FICO Xpress Optimization Examples Repository: Python files for the Mosel-Python comparison blog

FICO Xpress Optimization Examples Repository

Python files for the Mosel-Python comparison blog

Description

Python files for the blog post comparing Mosel and Python: 4 Main Takeaways from Comparing Xpress Mosel and Python for Optimization Models.

Instructions for running these files:

Extract the data files into the same directory as the Python files.
To run a single file via the command line, call Python and pass the filename followed by the first 2 digits of the data file. For example: python SparseGrouping_std.py 00

pythonblog.zip

[download all files]

Source Files

By clicking on a file name, a preview is opened at the bottom of this page.

ComplexConstraints_std.py	[download]
ComplexConstraints_adv.py	[download]
MatrixVariables_std.py	[download]
MatrixVariables_adv.py	[download]
ProductsMachines_std.py	[download]
ProductsMachines_adv.py	[download]
QuantityDiscount_std.py	[download]
QuantityDiscount_adv.py	[download]
SparseGrouping_std.py	[download]
SparseGrouping_adv.py	[download]
SparseVariables_std.py	[download]
SparseVariables_adv.py	[download]
TSP_std.py	[download]
TSP_adv.py	[download]

Data Files

00_H_MatrixVariables_V.csv	[download]
00_H_ProductsMachines_T.csv	[download]
00_H_TSP_cities.csv	[download]
00_H_ComplexConstraints_D.csv	[download]
00_H_ProductsMachines_K.csv	[download]
00_H_QuantityDiscount_V.csv	[download]
00_H_SparseVariables_C.csv	[download]
00_H_MatrixVariables_S.csv	[download]
00_H_SparseGrouping_C.csv	[download]
00_H_ProductsMachines_U.csv	[download]
00_H_TSP_tours.csv	[download]
ComplexConstraints.tar.gz	[download]
MatrixVariables.tar.gz	[download]
ProductsMachines.tar.gz	[download]
QuantityDiscount.tar.gz	[download]
SparseGrouping.tar.gz	[download]
SparseVariables.tar.gz	[download]
TSP.tar.gz	[download]
03_H_ProductsMachines_K.tar.gz	[download]
04_H_QuantityDiscount_V.tar.gz	[download]

SparseGrouping_adv.py

'''********************************************************
  * Python Example Problems                               *
  *                                                       *
  * file SparseGrouping_adv.py                            *
  * Improved version of model 'SparseGrouping_std.py'     *
  * -- Multiple cases within a loop over a sparse         *
  * array --                                              *
  *                                                       *
  * (c) 2019-2025 Fair Isaac Corporation                  *
  ******************************************************'''
#S:IMPORT
import pandas as pd
import numpy as np
import sys

if len(sys.argv) > 1:
    DATA_FILE_PREFIX = sys.argv[1]
else:
    DATA_FILE_PREFIX = "00"
print("#E:IMPORT")

print("#S:READ")
C = pd.read_csv(DATA_FILE_PREFIX + '_H_SparseGrouping_C.csv', index_col = ['i', 'j', 'k', 'l']).squeeze()
print("#E:READ")

print("#S:PROC")
a = np.array([100, 1000]) - 1
v = np.array([1, 2, 3])

G = pd.Series(data = v[np.searchsorted(a, C)], index = C.index, name = 'G')
print("#E:PROC")

print("#S:TEST")
for ((i, j, k, l), v) in G.items():
    print('{} {} {} {} {}'.format(i, j, k, l, v))
print("#E:TEST")


# Pietro suggestion