printLevel ) };
	+ TFitResultPtr fitResult { effSpline_->fitToTH1( hist, printLevel, doWL ) };
	if ( fitResult->Status() != 0 \|\| fitResult->CovMatrixStatus() < 2 ) {
	std::cerr << "WARNING in LauSplineDecayTimeEfficiency::fitToTH1 : fit failed with status " << fitResult->Status() << " and covariance matrix status " << fitResult->CovMatrixStatus() << "\n";
	std::cerr << " : will not update spline parameters based on this fit result" << std::endl;
	return;
	}
	if ( fitResult->CovMatrixStatus() == 2 )
	{
	std::cerr << "WARNING in LauSplineDecayTimeEfficiency::fitToTH1 : final covariance matrix not PosDef!" << std::endl;
	std::cerr << " : continuing, but double check your fit!" << std::endl;
	}

	const std::size_t nKnots { ownedParams_.size() };
	for ( std::size_t knot{0}; knot < nKnots; ++knot ) {
	const Double_t knotVal { fitResult->Value(knot) };
	const Double_t knotErr { fitResult->Error(knot) };

	std::cout << " : Setting parameter " << ownedParams_[knot]->name() << " to " << knotVal << " +/- " << knotErr << std::endl;

	ownedParams_[knot]->value( knotVal );
	ownedParams_[knot]->genValue( knotVal );
	ownedParams_[knot]->initValue( knotVal );
	ownedParams_[knot]->error( knotErr );
	}

	this->updateParameterCache();
	}

	#endif
	diff --git a/src/Lau1DCubicSpline.cc b/src/Lau1DCubicSpline.cc
	index b3e62cb..61bcf4a 100644
	--- a/src/Lau1DCubicSpline.cc
	+++ b/src/Lau1DCubicSpline.cc
	@@ -1,566 +1,567 @@

	/*
	Copyright 2015 University of Warwick

	Licensed 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

	Unless required by applicable law or agreed to in writing, software
	distributed under the License is distributed on an "AS IS" BASIS,
	WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	See the License for the specific language governing permissions and
	limitations under the License.
	*/

	/*
	Laura++ package authors:
	John Back
	Paul Harrison
	Thomas Latham
	*/

	/*! \file Lau1DCubicSpline.cc
	\brief File containing implementation of Lau1DCubicSpline class.
	*/

	#include <cmath>
	#include <cstdlib>
	#include <iostream>

	#include <TH2.h>
	#include <TSystem.h>

	#include "Lau1DCubicSpline.hh"
	#include "LauAbsRValue.hh"
	#include "LauParameter.hh"

	ClassImp(Lau1DCubicSpline)


	Lau1DCubicSpline::Lau1DCubicSpline(const std::vector<Double_t>& xs, const std::vector<Double_t>& ys,
	LauSplineType type,
	LauSplineBoundaryType leftBound,
	LauSplineBoundaryType rightBound,
	Double_t dydx0, Double_t dydxn) :
	nKnots_(xs.size()),
	x_(xs),
	y_(ys),
	type_(type),
	leftBound_(leftBound),
	rightBound_(rightBound),
	dydx0_(dydx0),
	dydxn_(dydxn)
	{
	init();
	}

	Double_t Lau1DCubicSpline::evaluate(Double_t x) const
	{
	// do not attempt to extrapolate the spline
	if( x<x_[0] \|\| x>x_[nKnots_-1] ) {
	std::cerr << "WARNING in Lau1DCubicSpline::evaluate : function is only defined between " << x_[0] << " and " << x_[nKnots_-1] << std::endl;
	std::cerr << " value at " << x << " returned as 0" << std::endl;
	return 0.;
	}

	// first determine which 'cell' of the spline x is in
	// cell i runs from knot i to knot i+1
	Int_t cell(0);

	while( x > x_[cell+1] ) {
	++cell;
	}

	// obtain x- and y-values of the neighbouring knots
	Double_t xLow = x_[cell];
	Double_t xHigh = x_[cell+1];
	Double_t yLow = y_[cell];
	Double_t yHigh = y_[cell+1];

	if(type_ == Lau1DCubicSpline::LinearInterpolation) {
	return yHigh(x-xLow)/(xHigh-xLow) + yLow(xHigh-x)/(xHigh-xLow);
	}

