ANN: Job posting -- developer position available
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Hey group, We have a developer position open here at Enthought, and I thought I'd see if anyone is interested. The posting is below. There is also a tech writer and HCI opening listed on the website: http://www.enthought.com/careers.html thanks! eric Position: Python Developer Type: Full-Time Enthought, Inc. is a technology startup in the Austin, TX area that is looking for a motivated Python Developer to join our development team. Responsibilities include developing and deploying scientific applications within the Fortune 500. Our size and prospects provide significant opportunity for growth and advancement for Enthought employees. Candidates should have the following qualifications: - BS or MS in Computer Science or Engineering or other scientific field - 3+ years experience in the software industry - Experience developing solutions in the following languages: - Python - C/C++ - User interface design experience - Developing and deploying custom solutions for clients - Excellent verbal and written communication skills Ideal candidates will also demonstrate the following skills: - Use of the wxPython user interface library - Experience with Geophysics applications - Experience in the fields of statistics, linear algebra and calculus Please send resumes to jobs@enthought.com.
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Hi all, There was a lot of discussion a long while back about how Numeric treats erros in the middle of an array operation. The way it works is if one operation in an array has a problem (overflow, division by zero, etc), an exception is returned. You have no idea which element caused the problem, and teh whole operation grinds to a halt. Personally, I would MUCH prefer MATLAB's way of handling this: the problematic operation results in a -Inf, Inf, or NaN result for that element, and the rest of the array operation can continue. MATLAB also provides utility functions along the line of isnan, isinf, etc, so you can check for the problematic areas later. There was a fair bit of disagreement over whether Numeric should act similarly, as well as the problem that not all compilers have the required IEEE support to make this work. Anyway, how does numarray handle this issue? I'd love to have the MATLAB behaviour...I'm writing this because I'm about to have to write a bunch of code to keep making sure I don't pass a 0 into log(), when I'd be much happier if I could just replace the NaNs with what I want later. -Chris -- Christopher Barker, Ph.D. Oceanographer NOAA/OR&R/HAZMAT (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception Chris.Barker@noaa.gov
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Chris Barker writes:
I don't recall if there was disagreement about this being useful, but perhaps there was disagreement that it should always do this.
numarray allows one to customize how errors are handled. You can choose: 1) to silently ignore all errors. 2) print a warning message (default) 3) raise an exception. One may separately set one of these three behaviors for each of the 4 ieee categories of floating point errors, namely 1) invalid results (i.e., NaNs) 2) divide by zeros (Infs) 3) overflows 4) underflows for the first two modes the computation on floats just inserts the appropriate ieee value in the array (Infs and NaNs). There are portable constants and functions to test and set these values (see examples below). These modes also apply to integer calculations. I've pasted some examples I presented from some slides shown at the scipy conference to illustrate how it works and what's available. Customize how errors are handled
Manipulate IEEE-754 special values
Use defined constants
Perry
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Perry Greenfield wrote:
I don't recall if there was disagreement about this being useful,
probably not
but perhaps there was disagreement that it should always do this.
absolutely, and I think there was a wide range of opinions about how usefull (and or critical!) this is.
Fabulous!!! You folks are wonderfull! I guess it's time to make the switch to numarray...I've been waiting for a compelling reason! -Chris -- Christopher Barker, Ph.D. Oceanographer NOAA/OR&R/HAZMAT (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception Chris.Barker@noaa.gov
![](https://secure.gravatar.com/avatar/5dde29b54a3f1b76b2541d0a4a9b232c.jpg?s=120&d=mm&r=g)
Hi all, There was a lot of discussion a long while back about how Numeric treats erros in the middle of an array operation. The way it works is if one operation in an array has a problem (overflow, division by zero, etc), an exception is returned. You have no idea which element caused the problem, and teh whole operation grinds to a halt. Personally, I would MUCH prefer MATLAB's way of handling this: the problematic operation results in a -Inf, Inf, or NaN result for that element, and the rest of the array operation can continue. MATLAB also provides utility functions along the line of isnan, isinf, etc, so you can check for the problematic areas later. There was a fair bit of disagreement over whether Numeric should act similarly, as well as the problem that not all compilers have the required IEEE support to make this work. Anyway, how does numarray handle this issue? I'd love to have the MATLAB behaviour...I'm writing this because I'm about to have to write a bunch of code to keep making sure I don't pass a 0 into log(), when I'd be much happier if I could just replace the NaNs with what I want later. -Chris -- Christopher Barker, Ph.D. Oceanographer NOAA/OR&R/HAZMAT (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception Chris.Barker@noaa.gov
![](https://secure.gravatar.com/avatar/c7976f03fcae7e1199d28d1c20e34647.jpg?s=120&d=mm&r=g)
Chris Barker writes:
I don't recall if there was disagreement about this being useful, but perhaps there was disagreement that it should always do this.
numarray allows one to customize how errors are handled. You can choose: 1) to silently ignore all errors. 2) print a warning message (default) 3) raise an exception. One may separately set one of these three behaviors for each of the 4 ieee categories of floating point errors, namely 1) invalid results (i.e., NaNs) 2) divide by zeros (Infs) 3) overflows 4) underflows for the first two modes the computation on floats just inserts the appropriate ieee value in the array (Infs and NaNs). There are portable constants and functions to test and set these values (see examples below). These modes also apply to integer calculations. I've pasted some examples I presented from some slides shown at the scipy conference to illustrate how it works and what's available. Customize how errors are handled
Manipulate IEEE-754 special values
Use defined constants
Perry
![](https://secure.gravatar.com/avatar/5dde29b54a3f1b76b2541d0a4a9b232c.jpg?s=120&d=mm&r=g)
Perry Greenfield wrote:
I don't recall if there was disagreement about this being useful,
probably not
but perhaps there was disagreement that it should always do this.
absolutely, and I think there was a wide range of opinions about how usefull (and or critical!) this is.
Fabulous!!! You folks are wonderfull! I guess it's time to make the switch to numarray...I've been waiting for a compelling reason! -Chris -- Christopher Barker, Ph.D. Oceanographer NOAA/OR&R/HAZMAT (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception Chris.Barker@noaa.gov
participants (3)
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Chris Barker
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eric jones
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Perry Greenfield