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• Multiplying Block Matrices in Numpy

  - by Ada Xu

  Hi Everyone I am python newbie I have to implement lasso L1 regression for a class assignment. This involves solving a quadratic equation involving block matrices. minimize x^t * H * x + f^t * x where x 0 Where H is a 2 X 2 block matrix with each element being a k dimensional matrix and x and f being a 2 X 1 vectors each element being a k dimension vector. I was thinking of using nd arrays. such that np.shape(H) = (2, 2, k, k) np.shape(x) = (2, k) But I figured out that np.dot(X, H) doesn't work here. Is there an easy way to solve this problem? Thanks in advance.

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• slicing arrays in numpy/scipy

  - by user248237

  I have an array like: a = array([[1,2,3],[3,4,5],[4,5,6]]) what's the most efficient way to slice out a 1x2 array out of this that has only the first two columns of "a"? I.e., array([[2,3],[4,5],[5,6]]) in this case. thanks.

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• Removing duplicates (within a given tolerance) from a Numpy array of vectors

  - by Brendan

  I have an Nx5 array containing N vectors of form 'id', 'x', 'y', 'z' and 'energy'. I need to remove duplicate points (i.e. where x, y, z all match) within a tolerance of say 0.1. Ideally I could create a function where I pass in the array, columns that need to match and a tolerance on the match. Following this thread on Scipy-user, I can remove duplicates based on a full array using record arrays, but I need to just match part of an array. Moreover this will not match within a certain tolerance. I could laboriously iterate through with a for loop in Python but is there a better Numponic way?

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• numpy array mapping and take average

  - by user566653

  Dear all, I have three array value = np.array ([1, 3, 3, 5, 5, 7, 3]) index = np.array ([1, 1, 3, 3, 6, 6, 6]) data = np.array ([1, 2, 3, 4, 5, 6]) and want to take average for item of "value" by array "index", and assign a new array with value of "data", such as [2, nan, 4, nan, nan, 5] first value is the average of 1st and 2nd of "value" second value is nan because there is not any key in "index" third value is the average of 3rd and 4th of "value" ... Thanks for your help!!! Regards, Roy

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• Numpy/Python performing terribly vs. Matlab

  - by Nissl

  Novice programmer here. I'm writing a program that analyzes the relative spatial locations of points (cells). The program gets boundaries and cell type off an array with the x coordinate in column 1, y coordinate in column 2, and cell type in column 3. It then checks each cell for cell type and appropriate distance from the bounds. If it passes, it then calculates its distance from each other cell in the array and if the distance is within a specified analysis range it adds it to an output array at that distance. My cell marking program is in wxpython so I was hoping to develop this program in python as well and eventually stick it into the GUI. Unfortunately right now python takes ~20 seconds to run the core loop on my machine while MATLAB can do ~15 loops/second. Since I'm planning on doing 1000 loops (with a randomized comparison condition) on ~30 cases times several exploratory analysis types this is not a trivial difference. I tried running a profiler and array calls are 1/4 of the time, almost all of the rest is unspecified loop time. Here is the python code for the main loop: for basecell in range (0, cellnumber-1): if firstcelltype == np.array((cellrecord[basecell,2])): xloc=np.array((cellrecord[basecell,0])) yloc=np.array((cellrecord[basecell,1])) xedgedist=(xbound-xloc) yedgedist=(ybound-yloc) if xloc>excludedist and xedgedist>excludedist and yloc>excludedist and yedgedist>excludedist: for comparecell in range (0, cellnumber-1): if secondcelltype==np.array((cellrecord[comparecell,2])): xcomploc=np.array((cellrecord[comparecell,0])) ycomploc=np.array((cellrecord[comparecell,1])) dist=math.sqrt((xcomploc-xloc)**2+(ycomploc-yloc)**2) dist=round(dist) if dist>=1 and dist<=analysisdist: arraytarget=round(dist*analysisdist/intervalnumber) addone=np.array((spatialraw[arraytarget-1])) addone=addone+1 targetcell=arraytarget-1 np.put(spatialraw,[targetcell,targetcell],addone) Here is the matlab code for the main loop: for basecell = 1:cellnumber; if firstcelltype==cellrecord(basecell,3); xloc=cellrecord(basecell,1); yloc=cellrecord(basecell,2); xedgedist=(xbound-xloc); yedgedist=(ybound-yloc); if (xloc>excludedist) && (yloc>excludedist) && (xedgedist>excludedist) && (yedgedist>excludedist); for comparecell = 1:cellnumber; if secondcelltype==cellrecord(comparecell,3); xcomploc=cellrecord(comparecell,1); ycomploc=cellrecord(comparecell,2); dist=sqrt((xcomploc-xloc)^2+(ycomploc-yloc)^2); if (dist>=1) && (dist<=100.4999); arraytarget=round(dist*analysisdist/intervalnumber); spatialsum(1,arraytarget)=spatialsum(1,arraytarget)+1; end end end end end end Thanks!

