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[newbie] confusion concerning fetching an element in a 2d-array

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  [newbie] confusion concerning fetching an element in a 2d-array Jean Dubois <jeandubois314@gmail.com> - 2014-03-25 03:26 -0700
    Re: [newbie] confusion concerning fetching an element in a 2d-array Steven D'Aprano <steve+comp.lang.python@pearwood.info> - 2014-03-25 11:01 +0000
      Re: [newbie] confusion concerning fetching an element in a 2d-array Jean Dubois <jeandubois314@gmail.com> - 2014-03-25 06:47 -0700
        Re: [newbie] confusion concerning fetching an element in a 2d-array Dave Angel <davea@davea.name> - 2014-03-25 10:42 -0400
          Re: [newbie] confusion concerning fetching an element in a 2d-array Mark H Harris <harrismh777@gmail.com> - 2014-03-25 11:40 -0500
          Re: [newbie] confusion concerning fetching an element in a 2d-array Mark H Harris <harrismh777@gmail.com> - 2014-03-25 11:40 -0500
          Re: [newbie] confusion concerning fetching an element in a 2d-array Jean Dubois <jeandubois314@gmail.com> - 2014-03-25 11:58 -0700
            Re: [newbie] confusion concerning fetching an element in a 2d-array Joel Goldstick <joel.goldstick@gmail.com> - 2014-03-25 15:15 -0400
              Re: [newbie] confusion concerning fetching an element in a 2d-array Jean Dubois <jeandubois314@gmail.com> - 2014-03-26 01:48 -0700
            Re: [newbie] confusion concerning fetching an element in a 2d-array Dave Angel <davea@davea.name> - 2014-03-25 15:58 -0400
              Re: [newbie] confusion concerning fetching an element in a 2d-array Jean Dubois <jeandubois314@gmail.com> - 2014-03-26 01:47 -0700
        Re: [newbie] confusion concerning fetching an element in a 2d-array Steven D'Aprano <steve+comp.lang.python@pearwood.info> - 2014-03-25 15:35 +0000
        Re: [newbie] confusion concerning fetching an element in a 2d-array Peter Otten <__peter__@web.de> - 2014-03-25 17:12 +0100
          Re: [newbie] confusion concerning fetching an element in a 2d-array Jean Dubois <jeandubois314@gmail.com> - 2014-03-25 11:33 -0700

#69005 — [newbie] confusion concerning fetching an element in a 2d-array

I'm confused by the behaviour of the following python-script I wrote:

#!/usr/bin/env python
#I first made a data file 'test.dat' with the following content
#1.0 2 3
#4 5 6.0
#7 8 9
import numpy as np
lines=[line.strip() for line in open('test.dat')]
#convert lines-list to numpy-array
array_lines=np.array(lines)
#fetch element at 2nd row, 2nd column:
print array_lines[1, 1]


When running the script I always get the following error:
IndexError: invalid index

Can anyone here explain me what I am doing wrong and how to fix it?

thanks in advance
jean

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#69008

On Tue, 25 Mar 2014 03:26:26 -0700, Jean Dubois wrote:

> I'm confused by the behaviour of the following python-script I wrote:
> 
> #!/usr/bin/env python
> #I first made a data file 'test.dat' with the following content 
> #1.0 2 3
> #4 5 6.0
> #7 8 9
> import numpy as np
> lines=[line.strip() for line in open('test.dat')] 
> #convert lines-list to numpy-array
> array_lines=np.array(lines)
> #fetch element at 2nd row, 2nd column: 
> print array_lines[1, 1]
> 
> 
> When running the script I always get the following error: IndexError:
> invalid index
> 
> Can anyone here explain me what I am doing wrong and how to fix it?

