[u/mrichter/AliRoot.git] / PWG2 / RESONANCES / AliRsnListOutput.cxx

//
// Class AliRsnListOutput
//
// This class defines a base classe to implement a Output
// which uses the internal RSN package event format (AliRsnEvent).
// It contains some default flags which turn out to be useful:
//  - a flag to select only the "true" pairs (tracks from same resonance)
//  - a flag to know if the computation is done over two events (mixing)
//
// Any kind of analysis object should be implemented as inheriting from this
// because the AliRsnAnalyzer which executes the analysis will accept a collection
// of such objects, in order to have a unique format of processing method
//
// The user who implements a kind of computation type should inherit from
// this class and override the virtual Outputs defined in it, which
// initialize the final output histogram and define how to process data.
//
//
// author: A. Pulvirenti             (email: alberto.pulvirenti@ct.infn.it)
//

#include <Riostream.h>

#include "AliLog.h"

#include "AliRsnValue.h"
#include "AliRsnLoop.h"

#include "AliRsnListOutput.h"

ClassImp(AliRsnListOutput)

//________________________________________________________________________________________
AliRsnListOutput::AliRsnListOutput(const char *name, AliRsnListOutput::EOut type) :
   TNamed(name, ""),
   fSkipFailed(kTRUE),
   fType(type),
   fSteps(0),
   fValues(0),
   fNValues(0),
   fList(0x0),
   fIndex(-1),
   fArray(0)
{
//
// Constructor.
// Requires a name for this object (which will be used to name the output object)
// and the definition of the output type from the built-in enumeration.
//
}

//________________________________________________________________________________________
AliRsnListOutput::AliRsnListOutput(const AliRsnListOutput &copy) :
   TNamed(copy),
   fSkipFailed(copy.fSkipFailed),
   fType(copy.fType),
   fSteps(copy.fSteps),
   fValues(copy.fValues),
   fNValues(copy.fNValues),
   fList(copy.fList),
   fIndex(copy.fIndex),
   fArray(0)
{
//
// Copy constructor.
// Since the pointer objects must be initialized in a second step,
// they are never copied, and then they are initialized to zero.
//
}

//________________________________________________________________________________________
const AliRsnListOutput& AliRsnListOutput::operator=(const AliRsnListOutput& copy)
{
//
// Assignment operator.
// Same consideration as the copiy constructor. In this case, there is
// the possibility to have the output objects alreasy initialized, but
// they are anyway reset.
//

   TNamed::operator=(copy);

   fSkipFailed = copy.fSkipFailed;
   fType = copy.fType;
   fSteps = copy.fSteps;
   fValues = copy.fValues;
   fNValues = copy.fNValues;
   fList = copy.fList;
   fIndex = copy.fIndex;
   fArray = copy.fArray;

   Reset();

   return (*this);
}

//__________________________________________________________________________________________________
AliRsnListOutput::~AliRsnListOutput()
{
//
// Destructor.
// Deletes the output objects.
//

   Reset();
}

//__________________________________________________________________________________________________
void AliRsnListOutput::Reset()
{
//
// Clear all output objects. In general, only one will be initialized at a time.
//

   fList = 0x0;
}

//_____________________________________________________________________________
void AliRsnListOutput::AddValue(AliRsnValue *value)
{
//
// Adds a value computation object to the list.
//

   fValues.AddLast(value);
}


//________________________________________________________________________________________
Bool_t AliRsnListOutput::Init(const char *prefix, TList *list)
{
//
// Initializes the output for this object.
// What kind of output depends on the 'fType' data member,
// and in case it is a CF container, also on the 'fSteps'.
// The object is named with the following criterion:
// <prefix>_<name>_<type>_<varList>
//

   Int_t i;

   // all output objects are cleared
   Reset();

   // count values and set dimension of arrays
   // do also some checks for a good match between type and output
   fNValues = fValues.GetEntries();
   if (fNValues < 1) {
      AliError("Need at least 1 value");
      return kFALSE;
   }
   if (fType == kHistoDefault && fNValues > 3) {
      AliInfo(Form("NValues = %d > 3 --> cannot use a normal histogram, need to use a sparse", fNValues));
      fType = kHistoSparse;
   }
   
