juliastats / distance.jl Goto Github PK

(I'd do this myself but I don't have JuliaStats permissions)

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Ref: https://discourse.julialang.org/t/package-compatibility-caps/15301

It's become a bit of a convention to use the plural for package names – freeing up the singular Distance for a type name. In this case, it's not really needed since the mathematical term for a distance is "metric", but it might be good to follow the convention when the ecosystem starts switching over to Julia 0.4.

It would be nice to add support for Jaccard distance and the Rogers-Tanimoto dissimilarity distance.

For some distance measures, correlations between columns with NaNs are being returned as zeros. For example:

x=randn(2,2)
x[1,1]=NaN
ans1=pairwise(Euclidean(), x)
ans2=sqrt(pairwise(SqEuclidean(), x))

You'll notice ans2 is correct, but ans1 is not...

I'm using a recent version of Julia, where At_mul_B is deprecated.

mahalanobis(x, y, Q)
x and y it's vectors
Q must be covariance ...

julia> Q=cov(x,y)
28.409813261664944

julia> mahalanobis(x, y, Q)
ERROR: no method mahalanobis(Array{Float64,1}, Array{Float64,1}, Float64)

julia>

Hi all, I want to use JSDistance function to calculate divergence of 10 probability distributions, however I found that the default JSDistanc function only can compare the divergence of two distributions.
Could I add a JSmetric function for this package?
The square root of the Jensen–Shannon divergence is a metric. In bioinformatics field, we often use it to test isoform abundance changes among multiple expreiments in RNA-Seq data.

Here is the Jensen-Shannon divergence of m discrete probability distributions (p^1, ...,p^m ):

JSmetric(p^1,...,p^m)=H(\frac{p^1+...+p^m}{m})-\frac{\sum_{j=1}^{m} H(p^j)}{m} 

where H() is entropy.

Currently the result type is always Float64 other than for the hamming metric and weighted (semi)metrics. It would make sense in many cases for the result type to be of the same type as the inputs, for example evaluate(dist::Euclidean,a::AbstractArray{Float32,1},b::AbstractArray{Float32,1}) could return a Float32. However, when a and b are vectors of Ints it would make sense to return a Float64.

What is the planned/intended behavior?

It seems that to_fptype (used in results_type) is gone. I don't know how to solve this---just removing the to_fptype() seems to work for me.

I'm a beginner and I would love a couple of examples, maybe even per function. They don't need to be crazy extensive, but just so I could copy-paste and have it work right away. Here's what I'd love to see (and maybe you'll see why I need them), just as an example:

using Distance
n = 5
m = 8
x = rand(n,m)
y = rand(n,m)
r = colwise(Euclidean,x,y)

Disclaimer: this doesn't work for me, I get an

ERROR: no method colwise(Type{Euclidean}, Array{Float64,2}, Array{Float64,2})

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If you'd like help or more information, please just reply to this issue.

http://iainnz.github.io/packages.julialang.org/?pkg=Distance&ver=0.3

To ensure that the functions work with them.

Hepy New Year;)
_
_ _ ()_ | A fresh approach to technical computing
() | () () | Documentation: http://docs.julialang.org
_ _ | | __ _ | Type "help()" for help.
| | | | | | |/ ` | |
| | || | | | (| | | Version 0.3.3 (2014-11-23 20:19 UTC)
/ |_'|||__'| | Official http://julialang.org/ release
|__/ | x86_64-w64-mingw32

julia> using Distance
WARNING: The Distance package is deprecated. Please use a new package Distances instead.

Please , remove "Distance" ffrom list of packages
Paul

Is is possible to add support for the span semi-norm which is defined as

spanNorm(x,y) = max(x-y) - min(x-y)

This is used frequently in value iteration for solving dynamic programming equations.

In Julia Studio 0.4.4 on Mac OS X 10.9, I am unable to load the Distance package. When I run:

julia> using Distance

Julia studio terminal do not respond, it never goes back to the prompt. I have tried to reinstall the package as well as to remove the ~/.julia folder, but the problem persists.

julia> Pkg.status()
Required packages:
 - DataFrames                    0.4.3
 - Distance                      0.2.6
 - IJulia                        0.1.11             55b60c47 (dirty)
 - RDatasets                     0.1.1
Additional packages:
  - BinDeps                       0.2.12
  - Blocks                        0.0.4
  - DataArrays                    0.0.3
  - GZip                          0.2.12
  - Homebrew                      0.0.6
  - JSON                          0.3.5
  - Nettle                        0.1.3
  - NumericExtensions             0.3.6
  - REPLCompletions               0.0.1
  - SortingAlgorithms             0.0.1
  - StatsBase                     0.3.8
  - URIParser                     0.0.2
  - ZMQ                           0.1.11

[enhancement] It would be freaking awesome if you could add a bwdist function. A function that will take an instance of a distance type and an n-dimensional array of Bool. It will then return an array with the same size as the input array where each cell has the distance to the closest true containing cell.
In addition: it might be relevant in this respect to return memory-cheap types dependent on the distance metric. Since the returned distances in bwdist will be whole positive numbers for many of the distance metrics (e.g. SqEuclidean, Cityblock, Chebyshev, Hamming, etc), it might be cool to work in Uint8, 16, 32, 64, or 128 (dependent on the largest possible distance) just to save place without any loss of accuracy. I guess the easiest is to just add "cheap" versions of those types (e.g. CheapSqEuclidean) to the set of existing distance types.

Hope you find this easy and fun!

Is there any reason that package doesn't have implementations for 1D distances? Like

evaluate{T <: Real}(dist::SqEuclidean, a::T, b::T) = (a-b)*(a-b)

I am trying to release a package that has Distance.jl and PyCall.jl as its only dependencies. I get the following errors when I use Pkg.publish(). Any thoughts on what I should do?

DataFrames v0.5.0 – no valid versions exist for package DataArrays
Distance v0.3.0 – no valid versions exist for package NumericExtensions
Distance v0.3.1 – no valid versions exist for package NumericExtensions
RDatasets v0.1.0 – no valid versions exist for package DataArrays

The following code fails with an InexactError:

pairwise(Euclidean(), [1 2;
                       3 4])

This could be changed by forcing certain metrics, like Euclidean, to specify their result_type as a floating point:

result_type(::Euclidean, T1::Type, T2::Type) = Float64

Does that seem alright to you?