1-D histogram with a float per channel (see TH1 documentation)
Public Types | |
| enum | { kNoAxis = 0 , kXaxis = (1ULL << (0)) , kYaxis = (1ULL << (1)) , kZaxis = (1ULL << (2)) , kAllAxes = kXaxis | kYaxis | kZaxis } |
| Enumeration specifying which axes can be extended. More... | |
| enum | { kSingleKey = (1ULL << (0)) , kOverwrite = (1ULL << (1)) , kWriteDelete = (1ULL << (2)) } |
| enum | { kNstat = 13 } |
| Size of statistics data (size of array used in GetStats()/ PutStats ). More... | |
| enum | { kIsOnHeap = 0x01000000 , kNotDeleted = 0x02000000 , kZombie = 0x04000000 , kInconsistent = 0x08000000 , kBitMask = 0x00ffffff } |
| enum | EBinErrorOpt { kNormal = 0 , kPoisson = 1 , kPoisson2 = 2 } |
| Enumeration specifying type of statistics for bin errors. More... | |
| enum | EDeprecatedStatusBits { kObjInCanvas = (1ULL << (3)) } |
| enum | EInconsistencyBits { kFullyConsistent = 0 , kDifferentLabels = (1ULL << (0)) , kDifferentBinLimits = (1ULL << (1)) , kDifferentAxisLimits = (1ULL << (2)) , kDifferentNumberOfBins = (1ULL << (3)) , kDifferentDimensions = (1ULL << (4)) } |
| Enumeration specifying inconsistencies between two histograms, in increasing severity. More... | |
| enum | EStatOverflows { kIgnore = 0 , kConsider = 1 , kNeutral = 2 } |
| Enumeration specifying the way to treat statoverflow. More... | |
| enum | EStatusBits { kNoStats = (1ULL << (9)) , kUserContour = (1ULL << (10)) , kLogX = (1ULL << (15)) , kIsZoomed = (1ULL << (16)) , kNoTitle = (1ULL << (17)) , kIsAverage = (1ULL << (18)) , kIsNotW = (1ULL << (19)) , kAutoBinPTwo = (1ULL << (20)) , kIsHighlight = (1ULL << (21)) } |
| TH1 status bits. More... | |
Public Member Functions | |
| TH1F () | |
| Constructor. | |
| TH1F (const char *name, const char *title, Int_t nbinsx, const Double_t *xbins) | |
| Create a 1-Dim histogram with variable bins of type float (see TH1::TH1 for explanation of parameters). | |
| TH1F (const char *name, const char *title, Int_t nbinsx, const Float_t *xbins) | |
| Create a 1-Dim histogram with variable bins of type float (see TH1::TH1 for explanation of parameters). | |
| TH1F (const char *name, const char *title, Int_t nbinsx, Double_t xlow, Double_t xup) | |
| Create a 1-Dim histogram with fix bins of type float (see TH1::TH1 for explanation of parameters). | |
| TH1F (const TH1F &h1f) | |
| Copy Constructor. | |
| TH1F (const TVectorF &v) | |
| Create a histogram from a TVectorF by default the histogram name is "TVectorF" and title = "". | |
| ~TH1F () override | |
| Destructor. | |
| void | AbstractMethod (const char *method) const |
| Call this function within a function that you don't want to define as purely virtual, in order not to force all users deriving from that class to implement that maybe (on their side) unused function; but at the same time, emit a run-time warning if they try to call it, telling that it is not implemented in the derived class: action must thus be taken on the user side to override it. | |
| virtual Bool_t | Add (const TH1 *h, const TH1 *h2, Double_t c1=1, Double_t c2=1) |
| Replace contents of this histogram by the addition of h1 and h2. | |
| virtual Bool_t | Add (const TH1 *h1, Double_t c1=1) |
| Performs the operation: this = this + c1*h1 If errors are defined (see TH1::Sumw2), errors are also recalculated. | |
| virtual Bool_t | Add (TF1 *h1, Double_t c1=1, Option_t *option="") |
| Performs the operation: this = this + c1*f1 if errors are defined (see TH1::Sumw2), errors are also recalculated. | |
| void | AddAt (Float_t c, Int_t i) |
| Add float c at position i. Check for out of bounds. | |
| void | AddBinContent (Int_t bin) override |
| Increment bin content by 1. | |
| void | AddBinContent (Int_t bin, Double_t w) override |
| Increment bin content by a weight w. | |
| void | Adopt (Int_t n, Float_t *array) |
| Adopt array arr into TArrayF, i.e. | |
| virtual Double_t | AndersonDarlingTest (const TH1 *h2, Double_t &advalue) const |
| Same function as above but returning also the test statistic value. | |
| virtual Double_t | AndersonDarlingTest (const TH1 *h2, Option_t *option="") const |
| Statistical test of compatibility in shape between this histogram and h2, using the Anderson-Darling 2 sample test. | |
| virtual void | AppendPad (Option_t *option="") |
| Append graphics object to current pad. | |
| Float_t | At (Int_t i) const |
| void | Browse (TBrowser *b) override |
| Browse the Histogram object. | |
| virtual Int_t | BufferEmpty (Int_t action=0) |
| Fill histogram with all entries in the buffer. | |
| virtual Bool_t | CanExtendAllAxes () const |
| Returns true if all axes are extendable. | |
| ULong_t | CheckedHash () |
| Check and record whether this class has a consistent Hash/RecursiveRemove setup (*) and then return the regular Hash value for this object. | |
| virtual Double_t | Chi2Test (const TH1 *h2, Option_t *option="UU", Double_t *res=nullptr) const |
| \( \chi^{2} \) test for comparing weighted and unweighted histograms. | |
| virtual Double_t | Chi2TestX (const TH1 *h2, Double_t &chi2, Int_t &ndf, Int_t &igood, Option_t *option="UU", Double_t *res=nullptr) const |
| The computation routine of the Chisquare test. | |
| virtual Double_t | Chisquare (TF1 *f1, Option_t *option="") const |
| Compute and return the chisquare of this histogram with respect to a function The chisquare is computed by weighting each histogram point by the bin error By default the full range of the histogram is used, unless TAxis::SetRange or TAxis::SetRangeUser was called before. | |
| virtual const char * | ClassName () const |
| Returns name of class to which the object belongs. | |
| void | Clear (Option_t *option="") override |
| Set name and title to empty strings (""). | |
| virtual void | ClearUnderflowAndOverflow () |
| Remove all the content from the underflow and overflow bins, without changing the number of entries After calling this method, every undeflow and overflow bins will have content 0.0 The Sumw2 is also cleared, since there is no more content in the bins. | |
| TObject * | Clone (const char *newname="") const override |
| Make a complete copy of the underlying object. | |
| Int_t | Compare (const TObject *obj) const override |
| Compare two TNamed objects. | |
| virtual Double_t | ComputeIntegral (Bool_t onlyPositive=false, Option_t *option="") |
| Compute integral (normalized cumulative sum of bins) w/o under/overflows The result is stored in fIntegral and used by the GetRandom functions. | |
| void | Copy (TArrayF &array) const |
| void | Copy (TAttFill &attfill) const |
| void | Copy (TAttLine &attline) const |
| void | Copy (TAttMarker &attmarker) const |
| void | Copy (TObject &hnew) const override |
| Copy this to newth1. | |
| virtual void | Delete (Option_t *option="") |
| Delete this object. | |
| virtual void | DirectoryAutoAdd (TDirectory *) |
| Callback to perform the automatic addition of the histogram to the given directory. | |
| Int_t | DistancetoLine (Int_t px, Int_t py, Double_t xp1, Double_t yp1, Double_t xp2, Double_t yp2) |
| Int_t | DistancetoPrimitive (Int_t px, Int_t py) override |
| Compute distance from point px,py to a line. | |
| virtual Bool_t | Divide (const TH1 *h1) |
| Divide this histogram by h1. | |
| virtual Bool_t | Divide (const TH1 *h1, const TH1 *h2, Double_t c1=1, Double_t c2=1, Option_t *option="") |
| Replace contents of this histogram by the division of h1 by h2. | |
| virtual Bool_t | Divide (TF1 *f1, Double_t c1=1) |
| Performs the operation: this = this/(c1*f1) if errors are defined (see TH1::Sumw2), errors are also recalculated. | |
| void | Draw (Option_t *option="") override |
| Draw this histogram with options. | |
| virtual void | DrawClass () const |
| Draw class inheritance tree of the class to which this object belongs. | |
| virtual TObject * | DrawClone (Option_t *option="") const |
| Draw a clone of this object in the current selected pad with: gROOT->SetSelectedPad(c1). | |
| virtual TH1 * | DrawCopy (Option_t *option="", const char *name_postfix="_copy") const |
| Copy this histogram and Draw in the current pad. | |
| virtual TH1 * | DrawNormalized (Option_t *option="", Double_t norm=1) const |
| Draw a normalized copy of this histogram. | |
| virtual void | DrawPanel () |
| Display a panel with all histogram drawing options. | |
| virtual void | Dump () const |
| Dump contents of object on stdout. | |
| virtual void | Error (const char *method, const char *msgfmt,...) const |
| Issue error message. | |
| virtual void | Eval (TF1 *f1, Option_t *option="") |
| Evaluate function f1 at the center of bins of this histogram. | |
| virtual void | Execute (const char *method, const char *params, Int_t *error=nullptr) |
| Execute method on this object with the given parameter string, e.g. | |
| virtual void | Execute (TMethod *method, TObjArray *params, Int_t *error=nullptr) |
| Execute method on this object with parameters stored in the TObjArray. | |
| void | ExecuteEvent (Int_t event, Int_t px, Int_t py) override |
| Execute action corresponding to one event. | |
| virtual void | ExtendAxis (Double_t x, TAxis *axis) |
| Histogram is resized along axis such that x is in the axis range. | |
| virtual void | Fatal (const char *method, const char *msgfmt,...) const |
| Issue fatal error message. | |
| virtual TH1 * | FFT (TH1 *h_output, Option_t *option) |
| This function allows to do discrete Fourier transforms of TH1 and TH2. | |
| virtual Int_t | Fill (const char *name, Double_t w) |
| Increment bin with namex with a weight w. | |
| virtual Int_t | Fill (Double_t x) |
| Increment bin with abscissa X by 1. | |
| virtual Int_t | Fill (Double_t x, Double_t w) |
| Increment bin with abscissa X with a weight w. | |
| virtual void | FillBuffer (char *&buffer) |
| Encode TNamed into output buffer. | |
| virtual void | FillN (Int_t ntimes, const Double_t *x, const Double_t *w, Int_t stride=1) |
| Fill this histogram with an array x and weights w. | |
| virtual void | FillN (Int_t, const Double_t *, const Double_t *, const Double_t *, Int_t) |
| void | FillRandom (const char *fname, Int_t ntimes=5000, TRandom *rng=nullptr) |
| Fill histogram following distribution in function fname. | |
| virtual void | FillRandom (TF1 *f1, Int_t ntimes=5000, TRandom *rng=nullptr) |
| virtual void | FillRandom (TH1 *h, Int_t ntimes=5000, TRandom *rng=nullptr) |
| Fill histogram following distribution in histogram h. | |
| virtual Int_t | FindBin (Double_t x, Double_t y=0, Double_t z=0) |
| Return Global bin number corresponding to x,y,z. | |
| virtual Int_t | FindFirstBinAbove (Double_t threshold=0, Int_t axis=1, Int_t firstBin=1, Int_t lastBin=-1) const |
| Find first bin with content > threshold for axis (1=x, 2=y, 3=z) if no bins with content > threshold is found the function returns -1. | |
| virtual Int_t | FindFixBin (Double_t x, Double_t y=0, Double_t z=0) const |
| Return Global bin number corresponding to x,y,z. | |
| virtual Int_t | FindLastBinAbove (Double_t threshold=0, Int_t axis=1, Int_t firstBin=1, Int_t lastBin=-1) const |
| Find last bin with content > threshold for axis (1=x, 2=y, 3=z) if no bins with content > threshold is found the function returns -1. | |
| TObject * | FindObject (const char *name) const override |
| Search object named name in the list of functions. | |
| TObject * | FindObject (const TObject *obj) const override |
| Search object obj in the list of functions. | |
| virtual TFitResultPtr | Fit (const char *formula, Option_t *option="", Option_t *goption="", Double_t xmin=0, Double_t xmax=0) |
| Fit histogram with function fname. | |
| virtual TFitResultPtr | Fit (TF1 *f1, Option_t *option="", Option_t *goption="", Double_t xmin=0, Double_t xmax=0) |
| Fit histogram with the function pointer f1. | |
| virtual void | FitPanel () |
| Display a panel with all histogram fit options. | |
| Float_t * | GetArray () |
| const Float_t * | GetArray () const |
| TH1 * | GetAsymmetry (TH1 *h2, Double_t c2=1, Double_t dc2=0) |
| Return a histogram containing the asymmetry of this histogram with h2, where the asymmetry is defined as: | |
| Double_t | GetAt (Int_t i) const override |
| virtual Color_t | GetAxisColor (Option_t *axis="X") const |
| Return the number of divisions for "axis". | |
| virtual Float_t | GetBarOffset () const |
| virtual Float_t | GetBarWidth () const |
| virtual Int_t | GetBin (Int_t binx, Int_t biny=0, Int_t binz=0) const |
| Return Global bin number corresponding to binx,y,z. | |
| virtual Double_t | GetBinCenter (Int_t bin) const |
| Return bin center for 1D histogram. | |
| virtual Double_t | GetBinContent (Int_t bin) const |
| Return content of bin number bin. | |
| virtual Double_t | GetBinContent (Int_t bin, Int_t) const |
| virtual Double_t | GetBinContent (Int_t bin, Int_t, Int_t) const |
| virtual Double_t | GetBinError (Int_t bin) const |
| Return value of error associated to bin number bin. | |
| virtual Double_t | GetBinError (Int_t binx, Int_t biny) const |
| virtual Double_t | GetBinError (Int_t binx, Int_t biny, Int_t binz) const |
| virtual Double_t | GetBinErrorLow (Int_t bin) const |
| Return lower error associated to bin number bin. | |
| virtual EBinErrorOpt | GetBinErrorOption () const |
| virtual Double_t | GetBinErrorUp (Int_t bin) const |
| Return upper error associated to bin number bin. | |
| virtual Double_t | GetBinLowEdge (Int_t bin) const |
| Return bin lower edge for 1D histogram. | |
| virtual Double_t | GetBinWidth (Int_t bin) const |
| Return bin width for 1D histogram. | |
| virtual Double_t | GetBinWithContent (Double_t c, Int_t &binx, Int_t firstx=0, Int_t lastx=0, Double_t maxdiff=0) const |
| Compute first binx in the range [firstx,lastx] for which diff = abs(bin_content-c) <= maxdiff. | |
| virtual void | GetBinXYZ (Int_t binglobal, Int_t &binx, Int_t &biny, Int_t &binz) const |
| Return binx, biny, binz corresponding to the global bin number globalbin see TH1::GetBin function above. | |
| const Double_t * | GetBuffer () const |
| Int_t | GetBufferLength () const |
| Int_t | GetBufferSize () const |
| virtual Double_t | GetCellContent (Int_t binx, Int_t biny) const |
| virtual Double_t | GetCellError (Int_t binx, Int_t biny) const |
| virtual void | GetCenter (Double_t *center) const |
| Fill array with center of bins for 1D histogram Better to use h1.GetXaxis()->GetCenter(center). | |
| virtual Int_t | GetContour (Double_t *levels=nullptr) |
| Return contour values into array levels if pointer levels is non zero. | |
| virtual Double_t | GetContourLevel (Int_t level) const |
| Return value of contour number level. | |
| virtual Double_t | GetContourLevelPad (Int_t level) const |
| Return the value of contour number "level" in Pad coordinates. | |
| TH1 * | GetCumulative (Bool_t forward=kTRUE, const char *suffix="_cumulative") const |
| Return a pointer to a histogram containing the cumulative content. | |
| virtual Int_t | GetDimension () const |
| TDirectory * | GetDirectory () const |
| virtual Option_t * | GetDrawOption () const |
| Get option used by the graphics system to draw this object. | |
| virtual Double_t | GetEffectiveEntries () const |
| Number of effective entries of the histogram. | |
| virtual Double_t | GetEntries () const |
| Return the current number of entries. | |
| virtual Color_t | GetFillColor () const |
| Return the fill area color. | |
| virtual Style_t | GetFillStyle () const |
| Return the fill area style. | |
| virtual TF1 * | GetFunction (const char *name) const |
| Return pointer to function with name. | |
| virtual const char * | GetIconName () const |
| Returns mime type name of object. | |
| virtual Double_t * | GetIntegral () |
| Return a pointer to the array of bins integral. | |
| virtual Double_t | GetKurtosis (Int_t axis=1) const |
| virtual Color_t | GetLabelColor (Option_t *axis="X") const |
| Return the "axis" label color. | |
| virtual Style_t | GetLabelFont (Option_t *axis="X") const |
| Return the "axis" label font. | |
| virtual Float_t | GetLabelOffset (Option_t *axis="X") const |
| Return the "axis" label offset. | |
| virtual Float_t | GetLabelSize (Option_t *axis="X") const |
| Return the "axis" label size. | |
| virtual Color_t | GetLineColor () const |
| Return the line color. | |
| virtual Style_t | GetLineStyle () const |
| Return the line style. | |
| virtual Width_t | GetLineWidth () const |
| Return the line width. | |
| TList * | GetListOfFunctions () const |
| virtual void | GetLowEdge (Double_t *edge) const |
| Fill array with low edge of bins for 1D histogram Better to use h1.GetXaxis()->GetLowEdge(edge). | |
| virtual Color_t | GetMarkerColor () const |
| Return the marker color. | |
| virtual Size_t | GetMarkerSize () const |
| Return the marker size. | |
| virtual Style_t | GetMarkerStyle () const |
| Return the marker style. | |
| virtual Double_t | GetMaximum (Double_t maxval=FLT_MAX) const |
| Return maximum value smaller than maxval of bins in the range, unless the value has been overridden by TH1::SetMaximum, in which case it returns that value. | |
| virtual Int_t | GetMaximumBin () const |
| Return location of bin with maximum value in the range. | |
| virtual Int_t | GetMaximumBin (Int_t &locmax, Int_t &locmay, Int_t &locmaz) const |
| Return location of bin with maximum value in the range. | |
| virtual Double_t | GetMaximumStored () const |
| virtual Double_t | GetMean (Int_t axis=1) const |
| For axis = 1,2 or 3 returns the mean value of the histogram along X,Y or Z axis. | |
| virtual Double_t | GetMeanError (Int_t axis=1) const |
| Return standard error of mean of this histogram along the X axis. | |
| virtual Double_t | GetMinimum (Double_t minval=-FLT_MAX) const |
| Return minimum value larger than minval of bins in the range, unless the value has been overridden by TH1::SetMinimum, in which case it returns that value. | |
| virtual void | GetMinimumAndMaximum (Double_t &min, Double_t &max) const |
| Retrieve the minimum and maximum values in the histogram. | |
| virtual Int_t | GetMinimumBin () const |
| Return location of bin with minimum value in the range. | |
| virtual Int_t | GetMinimumBin (Int_t &locmix, Int_t &locmiy, Int_t &locmiz) const |
| Return location of bin with minimum value in the range. | |
| virtual Double_t | GetMinimumStored () const |
| const char * | GetName () const override |
| Returns name of object. | |
