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PLearn 0.1
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#include <StatsIterator.h>


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 OptionList & | getOptionList () const |
| virtual OptionMap & | getOptionMap () const |
| virtual RemoteMethodMap & | getRemoteMethodMap () const |
| virtual StddevStatsIterator * | deepCopy (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 PPath & | declaringFile () |
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< int > | nsamples |
Private Types | |
| typedef StatsIterator | inherited |
Definition at line 163 of file StatsIterator.h.
typedef StatsIterator PLearn::StddevStatsIterator::inherited [private] |
Reimplemented from PLearn::StatsIterator.
Definition at line 165 of file StatsIterator.h.
| string PLearn::StddevStatsIterator::_classname_ | ( | ) | [static] |
Reimplemented from PLearn::StatsIterator.
Definition at line 200 of file StatsIterator.cc.
| OptionList & PLearn::StddevStatsIterator::_getOptionList_ | ( | ) | [static] |
Reimplemented from PLearn::StatsIterator.
Definition at line 200 of file StatsIterator.cc.
| RemoteMethodMap & PLearn::StddevStatsIterator::_getRemoteMethodMap_ | ( | ) | [static] |
Reimplemented from PLearn::StatsIterator.
Definition at line 200 of file StatsIterator.cc.
Reimplemented from PLearn::StatsIterator.
Definition at line 200 of file StatsIterator.cc.
| Object * PLearn::StddevStatsIterator::_new_instance_for_typemap_ | ( | ) | [static] |
Reimplemented from PLearn::Object.
Definition at line 200 of file StatsIterator.cc.
| StaticInitializer StddevStatsIterator::_static_initializer_ & PLearn::StddevStatsIterator::_static_initialize_ | ( | ) | [static] |
Reimplemented from PLearn::StatsIterator.
Definition at line 200 of file StatsIterator.cc.
| string PLearn::StddevStatsIterator::classname | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 200 of file StatsIterator.cc.
| void PLearn::StddevStatsIterator::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); }
| ol | List of options that is progressively being constructed for the current class. |
Reimplemented from PLearn::StatsIterator.
Definition at line 240 of file StatsIterator.cc.
References PLearn::declareOption(), PLearn::OptionBase::learntoption, mean, meansquared, and nsamples.
{
declareOption(ol, "mean", &StddevStatsIterator::mean, OptionBase::learntoption,
" mean\n");
declareOption(ol, "meansquared", &StddevStatsIterator::meansquared, OptionBase::learntoption,
" meansquared\n");
declareOption(ol, "nsamples", &StddevStatsIterator::nsamples, OptionBase::learntoption,
" nsamples\n");
inherited::declareOptions(ol);
}

| static const PPath& PLearn::StddevStatsIterator::declaringFile | ( | ) | [inline, static] |
Reimplemented from PLearn::StatsIterator.
Definition at line 177 of file StatsIterator.h.
:
static void declareOptions(OptionList& ol);
| StddevStatsIterator * PLearn::StddevStatsIterator::deepCopy | ( | CopiesMap & | copies | ) | const [virtual] |
Reimplemented from PLearn::StatsIterator.
Definition at line 200 of file StatsIterator.cc.
| bool PLearn::StddevStatsIterator::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 224 of file StatsIterator.cc.
References i, PLearn::mean(), n, and PLearn::sqrt().
{
Vec square_mean(mean.length());
for (int i=0;i<mean.length();i++)
{
//mean[i] /= nsamples[i];
real n = nsamples[i];
square_mean[i] = mean[i]*mean[i]/(n*(n-1.0));
meansquared[i] /= n-1.0;
}
//squareSubtract(meansquared, mean);
meansquared -= square_mean;
result = sqrt(meansquared);
return true;
}

| OptionList & PLearn::StddevStatsIterator::getOptionList | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 200 of file StatsIterator.cc.
| OptionMap & PLearn::StddevStatsIterator::getOptionMap | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 200 of file StatsIterator.cc.
| RemoteMethodMap & PLearn::StddevStatsIterator::getRemoteMethodMap | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 200 of file StatsIterator.cc.
| virtual string PLearn::StddevStatsIterator::info | ( | ) | const [inline, virtual] |
Returns a bit more informative string about object (default returns classname())
Reimplemented from PLearn::Object.
Definition at line 173 of file StatsIterator.h.
{ return "std_dev"; }
| void PLearn::StddevStatsIterator::init | ( | int | inputsize | ) | [virtual] |
Call this method once with the correct inputsize.
Implements PLearn::StatsIterator.
Definition at line 209 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();
}

| void PLearn::StddevStatsIterator::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); ... }
| copies | A map used by the deep-copy mechanism to keep track of already-copied objects. |
Reimplemented from PLearn::StatsIterator.
Definition at line 202 of file StatsIterator.cc.
References PLearn::deepCopyField(), and PLearn::mean().
{
inherited::makeDeepCopyFromShallowCopy(copies);
deepCopyField(mean, copies);
deepCopyField(meansquared, copies);
}

| void PLearn::StddevStatsIterator::oldwrite | ( | ostream & | out | ) | const [virtual] |
Reimplemented from PLearn::StatsIterator.
Definition at line 254 of file StatsIterator.cc.
References PLearn::mean(), PLearn::write(), PLearn::writeField(), PLearn::writeFooter(), and PLearn::writeHeader().
{
writeHeader(out,"StddevStatsIterator");
inherited::write(out);
writeField(out,"mean",mean);
writeField(out,"meansquared",meansquared);
writeField(out,"nsamples",nsamples);
writeFooter(out,"StddevStatsIterator");
}

| void PLearn::StddevStatsIterator::update | ( | const Vec & | input | ) | [virtual] |
Then iterate over the data set and call this method for each row.
Implements PLearn::StatsIterator.
Definition at line 219 of file StatsIterator.cc.
References PLearn::addXandX2IfNonMissing(), and PLearn::mean().
{
addXandX2IfNonMissing(input,nsamples,mean,meansquared);
}

Reimplemented from PLearn::StatsIterator.
Definition at line 177 of file StatsIterator.h.
Vec PLearn::StddevStatsIterator::mean [protected] |
Definition at line 169 of file StatsIterator.h.
Referenced by declareOptions().
Vec PLearn::StddevStatsIterator::meansquared [protected] |
Definition at line 168 of file StatsIterator.h.
Referenced by declareOptions().
TVec<int> PLearn::StddevStatsIterator::nsamples [protected] |
Definition at line 170 of file StatsIterator.h.
Referenced by declareOptions().
1.7.4