improve the doxygen docu of PRunAsymmetryRRF.*

This commit is contained in:
2025-11-15 07:54:12 +01:00
parent 7b82b2c2c8
commit a05b4fe867
2 changed files with 359 additions and 70 deletions

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@@ -51,7 +51,11 @@
// Constructor
//--------------------------------------------------------------------------
/**
* <p>Constructor
* \brief Default constructor that initializes all member variables.
*
* Sets all counters and indices to default/invalid values. This constructor
* creates an invalid instance that requires proper initialization via the
* main constructor.
*/
PRunAsymmetryRRF::PRunAsymmetryRRF() : PRunBase()
{
@@ -69,12 +73,30 @@ PRunAsymmetryRRF::PRunAsymmetryRRF() : PRunBase()
// Constructor
//--------------------------------------------------------------------------
/**
* <p>Constructor
* \brief Main constructor that initializes RRF asymmetry fitting.
*
* \param msrInfo pointer to the msr-file handler
* \param rawData raw run data
* \param runNo number of the run within the msr-file
* \param tag tag showing what shall be done: kFit == fitting, kView == viewing
* Performs comprehensive initialization for rotating reference frame analysis:
* 1. Validates RRF packing parameter from GLOBAL block (required for RRF)
* 2. Validates α parameter (required for asymmetry)
* 3. Validates β parameter (optional, defaults to 1)
* 4. Determines α/β configuration tag (1-4)
* 5. Calls PrepareData() to load and process histogram data with RRF transformation
*
* The α/β tag determines the asymmetry calculation method:
* - Tag 1: α=1, β=1 (no corrections)
* - Tag 2: α≠1, β=1 (forward/backward correction)
* - Tag 3: α=1, β≠1 (alternative correction)
* - Tag 4: α≠1, β≠1 (both corrections)
*
* RRF packing must be specified in the GLOBAL block (e.g., "rrf_packing 50").
* This parameter controls the rebinning after RRF transformation and is essential
* for proper signal extraction in the rotating frame.
*
* \param msrInfo Pointer to MSR file handler
* \param rawData Pointer to raw run data handler
* \param runNo Run number within the MSR file
* \param tag Operation mode (kFit or kView)
* \param theoAsData If true, calculate theory only at data points
*/
PRunAsymmetryRRF::PRunAsymmetryRRF(PMsrHandler *msrInfo, PRunDataHandler *rawData, UInt_t runNo, EPMusrHandleTag tag, Bool_t theoAsData) :
PRunBase(msrInfo, rawData, runNo, tag), fTheoAsData(theoAsData)
@@ -153,7 +175,10 @@ PRunAsymmetryRRF::PRunAsymmetryRRF(PMsrHandler *msrInfo, PRunDataHandler *rawDat
// Destructor
//--------------------------------------------------------------------------
/**
* <p>Destructor.
* \brief Destructor that cleans up histogram data.
*
* Clears all four histogram vectors (forward/backward × data/errors)
* to free memory.
*/
PRunAsymmetryRRF::~PRunAsymmetryRRF()
{
@@ -167,12 +192,24 @@ PRunAsymmetryRRF::~PRunAsymmetryRRF()
// CalcChiSquare (public)
//--------------------------------------------------------------------------
/**
* <p>Calculate chi-square.
* \brief Calculates chi-square for RRF asymmetry fit.
*
* <b>return:</b>
* - chisq value
* Computes χ² by comparing the measured RRF-transformed asymmetry with theory:
* χ² = Σ[(A_RRF,data - A_RRF,theory)²/σ²]
*
* \param par parameter vector iterated by minuit2
* The RRF asymmetry has already been calculated in PrepareData() by applying
* the transformation: A_RRF(t) = A(t) · 2cos(ω_RRF·t + φ_RRF)
*
* The theory function is similarly transformed and includes α/β corrections:
* - Tag 1 (α=β=1): A = f(t)
* - Tag 2 (α≠1, β=1): A = [f(t)(α+1) - (α-1)] / [(α+1) - f(t)(α-1)]
* - Tag 3 (α=1, β≠1): Uses β correction
* - Tag 4 (α≠1, β≠1): Uses both α and β corrections
*
* Supports OpenMP parallelization for faster calculation.