| virtual Int_t | GetNbinsX () const |
| virtual Int_t | GetNbinsY () const |
| virtual Int_t | GetNbinsZ () const |
| virtual Int_t | GetNcells () const |
| virtual Int_t | GetNdivisions (Option_t *axis="X") const |
| Return the number of divisions for "axis". | |
| virtual Double_t | GetNormFactor () const |
| char * | GetObjectInfo (Int_t px, Int_t py) const override |
| Redefines TObject::GetObjectInfo. | |
| Option_t * | GetOption () const override |
| TVirtualHistPainter * | GetPainter (Option_t *option="") |
| Return pointer to painter. | |
| virtual Int_t | GetQuantiles (Int_t n, Double_t *xp, const Double_t *p=nullptr) |
| Compute Quantiles for this histogram. | |
| virtual Double_t | GetRandom (TRandom *rng=nullptr, Option_t *option="") const |
| Return a random number distributed according the histogram bin contents. | |
| Double_t | GetRMS (Int_t axis=1) const |
| This function returns the Standard Deviation (Sigma) of the distribution not the Root Mean Square (RMS). | |
| Double_t | GetRMSError (Int_t axis=1) const |
| Int_t | GetSize () const |
| virtual Double_t | GetSkewness (Int_t axis=1) const |
| EStatOverflows | GetStatOverflows () const |
| Get the behaviour adopted by the object about the statoverflows. See EStatOverflows for more information. | |
| virtual void | GetStats (Double_t *stats) const |
| fill the array stats from the contents of this histogram The array stats must be correctly dimensioned in the calling program. | |
| virtual Double_t | GetStdDev (Int_t axis=1) const |
| Returns the Standard Deviation (Sigma). | |
| virtual Double_t | GetStdDevError (Int_t axis=1) const |
| Return error of standard deviation estimation for Normal distribution. | |
| Stat_t | GetSum () const |
| Double_t | GetSumOfAllWeights (const bool includeOverflow, Double_t *sumWeightSquare=nullptr) const |
| Return the sum of all weights and optionally also the sum of weight squares. | |
| virtual Double_t | GetSumOfWeights () const |
| Return the sum of weights across all bins excluding under/overflows. | |
| virtual TArrayD * | GetSumw2 () |
| virtual const TArrayD * | GetSumw2 () const |
| virtual Int_t | GetSumw2N () const |
| virtual Float_t | GetTickLength (Option_t *axis="X") const |
| Return the "axis" tick length. | |
| const char * | GetTitle () const override |
| Returns title of object. | |
| virtual Style_t | GetTitleFont (Option_t *axis="X") const |
| Return the "axis" title font. | |
| virtual Float_t | GetTitleOffset (Option_t *axis="X") const |
| Return the "axis" title offset. | |
| virtual Float_t | GetTitleSize (Option_t *axis="X") const |
| Return the "axis" title size. | |
| virtual UInt_t | GetUniqueID () const |
| Return the unique object id. | |
| TAxis * | GetXaxis () |
| const TAxis * | GetXaxis () const |
| TAxis * | GetYaxis () |
| const TAxis * | GetYaxis () const |
| TAxis * | GetZaxis () |
| const TAxis * | GetZaxis () const |
| virtual Bool_t | HandleTimer (TTimer *timer) |
| Execute action in response of a timer timing out. | |
| ULong_t | Hash () const override |
| Return hash value for this object. | |
| Bool_t | HasInconsistentHash () const |
| Return true is the type of this object is known to have an inconsistent setup for Hash and RecursiveRemove (i.e. | |
| virtual void | Info (const char *method, const char *msgfmt,...) const |
| Issue info message. | |
| virtual Bool_t | InheritsFrom (const char *classname) const |
| Returns kTRUE if object inherits from class "classname". | |
| virtual Bool_t | InheritsFrom (const TClass *cl) const |
| Returns kTRUE if object inherits from TClass cl. | |
| virtual void | Inspect () const |
| Dump contents of this object in a graphics canvas. | |
| virtual Double_t | Integral (Int_t binx1, Int_t binx2, Option_t *option="") const |
| Return integral of bin contents in range [binx1,binx2]. | |
| virtual Double_t | Integral (Option_t *option="") const |
| Return integral of bin contents. | |
| virtual Double_t | IntegralAndError (Int_t binx1, Int_t binx2, Double_t &err, Option_t *option="") const |
| Return integral of bin contents in range [binx1,binx2] and its error. | |
| virtual Double_t | Interpolate (Double_t x) const |
| Given a point x, approximates the value via linear interpolation based on the two nearest bin centers. | |
| virtual Double_t | Interpolate (Double_t x, Double_t y) const |
| 2d Interpolation. Not yet implemented. | |
| virtual Double_t | Interpolate (Double_t x, Double_t y, Double_t z) const |
| 3d Interpolation. Not yet implemented. | |
| void | InvertBit (UInt_t f) |
| TClass * | IsA () const override |
| Bool_t | IsBinOverflow (Int_t bin, Int_t axis=0) const |
| Return true if the bin is overflow. | |
| Bool_t | IsBinUnderflow (Int_t bin, Int_t axis=0) const |
| Return true if the bin is underflow. | |
| Bool_t | IsDestructed () const |
| IsDestructed. | |
| virtual Bool_t | IsEqual (const TObject *obj) const |
| Default equal comparison (objects are equal if they have the same address in memory). | |
| virtual Bool_t | IsFolder () const |
| Returns kTRUE in case object contains browsable objects (like containers or lists of other objects). | |
| virtual Bool_t | IsHighlight () const |
| Bool_t | IsOnHeap () const |
| Bool_t | IsSortable () const override |
| virtual Bool_t | IsTransparent () const |
| Bool_t | IsZombie () const |
| virtual Double_t | KolmogorovTest (const TH1 *h2, Option_t *option="") const |
| Statistical test of compatibility in shape between this histogram and h2, using Kolmogorov test. | |
| virtual void | LabelsDeflate (Option_t *axis="X") |
| Reduce the number of bins for the axis passed in the option to the number of bins having a label. | |
| virtual void | LabelsInflate (Option_t *axis="X") |
| Double the number of bins for axis. | |
| virtual void | LabelsOption (Option_t *option="h", Option_t *axis="X") |
| Sort bins with labels or set option(s) to draw axis with labels. | |
| void | ls (Option_t *option="") const override |
| List TNamed name and title. | |
| void | MayNotUse (const char *method) const |
| Use this method to signal that a method (defined in a base class) may not be called in a derived class (in principle against good design since a child class should not provide less functionality than its parent, however, sometimes it is necessary). | |
| virtual Long64_t | Merge (TCollection *list) |
| Long64_t | Merge (TCollection *list, Option_t *option) |
| Add all histograms in the collection to this histogram. | |
| virtual void | Modify () |
| virtual void | Modify () |
| virtual void | Modify () |
| virtual void | ModifyOn (TVirtualPad &pad) |
| virtual void | ModifyOn (TVirtualPad &pad) |
| virtual void | ModifyOn (TVirtualPad &pad) |
| virtual Bool_t | Multiply (const TH1 *h1) |
| Multiply this histogram by h1. | |
| virtual Bool_t | Multiply (const TH1 *h1, const TH1 *h2, Double_t c1=1, Double_t c2=1, Option_t *option="") |
| Replace contents of this histogram by multiplication of h1 by h2. | |
| virtual Bool_t | Multiply (TF1 *f1, Double_t c1=1) |
| Performs the operation: | |
| virtual void | Normalize (Option_t *option="") |
| Normalize a histogram to its integral or to its maximum. | |
| virtual Bool_t | Notify () |
| This method must be overridden to handle object notification (the base implementation is no-op). | |
| void | Obsolete (const char *method, const char *asOfVers, const char *removedFromVers) const |
| Use this method to declare a method obsolete. | |
| void | operator delete (void *, size_t) |
| Operator delete for sized deallocation. | |
| void | operator delete (void *ptr) |
| Operator delete. | |
| void | operator delete (void *ptr, void *vp) |
| Only called by placement new when throwing an exception. | |
| void | operator delete[] (void *, size_t) |
| Operator delete [] for sized deallocation. | |
| void | operator delete[] (void *ptr) |
| Operator delete []. | |
| void | operator delete[] (void *ptr, void *vp) |
| Only called by placement new[] when throwing an exception. | |
| void * | operator new (size_t sz) |
| void * | operator new (size_t sz, void *vp) |
| void * | operator new[] (size_t sz) |
| void * | operator new[] (size_t sz, void *vp) |
| TH1F & | operator= (const TH1F &h1) |
| Operator =. | |
| Float_t & | operator[] (Int_t i) |
| Float_t | operator[] (Int_t i) const |
| void | Paint (Option_t *option="") override |
| Control routine to paint any kind of histograms. | |
| virtual void | Pop () |
| Pop on object drawn in a pad to the top of the display list. | |
| void | Print (Option_t *option="") const override |
| Print some global quantities for this histogram. | |
| virtual void | PutStats (Double_t *stats) |
| Replace current statistics with the values in array stats. | |
| virtual Int_t | Read (const char *name) |
| Read contents of object with specified name from the current directory. | |
| virtual TH1 * | Rebin (Int_t ngroup=2, const char *newname="", const Double_t *xbins=nullptr) |
| Rebin this histogram. | |
| virtual void | RebinAxis (Double_t x, TAxis *axis) |
| virtual TH1 * | RebinX (Int_t ngroup=2, const char *newname="") |
| virtual void | Rebuild (Option_t *option="") |
| Using the current bin info, recompute the arrays for contents and errors. | |
| void | RecursiveRemove (TObject *obj) override |
| Recursively remove object from the list of functions. | |
| void | Reset () |
| void | Reset (Float_t val) |
| void | Reset (Option_t *option="") override |
| Reset. | |
| virtual void | ResetAttFill (Option_t *option="") |
| virtual void | ResetAttLine (Option_t *option="") |
| virtual void | ResetAttMarker (Option_t *toption="") |
| void | ResetBit (UInt_t f) |
| virtual void | ResetStats () |
| Reset the statistics including the number of entries and replace with values calculated from bin content. | |
| void | SaveAs (const char *filename="hist", Option_t *option="") const override |
| Save the histogram as .csv, .tsv or .txt. | |
| virtual void | SaveFillAttributes (std::ostream &out, const char *name, Int_t coldef=1, Int_t stydef=1001) |
| virtual void | SaveLineAttributes (std::ostream &out, const char *name, Int_t coldef=1, Int_t stydef=1, Int_t widdef=1) |
| virtual void | SaveMarkerAttributes (std::ostream &out, const char *name, Int_t coldef=1, Int_t stydef=1, Int_t sizdef=1) |
| void | SavePrimitive (std::ostream &out, Option_t *option="") override |
| Save primitive as a C++ statement(s) on output stream out. | |
| virtual void | Scale (Double_t c1=1, Option_t *option="") |
| Multiply this histogram by a constant c1. | |
| void | Set (Int_t n) override |
| Set size of this array to n floats. | |
| void | Set (Int_t n, const Float_t *array) |
| Set size of this array to n floats and set the contents. | |
| void | SetAt (Double_t v, Int_t i) override |
| virtual void | SetAxisColor (Color_t color=1, Option_t *axis="X") |
| Set color to draw the axis line and tick marks. | |
| virtual void | SetAxisRange (Double_t xmin, Double_t xmax, Option_t *axis="X") |
| Set the "axis" range. | |
| virtual void | SetBarOffset (Float_t offset=0.25) |
| Set the bar offset as fraction of the bin width for drawing mode "B". | |
| virtual void | SetBarWidth (Float_t width=0.5) |
| Set the width of bars as fraction of the bin width for drawing mode "B". | |
| virtual void | SetBinContent (Int_t bin, Double_t content) |
| Set bin content see convention for numbering bins in TH1::GetBin In case the bin number is greater than the number of bins and the timedisplay option is set or CanExtendAllAxes(), the number of bins is automatically doubled to accommodate the new bin. | |
| virtual void | SetBinContent (Int_t bin, Int_t, Double_t content) |
| virtual void | SetBinContent (Int_t bin, Int_t, Int_t, Double_t content) |
| virtual void | SetBinError (Int_t bin, Double_t error) |
| Set the bin Error Note that this resets the bin eror option to be of Normal Type and for the non-empty bin the bin error is set by default to the square root of their content. | |
| virtual void | SetBinError (Int_t binx, Int_t biny, Double_t error) |
| See convention for numbering bins in TH1::GetBin. | |
| virtual void | SetBinError (Int_t binx, Int_t biny, Int_t binz, Double_t error) |
| See convention for numbering bins in TH1::GetBin. | |
| virtual void | SetBinErrorOption (EBinErrorOpt type) |
| virtual void | SetBins (Int_t nx, const Double_t *xBins) |
| Redefine x axis parameters with variable bin sizes. | |
| virtual void | SetBins (Int_t nx, const Double_t *xBins, Int_t ny, const Double_t *yBins) |
| Redefine x and y axis parameters with variable bin sizes. | |
| virtual void | SetBins (Int_t nx, const Double_t *xBins, Int_t ny, const Double_t *yBins, Int_t nz, const Double_t *zBins) |
| Redefine x, y and z axis parameters with variable bin sizes. | |
| virtual void | SetBins (Int_t nx, Double_t xmin, Double_t xmax) |
| Redefine x axis parameters. | |
| virtual void | SetBins (Int_t nx, Double_t xmin, Double_t xmax, Int_t ny, Double_t ymin, Double_t ymax) |
| Redefine x and y axis parameters. | |
| virtual void | SetBins (Int_t nx, Double_t xmin, Double_t xmax, Int_t ny, Double_t ymin, Double_t ymax, Int_t nz, Double_t zmin, Double_t zmax) |
| Redefine x, y and z axis parameters. | |
| void | SetBinsLength (Int_t n=-1) override |
| Set total number of bins including under/overflow Reallocate bin contents array. | |
| void | SetBit (UInt_t f) |
| void | SetBit (UInt_t f, Bool_t set) |
| Set or unset the user status bits as specified in f. | |
| virtual void | SetBuffer (Int_t bufsize, Option_t *option="") |
| Set the maximum number of entries to be kept in the buffer. | |
| virtual UInt_t | SetCanExtend (UInt_t extendBitMask) |
| Make the histogram axes extendable / not extendable according to the bit mask returns the previous bit mask specifying which axes are extendable. | |
| virtual void | SetCellContent (Int_t binx, Int_t biny, Double_t content) |
| virtual void | SetCellError (Int_t binx, Int_t biny, Double_t content) |
| virtual void | SetColors (Color_t linecolor=-1, Color_t markercolor=-1, Color_t fillcolor=-1) |
| Shortcut to set the three histogram colors with a single call. | |
| virtual void | SetContent (const Double_t *content) |
| Replace bin contents by the contents of array content. | |
| virtual void | SetContour (Int_t nlevels, const Double_t *levels=nullptr) |
| Set the number and values of contour levels. | |
| virtual void | SetContourLevel (Int_t level, Double_t value) |
| Set value for one contour level. | |
| virtual void | SetDirectory (TDirectory *dir) |
| By default, when a histogram is created, it is added to the list of histogram objects in the current directory in memory. | |
| virtual void | SetDrawOption (Option_t *option="") |
| Set drawing option for object. | |
| virtual void | SetEntries (Double_t n) |
| virtual void | SetError (const Double_t *error) |
| Replace bin errors by values in array error. | |
| virtual void | SetFillAttributes () |
| virtual void | SetFillColor (Color_t fcolor) |
| Set the fill area color. | |
| void | SetFillColor (TColorNumber) |
| virtual void | SetFillColorAlpha (Color_t fcolor, Float_t falpha) |
| virtual void | SetFillStyle (Style_t fstyle) |
| Set the fill area style. | |
| virtual void | SetHighlight (Bool_t set=kTRUE) |
| Set highlight (enable/disable) mode for the histogram by default highlight mode is disable. | |
| virtual void | SetLabelColor (Color_t color=1, Option_t *axis="X") |
| Set axis labels color. | |
| virtual void | SetLabelFont (Style_t font=62, Option_t *axis="X") |
| Set font number used to draw axis labels. | |
| virtual void | SetLabelOffset (Float_t offset=0.005, Option_t *axis="X") |
| Set offset between axis and axis' labels. | |
| virtual void | SetLabelSize (Float_t size=0.02, Option_t *axis="X") |
| Set size of axis' labels. | |
| virtual void | SetLineAttributes () |
| virtual void | SetLineColor (Color_t lcolor) |
| Set the line color. | |
| void | SetLineColor (TColorNumber lcolor) |
| virtual void | SetLineColorAlpha (Color_t lcolor, Float_t lalpha) |
| virtual void | SetLineStyle (Style_t lstyle) |
| Set the line style. | |
| virtual void | SetLineWidth (Width_t lwidth) |
| Set the line width. | |
| virtual void | SetMarkerAttributes () |
| virtual void | SetMarkerColor (Color_t mcolor=1) |
| Set the marker color. | |
| void | SetMarkerColor (TColorNumber lcolor) |
| virtual void | SetMarkerColorAlpha (Color_t mcolor, Float_t malpha) |
| virtual void | SetMarkerSize (Size_t msize=1) |
| Set the marker size. | |
| virtual void | SetMarkerStyle (Style_t mstyle=1) |
| Set the marker style. | |
| virtual void | SetMaximum (Double_t maximum=-1111) |
| virtual void | SetMinimum (Double_t minimum=-1111) |
| void | SetName (const char *name) override |
| Change the name of this histogram. | |
| void | SetNameTitle (const char *name, const char *title) override |
| Change the name and title of this histogram. | |
| virtual void | SetNdivisions (Int_t n=510, Option_t *axis="X") |
| Set the number of divisions to draw an axis. | |
| virtual void | SetNormFactor (Double_t factor=1) |
| virtual void | SetOption (Option_t *option=" ") |
| void | SetStatOverflows (EStatOverflows statOverflows) |
| See GetStatOverflows for more information. | |
| virtual void | SetStats (Bool_t stats=kTRUE) |
| Set statistics option on/off. | |
| virtual void | SetTickLength (Float_t length=0.02, Option_t *axis="X") |
| Set the axis' tick marks length. | |
| void | SetTitle (const char *title) override |
| Change/set the title. | |
| virtual void | SetTitleFont (Style_t font=62, Option_t *axis="X") |
| Set the axis' title font. | |
| virtual void | SetTitleOffset (Float_t offset=1, Option_t *axis="X") |
| Specify a parameter offset to control the distance between the axis and the axis' title. | |
| virtual void | SetTitleSize (Float_t size=0.02, Option_t *axis="X") |
| Set the axis' title size. | |
| virtual void | SetUniqueID (UInt_t uid) |
| Set the unique object id. | |
| virtual void | SetXTitle (const char *title) |
| virtual void | SetYTitle (const char *title) |
| virtual void | SetZTitle (const char *title) |
| virtual TH1 * | ShowBackground (Int_t niter=20, Option_t *option="same") |
| This function calculates the background spectrum in this histogram. | |
| virtual Int_t | ShowPeaks (Double_t sigma=2, Option_t *option="", Double_t threshold=0.05) |