   // resize the output array
   fArray.Set(fNValues);

   // create the name
   TString name(Form("%s_%s", prefix, GetName()));
   AliRsnValue *val = 0x0;
   for (i = 0; i < fNValues; i++) {
      val = GetValue(i);
      if (!val) {
         AliError(Form("Slot %d in value list is NULL", i));
         return kFALSE;
      }
      name += '_';
      name += val->GetName();
   }
   
   // allowed objects
   TObject *object = 0x0;

   // initialize appropriate output object
   // and, if successful, insert into the list
   switch (fType) {
      case kHistoDefault:
         name.Append("_hist");
         object = CreateHistogram(name.Data());
         break;
      case kHistoSparse:
         name.Append("_hsparse");
         object = CreateHistogramSparse(name.Data());
         break;
      case kCFContainer:
         name.Append("_cf");
         object = CreateCFContainer(name.Data());
         break;
      default:
         AliWarning("Wrong type output or initialization failure");
   }
   
   if (object) {
      //AliInfo(Form("[%s]: initializing output '%s' (obj name = '%s') with %d values and format %d [%s]", GetName(), name.Data(), object->GetName(), fNValues, fType, object->ClassName()));
      fList = list;
      fList->Add(object);
      fIndex = fList->IndexOf(object);
      return kTRUE;
   }

   return kFALSE;
}

//________________________________________________________________________________________
TH1* AliRsnListOutput::CreateHistogram(const char *name)
{
//
// Initialize the 'default' TH1 output object.
// In case one of the expected axes is NULL, the initialization fails.
//

   // we expect to have maximum 3 axes in this case
   Int_t i, nbins[3] = {0, 0, 0};
   TArrayD  array[3];
   for (i = 0; i < fNValues; i++) {
      AliRsnValue *val = GetValue(i);
      if (!val) {
         AliError(Form("Expected axis %d is NULL", i));
         return 0x0;
      }
      nbins[i] = GetValue(i)->GetArray().GetSize() - 1;
      array[i] = GetValue(i)->GetArray();
   }
   
   TH1 *hist = 0x0;

   // create histogram depending on the number of axes
   switch (fNValues) {
      case 1:
         hist = new TH1F(name, "", nbins[0], array[0].GetArray());
         break;
      case 2:
         hist = new TH2F(name, "", nbins[0], array[0].GetArray(), nbins[1], array[1].GetArray());
         break;
      case 3:
         hist = new TH3F(name, "", nbins[0], array[0].GetArray(), nbins[1], array[1].GetArray(), nbins[2], array[2].GetArray());
         break;
      default:
         AliError(Form("Wrong number of dimensions: %d", fNValues))
         return 0x0;
   }

   if (hist) hist->Sumw2();
   return hist;
}

//________________________________________________________________________________________
THnSparseF* AliRsnListOutput::CreateHistogramSparse(const char *name)
{
//
// Initialize the THnSparse output object.
// In case one of the expected axes is NULL, the initialization fails.
//

   // retrieve binnings and sizes of all axes
   // since the check for null values is done in Init(),
   // we assume that here they must all be well defined
   Int_t i, *nbins = new Int_t[fNValues];
   TArrayD  *array = new TArrayD[fNValues];
   for (i = 0; i < fNValues; i++) {
      nbins[i] = GetValue(i)->GetArray().GetSize() - 1;
      array[i] = GetValue(i)->GetArray();
   }

   // create histogram
   THnSparseF *hist = new THnSparseF(name, "", fNValues, nbins);
   hist->Sumw2();

   // update the various axes using the definitions given in the array of axes here
   for (i = 0; i < fNValues; i++) {
      hist->GetAxis(i)->Set(nbins[i], array[i].GetArray());
   }

   // clear heap
   delete [] nbins;
   delete [] array;

   return hist;
}

//________________________________________________________________________________________
AliCFContainer* AliRsnListOutput::CreateCFContainer(const char *name)
{
//
// Initialize the AliCFContainer output object.
// In case one of the expected axes is NULL, the initialization fails.
//

