QuantEcon/QuantEcon.jl

random_stochastic_matrix and random_markov_chain support sparse output

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#102 opened on Mar 17, 2016

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 (0 comments) (0 reactions) (0 assignees)Julia (300 forks)batch import
enhancementhelp wanted

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Description

This might look like this:

random_markov_chain{T}(n::Int, k::Int=n, ::Type{Matrix{T}})  # ==> return dense array
random_markov_chain{T}(n::Int, k::Int=n, ::Type{SparseMatrixCSC{Int,T}})  # ==> return sparse array

Also, having Union{Int,Void} shouldn't be necessary here as it is in python because default arguments can depend on one another. (e.g. def f(n, k=n): is n't possible in python but function f(n, k=n) is possible in Julia)

Contributor guide

Research direction
Implement a new method for `random markov chain` (and similarly for `random stochastic matrix`) that accepts a type parameter to specify sparse output, using `sparse` from the built in package to construct a sparse matrix.
Tech stack
julia
Domain
backend
Issue type
Feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-3 hours
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Clear
Prerequisites
JuliaGit
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
75