org.saddle

Filling method for NA values. Non-sealed because could add more variants in the future.

Frame is an immutable container for 2D data which is indexed along both axes (rows, columns) by associated keys (i.e., indexes).

The primary use case is homogeneous data, but a secondary concern is to support heterogeneous data that is homogeneous ony within any given column.

The row index, column index, and constituent value data are all backed ultimately by arrays.

Frame is effectively a doubly-indexed associative map whose row keys and col keys each have an ordering provided by the natural (provided) order of their backing arrays.

Several factory and access methods are provided. In the following examples, assume that:

 val f = Frame('a'->Vec(1,2,3), 'b'->Vec(4,5,6))

The apply method takes a row and col key returns a slice of the original Frame:

 f(0,'a') == Frame('a'->Vec(1))

apply also accepts a org.saddle.index.Slice:

 f(0->1, 'b') == Frame('b'->Vec(4,5))
 f(0, *) == Frame('a'->Vec(1), 'b'->Vec(4))

You may slice using the col and row methods respectively, as follows:

 f.col('a') == Frame('a'->Vec(1,2,3))
 f.row(0) == Frame('a'->Vec(1), 'b'->Vec(4))
 f.row(0->1) == Frame('a'->Vec(1,2), 'b'->Vec(4,5))

You can achieve a similar effect with rowSliceBy and colSliceBy

The colAt and rowAt methods take an integer offset i into the Frame, and return a Series indexed by the opposing axis:

 f.rowAt(0) == Series('a'->1, 'b'->4)

If there is a one-to-one relationship between offset i and key (ie, no duplicate keys in the index), you may achieve the same effect via key as follows:

 f.first(0) == Series('a'->1, 'b'->4)
 f.firstCol('a') == Series(1,2,3)

The at method returns an instance of a org.saddle.scalar.Scalar, which behaves much like an Option; it can be either an instance of org.saddle.scalar.NA or a org.saddle.scalar.Value case class:

 f.at(0, 0) == scalar.Scalar(1)

The rowSlice and colSlice methods allows slicing the Frame for locations in [i, j) irrespective of the value of the keys at those locations.

 f.rowSlice(0,1) == Frame('a'->Vec(1), 'b'->Vec(4))

Finally, the method raw accesses a value directly, which may reveal the underlying representation of a missing value (so be careful).

 f.raw(0,0) == 1

Frame may be used in arithmetic expressions which operate on two Frames or on a Frame and a scalar value. In the former case, the two Frames will automatically align along their indexes:

 f + f.shift(1) == Frame('a'->Vec(NA,3,5), 'b'->Vec(NA,9,11))

Index provides a constant-time look-up of a value within array-backed storage, as well as operations to support joining and slicing.

Mat is an immutable container for 2D homogeneous data (a "matrix"). It is backed by a single array. Data is stored in row-major order.

Several element access methods are provided.

The at method returns an instance of a org.saddle.scalar.Scalar, which behaves much like an Option in that it can be either an instance of org.saddle.scalar.NA or a org.saddle.scalar.Value case class:

 val m = Mat(2,2,Array(1,2,3,4))
 m.at(0,0) == Value(1)

The method raw accesses the underlying value directly.

 val m = Mat(2,2,Array(1,2,3,4))
 m.raw(0,0) == 1d

Mat may be used in arithmetic expressions which operate on two Mats or on a Mat and a primitive value. A fe examples:

 val m = Mat(2,2,Array(1,2,3,4))
 m * m == Mat(2,2,Array(1,4,9,16))
 m dot m == Mat(2,2,Array(7d,10,15,22))
 m * 3 == Mat(2, 2, Array(3,6,9,12))

Note, Mat is generally compatible with EJML's DenseMatrix. It may be convenient to induce this conversion to do more complex linear algebra, or to work with a mutable data structure.

Convenience constructors for a Frame[RX, CX, Any] that accept arbitrarily-typed Vectors and Series as constructor parameters, leaving their internal representations unchanged.

Trait which specifies what percentile method to use

Trait which specifies how to break a rank tie

Augments Seq with a toFrame method that returns a new Frame instance.

For example,

 val t = IndexedSeq(("a", "x", 3), ("b", "y", 4))
 val f = t.toFrame

 res0: org.saddle.Frame[java.lang.String,java.lang.String,Int] =
 [2 x 2]
       x  y
       -- --
 a ->  3 NA
 b -> NA  4

Augments Seq with a toIndex method that returns a new Index instance.

For example,

 val i = IndexedSeq(1,2,3)
 val s = i.toIndex

Augments Seq with a toSeries method that returns a new Series instance.

For example,

 val p = IndexedSeq(1,2,3) zip IndexedSeq(4,5,6)
 val s = p.toSeries

Augments Seq with a toVec method that returns a new Vec instance.

For example,

 val s = IndexedSeq(1,2,3)
 val v = s.toVec

Series is an immutable container for 1D homogeneous data which is indexed by a an associated sequence of keys.

Both the index and value data are backed by arrays.

Series is effectively an associative map whose keys have an ordering provided by the natural (provided) order of the backing array.

Several element access methods are provided.

