Angus McMorland wrote:
> On 23 June 2010 16:13, Alan Bromborsky wrote:
>
>> Alan Bromborsky wrote:
>>
>>> In the transpose function we have transpose(a,axis) where axis can be a
>>> list of integers. But exactly what to the integers mean? If axis =
>
Alan Bromborsky wrote:
> In the transpose function we have transpose(a,axis) where axis can be a
> list of integers. But exactly what to the integers mean? If axis =
> [i1,i2] switching axis i1 with axis i2 is obvious, but what if axis =
> [i1,i2,i3]. Does this describe a cyclic
In the transpose function we have transpose(a,axis) where axis can be a
list of integers. But exactly what to the integers mean? If axis =
[i1,i2] switching axis i1 with axis i2 is obvious, but what if axis =
[i1,i2,i3]. Does this describe a cyclic permutation where
i1->i2->i3->i2 or what doe
Friedrich Romstedt wrote:
> 2010/6/13 Alan Bromborsky :
>
>> Friedrich Romstedt wrote:
>>
>>>> I am writing symbolic tensor package for general relativity. In making
>>>> symbolic tensors concrete
>>>> I generate
tware/theano/library/tensor/basic.html
>
> Dag Sverre
>
> Alan Bromborsky wrote:
>
>> Sebastian Walter wrote:
>>
>>> On Sun, Jun 13, 2010 at 8:11 PM, Alan Bromborsky
>>> wrote:
>>>
>>>
&g
Sebastian Walter wrote:
> On Sun, Jun 13, 2010 at 8:11 PM, Alan Bromborsky wrote:
>
>> Friedrich Romstedt wrote:
>>
>>> 2010/6/13 Pauli Virtanen :
>>>
>>>
>>>> def tensor_contraction_single(tensor, dimensions):
>>&
Friedrich Romstedt wrote:
> 2010/6/13 Alan Bromborsky :
>
>> I am writing symbolic tensor package for general relativity. In making
>> symbolic tensors concrete
>> I generate numpy arrays stuffed with sympy functions and symbols.
>>
>
> Tha
Friedrich Romstedt wrote:
> 2010/6/13 Pauli Virtanen :
>
>> def tensor_contraction_single(tensor, dimensions):
>>"""Perform a single tensor contraction over the dimensions given"""
>>swap = [x for x in range(tensor.ndim)
>>if x not in dimensions] + list(dimensions)
>>x =
Friedrich Romstedt wrote:
> 2010/6/12 Alan Bromborsky :
>
>> If I have a single numpy array, for example with 3 indices T_{ijk} and I
>> want to sum over two them in the sense of tensor contraction -
>>
>> T_{k} = \sum_{i=0}^{n-1} T_{iik}. Is there an eas
If I have a single numpy array, for example with 3 indices T_{ijk} and I
want to sum over two them in the sense of tensor contraction -
T_{k} = \sum_{i=0}^{n-1} T_{iik}. Is there an easy way to do this with
numpy?
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