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• .Net Array or IList<T> from NumPy array in IronPython?

  - by Barry Wark

  Imagine I have a .Net application that supports user extensions in the form of Python modules by embedding IronPython. Using Ironclad, I can allow users to make use of the NumPy and SciPy packages from within their modules. How good is the interop provided by Ironclad? My question is: can I use a NumPy array of type T provided by the user's module in the rest of my app that requires an IList<T>? Edit To clarify, IronPython exposes any Python enumerable of objects of type T as an IEnumerable<T> or an IList<T>. I'm not sure if NumPy arrays fit in this category. I would rather not have to call .tolist() on the NumPy array as the arrays may be quite large.

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• install python2.7.3 + numpy + scipy + matplotlib + scikits.statsmodels + pandas0.7.3 correctly

  - by boldnik

  ...using Linux (xubuntu). How to install python2.7.3 + numpy + scipy + matplotlib + scikits.statsmodels + pandas0.7.3 correctly ? My final aim is to have them working. The problem: ~$ python --version Python 2.7.3 so i already have a system-default 2.7.3, which is good! ~$ dpkg -s python-numpy Package: python-numpy Status: install ok installed and i already have numpy installed! great! But... ~$ python Python 2.7.3 (default, Oct 23 2012, 01:07:38) [GCC 4.6.1] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import numpy as nmp Traceback (most recent call last): File "<stdin>", line 1, in <module> ImportError: No module named numpy this module couldn't be find by python. The same with scipy, matplotlib. Why? ~$ sudo apt-get install python-numpy [...] Reading package lists... Done Building dependency tree Reading state information... Done python-numpy is already the newest version. [...] why it does not see numpy and others ? update: >>> import sys >>> print sys.path ['', '/usr/local/lib/python27.zip', '/usr/local/lib/python2.7', '/usr/local/lib/python2.7/plat-linux2', '/usr/local/lib/python2.7/lib-tk', '/usr/local/lib/python2.7/lib-old', '/usr/local/lib/python2.7/lib-dynload', '/usr/local/lib/python2.7/site-packages'] >>> so i do have /usr/local/lib/python2.7 ~$ pip freeze Warning: cannot find svn location for distribute==0.6.16dev-r0 BzrTools==2.4.0 CDApplet==1.0 [...] matplotlib==1.0.1 mutagen==1.19 numpy==1.5.1 [...] pandas==0.7.3 papyon==0.5.5 [...] pytz==2012g pyxdg==0.19 reportlab==2.5 scikits.statsmodels==0.3.1 scipy==0.11.0 [...] zope.interface==3.6.1 as you can see, those modules are already installed! But! ls -la /usr/local/lib/ gives ONLY python2.7 dir. And still ~$ python -V Python 2.7.3 and import sys sys.version '2.7.3 (default, Oct 23 2012, 01:07:38) \n[GCC 4.6.1]' updated: Probably I've missed another instance... One at /usr/Python-2.7.3/ and second (seems to be installed "by hands" far far ago) at /usr/python2.7.3/Python-2.7.3/ But how two identical versions can work at the same time??? Probably, one of them is "disabled" (not used by any program, but I don't know how to check if any program uses it). ~$ ls -la /usr/bin/python* lrwxrwxrwx 1 root root 9 2011-11-01 11:11 /usr/bin/python -> python2.7 -rwxr-xr-x 1 root root 2476800 2012-09-28 19:48 /usr/bin/python2.6 -rwxr-xr-x 1 root root 1452 2012-09-28 19:45 /usr/bin/python2.6-config -rwxr-xr-x 1 root root 2586060 2012-07-21 01:42 /usr/bin/python2.7 -rwxr-xr-x 1 root root 1652 2012-07-21 01:40 /usr/bin/python2.7-config lrwxrwxrwx 1 root root 9 2011-10-05 23:53 /usr/bin/python3 -> python3.2 lrwxrwxrwx 1 root root 11 2011-09-06 02:04 /usr/bin/python3.2 -> python3.2mu -rwxr-xr-x 1 root root 2852896 2011-09-06 02:04 /usr/bin/python3.2mu lrwxrwxrwx 1 root root 16 2011-10-08 19:50 /usr/bin/python-config -> python2.7-config there is a symlink python-python2.7, maybe I can ln -f -s this link to exact /usr/Python-2.7.3/python destination without harm ?? And how correctly to remove the 'copy' of 2.7.3?

