PLearn 0.1
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#include <ConditionalMeanImputationVMatrix.h>
Public Member Functions | |
ConditionalMeanImputationVMatrix () | |
virtual | ~ConditionalMeanImputationVMatrix () |
virtual void | build () |
Simply calls inherited::build() then build_(). | |
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 | getExample (int i, Vec &input, Vec &target, real &weight) |
Default version calls getSubRow based on inputsize_ targetsize_ weightsize_ But exotic subclasses may construct, input, target and weight however they please. | |
virtual real | get (int i, int j) const |
This method must be implemented in all subclasses. | |
virtual void | put (int i, int j, real value) |
This method must be implemented in all subclasses of writable matrices. | |
virtual void | getSubRow (int i, int j, Vec v) const |
It is suggested that this method be implemented in subclasses to speed up accesses (default version repeatedly calls get(i,j) which may have a significant overhead). | |
virtual void | putSubRow (int i, int j, Vec v) |
It is suggested that this method be implemented in subclasses of writable matrices to speed up accesses (default version repeatedly calls put(i,j,value) which may have a significant overhead) | |
virtual void | appendRow (Vec v) |
This method must be implemented for matrices that are allowed to grow. | |
virtual void | insertRow (int i, Vec v) |
This method must be implemented for matrices that are allowed to grow. | |
virtual void | getRow (int i, Vec v) const |
These methods do not usually need to be overridden in subclasses (default versions call getSubRow, which should do just fine) | |
virtual void | putRow (int i, Vec v) |
virtual void | getColumn (int i, Vec v) const |
Copies column i into v (which must have appropriate length equal to the VMat's length). | |
virtual string | classname () const |
virtual OptionList & | getOptionList () const |
virtual OptionMap & | getOptionMap () const |
virtual RemoteMethodMap & | getRemoteMethodMap () const |
virtual ConditionalMeanImputationVMatrix * | deepCopy (CopiesMap &copies) const |
Static Public Member Functions | |
static void | declareOptions (OptionList &ol) |
Declares this class' options. | |
static string | _classname_ () |
ConditionalMeanImputationVMatrix. | |
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 () |
Public Attributes | |
string | condmean_dir |
The directory in the source metadatadir housing the variable conditional mean files. | |
Mat | condmean |
The matrix of conditional means. | |
TVec< int > | condmean_col_ref |
The cross reference between columns of source and condmean. | |
Static Public Attributes | |
static StaticInitializer | _static_initializer_ |
Private Types | |
typedef ImputationVMatrix | inherited |
Private Member Functions | |
void | build_ () |
This does the actual building. | |
void | loadCondMeanMatrix () |
Private Attributes | |
int | source_length |
int | source_width |
int | source_inputsize |
int | source_targetsize |
int | source_weightsize |
int | source_row |
int | source_col |
PPath | source_metadata |
TVec< string > | source_names |
StatsCollector | source_stats |
Definition at line 53 of file ConditionalMeanImputationVMatrix.h.
typedef ImputationVMatrix PLearn::ConditionalMeanImputationVMatrix::inherited [private] |
Reimplemented from PLearn::ImputationVMatrix.
Definition at line 55 of file ConditionalMeanImputationVMatrix.h.
PLearn::ConditionalMeanImputationVMatrix::ConditionalMeanImputationVMatrix | ( | ) |
Definition at line 60 of file ConditionalMeanImputationVMatrix.cc.
{ }
PLearn::ConditionalMeanImputationVMatrix::~ConditionalMeanImputationVMatrix | ( | ) | [virtual] |
Definition at line 64 of file ConditionalMeanImputationVMatrix.cc.
{ }
string PLearn::ConditionalMeanImputationVMatrix::_classname_ | ( | ) | [static] |
ConditionalMeanImputationVMatrix.
Reimplemented from PLearn::ImputationVMatrix.
Definition at line 58 of file ConditionalMeanImputationVMatrix.cc.
OptionList & PLearn::ConditionalMeanImputationVMatrix::_getOptionList_ | ( | ) | [static] |
Reimplemented from PLearn::ImputationVMatrix.
Definition at line 58 of file ConditionalMeanImputationVMatrix.cc.
RemoteMethodMap & PLearn::ConditionalMeanImputationVMatrix::_getRemoteMethodMap_ | ( | ) | [static] |
Reimplemented from PLearn::ImputationVMatrix.
Definition at line 58 of file ConditionalMeanImputationVMatrix.cc.
Reimplemented from PLearn::ImputationVMatrix.