	// obtain t, the normalised x-coordinate within the cell,
	// and the coefficients a and b, which are defined in cell i as:
	//
	// a_i = k_i *(x_i+1 - x_i) - (y_i+1 - y_i),
	// b_i = -k_i+1*(x_i+1 - x_i) + (y_i+1 - y_i)
	//
	// where k_i is (by construction) the first derivative at knot i
	Double_t t = (x - xLow) / (xHigh - xLow);
	Double_t a = dydx_[cell] * (xHigh - xLow) - (yHigh - yLow);
	Double_t b = -1.dydx_[cell+1] (xHigh - xLow) + (yHigh - yLow);

	Double_t retVal = (1 - t) * yLow + t * yHigh + t * (1 - t) * ( a * (1 - t) + b * t );

	return retVal;
	}

	void Lau1DCubicSpline::updateYValues(const std::vector<Double_t>& ys)
	{
	y_ = ys;
	this->calcDerivatives();
	}

	void Lau1DCubicSpline::updateYValues(const std::vector<LauParameter*>& ys)
	{
	for (std::size_t i=0; i<nKnots_; ++i){
	y_[i] = ys[i]->unblindValue();
	}
	this->calcDerivatives();
	}

	void Lau1DCubicSpline::updateYValues(const std::vector<LauAbsRValue*>& ys)
	{
	for (std::size_t i=0; i<nKnots_; ++i){
	y_[i] = ys[i]->unblindValue();
	}
	this->calcDerivatives();
	}

	void Lau1DCubicSpline::updateType(LauSplineType type)
	{
	if(type_ != type) {
	type_ = type;
	this->calcDerivatives();
	}
	}

	void Lau1DCubicSpline::updateBoundaryConditions(LauSplineBoundaryType leftBound,
	LauSplineBoundaryType rightBound,
	Double_t dydx0, Double_t dydxn)
	{
	bool updateDerivatives{false};

	if(leftBound_ != leftBound \|\| rightBound_ != rightBound) {
	leftBound_ = leftBound;
	rightBound_ = rightBound;
	updateDerivatives = true;
	}

	if(dydx0_ != dydx0) {
	dydx0_ = dydx0;
	if(leftBound_ == Lau1DCubicSpline::Clamped) updateDerivatives = true;
	}

	if(dydxn_ != dydxn) {
	dydxn_ = dydxn;
	if(rightBound_ == Lau1DCubicSpline::Clamped) updateDerivatives = true;
	}

	if(updateDerivatives) {
	this->calcDerivatives();
	}
	}

	std::array<Double_t,4> Lau1DCubicSpline::getCoefficients(const std::size_t segIndex, const bool normalise) const
	{
	std::array<Double_t,4> result = {0.,0.,0.,0.};

	if(segIndex >= nKnots_-1)
	{
	std::cerr << "ERROR in Lau1DCubicSpline::getCoefficients requested for too high a knot value" << std::endl;
	return result;
	}

	Double_t xL = x_[segIndex] , xH = x_[segIndex+1];
	Double_t yL = y_[segIndex] , yH = y_[segIndex+1];
	Double_t h = xH-xL; //This number comes up a lot

	switch(type_)
	{
	case Lau1DCubicSpline::StandardSpline:
	case Lau1DCubicSpline::AkimaSpline:
	{
	Double_t kL = dydx_[segIndex], kH = dydx_[segIndex+1];

	//a and b based on definitions from https://en.wikipedia.org/wiki/Spline_interpolation#Algorithm_to_find_the_interpolating_cubic_spline
	Double_t a = kL*h-(yH-yL);
	Double_t b =-kH*h+(yH-yL);

	Double_t denom = -hhh;//The terms have a common demoninator

	result[0] = -bxLxLxH + axLxHxH + hh(xLyH - xHyL);
	result[1] = -axH(2xL+xH) + bxL(xL+2xH) + hh(yL-yH);
	result[2] = -b(2xL+xH) + a(xL+2xH);
	result[3] = -a+b;

	for(auto& res : result){res /= denom;}
	break;
	}
	/* case Lau1DCubicSpline::AkimaSpline: // Double check the Akima description of splines (in evaluate) right now they're the same except for the first derivatives
	{
	//using fomulae from https://asmquantmacro.com/2015/09/01/akima-spline-interpolation-in-excel/
	std::function<Double_t(Int_t)> m = [&](Int_t j) //formula to get the straight line gradient
	{
	if(j < 0){return 2*m(j+1)-m(j+2);}
	if(j >= nKnots_){return 2*m(j-1)-m(j-2);}
	return (y_[j+1]-y_[j]) / (x_[j+1]-x_[j]);
	};

