interpolation.jl

import Interpolations
import Dierckx

function interpolate_data(tsteps_old, tsteps_new, y, options)
  # Apply interpolation according to the options
  y_interp = if options.interpolation_method == "Dierckx"

    if options.boundary_condition == "flat"
      s = Dierckx.Spline1D(tsteps_old,y,bc="nearest")
      s(tsteps_new)
    elseif options.boundary_condition == "extrapolate"
      s = Dierckx.Spline1D(tsteps_old,y,bc="extrapolate")
      s(tsteps_new)
    end

  elseif options.interpolation_method == "Interpolations"

    if options.boundary_condition == "flat"
      #construct the interpolation object
      itp = Interpolations.interpolate(y, Interpolations.BSpline(Cubic()))
      itp = extrapolate(itp, Flat())
      #And evaluate it at daily time steps
      itp(tsteps_new)

    elseif options.boundary_condition == "extrapolate"

      #construct the interpolations object
      itp = Interpolations.interpolate(y, Interpolations.BSpline(Cubic()))
      itp = extrapolate(itp, Line())
      #and evaluate it at daily time steps
      itp(tsteps_new)
    end

  elseif options.interpolation_method == "Nearest"

    #Loop over target time steps
    map(tsteps_new) do itime
      #Find the nearest source time step
      d, ix = findmin(abs.(itime.-tsteps_old))
      tsteps_old[ix] # return value at this index
    end

  end
  return y_interp
end