PLearn 0.1
Public Member Functions | Static Public Member Functions | Static Public Attributes | Static Protected Member Functions | Protected Attributes | Private Types
PLearn::StderrStatsIterator Class Reference

#include <StatsIterator.h>

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List of all members.

Public Member Functions

virtual string info () const
 Returns a bit more informative string about object (default returns classname())
virtual void init (int inputsize)
 Call this method once with the correct inputsize.
virtual void update (const Vec &input)
 Then iterate over the data set and call this method for each row.
virtual bool finish ()
virtual string classname () const
virtual OptionListgetOptionList () const
virtual OptionMapgetOptionMap () const
virtual RemoteMethodMapgetRemoteMethodMap () const
virtual StderrStatsIteratordeepCopy (CopiesMap &copies) const
virtual void makeDeepCopyFromShallowCopy (CopiesMap &copies)
 Does the necessary operations to transform a shallow copy (this) into a deep copy by deep-copying all the members that need to be.
virtual void oldwrite (ostream &out) const

Static Public Member Functions

static string _classname_ ()
static OptionList_getOptionList_ ()
static RemoteMethodMap_getRemoteMethodMap_ ()
static Object_new_instance_for_typemap_ ()
static bool _isa_ (const Object *o)
static void _static_initialize_ ()
static const PPathdeclaringFile ()

Static Public Attributes

static StaticInitializer _static_initializer_

Static Protected Member Functions

static void declareOptions (OptionList &ol)
 Declare options (data fields) for the class.

Protected Attributes

Vec meansquared
Vec mean
TVec< intnsamples

Private Types

typedef StatsIterator inherited

Detailed Description

Definition at line 192 of file StatsIterator.h.


Member Typedef Documentation

Reimplemented from PLearn::StatsIterator.

Definition at line 194 of file StatsIterator.h.


Member Function Documentation

string PLearn::StderrStatsIterator::_classname_ ( ) [static]

Reimplemented from PLearn::StatsIterator.

Definition at line 280 of file StatsIterator.cc.

OptionList & PLearn::StderrStatsIterator::_getOptionList_ ( ) [static]

Reimplemented from PLearn::StatsIterator.

Definition at line 280 of file StatsIterator.cc.

RemoteMethodMap & PLearn::StderrStatsIterator::_getRemoteMethodMap_ ( ) [static]

Reimplemented from PLearn::StatsIterator.

Definition at line 280 of file StatsIterator.cc.

bool PLearn::StderrStatsIterator::_isa_ ( const Object o) [static]

Reimplemented from PLearn::StatsIterator.

Definition at line 280 of file StatsIterator.cc.

Object * PLearn::StderrStatsIterator::_new_instance_for_typemap_ ( ) [static]

Reimplemented from PLearn::Object.

Definition at line 280 of file StatsIterator.cc.

StaticInitializer StderrStatsIterator::_static_initializer_ & PLearn::StderrStatsIterator::_static_initialize_ ( ) [static]

Reimplemented from PLearn::StatsIterator.

Definition at line 280 of file StatsIterator.cc.

string PLearn::StderrStatsIterator::classname ( ) const [virtual]

Reimplemented from PLearn::Object.

Definition at line 280 of file StatsIterator.cc.

void PLearn::StderrStatsIterator::declareOptions ( OptionList ol) [static, protected]

Declare options (data fields) for the class.

Redefine this in subclasses: call declareOption(...) for each option, and then call inherited::declareOptions(options). Please call the inherited method AT THE END to get the options listed in a consistent order (from most recently defined to least recently defined).

  static void MyDerivedClass::declareOptions(OptionList& ol)
  {
      declareOption(ol, "inputsize", &MyObject::inputsize_,
                    OptionBase::buildoption,
                    "The size of the input; it must be provided");
      declareOption(ol, "weights", &MyObject::weights,
                    OptionBase::learntoption,
                    "The learned model weights");
      inherited::declareOptions(ol);
  }
Parameters:
olList of options that is progressively being constructed for the current class.

Reimplemented from PLearn::StatsIterator.

Definition at line 318 of file StatsIterator.cc.

References PLearn::declareOption(), PLearn::OptionBase::learntoption, mean, meansquared, and nsamples.

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static const PPath& PLearn::StderrStatsIterator::declaringFile ( ) [inline, static]

Reimplemented from PLearn::StatsIterator.

Definition at line 206 of file StatsIterator.h.

