NumPy array to Table or Matrix - pyo-discuss

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Message from discussion NumPy array to Table or Matrix
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Date: Sun, 11 Dec 2011 13:50:38 -0500
Message-ID: <CAMXBGhTREpdx0R0rbbz6JGbKf2+09C4Y2dJ0yTNowQn605N...@mail.gmail.com>
Subject: Re: [pyo-discuss] NumPy array to Table or Matrix
From: =?ISO-8859-1?Q?Olivier_B=E9langer?= <belan...@gmail.com>
To: pyo-discuss@googlegroups.com
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Hi Lennart,

There is no direct support for numpy array in pyo (it's in my plan to
implement it). The most straight-forward way to do this by now is to
convert your array to a list and give it to the "init" argument of a
DataTable or a NewMatrix object:

##################################################################################
from pyo import *
import numpy as np
import math

s = Server().boot()

size = 512
arr = np.array([math.sin(2 * math.pi * i / size) for i in range(size)])
t = DataTable(size, init=arr.tolist())
t.view()

size = 256
arr2 = np.array([[math.sin(2 * math.pi * j / size + math.sin(i/16.0)) for j
in range(size)] for i in range(size)])
m = NewMatrix(size, size, arr2.tolist())
m.view()

s.gui(locals())
##################################################################################

Olivier

2011/12/11 Lennart Hilbert <lennart.hilb...@googlemail.com>

> Hi,
>
> I am looking for a way to write the values of a NumPy float array into a
> pyo Table or Matrix object in a single, whole array operation.
>
> I assume I could use a loop over each element of the NumPy array. In each
> loop iteration I can use the put(value,x,y) method to the Matrix object to
> store the values one by one.
>
> But, that seems very inefficient to me. Is there a straight-forward way to
> assign a whole NumPy array to a pyo Matrix or Table in a single, whole
> array operation?
>
> Any comments appreciated. I did not find anything on this topic in the
> documentation and in this discussion group.
>
>
> Many thanks,
>
> Lennart
>

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Hi Lennart,<br><br>There is no direct support for numpy array in pyo (it&#3=
9;s in my plan to implement it). The most straight-forward way to do this b=
y now is to convert your array to a list and give it to the &quot;init&quot=
; argument of a DataTable or a NewMatrix object:<br>
<br>#######################################################################=
###########<br>from pyo import *<br>import numpy as np<br>import math<br><b=
r>s =3D Server().boot()<br><br>size =3D 512<br>arr =3D np.array([math.sin(2=
 * math.pi * i / size) for i in range(size)])<br>
t =3D DataTable(size, init=3Darr.tolist())<br>t.view()<br><br>size =3D 256<=
br>arr2 =3D np.array([[math.sin(2 * math.pi * j / size + math.sin(i/16.0)) =
for j in range(size)] for i in range(size)])<br>m =3D NewMatrix(size, size,=
 arr2.tolist())<br>
m.view()<br><br>s.gui(locals())<br>########################################=
##########################################<br><br>Olivier<br><br><div class=
=3D"gmail_quote">2011/12/11 Lennart Hilbert <span dir=3D"ltr">&lt;<a href=
=3D"mailto:lennart.hilb...@googlemail.com">lennart.hilb...@googlemail.com</=
a>&gt;</span><br>
<blockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1p=
x #ccc solid;padding-left:1ex">Hi,<br><br>I am looking for a way to write t=
he values of a NumPy float array into a pyo Table or Matrix object in a sin=
gle, whole array operation.<br>
<br>I assume I could use a loop over each element of the NumPy array. In ea=
ch loop iteration I can use the put(value,x,y) method to the Matrix object =
to store the values one by one.<br><br>But, that seems very inefficient to =
me. Is there a straight-forward way to assign a whole NumPy array to a pyo =
Matrix or Table in a single, whole array operation?<br>
<br>Any comments appreciated. I did not find anything on this topic in the =
documentation and in this discussion group.<br><pre><br></pre>Many thanks,<=
br><font color=3D"#888888"><br>Lennart<br></font></blockquote></div><br>

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