[Numpy-discussion] Created NumPy 1.7.x branch
Charles R Harris
charlesr.harris at gmail.com
Mon Jun 25 15:25:09 EDT 2012
On Mon, Jun 25, 2012 at 11:56 AM, Perry Greenfield <perry at stsci.edu> wrote:
> On Jun 25, 2012, at 12:20 PM, Charles R Harris wrote:
> >>> Most folks aren't going to transition from MATLAB or IDL.
> >>> Engineers tend to stick with the tools they learned in school,
> >>> they aren't interested in the tool itself as long as they can get
> >>> their job done. And getting the job done is what they are paid
> >>> for. That said, I doubt they would have much problem making the
> >>> adjustment if they were inclined to switch tools.
> >> I don't share your pessimism. You really think that "most folks
> >> aren't going to transition". It's happening now. It's been
> >> happening for several years.
> > I still haven't seen it. Once upon a time code for optical design
> > was a new thing and many folks wrote their own, myself for one.
> > These days they reach for Code V or Zemax. When they make the
> > schematics they use something like Solidworks. When it comes time
> > for thermal anaysis they run the Solidworks design into another
> > commercial program. When it comes time to manufacture the parts
> > another package takes the Solidworks data and produces nc
> > instructions to drive the tools. The thing is, there is a whole
> > ecosystem built around a few standard design tools. Similar
> > considerations hold in civil engineering, architecture, and many
> > other areas.
> > Another example would be Linux on the desktop. That never really
> > took off, Microsoft is still the dominant presence there. Where
> > Linux succeeded was in embedded devices and smart phones, markets
> > that hadn't yet developed a large ecosystem and where pennies count.
> > Now to Matlab, suppose you want to analyse thermal effects on an
> > orbiting satellite. Do you sit down and start writing new code in
> > Python or do you buy a package for Matlab that deals with orbital
> > calculations and knows all about shading and illumination? Suppose
> > further that you have a few weeks to pull it off and have used the
> > Matlab tools in the past. Matlab wins in this situation, Python
> > isn't even a consideration.
> > There are certainly places for Python out there. HPC is one, because
> > last I looked Matlab licenses were still based around the number of
> > cpu cores, so there are significant cost savings. Research that
> > needs innovative software is another area where Python has an
> > advantage. First, because in research it is expected that time will
> > be spent exploring new things, and second because it is easier to
> > write Python than Matlab scripts and there are more tools available
> > at no cost. On the other hand, if you need sophisticated
> > mathematics, Mathematica is the easy way to go.
> > Engineering is a big area, and only a small part of it offers
> > opportunity for Python to make inroads.
> It's hard to generalize that much here. There are some areas in what
> you say is true, particularly if whole industries rely on libraries
> that have much time involved in developing them, and for which it is
> particularly difficult to break away. But there are plenty of other
> areas where it isn't that hard.
> I'd characterize the process a bit differently. I would agree that it
> is pretty hard to get someone who has been using matlab or IDL for
> many years to transition. That doesn't happen very often (if it does,
> it's because all the other people they work with are using a different
> tool and they are forced to). I think we are targeting the younger
> people; those that do not have a lot of experience tied up in matlab
> or IDL. For example, IDL is very well established in astronomy, and
> we've seen few make that switch if they already have been using IDL
> for a while. But we are seeing many more younger astronomers choose
> Python over IDL these days.
I didn't bring up the Astronomy experience, but I think that is a special
case because it is a fairly small area and to some extent you had the
advantage of a supported center, STSci, maintaining some software. There
are also a lot of amateurs who can appreciate the low costs and simplicity
The software engineers use tends to be set early, in college or in their
first jobs. I suspect that these days professional astronomers spend a
number of years in graduate school where they have time to experiment a
bit. That is a nice luxury to have.
-------------- next part --------------
An HTML attachment was scrubbed...
More information about the NumPy-Discussion