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• How do I install the latest version of packages in Ubuntu?

  - by Roman

  For example I want to install the latest version of "numpy". I type the following: "sudo apt-get install python-numpy". When I type this the first time it installs something and if I type this the second time it writes that I have already the latest version of numpy. However, I see that my version of numpy is 1.1.1. and I know that it NOT the latest version. Why it happens and how this problem can be solved? I can find the *tar.gz file with the latest version, I can extract files with the archive and than I need to rune one of the scripts which will be somewhere among the extracted files. But I do not like this way. It is too complicated. I do not know where I should put all these files, I do not know which dependencies I should install before I run the script for the installation of numpy, I do not know where numpy will be put after installation and so on. Is there an easy way to get the latest version of numpy?

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• Installing Numpy locally

  - by Néstor

  I posted this question originally on StackOverflow, but a user suggested I moved it here so here I go! I have an account in a remote computer without root permissions and I needed to install a local version of Python (the remote computer has a version of Python that is incompatible with some codes I have), Numpy and Scipy there. I've been trying to install numpy locally since yesterday, with no success. I successfully installed a local version of Python (2.7.3) in /home/myusername/.local/, so I access to this version of Python by doing /home/myusername/.local/bin/python. I tried two ways of installing Numpy: I downloaded the lastest stable version of Numpy from the official webpage, unpacked it, got into the unpacked folder and did: /home/myusername/.local/bin/python setup.py install --prefix=/home/myusername/.local. However, I get the following error, which is followed by a series of other errors (deriving from this one): gcc -pthread -shared build/temp.linux-x86_64-2.7/numpy/core/blasdot/_dotblas.o -L/usr/local/lib -Lbuild/temp.linux-x86_64-2.7 -lptf77blas -lptcblas -latlas -o build/lib.linux-x86_64-2.7/numpy/core/_dotblas.so /usr/bin/ld: /usr/local/lib/libptcblas.a(cblas_dptgemm.o): relocation R_X86_64_32 against `a local symbol' can not be used when making a shared object; recompile with -fPIC Not really knowing what this meant (except that the error apparently has to do with the LAPACK library), I just did the same command as above, but now putting LDFLAGS='-fPIC', as suggested by the error i.e., I did LDFLAGS="-fPIC" /home/myusername/.local/bin/python setup.py install --prefix=/home/myusername/.local. However, I got the same error (except that the prefix -fPIC was addeded after the gcc command above). I tried installing it using pip, i.e., doing /home/myusername/.local/bin/pip install numpy /after successfully instaling pip in my local path). However, I get the exact same error. I searched on the web, but none of the errors seemed to be similar to mine. My first guess is that this has to do with some piece of code that needs root permissions to be executed, or maybe with some problem with the version of the LAPACK libraries or with gcc (gcc version 4.1.2 is installed on the remote computer). Help, anyone?

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• How to ship numpy with web2py application under myapp/modules?

