On 11/13/06, Seweryn Kokot <[EMAIL PROTECTED]> wrote:
Hello,

Why ipython and python interactive shell give two different information?

--- ipython
Python 2.4.4 (#2, Oct 20 2006, 00:23:25)
Type "copyright", "credits" or "license" for more information.

IPython 0.7.2 -- An enhanced Interactive Python.
?       -> Introduction to IPython's features.
%magic  -> Information about IPython's 'magic' % functions.
help    -> Python's own help system.
object? -> Details about 'object'. ?object also works, ?? prints more.

In [1]: from scipy import linalg

In [2]: help(linalg.eig)

Help on function eig in module numpy.linalg.linalg:

eig(a)
    eig(a) returns u,v  where u is the eigenvalues and
    v is a matrix of eigenvectors with vector v[:,i] corresponds to
    eigenvalue u[i].  Satisfies the equation dot(a, v[:,i]) =
    u[i]*v[:,i]
--- ipython

while

--- python
Python 2.4.4 (#2, Oct 20 2006, 00:23:25)
[GCC 4.1.2 20061015 (prerelease) (Debian 4.1.1-16.1)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> from scipy import linalg
>>> help(linalg.eig)

Help on function eig in module scipy.linalg.decomp:

eig(a, b=None, left=False, right=True, overwrite_a=False, overwrite_b=False)
    Solve ordinary and generalized eigenvalue problem
    of a square matrix.

    Inputs:

      a     -- An N x N matrix.
      b     -- An N x N matrix [default is identity(N)].
      left  -- Return left eigenvectors [disabled].
      right -- Return right eigenvectors [enabled].
      overwrite_a, overwrite_b -- save space by overwriting the a and/or
                                  b matrices (both False by default)

    Outputs:

      w      -- eigenvalues [left==right==False].
      w,vr   -- w and right eigenvectors [left==False,right=True].
      w,vl   -- w and left eigenvectors [left==True,right==False].
      w,vl,vr  -- [left==right==True].

    Definitions:
...
--- python

Any idea?

I expect scipy.linalg and numpy.linalg are different modules containing different functions. That said, the documentation in scipy.linalg looks quite a bit more complete.

Chuck


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