*
* \param par Parameter vector from MINUIT minimizer
* \return Chi-square value
*/
Double_t PRunAsymmetryRRF::CalcChiSquare(const std::vector<Double_t>& par)
{
@@ -269,12 +306,17 @@ Double_t PRunAsymmetryRRF::CalcChiSquare(const std::vector<Double_t>& par)
// CalcChiSquareExpected (public)
//--------------------------------------------------------------------------
/**
* <p>Calculate expected chi-square. Currently not implemented since not clear what to be done.
* \brief Calculates expected chi-square value.
*
* <b>return:</b>
* - chisq value == 0.0
* This function is currently not implemented for RRF asymmetry fits because the expected
* chi-square calculation for RRF-transformed asymmetry data requires a complex statistical
* treatment. The RRF transformation introduces correlations between adjacent bins that
* complicate the expected value calculation.
*
* \param par parameter vector iterated by minuit2
* \param par Parameter vector from MINUIT minimizer
* \return Always returns 0.0 (placeholder value)
*
* \todo Implement proper expected chi-square calculation for RRF asymmetry fits
*/
Double_t PRunAsymmetryRRF::CalcChiSquareExpected(const std::vector<Double_t>& par)
{
@@ -285,9 +327,16 @@ Double_t PRunAsymmetryRRF::CalcChiSquareExpected(const std::vector<Double_t>& pa
// CalcMaxLikelihood (public)
//--------------------------------------------------------------------------
/**
* <p>NOT IMPLEMENTED!!
* \brief Calculates maximum likelihood estimator for RRF asymmetry fit.
*
* \param par parameter vector iterated by minuit2
* Maximum likelihood estimation provides an alternative to χ² minimization and can be
* more appropriate for low-count data. However, the proper likelihood function for
* RRF-transformed μSR asymmetry data is complex and not yet implemented.
*
* \param par Parameter vector from MINUIT minimizer
* \return Placeholder value of 1.0
*
* \todo Implement proper Poisson-based maximum likelihood for RRF asymmetry fits
*/
Double_t PRunAsymmetryRRF::CalcMaxLikelihood(const std::vector<Double_t>& par)
{
@@ -300,9 +349,13 @@ Double_t PRunAsymmetryRRF::CalcMaxLikelihood(const std::vector<Double_t>& par)
// GetNoOfFitBins (public)
//--------------------------------------------------------------------------
/**
* <p>Calculate the number of fitted bins for the current fit range.
* \brief Returns the number of bins included in the RRF fit.
*
* <b>return:</b> number of fitted bins.
* Calculates and returns the number of RRF-transformed data bins that fall within
* the current fit range. This value is used for determining degrees of freedom and
* is recalculated when the fit range changes (e.g., via COMMAND block).
*
* \return Number of data bins included in the fit
*/
UInt_t PRunAsymmetryRRF::GetNoOfFitBins()
{
@@ -315,15 +368,28 @@ UInt_t PRunAsymmetryRRF::GetNoOfFitBins()
// SetFitRangeBin (public)
//--------------------------------------------------------------------------
/**
* <p>Allows to change the fit range on the fly. Used in the COMMAND block.
* The syntax of the string is: FIT_RANGE fgb[+n00] lgb[-n01] [fgb[+n10] lgb[-n11] ... fgb[+nN0] lgb[-nN1]].
* If only one pair of fgb/lgb is given, it is used for all runs in the RUN block section.
* If multiple fgb/lgb's are given, the number N has to be the number of RUN blocks in
* the msr-file.
* \brief Dynamically changes the fit range in bin units for RRF data.
*
* <p>nXY are offsets which can be used to shift, limit the fit range.
* Allows modification of the fit range at runtime, typically called from the COMMAND block.
* Supports bin-based fit ranges with optional offsets for fine-tuning.
*
* \param fitRange string containing the necessary information.