| Interface to TSpectrum::Search. | |
| std::size_t | size () const |
| virtual Int_t | Sizeof () const |
| Return size of the TNamed part of the TObject. | |
| virtual void | Smooth (Int_t ntimes=1, Option_t *option="") |
| Smooth bin contents of this histogram. | |
| void | Streamer (TBuffer &) override |
| Stream a class object. | |
| void | StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b) |
| virtual void | Sumw2 (Bool_t flag=kTRUE) |
| Create structure to store sum of squares of weights. | |
| virtual void | SysError (const char *method, const char *msgfmt,...) const |
| Issue system error message. | |
| Bool_t | TestBit (UInt_t f) const |
| Int_t | TestBits (UInt_t f) const |
| void | UseCurrentStyle () override |
| Copy current attributes from/to current style. | |
| virtual void | Warning (const char *method, const char *msgfmt,...) const |
| Issue warning message. | |
| virtual Int_t | Write (const char *name=nullptr, Int_t option=0, Int_t bufsize=0) |
| Write this object to the current directory. | |
| virtual Int_t | Write (const char *name=nullptr, Int_t option=0, Int_t bufsize=0) const |
| Write this object to the current directory. | |
Static Public Member Functions | |
| static void | AddDirectory (Bool_t add=kTRUE) |
| Sets the flag controlling the automatic add of histograms in memory. | |
| static Bool_t | AddDirectoryStatus () |
| Check whether TH1-derived classes should register themselves to the current gDirectory. | |
| static Int_t | CheckConsistency (const TH1 *h1, const TH1 *h2) |
| Check histogram compatibility. | |
| static TClass * | Class () |
| static const char * | Class_Name () |
| static constexpr Version_t | Class_Version () |
| static const char * | DeclFileName () |
| static Int_t | FitOptionsMake (Option_t *option, Foption_t &Foption) |
| Decode string choptin and fill fitOption structure. | |
| static Int_t | GetDefaultBufferSize () |
| Static function return the default buffer size for automatic histograms the parameter fgBufferSize may be changed via SetDefaultBufferSize. | |
| static Bool_t | GetDefaultSumw2 () |
| Return kTRUE if TH1::Sumw2 must be called when creating new histograms. | |
| static Longptr_t | GetDtorOnly () |
| Return destructor only flag. | |
| static Width_t | GetMarkerLineWidth (Style_t style) |
| static Style_t | GetMarkerStyleBase (Style_t style) |
| static Bool_t | GetObjectStat () |
| Get status of object stat flag. | |
| static TArray * | ReadArray (TBuffer &b, const TClass *clReq) |
| Read TArray object from buffer. | |
| static void | SavePrimitiveFunctions (std::ostream &out, const char *varname, TList *lst) |
| Save list of functions Also can be used by TGraph classes. | |
| static void | SetDefaultBufferSize (Int_t bufsize=1000) |
| Static function to set the default buffer size for automatic histograms. | |
| static void | SetDefaultSumw2 (Bool_t sumw2=kTRUE) |
| When this static function is called with sumw2=kTRUE, all new histograms will automatically activate the storage of the sum of squares of errors, ie TH1::Sumw2 is automatically called. | |
| static void | SetDtorOnly (void *obj) |
| Set destructor only flag. | |
| static void | SetObjectStat (Bool_t stat) |
| Turn on/off tracking of objects in the TObjectTable. | |
| static void | SmoothArray (Int_t NN, Double_t *XX, Int_t ntimes=1) |
| Smooth array xx, translation of Hbook routine hsmoof.F. | |
| static void | StatOverflows (Bool_t flag=kTRUE) |
| if flag=kTRUE, underflows and overflows are used by the Fill functions in the computation of statistics (mean value, StdDev). | |
| static TH1 * | TransformHisto (TVirtualFFT *fft, TH1 *h_output, Option_t *option) |
| For a given transform (first parameter), fills the histogram (second parameter) with the transform output data, specified in the third parameter If the 2nd parameter h_output is empty, a new histogram (TH1D or TH2D) is created and the user is responsible for deleting it. | |
| static void | WriteArray (TBuffer &b, const TArray *a) |
| Write TArray object to buffer. | |
Public Attributes | |
| Float_t * | fArray |
| Int_t | fN |
Protected Types | |
| enum | { kOnlyPrepStep = (1ULL << (3)) } |
Protected Member Functions | |
| virtual Int_t | AutoP2FindLimits (Double_t min, Double_t max) |
| Buffer-based estimate of the histogram range using the power of 2 algorithm. | |
| Int_t | AxisChoice (Option_t *axis) const |
| Choose an axis according to "axis". | |
| Bool_t | BoundsOk (const char *where, Int_t at) const |
| virtual Int_t | BufferFill (Double_t x, Double_t w) |
| accumulate arguments in buffer. | |
| virtual void | DoError (int level, const char *location, const char *fmt, va_list va) const |
| Interface to ErrorHandler (protected). | |
| virtual void | DoFillN (Int_t ntimes, const Double_t *x, const Double_t *w, Int_t stride=1) |
| Internal method to fill histogram content from a vector called directly by TH1::BufferEmpty. | |
| virtual Double_t | DoIntegral (Int_t ix1, Int_t ix2, Int_t iy1, Int_t iy2, Int_t iz1, Int_t iz2, Double_t &err, Option_t *opt, Bool_t doerr=kFALSE) const |
| Internal function compute integral and optionally the error between the limits specified by the bin number values working for all histograms (1D, 2D and 3D). | |
| virtual Bool_t | FindNewAxisLimits (const TAxis *axis, const Double_t point, Double_t &newMin, Double_t &newMax) |
| finds new limits for the axis so that point is within the range and the limits are compatible with the previous ones (see TH1::Merge). | |
| UInt_t | GetAxisLabelStatus () const |
| Internal function used in TH1::Fill to see which axis is full alphanumeric, i.e. | |
| virtual Double_t | GetBinErrorSqUnchecked (Int_t bin) const |
| Bool_t | GetStatOverflowsBehaviour () const |
| Bool_t | IsEmpty () const |
| Check if a histogram is empty (this is a protected method used mainly by TH1Merger ). | |
| int | LoggedInconsistency (const char *name, const TH1 *h1, const TH1 *h2, bool useMerge=false) const |
| void | MakeZombie () |
| Bool_t | OutOfBoundsError (const char *where, Int_t i) const |
| Generate an out-of-bounds error. Always returns false. | |
| TString | ProvideSaveName (Option_t *option, Bool_t testfdir=kFALSE) |
| Provide variable name for histogram for saving as primitive Histogram pointer has by default the histogram name with an incremental suffix. | |
| Double_t | RetrieveBinContent (Int_t bin) const override |
| Raw retrieval of bin content on internal data structure see convention for numbering bins in TH1::GetBin. | |
| virtual void | SavePrimitiveHelp (std::ostream &out, const char *hname, Option_t *option="") |
| Helper function for the SavePrimitive functions from TH1 or classes derived from TH1, eg TProfile, TProfile2D. | |
| void | SavePrimitiveNameTitle (std::ostream &out, const char *variable_name) |
| Save object name and title into the output stream "out". | |
| void | UpdateBinContent (Int_t bin, Double_t content) override |
| Raw update of bin content on internal data structure see convention for numbering bins in TH1::GetBin. | |
Static Protected Member Functions | |
| static Int_t | AutoP2GetBins (Int_t n) |
| Auxiliary function to get the next power of 2 integer value larger then n. | |
| static Double_t | AutoP2GetPower2 (Double_t x, Bool_t next=kTRUE) |
| Auxiliary function to get the power of 2 next (larger) or previous (smaller) a given x. | |
| static bool | CheckAxisLimits (const TAxis *a1, const TAxis *a2) |
| Check that the axis limits of the histograms are the same. | |
| static bool | CheckBinLabels (const TAxis *a1, const TAxis *a2) |
| Check that axis have same labels. | |
| static bool | CheckBinLimits (const TAxis *a1, const TAxis *a2) |
| Check bin limits. | |
| static bool | CheckConsistentSubAxes (const TAxis *a1, Int_t firstBin1, Int_t lastBin1, const TAxis *a2, Int_t firstBin2=0, Int_t lastBin2=0) |
| Check that two sub axis are the same. | |
| static bool | CheckEqualAxes (const TAxis *a1, const TAxis *a2) |
| Check that the axis are the same. | |
| static Bool_t | RecomputeAxisLimits (TAxis &destAxis, const TAxis &anAxis) |
| Finds new limits for the axis for the Merge function. | |
| static Bool_t | SameLimitsAndNBins (const TAxis &axis1, const TAxis &axis2) |
| Same limits and bins. | |
| static void | SavePrimitiveConstructor (std::ostream &out, TClass *cl, const char *variable_name, const char *constructor_agrs="", Bool_t empty_line=kTRUE) |
| Save object constructor in the output stream "out". | |
| static void | SavePrimitiveDraw (std::ostream &out, const char *variable_name, Option_t *option=nullptr) |
| Save invocation of primitive Draw() method Skipped if option contains "nodraw" string. | |
| static TString | SavePrimitiveVector (std::ostream &out, const char *prefix, Int_t len, Double_t *arr, Int_t flag=0) |
| Save array in the output stream "out" as vector. | |
Protected Attributes | |
| Short_t | fBarOffset |
| (1000*offset) for bar charts or legos | |
| Short_t | fBarWidth |
| (1000*width) for bar charts or legos | |
| EBinErrorOpt | fBinStatErrOpt |
| Option for bin statistical errors. | |
| Double_t * | fBuffer |
| [fBufferSize] entry buffer | |
| Int_t | fBufferSize |
| fBuffer size | |
| TArrayD | fContour |
| Array to display contour levels. | |
| Int_t | fDimension |
| ! Histogram dimension (1, 2 or 3 dim) | |
| TDirectory * | fDirectory |
| ! Pointer to directory holding this histogram | |
| Double_t | fEntries |
| Number of entries. | |
| Color_t | fFillColor |
| Fill area color. | |
| Style_t | fFillStyle |
| Fill area style. | |
| TList * | fFunctions |
| ->Pointer to list of functions (fits and user) | |
| Double_t * | fIntegral |
| ! Integral of bins used by GetRandom | |
| Color_t | fLineColor |
| Line color. | |
| Style_t | fLineStyle |
| Line style. | |
| Width_t | fLineWidth |
| Line width. | |
| Color_t | fMarkerColor |
| Marker color. | |
| Size_t | fMarkerSize |
| Marker size. | |
| Style_t | fMarkerStyle |
| Marker style. | |
| Double_t | fMaximum |
| Maximum value for plotting. | |
| Double_t | fMinimum |
| Minimum value for plotting. | |
| TString | fName |
| Int_t | fNcells |
| Number of bins(1D), cells (2D) +U/Overflows. | |
| Double_t | fNormFactor |
| Normalization factor. | |
| TString | fOption |
| Histogram options. | |
| TVirtualHistPainter * | fPainter |
| ! Pointer to histogram painter | |
| EStatOverflows | fStatOverflows |
| Per object flag to use under/overflows in statistics. | |
| TArrayD | fSumw2 |
| Array of sum of squares of weights. | |
| TString | fTitle |
| Double_t | fTsumw |
| Total Sum of weights. | |
| Double_t | fTsumw2 |
| Total Sum of squares of weights. | |
| Double_t | fTsumwx |
| Total Sum of weight*X. | |
| Double_t | fTsumwx2 |
| Total Sum of weight*X*X. | |
| TAxis | fXaxis |
| X axis descriptor. | |
| TAxis | fYaxis |
| Y axis descriptor. | |
| TAxis | fZaxis |
| Z axis descriptor. | |
Static Protected Attributes | |
| static Bool_t | fgAddDirectory = kTRUE |
| ! Flag to add histograms to the directory | |
| static Int_t | fgBufferSize = 1000 |
| ! Default buffer size for automatic histograms | |
| static Bool_t | fgDefaultSumw2 = kFALSE |
| ! Flag to call TH1::Sumw2 automatically at histogram creation time | |
| static Bool_t | fgStatOverflows = kFALSE |
| ! Flag to use under/overflows in statistics | |
Private Member Functions | |
| void | Build () |
| Creates histogram basic data structure. | |
| template<typename ValueType> | |
| void | SetSliceContent (const std::vector< Double_t > &values, const std::vector< std::pair< Int_t, Int_t > > &sliceEdges, ValueType *dataArray) |
| Sets the content of a slice of bins in a histogram. | |
| template<typename ValueType> | |
| void | SliceHistoInPlace (std::vector< Int_t > &args, ValueType *&dataArray, Int_t &fN) |
| Slices a histogram in place based on the specified bin ranges for each dimension. | |
Static Private Member Functions | |
| static void | AddToTObjectTable (TObject *) |
| Private helper function which will dispatch to TObjectTable::AddObj. | |
Private Attributes | |
| UInt_t | fBits |
| bit field status word | |
| UInt_t | fUniqueID |
| object unique identifier | |
Static Private Attributes | |
| static Longptr_t | fgDtorOnly = 0 |
| object for which to call dtor only (i.e. no delete) | |
| static Bool_t | fgObjectStat = kTRUE |
| if true keep track of objects in TObjectTable | |
Friends | |
| TH1F | operator* (const TH1F &h1, const TH1F &h2) |
| Operator *. | |
| TH1F | operator* (const TH1F &h1, Double_t c1) |
| TH1F | operator* (Double_t c1, const TH1F &h1) |
| Operator *. | |
| TH1F | operator+ (const TH1F &h1, const TH1F &h2) |
| Operator +. | |
| TH1F | operator- (const TH1F &h1, const TH1F &h2) |
| Operator -. | |
| TH1F | operator/ (const TH1F &h1, const TH1F &h2) |
| Operator /. | |
#include <TH1.h>
|
inherited |
|
protectedinherited |
|
inherited |
|
inherited |
Size of statistics data (size of array used in GetStats()/ PutStats ).
| Enumerator | |
|---|---|
| kNstat | Size of statistics data (up to TProfile3D). |
|
inherited |
|
inherited |
|
inherited |
|
inherited |
|
inherited |
|
inherited |
TH1 status bits.
|
explicit |
| TH1F::TH1F | ( | const TH1F & | h1f | ) |
|
inherited |
Call this function within a function that you don't want to define as purely virtual, in order not to force all users deriving from that class to implement that maybe (on their side) unused function; but at the same time, emit a run-time warning if they try to call it, telling that it is not implemented in the derived class: action must thus be taken on the user side to override it.
In other word, this method acts as a "runtime purely virtual" warning instead of a "compiler purely virtual" error.
Definition at line 1149 of file TObject.cxx.
|
virtualinherited |
Replace contents of this histogram by the addition of h1 and h2.
this = c1*h1 + c2*h2 if errors are defined (see TH1::Sumw2), errors are also recalculated
Note that if h1 or h2 have Sumw2 set, Sumw2 is automatically called for this if not already set.
Note also that adding histogram with labels is not supported, histogram will be added merging them by bin number independently of the labels. For adding histogram ith labels one should use TH1::Merge
SPECIAL CASE (Average/Efficiency histograms) For histograms representing averages or efficiencies, one should compute the average of the two histograms and not the sum. One can mark a histogram to be an average histogram by setting its bit kIsAverage with myhist.SetBit(TH1::kIsAverage); Note that the two histograms must have their kIsAverage bit set
IMPORTANT NOTE: If you intend to use the errors of this histogram later you should call Sumw2 before making this operation. This is particularly important if you fit the histogram after TH1::Add
IMPORTANT NOTE2: You should be careful about the statistics of the returned histogram, whose statistics may be binned or unbinned, depending on whether c1 is negative, whether TAxis::kAxisRange is true, and whether TH1::ResetStats has been called on either this or h1. See TH1::GetStats.
ANOTHER SPECIAL CASE : h1 = h2 and c2 < 0 do a scaling this = c1 * h1 / (bin Volume)
The function returns kFALSE if the Add operation failed
Reimplemented in TH2Poly, TProfile2D, TProfile3D, and TProfile.
Performs the operation: this = this + c1*h1 If errors are defined (see TH1::Sumw2), errors are also recalculated.
Note that if h1 has Sumw2 set, Sumw2 is automatically called for this if not already set.
Note also that adding histogram with labels is not supported, histogram will be added merging them by bin number independently of the labels. For adding histogram with labels one should use TH1::Merge
SPECIAL CASE (Average/Efficiency histograms) For histograms representing averages or efficiencies, one should compute the average of the two histograms and not the sum. One can mark a histogram to be an average histogram by setting its bit kIsAverage with myhist.SetBit(TH1::kIsAverage); Note that the two histograms must have their kIsAverage bit set
IMPORTANT NOTE1: If you intend to use the errors of this histogram later you should call Sumw2 before making this operation. This is particularly important if you fit the histogram after TH1::Add
IMPORTANT NOTE2: if h1 has a normalisation factor, the normalisation factor is used , ie this = this + c1*factor*h1 Use the other TH1::Add function if you do not want this feature
IMPORTANT NOTE3: You should be careful about the statistics of the returned histogram, whose statistics may be binned or unbinned, depending on whether c1 is negative, whether TAxis::kAxisRange is true, and whether TH1::ResetStats has been called on either this or h1. See TH1::GetStats.
The function return kFALSE if the Add operation failed
Reimplemented in TH2Poly, TProfile2D, TProfile3D, and TProfile.
Performs the operation: this = this + c1*f1 if errors are defined (see TH1::Sumw2), errors are also recalculated.
By default, the function is computed at the centre of the bin. if option "I" is specified (1-d histogram only), the integral of the function in each bin is used instead of the value of the function at the centre of the bin.
Only bins inside the function range are recomputed.
IMPORTANT NOTE: If you intend to use the errors of this histogram later you should call Sumw2 before making this operation. This is particularly important if you fit the histogram after TH1::Add
The function return kFALSE if the Add operation failed
Reimplemented in TH2Poly, TProfile2D, TProfile3D, and TProfile.
Add float c at position i. Check for out of bounds.
Definition at line 92 of file TArrayF.cxx.
|
inlineoverridevirtual |
Sets the flag controlling the automatic add of histograms in memory.
By default (fAddDirectory = kTRUE), histograms are automatically added to the current directory (gDirectory). Note that one histogram can be removed from its support directory by calling h->SetDirectory(nullptr) or h->SetDirectory(dir) to add it to the list of objects in the directory dir.
This is a static function. To call it, use TH1::AddDirectory
|
staticinherited |
Check whether TH1-derived classes should register themselves to the current gDirectory.
|
staticprivateinherited |
Private helper function which will dispatch to TObjectTable::AddObj.
Included here to avoid circular dependency between header files.
Definition at line 195 of file TObject.cxx.
