I have been working on generating all possible submodels for a biological problem. I have a working recursion for generating a big list of all the submodels I want. However, the lists get unmanageably large pretty fast (N=12 is just possible in the example below, N>12 uses too much memory). So I wanted to convert it to a generator function using yield instead, but I'm stuck.
My working recursive function looks like this:
def submodel_list(result, pat, current, maxn):
''' result is a list to append to
pat is the current pattern (starts as empty list)
current is the current number of the pattern
maxn is the number of items in the pattern
'''
if pat:
curmax = max(pat)
else:
curmax = 0
for i in range(current):
if i-1 <= curmax:
newpat = pat[:]
newpat.append(i)
if current == maxn:
result.append(newpat)
else:
submodel_generator(result, newpat, current+1, maxn)
result = []
submodel_list(result, [], 1, 5)
That gives me the expected list of submodels for my purposes.
Now, I want to get that same list using a recursion. Naively, I thought I could just switch out my result.append() for a yield function, and the rest would work OK. So I tried this:
def submodel_generator(pat, current, maxn):
'''same as submodel_list but yields instead'''
if pat:
curmax = max(pat)
else:
curmax = 0
for i in range(current):
print i, current, maxn
if i-1 <= curmax:
print curmax
newpat = pat[:]
newpat.append(i)
if current == maxn:
yield newpat
else:
submodel_generator(newpat, current+1, maxn)
b = submodel_generator([], 1, 5)
for model in b: print model
But now I get nothing. A (very dumb) bit of digging tells me the function gets to the final else statement once, then stops - i.e. the recursion no longer works.
Is there a way to turn my first, clunky, list-making function into a nice neat generator function? Is there something silly I've missed here? All help hugely appreciated!
You should change this:
submodel_generator(newpat, current+1, maxn)
to this:
for b in submodel_generator(newpat, current+1, maxn):
yield b
This will recursively yield the value from successive calls to the function.
[Update]: Note that as of Python 3.3, you can use the new yield from syntax:
yield from submodel_generator(newpat, current+1, maxn)
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