module Utils import TOML: parsefile import DelimitedFiles: readdlm import DSP function load_init_params(filename::String) meta = parsefile(filename)["metadata"] params = NamedTuple(Dict(Symbol(p["symbol"]) => p["initial_value"] for p in meta["parameters"])) lower_bounds = [p["min"] for p in meta["parameters"]] upper_bounds = [p["max"] for p in meta["parameters"]] return (meta=meta, params=params, lower_bounds=lower_bounds, upper_bounds=upper_bounds) end function select_columns(QIE_array, qmin, qmax, bin, err_mul) #""Select q / I(q) / err(q) data - Change I(q) value from mm^-1 to nm^-1' Q = Float64[] IDATA = Float64[] ERR = Float64[] for i in axes(QIE_array, 1) # keep only the values of q within bounds if qmin <= QIE_array[i, 1] <= qmax # skip all but the (k*bin)-th values if i % bin == 0 if QIE_array[i, 2] > 0 push!(Q, QIE_array[i, 1]) push!(IDATA, 1e-6 * QIE_array[i, 2]) if err_mul == 0 push!(ERR, 0.01 * 1e-6 * QIE_array[i, 2]) elseif QIE_array[i, 3] * err_mul > 0.01 * QIE_array[i, 2] push!(ERR, 1e-6 * QIE_array[i, 3] * err_mul) else push!(ERR, 0.01 * 1e-6 * QIE_array[i, 2]) end end end end end return (Q, IDATA, ERR) end """ compute_logscale_weights(q) Compute the weights W, which are proportional to the distance in the log space """ function compute_logscale_weights(q) diff_log_q = diff(log10.(q)) left_diff_log_q = view(diff_log_q, [firstindex(diff_log_q); eachindex(diff_log_q)]) right_diff_log_q = view(diff_log_q, [eachindex(diff_log_q); lastindex(diff_log_q)]) return left_diff_log_q + right_diff_log_q end function load_config(filename::String) meta, params_init, lower_bounds, upper_bounds = load_init_params(filename) f = open(meta["data_file"], "r") qie_data = readdlm(f, '\t') close(f) return (meta=meta, params_init=params_init, lower_bounds=lower_bounds, upper_bounds=upper_bounds, qie_deta=qie_data) end function lowpass_filter(i; σ=1) half_w = 10 x = range(-5, 5; length=2half_w + 1) i_padded = view(i, [fill(firstindex(i), half_w); eachindex(i); fill(lastindex(i), half_w)]) k = exp.(-0.5 * ((x / σ) .^ 2)) / (2 * σ * sqrt(2π)) k ./= sum(k) r = DSP.conv(i_padded, k)[2half_w+1:end-2half_w] return r end function chi2(I_data, I_model, err) return sum((I_data .- I_model ./ err) .^ 2) end function add_log_barriers(f::Function, constraints::Vector{Tuple{T,T}}; padding_factor=0.1) where {T<:Real} n = length(constraints) lower_shifts = Float64[] upper_shifts = Float64[] padding_factors = if padding_factor isa Vector padding_factor else fill(padding_factor, n) end k = 0 barrier_widths = map(constraints) do (lower, upper) k += 1 if upper <= lower throw("admissible set is empty, check constraints") end if isfinite(lower) push!(lower_shifts, lower) if isfinite(upper) push!(upper_shifts, upper) return padding_factors[k] * (upper - lower) else push!(upper_shifts, Inf) return 1.0 end else push!(lower_shifts, -Inf) if isfinite(upper) push!(upper_shifts, upper) return 1.0 else push!(upper_shifts, Inf) return 1.0 end end end function std_lower_barrier(s::Float64) return max(-log(s + 1.0), 0.0)^2 end function barrier(x::Vector{Float64}) lb = (x .- lower_shifts) ./ barrier_widths ub = (upper_shifts .- x) ./ barrier_widths lb_violations = findall(<=(-1.0), lb) ub_violations = findall(<=(-1.0), ub) if !isempty(lb_violations) err_msg = "" for i in lb_violations err_msg *= " · x[$i] = $(x[i]) < $(constraints[i][1]), width = $(barrier_widths[i])" end @error err_msg throw("lower bound violation for indice(s) $(lb_violations)") end if !isempty(ub_violations) err_msg = "" for i in ub_violations err_msg *= " · x[$i] = $(x[i]) > $(constraints[i][2]), width = $(barrier_widths[i])" end @error err_msg throw("upper bound violation for indice(s) $(ub_violations)") end v = sum(std_lower_barrier.(lb) + std_lower_barrier.(ub)) return v end return x::Vector{Float64} -> f(x) .+ barrier(x) end end # module Utils