org.saddle
==Saddle==
Saddle is a '''S'''cala '''D'''ata '''L'''ibrary.
Saddle provides array-backed, indexed one- and two-dimensional data structures.
These data structures are specialized on JVM primitives. With them one can often avoid the overhead of boxing and unboxing.
Basic operations also aim to be robust to missing values (NA's)
The building blocks are intended to be easily composed.
The foundational building blocks are:
Inspiration for Saddle comes from many sources, including the R programming language, the pandas data analysis library for Python, and the Scala collections library.
Attributes
Members list
Packages
This package contains utilities for working with arrays that are specialized for numeric types.
This package contains utilities for working with arrays that are specialized for numeric types.
Attributes
Provides type aliases for a few basic operations
Provides type aliases for a few basic operations
Attributes
Additional utilities that need a home
Additional utilities that need a home
Attributes
Factory methods to generate Vec instances
Factory methods to generate Vec instances
Attributes
Type members
Classlikes
Attributes
- Supertypes
-
class Objecttrait Matchableclass Any
Attributes
- Supertypes
-
trait Singletontrait Producttrait Mirrortrait Serializabletrait Producttrait Equalsclass FillMethodclass Objecttrait Matchableclass AnyShow all
- Self type
-
FillBackward.type
Attributes
- Supertypes
-
trait Singletontrait Producttrait Mirrortrait Serializabletrait Producttrait Equalsclass FillMethodclass Objecttrait Matchableclass AnyShow all
- Self type
-
FillForward.type
Filling method for NA values. Non-sealed because could add more variants in the future.
Filling method for NA values. Non-sealed because could add more variants in the future.
Attributes
- Supertypes
-
class Objecttrait Matchableclass Any
- Known subtypes
-
object FillBackward.typeobject FillForward.type
Frame
is an immutable container for 2D data which is indexed along both axes (rows, columns) by associated keys (i.e., indexes).
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 Frame
s 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))
Type parameters
- CX
-
The type of column keys
- RX
-
The type of row keys
- T
-
The type of entries in the frame
Value parameters
- colIx
-
An index for the columns
- rowIx
-
An index for the rows
- values
-
A sequence of Vecs which comprise the columns of the Frame
Attributes
- Companion
- object
- Supertypes
Attributes
Index provides a constant-time look-up of a value within array-backed storage, as well as operations to support joining and slicing.
Index provides a constant-time look-up of a value within array-backed storage, as well as operations to support joining and slicing.
Attributes
- Companion
- object
- Supertypes
-
class Objecttrait Matchableclass Any
- Known subtypes
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.
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 Mat
s 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.
Type parameters
- A
-
Type of elements within the Mat
Attributes
- Companion
- object
- Supertypes
Attributes
- Supertypes
-
trait Order[T]trait PartialOrder[T]trait Eq[T]trait Serializableclass Objecttrait Matchableclass AnyShow all
- Known subtypes
-
object doubleIsNumeric.typeobject floatIsNumeric.typeobject intIsNumeric.typeobject longIsNumeric.type
Attributes
- Supertypes
-
class Objecttrait Matchableclass Any
Attributes
- Supertypes
-
class Objecttrait Matchableclass Any
Augments Seq with a toFrame method that returns a new Frame instance.
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
Type parameters
- CX
-
Type of col index elements of Frame
- RX
-
Type of row index elements of Frame
- T
-
Type of data elements of Frame
Value parameters
- s
-
A value of type Seq[(RX, CX, T)]
Attributes
- Supertypes
-
class Objecttrait Matchableclass Any
Attributes
- Supertypes
-
class Objecttrait Matchableclass Any
Augments Seq with a toIndex method that returns a new Index instance.
Augments Seq with a toIndex method that returns a new Index instance.
For example,
val i = IndexedSeq(1,2,3)
val s = i.toIndex
Type parameters
- X
-
Type of index elements
Value parameters
- ix
-
A value of type Seq[X]
Attributes
- Supertypes
-
class Objecttrait Matchableclass Any
Attributes
- Supertypes
-
class Objecttrait Matchableclass Any
Augments Seq with a toSeries method that returns a new Series instance.
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
Type parameters
- T
-
Type of data elements of Series
- X
-
Type of index elements of Series
Value parameters
- s
-
A value of type Seq[(X, T)]
Attributes
- Supertypes
-
class Objecttrait Matchableclass Any
Augments Seq with a toVec method that returns a new Vec instance.
Augments Seq with a toVec method that returns a new Vec instance.
For example,
val s = IndexedSeq(1,2,3)
val v = s.toVec
Type parameters
- T
-
Type of elements of Vec
Value parameters
- s
-
A value of type Seq[T]
Attributes
- Supertypes
-
class Objecttrait Matchableclass Any
Series
is an immutable container for 1D homogeneous data which is indexed by a an associated sequence of keys.