   // retrieve binnings and sizes of all axes
   // since the check for null values is done in Init(),
   // we assume that here they must all be well defined
   Int_t i, *nbins = new Int_t[fNValues];
   TArrayD  *array = new TArrayD[fNValues];
   for (i = 0; i < fNValues; i++) {
      nbins[i] = GetValue(i)->GetArray().GetSize() - 1;
      array[i] = GetValue(i)->GetArray();
   }

   // create object
   AliCFContainer *cont = new AliCFContainer(name, "", fSteps, fNValues, nbins);

   // set the bin limits for each axis
   for (i = 0; i < fNValues; i++) {
      cont->SetBinLimits(i, array[i].GetArray());
   }

   // clear heap
   delete [] nbins;
   delete [] array;

   return cont;
}

//________________________________________________________________________________________
Bool_t AliRsnListOutput::Fill(TObject *target, Int_t step)
{
//
// Uses the passed argument to compute all values.
// If all computations were successful, fill the output
// Second argument (step) is needed only in case of CF containers.
// Return value is the AND of all computation successes.
//

   Int_t  i;

   // do computations
   Bool_t globalOK = kTRUE;
   AliRsnValue *val = 0x0;
   for (i = 0; i < fNValues; i++) {
      val = GetValue(i);
      if (!val) {
         AliError("NULL value found");
         return kFALSE;
      }
      globalOK = globalOK && val->Eval(target);
      fArray[i] = (Double_t)val->GetComputedValue();
   }
   if (!globalOK && fSkipFailed) return kFALSE;
   
   // retrieve object
   if (!fList || fIndex < 0) {
      AliError("List not initialized");
      return kFALSE;
   }
   TObject *obj = fList->At(fIndex);
   if (!obj) {
      AliError("Null pointer");
      return kFALSE;
   }
   
   // check
   //AliInfo(Form("[%s] Object index, name, type = %d, %s (%s)", GetName(), fIndex, obj->GetName(), obj->ClassName()));