  - by Newbie07

  I am having the following error while importing numpy from application/myapp/modules: Traceback (most recent call last): File "/home/mdipierro/make_web2py/web2py/gluon/restricted.py", line 212, in restricted File "D:/web2py_win/web2py/applications/myapp/controllers/default.py", line 13, in File "/home/mdipierro/make_web2py/web2py/gluon/custom_import.py", line 100, in custom_importer File "applications\myapp\modules\numpy\ __init__.py", line 137, in File "/home/mdipierro/make_web2py/web2py/gluon/custom_import.py", line 81, in custom_importer ImportError: Cannot import module 'add_newdocs' I tried adding 'application.myapp.modules.' in the 'import add_newdocs' statement of numpy\ __init.py__ and the error propagates to other subsequent imports(i.e. add_docs imports some other stuff and I get the ImportError again for these imports). So I narrowed down the problem to the "working directory" of the import statement. However, I do not wish to add 'application.myapp.modules.' in every import statement inside the package since it would be impractical and hard to edit if someone decides to rename the app later on. How do I make the import work smoothly? NOTE: It is necessary for me to put the numpy package in the app to ensure ease of deployment.

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• How to use numpy with OpenBLAS instead of Atlas in Ubuntu?

  - by pierotiste

  I have looked for an easy way to install/compile Numpy with OpenBLAS but didn't find an easy answer. All the documentation I have seen takes too much knowledge as granted for someone like me who is not used to compile software. There are two packages in Ubuntu related to OpenBLAS : libopenblas-base and libopenblas-dev. Once they are installed, what should I do to install Numpy again with them? Thanks! Note that when these OpenBLAS packages are installed, Numpy doesn't work anymore: it can't be imported: ImportError: /usr/lib/liblapack.so.3gf: undefined symbol: ATL_chemv. This was noticed here already. Answer to the question: Run sudo update-alternatives --all and set liblapack.so.3gf to /usr/lib/lapack/liblapack.so.3gf

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• How to save and load an array of complex numbers using numpy.savetxt?

  - by ptomato

  I want to use numpy.savetxt() to save an array of complex numbers to a text file. Problems: If you save the complex array with the default format string, the imaginary part is discarded. If you use fmt='%s', then numpy.loadtxt() can't load it unless you specify dtype=complex, converters={0: lambda s: complex(s)}. Even then, if there are NaN's in the array, loading still fails. It looks like someone has inquired about this multiple times on the Numpy mailing list and even filed a bug, but has not gotten a response. Before I put something together myself, is there a canonical way to do this?

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• Changing floating point behavior in Python to Numpy style.

  - by Tristan

  Is there a way to make Python floating point numbers follow numpy's rules regarding +/- Inf and NaN? For instance, making 1.0/0.0 = Inf. >>> from numpy import * >>> ones(1)/0 array([ Inf]) >>> 1.0/0.0 Traceback (most recent call last): File "<stdin>", line 1, in <module> ZeroDivisionError: float division Numpy's divide function divide(1.0,0.0)=Inf however it is not clear if it can be used similar to from __future__ import division.

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• How detect length of a numpy array with only one element?

  - by mishaF

  I am reading in a file using numpy.genfromtxt which brings in columns of both strings and numeric values. One thing I need to do is detect the length of the input. This is all fine provided there are more than one value read into each array. But...if there is only one element in the resulting array, the logic fails. I can recreate an example here: import numpy as np a = np.array(2.3) len(a) returns an error saying: TypeError: len() of unsized object however, If a has 2 or more elements, len() behaves as one would expect. import numpy as np a = np.array([2.3,3.6]) len(a) returns 2 My concern here is, if I use some strange exception handling, I can't distinguish between a being empty and a having length = 1.

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• Python — How can I find the square matrix of a lower triangular numpy matrix? (with a symmetrical upper triangle)

  - by Dana Gray

  I generated a lower triangular matrix, and I want to complete the matrix using the values in the lower triangular matrix to form a square matrix, symmetrical around the diagonal zeros. lower_triangle = numpy.array([ [0,0,0,0], [1,0,0,0], [2,3,0,0], [4,5,6,0]]) I want to generate the following complete matrix, maintaining the zero diagonal: complete_matrix = numpy.array([ [0, 1, 2, 4], [1, 0, 3, 5], [2, 3, 0, 6], [4, 5, 6, 0]]) Thanks.

