aGrUM 3.0.0
a C++ library for (probabilistic) graphical models
gum::learning::IDatabaseTable< T_DATA > Member List

This is the complete list of members for gum::learning::IDatabaseTable< T_DATA >, including all inherited members.

begin() constgum::learning::IDatabaseTable< T_DATA >
beginSafe() constgum::learning::IDatabaseTable< T_DATA >
clear()gum::learning::IDatabaseTable< T_DATA >virtual
clone() const =0gum::learning::IDatabaseTable< T_DATA >pure virtual
columnFromVariableName(std::string_view name) constgum::learning::IDatabaseTable< T_DATA >
columnsFromVariableName(std::string_view name) constgum::learning::IDatabaseTable< T_DATA >
const_iterator typedefgum::learning::IDatabaseTable< T_DATA >
const_iterator_safe typedefgum::learning::IDatabaseTable< T_DATA >
const_pointer typedefgum::learning::IDatabaseTable< T_DATA >
const_reference typedefgum::learning::IDatabaseTable< T_DATA >
content() const noexceptgum::learning::IDatabaseTable< T_DATA >
DBVector typedefgum::learning::IDatabaseTable< T_DATA >
difference_type typedefgum::learning::IDatabaseTable< T_DATA >
empty() const noexceptgum::learning::IDatabaseTable< T_DATA >
end() const noexceptgum::learning::IDatabaseTable< T_DATA >
endSafe() const noexceptgum::learning::IDatabaseTable< T_DATA >
eraseAllRows()gum::learning::IDatabaseTable< T_DATA >
eraseFirstRow()gum::learning::IDatabaseTable< T_DATA >
eraseFirstRows(const std::size_t k)gum::learning::IDatabaseTable< T_DATA >
eraseLastRow()gum::learning::IDatabaseTable< T_DATA >
eraseLastRows(const std::size_t k)gum::learning::IDatabaseTable< T_DATA >
eraseRow(std::size_t index)gum::learning::IDatabaseTable< T_DATA >
eraseRows(std::size_t deb, std::size_t end)gum::learning::IDatabaseTable< T_DATA >
False enum valuegum::learning::IDatabaseTable< T_DATA >
Handler classgum::learning::IDatabaseTable< T_DATA >friend
handler() constgum::learning::IDatabaseTable< T_DATA >
HandlerSafe classgum::learning::IDatabaseTable< T_DATA >friend
handlerSafe() constgum::learning::IDatabaseTable< T_DATA >
has_row_missing_val_gum::learning::IDatabaseTable< T_DATA >protected
hasMissingValues() constgum::learning::IDatabaseTable< T_DATA >
hasMissingValues(const std::size_t k) constgum::learning::IDatabaseTable< T_DATA >
IDatabaseTable(const MissingValType &missing_symbols, const std::vector< std::string > &var_names)gum::learning::IDatabaseTable< T_DATA >
IDatabaseTable(const IDatabaseTable< T_DATA > &from)gum::learning::IDatabaseTable< T_DATA >
IDatabaseTable(IDatabaseTable< T_DATA > &&from)gum::learning::IDatabaseTable< T_DATA >
ignoreColumn(const std::size_t k, const bool from_external_object=true)=0gum::learning::IDatabaseTable< T_DATA >pure virtual
ignoredColumns() const =0gum::learning::IDatabaseTable< T_DATA >pure virtual
inputColumns() const =0gum::learning::IDatabaseTable< T_DATA >pure virtual
insertRow(const std::vector< std::string > &new_row) override=0gum::learning::IDatabaseTable< T_DATA >pure virtual
insertRow(Row< T_DATA > &&new_row, const IsMissing contains_missing_data)gum::learning::IDatabaseTable< T_DATA >virtual
insertRow(const Row< T_DATA > &new_row, const IsMissing contains_missing_data)gum::learning::IDatabaseTable< T_DATA >virtual
insertRows(Matrix< T_DATA > &&new_rows, const DBVector< IsMissing > &rows_have_missing_vals)gum::learning::IDatabaseTable< T_DATA >virtual
insertRows(const Matrix< T_DATA > &new_rows, const DBVector< IsMissing > &rows_have_missing_vals)gum::learning::IDatabaseTable< T_DATA >virtual
IsMissing enum namegum::learning::IDatabaseTable< T_DATA >
isRowSizeOK_(const std::size_t size) constgum::learning::IDatabaseTable< T_DATA >protected
iterator typedefgum::learning::IDatabaseTable< T_DATA >
iterator_safe typedefgum::learning::IDatabaseTable< T_DATA >
Matrix typedefgum::learning::IDatabaseTable< T_DATA >
max_nb_threads_gum::learning::IDatabaseTable< T_DATA >mutableprotected
min_nb_rows_per_thread_gum::learning::IDatabaseTable< T_DATA >mutableprotected
minNbRowsPerThread() constgum::learning::IDatabaseTable< T_DATA >
missing_symbols_gum::learning::IDatabaseTable< T_DATA >protected
missingSymbols() constgum::learning::IDatabaseTable< T_DATA >
MissingValType typedefgum::learning::IDatabaseTable< T_DATA >
nbProcessingThreads_() constgum::learning::IDatabaseTable< T_DATA >protected
nbRows() const noexceptgum::learning::IDatabaseTable< T_DATA >
nbThreads() constgum::learning::IDatabaseTable< T_DATA >
nbVariables() const noexceptgum::learning::IDatabaseTable< T_DATA >
operator=(const IDatabaseTable< T_DATA > &from)gum::learning::IDatabaseTable< T_DATA >protected
operator=(IDatabaseTable< T_DATA > &&from)gum::learning::IDatabaseTable< T_DATA >protected
pointer typedefgum::learning::IDatabaseTable< T_DATA >
rangesProcessingThreads_(const std::size_t nb_threads) constgum::learning::IDatabaseTable< T_DATA >protected
reference typedefgum::learning::IDatabaseTable< T_DATA >
Row typedefgum::learning::IDatabaseTable< T_DATA >
rows_gum::learning::IDatabaseTable< T_DATA >protected
setAllRowsWeight(const double new_weight)gum::learning::IDatabaseTable< T_DATA >
setMaxNbThreads(const std::size_t nb) constgum::learning::IDatabaseTable< T_DATA >
setMinNbRowsPerThread(const std::size_t nb) constgum::learning::IDatabaseTable< T_DATA >
setVariableNames(const std::vector< std::string > &names, const bool from_external_object=true)=0gum::learning::IDatabaseTable< T_DATA >pure virtual
setWeight(const std::size_t i, const double weight)gum::learning::IDatabaseTable< T_DATA >
size() const noexceptgum::learning::IDatabaseTable< T_DATA >
size_type typedefgum::learning::IDatabaseTable< T_DATA >
True enum valuegum::learning::IDatabaseTable< T_DATA >
value_type typedefgum::learning::IDatabaseTable< T_DATA >
variable_names_gum::learning::IDatabaseTable< T_DATA >protected
variableName(const std::size_t k) constgum::learning::IDatabaseTable< T_DATA >
variableNames() const noexceptgum::learning::IDatabaseTable< T_DATA >
weight(const std::size_t i) constgum::learning::IDatabaseTable< T_DATA >
weight() constgum::learning::IDatabaseTable< T_DATA >
~IDatabaseTable()gum::learning::IDatabaseTable< T_DATA >virtual
aGrUM 3.0.0

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