matrix file format
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Hi, I'm trying to find out what format a matrix input file should have in numpy. example : I have the matrix : [[1 2 3 4 5 6 7 8 9]] and want to read it to nympy from a text-filen that is easy for a user to generate in an editor. Can you tell me how to do that. I read the manual and it didnøt given much af on idea. I thank you in advance Peter I. Hansen
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In principle there is no such format in the sense of other numerical environments. But it is possible to simple put the data into a python module and import that, like # Datafile data.py import Numeric data=Numeric.array([[1,2,3],[4,5,6],[7,8,9]]) # in python (other module or interactive session) from data import data print data HTH __Janko Peter I. Hansen writes:
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You have many options: I frequently use Konrad Hinsen's "Scientific" package (http://dirac.cnrs-orleans.fr/programs/scientific.html). It make importing files from user input or other packages like matlab easy and supports several file formats. The simpliest is a basic white-space-delimitted text file if you have a text file "arrayfile.txt" that looks like this: # arrayfile.txt (lines beginning with '#' are ignored) 1 2 3 4 5 6 6 8 9 You can fire up python and read in your matrix like this:
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I'm trying to find out what format a matrix input file should have in numpy.
Any format you like, but you have to supply the I/O code yourself. Which however is really simple. For example, the following function from ScientificPython: from Scientific.IO.TextFile import TextFile import string, Numeric def readArray(filename): "Return an array containing the data from file |filename|." data = [] for line in TextFile(filename): if line[0] != '#': data.append(map(eval, string.split(line))) a = Numeric.array(data) if a.shape[0] == 1 or a.shape[1] == 1: a = Numeric.ravel(a) return a Konrad. -- ------------------------------------------------------------------------------- Konrad Hinsen | E-Mail: hinsen@cnrs-orleans.fr Centre de Biophysique Moleculaire (CNRS) | Tel.: +33-2.38.25.56.24 Rue Charles Sadron | Fax: +33-2.38.63.15.17 45071 Orleans Cedex 2 | Deutsch/Esperanto/English/ France | Nederlands/Francais -------------------------------------------------------------------------------
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In principle there is no such format in the sense of other numerical environments. But it is possible to simple put the data into a python module and import that, like # Datafile data.py import Numeric data=Numeric.array([[1,2,3],[4,5,6],[7,8,9]]) # in python (other module or interactive session) from data import data print data HTH __Janko Peter I. Hansen writes:
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You have many options: I frequently use Konrad Hinsen's "Scientific" package (http://dirac.cnrs-orleans.fr/programs/scientific.html). It make importing files from user input or other packages like matlab easy and supports several file formats. The simpliest is a basic white-space-delimitted text file if you have a text file "arrayfile.txt" that looks like this: # arrayfile.txt (lines beginning with '#' are ignored) 1 2 3 4 5 6 6 8 9 You can fire up python and read in your matrix like this:
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I'm trying to find out what format a matrix input file should have in numpy.
Any format you like, but you have to supply the I/O code yourself. Which however is really simple. For example, the following function from ScientificPython: from Scientific.IO.TextFile import TextFile import string, Numeric def readArray(filename): "Return an array containing the data from file |filename|." data = [] for line in TextFile(filename): if line[0] != '#': data.append(map(eval, string.split(line))) a = Numeric.array(data) if a.shape[0] == 1 or a.shape[1] == 1: a = Numeric.ravel(a) return a Konrad. -- ------------------------------------------------------------------------------- Konrad Hinsen | E-Mail: hinsen@cnrs-orleans.fr Centre de Biophysique Moleculaire (CNRS) | Tel.: +33-2.38.25.56.24 Rue Charles Sadron | Fax: +33-2.38.63.15.17 45071 Orleans Cedex 2 | Deutsch/Esperanto/English/ France | Nederlands/Francais -------------------------------------------------------------------------------
participants (4)
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Christopher Lee
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Janko Hauser
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Konrad Hinsen
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Peter I. Hansen