:
    static void declareOptions(OptionList& ol);
StderrStatsIterator * PLearn::StderrStatsIterator::deepCopy ( CopiesMap copies) const [virtual]

Reimplemented from PLearn::StatsIterator.

Definition at line 280 of file StatsIterator.cc.

bool PLearn::StderrStatsIterator::finish ( ) [virtual]

Call this method when all the data has been shown (through update) If the method returns false, then a further pass through the data is required.

Implements PLearn::StatsIterator.

Definition at line 304 of file StatsIterator.cc.

References i, PLearn::mean(), PLearn::sqrt(), and PLearn::squareSubtract().

{
    for (int i=0;i<mean.length();i++)
    {
        mean[i] /= nsamples[i];
        meansquared[i] /= nsamples[i]-1;
    }
    squareSubtract(meansquared, mean);
    for (int i = 0; i < mean.length(); i++) {
        result[i] = sqrt(meansquared[i] / real(nsamples[i]));
    }
    return true;
}

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OptionList & PLearn::StderrStatsIterator::getOptionList ( ) const [virtual]

Reimplemented from PLearn::Object.

Definition at line 280 of file StatsIterator.cc.

OptionMap & PLearn::StderrStatsIterator::getOptionMap ( ) const [virtual]

Reimplemented from PLearn::Object.

Definition at line 280 of file StatsIterator.cc.

RemoteMethodMap & PLearn::StderrStatsIterator::getRemoteMethodMap ( ) const [virtual]

Reimplemented from PLearn::Object.

Definition at line 280 of file StatsIterator.cc.

virtual string PLearn::StderrStatsIterator::info ( ) const [inline, virtual]

Returns a bit more informative string about object (default returns classname())

Returns:
Information about the object

Reimplemented from PLearn::Object.

Definition at line 202 of file StatsIterator.h.

{ return "std_err"; }
void PLearn::StderrStatsIterator::init ( int  inputsize) [virtual]

Call this method once with the correct inputsize.

Implements PLearn::StatsIterator.

Definition at line 289 of file StatsIterator.cc.

References PLearn::mean().

{ 
    // We do not use resize on purpose, so 
    // that the previous result Vec does not get overwritten
    meansquared = Vec(inputsize);
    mean = Vec(inputsize);
    nsamples.resize(inputsize);
    nsamples.clear();
} 

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void PLearn::StderrStatsIterator::makeDeepCopyFromShallowCopy ( CopiesMap copies) [virtual]

Does the necessary operations to transform a shallow copy (this) into a deep copy by deep-copying all the members that need to be.

This needs to be overridden by every class that adds "complex" data members to the class, such as Vec, Mat, PP<Something>, etc. Typical implementation:

  void CLASS_OF_THIS::makeDeepCopyFromShallowCopy(CopiesMap& copies)
  {
      inherited::makeDeepCopyFromShallowCopy(copies);
      deepCopyField(complex_data_member1, copies);
      deepCopyField(complex_data_member2, copies);
      ...
  }
Parameters:
copiesA map used by the deep-copy mechanism to keep track of already-copied objects.

Reimplemented from PLearn::StatsIterator.

Definition at line 282 of file StatsIterator.cc.

References PLearn::deepCopyField(), and PLearn::mean().

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void PLearn::StderrStatsIterator::oldwrite ( ostream &  out) const [virtual]

Reimplemented from PLearn::StatsIterator.

Definition at line 332 of file StatsIterator.cc.

References PLearn::mean(), PLearn::write(), PLearn::writeField(), PLearn::writeFooter(), and PLearn::writeHeader().

{
    writeHeader(out,"StderrStatsIterator");
    inherited::write(out);
    writeField(out,"mean",mean);
    writeField(out,"meansquared",meansquared);
    writeField(out,"nsamples",nsamples);
    writeFooter(out,"StderrStatsIterator");
}

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void PLearn::StderrStatsIterator::update ( const Vec input) [virtual]

Then iterate over the data set and call this method for each row.

Implements PLearn::StatsIterator.

Definition at line 299 of file StatsIterator.cc.

References PLearn::addXandX2IfNonMissing(), and PLearn::mean().

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Member Data Documentation

Reimplemented from PLearn::StatsIterator.

Definition at line 206 of file StatsIterator.h.

Definition at line 198 of file StatsIterator.h.

Referenced by declareOptions().

Definition at line 197 of file StatsIterator.h.

Referenced by declareOptions().

Definition at line 199 of file StatsIterator.h.

Referenced by declareOptions().


The documentation for this class was generated from the following files:
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