   // fill output
   if (obj->IsA() == TH1F::Class()) {
      TH1F *h = (TH1F*)obj;
      h->Fill(fArray[0]);
      return kTRUE;
   } else if (obj->IsA() == TH2F::Class()) {
      TH2F *h = (TH2F*)obj;
      h->Fill(fArray[0], fArray[1]);
      return kTRUE;
   } else if (obj->IsA() == TH3F::Class()) {
      TH3F *h = (TH3F*)obj;
      h->Fill(fArray[0], fArray[1], fArray[2]);
      return kTRUE;
   } else if (obj->InheritsFrom(THnSparse::Class())) {
      THnSparseF *h = (THnSparseF*)obj;
      h->Fill(fArray.GetArray());
      return kTRUE;
   } else if (obj->InheritsFrom(AliCFContainer::Class())) {
      AliCFContainer *c = (AliCFContainer*)obj;
      c->Fill(fArray.GetArray(), step);
      return kTRUE;
   } else {
      AliError(Form("Not handled class '%s'", obj->ClassName()));
      return kFALSE;
   }
}
Commit	Line	Data
c865cb1d	1	//
	2	// Class AliRsnListOutput
	3	//
	4	// This class defines a base classe to implement a Output
	5	// which uses the internal RSN package event format (AliRsnEvent).
	6	// It contains some default flags which turn out to be useful:
	7	// - a flag to select only the "true" pairs (tracks from same resonance)
	8	// - a flag to know if the computation is done over two events (mixing)
	9	//
	10	// Any kind of analysis object should be implemented as inheriting from this
	11	// because the AliRsnAnalyzer which executes the analysis will accept a collection
	12	// of such objects, in order to have a unique format of processing method
	13	//
	14	// The user who implements a kind of computation type should inherit from
	15	// this class and override the virtual Outputs defined in it, which
	16	// initialize the final output histogram and define how to process data.
	17	//
	18	//
	19	// author: A. Pulvirenti (email: alberto.pulvirenti@ct.infn.it)
	20	//
	21
	22	#include <Riostream.h>
	23
	24	#include "AliLog.h"
	25
	26	#include "AliRsnValue.h"
	27	#include "AliRsnLoop.h"
	28
	29	#include "AliRsnListOutput.h"
	30
	31	ClassImp(AliRsnListOutput)
	32
	33	//________________________________________________________________________________________
	34	AliRsnListOutput::AliRsnListOutput(const char *name, AliRsnListOutput::EOut type) :
	35	TNamed(name, ""),
f34f960b	36	fSkipFailed(kTRUE),
c865cb1d	37	fType(type),
	38	fSteps(0),
	39	fValues(0),
	40	fNValues(0),
	41	fList(0x0),
	42	fIndex(-1),
	43	fArray(0)
	44	{
	45	//
	46	// Constructor.
	47	// Requires a name for this object (which will be used to name the output object)
	48	// and the definition of the output type from the built-in enumeration.
	49	//
	50	}
	51
	52	//________________________________________________________________________________________
	53	AliRsnListOutput::AliRsnListOutput(const AliRsnListOutput &copy) :
	54	TNamed(copy),
f34f960b	55	fSkipFailed(copy.fSkipFailed),
c865cb1d	56	fType(copy.fType),
	57	fSteps(copy.fSteps),
	58	fValues(copy.fValues),
	59	fNValues(copy.fNValues),
	60	fList(copy.fList),
	61	fIndex(copy.fIndex),
	62	fArray(0)
	63	{
	64	//
	65	// Copy constructor.
	66	// Since the pointer objects must be initialized in a second step,
	67	// they are never copied, and then they are initialized to zero.
	68	//
	69	}
	70
	71	//________________________________________________________________________________________
	72	const AliRsnListOutput& AliRsnListOutput::operator=(const AliRsnListOutput& copy)
	73	{
	74	//
	75	// Assignment operator.
	76	// Same consideration as the copiy constructor. In this case, there is
	77	// the possibility to have the output objects alreasy initialized, but
	78	// they are anyway reset.
	79	//
	80
	81	TNamed::operator=(copy);
	82
f34f960b	83	fSkipFailed = copy.fSkipFailed;
c865cb1d	84	fType = copy.fType;
	85	fSteps = copy.fSteps;
	86	fValues = copy.fValues;
	87	fNValues = copy.fNValues;
	88	fList = copy.fList;
	89	fIndex = copy.fIndex;
	90	fArray = copy.fArray;
	91
	92	Reset();
	93
	94	return (*this);
	95	}
	96
	97	//__________________________________________________________________________________________________
	98	AliRsnListOutput::~AliRsnListOutput()
	99	{
	100	//
	101	// Destructor.
	102	// Deletes the output objects.
	103	//
	104
	105	Reset();
