Re: [Numpy-discussion] question/request with Numeric compress and putmask

[Travis E. O. <oli...@ee...>]

Vineet Jain wrote:


> I'm using the Numeric arrays for financial data elements. I'm interfacing
> with an external c library which does not support invalid elements. To get
> around this I maintain a separate mask array in my python class which
> denotes which elements are valid. I then use the compress function with the
> mask array to get an array with valid elements which I pass to the c
> function.
> 
> What I would like to do is:
> 
> putmask(full_return_value, my_mask, return_value)
> 
> where return_value is treated like a list so that every 1 that is found in
> my_mask the next element in return_value is used. Is their anything that
> matches this?
> 

There are functions in SciPy to handle exactly this situation.


 >>> from scipy import *
 >>> info(insert)
  insert(arr, mask, vals)

Similar to putmask arr[mask] = vals but 1d array vals has the
same number of elements as the non-zero values of mask. Inverse of extract.
 >>> info(extract)
  extract(condition, arr)

Elements of ravel(condition) where ravel(condition) is true (1-d)

Equivalent of compress(ravel(condition), ravel(arr))



Thus, for your problem I would do:

financial_data 	= [10, 11, 22, 33, INVALID, INVALID, 44, 55]
my_mask 		= [1, 1, 1, 1, 0, 0, 1, 1]
compressed_data = extract(my_mask, financial_data)
return_value 	= some_c_function(compressed_data)
insert(financial_data, my_mask, return_value)


These functions are in scipy_base and so you only need to install 
scipy_base to get them.

Best regards,

-Travis Oliphant