note
sgt
<blockquote> As quick googling shows, default data type for numpy is 32-bit "single precision" "float"
</blockquote>
<p> Are you really sure? I was surprised by your claim that numpy use a default C float. I am a longtime Perl
and C hacker and no python expert. But I view the C float type as kind of archaic I use many math libs and
the trend is to go past the C double. It would be surprising for a modern lib like numpy to use such
a default. Also float() in python means floating point not C float.</p>
<p> Note that I do not really care if tool X is faster that tool Y when the sun, jupiter and the moon are aligned. But I did a bit of web search and could not _quickly_ come up with a definite answer! so I
decided to check. Seems that numpy default is a C double: </p>
<pre><code>
% steph@kerangi (/tmp/cpanm_t.d) %
% python3.8 -c 'import math as m; print(m.sin(float(1)))'
0.8414709848078965
% steph@kerangi (/tmp/cpanm_t.d) %
% python3.7
Python 3.7.7 (default, Apr 10 2020, 07:59:19)
[GCC 9.3.0] on cygwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy as np
>>> np.float
<class 'float'>
>>> np.float64
<class 'numpy.float64'>
>>> np.float32
<class 'numpy.float32'>
>>> print(np.sin(float(1)))
0.8414709848078965
>>> print(np.sin(np.float64(1)))
0.8414709848078965
>>> print(np.sin(np.float32(1)))
0.84147096
>>>
</code></pre>
<p> I think that PDL is really a fantastic piece of software and that it is pretty fast.
One possible pitfall, common to all C extensions to Perl,
is to go back and forth too many times between Perl and C as that can make a computation much slower.
It is often possible to avoid it.
</p>
hth cheers
--sgt
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