The apply method returns a slice of the original Series:

 val s = Series(Vec(1,2,3,4), Index('a','b','b','c'))
 s('a') == Series('a'->1)
 s('b') == Series('b'->2, 'b'->3)

Other ways to slice a series involve implicitly constructing an org.saddle.index.Slice object and passing it to the Series apply method:

 s('a'->'b') == Series('a'->1, 'b'->2, 'b'->3)
 s(* -> 'b') == Series('a'->1, 'b'->2, 'b'->3)
 s('b' -> *) == Series('b'->2, 'b'->3, 'c'->4)
 s(*) == s

The at method returns an instance of a org.saddle.scalar.Scalar, which behaves much like an Option in that it can be either an instance of org.saddle.scalar.NA or a org.saddle.scalar.Value case class:

 s.at(0) == Scalar(1)

The slice method allows slicing the Series for locations in [i, j) irrespective of the value of the keys at those locations.

 s.slice(2,4) == Series('b'->3, 'c'->4)

To slice explicitly by labels, use the sliceBy method, which is inclusive of the key boundaries:

 s.sliceBy('b','c') == Series('b'->3, 'c'->4)

The method raw accesses the value directly, which may reveal the underlying representation of a missing value (so be careful).

 s.raw(0) == 1

Series may be used in arithmetic expressions which operate on two Series or on a Series and a scalar value. In the former case, the two Series will automatically align along their indexes. A few examples:

 s * 2 == Series('a'->2, 'b'->4, ... )
 s + s.shift(1) == Series('a'->NA, 'b'->3, 'b'->5, ...)

Vec is an immutable container for 1D homogeneous data (a "vector"). It is backed by an array and indexed from 0 to length - 1.

Several element access methods are provided.

The apply() method returns a slice of the original vector:

 val v = Vec(1,2,3,4)
 v(0) == Vec(1)
 v(1, 2) == Vec(2,3)

The at method returns an instance of a org.saddle.scalar.Scalar, which behaves much like an Option in that it can be either an instance of org.saddle.scalar.NA or a org.saddle.scalar.Value case class:

 Vec[Int](1,2,3,na).at(0) == Scalar(1)
 Vec[Int](1,2,3,na).at(3) == NA

The method raw accesses the underlying value directly.

 Vec(1d,2,3).raw(0) == 1d

Vec may be used in arithmetic expressions which operate on two Vecs or on a Vec and a scalar value. A few examples:

 Vec(1,2,3,4) + Vec(2,3,4,5) == Vec(3,5,7,9)
 Vec(1,2,3,4) * 2 == Vec(2,4,6,8)

Note, Vec is implicitly convertible to an array for convenience; this could be abused to mutate the contents of the Vec. Try to avoid this!

Specialized methods for Vec[Double]

Methods in this class do not filter out NAs, e.g. Vec(NA,1d).max2 == NA rather than 1d

na provides syntactic sugar for constructing primitives recognized as NA. A use case is be:

 Vec[Int](1,2,na,4)

na will implicitly convert to a primitive having the designated missing value bit pattern. That pattern is as follows:

1. byte => Byte.MinValue
2. char => Char.MinValue
3. short => Short.Minvalue
4. int => Int.MinValue
5. long => Long.MinValue
6. float => Float.NaN
7. double => Double.NaN

The NA bit pattern for integral types is MinValue because it induces a symmetry on the remaining bound of values; e.g. the remaining Byte bound is (-127, +127).

Note since Booleans can only take on two values, it has no na primitive bit pattern.

Shorthand for class manifest typeclass

Shorthand for numeric typeclass

Shorthand for ordering typeclass

Shorthand for scalar tag typeclass

Syntactic sugar, placeholder for 'slice-all'

 val v = Vec(1,2,3, 4)
 val u = v(*)

Allow timing of an operation

 clock { bigMat.T dot bigMat }

Constant used in string byte-level manipulation

Augments Seq with a toFrame method that returns a new Frame instance.

For example,

 val t = IndexedSeq(("a", "x", 3), ("b", "y", 4))
 val f = t.toFrame

 res0: org.saddle.Frame[java.lang.String,java.lang.String,Int] =
 [2 x 2]
       x  y
       -- --
 a ->  3 NA
 b -> NA  4

Augments Seq with a toIndex method that returns a new Index instance.

For example,

 val i = IndexedSeq(1,2,3)
 val s = i.toIndex

Augments Seq with a toSeries method that returns a new Series instance.

For example,

 val p = IndexedSeq(1,2,3) zip IndexedSeq(4,5,6)
 val s = p.toSeries

Augments Seq with a toVec method that returns a new Vec instance.

For example,

 val s = IndexedSeq(1,2,3)
 val v = s.toVec

Specialized methods for Vec[Double]

Methods in this class do not filter out NAs, e.g. Vec(NA,1d).max2 == NA rather than 1d

Syntactic sugar, allow '->' to generate an (inclusive) index slice

 val v = Vec(1,2,3,4)
 val u = v(0 -> 2)

Syntactic sugar, allow ' -> *' to generate an (inclusive) index slice, open on right

 val v = Vec(1,2,3,4)
 val u = v(1 -> *)

Syntactic sugar, allow '* -> ' to generate an (inclusive) index slice, open on left

 val v = Vec(1,2,3,4)
 val u = v(* -> 2)