- Generated by
1.8.13
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Turi Create
4.0
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#include <ml/ml_data/row_reference.hpp>
Public Member Functions | |
| template<typename Entry > | |
| GL_HOT_INLINE void | fill (std::vector< Entry > &x) const |
| template<typename EigenXpr > | |
| GL_HOT_INLINE_FLATTEN void | fill (EigenXpr &&x, typename std::enable_if< std::is_convertible< EigenXpr, DenseVector >::value >::type *=0) const |
| void | fill_untranslated_values (std::vector< flexible_type > &x) const |
| template<typename EigenXpr > | |
| GL_HOT_INLINE_FLATTEN void | fill_eigen (EigenXpr &&x) const |
| template<typename ElementWriteFunction , typename ColumnEndFunction > | |
| GL_HOT_INLINE_FLATTEN void | unpack (ElementWriteFunction &&ewf, ColumnEndFunction &&cef) const |
| double | target_value () const GL_HOT_INLINE_FLATTEN |
| size_t | target_index () const GL_HOT_INLINE_FLATTEN |
| const std::shared_ptr< ml_metadata > & | metadata () const |
Static Public Member Functions | |
| static GL_HOT ml_data_row_reference | from_row (const std::shared_ptr< ml_metadata > &metadata, const flex_dict &row, ml_missing_value_action none_action=ml_missing_value_action::USE_NAN) |
A class containing a reference to the row of an ml_data instance, providing access to the underlying data.
In other words, you can do
it->fill(x);
or
auto row_ref = *it;
// do stuff ... row_ref.fill(x);
The data block pointed to by this reference is kept alive as long as this reference class exists.
Another example of how it is used is below:
sframe X = make_integer_testing_sframe( {"C1", "C2"}, { {0, 0}, {1, 1}, {2, 2}, {3, 3}, {4, 4} } );
ml_data data;
data.fill(X);
// Get row references
std::vector<ml_data_row_reference> rows(data.num_rows());
for(auto it = data.get_iterator(); !it.done(); ++it) { rows[it.row_index()] = *it; }
// Now go through and make sure that each of these hold the // correct answers.
std::vector<ml_data_entry> x;
for(size_t i = 0; i < rows.size(); ++i) {
// The metadata for the row is the same as that in the data. ASSERT_TRUE(rows[i].metadata().get() == data.metadata().get());
rows[i].fill(x);
ASSERT_EQ(x.size(), 2);
ASSERT_EQ(x[0].column_index, 0); ASSERT_EQ(x[0].index, 0); ASSERT_EQ(x[0].value, i);
ASSERT_EQ(x[1].column_index, 1); ASSERT_EQ(x[1].index, 0); ASSERT_EQ(x[1].value, i); } }
Definition at line 87 of file row_reference.hpp.
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inline |
Fill an observation vector, represented as an ml_data_entry struct. (column_index, index, value) pairs, from this row reference. For each column:
Categotical: Returns (col_id, v, 1) Numeric : Returns (col_id, 0, v) Vector : Returns (col_id, i, v) for each (i,v) in vector.
Example use is given by the following code:
std::vector<ml_data_entry> x;
row_ref.fill(x); double y = row_ref.target_value(); ...
Definition at line 259 of file row_reference.hpp.
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inline |
Fill a row of an Eigen expression in the current location in the iteration.
Example:
Eigen::MatrixXd X;
...
it.fill(X.row(row_idx));
| [in,out] | x | An eigen row expression. |
Definition at line 142 of file row_reference.hpp.
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inline |
The explicit version to fill an eigen expression.
Definition at line 287 of file row_reference.hpp.
| void turi::ml_data_row_reference::fill_untranslated_values | ( | std::vector< flexible_type > & | x | ) | const |
Fill an observation vector with the untranslated columns, if any have been specified at setup time. These columns are simply mapped back to their sarray counterparts.
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static |
Create an ml_data_row_reference from a single sframe row reference.
Row must be in the format {column_name, value} and columns correspond to the columns in metadata. Missing columns are treated as missing values.
Returns a single row reference.
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inline |
Returns a pointer to the metadata class that describes the data that this row reference refers to.
Definition at line 222 of file row_reference.hpp.
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inline |
Returns the current categorical target index, if present, or 0 if not present.
Definition at line 215 of file row_reference.hpp.
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inline |
Returns the current target value, if present, or 1 if not present. If the target column is supposed to be a categorical value, then use target_index().
Definition at line 208 of file row_reference.hpp.
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inline |
A generic function to unpack the values into a particular format. This allows, e.g. custom distance functions and stuff to work out well.
// Called for every element. // mode: What type of column it is. // feature_index: index within the column // index_size: number of features in this column. // index_offset: The global index would be index_offset + feature_index // value: the value of the feature.
auto unpack_function = [&](ml_column_mode mode, size_t column_index, size_t feature_index, double value, size_t index_size, size_t index_offset) { ... };
// Called after every column is done unpacking. auto column_end_function = [&](ml_column_mode mode, size_t column_index, size_t index_size) { ... };
Definition at line 189 of file row_reference.hpp.
1.8.13