library: libHist #include "TProfile.h" |
TProfile
class description - source file - inheritance tree (.pdf)
private:
virtual Int_t Fill(Axis_t)
virtual void FillN(Int_t, const Axis_t*, const Double_t*, Int_t)
Double_t* GetB()
Double_t* GetW()
Double_t* GetW2()
virtual void SetBins(Int_t, Double_t, Double_t, Int_t, Double_t, Double_t)
virtual void SetBins(Int_t, Double_t, Double_t, Int_t, Double_t, Double_t, Int_t, Double_t, Double_t)
protected:
virtual Int_t BufferFill(Axis_t, Stat_t)
virtual Int_t BufferFill(Axis_t x, Axis_t y, Stat_t w)
public:
TProfile()
TProfile(const char* name, const char* title, Int_t nbinsx, Axis_t xlow, Axis_t xup, Option_t* option)
TProfile(const char* name, const char* title, Int_t nbinsx, Axis_t xlow, Axis_t xup, Axis_t ylow, Axis_t yup, Option_t* option)
TProfile(const char* name, const char* title, Int_t nbinsx, const Float_t* xbins, Option_t* option)
TProfile(const char* name, const char* title, Int_t nbinsx, const Double_t* xbins, Option_t* option)
TProfile(const char* name, const char* title, Int_t nbinsx, const Double_t* xbins, Axis_t ylow, Axis_t yup, Option_t* option)
TProfile(const TProfile& profile)
virtual ~TProfile()
virtual void Add(TF1* h1, Double_t c1 = 1, Option_t* option)
virtual void Add(const TH1* h1, Double_t c1 = 1)
virtual void Add(const TH1* h1, const TH1* h2, Double_t c1 = 1, Double_t c2 = 1)
static void Approximate(Bool_t approx = kTRUE)
virtual Int_t BufferEmpty(Int_t action = 0)
void BuildOptions(Double_t ymin, Double_t ymax, Option_t* option)
static TClass* Class()
virtual void Copy(TObject& hnew) const
virtual void Divide(TF1* h1, Double_t c1 = 1)
virtual void Divide(const TH1* h1)
virtual void Divide(const TH1* h1, const TH1* h2, Double_t c1 = 1, Double_t c2 = 1, Option_t* option)
virtual TH1* DrawCopy(Option_t* option) const
virtual Int_t Fill(Axis_t x, Axis_t y)
virtual Int_t Fill(const char* namex, Axis_t y)
virtual Int_t Fill(Axis_t x, Axis_t y, Stat_t w)
virtual Int_t Fill(const char* namex, Axis_t y, Stat_t w)
virtual void FillN(Int_t ntimes, const Axis_t* x, const Axis_t* y, const Double_t* w, Int_t stride = 1)
virtual Stat_t GetBinContent(Int_t bin) const
virtual Stat_t GetBinContent(Int_t bin, Int_t) const
virtual Stat_t GetBinContent(Int_t bin, Int_t, Int_t) const
virtual Stat_t GetBinEntries(Int_t bin) const
virtual Stat_t GetBinError(Int_t bin) const
virtual Stat_t GetBinError(Int_t bin, Int_t) const
virtual Stat_t GetBinError(Int_t bin, Int_t, Int_t) const
Option_t* GetErrorOption() const
virtual void GetStats(Stat_t* stats) const
virtual Double_t GetYmax() const
virtual Double_t GetYmin() const
virtual TClass* IsA() const
virtual void LabelsDeflate(Option_t* axis = "X")
virtual void LabelsInflate(Option_t* axis = "X")
virtual void LabelsOption(Option_t* option = "h", Option_t* axis = "X")
virtual Int_t Merge(TCollection* list)
virtual void Multiply(TF1* h1, Double_t c1 = 1)
virtual void Multiply(const TH1* h1)
virtual void Multiply(const TH1* h1, const TH1* h2, Double_t c1 = 1, Double_t c2 = 1, Option_t* option)
TProfile& operator=(const TProfile&)
TH1D* ProjectionX(const char* name = "_px", Option_t* option = "e") const
virtual TH1* Rebin(Int_t ngroup = 2, const char* newname)
virtual void Reset(Option_t* option)
virtual void SavePrimitive(ofstream& out, Option_t* option)
virtual void Scale(Double_t c1 = 1)
virtual void SetBinEntries(Int_t bin, Stat_t w)
