Packages

  • package root
    Definition Classes
    root
  • package org
    Definition Classes
    root
  • package saddle

    Saddle is a Scala Data Library.

    Saddle

    Saddle is a Scala Data Library.

    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.

    Definition Classes
    org
  • package array

    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.

    Definition Classes
    saddle
  • package binary

    Binary serialization for Frame[String,String,T] or Mat[T] with primitive T

    Binary serialization for Frame[String,String,T] or Mat[T] with primitive T

    The layout of binary format is as follows:

    • The first 6 bytes are "SADDLE"
    • The next unsigned byte is the major version
    • The next unsigned byte is the minor version
    • The next 4 bytes form a little endian integer as HEADER_LENGTH
    • The next HEADER_LENGTH bytes form an UTF-8 string as the header.
    • The header is a valid JSON object with the following fields:
      • v: numeric positive integer is the version of the header structure
      • colix : a JSON array of strings, it is the column index of the frame
      • rowix : a JSON array of strings, it is the row index of the frame
      • numrows: numeric positive integer, number of rows
      • numcols: numeric positive integer, number of cols
      • Either one of rowix or numrows may be missing
      • Either one of colix or numcols may be missing
      • rowmajor : a boolean, indicating whether the data is stored in row-major or col-major order
      • datatype : string, either "double", "long", "int", "float", "byte"
    • The header is padded with spaces (0x20) such that HEADER_LENGTH+12 is divisible by 16. The count of spaces are included in HEADER_LENGTH.
    • The next width * numRows * numCols bytes form a little endian primitive array in row-major or col-major order. numRows and numCols are determined from the rowix/numrows and colix/numcols header fields. width is determined from the datatype field (8 for double and long, 4 for int and float, 1 for byte)
    Definition Classes
    saddle
  • package csv
    Definition Classes
    saddle
  • package groupby
    Definition Classes
    saddle
  • package index
    Definition Classes
    saddle
  • package io
    Definition Classes
    saddle
  • package linalg
    Definition Classes
    saddle
  • package macros
    Definition Classes
    saddle
  • package mat
    Definition Classes
    saddle
  • package npy
    Definition Classes
    saddle
  • package ops

    Provides type aliases for a few basic operations

    Provides type aliases for a few basic operations

    Definition Classes
    saddle
  • package scalar
    Definition Classes
    saddle
  • package spire
    Definition Classes
    saddle
  • package util

    Additional utilities that need a home

    Additional utilities that need a home

    Definition Classes
    saddle
  • package vec

    Factory methods to generate Vec instances

    Factory methods to generate Vec instances

    Definition Classes
    saddle
  • VecDefault

package vec

Factory methods to generate Vec instances

Linear Supertypes
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  1. vec
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Type Members

  1. class VecDefault[T] extends NumericOps[Vec[T]] with Vec[T]

Value Members

  1. def ones(sz: Int): Vec[Double]

    Generate a Vec[Double] containing a certain number of ones

    Generate a Vec[Double] containing a certain number of ones

    sz

    Number of elements of ones vec

  2. def rand(sz: Int): Vec[Double]

    Generate a uniform [0,1) random Vec[Double] of a certain number of elements

    Generate a uniform [0,1) random Vec[Double] of a certain number of elements

    sz

    Number of elements of random vector

  3. def randi(sz: Int): Vec[Int]

    Generate a uniform random Vec[Int] of a certain number of elements

    Generate a uniform random Vec[Int] of a certain number of elements

    sz

    Number of elements of random vector

  4. def randl(sz: Int): Vec[Long]

    Generate a uniform random Vec[Long] of a certain number of elements

    Generate a uniform random Vec[Long] of a certain number of elements

    sz

    Number of elements of random vector

  5. def randn(sz: Int): Vec[Double]

    Generate a standard normal random Vec[Double] of a certain number of elements

    Generate a standard normal random Vec[Double] of a certain number of elements

    sz

    Number of elements of random vector

  6. def randn2(sz: Int, mu: Double, sigma: Double): Vec[Double]

    Generate a gaussian(mu, sigma) random Vec[Double] of a certain number of elements

    Generate a gaussian(mu, sigma) random Vec[Double] of a certain number of elements

    sz

    Number of elements of random vector

    mu

    Mean of distribution

    sigma

    Stdev of distribution

  7. def randp(sz: Int): Vec[Double]

    Generate a uniform (0,1] random Vec[Double] of a certain number of elements

    Generate a uniform (0,1] random Vec[Double] of a certain number of elements

    sz

    Number of elements of random vector

  8. def randpi(sz: Int): Vec[Int]

    Generate a uniform random positive Vec[Int] of a certain number of elements

    Generate a uniform random positive Vec[Int] of a certain number of elements

    sz

    Number of elements of random vector

  9. def randpl(sz: Int): Vec[Long]

    Generate a uniform random positive Vec[Long] of a certain number of elements

    Generate a uniform random positive Vec[Long] of a certain number of elements

    sz

    Number of elements of random vector

  10. def range(from: Int, until: Int, step: Int = 1): Vec[Int]

    Generate a Vec[Int] containing the range of integers specified

    Generate a Vec[Int] containing the range of integers specified

    from

    Start of range

    until

    End of range, excluded from result

    step

    Stride of range

  11. def repeat[T](v: Array[T], n: Int)(implicit arg0: ST[T]): Array[T]

    Repeats a particular array some number of times

    Repeats a particular array some number of times

    T

    type of elements in array

    v

    array of values to repeat

    n

    number of repetitions

  12. def zeros(sz: Int): Vec[Double]

    Generate a Vec[Double] containing a certain number of zeros

    Generate a Vec[Double] containing a certain number of zeros

    sz

    Number of elements of zero vec

Inherited from AnyRef

Inherited from Any

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