Yes. Inspect the array by printing it, and you'll see that it is a one-
dimensional array, not two, and the entries are strings:


py> import numpy as np
py> # simulate a text file
... data = """1.0 2 3
... 4 5 6.0
... 7 8 9"""
py> lines=[line.strip() for line in data.split('\n')]
py> # convert lines-list to numpy-array
... array_lines = np.array(lines)
py> print array_lines
['1.0 2 3' '4 5 6.0' '7 8 9']


The interactive interpreter is your friend! You never need to guess what 
the problem is, Python has powerful introspection abilities, one of the 
most powerful is also one of the simplest: print. Another powerful tool 
in the interactive interpreter is help().

So, what to do about it? Firstly, convert your string read from a file 
into numbers, then build your array. Here's one way:

py> values = [float(s) for s in data.split()]
py> print values
[1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]
py> array_lines = np.array(values)
py> array_lines = array_lines.reshape(3, 3)
py> print array_lines
[[ 1.  2.  3.]
 [ 4.  5.  6.]
 [ 7.  8.  9.]]


There may be other ways to do this, but that works for me.


-- 
Steven D'Aprano
http://import-that.dreamwidth.org/

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#69026

Op dinsdag 25 maart 2014 12:01:37 UTC+1 schreef Steven D'Aprano:
> On Tue, 25 Mar 2014 03:26:26 -0700, Jean Dubois wrote:
>
> > I'm confused by the behaviour of the following python-script I wrote:
> > 
> > #!/usr/bin/env python
> > #I first made a data file 'test.dat' with the following content 
> > #1.0 2 3
> > #4 5 6.0
> > #7 8 9
> > import numpy as np
> > lines=[line.strip() for line in open('test.dat')] 
> > #convert lines-list to numpy-array
> > array_lines=np.array(lines)
> > #fetch element at 2nd row, 2nd column: 
> > print array_lines[1, 1]
> > 
> > 
> > When running the script I always get the following error: IndexError:
> > invalid index
> > 
> > Can anyone here explain me what I am doing wrong and how to fix it?
>
> Yes. Inspect the array by printing it, and you'll see that it is a one-
> dimensional array, not two, and the entries are strings:
>
>
> py> import numpy as np
> py> # simulate a text file
> ... data = """1.0 2 3
> ... 4 5 6.0
> ... 7 8 9"""
> py> lines=[line.strip() for line in data.split('\n')]
> py> # convert lines-list to numpy-array
> ... array_lines = np.array(lines)
> py> print array_lines
> ['1.0 2 3' '4 5 6.0' '7 8 9']
>
>
> The interactive interpreter is your friend! You never need to guess what 
> the problem is, Python has powerful introspection abilities, one of the 
> most powerful is also one of the simplest: print. Another powerful tool 
> in the interactive interpreter is help().
>
> So, what to do about it? Firstly, convert your string read from a file 
> into numbers, then build your array. Here's one way:
>
> py> values = [float(s) for s in data.split()]
> py> print values
> [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]
> py> array_lines = np.array(values)
> py> array_lines = array_lines.reshape(3, 3)
> py> print array_lines
> [[ 1.  2.  3.]
>  [ 4.  5.  6.]
>  [ 7.  8.  9.]]
>
Dear Steve,
Thanks for answering my question but unfortunately now I'm totally
confused. 
Above I see parts from different programs which I can't
assemble together to one working program (I really tried hard).
Can I tell from your comment I shouldn't use numpy?
I also don't see how to get the value an element specified by (row,
column) from a numpy_array like "array_lines" in my original code

All I need is a little python-example reading a file with e.g. three lines
with three numbers per line and putting those numbers  as floats in a
3x3-numpy_array, then selecting an element from that numpy_array using
it's row and column-number.

thanks in advance and kind regards,
jean

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#69035

 Jean Dubois <jeandubois314@gmail.com> Wrote in message:
> Op dinsdag 25 maart 2014 12:01:37 UTC+1 schreef Steven D'Aprano:

>>
>> py> values = [float(s) for s in data.split()]
>> py> print values
>> [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]
>> py> array_lines = np.array(values)
>> py> array_lines = array_lines.reshape(3, 3)
>> py> print array_lines
>> [[ 1.  2.  3.]
>>  [ 4.  5.  6.]
>>  [ 7.  8.  9.]]
>>
> Dear Steve,
> Thanks for answering my question but unfortunately now I'm totally
> confused. 
> Above I see parts from different programs which I can't
> assemble together to one working program (I really tried hard).
> Can I tell from your comment I shouldn't use numpy?
> I also don't see how to get the value an element specified by (row,
> column) from a numpy_array like "array_lines" in my original code

I don't use numpy,  but I thought Steven's description was clear
 enough.

Your problem was not the extraction,  but the creation of the
 array.  Use print to prove that to yourself. 

> 
> All I need is a little python-example reading a file with e.g. three lines
> with three numbers per line and putting those numbers  as floats in a
> 3x3-numpy_array, then selecting an element from that numpy_array using
> it's row and column-number.

If your instructor wanted you to copy examples,  he would have
 given you one.

First write some code to split and convert each line into floats.
 You don't even try that in your original.  Then do that in a
 loop. Now you have all the floats in one list or array. I presume
 that it's two dimensional.  Use print to check.  If it's not, 
 you'll have to either post process it with a reshape method,  or
 change the way you accumulate it. I can't help with the latter.
 



-- 
DaveA

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#69041

On 3/25/14 9:42 AM, Dave Angel wrote:
>> All I need is a little python-example reading a file with e.g. three lines
>> with three numbers per line and putting those numbers  as floats in a
>> 3x3-numpy_array, then selecting an element from that numpy_array using
>> it's row and column-number.
>
> If your instructor wanted you to copy examples,  he would have
>   given you one.

{ouch}


Give them a toad they'll have warts all day; teach them to eat a toad 
they'll never have warts again...   or something like that.

marcus

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#69051

On 3/25/14 9:42 AM, Dave Angel wrote:
>> All I need is a little python-example reading a file with e.g. three lines
>> with three numbers per line and putting those numbers  as floats in a
>> 3x3-numpy_array, then selecting an element from that numpy_array using
>> it's row and column-number.
>
> If your instructor wanted you to copy examples,  he would have
>   given you one.

{ouch}


Give them a toad they'll have warts all day; teach them to eat a toad 
they'll never have warts again...   or something like that.

marcus

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#69053

Op dinsdag 25 maart 2014 15:42:13 UTC+1 schreef Dave Angel:
> Jean Dubois <jeandubois314@gmail.com> Wrote in message:
> > Op dinsdag 25 maart 2014 12:01:37 UTC+1 schreef Steven D'Aprano:
> >>
> >> py> values = [float(s) for s in data.split()]
> >> py> print values
> >> [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]
> >> py> array_lines = np.array(values)
> >> py> array_lines = array_lines.reshape(3, 3)
> >> py> print array_lines
> >> [[ 1.  2.  3.]
> >>  [ 4.  5.  6.]
> >>  [ 7.  8.  9.]]
> >>
> > Dear Steve,
> > Thanks for answering my question but unfortunately now I'm totally
> > confused. 
> > Above I see parts from different programs which I can't
> > assemble together to one working program (I really tried hard).
> > Can I tell from your comment I shouldn't use numpy?
> > I also don't see how to get the value an element specified by (row,
> > column) from a numpy_array like "array_lines" in my original code
> I don't use numpy,  but I thought Steven's description was clear
>  enough.
> Your problem was not the extraction,  but the creation of the
>  array.  Use print to prove that to yourself. 
> > 
> > All I need is a little python-example reading a file with e.g. three lines
> > with three numbers per line and putting those numbers  as floats in a
> > 3x3-numpy_array, then selecting an element from that numpy_array using
> > it's row and column-number.
> If your instructor wanted you to copy examples,  he would have
>  given you one.
please Dave leave that belittling tone behind, there's no instructor
whatsoever involved here. I constructed this example myself as I know very
well I have to start with little pieces of code first to be able to master
larger problems later. I just wanted to figure this example out first,
and as I now learned from Peter's marvellous explanation there _is_ an
elegant solution in Python to this kind of problem.
So if you are irritated by newbie-questions in the future, just neglect
them

thanks
jean

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#69060

[Multipart message — attachments visible in raw view] — view raw

Jean, be aware there is also python tutor list you might like.  This is
sometimes a tough crowd here. Don't be discouraged. It can be a badge of
honor sometimes

