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refined numpy syntax

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rasbt 2014-06-16 23:00:23 -04:00
parent a76fa9a01b
commit 6cb30cfb38
2 changed files with 26 additions and 12 deletions
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1
tutorials/.~lock.matrix_cheatsheet_only.html# Normal file
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,sebastian,Macintosh.local,16.06.2014 22:50,file:///Users/sebastian/Library/Application%20Support/LibreOffice/4;

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tutorials/matrix_cheatsheet_only.html
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<title></title>
<meta name="generator" content="LibreOffice 4.2.4.2 (MacOSX)">
<meta name="created" content="0;0">
<meta name="changed" content="20140605;223752655486000">
<meta name="changed" content="20140616;225009144635000">
<style type="text/css">
<!--
td p { color: #000000; font-family: "Verdana"; font-size: 12pt }
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<col width="511">
<col width="690">
<tr>
<td height="57" bgcolor="#0066cc" style="border: none; padding: 0in">
<td height="58" bgcolor="#0066cc" style="border: none; padding: 0in">
<p align="center"><font color="#ffffff"><font face="Arial"><font size="5" style="font-size: 18pt"><b>Task</b></font></font></font></p>
</td>
<td bgcolor="#0066cc" style="border: none; padding: 0in">
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3</font></font></p>
</td>
<td bgcolor="#cfe7f5" style="border-top: none; border-bottom: none; border-left: 1px dotted #000000; border-right: 1px dotted #000000; padding: 0in 0.02in">
<p align="left"><font face="Andale Mono"><font size="1" style="font-size: 8pt"><font color="#ff420e"><font size="2" style="font-size: 10pt"><b>P&gt;</b></font></font>
a = np.array([[1],[2],[3]])<br><br><font color="#ff420e"><font size="2" style="font-size: 10pt"><b>P&gt;</b></font></font>
a<br>array([[1],<br>&nbsp;&nbsp; &nbsp; &nbsp; [2],<br>&nbsp;&nbsp;
&nbsp; &nbsp; [3]])</font></font></p>
<p align="left"><font color="#ff420e"><font face="Andale Mono"><font size="2" style="font-size: 10pt"><b>P&gt;</b></font></font></font><font face="Andale Mono"><font size="1" style="font-size: 8pt">
</font></font><font face="Andale Mono"><font size="1" style="font-size: 8pt">a</font></font><font color="#2fff12"><font face="AndaleMono, serif"><font size="4" style="font-size: 14pt">
</font></font></font><font color="#000000"><font face="Andale Mono"><font size="1" style="font-size: 8pt">=
np.array([1,2,3]).reshape(1,3)</font></font></font></p>
<p align="left"><font face="Andale Mono"><font size="1" style="font-size: 8pt"><br></font></font><font color="#ff420e"><font face="Andale Mono"><font size="2" style="font-size: 10pt"><b>P&gt;</b></font></font></font><font face="Andale Mono"><font size="1" style="font-size: 8pt">
</font></font><font color="#000000"><font face="Andale Mono"><font size="1" style="font-size: 8pt">b.shape<br>(1,
3)</font></font></font></p>
<p align="left"><br>
</p>
</td>
<td bgcolor="#cfe7f5" style="border-top: none; border-bottom: none; border-left: 1px dotted #000000; border-right: 1px dotted #000000; padding: 0in 0.02in">
<p align="left"><font face="Andale Mono"><font size="1" style="font-size: 8pt"><font color="#0000ff"><font size="2" style="font-size: 10pt"><b>R&gt;</b></font></font>
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<p align="left"><font face="Andale Mono"><font size="1" style="font-size: 8pt"><font color="#ff420e"><font size="2" style="font-size: 10pt"><b>P&gt;</b></font></font>
b = np.array([1,2,3])<br><br><font color="#ff420e"><font size="2" style="font-size: 10pt"><b>P&gt;</b></font></font>
b<br>array([1, 2, 3])</font></font></p>
<p align="left"><font face="Andale Mono"><font size="1" style="font-size: 8pt">#