Definition at line 58 of file ConditionalMeanImputationVMatrix.cc.
Object * PLearn::ConditionalMeanImputationVMatrix::_new_instance_for_typemap_ | ( | ) | [static] |
Reimplemented from PLearn::Object.
Definition at line 58 of file ConditionalMeanImputationVMatrix.cc.
StaticInitializer ConditionalMeanImputationVMatrix::_static_initializer_ & PLearn::ConditionalMeanImputationVMatrix::_static_initialize_ | ( | ) | [static] |
Reimplemented from PLearn::ImputationVMatrix.
Definition at line 58 of file ConditionalMeanImputationVMatrix.cc.
void PLearn::ConditionalMeanImputationVMatrix::appendRow | ( | Vec | v | ) | [virtual] |
This method must be implemented for matrices that are allowed to grow.
Reimplemented from PLearn::VMatrix.
Definition at line 127 of file ConditionalMeanImputationVMatrix.cc.
References PLERROR.
{ PLERROR("In ConditionalMeanImputationVMatrix::appendRow not implemented"); }
void PLearn::ConditionalMeanImputationVMatrix::build | ( | ) | [virtual] |
Simply calls inherited::build() then build_().
Reimplemented from PLearn::ImputationVMatrix.
Definition at line 79 of file ConditionalMeanImputationVMatrix.cc.
{ inherited::build(); build_(); }
void PLearn::ConditionalMeanImputationVMatrix::build_ | ( | ) | [private] |
This does the actual building.
Reimplemented from PLearn::ImputationVMatrix.
Definition at line 160 of file ConditionalMeanImputationVMatrix.cc.
References PLERROR.
{ if (!source) PLERROR("In ConditionalMeanImputationVMatrix::source vmat must be supplied"); loadCondMeanMatrix(); testResultantVMatrix(); }
string PLearn::ConditionalMeanImputationVMatrix::classname | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 58 of file ConditionalMeanImputationVMatrix.cc.
void PLearn::ConditionalMeanImputationVMatrix::declareOptions | ( | OptionList & | ol | ) | [static] |
Declares this class' options.
Reimplemented from PLearn::ImputationVMatrix.
Definition at line 68 of file ConditionalMeanImputationVMatrix.cc.
References PLearn::OptionBase::buildoption, condmean, condmean_col_ref, condmean_dir, PLearn::declareOption(), and PLearn::OptionBase::learntoption.
{ declareOption(ol, "condmean_dir", &ConditionalMeanImputationVMatrix::condmean_dir, OptionBase::buildoption, "The directory in the source metadatadir housing the variable conditional mean files.\n"); declareOption(ol, "condmean", &ConditionalMeanImputationVMatrix::condmean, OptionBase::learntoption, "The matrix of conditional means.\n"); declareOption(ol, "condmean_col_ref", &ConditionalMeanImputationVMatrix::condmean_col_ref, OptionBase::learntoption, "The cross reference between columns of source and condmean.\n"); inherited::declareOptions(ol); }
static const PPath& PLearn::ConditionalMeanImputationVMatrix::declaringFile | ( | ) | [inline, static] |
Reimplemented from PLearn::ImputationVMatrix.
Definition at line 105 of file ConditionalMeanImputationVMatrix.h.
ConditionalMeanImputationVMatrix * PLearn::ConditionalMeanImputationVMatrix::deepCopy | ( | CopiesMap & | copies | ) | const [virtual] |
Reimplemented from PLearn::ImputationVMatrix.
Definition at line 58 of file ConditionalMeanImputationVMatrix.cc.
This method must be implemented in all subclasses.
Returns element (i,j).
Implements PLearn::VMatrix.
Definition at line 101 of file ConditionalMeanImputationVMatrix.cc.
References PLearn::is_missing(), and PLERROR.
{ real variable_value = source->get(i, j); if (is_missing(variable_value) && condmean_col_ref[j] >= 0) return condmean(i, condmean_col_ref[j]); else if (is_missing(variable_value)) PLERROR("In ConditionalMeanImputationVMatrix::getExample(%d,%d) we have a missing value that haven't been assigned a value",i,j); return variable_value; }
Copies column i into v (which must have appropriate length equal to the VMat's length).
Reimplemented from PLearn::VMatrix.
Definition at line 150 of file ConditionalMeanImputationVMatrix.cc.
References i, PLearn::is_missing(), PLearn::TVec< T >::length(), and PLERROR.