	auto t = [&](Int_t j)
	{
	Double_t res = 0.; //originally res was called 't' but that produced a shadow warning
	Double_t denom = TMath::Abs(m(j+1)-m(j)) + TMath::Abs(m(j-1)-m(j-2));
	if(denom == 0){res = (m(j)-m(j-1))/2;} //Special case for when denom = 0
	else
	{
	res = TMath::Abs(m(j+1)-m(j))m(j-1) + TMath::Abs(m(j-1)-m(j-2))m(j);
	res /= denom;
	}
	return res;
	};

	//These are the p's to get the spline in the form p_k(x-xL)^k
	Double_t pDenom = x_[segIndex+1]/x_[segIndex]; //a denominator used for p[2] and p[3]
	std::array<Double_t,4> p = {y_[segIndex],t(segIndex),0.,0.}; //we'll do the last 2 below

	p[2] = 3m(segIndex)-2t(segIndex)-t(segIndex+1);
	p[2]/= pDenom;

	p[3] = t(segIndex)+t(segIndex+1)-2*m(segIndex);
	p[3]/= pDenom*pDenom;

	//Now finally rearranging the p's into the desired results
	result[0] = p[0]-p[1]xL+p[2]xLxL-p[3]xLxLxL;
	result[1] = p[1]-2p[2]xL+3p[3]xL*xL;
	result[2] = p[2]-3p[3]xL;
	result[3] = p[3];

	break;
	}*/
	case Lau1DCubicSpline::LinearInterpolation:
	{
	result[0] = xHyL-xLyH;
	result[1] = yH-yL;

	for(auto& res : result){res /= h;}
	break;
	}
	}

	if(normalise)
	{
	Double_t integral = this->integral();
	for(auto& res : result){res /= integral;}
	}

	return result;
	}

	Double_t Lau1DCubicSpline::integral() const
	{
	Double_t integral{0.0};
	for(std::size_t iKnot{0}; iKnot < nKnots_ -1; ++iKnot)
	{
	const Double_t minAbs { x_[iKnot] };
	const Double_t maxAbs { x_[iKnot+1] };

	const std::array<Double_t,4> coeffs { this->getCoefficients(iKnot, false) };

	auto integralFunc = [&coeffs](Double_t x){return coeffs[0]x + coeffs[1]xx/2.0 + coeffs[2]xxx/3.0 + coeffs[3]xxxx/4.0;};

	integral += integralFunc(maxAbs);
	integral -= integralFunc(minAbs);
	}
	return integral;
	}

	TF1* Lau1DCubicSpline::makeTF1(const bool normalise) const
	{
	TString functionString{""}; //make a long piecewise construction of all the spline pieces
	for(std::size_t segIndex{0}; segIndex < nKnots_-1; ++segIndex)
	{
	const std::array<Double_t,4> coeffs { this->getCoefficients(segIndex,normalise) };
	functionString += Form("(x>%f && x<= %f)*",x_[segIndex],x_[segIndex+1]);//get the bounds of this piece
	functionString += Form("(%f + %fx + %fx^2 + %f*x^3)",coeffs[0],coeffs[1],coeffs[2],coeffs[3]);
	if(segIndex < nKnots_ -2){functionString += " + \n";}//add to all lines except the last
	}

	TF1* func = new TF1("SplineFunction", functionString, x_.front(), x_.back());

	return func;
	}

	TF1* Lau1DCubicSpline::normaliseToTH1(TH1* hist, LauOutputLevel printLevel) const
	{
	//first define the fit function
	auto fitf = [this](Double_t* x, Double_t* par) {//there is only 1 x (the abscissa) and 1 par (a scaling of the entire thing)
	return this->evaluate( x[0] ) * par[0];
	};
	//Make the function
	TF1* FittedFunc = new TF1("FittedFunc",fitf,x_.front(),x_.back(),1);
	//Set the parameter name
	FittedFunc -> SetParNames("Constant");
	//Set the parameter limits and default value
	FittedFunc -> SetParLimits(0,0.,10.);
	FittedFunc -> SetParameter(0,1.);