virtual void SetBins(Int_t nbins, Double_t xmin, Double_t xmax)
virtual void SetBuffer(Int_t buffersize, Option_t* option)
virtual void SetErrorOption(Option_t* option)
virtual void ShowMembers(TMemberInspector& insp, char* parent)
virtual void Streamer(TBuffer& b)
void StreamerNVirtual(TBuffer& b)
protected:
TArrayD fBinEntries number of entries per bin
EErrorType fErrorMode Option to compute errors
Double_t fYmin Lower limit in Y (if set)
Double_t fYmax Upper limit in Y (if set)
Bool_t fScaling !True when TProfile::Scale is called
Stat_t fTsumwy Total Sum of weight*Y
Stat_t fTsumwy2 Total Sum of weight*Y*Y
static Bool_t fgApproximate bin error approximation option
Profile histograms are used to display the mean
value of Y and its RMS for each bin in X. Profile histograms are in many cases an
elegant replacement of two-dimensional histograms : the inter-relation of two
measured quantities X and Y can always be visualized by a two-dimensional
histogram or scatter-plot; its representation on the line-printer is not particularly
satisfactory, except for sparse data. If Y is an unknown (but single-valued)
approximate function of X, this function is displayed by a profile histogram with
much better precision than by a scatter-plot.
The following formulae show the cumulated contents (capital letters) and the values
displayed by the printing or plotting routines (small letters) of the elements for bin J.
2
H(J) = sum Y E(J) = sum Y
l(J) = sum l L(J) = sum l
h(J) = H(J)/L(J) s(J) = sqrt(E(J)/L(J)- h(J)**2)
e(J) = s(J)/sqrt(L(J))
In the special case where s(J) is zero (eg, case of 1 entry only in one bin)
e(J) is computed from the average of the s(J) for all bins.
This simple/crude approximation was suggested in order to keep the bin
during a fit operation.
Example of a profile histogram with its graphics output
{
TCanvas *c1 = new TCanvas("c1","Profile histogram example",200,10,700,500);
hprof = new TProfile("hprof","Profile of pz versus px",100,-4,4,0,20);
Float_t px, py, pz;
for ( Int_t i=0; i<25000; i++) {
gRandom->Rannor(px,py);
pz = px*px + py*py;
hprof->Fill(px,pz,1);
}
hprof->Draw();
}
/*
*/
TProfile() : TH1D()
*-*-*-*-*-*Default constructor for Profile histograms*-*-*-*-*-*-*-*-*
*-* ==========================================
~TProfile()
*-*-*-*-*-*Default destructor for Profile histograms*-*-*-*-*-*-*-*-*
*-* =========================================
TProfile(const char *name,const char *title,Int_t nbins,Axis_t xlow,Axis_t xup,Option_t *option)
: TH1D(name,title,nbins,xlow,xup)
*-*-*-*-*-*Normal Constructor for Profile histograms*-*-*-*-*-*-*-*-*-*
*-* ==========================================
The first five parameters are similar to TH1D::TH1D.
All values of y are accepted at filling time.
To fill a profile histogram, one must use TProfile::Fill function.
Note that when filling the profile histogram the function Fill
checks if the variable y is betyween fYmin and fYmax.
If a minimum or maximum value is set for the Y scale before filling,
then all values below ymin or above ymax will be discarded.
Setting the minimum or maximum value for the Y scale before filling
has the same effect as calling the special TProfile constructor below
where ymin and ymax are specified.
H(J) is printed as the channel contents. The errors displayed are s(J) if CHOPT='S'
(spread option), or e(J) if CHOPT=' ' (error on mean).
