# [SciPy-Dev] Proposed enhancement: pure Python implementation of LP simplex method (two-phase)

Pauli Virtanen pav@iki...
Fri Jul 30 03:49:31 CDT 2010

```Fri, 30 Jul 2010 09:48:49 +0800, Enzo Michelangeli wrote:
[clip]
>>> http://projects.scipy.org/scipy/ticket/1252
>>
>> I think your "test case" could easily be turned into a unit test, which
>> would make the submission more complete.
>
> Done.

Seems to work.

Some API nitpicks,

1)

Return a solution object rather than a tuple:

class NamedTuple(tuple):
def __new__(cls, values, names):
self = tuple.__new__(cls, values)
for value, name in zip(values, names):
setattr(self, name, value)
return self

class Solution(NamedTuple):
_fields = []
def __new__(cls, *a, **kw):
values = list(a)
for name in cls._fields[len(values):]:
values.append(kw.pop(name))
if len(values) != len(cls._fields) or kw:
raise ValueError("Invalid arguments")
return NamedTuple.__new__(cls, values, cls._fields)

def __repr__(self):
return "%s%s" % (self.__class__.__name__,
NamedTuple.__repr__(self))

class LPSolution(Solution):
"""
Solution to a linear programming problem

Attributes
----------
x
The optimal solution
min
The optimal value
is_bounded
True if the solution is bounded; False if unbounded
solvable
True if the problem is solvable; False if unsolvable
basis
Indices of the basis of the solution.
"""
_fields = ['x', 'min', 'is_bounded', 'solvable', 'basis']

def lp(...):
...
return LPSolution(optx, zmin, is_bounded, sol, basis)

We could (and probably should) replace *all* cases in Scipy where a tuple
is currently returned by this sort of pattern. It's backwards compatible,
since the returned object is still some sort of a tuple.

2)

Don't print to stdout.

Use warnings.warn if you need to warn about something.

3)

Call

c = np.asarray(c)
A = np.asarray(A)
b = np.asarray(b)

in the beginning -- good for convenience.

--
Pauli Virtanen

```