	106	}
	107
	108	//__________________________________________________________________________________________________
	109	void AliRsnListOutput::Reset()
	110	{
	111	//
	112	// Clear all output objects. In general, only one will be initialized at a time.
	113	//
	114
	115	fList = 0x0;
	116	}
	117
	118	//_____________________________________________________________________________
	119	void AliRsnListOutput::AddValue(AliRsnValue *value)
	120	{
	121	//
	122	// Adds a value computation object to the list.
	123	//
	124
	125	fValues.AddLast(value);
	126	}
	127
	128
	129	//________________________________________________________________________________________
	130	Bool_t AliRsnListOutput::Init(const char prefix, TList list)
	131	{
	132	//
	133	// Initializes the output for this object.
	134	// What kind of output depends on the 'fType' data member,
	135	// and in case it is a CF container, also on the 'fSteps'.
	136	// The object is named with the following criterion:
	137	// <prefix>_<name>_<type>_<varList>
	138	//
	139
	140	Int_t i;
	141
	142	// all output objects are cleared
	143	Reset();
	144
	145	// count values and set dimension of arrays
	146	// do also some checks for a good match between type and output
	147	fNValues = fValues.GetEntries();
148	if (fNValues < 1) {
149	AliError("Need at least 1 value");
150	return kFALSE;
151	}
152	if (fType == kHistoDefault && fNValues > 3) {
153	AliInfo(Form("NValues = %d > 3 --> cannot use a normal histogram, need to use a sparse", fNValues));
154	fType = kHistoSparse;
155	}
156
157	// resize the output array
158	fArray.Set(fNValues);
159
160	// create the name
161	TString name(Form("%s_%s", prefix, GetName()));
162	AliRsnValue *val = 0x0;
163	for (i = 0; i < fNValues; i++) {
164	val = GetValue(i);
165	if (!val) {
166	AliError(Form("Slot %d in value list is NULL", i));
167	return kFALSE;
168	}
169	name += '_';
170	name += val->GetName();
171	}
172
173	// allowed objects
174	TObject *object = 0x0;
175
176	// initialize appropriate output object
177	// and, if successful, insert into the list
178	switch (fType) {
179	case kHistoDefault:
180	name.Append("_hist");
181	object = CreateHistogram(name.Data());
182	break;
183	case kHistoSparse:
184	name.Append("_hsparse");
185	object = CreateHistogramSparse(name.Data());
186	break;
187	case kCFContainer:
188	name.Append("_cf");
189	object = CreateCFContainer(name.Data());
190	break;
191	default:
192	AliWarning("Wrong type output or initialization failure");
193	}
194
195	if (object) {
196	//AliInfo(Form("[%s]: initializing output '%s' (obj name = '%s') with %d values and format %d [%s]", GetName(), name.Data(), object->GetName(), fNValues, fType, object->ClassName()));
197	fList = list;
198	fList->Add(object);
199	fIndex = fList->IndexOf(object);
200	return kTRUE;
201	}
202
203	return kFALSE;
204	}
205
206	//________________________________________________________________________________________
207	TH1* AliRsnListOutput::CreateHistogram(const char *name)
208	{
209	//
210	// Initialize the 'default' TH1 output object.
211	// In case one of the expected axes is NULL, the initialization fails.
212	//
213
214	// we expect to have maximum 3 axes in this case
215	Int_t i, nbins[3] = {0, 0, 0};
216	TArrayD array[3];
217	for (i = 0; i < fNValues; i++) {
218	AliRsnValue *val = GetValue(i);
219	if (!val) {
220	AliError(Form("Expected axis %d is NULL", i));
221	return 0x0;
222	}
223	nbins[i] = GetValue(i)->GetArray().GetSize() - 1;
224	array[i] = GetValue(i)->GetArray();
225	}
226
227	TH1 *hist = 0x0;
228
229	// create histogram depending on the number of axes
230	switch (fNValues) {
231	case 1:
232	hist = new TH1F(name, "", nbins[0], array[0].GetArray());
233	break;
234	case 2:
235	hist = new TH2F(name, "", nbins[0], array[0].GetArray(), nbins[1], array[1].GetArray());
236	break;
237	case 3:
238	hist = new TH3F(name, "", nbins[0], array[0].GetArray(), nbins[1], array[1].GetArray(), nbins[2], array[2].GetArray());
239	break;
240	default:
241	AliError(Form("Wrong number of dimensions: %d", fNValues))
242	return 0x0;
243	}
244
245	if (hist) hist->Sumw2();
246	return hist;
247	}
248
