[Numpy-discussion] Deleting a row from a matrix

[Travis Oliphant]

Sebastian Haase wrote:
> On Friday 25 August 2006 08:01, Travis Oliphant wrote:
>   
>> Travis Oliphant wrote:
>>     
>>>> Now of course: I often needed to "insert"  a column, row or section, ...
>>>> ? I made a quick and dirty implementation for that myself:
>>>> def insert(arr, i, entry, axis=0):
>>>>     """returns new array with new element inserted at index i along axis
>>>>     if arr.ndim>1 and if entry is scalar it gets filled in (ref.
>>>> broadcasting)
>>>>
>>>>     note: (original) arr does not get affected
>>>>     """
>>>>     if i > arr.shape[axis]:
>>>>         raise IndexError, "index i larger than arr size"
>>>>     shape = list(arr.shape)
>>>>     shape[axis] += 1
>>>>     a= N.empty(dtype=arr.dtype, shape=shape)
>>>>     aa=N.transpose(a, [axis]+range(axis)+range(axis+1,a.ndim))
>>>>     aarr=N.transpose(arr, [axis]+range(axis)+range(axis+1,arr.ndim))
>>>>     aa[:i] = aarr[:i]
>>>>     aa[i+1:] = aarr[i:]
>>>>     aa[i] = entry
>>>>     return a
>>>>         
>>> Sure, it makes sense to parallel the delete function.
>>>       
>> Although there is already and insert function present in numpy....
>>
>> -Travis
>>     
>
> Yeah - I saw that ...
> maybe one could introduce consistent namings like
> arr.copy_insert()
> arr.copy_delete()
> arr.copy_append()
>   

I've come up with adding the functions (not methods at this point)

deletefrom
insertinto

appendto  (syntatic sugar for concatenate but with a separate argument 
for the array and the extra stuff) --- is this needed?

These functions will operate along a particular axis (default is axis=0 
to match concatenate).

Comments?

-Travis