Exports methods filter_u, filter_g, filter_r, filter_i, filter_z that linearly interpolate the SDSS discretised filters download from here. The filters are normalised in that their integral equals 1.
Produce plot with
using SloanUGRIZFilters
using PyPlot # must be independently installed
λ = 0:0.1:11300
plot(λ, filter_u.(λ),"m");fill_between(λ, 0*λ, filter_u.(λ),color="m",alpha=0.3)
plot(λ, filter_g.(λ),"c");fill_between(λ, 0*λ, filter_g.(λ),color="c",alpha=0.3)
plot(λ, filter_r.(λ),"g");fill_between(λ, 0*λ, filter_r.(λ),color="g",alpha=0.3)
plot(λ, filter_i.(λ),"y");fill_between(λ, 0*λ, filter_i.(λ),color="y",alpha=0.3)
plot(λ, filter_z.(λ),"r");fill_between(λ, 0*λ, filter_z.(λ),color="r",alpha=0.3)
Convenience function:
plot(createFilterMatrix(collect(λ)))
Check normalisation
using QuadGK # needs to be indepedently installed
# answers should be very very close to 1
map(f -> quadgk(f, 0, 12_000)[1], [filter_u, filter_g, filter_r, filter_i, filter_z])