* Syntax formats:
* - Single range: FIT_RANGE fgb[+n0] lgb[-n1]
* - Applied to all RUN blocks
* - Multiple ranges: FIT_RANGE fgb[+n00] lgb[-n01] fgb[+n10] lgb[-n11] ... fgb[+nN0] lgb[-nN1]
* - One pair per RUN block (N must equal number of RUN blocks)
*
* Parameters:
* - fgb: First good bin (start of fit range)
* - lgb: Last good bin (end of fit range)
* - +n: Positive offset to shift start forward
* - -n: Negative offset to shift end backward
*
* Example: "FIT_RANGE 10+5 200-10" uses bins [15, 190] for fitting
*
* Note: The bins refer to the RRF-packed data, not the original histograms.
*
* \param fitRange String containing fit range specification
*/
void PRunAsymmetryRRF::SetFitRangeBin(const TString fitRange)
{
@@ -405,7 +471,16 @@ void PRunAsymmetryRRF::SetFitRangeBin(const TString fitRange)
// CalcNoOfFitBins (public)
//--------------------------------------------------------------------------
/**
* <p>Calculate the number of fitted bins for the current fit range.
* \brief Calculates the number of bins included in the current RRF fit range.
*
* Determines fStartTimeBin and fEndTimeBin from the fit time range (fFitStartTime, fFitEndTime)
* and RRF-transformed data time grid. Ensures that bin indices remain within valid bounds.
* The result is stored in fNoOfFitBins.
*
* This calculation accounts for:
* - RRF-packed data time step and start time
* - Rounding effects (ceiling for start, floor for end)
* - Boundary conditions (clips to [0, RRF data size])
*/
void PRunAsymmetryRRF::CalcNoOfFitBins()
{
@@ -427,7 +502,24 @@ void PRunAsymmetryRRF::CalcNoOfFitBins()
// CalcTheory (protected)
//--------------------------------------------------------------------------
/**
* <p>Calculate theory for a given set of fit-parameters.
* \brief Calculates theoretical RRF asymmetry values for the current parameters.
*
* Computes the expected RRF asymmetry A_RRF(t) for all data points based on the current
* parameter values and the user-defined theory function. The calculation depends
* on the α/β correction mode:
*
* - Tag 1 (α=1, β=1): A(t) = f(t)
* - Tag 2 (α≠1, β=1): A(t) = [f(t)(α+1) - (α-1)] / [(α+1) - f(t)(α-1)]
* - Tag 3 (α=1, β≠1): A(t) = f(t)(β+1) / [2 - f(t)(β-1)]
* - Tag 4 (α≠1, β≠1): A(t) = [f(t)(αβ+1) - (α-1)] / [(α+1) - f(t)(αβ-1)]
*
* where f(t) is the raw theory function from the THEORY block.
*
* Note: The RRF transformation is applied during data preparation (PrepareViewData),
* not here. This function calculates the standard asymmetry theory which is then
* transformed to the rotating frame during visualization.
*
* The calculated values are stored in fData for plotting and comparison with measured RRF data.
*/
void PRunAsymmetryRRF::CalcTheory()
{
@@ -511,23 +603,33 @@ void PRunAsymmetryRRF::CalcTheory()
// PrepareData (protected)
//--------------------------------------------------------------------------
/**
* <p>Prepare data for fitting or viewing. What is already processed at this stage:
* - get all needed forward/backward histograms
* - get time resolution
* - get start/stop fit time
* - get t0's and perform necessary cross checks (e.g. if t0 of msr-file (if present) are consistent with t0 of the data files, etc.)
* - add runs (if addruns are present)
* - group histograms (if grouping is present)
* - subtract background
* \brief Main data preparation routine for RRF asymmetry fitting and viewing.
