DemoPlots

plot_demography(para::Vector{T}, stderrors::Vector{T} ax; kwargs...)
plot_demography(fit::DemoInfer.FitResult, ax; kwargs...)

Plot the demographic profile encoded in the parameters inferred by the fit.

ax is the pyplot ax where to plot the demographic profile.

Arguments

• max_t = 1e7: the furthest time to plot
• g = 29: arbitrary scaling factor for a generation

Further optional arguments are passed to plot from pyplot.

plot_input(TN, ax; max_t = 1e7, g = 29, kwargs...)

Plot the demographic profile encoded in the parameters TN as input.

Arguments

• max_t: the furthest time to plot
• g = 29: arbitrary scaling factor for a generation
• kwargs...: the keywords that PyPlot plot accepts

plot_lineages(para::Vector, ax, rho; max_t = 1e7, g = 29, k = 0, kwargs...)

Plot the number of coalescing lineages as a function of time, given the parameters para.

ax is a pyplot axis, rho is the recombination rate per bp per generation.

Arguments

• max_t = 1e7: the furthest time, in generations, at which the coalescent is evaluated
• g = 29: arbitrary scaling factor for a generation
• k = 0: the minimum length of associated IBD segment in bp

Further optional arguments are passed to plot and scatter from pyplot.

plot_remnbps(para::Vector, ax; max_t = 1e7, g = 29, kwargs...)

Plot the remaining number of base pairs as a function of time, given the parameters para.

ax is a pyplot axis.

Arguments

• max_t = 1e7: the furthest time, in generations, at which the coalescent is evaluated
• g = 29: arbitrary scaling factor for a generation

Further optional arguments are passed to plot and scatter from pyplot.

xy(h::HistogramBinnings.Histogram{T, 1, E}; mode = :density) where {T, E}

Return the midpoints and the weights of the histogram h.

Arguments

• h: the histogram
• mode: the normalization mode, :density normalizes counts by bins widths