Hi all,
Myself and several colleagues have recently started work on a Python library
for solar physics http://www.sunpy.org/, in order to provide an
alternative to the current mainstay for solar
physicshttp://www.lmsal.com/solarsoft/,
which is written in IDL.
One of the first steps we have taken
hi Keith,
I do not think that your primary concern should be with this kind of
speed test at this stage :
1/ rest assured that this sort of tests have been performed in other
contexts, and you can always do some hard work on high level computing
languages like IDL and python to improve
On Mon, Sep 26, 2011 at 3:19 PM, Keith Hughitt keith.hugh...@gmail.com wrote:
Hi all,
Myself and several colleagues have recently started work on a Python library
for solar physics, in order to provide an alternative to the current
mainstay for solar physics, which is written in IDL.
One of
On Mon, Sep 26, 2011 at 8:19 AM, Keith Hughitt keith.hugh...@gmail.comwrote:
Hi all,
Myself and several colleagues have recently started work on a Python
library for solar physics http://www.sunpy.org/, in order to provide an
alternative to the current mainstay for solar
Hello Keith,
While I also echo Johann's points about the arbitrariness and non-utility of
benchmarking I'll briefly comment just on just a few tests to help out with
getting things into idiomatic python/numpy:
Tests 1 and 2 are fairly pointless (empty for loop and empty procedure) that
won't
On Mon, Sep 26, 2011 at 8:24 AM, Zachary Pincus zachary.pin...@yale.edu wrote:
Test 3:
#Test 3 - Add 20 scalar ints
nrep = 200 * scale_factor
for i in range(nrep):
a = i + 1
well, python looping is slow... one doesn't do such loops in idiomatic code
if the
Using Source Forge download of NumPy installer package:
numpy-1.6.1-win32-superpack-python 2.7.exe.
Installation Wizard starts, but then installation fails with error message:
Python version 2.7 required, which was not found in the registry
Idle says it's using:
Python 2.7.2 64 bit AMD64
One minor thing is you should use xrange rather than range. Although it will
probably only make a difference for the empty loop ;)
Otherwise, from what I can see, tests where numpy is really much worse are:
- 1, 2, 3, 15, 18: Not numpy but Python related: for loops are not efficient
- 6, 10:
On Mon, Sep 26, 2011 at 9:43 AM, The Helmbolds hel...@yahoo.com wrote:
Using Source Forge download of NumPy installer package:
numpy-1.6.1-win32-superpack-python 2.7.exe.
Installation Wizard starts, but then installation fails with error message:
Python version 2.7 required, which was
You are probably trying to install the 32 bit version of numpy on your 64
bit Python. Either switch to 64 bit numpy or 32 bit Python.
-=- Olivier
2011/9/26 The Helmbolds hel...@yahoo.com
Using Source Forge download of NumPy installer package:
numpy-1.6.1-win32-superpack-python 2.7.exe.
Python. If you need free 64 bit numpy on windows your best bet is probably
here http://www.lfd.uci.edu/%7Egohlke/pythonlibs/.
Chuck
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hi all,
now free solver interalg from OpenOpt framework (based on interval
analysis) can solve ODE dy/dt = f(t) with guaranteed specifiable
accuracy.
See the ODE webpage for more details, there is an example of
comparison with scipy.integrate.odeint, where latter fails to solve
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