Use a gridded search to find a combination of one or more of chemical activities of basis species, temperature and/or pressure that maximize or minimize a objective function of the metastable equilibrium chemical activities of the species of interest.

1 2 3 4 5 |

`lims` |
list, specification of search limits |

`objective` |
character, name of objective function to optimize |

`niter` |
numeric, number of iterations |

`res` |
numeric, grid resolution (number of points on one edge) |

`iprotein` |
numeric, indices of proteins |

`plot.it` |
logical, make a plot? |

`T` |
numeric, temperature |

`P` |
numeric, pressure; or character, "Psat" |

`labcex` |
numeric, character expansion for plot labels |

`loga2` |
numeric, reference logarithms of activity of species |

`loga.balance` |
numeric, logarithm of total activity of balanced quantity (passed to |

`rat` |
numeric, ratio of edge length in successive iterations |

`balance` |
character or numeric, balanced quantity (passed to |

`normalize` |
logical, normalize chemical formulas by the balance vector? (passed to |

`x` |
list, object of class |

`which` |
numeric, which of the parameters to plot |

`mar` |
numeric, plot margin specification |

`xlab` |
character, x-axis label |

`...` |
additional arguments passed to |

`findit`

implements a gridded optimization to find the minimum or maximum value of an `objective`

function.
The variables are one or more of the chemical activities, temperature and/or pressure whose ranges are listed in `lims`

.
Generally, the system (`basis`

species and `species`

of interest) must be set up before calling this function.
If `iprotein`

is supplied, indicating a set of proteins to use in the calculation, the definition of the `species`

is not required.
`lims`

is a list, each element of which is vector having a name that is the formula of one of the basis species, T or P and a pair of values indicating the range of the named parameter.
The values are the logarithms of activities of the basis species, or temperature or pressure (in the user's units; see `util.units`

).
If either T or P is missing from the list in `lims`

, the calculations are performed at isothermal and/or isobaric conditions indicated by `T`

and `P`

arguments.

Taking *nd* as the number of dimensions (number of variables in `lims`

), default values of `niter`

and `res`

come from the following table.
These settings have been selected to be able to run the function quickly in the higher dimensions.
Detailed studies of a system might have to use more iterations and/or higher resolutions.

`nd` | `niter` | `res` | grid points (`res^nd` ) | `rat` |

1 | 4 | 128 | 128 | 0.7 |

2 | 6 | 64 | 4096 | 0.7 |

3 | 6 | 16 | 4096 | 0.8 |

4 | 8 | 8 | 4096 | 0.9 |

5 | 12 | 6 | 7776 | 0.9 |

6 | 12 | 4 | 4096 | 0.95 |

7 | 12 | 4 | 16384 | 0.95 |

The function performs `niter`

iterations.
At first, the limits of the parameters given in `lims`

define the extent of a *nd*-dimensional box around the space of interest.
The value of `objective`

is calculated at each of the *res^nd* grid points and and optimum value located (see `revisit`

).
In the next iteration the new search box is centered on the location of the optimum value, and the edges are shrunk so their length is `rat`

* the length in the previous step.
If the limits of any of the parameters extend beyond those in `lims`

, they are pushed in to fit (preserving the difference between them).

`plot_findit`

plots the values of the parameters and the objective function as a function of the number of iterations.

`findit`

returns a list having class `findit`

with elements `value`

(values of the parameters, and value of the objective function, at each iteration), `lolim`

(lower limits of the parameters) and `hilim`

(upper limits of the parameters).

`demo("findit")`

and `tests/test-findit.R`

for examples.

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.