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I am trying to do some parameter testing on another code using python. I need to test 6 independent parameters, but I need all of the possible combinations of them.
Each parameter has a minimum, a maximum, and a step value that needs to be passed to it. The first easy solution that popped into my head was a nested for loop structure that looked horrific, like this:
for var1 in xrange(min1,max1,step1): for var2 in xrange(min2,max2,step2): ... ... ... for var6 in xrange(min6,max6,step6): ''' Do something and be icky in the process due to being in the middle of six nested for loops ''' I decided, no! This shall not stand. So I've been trying to work out a way to do this recursively, or at the very least, not nested six times. I can't really come up with a good scheme to do so. The biggest obstacle for me is that each variable has a different min, max, and step value.
My thoughts so far aren't very helpful. I keep trying to make some recursive function work, but I just can't figure it out without nesting more for loops within the function. I've seen a lot of reference to itertools.product on here, but I can't quite figure out how to make that work either.
Edit: What I'm doing is creating a directory named after the combination of the parameters, writing a file with those parameters, running another code with this file, and analyzing the output from that code. I am doing nothing in literally any of the for loops except for the final one. A lot of the parameters only have 2 values, some have 10, others have 3... it just kind of varies.
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Nesting loops inside of each other in python makes for much harder code to understand, it takes more brain power to understand, and is thus more error prone than if its avoidable.
Avoid nested loops with itertools. You can use itertools. product() to get all combinations of multiple lists in one loop and get the same result as nested loops. Since it is a single loop, you can simply break under the desired conditions. Adding the argument of itertools.
The complexity of having nested loops in your case is O(n * m) - n the length of orderArr , and m the length of myArr . This solution complexity is O(n + m) because we're creating the dictionary object using Array#reduce with complexity of O(m), and then filtering the orderArray with a complexity of O(n).
Here's how to use product:
x1 = xrange(min1,max1,step1) x2 = xrange(min2,max2,step2) x3 = xrange(min3,max3,step3) ... for v1, v2, v3, v4, v5, v6 in itertools.product(x1, x2, x3, x4, x5, x6): icky_thing(....) or a bit more compactly:
ranges = [ xrange(min1,max1,step1), xrange(min2,max2,step2), xrange(min3,max3,step3), ... ] for v1, v2, v3, v4, v5, v6 in itertools.product(*ranges): icky_thing(....) If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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