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#69108

Op dinsdag 25 maart 2014 20:15:27 UTC+1 schreef Joel Goldstick:
> Jean, be aware there is also python tutor list you might like.  This is sometimes a tough crowd here. Don't be discouraged. It can be a badge of honor sometimes

thanks for the suggestions, I already subscribed to the python tutor list

kind regards,
jean

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#69063

 Jean Dubois <jeandubois314@gmail.com> Wrote in message:
> Op dinsdag 25 maart 2014 15:42:13 UTC+1 schreef Dave Angel:

>> If your instructor wanted you to copy examples,  he would have
>>  given you one.
> please Dave leave that belittling tone behind, there's no instructor
> whatsoever involved here. 

It wasn't my intention to belittle you; I'm sorry. But we do get a
 lot of people here asking for homework help, and not saying
 that's what it is. And when it's homework we do better explaining
 than just writing the code. 

In fact you only needed to add a line like
     data= infile.read ()
to Steven's original to get a complete working example. 

> I constructed this example myself as I know very
> well I have to start with little pieces of code first to be able to master
> larger problems later. I just wanted to figure this example out first,
> and as I now learned from Peter's marvellous explanation there _is_ an
> elegant solution in Python to this kind of problem.
> So if you are irritated by newbie-questions in the future, just neglect
> them

Not irritated,  just temporarily misguided. 


-- 
DaveA

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#69107

Op dinsdag 25 maart 2014 20:58:10 UTC+1 schreef Dave Angel:
> Jean Dubois <jeandubois314@gmail.com> Wrote in message:
> > Op dinsdag 25 maart 2014 15:42:13 UTC+1 schreef Dave Angel:
>
> >> If your instructor wanted you to copy examples,  he would have
> >>  given you one.
> > please Dave leave that belittling tone behind, there's no instructor
> > whatsoever involved here. 
>
> It wasn't my intention to belittle you; I'm sorry. But we do get a
>  lot of people here asking for homework help, and not saying
>  that's what it is. And when it's homework we do better explaining
>  than just writing the code. 
>
> In fact you only needed to add a line like
>      data= infile.read ()
> to Steven's original to get a complete working example. 
>
> > I constructed this example myself as I know very
> > well I have to start with little pieces of code first to be able to master
> > larger problems later. I just wanted to figure this example out first,
> > and as I now learned from Peter's marvellous explanation there _is_ an
> > elegant solution in Python to this kind of problem.
> > So if you are irritated by newbie-questions in the future, just neglect
> > them
>
> Not irritated,  just temporarily misguided. 
OK, no hard feelings

kind regards,
jean

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#69039

On Tue, 25 Mar 2014 06:47:23 -0700, Jean Dubois wrote:

[...]
> Thanks for answering my question but unfortunately now I'm totally
> confused.
> Above I see parts from different programs which I can't assemble
> together to one working program (I really tried hard). Can I tell from
> your comment I shouldn't use numpy? 

No, you misunderstood me. I never suggested that you avoid numpy. If you 
read my code, I use numpy. That's the "import numpy as np", and then 
later I refer to np.

What I suggested is that you open up the Python interactive interpreter 
and use it for experimentation. Not that you avoid numpy! You will use 
numpy inside the interactive interpreter.

Do you know how to start the interactive interpreter? You seem to be 
using Linux, or maybe Mac. Open a console or xterm window, and type

python

then press Enter, and the interactive interpreter will start.