Adopt array arr into TArrayF, i.e.
don't copy arr but use it directly in TArrayF. User may not delete arr, TArrayF dtor will do it.
Definition at line 80 of file TArrayF.cxx.
Statistical test of compatibility in shape between this histogram and h2, using the Anderson-Darling 2 sample test.
The AD 2 sample test formula are derived from the paper F.W Scholz, M.A. Stephens "k-Sample Anderson-Darling Test".
The test is implemented in root in the ROOT::Math::GoFTest class It is the same formula ( (6) in the paper), and also shown in this preprint
Binned data are considered as un-binned data with identical observation happening in the bin center.
| [in] | h2 | Pointer to 1D histogram |
| [in] | option | is a character string to specify options
|
|
virtualinherited |
Append graphics object to current pad.
In case no current pad is set yet, create a default canvas with the name "c1".
Definition at line 204 of file TObject.cxx.
Buffer-based estimate of the histogram range using the power of 2 algorithm.
Used by the autobin power of 2 algorithm.
Works on arguments (min and max from fBuffer) and internal inputs: fXmin, fXmax, NBinsX (from fXaxis), ... Result save internally in fXaxis.
Overloaded by TH2 and TH3.
Return -1 if internal inputs are inconsistent, 0 otherwise.
|
overridevirtualinherited |
Fill histogram with all entries in the buffer.
Reimplemented in TH2, TH3, TProfile2D, TProfile3D, and TProfile.
accumulate arguments in buffer.
When buffer is full, empty the buffer
Reimplemented in TH2, TH3, TProfile2D, TProfile3D, and TProfile.
|
privateinherited |
|
virtualinherited |
|
inlineinherited |
Check and record whether this class has a consistent Hash/RecursiveRemove setup (*) and then return the regular Hash value for this object.
The intent is for this routine to be called instead of directly calling the function Hash during "insert" operations. See TObject::HasInconsistenTObjectHash();
(*) The setup is consistent when all classes in the class hierarchy that overload TObject::Hash do call ROOT::CallRecursiveRemoveIfNeeded in their destructor. i.e. it is safe to call the Hash virtual function during the RecursiveRemove operation.
|
virtualinherited |
\( \chi^{2} \) test for comparing weighted and unweighted histograms.
Compares the histograms' adjusted (normalized) residuals. Function: Returns p-value. Other return values are specified by the 3rd parameter
| [in] | h2 | the second histogram |
| [in] | option |
|
| [in] | res | not empty - computes normalized residuals and returns them in this array |
The current implementation is based on the papers \( \chi^{2} \) test for comparison of weighted and unweighted histograms" in Proceedings of PHYSTAT05 and "Comparison weighted and unweighted histograms", arXiv:physics/0605123 by N.Gagunashvili. This function has been implemented by Daniel Haertl in August 2006.
A frequently used technique in data analysis is the comparison of histograms. First suggested by Pearson [1] the \( \chi^{2} \) test of homogeneity is used widely for comparing usual (unweighted) histograms. This paper describes the implementation modified \( \chi^{2} \) tests for comparison of weighted and unweighted histograms and two weighted histograms [2] as well as usual Pearson's \( \chi^{2} \) test for comparison two usual (unweighted) histograms.
Comparison of two histograms expect hypotheses that two histograms represent identical distributions. To make a decision p-value should be calculated. The hypotheses of identity is rejected if the p-value is lower then some significance level. Traditionally significance levels 0.1, 0.05 and 0.01 are used. The comparison procedure should include an analysis of the residuals which is often helpful in identifying the bins of histograms responsible for a significant overall \( \chi^{2} \) value. Residuals are the difference between bin contents and expected bin contents. Most convenient for analysis are the normalized residuals. If hypotheses of identity are valid then normalized residuals are approximately independent and identically distributed random variables having N(0,1) distribution. Analysis of residuals expect test of above mentioned properties of residuals. Notice that indirectly the analysis of residuals increase the power of \( \chi^{2} \) test.
\( \chi^{2} \) test for comparison two (unweighted) histograms: Let us consider two histograms with the same binning and the number of bins equal to r. Let us denote the number of events in the ith bin in the first histogram as ni and as mi in the second one. The total number of events in the first histogram is equal to:
\[ N = \sum_{i=1}^{r} n_{i} \]
and
\[ M = \sum_{i=1}^{r} m_{i} \]
in the second histogram. The hypothesis of identity (homogeneity) [3] is that the two histograms represent random values with identical distributions. It is equivalent that there exist r constants p1,...,pr, such that
\[\sum_{i=1}^{r} p_{i}=1 \]
and the probability of belonging to the ith bin for some measured value in both experiments is equal to pi. The number of events in the ith bin is a random variable with a distribution approximated by a Poisson probability distribution
\[\frac{e^{-Np_{i}}(Np_{i})^{n_{i}}}{n_{i}!} \]
for the first histogram and with distribution
\[\frac{e^{-Mp_{i}}(Mp_{i})^{m_{i}}}{m_{i}!} \]
for the second histogram. If the hypothesis of homogeneity is valid, then the maximum likelihood estimator of pi, i=1,...,r, is
\[\hat{p}_{i}= \frac{n_{i}+m_{i}}{N+M} \]
and then
\[ X^{2} = \sum_{i=1}^{r}\frac{(n_{i}-N\hat{p}_{i})^{2}}{N\hat{p}_{i}} + \sum_{i=1}^{r}\frac{(m_{i}-M\hat{p}_{i})^{2}}{M\hat{p}_{i}} =\frac{1}{MN} \sum_{i=1}^{r}\frac{(Mn_{i}-Nm_{i})^{2}}{n_{i}+m_{i}} \]
has approximately a \( \chi^{2}_{(r-1)} \) distribution [3]. The comparison procedure can include an analysis of the residuals which is often helpful in identifying the bins of histograms responsible for a significant overall \( \chi^{2} \) value. Most convenient for analysis are the adjusted (normalized) residuals [4]
\[ r_{i} = \frac{n_{i}-N\hat{p}_{i}}{\sqrt{N\hat{p}_{i}}\sqrt{(1-N/(N+M))(1-(n_{i}+m_{i})/(N+M))}} \]
If hypotheses of homogeneity are valid then residuals ri are approximately independent and identically distributed random variables having N(0,1) distribution. The application of the \( \chi^{2} \) test has restrictions related to the value of the expected frequencies Npi, Mpi, i=1,...,r. A conservative rule formulated in [5] is that all the expectations must be 1 or greater for both histograms. In practical cases when expected frequencies are not known the estimated expected frequencies \( M\hat{p}_{i}, N\hat{p}_{i}, i=1,...,r \) can be used.
A simple modification of the ideas described above can be used for the comparison of the usual (unweighted) and weighted histograms. Let us denote the number of events in the ith bin in the unweighted histogram as ni and the common weight of events in the ith bin of the weighted histogram as wi. The total number of events in the unweighted histogram is equal to
\[ N = \sum_{i=1}^{r} n_{i} \]
and the total weight of events in the weighted histogram is equal to
\[ W = \sum_{i=1}^{r} w_{i} \]
Let us formulate the hypothesis of identity of an unweighted histogram to a weighted histogram so that there exist r constants p1,...,pr, such that
\[ \sum_{i=1}^{r} p_{i} = 1 \]
for the unweighted histogram. The weight wi is a random variable with a distribution approximated by the normal probability distribution \( N(Wp_{i},\sigma_{i}^{2}) \) where \( \sigma_{i}^{2} \) is the variance of the weight wi. If we replace the variance \( \sigma_{i}^{2} \) with estimate \( s_{i}^{2} \) (sum of squares of weights of events in the ith bin) and the hypothesis of identity is valid, then the maximum likelihood estimator of pi,i=1,...,r, is
\[ \hat{p}_{i} = \frac{Ww_{i}-Ns_{i}^{2}+\sqrt{(Ww_{i}-Ns_{i}^{2})^{2}+4W^{2}s_{i}^{2}n_{i}}}{2W^{2}} \]
We may then use the test statistic
\[ X^{2} = \sum_{i=1}^{r} \frac{(n_{i}-N\hat{p}_{i})^{2}}{N\hat{p}_{i}} + \sum_{i=1}^{r} \frac{(w_{i}-W\hat{p}_{i})^{2}}{s_{i}^{2}} \]
and it has approximately a \( \sigma^{2}_{(r-1)} \) distribution [2]. This test, as well as the original one [3], has a restriction on the expected frequencies. The expected frequencies recommended for the weighted histogram is more than 25. The value of the minimal expected frequency can be decreased down to 10 for the case when the weights of the events are close to constant. In the case of a weighted histogram if the number of events is unknown, then we can apply this recommendation for the equivalent number of events as
\[ n_{i}^{equiv} = \frac{ w_{i}^{2} }{ s_{i}^{2} } \]
The minimal expected frequency for an unweighted histogram must be 1. Notice that any usual (unweighted) histogram can be considered as a weighted histogram with events that have constant weights equal to 1. The variance \( z_{i}^{2} \) of the difference between the weight wi and the estimated expectation value of the weight is approximately equal to:
\[ z_{i}^{2} = Var(w_{i}-W\hat{p}_{i}) = N\hat{p}_{i}(1-N\hat{p}_{i})\left(\frac{Ws_{i}^{2}}{\sqrt{(Ns_{i}^{2}-w_{i}W)^{2}+4W^{2}s_{i}^{2}n_{i}}}\right)^{2}+\frac{s_{i}^{2}}{4}\left(1+\frac{Ns_{i}^{2}-w_{i}W}{\sqrt{(Ns_{i}^{2}-w_{i}W)^{2}+4W^{2}s_{i}^{2}n_{i}}}\right)^{2} \]
The residuals
\[ r_{i} = \frac{w_{i}-W\hat{p}_{i}}{z_{i}} \]
have approximately a normal distribution with mean equal to 0 and standard deviation equal to 1.
Let us denote the common weight of events of the ith bin in the first histogram as w1i and as w2i in the second one. The total weight of events in the first histogram is equal to
\[ W_{1} = \sum_{i=1}^{r} w_{1i} \]
and
\[ W_{2} = \sum_{i=1}^{r} w_{2i} \]
in the second histogram. Let us formulate the hypothesis of identity of weighted histograms so that there exist r constants p1,...,pr, such that
\[ \sum_{i=1}^{r} p_{i} = 1 \]
and also expectation value of weight w1i equal to W1pi and expectation value of weight w2i equal to W2pi. Weights in both the histograms are random variables with distributions which can be approximated by a normal probability distribution \( N(W_{1}p_{i},\sigma_{1i}^{2}) \) for the first histogram and by a distribution \( N(W_{2}p_{i},\sigma_{2i}^{2}) \) for the second. Here \( \sigma_{1i}^{2} \) and \( \sigma_{2i}^{2} \) are the variances of w1i and w2i with estimators \( s_{1i}^{2} \) and \( s_{2i}^{2} \) respectively. If the hypothesis of identity is valid, then the maximum likelihood and Least Square Method estimator of pi,i=1,...,r, is
\[ \hat{p}_{i} = \frac{w_{1i}W_{1}/s_{1i}^{2}+w_{2i}W_{2} /s_{2i}^{2}}{W_{1}^{2}/s_{1i}^{2}+W_{2}^{2}/s_{2i}^{2}} \]
We may then use the test statistic
\[ X^{2} = \sum_{i=1}^{r} \frac{(w_{1i}-W_{1}\hat{p}_{i})^{2}}{s_{1i}^{2}} + \sum_{i=1}^{r} \frac{(w_{2i}-W_{2}\hat{p}_{i})^{2}}{s_{2i}^{2}} = \sum_{i=1}^{r} \frac{(W_{1}w_{2i}-W_{2}w_{1i})^{2}}{W_{1}^{2}s_{2i}^{2}+W_{2}^{2}s_{1i}^{2}} \]
and it has approximately a \( \chi^{2}_{(r-1)} \) distribution [2]. The normalized or studentised residuals [6]
\[ r_{i} = \frac{w_{1i}-W_{1}\hat{p}_{i}}{s_{1i}\sqrt{1 - \frac{1}{(1+W_{2}^{2}s_{1i}^{2}/W_{1}^{2}s_{2i}^{2})}}} \]
have approximately a normal distribution with mean equal to 0 and standard deviation 1. A recommended minimal expected frequency is equal to 10 for the proposed test.
The method described herein is now illustrated with an example. We take a distribution
\[ \phi(x) = \frac{2}{(x-10)^{2}+1} + \frac{1}{(x-14)^{2}+1} (1) \]
defined on the interval [4,16]. Events distributed according to the formula (1) are simulated to create the unweighted histogram. Uniformly distributed events are simulated for the weighted histogram with weights calculated by formula (1). Each histogram has the same number of bins: 20. Fig.1 shows the result of comparison of the unweighted histogram with 200 events (minimal expected frequency equal to one) and the weighted histogram with 500 events (minimal expected frequency equal to 25)
/// End_Macro Fig 1. An example of comparison of the unweighted histogram with 200 events and the weighted histogram with 500 events:
The value of the test statistic \( \chi^{2} \) is equal to 21.09 with p-value equal to 0.33, therefore the hypothesis of identity of the two histograms can be accepted for 0.05 significant level. The behavior of the normalized residuals plot (see Fig. 1c) and the normal Q-Q plot (see Fig. 1d) of residuals are regular and we cannot identify the outliers or bins with a big influence on \( \chi^{2} \).
The second example presents the same two histograms but 17 events was added to content of bin number 15 in unweighted histogram. Fig.2 shows the result of comparison of the unweighted histogram with 217 events (minimal expected frequency equal to one) and the weighted histogram with 500 events (minimal expected frequency equal to 25)
/// End_Macro Fig 2. An example of comparison of the unweighted histogram with 217 events and the weighted histogram with 500 events:
The value of the test statistic \( \chi^{2} \) is equal to 32.33 with p-value equal to 0.029, therefore the hypothesis of identity of the two histograms is rejected for 0.05 significant level. The behavior of the normalized residuals plot (see Fig. 2c) and the normal Q-Q plot (see Fig. 2d) of residuals are not regular and we can identify the outlier or bin with a big influence on \( \chi^{2} \).
Reimplemented in TProfile2D, TProfile3D, and TProfile.
|
virtualinherited |
The computation routine of the Chisquare test.
For the method description, see Chi2Test() function.
| [in] | h2 | the second histogram |
| [in] | option |
|
| [out] | igood | test output
|
| [out] | chi2 | chisquare of the test |
| [out] | ndf | number of degrees of freedom (important, when both histograms have the same empty bins) |
| [out] | res | normalized residuals for further analysis |
Compute and return the chisquare of this histogram with respect to a function The chisquare is computed by weighting each histogram point by the bin error By default the full range of the histogram is used, unless TAxis::SetRange or TAxis::SetRangeUser was called before.
Use option "R" for restricting the chisquare calculation to the given range of the function Use option "L" for using the chisquare based on the poisson likelihood (Baker-Cousins Chisquare) Use option "P" for using the Pearson chisquare based on the expected bin errors Use option "I" for using the integral of the function in each bin instead of the value at the bin center
|
static |
|
static |
|
inlinestaticconstexpr |
|
virtualinherited |
Returns name of class to which the object belongs.
Definition at line 227 of file TObject.cxx.
|
overridevirtualinherited |
Set name and title to empty strings ("").
Reimplemented from TObject.
Reimplemented in TPrincipal, TProcessID, TStreamerInfo, TTask, TVirtualFitter, and TVirtualStreamerInfo.
Definition at line 63 of file TNamed.cxx.
|
virtualinherited |
|
overridevirtualinherited |
Compare two TNamed objects.
Returns 0 when equal, -1 when this is smaller and +1 when bigger (like strcmp).
Reimplemented from TObject.
Reimplemented in TStructNodeProperty.
Definition at line 84 of file TNamed.cxx.
|
virtualinherited |
Compute integral (normalized cumulative sum of bins) w/o under/overflows The result is stored in fIntegral and used by the GetRandom functions.
This function is automatically called by GetRandom when the fIntegral array does not exist or when the number of entries in the histogram has changed since the previous call to GetRandom. The resulting integral is normalized to 1. If the routine is called with the onlyPositive flag set an error will be produced in case of negative bin content and a NaN value returned
| onlyPositive | If set to true, an error will be produced and NaN will be returned when a bin with negative number of entries is encountered. |
| option |
|
Reimplemented in TH2Poly.
|
inlineinherited |
|
inherited |
|
inherited |
|
inherited |
|
overridevirtual |
|
inlinestatic |
|
virtualinherited |
Delete this object.
Typically called as a command via the interpreter. Normally use "delete" operator when object has been allocated on the heap.
Reimplemented in RooLinkedList, TAxis, TBtree, TCanvas, TClonesArray, TCollection, TDirectory, TDirectoryFile, TExMap, TFile, TGFrame, TGItemContext, TGTextEdit, THashList, THashTable, TKey, TKeySQL, TKeyXML, TList, TListOfDataMembers, TListOfEnums, TListOfEnumsWithLock, TListOfFunctions, TListOfFunctionTemplates, TMap, TMVA::Results, TObjArray, TObjectTable, TOrdCollection, TProtoClass, TQCommand, TRefArray, TSystemDirectory, TSystemFile, TThread, TTree, TTreeViewer, TViewPubDataMembers, and TViewPubFunctions.
Definition at line 268 of file TObject.cxx.
|
virtualinherited |
|
inherited |
Compute distance from point px,py to a line.
Compute the closest distance of approach from point px,py to elements of a histogram. The distance is computed in pixels units.
Currently, this simple model computes the distance from the mouse to the histogram contour only.
Reimplemented from TObject.
Divide this histogram by h1.
this = this/h1 if errors are defined (see TH1::Sumw2), errors are also recalculated. Note that if h1 has Sumw2 set, Sumw2 is automatically called for this if not already set. The resulting errors are calculated assuming uncorrelated histograms. See the other TH1::Divide that gives the possibility to optionally compute binomial errors.
IMPORTANT NOTE: If you intend to use the errors of this histogram later you should call Sumw2 before making this operation. This is particularly important if you fit the histogram after TH1::Scale
The function return kFALSE if the divide operation failed
Reimplemented in TProfile2D, TProfile3D, and TProfile.
|
virtualinherited |
Replace contents of this histogram by the division of h1 by h2.
this = c1*h1/(c2*h2)
If errors are defined (see TH1::Sumw2), errors are also recalculated Note that if h1 or h2 have Sumw2 set, Sumw2 is automatically called for this if not already set. The resulting errors are calculated assuming uncorrelated histograms. However, if option ="B" is specified, Binomial errors are computed. In this case c1 and c2 do not make real sense and they are ignored.
IMPORTANT NOTE: If you intend to use the errors of this histogram later you should call Sumw2 before making this operation. This is particularly important if you fit the histogram after TH1::Divide
Please note also that in the binomial case errors are calculated using standard binomial statistics, which means when b1 = b2, the error is zero. If you prefer to have efficiency errors not going to zero when the efficiency is 1, you must use the function TGraphAsymmErrors::BayesDivide, which will return an asymmetric and non-zero lower error for the case b1=b2.
The function return kFALSE if the divide operation failed
Reimplemented in TProfile2D, TProfile3D, and TProfile.
