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Cash flow model libraryΒΆ

Besides cash flow tables, costs and incomes associated with operations or tree value models can also be defined with cash flow models; i.e., models predicting the unit price changes over time based on some variables.

All cash flow models have the same set of input parameters:

  • table – cash flow table object (for details, see
  • date – current date as datetime object
  • variables – cash flow model input variables
  • parameters – cash flow model parameters
  • errors – container for returning errors from the model

Below is an example of a stochastic timber assortment price model:

def random_prices(table, date, variables, parameters, errors):
    ret = True
    index = (1,2)

    # the initial year is now fixed to 2008
    n = date.year - 2008 + 1

    # load the prices and compute standardized delta (increment), simulate
    # prices for the next n years
    prices, delta_st = _load_prices()
    P = _simulate(prices, delta_st, n, 2)

    # store the prices of the last year
    table.set_values(index, PINELOG, P[-1,0])
    table.set_values(index, SPRUCELOG, P[-1,1])
    table.set_values(index, BIRCHLOG1, P[-1,2])
    table.set_values(index, BIRCHLOG2, P[-1,2])
    table.set_values(index, PINEPULP, P[-1,3])
    table.set_values(index, SPRUCEPULP, P[-1,4])
    table.set_values(index, BIRCHPULP1, P[-1,5])
    table.set_values(index, BIRCHPULP2, P[-1,5])

    return ret