*
* Error propagation for \f$ A_i = (f_i^{\rm c}-b_i^{\rm c})/(f_i^{\rm c}+b_i^{\rm c})\f$:
* \f[ \Delta A_i = \pm\frac{2}{(f_i^{\rm c}+b_i^{\rm c})^2}\left[
* (b_i^{\rm c})^2 (\Delta f_i^{\rm c})^2 +
* (\Delta b_i^{\rm c})^2 (f_i^{\rm c})^2\right]^{1/2}\f]
* Performs comprehensive data preparation specifically for rotating reference frame analysis:
* - Loading forward/backward histograms from data files
* - Extracting metadata (field, energy, temperature)
* - Determining time resolution from data file
* - Validating and retrieving t0 values for all histograms
* - Adding multiple runs together (if addruns are specified)
* - Grouping multiple histograms (if grouping is specified)
* - Subtracting background (fixed or estimated)
* - Calculating standard asymmetry and error bars
* - NOTE: RRF transformation is NOT applied here (it's done in PrepareFitData/PrepareViewData)
*
* <b>return:</b>
* - true if everthing went smooth
* - false, otherwise.
* The standard asymmetry is calculated as:
* \f[ A_i = \frac{f_i^{\rm c} - b_i^{\rm c}}{f_i^{\rm c} + b_i^{\rm c}} \f]
*
* Error propagation (assuming Poisson statistics):
* \f[ \Delta A_i = \pm\frac{2}{(f_i^{\rm c}+b_i^{\rm c})^2}\sqrt{
* (b_i^{\rm c})^2 (\Delta f_i^{\rm c})^2 +
* (f_i^{\rm c})^2 (\Delta b_i^{\rm c})^2} \f]
*
* where \f$ f_i^{\rm c} \f$ and \f$ b_i^{\rm c} \f$ are background-corrected forward and
* backward histograms, respectively.
*
* The RRF transformation and packing are applied later in PrepareFitData() or PrepareViewData().
*
* \return True if data preparation succeeds, false on any error
*/
Bool_t PRunAsymmetryRRF::PrepareData()
{
@@ -899,8 +1001,25 @@ Bool_t PRunAsymmetryRRF::SubtractEstimatedBkg()
// PrepareFitData (protected)
//--------------------------------------------------------------------------
/**
* <p>Take the pre-processed data (i.e. grouping and addrun are preformed, background correction already carried out)
* and form the asymmetry for fitting.
* \brief Processes pre-grouped data and calculates RRF asymmetry for fitting.
*
* Takes forward/backward histograms (after grouping, addrun, and background correction) and
* performs the RRF transformation for fitting:
*
* 1. Aligns forward/backward histograms (ensures 'first good bin - t0' is identical)
* 2. Calculates standard asymmetry: \f$ A_i = (f_i^{\rm c}-b_i^{\rm c})/(f_i^{\rm c}+b_i^{\rm c}) \f$
* 3. Applies RRF transformation: \f$ A_{\rm RRF}(t) = A(t) \cdot 2\cos(\omega_{\rm RRF} t + \phi_{\rm RRF}) \f$
* 4. Applies RRF packing (rebinning) to reduce noise after mixing
* 5. Propagates errors through both transformations
*
* Error propagation for asymmetry:
* \f[ \delta A_i = \frac{2}{(f_i^{\rm c}+b_i^{\rm c})^2}\sqrt{(b_i^{\rm c})^2 (\delta f_i^{\rm c})^2 + (f_i^{\rm c})^2 (\delta b_i^{\rm c})^2} \f]
*
* RRF packing averages multiple bins to improve statistics after frequency mixing:
* - Packed value: sum of bins / packing factor
* - Error: \f$ \sigma_{\rm packed} = \sqrt{\sum \sigma_i^2}/N_{\rm pack} \f$
*
* \return True on success, false if data preparation fails
*/
Bool_t PRunAsymmetryRRF::PrepareFitData()
{
@@ -1015,20 +1134,29 @@ Bool_t PRunAsymmetryRRF::PrepareFitData()
// PrepareViewData (protected)
//--------------------------------------------------------------------------
/**
* <p>Take the pre-processed data (i.e. grouping and addrun are preformed) and form the asymmetry for view representation.
* Before forming the asymmetry, the following checks will be performed:
* -# check if view packing is whished.
* -# check if data range is given, if not try to estimate one.
* -# check that data range is present, that it makes any sense.
