On Thu, Jun 23, 2011 at 8:20 AM, Neal Becker <[email protected]> wrote:
> Olivier Delalleau wrote:
>
>> What about :
>> dict((k, [e for e in arr if (e['x0'], e['x1']) == k]) for k in cases)
>> ?
>
> Not bad! Thanks!
>
> BTW, is there an easier way to get the unique keys, then this:
>
> cases = tuple (set (tuple((e['a'],e['b'])) for e in u))
I think you can just combine these 2
experiments = defaultdict([]) #syntax ?
for i, e in enumerate(arr):
experiments[tuple((e['a'],e['b']))].append(i)
#experiments[tuple((e['a'],e['b']))].append(y['c']) #or just
summarize results
experiments.keys() #uniques
(just typed not checked)
Josef
>
>>
>> (note: it is inefficient written this way though)
>>
>> -=- Olivier
>>
>> 2011/6/23 Neal Becker <[email protected]>
>>
>>> I have a set of experiments that I want to plot. There will be many plots.
>>> Each will show different test conditions.
>>>
>>> Suppose I put each of the test conditions and results into a recarray. The
>>> recarray could be:
>>>
>>> arr = np.empty ((#experiments,), dtype=[('x0',int), ('x1',int), ('y0',int)]
>>>
>>> where x0,x1 are 2 test conditions, and y0 is a result.
>>>
>>> First I want to group the plots such according to the test conditions. So,
>>> I
>>> want to first find what all the combinations of test conditions are.
>>>
>>> Dunno if there is anything simpler than:
>>>
>>> cases = tuple (set ((e['x0'], e['x1'])) for e in arr)
>>>
>>> Next, need to select all those experiments which match each of these cases.
>>> Now
>>> I know of no easy way.
>>>
>>> Any suggestions? Perhaps I should look again at pytables?
>>>
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>>>
>
>
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