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<div name="messageBodySection" style="font-size: 14px; font-family: -apple-system, BlinkMacSystemFont, sans-serif;"><font face="Helvetica">There are a couple of interesting observations here. In your first bit, you have:</font>
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<div class="pre" style="margin: 0px; padding: 0px;"><font face="Helvetica">## works with a row vector<br />
vect0 = np.random.rand(5)</font></div>
<div class="pre" style="margin: 0px; padding: 0px;"><font face="Helvetica">mat[:,0]=np.transpose(vect0)<br /></font></div>
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<div><font face="Helvetica">(or I prefer vect0.T). Did you happen to notice that this works too:</font></div>
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<div class="pre" style="margin: 0px; padding: 0px;"><font face="Helvetica">mat[:,0]=vect0</font></div>
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<div><font face="Helvetica">The transpose or the original work as well. Unlike Scilab, python’s arrays can be literally 1-dimensional. Not 5x1 but just 5, which doesn’t have a transpose, because it doesn’t have a 2nd dimension.</font></div>
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<div><font face="Helvetica">you can see that in vect0.shape</font></div>
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<div><font face="Helvetica">so np.random.rand(5) doesn’t make a row-vector but a length 5 array, which is different than </font><span style="font-family: Helvetica;">np.random.rand(5,1) or </span><span style="font-family: Helvetica;">np.random.rand(1,5). Thus, you have to make sure the shapes all work. </span></div>
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<div><font face="Helvetica">in your second example, with the column vector, you can also slice along the 2nd dimension without transposing like:</font></div>
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<div class="pre" style="margin: 0px; padding: 0px; font-family: monospace;">mat[:,0]=vect0[:,0]</div>
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<div><font face="Helvetica">mat[:,0] seems to have shape of (5,) which is just length-5 array, so setting it equal to 1xN or Nx1 arrays seems to cause some issues.</font></div>
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- Brian</div>
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On Jul 3, 2017, 15:57 -0400, paul.carrico@free.fr, wrote:<br />
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<div class="pre" style="margin: 0; padding: 0; font-family: monospace">Dear All</div>
<div class="pre" style="margin: 0; padding: 0; font-family: monospace"> </div>
<div class="pre" style="margin: 0; padding: 0; font-family: monospace">I'm a like matlab user (more specifically a Scilab one) for years, and because I've to deal with huge ascii files (with dozens of millions of lines), I decided to have a look to Python and Numpy, including vectorization topics.</div>
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<div class="pre" style="margin: 0; padding: 0; font-family: monospace">Obviously I've been influenced by my current feedbacks.</div>
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<div class="pre" style="margin: 0; padding: 0; font-family: monospace">I've a basic question concerning the current code: why it is necessary to transpose the column vector (still in the right format in my mind)? does it make sens?</div>
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<div class="pre" style="margin: 0; padding: 0; font-family: monospace">Thanks</div>
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<div class="pre" style="margin: 0; padding: 0; font-family: monospace">Paul</div>
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<div class="pre" style="margin: 0; padding: 0; font-family: monospace">####################################</div>
<div class="pre" style="margin: 0; padding: 0; font-family: monospace">import numpy as np ## np = raccourci<br />
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## works with a row vector<br />
vect0 = np.random.rand(5); print vect0; print("\n")<br />
mat = np.zeros((5,4),dtype=float)<br />
mat[:,0]=np.transpose(vect0); print mat<br />
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## works while the vector is still in column i.e. in a right format, isn't it?<br />
vect0 = np.random.rand(5,1); print vect0; print("\n")<br />
mat = np.zeros((5,4),dtype=float)<br />
mat[:,0]=np.transpose(vect0); print mat<br />
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## does not work<br />
vect0 = np.random.rand(5,1); print vect0; print("\n")<br />
mat = np.zeros((5,4),dtype=float)<br />
mat[:,0]=np(vect0); print mat</div>
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