> I also don't see how to get the
> value an element specified by (row, column) from a numpy_array like
> "array_lines" in my original code

Once you build the array, you get the element the same way you tried (but 
failed) earlier:

print array_lines[1, 1]


will print the element at row 1, column 1. The problem you had before was 
that you had a one dimensional array, not a two dimensional one.


> All I need is a little python-example reading a file with e.g. three
> lines with three numbers per line and putting those numbers  as floats
> in a 3x3-numpy_array, then selecting an element from that numpy_array
> using it's row and column-number.

Yes, I'm sure you do. And you will learn much more by writing this code 
yourself.

You were very, very close with your earlier attempt. In English, you had:

* import the numpy module
* read the file into a list of text lines
* store the text lines in a numpy array
* try to print a single item from the array

but it failed because the list of lines was only one dimensional. I gave 
you some code that was very similar:

* import the numpy module
* fake a text file using a string
* split the string into a list of substrings
* convert each substring into a number (float)
* store the numbers in a numpy array
* change the size of the array to turn it from 1D to 2D
* print the array


Can you identify which part of code goes with each English description? 
That's your first job. Then identify the parts of code you want to take 
from my example and put it into your example.

Good luck, and have fun!



-- 
Steven D'Aprano
http://import-that.dreamwidth.org/

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#69040

Jean Dubois wrote:

> Op dinsdag 25 maart 2014 12:01:37 UTC+1 schreef Steven D'Aprano:
>> On Tue, 25 Mar 2014 03:26:26 -0700, Jean Dubois wrote:
>>
>> > I'm confused by the behaviour of the following python-script I wrote:
>> > 
>> > #!/usr/bin/env python
>> > #I first made a data file 'test.dat' with the following content
>> > #1.0 2 3
>> > #4 5 6.0
>> > #7 8 9
>> > import numpy as np
>> > lines=[line.strip() for line in open('test.dat')]
>> > #convert lines-list to numpy-array
>> > array_lines=np.array(lines)
>> > #fetch element at 2nd row, 2nd column:
>> > print array_lines[1, 1]
>> > 
>> > 
>> > When running the script I always get the following error: IndexError:
>> > invalid index
>> > 
>> > Can anyone here explain me what I am doing wrong and how to fix it?
>>
>> Yes. Inspect the array by printing it, and you'll see that it is a one-
>> dimensional array, not two, and the entries are strings:
>>
>>
>> py> import numpy as np
>> py> # simulate a text file
>> ... data = """1.0 2 3
>> ... 4 5 6.0
>> ... 7 8 9"""
>> py> lines=[line.strip() for line in data.split('\n')]
>> py> # convert lines-list to numpy-array
>> ... array_lines = np.array(lines)
>> py> print array_lines
>> ['1.0 2 3' '4 5 6.0' '7 8 9']
>>
>>
>> The interactive interpreter is your friend! You never need to guess what
>> the problem is, Python has powerful introspection abilities, one of the
>> most powerful is also one of the simplest: print. Another powerful tool
>> in the interactive interpreter is help().
>>
>> So, what to do about it? Firstly, convert your string read from a file
>> into numbers, then build your array. Here's one way:
>>
>> py> values = [float(s) for s in data.split()]
>> py> print values
>> [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]
>> py> array_lines = np.array(values)
>> py> array_lines = array_lines.reshape(3, 3)
>> py> print array_lines
>> [[ 1.  2.  3.]
>>  [ 4.  5.  6.]
>>  [ 7.  8.  9.]]
>>
> Dear Steve,
> Thanks for answering my question but unfortunately now I'm totally
> confused.
> Above I see parts from different programs which I can't
> assemble together to one working program (I really tried hard).
> Can I tell from your comment I shouldn't use numpy?
> I also don't see how to get the value an element specified by (row,
> column) from a numpy_array like "array_lines" in my original code
> 
> All I need is a little python-example reading a file with e.g. three lines
> with three numbers per line and putting those numbers  as floats in a
> 3x3-numpy_array, then selecting an element from that numpy_array using
> it's row and column-number.