	// Options to:
	// - N = do not store the graphics function
	// - 0 = do not plot the fit result
	TString fitOptions {"N 0"};

	switch ( printLevel ) {
	case LauOutputLevel::Verbose :
	fitOptions += " V";
	break;
	case LauOutputLevel::Quiet :
	fitOptions += " Q";
	break;
	case LauOutputLevel::Standard :
	break;
	}

	hist->Fit( "FittedFunc", fitOptions );

	return FittedFunc;
	}

	-TFitResultPtr Lau1DCubicSpline::fitToTH1(TH1* hist, LauOutputLevel printLevel)
	+TFitResultPtr Lau1DCubicSpline::fitToTH1(TH1* hist, LauOutputLevel printLevel, const bool doWL)
	{
	auto fitf = [this](Double_t* x, Double_t* par) {
	this -> updateYValues( std::vector<Double_t>(par, par + nKnots_) );
	return this -> evaluate( x[0] );
	};

	TF1 FittedFunc("FittedFunc",fitf,x_.front(),x_.back(),nKnots_);

	const Double_t knotMax { hist->GetMaximum() * 1.5 };

	for(std::size_t knot{0}; knot <= nKnots_ ; ++knot)
	{
	FittedFunc.SetParName(knot, Form("Knot%lu",knot));
	FittedFunc.SetParLimits(knot, 0., knotMax);
	FittedFunc.SetParameter(knot, y_[knot]);
	}

	// Options to:
	// - N = do not store the graphics function
	// - 0 = do not plot the fit result
	// - S = save the result of the fit
	// - WL= do a weighted likelihood fit (not chi2)
	- TString fitOptions {"N 0 S WL"};
	+ TString fitOptions {"N 0 S"};
	+ if(doWL){fitOptions += " WL";}

	switch ( printLevel ) {
	case LauOutputLevel::Verbose :
	fitOptions += " V";
	break;
	case LauOutputLevel::Quiet :
	fitOptions += " Q";
	break;
	case LauOutputLevel::Standard :
	break;
	}

	return hist->Fit( "FittedFunc", fitOptions );
	}

	void Lau1DCubicSpline::init()
	{
	if( y_.size() != x_.size()) {
	std::cerr << "ERROR in Lau1DCubicSpline::init : The number of y-values given does not match the number of x-values" << std::endl;
	std::cerr << " Found " << y_.size() << ", expected " << x_.size() << std::endl;
	gSystem->Exit(EXIT_FAILURE);
	}

	if( nKnots_ < 3 ) {
	std::cerr << "ERROR in Lau1DCubicSpline::init : The number of knots is too small" << std::endl;
	std::cerr << " Found " << nKnots_ << ", expected at least 3 (to have at least 1 internal knot)" << std::endl;
	gSystem->Exit(EXIT_FAILURE);
	}

	dydx_.assign(nKnots_,0.0);

	a_.assign(nKnots_,0.0);
	b_.assign(nKnots_,0.0);
	c_.assign(nKnots_,0.0);
	d_.assign(nKnots_,0.0);

	this->calcDerivatives();
	}

	void Lau1DCubicSpline::calcDerivatives()
	{
	switch ( type_ ) {
	case Lau1DCubicSpline::StandardSpline :
	this->calcDerivativesStandard();
	break;
	case Lau1DCubicSpline::AkimaSpline :
	this->calcDerivativesAkima();
	break;
	case Lau1DCubicSpline::LinearInterpolation :
	//derivatives not needed for linear interpolation
	break;
	}
	}

	void Lau1DCubicSpline::calcDerivativesStandard()
	{
	// derivatives are determined such that the second derivative is continuous at internal knots

	// derivatives, k_i, are the solutions to a set of linear equations of the form:
	// a_i * k_i-1 + b_i * k+i + c_i * k_i+1 = d_i with a_0 = 0, c_n-1 = 0

	// this is solved using the tridiagonal matrix algorithm as on en.wikipedia.org/wiki/Tridiagonal_matrix_algorithm

	// first and last equations give boundary conditions
	// - for natural boundary, require f''(x) = 0 at end knot
	// - for 'not a knot' boundary, require f'''(x) continuous at second knot
	// - for clamped boundary, require predefined value of f'(x) at end knot