Performs the operation: this = this/(c1*f1) if errors are defined (see TH1::Sumw2), errors are also recalculated.
Only bins inside the function range are recomputed. IMPORTANT NOTE: If you intend to use the errors of this histogram later you should call Sumw2 before making this operation. This is particularly important if you fit the histogram after TH1::Divide
The function return kFALSE if the divide operation failed
Reimplemented in TH2Poly, TProfile2D, TProfile3D, and TProfile.
|
protectedvirtualinherited |
Interface to ErrorHandler (protected).
Reimplemented in TThread, and TTreeViewer.
Definition at line 1059 of file TObject.cxx.
|
overridevirtualinherited |
Draw this histogram with options.
Histograms are drawn via the THistPainter class. Each histogram has a pointer to its own painter (to be usable in a multithreaded program). The same histogram can be drawn with different options in different pads. If a histogram is updated after it has been drawn, the updated data will be shown the next time the pad is updated. One does not need to redraw the histogram.
When a histogram is deleted, the histogram is automatically removed from all pads where it was drawn. If a histogram should be modified or deleted without affecting what is drawn, it should be drawn using DrawCopy().
By default, TH1::Draw clears the current pad. Passing the option "SAME", the histogram will be drawn on top of what's in the pad. One can use TH1::SetMaximum and TH1::SetMinimum to force a particular value for the maximum or the minimum scale on the plot.
TH1::UseCurrentStyle can be used to change all histogram graphics attributes to correspond to the current selected style. This function must be called for each histogram. In case one reads and draws many histograms from a file, one can force the histograms to inherit automatically the current graphics style by calling before gROOT->ForceStyle();
See the THistPainter class for a description of all the drawing options.
Reimplemented from TObject.
|
virtualinherited |
Draw class inheritance tree of the class to which this object belongs.
If a class B inherits from a class A, description of B is drawn on the right side of description of A. Member functions overridden by B are shown in class A with a blue line crossing-out the corresponding member function. The following picture is the class inheritance tree of class TPaveLabel:
Reimplemented in TGFrame, TSystemDirectory, and TSystemFile.
Definition at line 308 of file TObject.cxx.
Draw a clone of this object in the current selected pad with: gROOT->SetSelectedPad(c1).
If pad was not selected - gPad will be used.
Reimplemented in TAxis, TCanvas, TGFrame, TSystemDirectory, and TSystemFile.
Definition at line 319 of file TObject.cxx.
|
virtualinherited |
Copy this histogram and Draw in the current pad.
Once the histogram is drawn into the pad, the original and its drawn copy can be modified or deleted without affecting each other. The copied histogram will be owned by the pad, and is deleted when the pad is cleared.
DrawCopy() is useful if the original histogram is a temporary, e.g. from code such as
If Draw() has been used, the histograms would disappear from the canvas at the end of this function.
By default a postfix "_copy" is added to the histogram name. Pass an empty postfix in case you want to draw a histogram with the same name.
See Draw() for the list of options.
In contrast to TObject::DrawClone(), DrawCopy
Draw a normalized copy of this histogram.
A clone of this histogram is normalized to norm and drawn with option. A pointer to the normalized histogram is returned. The contents of the histogram copy are scaled such that the new sum of weights (excluding under and overflow) is equal to norm. Note that the returned normalized histogram is not added to the list of histograms in the current directory in memory. It is the user's responsibility to delete this histogram. The kCanDelete bit is set for the returned object. If a pad containing this copy is cleared, the histogram will be automatically deleted.
See Draw for the list of options
|
virtualinherited |
|
virtualinherited |
Dump contents of object on stdout.
Using the information in the object dictionary (class TClass) each data member is interpreted. If a data member is a pointer, the pointer value is printed
The following output is the Dump of a TArrow object:
Reimplemented in TClass, TCollection, TGFrame, TGPack, and TSystemFile.
Definition at line 367 of file TObject.cxx.
|
virtualinherited |
Issue error message.
Use "location" to specify the method where the error occurred. Accepts standard printf formatting arguments.
Reimplemented in TFitResult.
Definition at line 1098 of file TObject.cxx.
Evaluate function f1 at the center of bins of this histogram.
|
virtualinherited |
Execute method on this object with the given parameter string, e.g.
"3.14,1,\"text\"".
Reimplemented in ROOT::R::TRInterface, TCling, TContextMenu, TInterpreter, and TMethodCall.
Definition at line 378 of file TObject.cxx.
|
virtualinherited |
Execute method on this object with parameters stored in the TObjArray.
The TObjArray should contain an argv vector like:
Reimplemented in ROOT::R::TRInterface, TCling, TContextMenu, TInterpreter, and TMethodCall.
Definition at line 398 of file TObject.cxx.
Execute action corresponding to one event.
This member function is called when a histogram is clicked with the locator
If Left button clicked on the bin top value, then the content of this bin is modified according to the new position of the mouse when it is released.
Reimplemented from TObject.
Histogram is resized along axis such that x is in the axis range.
The new axis limits are recomputed by doubling iteratively the current axis range until the specified value x is within the limits. The algorithm makes a copy of the histogram, then loops on all bins of the old histogram to fill the extended histogram. Takes into account errors (Sumw2) if any. The algorithm works for 1-d, 2-D and 3-D histograms. The axis must be extendable before invoking this function. Ex:
Reimplemented in TProfile2D, TProfile3D, and TProfile.
|
virtualinherited |
Issue fatal error message.
Use "location" to specify the method where the fatal error occurred. Accepts standard printf formatting arguments.
Definition at line 1126 of file TObject.cxx.
This function allows to do discrete Fourier transforms of TH1 and TH2.
Available transform types and flags are described below.
To extract more information about the transform, use the function TVirtualFFT::GetCurrentTransform() to get a pointer to the current transform object.
| [out] | h_output | histogram for the output. If a null pointer is passed, a new histogram is created and returned, otherwise, the provided histogram is used and should be big enough |
| [in] | option | option parameters consists of 3 parts:
|
Examples of valid options: "Mag R2C M" "Re R2R_11" "Im R2C ES" "PH R2HC EX"
Reimplemented in TH2Poly.
Increment bin with namex with a weight w.
if x is less than the low-edge of the first bin, the Underflow bin is incremented if x is equal to or greater than the upper edge of last bin, the Overflow bin is incremented
If the weight is not equal to 1, the storage of the sum of squares of weights is automatically triggered and the sum of the squares of weights is incremented by \( w^2 \) in the bin corresponding to x.
The function returns the corresponding bin number which has its content incremented by w.
Reimplemented in TH2, TH2Poly, TH3, TProfile2D, TProfile2Poly, TProfile3D, and TProfile.
Increment bin with abscissa X by 1.
if x is less than the low-edge of the first bin, the Underflow bin is incremented if x is equal to or greater than the upper edge of last bin, the Overflow bin is incremented
If the storage of the sum of squares of weights has been triggered, via the function Sumw2, then the sum of the squares of weights is incremented by 1 in the bin corresponding to x.
The function returns the corresponding bin number which has its content incremented by 1
Reimplemented in TH2, TH2Poly, TH3, TProfile2D, TProfile2Poly, TProfile3D, and TProfile.
Increment bin with abscissa X with a weight w.
if x is less than the low-edge of the first bin, the Underflow bin is incremented if x is equal to or greater than the upper edge of last bin, the Overflow bin is incremented
If the weight is not equal to 1, the storage of the sum of squares of weights is automatically triggered and the sum of the squares of weights is incremented by \( w^2 \) in the bin corresponding to x.
The function returns the corresponding bin number which has its content incremented by w
Reimplemented in TH2, TH2Poly, TH3, TProfile2D, TProfile2Poly, TProfile3D, and TProfile.
|
virtualinherited |
Encode TNamed into output buffer.
Reimplemented in TDirectoryFile, TFile, TKey, TKeySQL, TKeyXML, TSQLFile, and TXMLFile.
Definition at line 103 of file TNamed.cxx.
|
virtualinherited |
Fill this histogram with an array x and weights w.
| [in] | ntimes | number of entries in arrays x and w (array size must be ntimes*stride) |
| [in] | x | array of values to be histogrammed |
| [in] | w | array of weighs |
| [in] | stride | step size through arrays x and w |
If the weight is not equal to 1, the storage of the sum of squares of weights is automatically triggered and the sum of the squares of weights is incremented by \( w^2 \) in the bin corresponding to x. if w is NULL each entry is assumed a weight=1
Fill histogram following distribution in function fname.
| fname | : Function name used for filling the histogram |
| ntimes | : number of times the histogram is filled |
| rng | : (optional) Random number generator used to sample |
The distribution contained in the function fname (TF1) is integrated over the channel contents for the bin range of this histogram. It is normalized to 1.
Getting one random number implies:
One can also call TF1::GetRandom to get a random variate from a function.
Fill histogram following distribution in histogram h.
| h | : Histogram pointer used for sampling random number |
| ntimes | : number of times the histogram is filled |
| rng | : (optional) Random number generator used for sampling |
The distribution contained in the histogram h (TH1) is integrated over the channel contents for the bin range of this histogram. It is normalized to 1.
Getting one random number implies:
SPECIAL CASE when the target histogram has the same binning as the source. in this case we simply use a poisson distribution where the mean value per bin = bincontent/integral.
Return Global bin number corresponding to x,y,z.
2-D and 3-D histograms are represented with a one dimensional structure. This has the advantage that all existing functions, such as GetBinContent, GetBinError, GetBinFunction work for all dimensions. This function tries to extend the axis if the given point belongs to an under-/overflow bin AND if CanExtendAllAxes() is true.
See also TH1::GetBin, TAxis::FindBin and TAxis::FindFixBin
Reimplemented in TH2Poly.
|
virtualinherited |
Find first bin with content > threshold for axis (1=x, 2=y, 3=z) if no bins with content > threshold is found the function returns -1.
The search will occur between the specified first and last bin. Specifying the value of the last bin to search to less than zero will search until the last defined bin.
Return Global bin number corresponding to x,y,z.
2-D and 3-D histograms are represented with a one dimensional structure. This has the advantage that all existing functions, such as GetBinContent, GetBinError, GetBinFunction work for all dimensions. This function DOES NOT try to extend the axis if the given point belongs to an under-/overflow bin.
See also TH1::GetBin, TAxis::FindBin and TAxis::FindFixBin
|
virtualinherited |
Find last bin with content > threshold for axis (1=x, 2=y, 3=z) if no bins with content > threshold is found the function returns -1.
The search will occur between the specified first and last bin. Specifying the value of the last bin to search to less than zero will search until the last defined bin.
|
protectedvirtualinherited |
finds new limits for the axis so that point is within the range and the limits are compatible with the previous ones (see TH1::Merge).
new limits are put into newMin and newMax variables. axis - axis whose limits are to be recomputed point - point that should fit within the new axis limits newMin - new minimum will be stored here newMax - new maximum will be stored here. false if failed (e.g. if the initial axis limits are wrong or the new range is more than \( 2^{64} \) times the old one).
|
overridevirtualinherited |
|
virtualinherited |
Fit histogram with function fname.
fname is the name of a function available in the global ROOT list of functions gROOT->GetListOfFunctions. Note that this is not thread safe. The list include any TF1 object created by the user plus some pre-defined functions which are automatically created by ROOT the first time a pre-defined function is requested from gROOT (i.e. when calling gROOT->GetFunction(const char *name)). These pre-defined functions are:
For printing the list of all available functions do:
TF1::InitStandardFunctions(); // not needed if `gROOT->GetFunction` is called before TF2::InitStandardFunctions(); TF3::InitStandardFunctions(); // For 2D or 3D gROOT->GetListOfFunctions()->ls()
fname can also be a formula that is accepted by the linear fitter containing the special operator ++, representing linear components separated by ++ sign, for example x++sin(x) for fitting [0]*x+[1]*sin(x)
This function finds a pointer to the TF1 object with name fname and calls TH1::Fit(TF1 *, Option_t *, Option_t *, Double_t, Double_t). See there for the fitting options and the details about fitting histograms
|
virtualinherited |
Fit histogram with the function pointer f1.
| [in] | f1 | pointer to the function object |
| [in] | option | string defining the fit options (see table below). |
| [in] | goption | specify a list of graphics options. See TH1::Draw for a complete list of these options. |
| [in] | xxmin | lower fitting range |
| [in] | xxmax | upper fitting range |
Here is the full list of fit options that can be given in the parameter option. Several options can be used together by concatanating the strings without the need of any delimiters.
| option | description |
|---|---|
| "L" | Uses a log likelihood method (default is chi-square method). To be used when the histogram represents counts. |
| "WL" | Weighted log likelihood method. To be used when the histogram has been filled with weights different than 1. This is needed for getting correct parameter uncertainties for weighted fits. |
| "P" | Uses Pearson chi-square method. Uses expected errors instead of the observed one (default case). The expected error is instead estimated from the square-root of the bin function value. |
| "MULTI" | Uses Loglikelihood method based on multi-nomial distribution. In this case the function must be normalized and one fits only the function shape. |
| "W" | Fit using the chi-square method and ignoring the bin uncertainties and skip empty bins. |
| "WW" | Fit using the chi-square method and ignoring the bin uncertainties and include the empty bins. |
| "I" | Uses the integral of function in the bin instead of the default bin center value. |
| "F" | Uses the default minimizer (e.g. Minuit) when fitting a linear function (e.g. polN) instead of the linear fitter. |
| "U" | Uses a user specified objective function (e.g. user providedlikelihood function) defined using TVirtualFitter::SetFCN |
| "E" | Performs a better parameter errors estimation using the Minos technique for all fit parameters. |
| "M" | Uses the IMPROVE algorithm (available only in TMinuit). This algorithm attempts improve the found local minimum by searching for a better one. |
| "S" | The full result of the fit is returned in the TFitResultPtr. This is needed to get the covariance matrix of the fit. See TFitResult and the base class ROOT::Math::FitResult. |
| "Q" | Quiet mode (minimum printing) |
| "V" | Verbose mode (default is between Q and V) |
| "+" | Adds this new fitted function to the list of fitted functions. By default, the previous function is deleted and only the last one is kept. |
| "N" | Does not store the graphics function, does not draw the histogram with the function after fitting. |
| "0" | Does not draw the histogram and the fitted function after fitting, but in contrast to option "N", it stores the fitted function in the histogram list of functions. |
| "R" | Fit using a fitting range specified in the function range with TF1::SetRange. |
| "B" | Use this option when you want to fix or set limits on one or more parameters and the fitting function is a predefined one (e.g gaus, expo,..), otherwise in case of pre-defined functions, some default initial values and limits will be used. |
| "C" | In case of linear fitting, do no calculate the chisquare (saves CPU time). |
| "G" | Uses the gradient implemented in TF1::GradientPar for the minimization. This allows to use Automatic Differentiation when it is supported by the provided TF1 function. |
| "WIDTH" | Scales the histogran bin content by the bin width (useful for variable bins histograms) |
| "SERIAL" | Runs in serial mode. By default if ROOT is built with MT support and MT is enables, the fit is perfomed in multi-thread - "E" Perform better Errors estimation using Minos technique |
| "MULTITHREAD" | Forces usage of multi-thread execution whenever possible |
The default fitting of an histogram (when no option is given) is perfomed as following:
The Fit is perfomed using the default Minimizer, defined in the ROOT::Math::MinimizerOptions class. It is possible to change the default minimizer and its configuration parameters by calling these static functions before fitting (before calling TH1::Fit):
Other options are possible depending on the Minimizer used, see the corresponding documentation. The default minimizer can be also set in the resource file in etc/system.rootrc. For example
By default a chi-square (least-square) fit is performed on the histogram. The so-called modified least-square method is used where the residual for each bin is computed using as error the observed value (the bin error) returned by TH1::GetBinError
\[ Chi2 = \sum_{i}{ \left(\frac{y(i) - f(x(i) | p )}{e(i)} \right)^2 } \]
where y(i) is the bin content for each bin i, x(i) is the bin center and e(i) is the bin error (sqrt(y(i) for an un-weighted histogram). Bins with zero errors are excluded from the fit. See also later the note on the treatment of empty bins. When using option "I" the residual is computed not using the function value at the bin center, f(x(i)|p), but the integral of the function in the bin, Integral{ f(x|p)dx }, divided by the bin volume. When using option P (Pearson chi2), the expected error computed as e(i) = sqrt(f(x(i)|p)) is used. In this case empty bins are considered in the fit. Both chi-square methods should not be used when the bin content represent counts, especially in case of low bin statistics, because they could return a biased result.
When using option "L" a likelihood fit is used instead of the default chi-square fit. The likelihood is built assuming a Poisson probability density function for each bin. The negative log-likelihood to be minimized is
\[ NLL = - \sum_{i}{ \log {\mathrm P} ( y(i) | f(x(i) | p ) ) } \]
where P(y|f) is the Poisson distribution of observing a count y(i) in the bin when the expected count is f(x(i)|p). The exact likelihood used is the Poisson likelihood described in this paper: S. Baker and R. D. Cousins, “Clarification of the use of chi-square and likelihood functions in fits to histograms,” Nucl. Instrum. Meth. 221 (1984) 437.
\[ NLL = \sum_{i}{( f(x(i) | p ) + y(i)\log(y(i)/ f(x(i) | p )) - y(i)) } \]
By using this formulation, 2*NLL can be interpreted as the chi-square resulting from the fit.
This method should be always used when the bin content represents counts (i.e. errors are sqrt(N) ). The likelihood method has the advantage of treating correctly bins with low statistics. In case of high statistics/bin the distribution of the bin content becomes a normal distribution and the likelihood and the chi2 fit give the same result.
The likelihood method, although a bit slower, it is therefore the recommended method, when the histogram represent counts (Poisson statistics), where the chi-square methods may give incorrect results, especially in case of low statistics. In case of a weighted histogram, it is possible to perform also a likelihood fit by using the option "WL". Note a weighted histogram is a histogram which has been filled with weights and it has the information on the sum of the weight square for each bin ( TH1::Sumw2() has been called). The bin error for a weighted histogram is the square root of the sum of the weight square.
The function returns a TFitResultPtr which can hold a pointer to a TFitResult object. By default the TFitResultPtr contains only the status of the fit which is return by an automatic conversion of the TFitResultPtr to an integer. One can write in this case directly:
If the option "S" is instead used, TFitResultPtr behaves as a smart pointer to the TFitResult object. This is useful for retrieving the full result information from the fit, such as the covariance matrix, as shown in this example code:
The fit parameters, error and chi-square (but not covariance matrix) can be retrieved also directly from the fitted function that is passed to this call. Given a pointer to an associated fitted function myfunc, one can retrieve the function/fit parameters with calls such as:
One or more objects (typically a TF1*) can be added to the list of functions (fFunctions) associated to each histogram. When TH1::Fit is invoked, the fitted function is added to the histogram list of functions (fFunctions). If the histogram is made persistent, the list of associated functions is also persistent. Given a histogram h, one can retrieve an associated function with:
or by quering directly the list obtained by calling TH1::GetListOfFunctions.