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, ...)
Type parameters
- T
-
Type of elements in the values array, for which there must be an implicit ST
- X
-
Type of elements in the index, for which there must be an implicit Ordering and ST
Value parameters
- index
-
Index backing the keys in the Series
- values
-
Vec backing the values in the Series
Attributes
- Companion
- object
- Supertypes
Attributes
Vec
is an immutable container for 1D homogeneous data (a "vector"). It is backed by an array and indexed from 0 to length - 1.
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 Vec
s 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!
Type parameters
- T
-
Type of elements within the Vec
Attributes
- Companion
- object
- Supertypes
- Known subtypes
-
class VecDefault[T]
Specialized methods for Vec[Double]
Specialized methods for Vec[Double]
Methods in this class do not filter out NAs, e.g. Vec(NA,1d).max2 == NA rather than 1d
Attributes
- Supertypes
-
class Objecttrait Matchableclass Any
Attributes
- Supertypes
-
trait Hash[Double]trait Numeric[Double]trait Order[Double]trait PartialOrder[Double]trait Eq[Double]trait Serializableclass Objecttrait Matchableclass AnyShow all
- Self type
-
doubleIsNumeric.type
Attributes
- Supertypes
-
trait Hash[Float]trait Numeric[Float]trait Order[Float]trait PartialOrder[Float]trait Eq[Float]trait Serializableclass Objecttrait Matchableclass AnyShow all
- Self type
-
floatIsNumeric.type
Attributes
- Supertypes
-
trait Numeric[Int]trait Order[Int]trait PartialOrder[Int]trait Eq[Int]trait Serializableclass Objecttrait Matchableclass AnyShow all
- Self type
-
intIsNumeric.type
Attributes
- Supertypes
-
trait Numeric[Long]trait Order[Long]trait PartialOrder[Long]trait Eq[Long]trait Serializableclass Objecttrait Matchableclass AnyShow all
- Self type
-
longIsNumeric.type
Types
Shorthand for class manifest typeclass
Shorthand for class manifest typeclass
Attributes
Shorthand for ordering typeclass
Shorthand for ordering typeclass
Attributes
Value members
Concrete methods
Syntactic sugar, placeholder for 'slice-all'
Syntactic sugar, placeholder for 'slice-all'
val v = Vec(1,2,3, 4)
val u = v(*)
Attributes
Allow timing of an operation
Allow timing of an operation
clock { bigMat.T dot bigMat }
Attributes
na
provides syntactic sugar for constructing primitives recognized as NA. A use case is be:
na
provides syntactic sugar for constructing primitives recognized as NA. A use case is be:
Vec[Int](1,2,na,4)
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).
Attributes
Implicits
Implicits
Augments Seq with a toFrame method that returns a new Frame instance.
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
Type parameters
- CX
-
Type of col index elements of Frame
- RX
-
Type of row index elements of Frame
- T
-
Type of data elements of Frame
Value parameters
- s
-
A value of type Seq[(RX, CX, T)]
Attributes
Augments Seq with a toIndex method that returns a new Index instance.
Augments Seq with a toIndex method that returns a new Index instance.
For example,
val i = IndexedSeq(1,2,3)
val s = i.toIndex
Type parameters
- X
-
Type of index elements
Value parameters
- ix
-
A value of type Seq[X]
Attributes
Augments Seq with a toSeries method that returns a new Series instance.
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
Type parameters
- T
-
Type of data elements of Series
- X
-
Type of index elements of Series
Value parameters
- s
-
A value of type Seq[(X, T)]
Attributes
Augments Seq with a toVec method that returns a new Vec instance.
Augments Seq with a toVec method that returns a new Vec instance.
For example,
val s = IndexedSeq(1,2,3)
val v = s.toVec
Type parameters
- T
-
Type of elements of Vec
Value parameters
- s
-
A value of type Seq[T]
Attributes
Specialized methods for Vec[Double]
Specialized methods for Vec[Double]
Methods in this class do not filter out NAs, e.g. Vec(NA,1d).max2 == NA rather than 1d
Attributes
Syntactic sugar, allow '->' to generate an (inclusive) index slice
Syntactic sugar, allow '->' to generate an (inclusive) index slice
val v = Vec(1,2,3,4)
val u = v(0 -> 2)
Attributes
Syntactic sugar, allow ' -> *' to generate an (inclusive) index slice, open on right
Syntactic sugar, allow ' -> *' to generate an (inclusive) index slice, open on right
val v = Vec(1,2,3,4)
val u = v(1 -> *)
Attributes
Syntactic sugar, allow '* -> ' to generate an (inclusive) index slice, open on left
Syntactic sugar, allow '* -> ' to generate an (inclusive) index slice, open on left
val v = Vec(1,2,3,4)
val u = v(* -> 2)