I'll try, too, but be warned that I'm using the same methology as Steven. 
Try to replicate every step in the following exploration.

First let's make sure we start with the same data:

$ cat test.dat
1.0 2 3
4 5 6.0
7 8 9

Then fire up the interactve interpreter:

$ python
Python 2.7.5+ (default, Feb 27 2014, 19:37:08) 
[GCC 4.8.1] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy
>>> lines = [line.strip() for line in open("test.dat")]
>>> lines
['1.0 2 3', '4 5 6.0', '7 8 9']

As you can see lines is a list of three strings.
Let's break these strings into parts:

>>> cells = [line.split() for line in lines]
>>> cells
[['1.0', '2', '3'], ['4', '5', '6.0'], ['7', '8', '9']]

We now have a list of lists of strings and you can address individual items 
with

>>> cells[1][2]
'6.0'

What happens when pass this list of lists of strings to the numpy.array() 
constructor?

>>> a = numpy.array(cells)
>>> a
array([['1.0', '2', '3'],
       ['4', '5', '6.0'],
       ['7', '8', '9']], 
      dtype='|S3')
>>> a[1,2]
'6.0'

It sort of works, but the array entries are strings rather than floating 
point numbers. Let's fix that:

>>> a = numpy.array(cells, dtype=float)
>>> a
array([[ 1.,  2.,  3.],
       [ 4.,  5.,  6.],
       [ 7.,  8.,  9.]])
>>> a[1,2]
6.0

OK, now we can put the previous steps into a script:

$ cat tmp.py
import numpy
cells = [line.split() for line in open("test.dat")]
a = numpy.array(cells, dtype=float)
print a[1, 2]

Run it:
$ python tmp.py
6.0

Seems to work. But reading a 2D array from a file really looks like a common  
task -- there should be a library function for that:

$ python
Python 2.7.5+ (default, Feb 27 2014, 19:37:08) 
[GCC 4.8.1] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy
>>> numpy.loadtxt("test.dat")
array([[ 1.,  2.,  3.],
       [ 4.,  5.,  6.],
       [ 7.,  8.,  9.]])