	// non-zero values of a_0 and c_n-1 would give cyclic boundary conditions
	a_[0] = 0.;
	c_[nKnots_-1] = 0.;

	// set left boundary condition
	if(leftBound_ == Lau1DCubicSpline::Natural) {
	b_[0] = 2./(x_[1]-x_[0]);
	c_[0] = 1./(x_[1]-x_[0]);
	d_[0] = 3.(y_[1]-y_[0])/((x_[1]-x_[0])(x_[1]-x_[0]));

	} else if(leftBound_ == Lau1DCubicSpline::NotAKnot) {
	// define the width, h, and the 'slope', delta, of the first cell
	Double_t h1(x_[1]-x_[0]), h2(x_[2]-x_[0]);
	Double_t delta1((y_[1]-y_[0])/h1), delta2((y_[2]-y_[1])/h2);

	// these coefficients can be determined by requiring f'''_0(x_1) = f'''_1(x_1)
	// the requirement f''_0(x_1) = f''_1(x_1) has been used to remove the dependence on k_2
	b_[0] = h2;
	c_[0] = h1+h2;
	d_[0] = delta1(2.h2h2 + 3.h1h2)/(h1+h2) + delta25.h1h1/(h1+h2);

	} else { //Clamped
	b_[0] = 1.;
	c_[0] = 0.;
	d_[0] = dydx0_;
	}

	// set right boundary condition
	if(rightBound_ == Lau1DCubicSpline::Natural) {
	a_[nKnots_-1] = 1./(x_[nKnots_-1]-x_[nKnots_-2]);
	b_[nKnots_-1] = 2./(x_[nKnots_-1]-x_[nKnots_-2]);
	d_[nKnots_-1] = 3.(y_[nKnots_-1]-y_[nKnots_-2])/((x_[nKnots_-1]-x_[nKnots_-2])(x_[nKnots_-1]-x_[nKnots_-2]));

	} else if(rightBound_ == Lau1DCubicSpline::NotAKnot) {
	// define the width, h, and the 'slope', delta, of the last cell
	Double_t hnm1(x_[nKnots_-1]-x_[nKnots_-2]), hnm2(x_[nKnots_-2]-x_[nKnots_-3]);
	Double_t deltanm1((y_[nKnots_-1]-y_[nKnots_-2])/hnm1), deltanm2((y_[nKnots_-2]-y_[nKnots_-3])/hnm2);

	// these coefficients can be determined by requiring f'''_n-3(x_n-2) = f'''_n-2(x_n-2)
	// the requirement f''_n-3(x_n-2) = f''_n-2(x_n-2) has been used to remove
	// the dependence on k_n-3
	a_[nKnots_-1] = hnm2 + hnm1;
	b_[nKnots_-1] = hnm1;
	d_[nKnots_-1] = deltanm2hnm1hnm1/(hnm2+hnm1) + deltanm1(2.hnm2hnm2 + 3.hnm2*hnm1)/(hnm2+hnm1);

	} else { //Clamped
	a_[nKnots_-1] = 0.;
	b_[nKnots_-1] = 1.;
	d_[nKnots_-1] = dydxn_;
	}

	// the remaining equations ensure that f_i-1''(x_i) = f''_i(x_i) for all internal knots
	for(std::size_t i{1}; i<nKnots_-1; ++i) {
	a_[i] = 1./(x_[i]-x_[i-1]);
	b_[i] = 2./(x_[i]-x_[i-1]) + 2./(x_[i+1]-x_[i]);
	c_[i] = 1./(x_[i+1]-x_[i]);
	d_[i] = 3.(y_[i]-y_[i-1])/((x_[i]-x_[i-1])(x_[i]-x_[i-1])) + 3.(y_[i+1]-y_[i])/((x_[i+1]-x_[i])(x_[i+1]-x_[i]));
	}

	// forward sweep - replace c_i and d_i with
	//
	// c'_i = c_i / b_i for i = 0
	// c_i / (b_i - a_i * c_i-1) otherwise
	//
	// and
	//
	// d'_i = d_i / b_i for i = 0
	// (d_i - a_i * d_i-1) / (b_i - a_i * c_i-1) otherwise

	c_[0] /= b_[0];
	d_[0] /= b_[0];

	for(std::size_t i{1}; i<nKnots_-1; ++i) {
	c_[i] = c_[i] / (b_[i] - a_[i]*c_[i-1]);
	d_[i] = (d_[i] - a_[i]d_[i-1]) / (b_[i] - a_[i]c_[i-1]);
	}

	d_[nKnots_-1] = (d_[nKnots_-1] - a_[nKnots_-1]d_[nKnots_-2]) / (b_[nKnots_-1] - a_[nKnots_-1]c_[nKnots_-2]);