249	//________________________________________________________________________________________
250	THnSparseF* AliRsnListOutput::CreateHistogramSparse(const char *name)
251	{
252	//
253	// Initialize the THnSparse output object.
254	// In case one of the expected axes is NULL, the initialization fails.
255	//
256
257	// retrieve binnings and sizes of all axes
258	// since the check for null values is done in Init(),
259	// we assume that here they must all be well defined
260	Int_t i, *nbins = new Int_t[fNValues];
261	TArrayD *array = new TArrayD[fNValues];
262	for (i = 0; i < fNValues; i++) {
263	nbins[i] = GetValue(i)->GetArray().GetSize() - 1;
264	array[i] = GetValue(i)->GetArray();
265	}
266
267	// create histogram
268	THnSparseF *hist = new THnSparseF(name, "", fNValues, nbins);
269	hist->Sumw2();
270
271	// update the various axes using the definitions given in the array of axes here
272	for (i = 0; i < fNValues; i++) {
273	hist->GetAxis(i)->Set(nbins[i], array[i].GetArray());
274	}
275
276	// clear heap
277	delete [] nbins;
278	delete [] array;
279
280	return hist;
281	}
282
283	//________________________________________________________________________________________
284	AliCFContainer* AliRsnListOutput::CreateCFContainer(const char *name)
285	{
286	//
287	// Initialize the AliCFContainer output object.
288	// In case one of the expected axes is NULL, the initialization fails.
289	//
290
291	// retrieve binnings and sizes of all axes
292	// since the check for null values is done in Init(),
293	// we assume that here they must all be well defined
294	Int_t i, *nbins = new Int_t[fNValues];
295	TArrayD *array = new TArrayD[fNValues];
296	for (i = 0; i < fNValues; i++) {
297	nbins[i] = GetValue(i)->GetArray().GetSize() - 1;
298	array[i] = GetValue(i)->GetArray();
299	}
300
301	// create object
302	AliCFContainer *cont = new AliCFContainer(name, "", fSteps, fNValues, nbins);
303
304	// set the bin limits for each axis
305	for (i = 0; i < fNValues; i++) {
306	cont->SetBinLimits(i, array[i].GetArray());
307	}
308
309	// clear heap
310	delete [] nbins;
311	delete [] array;
312
313	return cont;
314	}
315
316	//________________________________________________________________________________________
317	Bool_t AliRsnListOutput::Fill(TObject *target, Int_t step)
318	{
319	//
320	// Uses the passed argument to compute all values.
321	// If all computations were successful, fill the output
322	// Second argument (step) is needed only in case of CF containers.
323	// Return value is the AND of all computation successes.
324	//
325
326	Int_t i;
327
328	// do computations
329	Bool_t globalOK = kTRUE;
330	AliRsnValue *val = 0x0;
331	for (i = 0; i < fNValues; i++) {
332	val = GetValue(i);
333	if (!val) {
334	AliError("NULL value found");
335	return kFALSE;
336	}
337	globalOK = globalOK && val->Eval(target);
338	fArray[i] = (Double_t)val->GetComputedValue();
339	}
f34f960b	340	if (!globalOK && fSkipFailed) return kFALSE;
c865cb1d	341
	342	// retrieve object
	343	if (!fList \|\| fIndex < 0) {
	344	AliError("List not initialized");
	345	return kFALSE;
	346	}
	347	TObject *obj = fList->At(fIndex);
	348	if (!obj) {
	349	AliError("Null pointer");
	350	return kFALSE;
	351	}
	352
	353	// check
	354	//AliInfo(Form("[%s] Object index, name, type = %d, %s (%s)", GetName(), fIndex, obj->GetName(), obj->ClassName()));
	355
	356	// fill output
	357	if (obj->IsA() == TH1F::Class()) {
	358	TH1F h = (TH1F)obj;
	359	h->Fill(fArray[0]);
	360	return kTRUE;
	361	} else if (obj->IsA() == TH2F::Class()) {
	362	TH2F h = (TH2F)obj;
	363	h->Fill(fArray[0], fArray[1]);
	364	return kTRUE;
	365	} else if (obj->IsA() == TH3F::Class()) {
	366	TH3F h = (TH3F)obj;
	367	h->Fill(fArray[0], fArray[1], fArray[2]);
	368	return kTRUE;
	369	} else if (obj->InheritsFrom(THnSparse::Class())) {
	370	THnSparseF h = (THnSparseF)obj;
	371	h->Fill(fArray.GetArray());
	372	return kTRUE;
	373	} else if (obj->InheritsFrom(AliCFContainer::Class())) {
	374	AliCFContainer c = (AliCFContainer)obj;
	375	c->Fill(fArray.GetArray(), step);
	376	return kTRUE;
	377	} else {
	378	AliError(Form("Not handled class '%s'", obj->ClassName()));
	379	return kFALSE;
	380	}
	381	}