clim kwarg in expressionPalette or expressionColors

[gszep]

I would like to more precisely control the dynamic range of the expressionPalette. For example my expressions range from -2 to 7, but the interesting region lies from -1 to 1. I want to adjust my colour range so any expression values outside of the limits [-1,1] are clipped to the boundary colours.

It is possible to to this by pre-processing the input data, which would re-calculate the inputs each time I change the colour range which doesn't seem to be necessary. It makes more sense to have to colour representation change, not the underlying data.

As you can imagine, this will eventually be used in an interactive figure :)

[gszep]

maybe with using the cgrad method? https://docs.juliaplots.org/latest/generated/colorschemes/

[gszep]

palette = cgrad(:viridis)
scale(x::Number,y::StepRangeLen) = ( x - minimum(y) )/( maximum(y) - minimum(y) )
color = map( x->palette[scale(x,channelRange)], fcsdata[!,channel] )

[exaexa]

Yes, this would help a lot. The scaling is now (partially) done by scaleMinMax (see README examples). Perhaps the easiest way to have that working would be to supply kwargs min/max to the scaleMinMax function that set the bounds properly. Would that work for you?

See https://github.com/LCSB-BioCore/GigaScatter.jl/blob/master/src/colors.jl#L114 for scaleMinMax.

I didn't know about cgrad, I guess I can replace a bit of the code with that, e.g. this https://github.com/LCSB-BioCore/GigaScatter.jl/blob/master/src/colors.jl#L28 .

[gszep]

I realised that calling palette(::Float64) is 10x slower than palette(::Int64) and therefore it makes sense to pre-compute color indexes for each event. Here is the snippet I am working with:

channelRange, nlevels = range(-2,7,length=50), 10
palette = cgrad(:viridis,nlevels,categorical=true)

channels = names(fcsdata)
channel = Observable(first(channels))

function toIndex(x::AbstractVector{<:Number})
    min,max = extrema(channelRange)
    scaled = ( x .- min ) / ( max - min )
    
    @. scaled[scaled<0] = 0
    @. scaled[1<scaled] = 1
    
    return @. trunc(Int,nlevels*scaled) + 1
end

colorIndex = combine(fcsdata,[ col => toIndex => col for col ∈ names(fcsdata) ] )
color = Observable(palette[ colorIndex[!,channel[]] ])

############################# update on channel change
on(channel) do channel
    color[] = palette[ colorIndex[!,channel] ]
end

here color[] is a Vector{RGBA{Float64}} which is a good input for the color kwarg in Makie.jl. Is it also suitable for GigaScatter.jl?

[exaexa]

the slowness is quite likely because the float version is doing the interpolation with all colors; I guess I can do the same with our ColorPalette. I'll likely get to it tomorrow.