results.rst

Extracting results

Once the model has been run, timeseries of solute outputs can be found in <Model object>.data_df. To save these as a .csv use:

my_model.data_df.to_csv('my_model_outputs.csv')

where my_model is a Model object.

Alternatively, raw results in the form of output arrays can be accessed through the <Model object>.results property, which returns a dict with the following keys:

sT : m x n+1 numpy float64 2D array

Array of instantaneous age-ranked storage for n+1 times, m ages. First column is initial condition (given by the sT_init option if provided, or all zeros otherwise)

pQ : m x n x q numpy float64 2D array

Array of timestep-averaged time-varying backward transit time distributions over m ages, at n times, for q fluxes.

WaterBalance : m x n numpy float64 2D array

Should always be within tolerances of zero, unless something is very wrong.

C_Q : n x q x s float64 ndarray

If input concetrations are provided (see :ref:`solspec`), this gives the timeseries of timestep-averaged outflow concentration

mT : m x n+1 x s float64 ndarray

Array of instantaneous age-ranked solute mass over m ages, at n times, for s solutes. First column is initial condition

mQ : m x n x q x s float64 ndarray

Array of timestep-averaged age-ranked solute mass flux over m ages, at n times, for q fluxes and s solutes.

mR : m x n x s float64 ndarray

Array of timestep-averaged age-ranked solute reaction flux over m ages, at n times, for s solutes.

SoluteBalance : m x n x s float64 ndarray

Should always be within tolerances of zero, unless something is very wrong.

The order that the fluxes q and solutes s appear in these arrays is given by the properties my_model.fluxorder and my_model.solorder. These provide lists of the column names in the order they are given in results.