The status of the fit is obtained converting the TFitResultPtr to an integer independently if the fit option "S" is used or not:
In order to fit in a sub-range of the histogram you have two options:
The fitting range is also limited by the histogram range defined using TAxis::SetRange or TAxis::SetRangeUser. Therefore the fitting range is the smallest range between the histogram one and the one defined by one of the two previous options described above.
Parameters must be initialized before invoking the Fit function. The setting of the parameter initial values is automatic for the predefined functions such as poln, expo, gaus, landau. One can however disable this automatic computation by using the option "B". Note that if a predefined function is defined with an argument, eg, gaus(0), expo(1), you must specify the initial values for the parameters. You can specify boundary limits for some or all parameters via
if parmin >= parmax, the parameter is fixed Note that you are not forced to fix the limits for all parameters. For example, if you fit a function with 6 parameters, you can do:
With this setup, parameters 0->2 can vary freely Parameter 3 has boundaries [-10,-4] with initial value -8 Parameter 4 is fixed to 0 Parameter 5 is fixed to 100. When the lower limit and upper limit are equal, the parameter is fixed. However to fix a parameter to 0, one must call the FixParameter function.
The statistics box can display the result of the fit. You can change the statistics box to display the fit parameters with the TStyle::SetOptFit(mode) method. This mode has four digits. mode = pcev (default = 0111)
v = 1; print name/values of parameters e = 1; print errors (if e=1, v must be 1) c = 1; print Chisquare/Number of degrees of freedom p = 1; print Probability
For example: gStyle->SetOptFit(1011); prints the fit probability, parameter names/values, and errors. You can change the position of the statistics box with these lines (where g is a pointer to the TGraph):
TPaveStats *st = (TPaveStats*)g->GetListOfFunctions()->FindObject("stats");
st->SetX1NDC(newx1); //new x start position
st->SetX2NDC(newx2); //new x end position
It is possible to fit a TH2 with a TF1 or a TH3 with a TF2. In this case the chi-square is computed from the squared error distance between the function values and the bin centers weighted by the bin content. For correct error scaling, the obtained parameter error are corrected as in the case when the option "W" is used.
By default when fitting a chi square function is used for fitting. When option "L" is used a Poisson likelihood function is used. Using option "MULTI" a multinomial likelihood fit is used. Thes functions are defined in the header Fit/Chi2Func.h or Fit/PoissonLikelihoodFCN and they are implemented using the routines FitUtil::EvaluateChi2 or FitUtil::EvaluatePoissonLogL in the file math/mathcore/src/FitUtil.cxx. It is possible to specify a user defined fitting function, using option "U" and calling the following functions:
where MyFittingFunction is of type:
Empty bins, which have the content equal to zero AND error equal to zero, are excluded by default from the chi-square fit, but they are considered in the likelihood fit. since they affect the likelihood if the function value in these bins is not negligible. Note that if the histogram is having bins with zero content and non zero-errors they are considered as any other bins in the fit. Instead bins with zero error and non-zero content are by default excluded in the chi-squared fit. In general, one should not fit a histogram with non-empty bins and zero errors.
If the bin errors are not known, one should use the fit option "W", which gives a weight=1 for each bin (it is an unweighted least-square fit). When using option "WW" the empty bins will be also considered in the chi-square fit with an error of 1. Note that in this fitting case (option "W" or "WW") the resulting fitted parameter errors are corrected by the obtained chi2 value using this scaling expression: errorp *= sqrt(chisquare/(ndf-1)) as it is done when fitting a TGraph with no point errors.
You can use TF1::RejectPoint inside your fitting function to exclude some points within a certain range from the fit. See the tutorial fit/fitExclude.C.
When selecting the option "0", the fitted function is added to the list of functions of the histogram, but it is not drawn when the histogram is drawn. You can undo this behaviour resetting its corresponding bit in the TF1 object as following:
|
virtualinherited |
|
inlineinherited |
Return a histogram containing the asymmetry of this histogram with h2, where the asymmetry is defined as:
works for 1D, 2D, etc. histograms c2 is an optional argument that gives a relative weight between the two histograms, and dc2 is the error on this weight. This is useful, for example, when forming an asymmetry between two histograms from 2 different data sets that need to be normalized to each other in some way. The function calculates the errors assuming Poisson statistics on h1 and h2 (that is, dh = sqrt(h)).
example: assuming 'h1' and 'h2' are already filled
then 'h3' is created and filled with the asymmetry between 'h1' and 'h2'; h1 and h2 are left intact.
Note that it is the user's responsibility to manage the created histogram. The name of the returned histogram will be Asymmetry_nameOfh1-nameOfh2
code proposed by Jason Seely (seely.nosp@m.@mit.nosp@m..edu) and adapted by R.Brun
clone the histograms so top and bottom will have the correct dimensions: Sumw2 just makes sure the errors will be computed properly when we form sums and ratios below.
|
protectedinherited |
|
inlinevirtualinherited |
|
inlinevirtualinherited |
Return Global bin number corresponding to binx,y,z.
2-D and 3-D histograms are represented with a one dimensional structure. This has the advantage that all existing functions, such as GetBinContent, GetBinError, GetBinFunction work for all dimensions.
In case of a TH1x, returns binx directly. see TH1::GetBinXYZ for the inverse transformation.
Convention for numbering bins
For all histogram types: nbins, xlow, xup
In case of 2-D or 3-D histograms, a "global bin" number is defined. For example, assuming a 3-D histogram with binx,biny,binz, the function
returns a global/linearized bin number. This global bin is useful to access the bin information independently of the dimension.
Return content of bin number bin.
Implemented in TH1C,S,F,D
Convention for numbering bins
For all histogram types: nbins, xlow, xup
In case of 2-D or 3-D histograms, a "global bin" number is defined. For example, assuming a 3-D histogram with binx,biny,binz, the function
returns a global/linearized bin number. This global bin is useful to access the bin information independently of the dimension.
Reimplemented in TH2, TH2Poly, TH3, TProfile2D, TProfile2Poly, TProfile3D, and TProfile.
Reimplemented in TH2, TH2Poly, TH3, TProfile2D, TProfile2Poly, TProfile3D, and TProfile.
Reimplemented in TH2, TH2Poly, TH3, TProfile2D, TProfile2Poly, TProfile3D, and TProfile.
Return value of error associated to bin number bin.
if the sum of squares of weights has been defined (via Sumw2), this function returns the sqrt(sum of w2). otherwise it returns the sqrt(contents) for this bin.
Reimplemented in TH2Poly, TProfile2D, TProfile2Poly, TProfile3D, and TProfile.
Reimplemented in TH2Poly, TProfile2D, TProfile2Poly, TProfile3D, and TProfile.
|
inlinevirtualinherited |
Reimplemented in TH2Poly, TProfile2D, TProfile2Poly, TProfile3D, and TProfile.
|
inlinevirtualinherited |
Reimplemented in TProfile2D, TProfile3D, and TProfile.
|
virtualinherited |
Compute first binx in the range [firstx,lastx] for which diff = abs(bin_content-c) <= maxdiff.
In case several bins in the specified range with diff=0 are found the first bin found is returned in binx. In case several bins in the specified range satisfy diff <=maxdiff the bin with the smallest difference is returned in binx. In all cases the function returns the smallest difference.
NOTE1: if firstx <= 0, firstx is set to bin 1 if (lastx < firstx then firstx is set to the number of bins ie if firstx=0 and lastx=0 (default) the search is on all bins.
NOTE2: if maxdiff=0 (default), the first bin with content=c is returned.
|
virtualinherited |
|
inherited |
Return a pointer to a histogram containing the cumulative content.
The cumulative can be computed both in the forward (default) or backward direction; the name of the new histogram is constructed from the name of this histogram with the suffix "suffix" appended provided by the user. If not provided a default suffix="_cumulative" is used.
The cumulative distribution is formed by filling each bin of the resulting histogram with the sum of that bin and all previous (forward == kTRUE) or following (forward = kFALSE) bins.
Note: while cumulative distributions make sense in one dimension, you may not be getting what you expect in more than 1D because the concept of a cumulative distribution is much trickier to define; make sure you understand the order of summation before you use this method with histograms of dimension >= 2.
Note 2: By default the cumulative is computed from bin 1 to Nbins If an axis range is set, values between the minimum and maximum of the range are set. Setting an axis range can also be used for including underflow and overflow in the cumulative (e.g. by setting h->GetXaxis()->SetRange(0, h->GetNbinsX()+1); )
|
staticinherited |
|
staticinherited |
|
inlinevirtualinherited |
|
inlineinherited |
|
virtualinherited |
Get option used by the graphics system to draw this object.
Note that before calling object.GetDrawOption(), you must have called object.Draw(..) before in the current pad.
Reimplemented in TBrowser, TFitEditor, TGedFrame, TGFileBrowser, TRootBrowser, and TRootBrowserLite.
Definition at line 445 of file TObject.cxx.
|
staticinherited |
Return destructor only flag.
Definition at line 1196 of file TObject.cxx.
|
virtualinherited |
Number of effective entries of the histogram.
\[neff = \frac{(\sum Weights )^2}{(\sum Weight^2 )} \]
In case of an unweighted histogram this number is equivalent to the number of entries of the histogram. For a weighted histogram, this number corresponds to the hypothetical number of unweighted entries a histogram would need to have the same statistical power as this weighted histogram. Note: The underflow/overflow are included if one has set the TH1::StatOverFlows flag and if the statistics has been computed at filling time. If a range is set in the histogram the number is computed from the given range.
|
virtualinherited |
|
inlinevirtualinherited |
Return the fill area color.
Reimplemented in TGraphMultiErrors, TGWin32, TGWin32VirtualXProxy, and TGX11.
Definition at line 32 of file TAttFill.h.
|
inlinevirtualinherited |
Return the fill area style.
Reimplemented in TGraphMultiErrors, TGWin32, TGWin32VirtualXProxy, and TGX11.
Definition at line 33 of file TAttFill.h.
|
virtualinherited |
|
virtualinherited |
Returns mime type name of object.
Used by the TBrowser (via TGMimeTypes class). Override for class of which you would like to have different icons for objects of the same class.
Reimplemented in ROOT::Experimental::XRooFit::xRooNode, TASImage, TBranch, TBranchElement, TGeoVolume, TGMainFrame, TKey, TMethodBrowsable, TSystemFile, and TVirtualBranchBrowsable.
Definition at line 472 of file TObject.cxx.
|
virtualinherited |
Return a pointer to the array of bins integral.
if the pointer fIntegral is null, TH1::ComputeIntegral is called The array dimension is the number of bins in the histograms including underflow and overflow (fNCells) the last value integral[fNCells] is set to the number of entries of the histogram
Note, that since third and fourth moment are not calculated at the fill time, kurtosis and its standard error are computed bin by bin
IMPORTANT NOTE: The returned value depends on how the histogram statistics are calculated. See TH1::GetMean and TH1::GetStdDev.
|
inlinevirtualinherited |
Return the line color.
Reimplemented in TGraphMultiErrors, and TGWin32VirtualXProxy.
Definition at line 36 of file TAttLine.h.
|
inlinevirtualinherited |
Return the line style.
Reimplemented in TGraphMultiErrors, TGWin32, TGWin32VirtualXProxy, and TGX11.
Definition at line 37 of file TAttLine.h.
|
inlinevirtualinherited |
Return the line width.
Reimplemented in TGraphMultiErrors, TGWin32, TGWin32VirtualXProxy, and TGX11.
Definition at line 38 of file TAttLine.h.
|
virtualinherited |
|
inlinevirtualinherited |
Return the marker color.
Reimplemented in TGWin32VirtualXProxy.
Definition at line 33 of file TAttMarker.h.
|
inlinevirtualinherited |
Return the marker size.
Reimplemented in TGWin32VirtualXProxy.
Definition at line 35 of file TAttMarker.h.
|
inlinevirtualinherited |
Return the marker style.
Reimplemented in TGWin32VirtualXProxy.
Definition at line 34 of file TAttMarker.h.
Return maximum value smaller than maxval of bins in the range, unless the value has been overridden by TH1::SetMaximum, in which case it returns that value.
This happens, for example, when the histogram is drawn and the y or z axis limits are changed
To get the maximum value of bins in the histogram regardless of whether the value has been overridden (using TH1::SetMaximum), use
TH1::GetMaximumBin can be used to get the location of the maximum value.
Reimplemented in TH2Poly.
|
virtualinherited |
|
inlinevirtualinherited |
For axis = 1,2 or 3 returns the mean value of the histogram along X,Y or Z axis.
For axis = 11, 12, 13 returns the standard error of the mean value of the histogram along X, Y or Z axis
Note that the mean value/StdDev is computed using the bins in the currently defined range (see TAxis::SetRange). By default the range includes all bins from 1 to nbins included, excluding underflows and overflows. To force the underflows and overflows in the computation, one must call the static function TH1::StatOverflows(kTRUE) before filling the histogram.
IMPORTANT NOTE: The returned value depends on how the histogram statistics are calculated. By default, if no range has been set, the returned mean is the (unbinned) one calculated at fill time. If a range has been set, however, the mean is calculated using the bins in range, as described above; THIS IS TRUE EVEN IF THE RANGE INCLUDES ALL BINS–use TAxis::SetRange(0, 0) to unset the range. To ensure that the returned mean (and all other statistics) is always that of the binned data stored in the histogram, call TH1::ResetStats. See TH1::GetStats.
Return mean value of this histogram along the X axis.
Return standard error of mean of this histogram along the X axis.
Note that the mean value/StdDev is computed using the bins in the currently defined range (see TAxis::SetRange). By default the range includes all bins from 1 to nbins included, excluding underflows and overflows. To force the underflows and overflows in the computation, one must call the static function TH1::StatOverflows(kTRUE) before filling the histogram.
Also note, that although the definition of standard error doesn't include the assumption of normality, many uses of this feature implicitly assume it.
IMPORTANT NOTE: The returned value depends on how the histogram statistics are calculated. By default, if no range has been set, the returned value is the (unbinned) one calculated at fill time. If a range has been set, however, the value is calculated using the bins in range, as described above; THIS IS TRUE EVEN IF THE RANGE INCLUDES ALL BINS–use TAxis::SetRange(0, 0) to unset the range. To ensure that the returned value (and all other statistics) is always that of the binned data stored in the histogram, call TH1::ResetStats. See TH1::GetStats.
Return minimum value larger than minval of bins in the range, unless the value has been overridden by TH1::SetMinimum, in which case it returns that value.
This happens, for example, when the histogram is drawn and the y or z axis limits are changed
To get the minimum value of bins in the histogram regardless of whether the value has been overridden (using TH1::SetMinimum), use
TH1::GetMinimumBin can be used to get the location of the minimum value.
Reimplemented in TH2Poly.
Retrieve the minimum and maximum values in the histogram.
This will not return a cached value and will always search the histogram for the min and max values. The user can condition whether or not to call this with the GetMinimumStored() and GetMaximumStored() methods. If the cache is empty, then the value will be -1111. Users can then use the SetMinimum() or SetMaximum() methods to cache the results. For example, the following recipe will make efficient use of this method and the cached minimum and maximum values.
| min | reference to variable that will hold found minimum value |
| max | reference to variable that will hold found maximum value |
|
virtualinherited |
|
inlinevirtualinherited |
|
inlineoverridevirtualinherited |
|
inlinevirtualinherited |
|
staticinherited |
Get status of object stat flag.
Definition at line 1181 of file TObject.cxx.
|
inlineoverridevirtualinherited |
|
inherited |
Compute Quantiles for this histogram.
A quantile x_p := Q(p) is defined as the value x_p such that the cumulative probability distribution Function F of variable X yields:
For instance the median x_0.5 of a distribution is defined as that value of the random variable X for which the distribution function equals 0.5:
| [in] | n | maximum size of the arrays xp and p (if given) |
| [out] | xp | array to be filled with nq quantiles evaluated at (p). Memory has to be preallocated by caller.
|
| [in] | p | array of cumulative probabilities where quantiles should be evaluated.
|
Note that the Integral of the histogram is automatically recomputed if the number of entries is different of the number of entries when the integral was computed last time. In case you do not use the Fill functions to fill your histogram, but SetBinContent, you must call TH1::ComputeIntegral before calling this function.
Getting quantiles xp from two histograms and storing results in a TGraph, a so-called QQ-plot
Example:
Return a random number distributed according the histogram bin contents.
This function checks if the bins integral exists. If not, the integral is evaluated, normalized to one.
| rng | (optional) Random number generator pointer used (default is gRandom) |
| option | (optional) Set it to "width" if your non-uniform bin contents represent a density rather than counts |
The integral is automatically recomputed if the number of entries is not the same then when the integral was computed.
This function returns the Standard Deviation (Sigma) of the distribution not the Root Mean Square (RMS).
The name "RMS" is been often used as a synonym for the Standard Deviation and it was introduced many years ago (Hbook/PAW times). We keep the name GetRMS for continuity as an alias to GetStdDev. GetStdDev() should be used instead.
Note, that since third and fourth moment are not calculated at the fill time, skewness and its standard error are computed bin by bin
IMPORTANT NOTE: The returned value depends on how the histogram statistics are calculated. See TH1::GetMean and TH1::GetStdDev.
|
inlineinherited |
|
inlineprotectedinherited |
|
virtualinherited |
fill the array stats from the contents of this histogram The array stats must be correctly dimensioned in the calling program.
If no axis-subrange is specified (via TAxis::SetRange), the array stats is simply a copy of the statistics quantities computed at filling time. If a sub-range is specified, the function recomputes these quantities from the bin contents in the current axis range.
IMPORTANT NOTE: This means that the returned statistics are context-dependent. If TAxis::kAxisRange, the returned statistics are dependent on the binning; otherwise, they are a copy of the histogram statistics computed at fill time, which are unbinned by default (calling TH1::ResetStats forces them to use binned statistics). You can reset TAxis::kAxisRange using TAxis::SetRange(0, 0).
Note that the mean value/StdDev is computed using the bins in the currently defined range (see TAxis::SetRange). By default the range includes all bins from 1 to nbins included, excluding underflows and overflows. To force the underflows and overflows in the computation, one must call the static function TH1::StatOverflows(kTRUE) before filling the histogram.
Reimplemented in TH2, TH2Poly, TH3, TProfile2D, TProfile2Poly, TProfile3D, and TProfile.
Returns the Standard Deviation (Sigma).
The Sigma estimate is computed as
\[\sqrt{\frac{1}{N}(\sum(x_i-x_{mean})^2)} \]
For axis = 1,2 or 3 returns the Sigma value of the histogram along X, Y or Z axis For axis = 11, 12 or 13 returns the error of StdDev estimation along X, Y or Z axis for Normal distribution
Note that the mean value/sigma is computed using the bins in the currently defined range (see TAxis::SetRange). By default the range includes all bins from 1 to nbins included, excluding underflows and overflows. To force the underflows and overflows in the computation, one must call the static function TH1::StatOverflows(kTRUE) before filling the histogram.