See TProfile::BuildOptions for explanation of parameters
see also comments in the TH1 base class constructors
TProfile(const char *name,const char *title,Int_t nbins,const Float_t *xbins,Option_t *option)
: TH1D(name,title,nbins,xbins)
*-*-*-*-*-*Constructor for Profile histograms with variable bin size*-*-*-*-*
*-* =========================================================
See TProfile::BuildOptions for more explanations on errors
see also comments in the TH1 base class constructors
TProfile(const char *name,const char *title,Int_t nbins,const Double_t *xbins,Option_t *option)
: TH1D(name,title,nbins,xbins)
*-*-*-*-*-*Constructor for Profile histograms with variable bin size*-*-*-*-*
*-* =========================================================
See TProfile::BuildOptions for more explanations on errors
see also comments in the TH1 base class constructors
TProfile(const char *name,const char *title,Int_t nbins,const Double_t *xbins,Axis_t ylow,Axis_t yup,Option_t *option)
: TH1D(name,title,nbins,xbins)
*-*-*-*-*-*Constructor for Profile histograms with variable bin size*-*-*-*-*
*-* =========================================================
See TProfile::BuildOptions for more explanations on errors
see also comments in the TH1 base class constructors
TProfile(const char *name,const char *title,Int_t nbins,Axis_t xlow,Axis_t xup,Axis_t ylow,Axis_t yup,Option_t *option)
: TH1D(name,title,nbins,xlow,xup)
*-*-*-*-*-*Constructor for Profile histograms with range in y*-*-*-*-*-*
*-* ==================================================
The first five parameters are similar to TH1D::TH1D.
Only the values of Y between YMIN and YMAX will be considered at filling time.
ymin and ymax will also be the maximum and minimum values
on the y scale when drawing the profile.
See TProfile::BuildOptions for more explanations on errors
see also comments in the TH1 base class constructors
void BuildOptions(Double_t ymin, Double_t ymax, Option_t *option)
*-*-*-*-*-*-*Set Profile histogram structure and options*-*-*-*-*-*-*-*-*
*-* ===========================================
If a bin has N data points all with the same value Y (especially
possible when dealing with integers), the spread in Y for that bin
is zero, and the uncertainty assigned is also zero, and the bin is
ignored in making subsequent fits. If SQRT(Y) was the correct error
in the case above, then SQRT(Y)/SQRT(N) would be the correct error here.
In fact, any bin with non-zero number of entries N but with zero spread
should have an uncertainty SQRT(Y)/SQRT(N).
Now, is SQRT(Y)/SQRT(N) really the correct uncertainty?
that it is only in the case where the Y variable is some sort
of counting statistics, following a Poisson distribution. This should
probably be set as the default case. However, Y can be any variable
from an original NTUPLE, not necessarily distributed "Poissonly".
The computation of errors is based on the parameter option:
option:
' ' (Default) Errors are Spread/SQRT(N) for Spread.ne.0. ,
" " SQRT(Y)/SQRT(N) for Spread.eq.0,N.gt.0 ,
" " 0. for N.eq.0
's' Errors are Spread for Spread.ne.0. ,
" " SQRT(Y) for Spread.eq.0,N.gt.0 ,
" " 0. for N.eq.0
'i' Errors are Spread/SQRT(N) for Spread.ne.0. ,
" " 1./SQRT(12.*N) for Spread.eq.0,N.gt.0 ,
" " 0. for N.eq.0
The third case above corresponds to Integer Y values for which the
uncertainty is +-0.5, with the assumption that the probability that Y
takes any value between Y-0.5 and Y+0.5 is uniform (the same argument
goes for Y uniformly distributed between Y and Y+1); this would be
useful if Y is an ADC measurement, for example. Other, fancier options
would be possible, at the cost of adding one more parameter to the PROFILE
command. For example, if all Y variables are distributed according to some
known Gaussian of standard deviation Sigma, then:
'G' Errors are Spread/SQRT(N) for Spread.ne.0. ,
" " Sigma/SQRT(N) for Spread.eq.0,N.gt.0 ,
" " 0. for N.eq.0
For example, this would be useful when all Y's are experimental quantities
measured with the same instrument with precision Sigma.