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• speed of map() vs. list comprehension vs. numpy vectorized function in python

  - by mcstrother

  I have a function foo(i) that takes an integer and takes a significant amount of time to execute. Will there be a significant performance difference between any of the following ways of initializing 'a': a = [foo(i) for i in xrange(100)] , a = map(foo, range(100)) , and vfoo = numpy.vectorize(foo) vfoo(range(100)) ? (I don't care whether the output is a list or a numpy array). Is there some other better way of doing this? Thanks.

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• Why wont numpy matrix let me print its rows?

  - by uberjumper

  Okay this is probably a really dumb question, however its really starting to hurt. I have a numpy matrix, and basically i print it out row by row. However i want to make each row be formatted and separated properly. >>> arr = numpy.matrix([[x for x in range(5)] for y in range(5)]) >>> arr matrix([[0, 1, 2, 3, 4], [0, 1, 2, 3, 4], [0, 1, 2, 3, 4], [0, 1, 2, 3, 4], [0, 1, 2, 3, 4]]) Lets say i want to print the first row, and add a '|' between each element: >>> '|'.join(map(str, arr[0,])) '[[0 1 2 3 4]]' Err... >>> '|'.join(map(lambda x: str(x[0]), arr[0])) '[[0 1 2 3 4]]' I am really confused by this behavior why does it do this?

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• Python: how do I install SciPy on 64 bit Windows?

  - by Peter Mortensen

  How do I install SciPy on my system? Update 1: for the NumPy part (that SciPy depends on) there is actually an installer for 64 bit Windows: numpy-1.3.0.win-amd64-py2.6.msi (is direct download URL, 2310144 bytes). Running the SciPy superpack installer results in this message in a dialog box: "Cannot install. Python version 2.6 required, which was not found in the registry." I already have Python 2.6.2 installed (and a working Django installation in it), but I don't know about any Registry story. The registry entries seems to already exist: REGEDIT4 [HKEY_LOCAL_MACHINE\SOFTWARE\Python] [HKEY_LOCAL_MACHINE\SOFTWARE\Python\PythonCore] [HKEY_LOCAL_MACHINE\SOFTWARE\Python\PythonCore\2.6] [HKEY_LOCAL_MACHINE\SOFTWARE\Python\PythonCore\2.6\Help] [HKEY_LOCAL_MACHINE\SOFTWARE\Python\PythonCore\2.6\Help\Main Python Documentation] @="D:\\Python262\\Doc\\python262.chm" [HKEY_LOCAL_MACHINE\SOFTWARE\Python\PythonCore\2.6\InstallPath] @="D:\\Python262\\" [HKEY_LOCAL_MACHINE\SOFTWARE\Python\PythonCore\2.6\InstallPath\InstallGroup] @="Python 2.6" [HKEY_LOCAL_MACHINE\SOFTWARE\Python\PythonCore\2.6\Modules] [HKEY_LOCAL_MACHINE\SOFTWARE\Python\PythonCore\2.6\PythonPath] @="D:\\Python262\\Lib;D:\\Python262\\DLLs;D:\\Python262\\Lib\\lib-tk" What I have done so far: Step 1 Downloaded the NumPy superpack installer numpy-1.3.0rc2-win32-superpack-python2.6.exe (direct download URL, 4782592 bytes). Running this installer resulted in the same message, "Cannot install. Python version 2.6 required, which was not found in the registry.". Update: there is actually an installer for NumPy that works - see beginning of the question. Step 2 Tried to install NumPy in another way. Downloaded the zip package numpy-1.3.0rc2.zip (direct download URL, 2404011 bytes), extracted the zip file in a normal way to a temporary directory, D:\temp7\numpy-1.3.0rc2 (where setup.py and README.txt is). I then opened a command line window and: d: cd D:\temp7\numpy-1.3.0rc2 setup.py install This ran for a long time and also included use of cl.exe (part of Visual Studio). Here is a nearly 5000 lines long transcript (230 KB). This seemed to work. I can now do this in Python: import numpy as np np.random.random(10) with this result: array([ 0.35667511, 0.56099423, 0.38423629, 0.09733172, 0.81560421, 0.18813222, 0.10566666, 0.84968066, 0.79472597, 0.30997724]) Step 3 Downloaded the SciPy superpack installer, scipy-0.7.1rc3- win32-superpack-python2.6.exe (direct download URL, 45597175 bytes). Running this installer resulted in the message listed in the beginning Step 4 Tried to install SciPy in another way. Downloaded the zip package scipy-0.7.1rc3.zip (direct download URL, 5506562 bytes), extracted the zip file in a normal way to a temporary directory, D:\temp7\scipy-0.7.1 (where setup.py and README.txt is). I then opened a command line window and: d: cd D:\temp7\scipy-0.7.1 setup.py install This did not achieve much - here is a transcript (about 95 lines). And it fails: >>> import scipy as sp2 Traceback (most recent call last): File "<stdin>", line 1, in <module> ImportError: No module named scipy Platform: Python 2.6.2 installed in directory D:\Python262, Windows XP 64 bit SP2, 8 GB RAM, Visual Studio 2008 Professional Edition installed. The startup screen of the installed Python is: Python 2.6.2 (r262:71605, Apr 14 2009, 22:46:50) [MSC v.1500 64 bit (AMD64)] on win32 Type "help", "copyright", "credits" or "license" for more information. >>> Value of PATH, result from SET in a command line window: Path=D:\Perl64\site\bin;D:\Perl64\bin;C:\Program Files (x86)\PC Connectivity Solution\;D:\Perl\site\bin;D:\Perl\bin;C:\WINDOWS\system32;C:\WINDOWS;C:\WINDOWS\System32\Wbem;C:\Program Files (x86)\ATI Technologies\ATI.ACE\Core-Static;d:\Program Files (x86)\WinSCP\;D:\MassLynx\;D:\Program Files (x86)\Analyst\bin;d:\Python262;d:\Python262\Scripts;D:\Program Files (x86)\TortoiseSVN\bin;D:\Program Files\TortoiseSVN\bin;C:\WINDOWS\system32\WindowsPowerShell\v1.0;D:\Program Files (x86)\IDM Computer Solutions\UltraEdit\

