[Numpy-discussion] Created NumPy 1.7.x branch
Mon Jun 25 12:56:54 CDT 2012
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.
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