# ManifoldLearning methods broken?
**URL:** https://discourse.julialang.org/t/manifoldlearning-methods-broken/9058
**Category:** General Usage
**Tags:** question, package, plotting
**Created:** [February 14, 2018, 3:29pm UTC](https://discourse.julialang.org/t/manifoldlearning-methods-broken/9058 "2018-02-14T15:29:19Z")
**Posts on this page:** 7
**Page:** 1
### Author:  [@burfel](https://discourse.julialang.org/u/burfel)
#### Post date: [February 14, 2018, 3:29pm UTC](https://discourse.julialang.org/t/manifoldlearning-methods-broken/9058/1 "2018-02-14T15:29:19Z")
I am trying to get the methods in the _ManifoldLearning.jl_ package running and get the following error messages… I use the sample code from the documentation.
```julia
# Isomap
Y_Isomap = transform(Isomap,data_array; k=12,d=2)
```
> MethodError: no method matching Dict(::Array{Int64,1}, ::UnitRange{Int64})
> Closest candidates are:
> Dict(::Any) at dict.jl:144
> #transform#6(::Int64, ::Int64, ::Function, ::Type{ManifoldLearning.Isomap}, ::Array{Float64,2}) at isomap.jl:59
> (::MultivariateStats.#kw##transform)(::Array{Any,1}, ::MultivariateStats.#transform, ::Type{ManifoldLearning.Isomap}, ::Array{Float64,2}) at :0
> include\_string(::String, ::String) at loading.jl:522
> include\_string(::String, ::String, ::Int64) at eval.jl:30
> include\_string(::Module, ::String, ::String, ::Int64, ::Vararg{Int64,N} where N) at eval.jl:34
> (::Atom.##100#105{String,Int64,String})() at eval.jl:75
> withpath(::Atom.##100#105{String,Int64,String}, ::String) at utils.jl:30
> withpath(::Function, ::String) at eval.jl:38
> hideprompt(::Atom.##99#104{String,Int64,String}) at repl.jl:59
> macro expansion at eval.jl:73 [inlined]
> (::Atom.##98#103{Dict{String,Any}})() at task.jl:80
```julia
# Diffusion maps
Y_DiffMap = transform(DiffMap, data_array; d=2, t=1, ɛ=1.0)
```
> UndefVarError: transform! not defined
> #transform#19(::Int64, ::Int64, ::Float64, ::Function, ::Type{ManifoldLearning.DiffMap}, ::Array{Float64,2}) at diffmaps.jl:37
> (::MultivariateStats.#kw##transform)(::Array{Any,1}, ::MultivariateStats.#transform, ::Type{ManifoldLearning.DiffMap}, ::Array{Float64,2}) at :0
> include\_string(::String, ::String) at loading.jl:522
> include\_string(::String, ::String, ::Int64) at eval.jl:30
> include\_string(::Module, ::String, ::String, ::Int64, ::Vararg{Int64,N} where N) at eval.jl:34
> (::Atom.##100#105{String,Int64,String})() at eval.jl:75
> withpath(::Atom.##100#105{String,Int64,String}, ::String) at utils.jl:30
> withpath(::Function, ::String) at eval.jl:38
> hideprompt(::Atom.##99#104{String,Int64,String}) at repl.jl:59
> macro expansion at eval.jl:73 [inlined]
> (::Atom.##98#103{Dict{String,Any}})() at task.jl:80
```julia
# Local linear embedding
Y_LLE = transform(LLE, data_array; k = 12, d = 2)
```
> MethodError: no method matching Dict(::Array{Int64,1}, ::UnitRange{Int64})
> Closest candidates are:
> Dict(::Any) at dict.jl:144
> #transform#12(::Int64, ::Int64, ::Function, ::Type{ManifoldLearning.LLE}, ::Array{Float64,2}) at lle.jl:51
> (::MultivariateStats.#kw##transform)(::Array{Any,1}, ::MultivariateStats.#transform, ::Type{ManifoldLearning.LLE}, ::Array{Float64,2}) at :0
> include\_string(::String, ::String) at loading.jl:522
> include\_string(::String, ::String, ::Int64) at eval.jl:30
> include\_string(::Module, ::String, ::String, ::Int64, ::Vararg{Int64,N} where N) at eval.jl:34
> (::Atom.##100#105{String,Int64,String})() at eval.jl:75
> withpath(::Atom.##100#105{String,Int64,String}, ::String) at utils.jl:30
> withpath(::Function, ::String) at eval.jl:38
> hideprompt(::Atom.##99#104{String,Int64,String}) at repl.jl:59
> macro expansion at eval.jl:73 [inlined]
> (::Atom.##98#103{Dict{String,Any}})() at task.jl:80
```julia
# Hessian Eigenmaps transformation
Y_HLLE = transform(HLLE, data_array; k = 12, d = 2)
```
> UndefVarError: int not defined
> #transform#9(::Int64, ::Int64, ::Function, ::Type{ManifoldLearning.HLLE}, ::Array{Float64,2}) at hlle.jl:44
> (::MultivariateStats.#kw##transform)(::Array{Any,1}, ::MultivariateStats.#transform, ::Type{ManifoldLearning.HLLE}, ::Array{Float64,2}) at :0