{ source-> getColumn(i, v); for (int source_row = 0; source_row < v->length(); source_row++) if (is_missing(v[source_row]) && condmean_col_ref[i] >= 0) v[source_row] = condmean(source_row, condmean_col_ref[i]); else if (is_missing(v[source_row])) PLERROR("In ConditionalMeanImputationVMatrix::getColumn(%d,vec) we have a missing value in row %d that haven't been assigned a value",i,source_row); }
void PLearn::ConditionalMeanImputationVMatrix::getExample | ( | int | i, |
Vec & | input, | ||
Vec & | target, | ||
real & | weight | ||
) | [virtual] |
Default version calls getSubRow based on inputsize_ targetsize_ weightsize_ But exotic subclasses may construct, input, target and weight however they please.
If not a weighted matrix, weight should be set to default value 1.
Reimplemented from PLearn::VMatrix.
Definition at line 93 of file ConditionalMeanImputationVMatrix.cc.
References PLearn::is_missing(), PLearn::TVec< T >::length(), and PLERROR.
{ source->getExample(i, input, target, weight); for (int source_col = 0; source_col < input->length(); source_col++) if (is_missing(input[source_col]) && condmean_col_ref[source_col] >= 0) input[source_col] = condmean(i, condmean_col_ref[source_col]); else if (is_missing(input[source_col])) PLERROR("In ConditionalMeanImputationVMatrix::getExample(%d,vec,vec,vec) we have a missing value in column %d that haven't been assigned a value",i,source_col); }
OptionList & PLearn::ConditionalMeanImputationVMatrix::getOptionList | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 58 of file ConditionalMeanImputationVMatrix.cc.
OptionMap & PLearn::ConditionalMeanImputationVMatrix::getOptionMap | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 58 of file ConditionalMeanImputationVMatrix.cc.
RemoteMethodMap & PLearn::ConditionalMeanImputationVMatrix::getRemoteMethodMap | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 58 of file ConditionalMeanImputationVMatrix.cc.
These methods do not usually need to be overridden in subclasses (default versions call getSubRow, which should do just fine)
Copies row i into v (which must have appropriate length equal to the VMat's width).
Reimplemented from PLearn::VMatrix.
Definition at line 137 of file ConditionalMeanImputationVMatrix.cc.
References PLearn::is_missing(), PLearn::TVec< T >::length(), and PLERROR.
{ source-> getRow(i, v); for (int source_col = 0; source_col < v->length(); source_col++) if (is_missing(v[source_col]) && condmean_col_ref[source_col] >= 0) v[source_col] = condmean(i, condmean_col_ref[source_col]); else if (is_missing(v[source_col])) PLERROR("In ConditionalMeanImputationVMatrix::getRow(%d,vec) we have a missing value in column %d that haven't been assigned a value",i,source_col); }
It is suggested that this method be implemented in subclasses to speed up accesses (default version repeatedly calls get(i,j) which may have a significant overhead).
Fills v with the subrow i lying between columns j (inclusive) and j+v.length() (exclusive).
Reimplemented from PLearn::VMatrix.
Definition at line 114 of file ConditionalMeanImputationVMatrix.cc.
References PLearn::is_missing(), PLearn::TVec< T >::length(), and PLERROR.
{ source->getSubRow(i, j, v); for (int source_col = 0; source_col < v->length(); source_col++) if (is_missing(v[source_col])) v[source_col] = condmean(i, condmean_col_ref[source_col + j]); else if (is_missing(v[source_col])) PLERROR("In ConditionalMeanImputationVMatrix::getSubRow(%d,%d,vec) we have a missing value in colomn %d that haven't been assigned a value",i,j,source_col); }
This method must be implemented for matrices that are allowed to grow.
Reimplemented from PLearn::VMatrix.
Definition at line 132 of file ConditionalMeanImputationVMatrix.cc.
References PLERROR.
{ PLERROR("In ConditionalMeanImputationVMatrix::insertRow not implemented"); }
void PLearn::ConditionalMeanImputationVMatrix::loadCondMeanMatrix | ( | ) | [private] |
Definition at line 167 of file ConditionalMeanImputationVMatrix.cc.
References PLearn::isfile(), PLearn::VMat::length(), and PLERROR.
