Re: [Tutor] Pyuthon 3 Combine 1 D Arrays
On 05/17/2017 06:15 PM, Luis JM Amoreira wrote:
Hi,
If your arrays have shape (300,1) (single column, 300 rows right?) then
M = numpy.hstack((array1, array2)) is an array with shape (300, 2) (300
rows, 2 columns) and M.T is 2 by 300 [shape (2, 300)]. Take an example:
In [11]: import numpy as np
In [12]: a1=np.random.rand(3,1)
In [13]: a1
Out[13]:
array([[ 0.09042866],
[ 0.63008665],
[ 0.99106757]])
In [14]: a2=np.random.rand(3,1)
In [15]: np.hstack((a1,a2))
Out[15]:
array([[ 0.09042866, 0.99965848],
[ 0.63008665, 0.12334957],
[ 0.99106757, 0.43502637]])
In [16]: np.hstack((a1,a2)).T
Out[16]:
array([[ 0.09042866, 0.63008665, 0.99106757],
[ 0.99965848, 0.12334957, 0.43502637]])
Hope this helps!
ze
On 05/17/2017 08:50 PM, Stephen P. Molnar wrote:
I'm beginning to think that I don't know how to ask the question as
Google and Stack Overflow have resulted in nothing. All of the
results seem to deal with integers.
I have a number of single column floating point arrays each containing
300 entries that I want to combine into a n by 300 array where n is
the number of single column arrays.
I have tried zip, np.concatenate etc with only failure.
Thanks in advance.
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Thanks for your reply.
Here's what I get:
Traceback (most recent call last):
File "", line 1, in
runfile('/home/comp/Apps/Python/Molecular_Transforms/Basic/MolT_app_1.py',
wdir='/home/comp/Apps/Python/Molecular_Transforms/Basic')
File
"/home/comp/Apps/anaconda3/lib/python3.6/site-packages/spyder/utils/site/sitecustomize.py",
line 880, in runfile
execfile(filename, namespace)
File
"/home/comp/Apps/anaconda3/lib/python3.6/site-packages/spyder/utils/site/sitecustomize.py",
line 102, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File
"/home/comp/Apps/Python/Molecular_Transforms/Basic/MolT_app_1.py", line
289, in
f.write("\n".join("".join(map(str, x)) for x in (name_I_app)))
File
"/home/comp/Apps/Python/Molecular_Transforms/Basic/MolT_app_1.py", line
289, in
f.write("\n".join("".join(map(str, x)) for x in (name_I_app)))
TypeError: 'numpy.float64' object is not iterable
However, numpy.column_stack works.
Problem solved.
--
Stephen P. Molnar, Ph.D.Life is a fuzzy set
www.molecular-modeling.net Stochastic and multivariate
(614)312-7528 (c)
Skype: smolnar1
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Re: [Tutor] Pyuthon 3 Combine 1 D Arrays
On 17/05/17 20:50, Stephen P. Molnar wrote: > I'm beginning to think that I don't know how to ask the question as > Google and Stack Overflow have resulted in nothing. All of the results > seem to deal with integers. Have you tried asking on the scipy forum? https://www.scipy.org/scipylib/mailing-lists.html -- Alan G Author of the Learn to Program web site http://www.alan-g.me.uk/ http://www.amazon.com/author/alan_gauld Follow my photo-blog on Flickr at: http://www.flickr.com/photos/alangauldphotos ___ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
[Tutor] Pyuthon 3 Combine 1 D Arrays
I'm beginning to think that I don't know how to ask the question as Google and Stack Overflow have resulted in nothing. All of the results seem to deal with integers. I have a number of single column floating point arrays each containing 300 entries that I want to combine into a n by 300 array where n is the number of single column arrays. I have tried zip, np.concatenate etc with only failure. Thanks in advance. -- Stephen P. Molnar, Ph.D.Life is a fuzzy set www.molecular-modeling.net Stochastic and multivariate (614)312-7528 (c) Skype: smolnar1 1.00e+00 1.100334448160535050e+00 1.200668896321070322e+00 1.301003344481605373e+00 1.401337792642140423e+00 1.501672240802675695e+00 1.602006688963210745e+00 1.702341137123745796e+00 1.802675585284280846e+00 1.903010033444816118e+00 2.003344481605351390e+00 2.103678929765885997e+00 2.204013377926421491e+00 2.304347826086956541e+00 2.404682274247491591e+00 2.505016722408027086e+00 2.605351170568561692e+00 