> include\_string(::String, ::String) at loading.jl:522
> include\_string(::String, ::String, ::Int64) at eval.jl:30
> include\_string(::Module, ::String, ::String, ::Int64, ::Vararg{Int64,N} where N) at eval.jl:34
> (::Atom.##100#105{String,Int64,String})() at eval.jl:75
> withpath(::Atom.##100#105{String,Int64,String}, ::String) at utils.jl:30
> withpath(::Function, ::String) at eval.jl:38
> hideprompt(::Atom.##99#104{String,Int64,String}) at repl.jl:59
> macro expansion at eval.jl:73 [inlined]
> (::Atom.##98#103{Dict{String,Any}})() at task.jl:80
And when I try to plot it, I get
`scatter(Y_LEM, title="LEM - ManifoldLearning")`
> No user recipe defined for ManifoldLearning.LEM
> macro expansion at series.jl:132 [inlined]
> apply\_recipe(::Dict{Symbol,Any}, ::Type{Plots.SliceIt}, ::Void, ::ManifoldLearning.LEM, ::Void) at RecipesBase.jl:287
> \_process\_userrecipes(::Plots.Plot{Plots.GRBackend}, ::Dict{Symbol,Any}, ::Tuple{ManifoldLearning.LEM}) at pipeline.jl:81
> \_plot!(::Plots.Plot{Plots.GRBackend}, ::Dict{Symbol,Any}, ::Tuple{ManifoldLearning.LEM}) at plot.jl:177
> (::RecipesBase.#kw##plot)(::Array{Any,1}, ::RecipesBase.#plot, ::ManifoldLearning.LEM) at :0
> #scatter#632(::Array{Any,1}, ::Function, ::ManifoldLearning.LEM, ::Vararg{ManifoldLearning.LEM,N} where N) at RecipesBase.jl:381
> (::Plots.#kw##scatter)(::Array{Any,1}, ::Plots.#scatter, ::ManifoldLearning.LEM, ::Vararg{ManifoldLearning.LEM,N} where N) at :0
> include\_string(::String, ::String) at loading.jl:522
> include\_string(::String, ::String, ::Int64) at eval.jl:30
> include\_string(::Module, ::String, ::String, ::Int64, ::Vararg{Int64,N} where N) at eval.jl:34
> (::Atom.##100#105{String,Int64,String})() at eval.jl:75
> withpath(::Atom.##100#105{String,Int64,String}, ::String) at utils.jl:30
> withpath(::Function, ::String) at eval.jl:38
> hideprompt(::Atom.##99#104{String,Int64,String}) at repl.jl:59
> macro expansion at eval.jl:73 [inlined]
> (::Atom.##98#103{Dict{String,Any}})() at task.jl:80
my data\_array is a 547×96 Array{Float64,2}.
Help much appreciated!
---
### Author:  [@burfel](https://discourse.julialang.org/u/burfel)
#### Post date: [February 21, 2018, 1:23pm UTC](https://discourse.julialang.org/t/manifoldlearning-methods-broken/9058/2 "2018-02-21T13:23:04Z")
Are these methods working for anyone?
---
### Author:  [@y4lu](https://discourse.julialang.org/u/y4lu)
#### Post date: [February 21, 2018, 1:58pm UTC](https://discourse.julialang.org/t/manifoldlearning-methods-broken/9058/3 "2018-02-21T13:58:55Z")
These might be helpful
```julia
int(x) = Int(x);
base.Dict(x::Array{Int64, 1}, y::UnitRange{Int64}) = Dict(x=>y);
```
---
### Author:  [@burfel](https://discourse.julialang.org/u/burfel)
#### Post date: [February 21, 2018, 4:26pm UTC](https://discourse.julialang.org/t/manifoldlearning-methods-broken/9058/4 "2018-02-21T16:26:52Z")
Could you please elaborate a bit. It is still returning the same error messages.
If you get any of the methods above running, could you please provide some sample code? Thanks.
---
### Author:  [@pegger0709](https://discourse.julialang.org/u/pegger0709)
#### Post date: [June 19, 2018, 7:48am UTC](https://discourse.julialang.org/t/manifoldlearning-methods-broken/9058/5 "2018-06-19T07:48:20Z")
I’m having the same problem as burfel (I’m using julia v0.6.3). I tried y4lu’s suggested fix, and that didn’t help. Are others having the same problem? Should this be raised in a different forum?
---
### Author:  [@Tamas\_Papp](https://discourse.julialang.org/u/Tamas_Papp)
#### Post date: [June 19, 2018, 8:08am UTC](https://discourse.julialang.org/t/manifoldlearning-methods-broken/9058/6 "2018-06-19T08:08:09Z")
You can try opening an issue at the repo
[https://github.com/wildart/ManifoldLearning.jl](https://github.com/wildart/ManifoldLearning.jl)
but there seems to be no recent activity so it may be abandonned.
---
### Author:  [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)
#### Post date: [June 19, 2018, 8:20am UTC](https://discourse.julialang.org/t/manifoldlearning-methods-broken/9058/7 "2018-06-19T08:20:29Z")
It works on the master branch.