	// back substitution - calculate k_i = dy/dx at each knot
	//
	// k_i = d'_i for i = n-1
	// d'_i - c'_i * k_i+1 otherwise

	dydx_[nKnots_-1] = d_[nKnots_-1];

	for(int i {static_cast<int>(nKnots_-2)}; i>=0; --i) {
	dydx_[i] = d_[i] - c_[i]*dydx_[i+1];
	}
	}

	void Lau1DCubicSpline::calcDerivativesAkima() {
	//derivatives are calculated according to the Akima method
	// J.ACM vol. 17 no. 4 pp 589-602

	Double_t am1(0.), an(0.), anp1(0.);

	// a[i] is the slope of the segment from point i-1 to point i
	//
	// n.b. segment 0 is before point 0 and segment n is after point n-1
	// internal segments are numbered 1 - n-1
	for(std::size_t i{1}; i<nKnots_; ++i) {
	a_[i] = (y_[i]-y_[i-1])/(x_[i]-x_[i-1]);
	}

	// calculate slopes between additional points on each end according to the Akima method
	// method assumes that the additional points follow a quadratic defined by the last three points
	// this leads to the relations a[2] - a[1] = a[1] - a[0] = a[0] - a[-1] and a[n-1] - a[n-2] = a[n] - a[n-1] = a[n+1] - a[n]
	a_[0] = 2*a_[1] - a_[2];
	am1 = 2*a_[0] - a_[1];

	an = 2*a_[nKnots_-1] - a_[nKnots_-2];
	anp1 = 2*an - a_[nKnots_-1];

	// b[i] is the weight of a[i] towards dydx[i]
	// c[i] is the weight of a[i+1] towards dydx[i]
	// See Appendix A of J.ACM vol. 17 no. 4 pp 589-602 for a justification of these weights
	b_[0] = TMath::Abs(a_[1] - a_[0]);
	b_[1] = TMath::Abs(a_[2] - a_[1]);

	c_[0] = TMath::Abs(a_[0] - am1 );
	c_[1] = TMath::Abs(a_[1] - a_[0]);

	for(std::size_t i{2}; i<nKnots_-2; ++i) {
	b_[i] = TMath::Abs(a_[i+2] - a_[i+1]);
	c_[i] = TMath::Abs(a_[i] - a_[i-1]);
	}

	b_[nKnots_-2] = TMath::Abs(an - a_[nKnots_-1]);
	b_[nKnots_-1] = TMath::Abs(anp1 - an );

	c_[nKnots_-2] = TMath::Abs(a_[nKnots_-2] - a_[nKnots_-3]);
	c_[nKnots_-1] = TMath::Abs(a_[nKnots_-1] - a_[nKnots_-2]);

	// dy/dx calculated as the weighted average of a[i] and a[i+1]:
	// dy/dx_i = ( \| a_i+2 - a_i+1 \| a_i + \| a_i - a_i-1 \| a_i+1 ) / ( \| a_i+2 - a_i+1 \| + \| a_i - a_i-1 \| )
	// in the special case a_i-1 == a_i != a_i+1 == a_i+2 this function is undefined so dy/dx is then defined as (a_i + a_i+1) / 2
	for(std::size_t i{0}; i<nKnots_-2; ++i) {
	if(b_[i]==0 && c_[i]==0) {
	dydx_[i] = ( a_[i] + a_[i+1] ) / 2.;
	} else {
	dydx_[i] = ( b_[i] * a_[i] + c_[i] * a_[i+1] ) / ( b_[i] + c_[i] );
	}
	}

	if(b_[nKnots_-1]==0 && c_[nKnots_-1]==0) {
	dydx_[nKnots_-1] = ( a_[nKnots_-1] + an ) / 2.;
	} else {
	dydx_[nKnots_-1] = ( b_[nKnots_-1] * a_[nKnots_-1] + c_[nKnots_-1] * an ) / ( b_[nKnots_-1] + c_[nKnots_-1] );
	}
	}

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