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.. currentmodule:: ficus

Run ficus

Run from Python

Running the model from python gives you more options for running the optimisation and plotting the results. Simply run the runficus.py script in the examples folder using e.g. python, ipython or spyder. After running the script, the shell should show the actual status and a few minutes later six result figures should show up. The sub-folder result should contain the saved result figures as well as a result-file.

runficus.py

Here the runficus.py script is explained step by step, so you can change it and use it for your own model.

import os
import ficus

Two packages are included.

To import ficus, ficus.py hast to be either in the same directory than runficus.py or in any directory, that is searched by python. To make sure this is the case, follow step 4 of the :ref:` installation <install-ref>`.

input_file = 'example.xlsx'

Gives the path to the input_file used for model creation. If the file is not in the same folder than ficus.py, give the FULL PATH (e.g. C:\YOUR\INPUT\FILE.xlsx). To run one of the other examples, just change the name of the input file.

result_folder = 'result'
result_name = os.path.splitext(os.path.split(input_file)[1])[0]
result_dir = ficus.prepare_result_directory(result_folder,result_name)

Creates a time stamped folder result_name-TIME within the result_folder directory and saves the full path to result_dir. Give FULL PATH for result_folder, if it should not be in the same directory, than runficus.py

prob = ficus.run_ficus(input_file, opt = 'cbc', neos=True)

The :func:`run_ficus` function, is the "work horse", where most computation and time is spent. The optimization problem is first defined and filled with values from the input_file. Then the solver opt is called to solve the model. If neos is set to True, the problem is sent to the 'NEOS Server for Optimization'_ to solve the problem (Note, that using some solvers on NEOS require a license). If neos is set to false, the locally installed solver is used (if installed). After solving the problem the results are read back to the prob object.

If locally installed solver gurobi or cplex are used, the parameter Threads allows to set the maximal number of simultaneous CPU threads.

ficus.report(prob, result_dir)

Saves the results from the object prob to an excel file in the directory result_dir.

ficus.result_figures(result_dir,prob=prob, show=True)

Reads and plots the results from the object prob and saves them in the directory result_dir. Can also be used to plot data from a given result-file with the Parameter resultfile=PATH\\TO\\RESULTFILE.xlsx instead of giving prob. show turns on/off showing the plots.

Run from Excel

For an easy first run of ficus without using any python environment a small macro in VBA allows running the optimization directly from Excel. Still python an all needed packages have to be installed on the computer.

  • Open the file example_fromexcel.xlsm in the examples folder
  • Go to the RUN sheet and choose a solver. If you choose any other than a neos-... solver, the solver hast to be installed locally on your computer. With me only the mosek and the cbc solver from NEOS Server for Optimization are working (no installation of solvers required)
  • Push the RUN OPTIMIZATION button.

A cmd window should appear showing the actual status and a few minutes later six result figures should show up. The sub-folder result should contain the saved result figures as well as a result-file.

Using this way of running the model, the function :func:`run_from_excel` from the ficus.py script is called within VBA. This requires, that ficus.py can be found by python. To make sure this is the case, follow step 4 of the :ref:`installation <install-ref>`.

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