TProfile(const TProfile &profile) : TH1D()
void Add(TF1 *, Double_t, Option_t * )
Performs the operation: this = this + c1*f1
void Add(const TH1 *h1, Double_t c1)
Performs the operation: this = this + c1*h1
void Add(const TH1 *h1, const TH1 *h2, Double_t c1, Double_t c2)
*-*-*-*-*Replace contents of this profile by the addition of h1 and h2*-*-*
*-* =============================================================
this = c1*h1 + c2*h2
void Approximate(Bool_t approx)
static function
set the fgApproximate flag. When the flag is true, the function GetBinError
will approximate the bin error with the average profile error on all bins
in the following situation only
- the number of bins in the profile is less than 1002
- the bin number of entries is small ( <5)
- the estimated bin error is extremely small compared to the bin content
(see TProfile::GetBinError)
Int_t BufferEmpty(Int_t action)
Fill histogram with all entries in the buffer.
action = -1 histogram is reset and refilled from the buffer (called by THistPainter::Paint)
action = 0 histogram is filled from the buffer
action = 1 histogram is filled and buffer is deleted
The buffer is automatically deleted when the number of entries
in the buffer is greater than the number of entries in the histogram
Int_t BufferFill(Axis_t x, Axis_t y, Stat_t w)
accumulate arguments in buffer. When buffer is full, empty the buffer
fBuffer[0] = number of entries in buffer
fBuffer[1] = w of first entry
fBuffer[2] = x of first entry
fBuffer[3] = y of first entry
void Copy(TObject &obj) const
*-*-*-*-*-*-*-*Copy a Profile histogram to a new profile histogram*-*-*-*-*
*-* ===================================================
void Divide(TF1 *, Double_t )
Performs the operation: this = this/(c1*f1)
void Divide(const TH1 *h1)
*-*-*-*-*-*-*-*-*-*-*Divide this profile by h1*-*-*-*-*-*-*-*-*-*-*-*-*
*-* =========================
this = this/h1
This function accepts to divide a TProfile by a histogram
void Divide(const TH1 *h1, const TH1 *h2, Double_t c1, Double_t c2, Option_t *option)
*-*-*-*-*Replace contents of this profile by the division of h1 by h2*-*-*
*-* ============================================================
this = c1*h1/(c2*h2)
TH1* DrawCopy(Option_t *option) const
*-*-*-*-*-*-*-*Draw a copy of this profile histogram*-*-*-*-*-*-*-*-*-*-*-*
*-* =====================================
Int_t Fill(Axis_t x, Axis_t y)
*-*-*-*-*-*-*-*-*-*-*Fill a Profile histogram (no weights)*-*-*-*-*-*-*-*
*-* =====================================
Int_t Fill(const char *namex, Axis_t y)
Fill a Profile histogram (no weights)
Int_t Fill(Axis_t x, Axis_t y, Stat_t w)
*-*-*-*-*-*-*-*-*-*-*Fill a Profile histogram with weights*-*-*-*-*-*-*-*
*-* =====================================
Int_t Fill(const char *namex, Axis_t y, Stat_t w)
Fill a Profile histogram with weights
void FillN(Int_t ntimes, const Axis_t *x, const Axis_t *y, const Stat_t *w, Int_t stride)
*-*-*-*-*-*-*-*-*-*-*Fill a Profile histogram with weights*-*-*-*-*-*-*-*
*-* =====================================
Stat_t GetBinContent(Int_t bin) const
*-*-*-*-*-*-*Return bin content of a Profile histogram*-*-*-*-*-*-*-*-*-*
*-* =========================================
Stat_t GetBinEntries(Int_t bin) const
*-*-*-*-*-*-*Return bin entries of a Profile histogram*-*-*-*-*-*-*-*-*-*
*-* =========================================
Stat_t GetBinError(Int_t bin) const
*-*-*-*-*-*-*Return bin error of a Profile histogram*-*-*-*-*-*-*-*-*-*
*-* =======================================
Computing errors: A moving field
=================================
The computation of errors for a TProfile has evolved with the versions
of ROOT. The difficulty is in computing errors for bins with low statistics.