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• Numpy: Creating a complex array from 2 real ones?

  - by Duncan Tait

  I swear this should be so easy... Why is it not? :( In fact, I want to combine 2 parts of the same array to make a complex array: Data[:,:,:,0] , Data[:,:,:,1] These don't work: x = np.complex(Data[:,:,:,0], Data[:,:,:,1]) x = complex(Data[:,:,:,0], Data[:,:,:,1]) Am I missing something? Does numpy not like performing array functions on complex numbers? Here's the error: TypeError: only length-1 arrays can be converted to Python scalars Cheers

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• efficiently finding the interval with non-zeros in scipy/numpy in Python?

  - by user248237

  suppose I have a python list or a python 1-d array (represented in numpy). assume that there is a contiguous stretch of elements how can I find the start and end coordinates (i.e. indices) of the stretch of non-zeros in this list or array? for example, a = [0, 0, 0, 0, 1, 2, 3, 4] nonzero_coords(a) should return [4, 7]. for: b = [1, 2, 3, 4, 0, 0] nonzero_coords(b) should return [0, 2]. thanks.

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• How do I convert a numpy array to (and display) an image?

  - by jlswint

  I have created an array thusly: import numpy as np data = np.zeros( (512,512,3), dtype=np.uint8) data[256,256] = [255,0,0] What I want this to do is display a single red dot in the center of a 512x512 image. (At least to begin with... I think I can figure out the rest from there)

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• Using NumPy arrays as 2D mathematical vectors?

  - by CorundumGames

  Right now I'm using lists as position, velocity, and acceleration vectors in my game. Is that a better option than using NumPy's arrays (not the standard library's) as vectors (with float data types)? I'm frequently adding vectors and changing their values directly, then placing the values in these vectors into a Pygame Rect. The vector is used for position (because Rects can't hold floats, so we can't go "between" pixels), and the Rect is used for rendering (because Pygame will only take in Rects for rendering positions).