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#69050

Op dinsdag 25 maart 2014 17:12:12 UTC+1 schreef Peter Otten:
> Jean Dubois wrote:
> > Op dinsdag 25 maart 2014 12:01:37 UTC+1 schreef Steven D'Aprano:
> >> On Tue, 25 Mar 2014 03:26:26 -0700, Jean Dubois wrote:
> >>
> >> > I'm confused by the behaviour of the following python-script I wrote:
> >> > 
> >> > #!/usr/bin/env python
> >> > #I first made a data file 'test.dat' with the following content
> >> > #1.0 2 3
> >> > #4 5 6.0
> >> > #7 8 9
> >> > import numpy as np
> >> > lines=[line.strip() for line in open('test.dat')]
> >> > #convert lines-list to numpy-array
> >> > array_lines=np.array(lines)
> >> > #fetch element at 2nd row, 2nd column:
> >> > print array_lines[1, 1]
> >> > 
> >> > 
> >> > When running the script I always get the following error: IndexError:
> >> > invalid index
> >> > 
> >> > Can anyone here explain me what I am doing wrong and how to fix it?
> >>
> >> Yes. Inspect the array by printing it, and you'll see that it is a one-
> >> dimensional array, not two, and the entries are strings:
> >>
> >>
> >> py> import numpy as np
> >> py> # simulate a text file
> >> ... data = """1.0 2 3
> >> ... 4 5 6.0
> >> ... 7 8 9"""
> >> py> lines=[line.strip() for line in data.split('\n')]
> >> py> # convert lines-list to numpy-array
> >> ... array_lines = np.array(lines)
> >> py> print array_lines
> >> ['1.0 2 3' '4 5 6.0' '7 8 9']
> >>
> >>
> >> The interactive interpreter is your friend! You never need to guess what
> >> the problem is, Python has powerful introspection abilities, one of the
> >> most powerful is also one of the simplest: print. Another powerful tool
> >> in the interactive interpreter is help().
> >>
> >> So, what to do about it? Firstly, convert your string read from a file
> >> into numbers, then build your array. Here's one way:
> >>
> >> py> values = [float(s) for s in data.split()]
> >> py> print values
> >> [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]
> >> py> array_lines = np.array(values)
> >> py> array_lines = array_lines.reshape(3, 3)
> >> py> print array_lines
> >> [[ 1.  2.  3.]
> >>  [ 4.  5.  6.]
> >>  [ 7.  8.  9.]]
> >>
> > Dear Steve,
> > Thanks for answering my question but unfortunately now I'm totally
> > confused.
> > Above I see parts from different programs which I can't
> > assemble together to one working program (I really tried hard).
> > Can I tell from your comment I shouldn't use numpy?
> > I also don't see how to get the value an element specified by (row,
> > column) from a numpy_array like "array_lines" in my original code
> > 
> > All I need is a little python-example reading a file with e.g. three lines
> > with three numbers per line and putting those numbers  as floats in a
> > 3x3-numpy_array, then selecting an element from that numpy_array using
> > it's row and column-number.
> I'll try, too, but be warned that I'm using the same methology as Steven. 
> Try to replicate every step in the following exploration.
> First let's make sure we start with the same data:
> $ cat test.dat
> 1.0 2 3
> 4 5 6.0
> 7 8 9
> Then fire up the interactve interpreter:
> $ python
> Python 2.7.5+ (default, Feb 27 2014, 19:37:08) 
> [GCC 4.8.1] on linux2
> Type "help", "copyright", "credits" or "license" for more information.
> >>> import numpy
> >>> lines = [line.strip() for line in open("test.dat")]
> >>> lines
> ['1.0 2 3', '4 5 6.0', '7 8 9']
> As you can see lines is a list of three strings.
> Let's break these strings into parts:
> >>> cells = [line.split() for line in lines]
> >>> cells
> [['1.0', '2', '3'], ['4', '5', '6.0'], ['7', '8', '9']]
> We now have a list of lists of strings and you can address individual items 
> with
> >>> cells[1][2]
> '6.0'
> What happens when pass this list of lists of strings to the numpy.array() 
> constructor?
> >>> a = numpy.array(cells)
> >>> a
> array([['1.0', '2', '3'],
>        ['4', '5', '6.0'],
>        ['7', '8', '9']], 
>       dtype='|S3')
> >>> a[1,2]
> '6.0'
> It sort of works, but the array entries are strings rather than floating 
> point numbers. Let's fix that:
> >>> a = numpy.array(cells, dtype=float)
> >>> a
> array([[ 1.,  2.,  3.],
>        [ 4.,  5.,  6.],
>        [ 7.,  8.,  9.]])
> >>> a[1,2]
> 6.0
> OK, now we can put the previous steps into a script:
> $ cat tmp.py
> import numpy
> cells = [line.split() for line in open("test.dat")]
> a = numpy.array(cells, dtype=float)
> print a[1, 2]
> Run it:
> $ python tmp.py
> 6.0
> Seems to work. But reading a 2D array from a file really looks like a common  
> task -- there should be a library function for that:
> $ python
> Python 2.7.5+ (default, Feb 27 2014, 19:37:08) 
> [GCC 4.8.1] on linux2
> Type "help", "copyright", "credits" or "license" for more information.
> >>> import numpy
> >>> numpy.loadtxt("test.dat")
> array([[ 1.,  2.,  3.],
>        [ 4.,  5.,  6.],
>        [ 7.,  8.,  9.]])

Thank you very much Peter for this great lesson, you made a lot of things
clear to me. 

sincerely
jean

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