IMPORTANT NOTE: The returned value depends on how the histogram statistics are calculated. By default, if no range has been set, the returned standard deviation is the (unbinned) one calculated at fill time. If a range has been set, however, the standard deviation is calculated using the bins in range, as described above; THIS IS TRUE EVEN IF THE RANGE INCLUDES ALL BINS–use TAxis::SetRange(0, 0) to unset the range. To ensure that the returned standard deviation (and all other statistics) is always that of the binned data stored in the histogram, call TH1::ResetStats. See TH1::GetStats.
Return error of standard deviation estimation for Normal distribution.
Note that the mean value/StdDev is computed using the bins in the currently defined range (see TAxis::SetRange). By default the range includes all bins from 1 to nbins included, excluding underflows and overflows. To force the underflows and overflows in the computation, one must call the static function TH1::StatOverflows(kTRUE) before filling the histogram.
Value returned is standard deviation of sample standard deviation. Note that it is an approximated value which is valid only in the case that the original data distribution is Normal. The correct one would require the 4-th momentum value, which cannot be accurately estimated from a histogram since the x-information for all entries is not kept.
IMPORTANT NOTE: The returned value depends on how the histogram statistics are calculated. By default, if no range has been set, the returned value is the (unbinned) one calculated at fill time. If a range has been set, however, the value is calculated using the bins in range, as described above; THIS IS TRUE EVEN IF THE RANGE INCLUDES ALL BINS–use TAxis::SetRange(0, 0) to unset the range. To ensure that the returned value (and all other statistics) is always that of the binned data stored in the histogram, call TH1::ResetStats. See TH1::GetStats.
|
inlinevirtualinherited |
|
inlinevirtualinherited |
|
inlineoverridevirtualinherited |
|
virtualinherited |
Return the unique object id.
Definition at line 480 of file TObject.cxx.
Execute action in response of a timer timing out.
This method must be overridden if an object has to react to timers.
Reimplemented in TGCommandPlugin, TGDNDManager, TGFileContainer, TGHtml, TGLEventHandler, TGPopupMenu, TGraphTime, TGScrollBar, TGShutter, TGTextEdit, TGTextEditor, TGTextEntry, TGTextView, TGToolTip, TGuiBldDragManager, TGWindow, and TTreeViewer.
Definition at line 516 of file TObject.cxx.
|
inlineoverridevirtualinherited |
Return hash value for this object.
Note: If this routine is overloaded in a derived class, this derived class should also add
Otherwise, when RecursiveRemove is called (by ~TObject or example) for this type of object, the transversal of THashList and THashTable containers will will have to be done without call Hash (and hence be linear rather than logarithmic complexity). You will also see warnings like
Reimplemented from TObject.
|
inlineinherited |
Return true is the type of this object is known to have an inconsistent setup for Hash and RecursiveRemove (i.e.
missing call to RecursiveRemove in destructor).
Note: Since the consistency is only tested for during inserts, this routine will return true for object that have never been inserted whether or not they have a consistent setup. This has no negative side-effect as searching for the object with the right or wrong Hash will always yield a not-found answer (Since anyway no hash can be guaranteed unique, there is always a check)
|
virtualinherited |
Issue info message.
Use "location" to specify the method where the warning occurred. Accepts standard printf formatting arguments.
Definition at line 1072 of file TObject.cxx.
|
virtualinherited |
Returns kTRUE if object inherits from class "classname".
Reimplemented in TClass.
Definition at line 549 of file TObject.cxx.
Returns kTRUE if object inherits from TClass cl.
Reimplemented in TClass.
Definition at line 557 of file TObject.cxx.
|
virtualinherited |
Dump contents of this object in a graphics canvas.
Same action as Dump but in a graphical form. In addition pointers to other objects can be followed.
The following picture is the Inspect of a histogram object:
Reimplemented in ROOT::Experimental::XRooFit::xRooNode, TGFrame, TInspectorObject, and TSystemFile.
Definition at line 570 of file TObject.cxx.
Return integral of bin contents.
Only bins in the bins range are considered.
By default the integral is computed as the sum of bin contents in the range. if option "width" is specified, the integral is the sum of the bin contents multiplied by the bin width in x.
|
virtualinherited |
Return integral of bin contents in range [binx1,binx2] and its error.
By default the integral is computed as the sum of bin contents in the range. if option "width" is specified, the integral is the sum of the bin contents multiplied by the bin width in x. the error is computed using error propagation from the bin errors assuming that all the bins are uncorrelated
|
inlineoverridevirtual |
|
inlineinherited |
IsDestructed.
|
protectedinherited |
Default equal comparison (objects are equal if they have the same address in memory).
More complicated classes might want to override this function.
Reimplemented in TGObject, TObjString, TPair, and TQCommand.
Definition at line 589 of file TObject.cxx.
|
virtualinherited |
Returns kTRUE in case object contains browsable objects (like containers or lists of other objects).
Reimplemented in ROOT::Experimental::XRooFit::xRooNode, ROOT::Internal::THnBaseBrowsable, TApplicationRemote, TAxis3D, TBaseClass, TBranch, TBranchClones, TBranchElement, TBranchObject, TBranchSTL, TBrowserObject, TCanvas, TClass, TCollection, TDatabasePDG, TDirectory, TFolder, TGeoManager, TGeometry, TGeoNode, TGeoNodeMatrix, TGeoOverlap, TGeoTrack, TGeoVolume, THbookFile, THbookKey, THnBase, TKey, TMapFile, TMultiDimFit, TNode, TPad, TPair, TParticleClassPDG, TPrincipal, TRemoteObject, TROOT, TRootIconList, TSPlot, TSystemDirectory, TTask, TTree, and TVirtualBranchBrowsable.
Definition at line 579 of file TObject.cxx.
|
inlinevirtualinherited |
|
inlineoverridevirtualinherited |
Reimplemented from TObject.
Reimplemented in TStructNodeProperty.
|
inlinevirtualinherited |
Reimplemented in TGWin32VirtualXProxy.
Definition at line 49 of file TAttFill.h.
Statistical test of compatibility in shape between this histogram and h2, using Kolmogorov test.
Note that the KolmogorovTest (KS) test should in theory be used only for unbinned data and not for binned data as in the case of the histogram (see NOTE 3 below). So, before using this method blindly, read the NOTE 3.
Default: Ignore under- and overflow bins in comparison
| [in] | h2 | histogram |
| [in] | option | is a character string to specify options
|
The returned function value is the probability of test (much less than one means NOT compatible)
Code adapted by Rene Brun from original HBOOK routine HDIFF
NOTE1 A good description of the Kolmogorov test can be seen at: http://www.itl.nist.gov/div898/handbook/eda/section3/eda35g.htm
NOTE2 see also alternative function TH1::Chi2Test The Kolmogorov test is assumed to give better results than Chi2Test in case of histograms with low statistics.
NOTE3 (Jan Conrad, Fred James) "The returned value PROB is calculated such that it will be uniformly distributed between zero and one for compatible histograms, provided the data are not binned (or the number of bins is very large compared with the number of events). Users who have access to unbinned data and wish exact confidence levels should therefore not put their data into histograms, but should call directly TMath::KolmogorovTest. On the other hand, since TH1 is a convenient way of collecting data and saving space, this function has been provided. However, the values of PROB for binned data will be shifted slightly higher than expected, depending on the effects of the binning. For example, when comparing two uniform distributions of 500 events in 100 bins, the values of PROB, instead of being exactly uniformly distributed between zero and one, have a mean value of about 0.56. We can apply a useful rule: As long as the bin width is small compared with any significant physical effect (for example the experimental resolution) then the binning cannot have an important effect. Therefore, we believe that for all practical purposes, the probability value PROB is calculated correctly provided the user is aware that: 1. The value of PROB should not be expected to have exactly the correct distribution for binned data. 2. The user is responsible for seeing to it that the bin widths are small compared with any physical phenomena of interest. 3. The effect of binning (if any) is always to make the value of PROB slightly too big. That is, setting an acceptance criterion of (PROB>0.05 will assure that at most 5% of truly compatible histograms are rejected, and usually somewhat less."
Note also that for GoF test of unbinned data ROOT provides also the class ROOT::Math::GoFTest. The class has also method for doing one sample tests (i.e. comparing the data with a given distribution).
|
virtualinherited |
Reduce the number of bins for the axis passed in the option to the number of bins having a label.
The method will remove only the extra bins existing after the last "labeled" bin. Note that if there are "un-labeled" bins present between "labeled" bins they will not be removed
Reimplemented in TProfile2D, TProfile3D, and TProfile.
|
virtualinherited |
Double the number of bins for axis.
Refill histogram. This function is called by TAxis::FindBin(const char *label)
Reimplemented in TProfile2D, TProfile3D, and TProfile.
Sort bins with labels or set option(s) to draw axis with labels.
| [in] | option |
|
In case not all bins have labels sorting will work only in the case the first n consecutive bins have all labels and sorting will be performed on those label bins.
| [in] | ax | axis |
Reimplemented in TProfile2D, TProfile3D, and TProfile.
|
overridevirtualinherited |
List TNamed name and title.
Reimplemented from TObject.
Reimplemented in ROOT::Experimental::XRooFit::xRooBrowser, TNode, TROOT, TStreamerBase, TStreamerElement, TStreamerInfo, TStreamerSTL, TTask, TText, and TVirtualStreamerInfo.
Definition at line 112 of file TNamed.cxx.
|
inherited |
Use this method to signal that a method (defined in a base class) may not be called in a derived class (in principle against good design since a child class should not provide less functionality than its parent, however, sometimes it is necessary).
Definition at line 1160 of file TObject.cxx.
|
inlinevirtualinherited |
Reimplemented in TH2Poly, TProfile2D, TProfile2Poly, TProfile3D, and TProfile.
|
inherited |
Add all histograms in the collection to 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. If all histograms have bin labels, bins with identical labels will be merged, no matter what their order is. If overflows are present and limits are different the function will fail. The function returns the total number of entries in the result histogram if the merge is successful, -1 otherwise.
Possible option: -NOL : the merger will ignore the labels and merge the histograms bin by bin using bin center values to match bins -NOCHECK: the histogram will not perform a check for duplicate labels in case of axes with labels. The check (enabled by default) slows down the merging
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 and the upper limit must also be a multiple of the bin width. Example:
|
virtualinherited |
|
virtualinherited |
|
virtualinherited |
|
virtualinherited |
|
virtualinherited |
|
virtualinherited |
Multiply this histogram by h1.
this = this*h1
If errors of this are available (TH1::Sumw2), errors are recalculated. Note that if h1 has Sumw2 set, Sumw2 is automatically called for this if not already set.
IMPORTANT NOTE: If you intend to use the errors of this histogram later you should call Sumw2 before making this operation. This is particularly important if you fit the histogram after TH1::Multiply
The function return kFALSE if the Multiply operation failed
Reimplemented in TProfile2D, TProfile3D, and TProfile.
|
virtualinherited |
Replace contents of this histogram by multiplication of h1 by h2.
this = (c1*h1)*(c2*h2)
If errors of this are available (TH1::Sumw2), errors are recalculated. Note that if h1 or h2 have Sumw2 set, Sumw2 is automatically called for this if not already set.
IMPORTANT NOTE: If you intend to use the errors of this histogram later you should call Sumw2 before making this operation. This is particularly important if you fit the histogram after TH1::Multiply
The function return kFALSE if the Multiply operation failed
Reimplemented in TProfile2D, TProfile3D, and TProfile.
Performs the operation:
this = this*c1*f1
If errors are defined (see TH1::Sumw2), errors are also recalculated.
Only bins inside the function range are recomputed. IMPORTANT NOTE: If you intend to use the errors of this histogram later you should call Sumw2 before making this operation. This is particularly important if you fit the histogram after TH1::Multiply
The function return kFALSE if the Multiply operation failed
Reimplemented in TH2Poly, TProfile2D, TProfile3D, and TProfile.
|
virtualinherited |
Normalize a histogram to its integral or to its maximum.
| option | normalization strategy ("", "max" or "sum")
|
In case the norm is zero, it raises an error.
|
virtualinherited |
This method must be overridden to handle object notification (the base implementation is no-op).
Different objects in ROOT use the Notify method for different purposes, in coordination with other objects that call this method at the appropriate time.
For example, TLeaf uses it to load class information; TBranchRef to load contents of referenced branches TBranchRef; most notably, based on Notify, TChain implements a callback mechanism to inform interested parties when it switches to a new sub-tree.
Reimplemented in h1analysis, h1analysisTreeReader, TARInterruptHandler, TASInputHandler, TASInterruptHandler, TASLogHandler, TASSigPipeHandler, TBlinkTimer, TBranchElement, TBranchRef, TBreakLineCom, TBrowserTimer, TCollection, TDelCharCom, TDelTextCom, TFileHandler, TGContainerKeyboardTimer, TGContainerScrollTimer, TGInputHandler, TGLRedrawTimer, TGTextEditHist, TGuiBldDragManagerRepeatTimer, TIdleTimer, TInsCharCom, TInsTextCom, TInterruptHandler, TLeafObject, TMessageHandler, TNotifyLink< Type >, TNotifyLink< RNoCleanupNotifierHelper >, TNotifyLink< ROOT::Detail::TBranchProxy >, TNotifyLink< TTreeReader >, TPopupDelayTimer, TProcessEventTimer, TRefTable, TRepeatTimer, TSBRepeatTimer, TSelector, TSelectorDraw, TSelectorEntries, TSignalHandler, TSingleShotCleaner, TSocketHandler, TStdExceptionHandler, TSysEvtHandler, TTermInputHandler, TThreadTimer, TTimeOutTimer, TTimer, TTipDelayTimer, TTree, TTreeFormula, TTreeFormulaManager, TTreeReader, TViewTimer, and TViewUpdateTimer.
Definition at line 618 of file TObject.cxx.
|
inherited |
Use this method to declare a method obsolete.
Specify as of which version the method is obsolete and as from which version it will be removed.
Definition at line 1169 of file TObject.cxx.
|
inherited |
Operator delete for sized deallocation.
Definition at line 1234 of file TObject.cxx.
|
inherited |
Operator delete.
Definition at line 1212 of file TObject.cxx.
|
inherited |
Only called by placement new when throwing an exception.
Definition at line 1266 of file TObject.cxx.
|
inherited |
Operator delete [] for sized deallocation.
Definition at line 1245 of file TObject.cxx.
|
inherited |
Operator delete [].
Definition at line 1223 of file TObject.cxx.
|
inherited |
Only called by placement new[] when throwing an exception.
Definition at line 1274 of file TObject.cxx.
|
inlineinherited |
|
inlineinherited |
|
inlineinherited |
Generate an out-of-bounds error. Always returns false.
Definition at line 29 of file TArray.cxx.
|
overridevirtualinherited |
|
virtualinherited |
Pop on object drawn in a pad to the top of the display list.
I.e. it will be drawn last and on top of all other primitives.
Reimplemented in TFrame, TPad, and TVirtualPad.
Definition at line 640 of file TObject.cxx.
|
overridevirtualinherited |
Print some global quantities for this histogram.
| [in] | option |
|
Reimplemented from TObject.
Provide variable name for histogram for saving as primitive Histogram pointer has by default the histogram name with an incremental suffix.
If the histogram belongs to a graph or a stack the suffix is not added because the graph and stack objects are not aware of this new name. Same thing if the histogram is drawn with the option COLZ because the TPaletteAxis drawn when this option is selected, does not know this new name either.
|
virtualinherited |
Replace current statistics with the values in array stats.
Reimplemented in TH2, TH3, TProfile2D, TProfile3D, and TProfile.
|
virtualinherited |
Read contents of object with specified name from the current directory.
First the key with the given name is searched in the current directory, next the key buffer is deserialized into the object. The object must have been created before via the default constructor. See TObject::Write().
Reimplemented in TBuffer, TKey, TKeySQL, and TKeyXML.
Definition at line 673 of file TObject.cxx.
Read TArray object from buffer.
Simplified version of TBuffer::ReadObject (does not keep track of multiple references to same array).
Definition at line 40 of file TArray.cxx.
|
virtualinherited |
Rebin this histogram.
If newname is blank (default), the current histogram is modified and a pointer to it is returned.
If newname is not blank, the current histogram is not modified, and a new histogram is returned which is a Clone of the current histogram with its name set to newname.
The parameter ngroup indicates how many bins of this have to be merged into one bin of the result.
If the original histogram has errors stored (via Sumw2), the resulting histograms has new errors correctly calculated.
examples: if h1 is an existing TH1F histogram with 100 bins
NOTE: If ngroup is not an exact divider of the number of bins, the top limit of the rebinned histogram is reduced to the upper edge of the last bin that can make a complete group. The remaining bins are added to the overflow bin. Statistics will be recomputed from the new bin contents.
A new histogram is created (you should specify newname). The parameter ngroup is the number of variable size bins in the created histogram. The array xbins must contain ngroup+1 elements that represent the low-edges of the bins. If the original histogram has errors stored (via Sumw2), the resulting histograms has new errors correctly calculated.
NOTE: The bin edges specified in xbins should correspond to bin edges in the original histogram. If a bin edge in the new histogram is in the middle of a bin in the original histogram, all entries in the split bin in the original histogram will be transferred to the lower of the two possible bins in the new histogram. This is probably not what you want. A warning message is emitted in this case
examples: if h1 is an existing TH1F histogram with 100 bins
Reimplemented in TH2, TH3, and TProfile2D.
|
virtualinherited |
|
overridevirtualinherited |
|
overridevirtual |
|
virtualinherited |
Reimplemented in TGWin32VirtualXProxy.
|
virtualinherited |
Reimplemented in TGWin32VirtualXProxy.
|
virtualinherited |
Reimplemented in TGWin32VirtualXProxy.
|
virtualinherited |
Reset the statistics including the number of entries and replace with values calculated from bin content.
The number of entries is set to the total bin content or (in case of weighted histogram) to number of effective entries
|
overridevirtualinherited |
Save the histogram as .csv, .tsv or .txt.
In case of any other extension, fall back to TObject::SaveAs, which saves as a .C macro (but with the file name extension specified by the user)
The Under/Overflow bins are also exported (as first and last lines) The fist 2 columns are the lower and upper edges of the bins Column 3 contains the bin contents The last column contains the error in y. If errors are not present, the column is left empty
The result can be immediately imported into Excel, gnuplot, Python or whatever, without the needing to install pyroot, etc.
| filename | the name of the file where to store the histogram |
| option | some tuning options |
The file extension defines the delimiter used:
If option = "title" a title line is generated. If the y-axis has a title, this title is displayed as column 3 name, otherwise, it shows "BinContent"
Reimplemented from TObject.
|
virtualinherited |
|
virtualinherited |
|
virtualinherited |
|
overridevirtualinherited |
Save primitive as a C++ statement(s) on output stream out.
Reimplemented from TObject.
Reimplemented in TH2Poly, TProfile2D, TProfile3D, and TProfile.
|
staticprotectedinherited |
Save object constructor in the output stream "out".
Can be used as first statement when implementing SavePrimitive() method for the object
Definition at line 777 of file TObject.cxx.
|
staticprotectedinherited |
Save invocation of primitive Draw() method Skipped if option contains "nodraw" string.
Definition at line 845 of file TObject.cxx.
|
staticinherited |
|
protectedvirtualinherited |
|
protectedinherited |
Save object name and title into the output stream "out".