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• pylab.savefig() and pylab.show() image difference

  - by Jack1990

  I'm making an script to automatically create plots from .xvg files, but there's a problem when I'm trying to use pylab's savefig() method. Using pylab.show() and saving from there, everything's fine. Using pylab.show() Using pylab.savefig() def producePlot(timestep, energy_values,type_line = 'r', jump = 1,finish = 100): fc = sp.interp1d(timestep[::jump], energy_values[::jump],kind='cubic') xnew = numpy.linspace(0, finish, finish*2) pylab.plot(xnew, fc(xnew),type_line) pylab.xlabel('Time in ps ') pylab.ylabel('kJ/mol') pylab.xlim(xmin=0, xmax=finish) def produceSimplePlot(timestep, energy_values,type_line = 'r', jump = 1,finish = 100): pylab.plot(timestep, energy_values,type_line) pylab.xlabel('Time in ps ') pylab.ylabel('kJ/mol') pylab.xlim(xmin=0, xmax=finish) def linearRegression(timestep, energy_values, type_line = 'g'): #, jump = 1,finish = 100): from scipy import stats import numpy #print 'fuck' timestep = numpy.asarray(timestep) slope, intercept, r_value, p_value, std_err = stats.linregress(timestep,energy_values) line = slope*timestep+intercept pylab.plot(timestep, line, type_line) def plottingTime(Title,file_name, timestep, energy_values ,loc, jump , finish): pylab.title(Title) producePlot(timestep,energy_values, 'b',jump, finish) linearRegression(timestep,energy_values) import numpy Average = numpy.average(energy_values) #print Average pylab.legend(("Average = %.2f" %(Average),'Linear Reg'),loc) #pylab.show() pylab.savefig('%s.jpg' %file_name[:-4], bbox_inches= None, pad_inches=0) #if __name__ == '__main__': #plottingTime(Title,timestep1, energy_values, jump =10, finish = 4800) def specialCase(Title,file_name, timestep, energy_values,loc, jump, finish): #print 'Working here ...?' pylab.title(Title) producePlot(timestep,energy_values, 'b',jump, finish) import numpy from pylab import * Average = numpy.average(energy_values) #print Average pylab.legend(("Average = %.2g" %(Average), Title),loc) locs,labels = yticks() yticks(locs, map(lambda x: "%.3g" % x, locs)) #pylab.show() pylab.savefig('%s.jpg' %file_name[:-4] , bbox_inches= None, pad_inches=0) Thanks in advance, John

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• Finding a list of indices from master array using secondary array with non-unique entries

  - by fideli

  I have a master array of length n of id numbers that apply to other analogous arrays with corresponding data for elements in my simulation that belong to those id numbers (e.g. data[id]). Were I to generate a list of id numbers of length m separately and need the information in the data array for those ids, what is the best method of getting a list of indices idx of the original array of ids in order to extract data[idx]? That is, given: a=numpy.array([1,3,4,5,6]) # master array b=numpy.array([3,4,3,6,4,1,5]) # secondary array I would like to generate idx=numpy.array([1,2,1,4,2,0,3]) The array a is typically in sequential order but it's not a requirement. Also, array b will most definitely have repeats and will not be in any order. My current method of doing this is: idx=numpy.array([numpy.where(a==bi)[0][0] for bi in b]) I timed it using the following test: a=(numpy.random.uniform(100,size=100)).astype('int') b=numpy.repeat(a,100) timeit method1(a,b) 10 loops, best of 3: 53.1 ms per loop Is there a better way of doing this?

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• How do I create an empty array/matrix in NumPy?

  - by Ben

  I'm sure I must be being very dumb, but I can't figure out how to use an array or matrix in the way that I would normally use a list. I.e., I want to create an empty array (or matrix) and then add one column (or row) to it at a time. At the moment the only way I can find to do this is like: mat = None for col in columns: if mat is None: mat = col else: mat = hstack((mat, col)) Whereas if it were a list, I'd do something like this: list = [] for item in data: list.append(item) Is there a way to use that kind of notation for NumPy arrays or matrices? (Or a better way -- I'm still pretty new to python!)

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