- prior to version 3.00, we had no special treatment of low statistic bins.
As a result, these bins had huge errors. The reason is that the
expression eprim2 is very close to 0 (rounding problems) or 0.
- in version 3.00 (18 Dec 2000), the algorithm is protected for values of
eprim2 very small and the bin errors set to the average bin errors, following
recommendations from a group of users.
- in version 3.01 (19 Apr 2001), it is realized that the algorithm above
should be applied only to low statistic bins.
- in version 3.02 (26 Sep 2001), the same group of users recommend instead
to take two times the average error on all bins for these low
statistics bins giving a very small value for eprim2.
- in version 3.04 (Nov 2002), the algorithm is modified/protected for the case
when a TProfile is projected (ProjectionX). The previous algorithm
generated a N^2 problem when projecting a TProfile with a large number of
bins (eg 100000).
- in version 3.05/06, a new static function TProfile::Approximate
is introduced to enable or disable (default) the approximation.
Ideas for improvements of this algorithm are welcome. No suggestions
received since our call for advice to roottalk in Jul 2002.
see for instance: http://root.cern.ch/root/roottalk/roottalk02/2916.html
Option_t* GetErrorOption() const
*-*-*-*-*-*-*-*-*-*Return option to compute profile errors*-*-*-*-*-*-*-*-*
*-* =======================================
void GetStats(Stat_t *stats) const
fill the array stats from the contents of this profile
The array stats must be correctly dimensionned in the calling program.
stats[0] = sumw
stats[1] = sumw2
stats[2] = sumwx
stats[3] = sumwx2
stats[4] = sumwy
stats[5] = sumwy2
The function recomputes the statistics quantities
from the bin contents in the current axis range.
void LabelsDeflate(Option_t *)
Reduce the number of bins for this axis to the number of bins having a label.
void LabelsInflate(Option_t *)
Double the number of bins for axis.
Refill histogram
This function is called by TAxis::FindBin(const char *label)
void LabelsOption(Option_t *option, Option_t * /*ax*/)
Set option(s) to draw axis with labels
option = "a" sort by alphabetic order
= ">" sort by decreasing values
= "<" sort by increasing values
= "h" draw labels horizonthal
= "v" draw labels vertical
= "u" draw labels up (end of label right adjusted)
= "d" draw labels down (start of label left adjusted)
Int_t Merge(TCollection *list)
Merge all histograms in the collection in this histogram.
This function computes the min/max for the x axis,
compute a new number of bins, if necessary,
add bin contents, errors and statistics.
The function returns the merged number of entries if the merge is
successfull, -1 otherwise.
IMPORTANT remark. The axis x may have different number
of bins and different limits, BUT the largest bin width must be
a multiple of the smallest bin width.
void Multiply(TF1 *f1, Double_t c1)
Performs the operation: this = this*c1*f1
void Multiply(const TH1 *)
*-*-*-*-*-*-*-*-*-*-*Multiply this profile by h1*-*-*-*-*-*-*-*-*-*-*-*-*
*-* =============================
this = this*h1
void Multiply(const TH1 *, const TH1 *, Double_t, Double_t, Option_t *)
*-*-*-*-*Replace contents of this profile by multiplication of h1 by h2*-*
*-* ================================================================
this = (c1*h1)*(c2*h2)
TH1D* ProjectionX(const char *name, Option_t *option) const
*-*-*-*-*Project this profile into a 1-D histogram along X*-*-*-*-*-*-*
*-* =================================================
The projection is always of the type TH1D.
if option "E" is specified, the errors are computed. (default)
TH1* Rebin(Int_t ngroup, const char*newname)
*-*-*-*-*Rebin this profile grouping ngroup bins together*-*-*-*-*-*-*-*-*
*-* ================================================
if newname is not blank a new temporary profile hnew is created.
else the current profile is modified (default)
The parameter ngroup indicates how many bins of this have to me merged
into one bin of hnew
If the original profile has errors stored (via Sumw2), the resulting
profile has new errors correctly calculated.
examples: if hp is an existing TProfile histogram with 100 bins
hp->Rebin(); //merges two bins in one in hp: previous contents of hp are lost
hp->Rebin(5); //merges five bins in one in hp
TProfile *hnew = hp->Rebin(5,"hnew"); // creates a new profile hnew
//merging 5 bins of hp in one bin
NOTE1: If ngroup is not an exact divider of the number of bins,
the top limit of the rebinned profile is changed
to the upper edge of the bin=newbins*ngroup and the corresponding
bins are added to the overflow bin.
