Working with Indices¶
Without indices, it is really hard to work with big models: one has to give each variable a different name. In modern modeling languages such as AMPL and GMPL, index sets are an essential building instrument, which is really not surprising, as we see indices almost everywhere in advanced mathematics. PyMathProg also provides a solution to indexing into variables and constraints.
Natural indices¶
Python already provides some natural indices: tuples, lists, sets(such as the keys in a dict), or anything iterable(e.g. a generator, a sequence, etc.). For an object to become an legitimate index, it has to be immutable, which means that its value should not change (in the sense defined by the magic method of __eq__) during its entire life cycle. By the tacit contract between objects in Python, objects of equal value should also produce the same hash code, thus immutable objects have a constant hash code, which is used for indexing purposes to quickly locate an object in a set or dict.
PyMathProg trusts you to provide a list, a tuple, a set, a dict (in such case only the keys are used for indices), or any iterable as a set of indices without repeated elements. They can be utilized in PyMathProg as indices for variables, constraints, and parameters. If your put duplicate indices there, things could get lost.
Combined indices¶
PyMathProg also provides a way to combine smaller index sets into bigger ones by the concept of set product. Given two sets A and B, the product of A * B is defined as:
A * B = { (a,b) : a in A, b in B }
In the pymprog module, there is a class to achieve this:
>>> from pymprog import *
>>> A = (1, 2, 3)
>>> B = (6, 7, 8)
>>> C = iprod(A,B)
>>> for c in C: print(c)
...
(1, 6) (1, 7) (1, 8) (2, 6) (2, 7) (2, 8) (3, 6) (3, 7) (3, 8)
Well, that’s about it. By the way, the constructor iprod(...) can take as many iterables (sets, lists, tuples, or sequences) as you want – that’s the cool part of it.
Use index with variables¶
It is simple to create many variables over some indices in PyMathProg. Let’s continue the Python session above:
>>> begin('test')
>>> x = var('x', C)
>>> type(x)
<type 'dict'>
>>> x[2,7].name
'x[2,7]'
So we use the combined set C as the index set to create variables, the major variable name is ‘X’. Out of curiosity, we want to know the type of the python object referenced by ‘x’: it turns out to be a dict type – probably that is not that important anyway, what is more important is how easily and intuitively it is indexed, as shown in the next line.