By the way, following Jason's reasoning above, by re-defining ZZ (which I 
have just realised was a bad choice of variable name sorry!) as 

ZZ = diagonal_matrix([exp(2*pi*I/4)^ii for ii in range(0,4)]).dense_matrix()

the problem does indeed go away. So there is a temporary workaround ...

On Saturday, August 17, 2013 9:58:40 AM UTC+1, GaryMak wrote:
>
> Dear Jason,
>
> thank you very much.
>
> Re the patch: sadly, I tried (thanks to Basu's infinitely patient hints) 
> to get involved with amending the docs a few months ago, but failed 
> miserably and even put up an ad for someone to help me with SAGE/computing 
> here at Imperial (!) but got nowhere with that ... I would love to be able 
> to do this but there are certain basics of how you guys have set this up 
> which I simply do not understand. And, frankly, my one year of formal IT 
> tuition in 1987 just doesn't cut it! So if you guys know of anyone in 
> London who can do some hand-holding (for which I'm happy to pay) through 
> this stuff then please put us in contact and I'll have another go ...
>
> Best regards
>
> Gary
>
> On Saturday, August 17, 2013 2:06:59 AM UTC+1, Jason Grout wrote:
>>
>> On 8/16/13 5:34 PM, Jason Grout wrote: 
>> > entries=dict([(e[0],e[1].n(prec, digits)) for e in 
>> > self._entries.iteritems()]) 
>> > if len(self)-1 not in entries: 
>> >      entries[len(self)-1]=0 
>> > vector(entries, sparse=True) 
>>
>>
>> It could be shortened by using the setdefault method: 
>>
>> entries=dict([(e[0],e[1].n(prec, digits)) for e in 
>> self._entries.iteritems()]) 
>> entries.setdefault(len(self)-1, 0) 
>> vector(entries, sparse=True) 
>>
>> Thanks, 
>>
>> Jason 
>>
>>
>>

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