* -# check that 'first good bin'-'t0' is the same for forward and backward histogram. If not adjust it.
* -# pack data (rebin).
* -# if packed forward size != backward size, truncate the longer one such that an asymmetry can be formed.
* -# calculate the asymmetry: \f$ A_i = (\alpha f_i^c-b_i^c)/(\alpha \beta f_i^c+b_i^c) \f$
* -# calculate the asymmetry errors: \f$ \delta A_i = 2 \sqrt{(b_i^c)^2 (\delta f_i^c)^2 + (\delta b_i^c)^2 (f_i^c)^2}/(f_i^c+b_i^c)^2\f$
* -# calculate the theory vector.
* \brief Prepares RRF asymmetry data for plotting and visualization.
*
* \param runData raw run data needed to perform some crosschecks
* \param histoNo histogram number (within a run). histoNo[0]: forward histogram number, histNo[1]: backward histogram number
* Processes pre-grouped data for display in plots with RRF transformation and
* special handling for visualization. Similar to PrepareFitData but includes
* theory calculation with Kaiser FIR filtering for smooth RRF curves.
*
* Processing steps:
* 1. Validates and estimates data range if needed
* 2. Aligns forward/backward histogram start bins relative to t0
* 3. Ensures equal bin counts between forward/backward
* 4. Calculates standard asymmetry: \f$ A_i = (\alpha f_i^{\rm c} - b_i^{\rm c})/(\alpha \beta f_i^{\rm c} + b_i^{\rm c}) \f$
* 5. Applies RRF transformation: \f$ A_{\rm RRF}(t) = A(t) \cdot 2\cos(\omega_{\rm RRF} t + \phi_{\rm RRF}) \f$
* 6. Applies RRF packing for visualization
* 7. Propagates errors: \f$ \delta A_i = \frac{2}{(f_i^{\rm c}+b_i^{\rm c})^2}\sqrt{(b_i^{\rm c})^2 (\delta f_i^{\rm c})^2 + (f_i^{\rm c})^2 (\delta b_i^{\rm c})^2} \f$
* 8. Calculates theory curve at high resolution
* 9. Applies RRF transformation to theory
* 10. Applies Kaiser FIR filter to smooth theory curve
*
* The RRF frequency and phase are read from the PLOT block settings.
*
* \param runData Pointer to raw run data for validation and cross-checks
* \param histoNo Array of histogram indices: [0]=forward, [1]=backward
* \return True on success, false on error
*/
Bool_t PRunAsymmetryRRF::PrepareViewData(PRawRunData* runData, UInt_t histoNo[2])
{

View File

@@ -34,55 +34,216 @@
//---------------------------------------------------------------------------
/**
* <p>Class handling the asymmetry fit.
* \brief Class for handling μSR asymmetry fits in the Rotating Reference Frame (RRF).
*
* PRunAsymmetryRRF extends PRunBase to handle asymmetry fitting where data is transformed
* into a rotating reference frame. This technique is particularly useful for analyzing
* high-frequency oscillations in μSR spectra by mixing the signal with a reference frequency.
*
* The RRF transformation:
* \f[ A_{\rm RRF}(t) = A(t) \cdot 2\cos(\omega_{\rm RRF} t + \phi_{\rm RRF}) \f]
*
* where:
* - \f$ A(t) \f$ is the standard asymmetry: \f$ A(t) = \frac{F(t) - \alpha B(t)}{F(t) + \alpha B(t)} \f$
* - \f$ \omega_{\rm RRF} \f$ is the RRF frequency (specified in PLOT block)
* - \f$ \phi_{\rm RRF} \f$ is the RRF phase (specified in PLOT block)
*
* Key features:
* - Transforms high-frequency oscillations to lower frequencies
* - Requires special RRF packing parameter from GLOBAL block
* - Supports α/β correction parameters (same as PRunAsymmetry)
* - Applies Kaiser FIR filtering to theory curves for smooth visualization
*
* The RRF technique is essential for:
* - High transverse field (TF) measurements
* - Analyzing fast precession frequencies
* - Improving signal-to-noise in specific frequency ranges
*
* \see PRunAsymmetry for standard (non-RRF) asymmetry fitting
* \see PRunBase for the base class providing common functionality
*/
class PRunAsymmetryRRF : public PRunBase
{
public:
/// Default constructor
PRunAsymmetryRRF();
/**
* \brief Main constructor for RRF asymmetry fitting.