Statistics will be recomputed from the new bin contents.
void Reset(Option_t *option)
*-*-*-*-*-*-*-*-*-*Reset contents of a Profile histogram*-*-*-*-*-*-*-*-*
*-* =====================================
void SavePrimitive(ofstream &out, Option_t *option)
Save primitive as a C++ statement(s) on output stream out
void Scale(Double_t c1)
*-*-*-*-*Multiply this profile by a constant c1*-*-*-*-*-*-*-*-*
*-* ======================================
this = c1*this
This function uses the services of TProfile::Add
void SetBinEntries(Int_t bin, Stat_t w)
*-*-*-*-*-*-*-*-*Set the number of entries in bin*-*-*-*-*-*-*-*-*-*-*-*
*-* ================================
void SetBins(Int_t nx, Double_t xmin, Double_t xmax)
*-*-*-*-*-*-*-*-*Redefine x axis parameters*-*-*-*-*-*-*-*-*-*-*-*
*-* ===========================
void SetBuffer(Int_t buffersize, Option_t *)
set the buffer size in units of 8 bytes (double)
void SetErrorOption(Option_t *option)
*-*-*-*-*-*-*-*-*-*Set option to compute profile errors*-*-*-*-*-*-*-*-*
*-* =====================================
The computation of errors is based on the parameter option:
option:
' ' (Default) Errors are Spread/SQRT(N) for Spread.ne.0. ,
" " SQRT(Y)/SQRT(N) for Spread.eq.0,N.gt.0 ,
" " 0. for N.eq.0
's' Errors are Spread for Spread.ne.0. ,
" " SQRT(Y) for Spread.eq.0,N.gt.0 ,
" " 0. for N.eq.0
'i' Errors are Spread/SQRT(N) for Spread.ne.0. ,
" " 1./SQRT(12.*N) for Spread.eq.0,N.gt.0 ,
" " 0. for N.eq.0
See TProfile::BuildOptions for explanation of all options
void Streamer(TBuffer &R__b)
Stream an object of class TProfile.
Inline Functions
Int_t BufferFill(Axis_t x, Axis_t y, Stat_t w)
void SetBins(Int_t, Double_t, Double_t, Int_t, Double_t, Double_t, Int_t, Double_t, Double_t)
Double_t* GetB()
Double_t* GetW()
Double_t* GetW2()
Int_t Fill(const char* namex, Axis_t y, Stat_t w)
void FillN(Int_t ntimes, const Axis_t* x, const Axis_t* y, const Double_t* w, Int_t stride = 1)
Stat_t GetBinContent(Int_t bin, Int_t) const
Stat_t GetBinContent(Int_t bin, Int_t, Int_t) const
Stat_t GetBinError(Int_t bin, Int_t) const
Stat_t GetBinError(Int_t bin, Int_t, Int_t) const
Double_t GetYmin() const
Double_t GetYmax() const
void SetBins(Int_t nbins, Double_t xmin, Double_t xmax)
TClass* Class()
TClass* IsA() const
void ShowMembers(TMemberInspector& insp, char* parent)
void StreamerNVirtual(TBuffer& b)
TProfile& operator=(const TProfile&)
Author: Rene Brun 29/09/95
Last update: root/hist:$Name: $:$Id: TProfile.cxx,v 1.50 2004/10/22 16:19:18 brun Exp $
Copyright (C) 1995-2000, Rene Brun and Fons Rademakers. *
ROOT page - Class index - Class Hierarchy - Top of the page
This page has been automatically generated. If you have any comments or suggestions about the page layout send a mail to ROOT support, or contact the developers with any questions or problems regarding ROOT.