{ // initialize source dataset source_length = source->length(); source_width = source->width(); source_inputsize = source->inputsize(); source_targetsize = source->targetsize(); source_weightsize = source->weightsize(); source_names.resize(source_width); source_names = source->fieldNames(); source_metadata = source->getMetaDataDir(); length_ = source_length; width_ = source_width; inputsize_ = source_inputsize; targetsize_ = source_targetsize; weightsize_ = source_weightsize; declareFieldNames(source_names); // count the # of variables with missing values in the source datasets. // create a matrix in memory with this number of columns and keep cross reference of columns. int count_variable_with_missing = 0; condmean_col_ref.resize(source_width); condmean_col_ref.fill(-1); for (source_col = 0; source_col < source_width; source_col++) { source_stats = source->getStats(source_col); if (source_stats.nmissing() <= 0) continue; condmean_col_ref[source_col] = count_variable_with_missing; count_variable_with_missing += 1; } condmean.resize(source_length, count_variable_with_missing); // for each variable with missing value, // look for the (cond_mean_dir (/TreeCondMean/dir/) + field_name + /Split0/test1_outputs.pmat) file in the metadatadir; // add its column 0 as a column of the condmean matrix. for (source_col = 0; source_col < source_width; source_col++) { source_stats = source->getStats(source_col); if (source_stats.nmissing() <= 0) continue; int condmean_col = condmean_col_ref[source_col]; PPath condmean_variable_file_name = source_metadata + "/" + condmean_dir + "/dir/" + source_names[source_col] + "/Split0/test1_outputs.pmat"; if (!isfile(condmean_variable_file_name)) PLERROR("In ConditionalMeanImputationVMatrix::A conditional mean file(%s) was not found for variable %s", condmean_variable_file_name.c_str(),source_names[source_col].c_str()); VMat condmean_variable_file = new FileVMatrix(condmean_variable_file_name, false); if (condmean_variable_file->length() != source_length) PLERROR("In ConditionalMeanImputationVMatrix::Source and conditional mean file length are not equal for variable %s", source_names[source_col].c_str()); for (source_row = 0; source_row < source_length; source_row++) condmean(source_row, condmean_col) = condmean_variable_file->get(source_row, 0); } }
void PLearn::ConditionalMeanImputationVMatrix::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::ImputationVMatrix.
Definition at line 85 of file ConditionalMeanImputationVMatrix.cc.
References PLearn::deepCopyField().
{ deepCopyField(condmean_dir, copies); deepCopyField(condmean, copies); deepCopyField(condmean_col_ref, copies); inherited::makeDeepCopyFromShallowCopy(copies); }
This method must be implemented in all subclasses of writable matrices.
Sets element (i,j) to value.
Reimplemented from PLearn::VMatrix.
Definition at line 109 of file ConditionalMeanImputationVMatrix.cc.
References PLERROR.
{ PLERROR("In ConditionalMeanImputationVMatrix::put not implemented"); }
Reimplemented from PLearn::VMatrix.
Definition at line 145 of file ConditionalMeanImputationVMatrix.cc.
References PLERROR.
{ PLERROR("In ConditionalMeanImputationVMatrix::putRow not implemented"); }
It is suggested that this method be implemented in subclasses of writable matrices to speed up accesses (default version repeatedly calls put(i,j,value) which may have a significant overhead)
Reimplemented from PLearn::VMatrix.
Definition at line 122 of file ConditionalMeanImputationVMatrix.cc.
References PLERROR.
{ PLERROR("In ConditionalMeanImputationVMatrix::putSubRow not implemented"); }
Reimplemented from PLearn::ImputationVMatrix.
Definition at line 105 of file ConditionalMeanImputationVMatrix.h.
The matrix of conditional means.
Definition at line 63 of file ConditionalMeanImputationVMatrix.h.
Referenced by declareOptions().
The cross reference between columns of source and condmean.
Definition at line 66 of file ConditionalMeanImputationVMatrix.h.
Referenced by declareOptions().
The directory in the source metadatadir housing the variable conditional mean files.
Definition at line 60 of file ConditionalMeanImputationVMatrix.h.
Referenced by declareOptions().
Definition at line 96 of file ConditionalMeanImputationVMatrix.h.
Definition at line 92 of file ConditionalMeanImputationVMatrix.h.
Definition at line 90 of file ConditionalMeanImputationVMatrix.h.
Definition at line 97 of file ConditionalMeanImputationVMatrix.h.
TVec<string> PLearn::ConditionalMeanImputationVMatrix::source_names [private] |
Definition at line 98 of file ConditionalMeanImputationVMatrix.h.
Definition at line 95 of file ConditionalMeanImputationVMatrix.h.
Definition at line 99 of file ConditionalMeanImputationVMatrix.h.
Definition at line 93 of file ConditionalMeanImputationVMatrix.h.
Definition at line 94 of file ConditionalMeanImputationVMatrix.h.
Definition at line 91 of file ConditionalMeanImputationVMatrix.h.