return object from dictionary of nested lists when a condition (python) -

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i have dictionary looks like: 

myd={'key_0':[[['descrp_0_0'],obj_0_0],.....,[['descrp_0_n'],obj_0_n]]  ,.....,  'key_n':[[['descrp_n_0'],obj_n_0],.....,[['descrp_n_n'],obj_n_n]]}

all objs ndarrays of same shape , have function f() returns x float i.e.: obj_0_0.f() --> x_0_0

i want extract dictionary descrp , obj , respective key obj.f() (i.e. x) minimum values in each key (at myd scope of n keys give n items in shape of [descrp,obj]):

the result must like:

resd = {'key_0':[[descrp_0_min],obj_0_min],     .....,      'key_n':[[descrp_n_min],obj_0_min]}

something like:

minxs = [min([item[-1].f() item in v]) k,v in myd.iteritems()]  minobjs = [item k,v in myd.iteritems() item in v if item[-1].get_potential_energy() == minxs[myd.keys().index(k)]]  resultlist = zip(myd.keys(),minobjs) resultdict = dict() in resultlist:      resultdict[i[0]]=i[1]

although works rather cumbersome , think there must easier way this. or maybe should use numpy.ndarray purpose?

i appreciate , comments.

if i've understood structure of data correctly, think can solve dictionary comprehension calls builtin min function , gives key function.

results = {key: min(values, key=lambda x:x[-1].f())            key, values in myd.iteritems()}

your code close already!


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