Definition at line 135 of file TNamed.cxx.
|
staticprotectedinherited |
Save array in the output stream "out" as vector.
Create unique variable name based on prefix value Returns name of vector which can be used in constructor or in other places of C++ code If flag === kTRUE, just add empty line If flag === 111, check if array is empty and return nullptr or <vectorname>.data()
Definition at line 796 of file TObject.cxx.
Multiply this histogram by a constant c1.
this = c1*this
Note that both contents and errors (if any) are scaled. This function uses the services of TH1::Add
IMPORTANT NOTE: Sumw2() is called automatically when scaling. If you are not interested in the histogram statistics you can call Sumw2(kFALSE) or use the option "nosw2"
One can scale a histogram such that the bins integral is equal to the normalization parameter via TH1::Scale(Double_t norm), where norm is the desired normalization divided by the integral of the histogram.
If option contains "width" the bin contents and errors are divided by the bin width.
Reimplemented in TH2Poly, TProfile2D, TProfile3D, and TProfile.
|
overridevirtualinherited |
Set size of this array to n floats.
A new array is created, the old contents copied to the new array, then the old array is deleted. This function should not be called if the array was declared via Adopt.
Implements TArray.
Definition at line 104 of file TArrayF.cxx.
Set size of this array to n floats and set the contents.
This function should not be called if the array was declared via Adopt.
Definition at line 131 of file TArrayF.cxx.
|
inlinevirtualinherited |
|
inlinevirtualinherited |
Set the bin Error Note that this resets the bin eror option to be of Normal Type and for the non-empty bin the bin error is set by default to the square root of their content.
Note that in case the user sets after calling SetBinError explicitly a new bin content (e.g. using SetBinContent) he needs then to provide also the corresponding bin error (using SetBinError) since the bin error will not be recalculated after setting the content and a default error = 0 will be used for those bins.
See convention for numbering bins in TH1::GetBin
Reimplemented in TH2Poly.
|
inlinevirtualinherited |
Redefine x axis parameters with variable bin sizes.
The X axis parameters are modified. The bins content array is resized if errors (Sumw2) the errors array is resized The previous bin contents are lost To change only the axis limits, see TAxis::SetRange xBins is supposed to be of length nx+1
Reimplemented in TProfile2D, TProfile3D, and TProfile.
|
virtualinherited |
Redefine x and y axis parameters with variable bin sizes.
The X and Y axis parameters are modified. The bins content array is resized if errors (Sumw2) the errors array is resized The previous bin contents are lost To change only the axis limits, see TAxis::SetRange xBins is supposed to be of length nx+1, yBins is supposed to be of length ny+1
Reimplemented in TProfile2D, TProfile3D, and TProfile.
|
virtualinherited |
Redefine x, y and z axis parameters with variable bin sizes.
The X, Y and Z axis parameters are modified. The bins content array is resized if errors (Sumw2) the errors array is resized The previous bin contents are lost To change only the axis limits, see TAxis::SetRange xBins is supposed to be of length nx+1, yBins is supposed to be of length ny+1, zBins is supposed to be of length nz+1
Reimplemented in TProfile2D, TProfile3D, and TProfile.
Redefine x axis parameters.
The X axis parameters are modified. The bins content array is resized if errors (Sumw2) the errors array is resized The previous bin contents are lost To change only the axis limits, see TAxis::SetRange
Reimplemented in TProfile2D, TProfile3D, and TProfile.
|
virtualinherited |
Redefine x and y axis parameters.
The X and Y axis parameters are modified. The bins content array is resized if errors (Sumw2) the errors array is resized The previous bin contents are lost To change only the axis limits, see TAxis::SetRange
Reimplemented in TProfile2D, TProfile3D, and TProfile.
|
virtualinherited |
Redefine x, y and z axis parameters.
The X, Y and Z axis parameters are modified. The bins content array is resized if errors (Sumw2) the errors array is resized The previous bin contents are lost To change only the axis limits, see TAxis::SetRange
Reimplemented in TProfile2D, TProfile3D, and TProfile.
|
overridevirtual |
Set or unset the user status bits as specified in f.
Definition at line 888 of file TObject.cxx.
Set the maximum number of entries to be kept in the buffer.
Reimplemented in TProfile2D, TProfile3D, and TProfile.
|
virtualinherited |
Shortcut to set the three histogram colors with a single call.
By default: linecolor = markercolor = fillcolor = -1 If a color is < 0 this method does not change the corresponding color if positive or null it set the color.
For instance:
will set the line color and the marker color to red.
|
virtualinherited |
Set the number and values of contour levels.
By default the number of contour levels is set to 20. The contours values in the array "levels" should be specified in increasing order.
if argument levels = 0 or missing, nlevels equidistant contours are computed between zmin and zmax - dz, both included, with step dz = (zmax - zmin)/nlevels. Note that contour lines are not centered, but contour surfaces (when drawing with COLZ) will be, since contour color i covers the region of values between contour line i and i+1.
|
staticinherited |
|
virtualinherited |
By default, when a histogram is created, it is added to the list of histogram objects in the current directory in memory.
Remove reference to this histogram from current directory and add reference to new directory dir. dir can be 0 in which case the histogram does not belong to any directory.
Note that the directory is not a real property of the histogram and it will not be copied when the histogram is copied or cloned. If the user wants to have the copied (cloned) histogram in the same directory, he needs to set again the directory using SetDirectory to the copied histograms
|
virtualinherited |
Set drawing option for object.
This option only affects the drawing style and is stored in the option field of the TObjOptLink supporting a TPad's primitive list (TList). Note that it does not make sense to call object.SetDrawOption(option) before having called object.Draw().
Reimplemented in RooPlot, TAxis, TBrowser, TGedFrame, TGFrame, TPad, TPaveStats, TRootBrowserLite, TSystemDirectory, and TSystemFile.
Definition at line 871 of file TObject.cxx.
|
staticinherited |
Set destructor only flag.
Definition at line 1204 of file TObject.cxx.
|
inlinevirtualinherited |
|
virtualinherited |
|
virtualinherited |
Reimplemented in TGWin32VirtualXProxy.
|
inlinevirtualinherited |
Set the fill area color.
Reimplemented in TGQuartz, TGraphMultiErrors, TGWin32, TGWin32VirtualXProxy, TGX11, TPDF, TPostScript, TSpider, TSVG, TTeXDump, and TVirtualX.
Definition at line 40 of file TAttFill.h.
|
inherited |
Reimplemented in TGraphMultiErrors.
|
inlinevirtualinherited |
Set the fill area style.
Reimplemented in TGQuartz, TGraphMultiErrors, TGWin32, TGWin32VirtualXProxy, TGX11, TPad, TSpider, and TVirtualX.
Definition at line 42 of file TAttFill.h.
Set font number used to draw axis labels.
font : Text font code = 10*fontnumber + precision Font numbers must be between 1 and 14 precision = 1 fast hardware fonts (steps in the size) precision = 2 scalable and rotatable hardware fonts
The default font number is 62. axis specifies which axis ("x","y","z"), default = "x" if axis="xyz" set all 3 axes
|
virtualinherited |
Reimplemented in TGWin32VirtualXProxy.
|
inlinevirtualinherited |
Set the line color.
Reimplemented in ROOT::Experimental::REveLine, ROOT::Experimental::REveStraightLineSet, ROOT::Experimental::REveTrackList, TEveLine, TEveStraightLineSet, TEveTrackList, TGeoVolume, TGeoVolumeMulti, TGQuartz, TGraphMultiErrors, TGWin32, TGWin32VirtualXProxy, TGX11, TParallelCoordRange, TPDF, TPostScript, TSpider, TSVG, TTeXDump, and TVirtualX.
Definition at line 44 of file TAttLine.h.
|
inherited |
Reimplemented in TGraphMultiErrors.
|
inlinevirtualinherited |
Set the line style.
Reimplemented in ROOT::Experimental::REveLine, ROOT::Experimental::REveTrackList, TEveLine, TEveTrackList, TGeoVolume, TGeoVolumeMulti, TGQuartz, TGraphMultiErrors, TGWin32, TGWin32VirtualXProxy, TGX11, TPDF, TPostScript, TSpider, TSVG, TTeXDump, and TVirtualX.
Definition at line 46 of file TAttLine.h.
|
inlinevirtualinherited |
Set the line width.
Reimplemented in ROOT::Experimental::REveLine, ROOT::Experimental::REveTrackList, TEveLine, TEveTrackList, TGeoVolume, TGeoVolumeMulti, TGQuartz, TGraphMultiErrors, TGWin32, TGWin32VirtualXProxy, TGX11, TPaletteAxis, TParallelCoordRange, TPDF, TPostScript, TSpider, TSVG, TTeXDump, and TVirtualX.
Definition at line 47 of file TAttLine.h.
|
virtualinherited |
Reimplemented in TGWin32VirtualXProxy.
|
inlinevirtualinherited |
Set the marker color.
Reimplemented in ROOT::Experimental::REveLine, ROOT::Experimental::REvePointSet, ROOT::Experimental::REvePointSetArray, ROOT::Experimental::REveTrackList, TEveLine, TEvePointSet, TEvePointSetArray, TEveTrackList, TGQuartz, TGWin32, TGWin32VirtualXProxy, TGX11, TPDF, TPostScript, TSVG, TTeXDump, and TVirtualX.
Definition at line 41 of file TAttMarker.h.
|
inherited |
|
inlinevirtualinherited |
Set the marker size.
Note that the marker styles number 1 6 and 7 (the dots), cannot be scaled. They are meant to be very fast to draw and are always drawn with the same number of pixels; therefore this method does not apply on them.
Reimplemented in ROOT::Experimental::REvePointSet, ROOT::Experimental::REvePointSetArray, ROOT::Experimental::REveTrackList, TEvePointSet, TEvePointSetArray, TEveTrackList, TGQuartz, TGWin32, TGWin32VirtualXProxy, TGX11, TTeXDump, and TVirtualX.
Definition at line 48 of file TAttMarker.h.
|
inlinevirtualinherited |
Set the marker style.
Reimplemented in ROOT::Experimental::REvePointSet, ROOT::Experimental::REvePointSetArray, ROOT::Experimental::REveTrackList, TEvePointSet, TEvePointSetArray, TEveTrackList, TGQuartz, TGWin32, TGWin32VirtualXProxy, TGX11, and TVirtualX.
Definition at line 43 of file TAttMarker.h.
|
inlinevirtualinherited |
|
inlinevirtualinherited |
|
overridevirtualinherited |
|
overridevirtualinherited |
Set the number of divisions to draw an axis.
ndiv : Number of divisions.
n = N1 + 100*N2 + 10000*N3
N1=number of primary divisions.
N2=number of secondary divisions.
N3=number of 3rd divisions.
e.g.:
nndi=0 --> no tick marks.
nndi=2 --> 2 divisions, one tick mark in the middle
of the axis.
axis specifies which axis ("x","y","z"), default = "x" if axis="xyz" set all 3 axes
|
inlinevirtualinherited |
|
staticinherited |
Turn on/off tracking of objects in the TObjectTable.
Definition at line 1188 of file TObject.cxx.
|
inlinevirtualinherited |
|
inlineprivateinherited |
Sets the content of a slice of bins in a histogram.
This function allows setting the content of a slice of bins in a histogram by specifying the edges of the slice and the corresponding values to assign.
| ValueType | The type of the histogram's data. |
| values | A vector of values to assign to the bins in the specified slice. |
| sliceEdges | A vector of pairs specifying the low and upper edges of the slice for each dimension. |
| dataArray | A pointer to the histogram's data array. |
|
inlineinherited |
|
overridevirtualinherited |
Change/set the title.
If title is in the form stringt;stringx;stringy;stringz;stringc the histogram title is set to stringt, the x axis title to stringx, the y axis title to stringy, the z axis title to stringz, and the c axis title for the palette is ignored at this stage. Note that you can use e.g. stringt;stringx if you only want to specify title and x axis title.
To insert the character ; in one of the titles, one should use #; or #semicolon.
Reimplemented from TNamed.
Specify a parameter offset to control the distance between the axis and the axis' title.
axis specifies which axis ("x","y","z"), default = "x" if axis="xyz" set all 3 axes
|
virtualinherited |
Set the unique object id.
Definition at line 899 of file TObject.cxx.
|
inlinevirtualinherited |
|
inlinevirtualinherited |
|
inlinevirtualinherited |
This function calculates the background spectrum in this histogram.
The background is returned as a histogram.
| [in] | niter | number of iterations (default value = 2) Increasing niter make the result smoother and lower. |
| [in] | option | may contain one of the following options
|
NOTE that the background is only evaluated in the current range of this histogram. i.e., if this has a bin range (set via h->GetXaxis()->SetRange(binmin, binmax), the returned histogram will be created with the same number of bins as this input histogram, but only bins from binmin to binmax will be filled with the estimated background.
|
virtualinherited |
Interface to TSpectrum::Search.
The function finds peaks in this histogram where the width is > sigma and the peak maximum greater than threshold*maximum bin content of this. For more details see TSpectrum::Search. Note the difference in the default value for option compared to TSpectrum::Search option="" by default (instead of "goff").
Reimplemented in TH2.
|
virtualinherited |
Return size of the TNamed part of the TObject.
Reimplemented in TDirectory, TDirectoryFile, TFile, TKey, TSQLFile, and TXMLFile.
Definition at line 182 of file TNamed.cxx.
|
inlineprivateinherited |
Slices a histogram in place based on the specified bin ranges for each dimension.
This function modifies the histogram by extracting a sub-region defined by the provided bin ranges for each dimension. The resulting histogram will have updated bin counts, edges, and contents. Bin contents outside the range fall into the flow bins. The histogram's internal data array is freed and reallocated by this function. This function is used by the python implementation of the Unified Histogram Interface (UHI) for slicing.
| ValueType | The type of the histogram's data. |
| args | A vector of integers specifying the low and upper edges of the slice for each dimension. |
| dataArray | A pointer to the histogram's data array. |
| fN | The size of dataArray. |
Smooth bin contents of this histogram.
if option contains "R" smoothing is applied only to the bins defined in the X axis range (default is to smooth all bins) Bin contents are replaced by their smooth values. Errors (if any) are not modified. the smoothing procedure is repeated ntimes (default=1)
Reimplemented in TH2.
Smooth array xx, translation of Hbook routine hsmoof.F.
Based on algorithm 353QH twice presented by J. Friedman in Proc. of the 1974 CERN School of Computing, Norway, 11-24 August, 1974. See also Section 4.2 in J. Friedman, Data Analysis Techniques for High Energy Physics.
|
inline |
Create structure to store sum of squares of weights.
if histogram is already filled, the sum of squares of weights is filled with the existing bin contents
The error per bin will be computed as sqrt(sum of squares of weight) for each bin.
This function is automatically called when the histogram is created if the static function TH1::SetDefaultSumw2 has been called before. If flag = false the structure containing the sum of the square of weights is rest and it will be empty, but it is not deleted (i.e. GetSumw2()->fN = 0)
Reimplemented in TProfile2D, TProfile3D, and TProfile.
|
virtualinherited |
Issue system error message.
Use "location" to specify the method where the system error occurred. Accepts standard printf formatting arguments.
Definition at line 1112 of file TObject.cxx.
|
staticinherited |
For a given transform (first parameter), fills the histogram (second parameter) with the transform output data, specified in the third parameter If the 2nd parameter h_output is empty, a new histogram (TH1D or TH2D) is created and the user is responsible for deleting it.
Available options:
|
overridevirtualinherited |
|
virtualinherited |
Issue warning message.
Use "location" to specify the method where the warning occurred. Accepts standard printf formatting arguments.
Definition at line 1084 of file TObject.cxx.
|
virtualinherited |
Write this object to the current directory.
For more see the const version of this method.
Reimplemented in ROOT::TBufferMergerFile, TBuffer, TCollection, TDirectory, TDirectoryFile, TFile, TMap, TParallelMergingFile, TSQLFile, TTree, and TXMLFile.
Definition at line 989 of file TObject.cxx.
|
virtualinherited |
Write this object to the current directory.
The data structure corresponding to this object is serialized. The corresponding buffer is written to the current directory with an associated key with name "name".
Writing an object to a file involves the following steps:
Bufsize can be given to force a given buffer size to write this object. By default, the buffersize will be taken from the average buffer size of all objects written to the current file so far.
If a name is specified, it will be the name of the key. If name is not given, the name of the key will be the name as returned by GetName().
The option can be a combination of: kSingleKey, kOverwrite or kWriteDelete Using the kOverwrite option a previous key with the same name is overwritten. The previous key is deleted before writing the new object. Using the kWriteDelete option a previous key with the same name is deleted only after the new object has been written. This option is safer than kOverwrite but it is slower. NOTE: Neither kOverwrite nor kWriteDelete reduces the size of a TFile– the space is simply freed up to be overwritten; in the case of a TTree, it is more complicated. If one opens a TTree, appends some entries, then writes it out, the behaviour is effectively the same. If, however, one creates a new TTree and writes it out in this way, only the metadata is replaced, effectively making the old data invisible without deleting it. TTree::Delete() can be used to mark all disk space occupied by a TTree as free before overwriting its metadata this way. The kSingleKey option is only used by TCollection::Write() to write a container with a single key instead of each object in the container with its own key.
An object is read from the file into memory via TKey::Read() or via TObject::Read().
The function returns the total number of bytes written to the file. It returns 0 if the object cannot be written.
Reimplemented in TBuffer, TCollection, TDirectory, TDirectoryFile, TFile, TMap, TParallelMergingFile, TSQLFile, TTree, and TXMLFile.
Definition at line 964 of file TObject.cxx.
Write TArray object to buffer.
Simplified version of TBuffer::WriteObject (does not keep track of multiple references to the same array).
Definition at line 81 of file TArray.cxx.
|
protectedinherited |
|
protectedinherited |
|
protectedinherited |
|
privateinherited |
|
protectedinherited |
|
protectedinherited |
|
protectedinherited |
|
protectedinherited |
|
protectedinherited |
Fill area color.
Definition at line 24 of file TAttFill.h.
|
protectedinherited |
Fill area style.
Definition at line 25 of file TAttFill.h.
|
protectedinherited |
|
staticprotectedinherited |
|
staticprivateinherited |
|
protectedinherited |
|
protectedinherited |
Line color.
Definition at line 24 of file TAttLine.h.
|
protectedinherited |
Line style.
Definition at line 25 of file TAttLine.h.
|
protectedinherited |
Line width.
Definition at line 26 of file TAttLine.h.
|
protectedinherited |
Marker color.
Definition at line 24 of file TAttMarker.h.
|
protectedinherited |
Marker size.
Definition at line 26 of file TAttMarker.h.
|
protectedinherited |
Marker style.
Definition at line 25 of file TAttMarker.h.
|
protectedinherited |
|
protectedinherited |
|
protectedinherited |
|
protectedinherited |
|
protectedinherited |
|
protectedinherited |
|
protectedinherited |
|
protectedinherited |
|
protectedinherited |
|
protectedinherited |
|
privateinherited |