note that numpy doesn't have <br># explicit “row-vectors”, but
1-D <br># arrays</font></font></p>
<p style="margin-bottom: 0in"><font face="Liberation Serif, serif"><font size="3" style="font-size: 12pt"><font color="#ff420e"><font face="Andale Mono"><font size="2" style="font-size: 10pt"><b>P&gt;</b></font></font></font><font color="#2fff12"><font face="AndaleMono, serif"><font size="1" style="font-size: 8pt"><b>
</b></font></font></font><font color="#000000"><font face="Andale Mono"><font size="1" style="font-size: 8pt">b.shape</font></font></font></font></font></p>
<p style="margin-bottom: 0in"><font face="Andale Mono"><font size="1" style="font-size: 8pt">(3,)</font></font></p>
<p align="left"><font face="Andale Mono"><font size="1" style="font-size: 8pt"><br></font></font><br>
</p>
</td>
<td bgcolor="#ffffff" style="border-top: none; border-bottom: none; border-left: 1px dotted #000000; border-right: 1px dotted #000000; padding: 0in 0.02in">
<p align="left"><font face="Andale Mono"><font size="1" style="font-size: 8pt"><font color="#0000ff"><font size="2" style="font-size: 10pt"><b>R&gt;</b></font></font>
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</td>
<td bgcolor="#cfe7f5" style="border-top: none; border-bottom: none; border-left: 1px dotted #000000; border-right: 1px dotted #000000; padding: 0in 0.02in">
<p align="left"><font face="Andale Mono"><font size="1" style="font-size: 8pt"><font color="#ff420e"><font size="2" style="font-size: 10pt"><b>P&gt;</b></font></font>
np.ones([3,2])<br>array([[ 1.,&nbsp; 1.],<br>&nbsp;&nbsp; &nbsp; &nbsp;
np.ones((3,2))<br>array([[ 1.,&nbsp; 1.],<br>&nbsp;&nbsp; &nbsp; &nbsp;
[ 1.,&nbsp; 1.],<br>&nbsp;&nbsp; &nbsp; &nbsp; [ 1.,&nbsp; 1.]])</font></font></p>
</td>
<td bgcolor="#cfe7f5" style="border-top: none; border-bottom: none; border-left: 1px dotted #000000; border-right: 1px dotted #000000; padding: 0in 0.02in">
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A = np.array([[1,2,3],[4,5,6],[7,8,9]])<br><br><font color="#ff420e"><font size="2" style="font-size: 10pt"><b>P&gt;</b></font></font>
A<br>array([[1, 2, 3],<br>&nbsp;&nbsp; &nbsp; &nbsp; [4, 5, 9],<br>&nbsp;&nbsp;
&nbsp; &nbsp; [7, 8, 9]])<br><br><font color="#ff420e"><font size="2" style="font-size: 10pt"><b>P&gt;</b></font></font>
total_elements = A.shape[0] * A.shape[1]<br><br><font color="#ff420e"><font size="2" style="font-size: 10pt"><b>P&gt;</b></font></font>
B = A.reshape(1, total_elements)&nbsp;<br><br># or
A.reshape(1,9)<br># Alternative: A.shape = (1,9)&nbsp;<br>#
to&nbsp;change the array in place<br><br><font color="#ff420e"><font size="2" style="font-size: 10pt"><b>P&gt;</b></font></font>
total_elements = np.prod(A.shape)</font></font></p>
<p align="left"><font face="Andale Mono"><font size="1" style="font-size: 8pt"><font color="#ff420e"><font size="2" style="font-size: 10pt"><b>P&gt;</b></font></font>
B = A.reshape(1, total_elements)&nbsp;<br><br># alternative
shortcut:<br># A.reshape(1,-1)<br><br><font color="#ff420e"><font size="2" style="font-size: 10pt"><b>P&gt;</b></font></font>
B<br>array([[1, 2, 3, 4, 5, 6, 7, 8, 9]])</font></font></p>
</td>
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</td>
</tr>
<tr valign="top">
<td height="539" bgcolor="#ffffff" style="border-top: none; border-bottom: none; border-left: none; border-right: 1px solid #000000; padding-top: 0in; padding-bottom: 0in; padding-left: 0in; padding-right: 0.02in">
<td height="540" bgcolor="#ffffff" style="border-top: none; border-bottom: none; border-left: none; border-right: 1px solid #000000; padding-top: 0in; padding-bottom: 0in; padding-left: 0in; padding-right: 0.02in">
<p align="left"><font face="Arial"><font size="2" style="font-size: 10pt"><b>Generating
a Gaussian dataset:<br><br>creating random vectors from the
multivariate normal<br>distribution given mean and covariance