* \param msrInfo Pointer to MSR file handler
* \param rawData Pointer to raw run data handler
* \param runNo Run number within the MSR file
* \param tag Operation mode (kFit for fitting, kView for viewing)
* \param theoAsData If true, calculate theory only at data points; if false, calculate additional points for Fourier
*/
PRunAsymmetryRRF(PMsrHandler *msrInfo, PRunDataHandler *rawData, UInt_t runNo, EPMusrHandleTag tag, Bool_t theoAsData);
/// Destructor
virtual ~PRunAsymmetryRRF();
/**
* \brief Calculates chi-square for the RRF asymmetry fit.
* \param par Parameter vector from MINUIT
* \return Chi-square value
*/
virtual Double_t CalcChiSquare(const std::vector<Double_t>& par);
/**
* \brief Calculates expected chi-square (for statistical analysis).
* \param par Parameter vector from MINUIT
* \return Expected chi-square value
*/
virtual Double_t CalcChiSquareExpected(const std::vector<Double_t>& par);
/**
* \brief Calculates maximum likelihood estimator.
* \param par Parameter vector from MINUIT
* \return Maximum likelihood value
*/
virtual Double_t CalcMaxLikelihood(const std::vector<Double_t>& par);
/**
* \brief Calculates theoretical RRF asymmetry function.
*
* Computes the theory values in the rotating reference frame based on
* current parameters and applies the RRF transformation.
*/
virtual void CalcTheory();
/**
* \brief Returns the number of bins used in the fit.
* \return Number of fit bins
*/
virtual UInt_t GetNoOfFitBins();
/**
* \brief Sets the fit range in bins (can be changed dynamically via COMMAND block).
* \param fitRange Fit range string specification
*/
virtual void SetFitRangeBin(const TString fitRange);
/**
* \brief Returns the first bin used in the fit.
* \return Start time bin index
*/
virtual Int_t GetStartTimeBin() { return fStartTimeBin; }
/**
* \brief Returns the last bin used in the fit.
* \return End time bin index
*/
virtual Int_t GetEndTimeBin() { return fEndTimeBin; }
/**
* \brief Calculates the number of bins to be fitted.
*
* Determines fNoOfFitBins based on the fit range and RRF-packed data availability.
*/
virtual void CalcNoOfFitBins();
protected:
/**
* \brief Prepares all data for RRF fitting or viewing.
* \return True on success, false on error
*
* Main data preparation routine that handles background subtraction,
* RRF packing, and asymmetry calculation from forward/backward histograms.
*/
virtual Bool_t PrepareData();
/**
* \brief Prepares RRF data specifically for fitting.
* \return True on success, false on error
*
* Processes data for fitting, including RRF transformation, packing,
* and asymmetry calculation with proper error propagation.
*/
virtual Bool_t PrepareFitData();
/**
* \brief Prepares RRF data for viewing/plotting.
* \param runData Pointer to raw run data
* \param histoNo Array of histogram numbers [0]=forward, [1]=backward
* \return True on success, false on error
*
* Similar to PrepareFitData but includes theory calculation and
* Kaiser FIR filtering for smooth visualization of RRF curves.
*/
virtual Bool_t PrepareViewData(PRawRunData* runData, UInt_t histoNo[2]);
private:
UInt_t fAlphaBetaTag; ///< \f$ 1 \to \alpha = \beta = 1\f$; \f$ 2 \to \alpha \neq 1, \beta = 1\f$; \f$ 3 \to \alpha = 1, \beta \neq 1\f$; \f$ 4 \to \alpha \neq 1, \beta \neq 1\f$.
UInt_t fNoOfFitBins; ///< number of bins to be be fitted
Int_t fRRFPacking; ///< RRF packing for this particular run. Given in the GLOBAL-block.
