Hi Travis
On Thu, Dec 20, 2007 at 05:24:44PM -0600, Travis E. Oliphant wrote:
* bool(x) raises a ValueError, as it does for ndarrays.
What does bool(x) raise for numpy.core.ma.
It now behaves the same way as numpy does, raising a ValueError:
In [1]: bool(N.ma.array([0,1]))
On Fri, Dec 21, 2007 at 10:43:28AM +0200, Stefan van der Walt wrote:
On Thu, Dec 20, 2007 at 05:24:44PM -0600, Travis E. Oliphant wrote:
* bool(x) raises a ValueError, as it does for ndarrays.
What does bool(x) raise for numpy.core.ma.
Sorry, I realise you were talking about the old
On Thu, Dec 20, 2007 at 06:52:38PM -0500, Pierre GM wrote:
If we can document exactly what the compatibility issues are (and it
looks like we are almost there), we should move forward.
OK, I'll take care of that this week-end. Stefan, feel free to beat me to
it...
A first draft is here:
Stefan,
I think the description of the putmask difference is missing the point.
The real difference is not in the way the third argument is handled,
or its required shape, but in whether the mask is updated or not.
numpy.ma.putmask updates the mask; that is, if it puts something into
the
Stefan van der Walt wrote:
Hi Travis,
During the sprint I also merged Pierre's MaskedArray code into the
maskedarray branch. That is nearly done, with only a few unit tests
still failing -- ones brought over from the old numpy.ma.
This is mainly due to some changes in the API, for example
Pierre GM wrote:
All,
I'd like to move forward with it sooner (for 1.0.5) if the API changes
are not drastic. Although ideally 0 API changes would be desireable,
I'm not sure if that is feasible. Are put and putmask the only changes
in the API. What are the rest of them?
* cumsum(cumprod) works as if the _data array was filled with 0 (1). The
mask is preserved, but not updated. (the output of numpy.core.ma has
nomask).
I don't understand what you mean here.So, the mask effectively
removes those elements from the sum(product) computation? What does it
