HNumeric
Packages
- HNum.Vector : Contain vector, matrix, linear algebra
- HNum.Stats : Contain statistical functions
Installation
1. Cabal Install
cabal update
cabal install HNumeric
That's all!
2. Import to Stack project
If you use this package to your own project, then you should change stack.yaml
and package.yaml
1) Change stack.yaml
# In stack.yaml
extra-deps:
- git: https://github.com/Axect/HNumeric.git
commit: [Latest Commit]
- normaldistribution-1.1.0.3
- random-1.1
2) Change package.yaml
# In package.yaml
dependecies:
- base
- HNumeric
- normaldistribution
- random
Then enjoy!
Usage
Import Module
Basic Vector Usage
-- HNumeric-0.3.0.0 Documentation
let a = vector [1,2,3] -- Vector declaration
let b = Vector [4,5,6] -- small v and large V are same (for convenient)
-- Print Vector
print a
-- You can (+1) by fmap (Vector is functor)
(+1) <$> a
-- Or MATLAB-like operator (.+, .-, .*, ./, .^)
a .+ 1 -- do not 1 .+ a (. means position of vector)
-- You can make list from vector
toList a -- [1, 2, 3]
-- You can make vector from list
fromList [1,2,3] -- Vector [1,2,3]
-- You can add (subtract, multiply, divide) vectors
a + b -- Vector [5,7,9]
-- Also dot product is here.
a .*. b -- 1*4 + 2*5 + 3*6 = 32
-- Declare Matrix (Syntactic Sugar)
let c = matrix [[1,2],[3,4]]
-- or Declare using R Syntax
let d = Matrix {val = Vector [5,6,7,8], row = 2, col = 2, byRow = True}
-- Determinant
det c
-- Inverse
inv c
-- Transpose
transpose c
-- Matrix ops with Constant (+, -, *, /, ^)
c .+ 1 -- Matrix [[2,3],[4,5]]
-- Matrix ops with Matrix (+, -)
c + c -- Matrix [[2,4],[6,8]]
-- Matrix Multiplication
c %*% d
-- Matrix - Inverse Multiplication
c %/% d
-- Vector Concatenate
hcat a b -- Vector [1,2,3,4,5,6]
vcat a b -- Matrix [[1,2,3],[4,5,6]]
-- Matrix Concatenate
hcat c d -- Matrix [[1,2,5,6],[3,4,7,8]]
vcat c d -- Matrix [[1,2],[3,4],[5,6],[7,8]]
-- Insert Vector to Matrix
vector [1, 2] .: c -- Matrix [[1,2],[1,2],[3,4]]
Basic Stats Usage
-- Sample Vector (import Vector)
v = vector [1..10]
w = vector [10, 9 .. 1]
-- Mean
mean v
-- Var
var v
-- Std
std v
-- Cov Matrix
cov v w
-- Only Cov
cov' v w
-- Linear Fit
(intercept, slope) = lm v w -- (11.0, -1.0) -- (Intercept, Slope)
-- Linear Fit function
lineFit (intercept, slope) (Vector [1 .. 20])
-- RSS
rss v w
-- RSE
rse v w
DONE
- Effective Matrix Structure (R-like Structure)
- Divide and Conquer Matrix Multiplication, Determinant, Inverse
TODO (2018.06.08)
- DSL Documentation by LaTeX (Soon)
- Make CSV Package
- Make DataFrame type