Bool_t fTheoAsData; ///< true=only calculate the theory points at the data points, false=calculate more points for the theory as compared to data are calculated which lead to 'nicer' Fouriers
UInt_t fAlphaBetaTag; ///< Tag indicating α/β configuration: 1=both unity, 2=α free/β unity, 3=α unity/β free, 4=both free
UInt_t fNoOfFitBins; ///< Number of bins included in the fit after RRF packing
Int_t fRRFPacking; ///< RRF packing factor from GLOBAL block (required for RRF analysis)
Bool_t fTheoAsData; ///< If true, theory calculated only at data points; if false, extra points for nicer Fourier transforms
PDoubleVector fForward; ///< forward histo data
PDoubleVector fForwardErr; ///< forward histo errors
PDoubleVector fBackward; ///< backward histo data
PDoubleVector fBackwardErr; ///< backward histo errors
PDoubleVector fForward; ///< Forward detector histogram data
PDoubleVector fForwardErr; ///< Forward detector histogram errors
PDoubleVector fBackward; ///< Backward detector histogram data
PDoubleVector fBackwardErr; ///< Backward detector histogram errors
Int_t fGoodBins[4]; ///< keep first/last good bins. 0=fgb, 1=lgb (forward); 2=fgb, 3=lgb (backward)
Int_t fGoodBins[4]; ///< Good bin boundaries: [0]=forward first, [1]=forward last, [2]=backward first, [3]=backward last
Int_t fStartTimeBin; ///< bin at which the fit starts
Int_t fEndTimeBin; ///< bin at which the fit ends
Int_t fStartTimeBin; ///< First bin index for fitting (after RRF transformation)
Int_t fEndTimeBin; ///< Last bin index for fitting (after RRF transformation)
/**
* \brief Subtracts fixed background from histograms.
*
* Subtracts user-specified fixed background values from forward and backward histograms.
* Background values are read from the MSR file (e.g., "backgr.fix 2 3" for forward/backward).
*
* Error propagation:
* \f[ \Delta f_i^{\rm c} = \pm\sqrt{(\Delta f_i)^2 + (\Delta \mathrm{bkg})^2} = \pm\sqrt{f_i + \mathrm{bkg}} \f]
*
* \return True on success, false if background values are missing
*/
Bool_t SubtractFixBkg();
/**
* \brief Estimates and subtracts background from histograms.
*
* Calculates background from a specified bin range (typically before t0) and subtracts it.
* The background range is adjusted to align with accelerator beam cycles when applicable.
*
* \return True on success, false if background range is out of bounds
*/
Bool_t SubtractEstimatedBkg();
/**
* \brief Retrieves proper t0 values for all histograms.
*
* Determines t0 (time zero) values for forward and backward histograms from
* RUN block, GLOBAL block, or data file (in priority order).
*
* \param runData Pointer to raw run data containing histogram information
* \param globalBlock Pointer to global MSR block with default t0 values
* \param forwardHisto Vector of forward histogram indices
* \param backwardHistoNo Vector of backward histogram indices
* \return True on success, false if t0 values cannot be determined
*/
virtual Bool_t GetProperT0(PRawRunData* runData, PMsrGlobalBlock *globalBlock, PUIntVector &forwardHisto, PUIntVector &backwardHistoNo);
/**
* \brief Retrieves proper data range for histograms.
*
* Determines the "good bins" range for data analysis from RUN block,
* GLOBAL block, or estimates (in priority order).
*
* \param runData Pointer to raw run data
* \param histoNo Array of histogram numbers [0]=forward, [1]=backward
* \return True on success, false on error
*/
virtual Bool_t GetProperDataRange(PRawRunData* runData, UInt_t histoNo[2]);
/**
* \brief Determines the proper fit range from global block.
*
* Extracts fit range settings from the GLOBAL block if not specified in the RUN block.
* The fit range defines the time window used for χ² minimization.
*
* \param globalBlock Pointer to global MSR block containing default fit range
*/
virtual void GetProperFitRange(PMsrGlobalBlock *globalBlock);
};