2.705685618729097186e+00 2.806020066889632236e+00 2.906354515050167286e+00 3.006688963210702337e+00 3.107023411371237387e+00 3.207357859531772437e+00 3.307692307692307931e+00 3.408026755852842982e+00 3.508361204013378032e+00 3.608695652173913082e+00 3.709030100334448132e+00 3.809364548494983183e+00 3.909698996655518677e+00 4.010033444816054171e+00 4.110367892976588777e+00 4.210702341137123383e+00 4.311036789297658878e+00 4.411371237458194372e+00 4.511705685618728978e+00 4.612040133779264472e+00 4.712374581939799967e+00 4.812709030100334573e+00 4.913043478260869179e+00 5.013377926421404673e+00 5.113712374581940168e+00 5.214046822742474774e+00 5.314381270903010268e+00 5.414715719063544874e+00 5.515050167224080369e+00 5.615384615384615863e+00 5.715719063545150469e+00 5.816053511705685963e+00 5.916387959866220569e+00 6.016722408026756064e+00 6.117056856187290670e+00 6.217391304347826164e+00 6.317725752508361658e+00 6.418060200668896265e+00 6.518394648829431759e+00 6.618729096989966365e+00 6.719063545150501859e+00 6.819397993311037354e+00 6.919732441471571960e+00 7.020066889632107454e+00 7.120401337792642060e+00 7.220735785953177555e+00 7.321070234113712161e+00 7.421404682274247655e+00 7.521739130434783149e+00 7.622073578595317755e+00 7.722408026755853250e+00 7.822742474916387856e+00 7.923076923076923350e+00 8.023411371237457956e+00 8.123745819397992562e+00 8.224080267558528945e+00 8.324414715719063551e+00 8.424749163879599934e+00 8.525083612040134540e+00 8.625418060200669146e+00 8.725752508361203752e+00 8.826086956521738358e+00 8.926421404682274741e+00 9.026755852842809347e+00 9.127090301003343953e+00 9.227424749163880335e+00 9.327759197324414941e+00 9.428093645484949548e+00 9.528428093645485930e+00 9.628762541806020536e+00 9.729096989966555142e+00 9.829431438127089748e+00 9.929765886287626131e+00 1.003010033444816074e+01 1.013043478260869534e+01 1.023076923076923173e+01 1.033110367892976633e+01 1.043143812709030094e+01 1.053177257525083554e+01 1.063210702341137193e+01 1.073244147157190653e+01 1.083277591973244114e+01 1.093311036789297752e+01 1.103344481605351213e+01 1.113377926421404673e+01 1.123411371237458134e+01 1.133444816053511772e+01 1.143478260869565233e+01 1.153511705685618693e+01 1.163545150501672332e+01 1.173578595317725792e+01 1.183612040133779253e+01 1.193645484949832891e+01 1.203678929765886352e+01 1.213712374581939812e+01 1.223745819397993273e+01 1.233779264214046911e+01 1.243812709030100372e+01 1.253846153846153832e+01 1.263879598662207471e+01 1.273913043478260931e+01 1.283946488294314392e+01 1.293979933110367853e+01 1.304013377926421491e+01 1.314046822742474951e+01 1.324080267558528412e+01 1.334113712374582050e+01 1.344147157190635511e+01 1.354180602006688972e+01 1.364214046822742432e+01 1.374247491638796070e+01 1.384280936454849531e+01 1.394314381270902992e+01 1.404347826086956630e+01 1.414381270903010090e+01 1.424414715719063551e+01 1.434448160535117012e+01 1.81605351170650e+01 1.454515050167224111e+01 1.464548494983277571e+01 1.474581939799331209e+01 1.484615384615384670e+01 1.494648829431438131e+01 1.504682274247491591e+01 1.514715719063545230e+01 1.524749163879598690e+01 1.534782608695652151e+01 1.544816053511705789e+01 1.554849498327759250e+01 1.564882943143812710e+01 1.574916387959866171e+01 1.584949832775919809e+01 1.594983277591973270e+01 1.605016722408026908e+01 1.615050167224080369e+01 1.625083612040133829e+01 1.635117056856187290e+01 1.645150501672240750e+01 1.655183946488294566e+01 1.665217391304347672e+01 1.675250836120401488e+01 1.685284280936454948e+01 1.695317725752508409e+01 1.705351170568561869e+01 1.715384615384615330e+01 1.725418060200668791e+01 1.735451505016722606e+01 1.745484949832776067e+01 1.755518394648829528e+01 1.765551839464882988e+01 1.775585284280936449e+01 1.785618729096989910e+01 1.795652173913043370e+01 1.805685618729097186e+01 1.815719063545150647e+01 1.825752508361204107e+01 1.835785953177257568e+01 1.845819397993311028e+01 1.855852842809364489e+01
