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Python bug? Indexing to matrices

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  Python bug? Indexing to matrices David <davidbtdt@gmail.com> - 2011-07-11 22:39 -0700
    Re: Python bug? Indexing to matrices Chris Rebert <clp2@rebertia.com> - 2011-07-11 22:44 -0700
    Re: Python bug? Indexing to matrices Ben Finney <ben+python@benfinney.id.au> - 2011-07-12 15:59 +1000
    Re: Python bug? Indexing to matrices sturlamolden <sturlamolden@yahoo.no> - 2011-07-12 05:59 -0700
      Re: Python bug? Indexing to matrices sturlamolden <sturlamolden@yahoo.no> - 2011-07-12 06:03 -0700
      Re: Python bug? Indexing to matrices David <davidbtdt@gmail.com> - 2011-07-12 06:23 -0700

#9304 — Python bug? Indexing to matrices

Should the following line work for defining a matrix with zeros?

c= [[0]*col]*row

where "col" is the number of columns in the matrix and "row" is of
course the number of rows.

If this a valid way of initializing a matrix in Python 3.2.1, then it
appears to me that a bug surfaces in Python when performing this line:

c[i][j] = c[i][j] + a[i][k] * b[k][j]

It writes to the jth column rather than just the i,j cell.

I'm new at Python and am not sure if I'm just doing something wrong if
there is really a bug in Python.  The script works fine if I
initialize the matrix with numpy instead:

c = np.zeros((row,col))

So, I know my matrix multiply algorithm is correct (I know I could use
numpy for matrix multiplication, this was just to learn Python).

I've attached my source code below.

TIA,

David

-----

#!python
#	dot.py - Matrix multiply in matricies: [c] = [a] * [b]

import numpy as np

a = [[3, 7], [-2, 1], [2, 4]]
b = [[2, 1, -3, 1], [4, 3, -2, 3]]

print("a = {0}, b = {1}".format(a,b))


row = len(a)
col = len(b[0])

#c = np.zeros((row,col))    # <----- Correct results when using this
line
c= [[0]*col]*row                # <----- Incorrect results when using
this line
print(c)

for i in range(row):			# Index into rows of [a]
	for j in range(col):		# Index into columns of [b]
		c[i][j] = 0

		for k in range(len(b)):		# Index into columns of [a] and rows of [b]
			print("c[{0}][{1}] + a[{2}][{3}] * b[{4}][{5}] = {6} + {7} *
{8}".format(i,j,i,k,k,j,c[i][j],a[i][k],b[k][j]))
			c[i][j] = c[i][j] + a[i][k] * b[k][j]

print(c)

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#9305

On Mon, Jul 11, 2011 at 10:39 PM, David <davidbtdt@gmail.com> wrote:
> Should the following line work for defining a matrix with zeros?
>
> c= [[0]*col]*row
>
> where "col" is the number of columns in the matrix and "row" is of
> course the number of rows.

Nope. See the FAQ:
http://docs.python.org/faq/programming.html#how-do-i-create-a-multidimensional-list

Cheers,
Chris

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#9307

David <davidbtdt@gmail.com> writes:

> Should the following line work for defining a matrix with zeros?
>
> c= [[0]*col]*row

No. Python lists are not matrixes and are not arrays.

If you want good implementations of arrays and matrices, use NumPy
<URL:http://numpy.scipy.org/>.

-- 
 \      “Properly read, the Bible is the most potent force for atheism |
  `\                                    ever conceived.” —Isaac Asimov |
_o__)                                                                  |
Ben Finney

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#9313

On 12 Jul, 07:39, David <davidb...@gmail.com> wrote:
> Should the following line work for defining a matrix with zeros?
>
> c= [[0]*col]*row

No. The rows will be aliased.

This will work:

c = [[0]*col for i in range(row)]

Note that Python lists are not ment to be used as matrices. We have
NumPy or the array module for that.


> If this a valid way of initializing a matrix in Python 3.2.1, then it
> appears to me that a bug surfaces in Python when performing this line:
>
> c[i][j] = c[i][j] + a[i][k] * b[k][j]
>
> It writes to the jth column rather than just the i,j cell.

That is due to aliasing.


> I'm new at Python and am not sure if I'm just doing something wrong if
> there is really a bug in Python.  The script works fine if I
> initialize the matrix with numpy instead:
>
> c = np.zeros((row,col))
>
> So, I know my matrix multiply algorithm is correct (I know I could use
> numpy for matrix multiplication, this was just to learn Python).

Like so:

   np.dot(a,b)

or

   ma = np.matrix(a)
   mb = np.matrix(b)
   a*b

or call BLAS directly:

   scipy.linalg.fblas.dgemm


Sturla

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#9314

On 12 Jul, 14:59, sturlamolden <sturlamol...@yahoo.no> wrote:

>    ma = np.matrix(a)
>    mb = np.matrix(b)
>    a*b

ma*mb

Sorry for the typo.

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#9315

Thank all for the very helpful replies.  The goal of the matrix
multiply exercise was just to help my son and I learn Python better.
I now understand *why* my initialization of [c] was wrong and I am
continuing to check out numpy and scipy.

Regards,
David

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