SparseDataset

All Superinterfaces:

Dataset<smile.util.SparseArray>
```
public interface SparseDataset
extends Dataset<smile.util.SparseArray>
```
List of Lists sparse matrix format. LIL stores one list per row, where each entry stores a column index and value. Typically, these entries are kept sorted by column index for faster lookup. This format is good for incremental matrix construction.
LIL is typically used to construct the matrix. Once the matrix is constructed, it is typically converted to a format, such as Harwell-Boeing column-compressed sparse matrix format, which is more efficient for matrix operations.

Method Summary

All Methods Static Methods Instance Methods Abstract Methods Default Methods
Modifier and Type	Method and Description
`static SparseDataset`	`from(java.nio.file.Path path)` Parses spare dataset in coordinate triple tuple list format.
`static SparseDataset`	`from(java.nio.file.Path path, int arrayIndexOrigin)` Reads spare dataset in coordinate triple tuple list format.
`default double`	`get(int i, int j)` Returns the value at entry (i, j).
`int`	`ncols()` Returns the number of columns.
`default int`	`nrows()` Returns the number of rows.
`int`	`nz()` Returns the number of nonzero entries.
`int`	`nz(int j)` Returns the number of nonzero entries in column j.
`static SparseDataset`	`of(java.util.Collection<smile.util.SparseArray> data)` Returns a default implementation of SparseDataset from a collection.
`static SparseDataset`	`of(java.util.Collection<smile.util.SparseArray> data, int ncols)` Returns a default implementation of SparseDataset from a collection.
`static SparseDataset`	`of(Dataset<Instance<smile.util.SparseArray>> data)` Strips the response variable and returns a SparseDataset.
`static SparseDataset`	`of(java.util.stream.Stream<smile.util.SparseArray> data)` Returns a default implementation of SparseDataset from a collection.
`default smile.math.matrix.SparseMatrix`	`toMatrix()` Convert into Harwell-Boeing column-compressed sparse matrix format.
`default void`	`unitize()` Unitize each row so that L2 norm of x = 1.
`default void`	`unitize1()` Unitize each row so that L1 norm of x is 1.

Methods inherited from interface smile.data.Dataset
apply, distributed, get, isEmpty, of, size, stream, toDataset, toMatrix, toString

- Method Detail
  - nz
```
int nz()
```
    Returns the number of nonzero entries.
  - nz
```
int nz(int j)
```
    Returns the number of nonzero entries in column j.
  - nrows
```
default int nrows()
```
    Returns the number of rows.
  - ncols
```
int ncols()
```
    Returns the number of columns.
  - get
```
default double get(int i,
                   int j)
```
    Returns the value at entry (i, j).
    
    Parameters:
    
    i - the row index.
    
    j - the column index.
  - unitize
```
default void unitize()
```
    Unitize each row so that L2 norm of x = 1.
  - unitize1
```
default void unitize1()
```
    Unitize each row so that L1 norm of x is 1.
  - toMatrix
```
default smile.math.matrix.SparseMatrix toMatrix()
```
    Convert into Harwell-Boeing column-compressed sparse matrix format.
  - of
```
static SparseDataset of(java.util.stream.Stream<smile.util.SparseArray> data)
```
    Returns a default implementation of SparseDataset from a collection.
    
    Parameters:
    
    data - sparse arrays.
  - of
```
static SparseDataset of(java.util.Collection<smile.util.SparseArray> data)
```
    Returns a default implementation of SparseDataset from a collection.
    
    Parameters:
    
    data - sparse arrays.
  - of
```
static SparseDataset of(java.util.Collection<smile.util.SparseArray> data,
                        int ncols)
```
    Returns a default implementation of SparseDataset from a collection.
    
    Parameters:
    
    data - sparse arrays.
    
    ncols - the number of columns.
  - of
```
static SparseDataset of(Dataset<Instance<smile.util.SparseArray>> data)
```
    Strips the response variable and returns a SparseDataset.
  - from
```
static SparseDataset from(java.nio.file.Path path)
                   throws java.io.IOException,
                          java.text.ParseException
```
    Parses spare dataset in coordinate triple tuple list format. Coordinate file stores a list of (row, column, value) tuples.
    
    Parameters:
    
    path - the input file path.
    
    Throws:
    
    java.io.IOException
    
    java.text.ParseException
  - from
```
static SparseDataset from(java.nio.file.Path path,
                          int arrayIndexOrigin)
                   throws java.io.IOException,
                          java.text.ParseException
```
    Reads spare dataset in coordinate triple tuple list format. Coordinate file stores a list of (row, column, value) tuples:
```
 instanceID attributeID value
 instanceID attributeID value
 instanceID attributeID value
 instanceID attributeID value
 ...
 instanceID attributeID value
 instanceID attributeID value
 instanceID attributeID value
 
```
    Ideally, the entries are sorted (by row index, then column index) to improve random access times. This format is good for incremental matrix construction.
    In addition, there may a header line
```
 D W N   // The number of rows, columns and nonzero entries.
 
```
    or 3 header lines
```
 D    // The number of rows
 W    // The number of columns
 N    // The total number of nonzero entries in the dataset.
 
```
    Parameters:
    
    path - the input file path.
    
    arrayIndexOrigin - the starting index of array. By default, it is 0 as in C/C++ and Java. But it could be 1 to parse data produced by other programming language such as Fortran.
    
    Throws:
    
    java.io.IOException - if stream to file cannot be read or closed.
    
    java.text.ParseException - if an index is not an integer or the value is not a double.

Interface SparseDataset

Method Summary

Methods inherited from interface smile.data.Dataset

Method Detail

nz

nz

nrows

ncols

get

unitize

unitize1

toMatrix

of

of

of

of

from

from