[SciPy-dev] Changes to trunk/scipy/optimize

Stéfan van der Walt stefan@sun.ac...
Tue Feb 9 03:31:12 CST 2010


Hi all,

I noticed the following changeset coming through. Do you think docstrings
are the right place for advertising external packages?  If not, should they
be moved to the module docstring, or removed entirely?

Regards
Stéfan

---------- Forwarded message ----------
Author: dmitrey.kroshko
Date: 2010-02-09 02:41:34 -0600 (Tue, 09 Feb 2010)
New Revision: 6221

Modified:
  trunk/scipy/optimize/anneal.py
  trunk/scipy/optimize/cobyla.py
  trunk/scipy/optimize/lbfgsb.py
  trunk/scipy/optimize/minpack.py
  trunk/scipy/optimize/nnls.py
  trunk/scipy/optimize/optimize.py
  trunk/scipy/optimize/slsqp.py
  trunk/scipy/optimize/tnc.py
Log:
scikits.openopt replaced by mere openopt


Modified: trunk/scipy/optimize/anneal.py
===================================================================
--- trunk/scipy/optimize/anneal.py      2010-02-08 15:18:27 UTC (rev 6220)
+++ trunk/scipy/optimize/anneal.py      2010-02-09 08:41:34 UTC (rev 6221)
@@ -217,6 +217,8 @@

      fixed_point -- scalar fixed-point finder

+      OpenOpt -- Python package with more optimization solvers
+
    """
    x0 = asarray(x0)
    lower = asarray(lower)

Modified: trunk/scipy/optimize/cobyla.py
===================================================================
--- trunk/scipy/optimize/cobyla.py      2010-02-08 15:18:27 UTC (rev 6220)
+++ trunk/scipy/optimize/cobyla.py      2010-02-09 08:41:34 UTC (rev 6221)
@@ -46,8 +46,6 @@

    See also:

-        scikits.openopt, which offers a unified syntax to call this and
other solvers
-
        fmin, fmin_powell, fmin_cg,
              fmin_bfgs, fmin_ncg -- multivariate local optimizers
        leastsq -- nonlinear least squares minimizer
@@ -65,6 +63,9 @@

        fixed_point -- scalar fixed-point finder

+        OpenOpt -- a tool which offers a unified syntax to call this and
+         other solvers with possibility of automatic differentiation
+
    """
    err = "cons must be a sequence of callable functions or a single"\
              " callable function."

Modified: trunk/scipy/optimize/lbfgsb.py
===================================================================
--- trunk/scipy/optimize/lbfgsb.py      2010-02-08 15:18:27 UTC (rev 6220)
+++ trunk/scipy/optimize/lbfgsb.py      2010-02-09 08:41:34 UTC (rev 6221)
@@ -119,8 +119,6 @@
       ACM Transactions on Mathematical Software, Vol 23, Num. 4, pp. 550 -
560.

    See also:
-        scikits.openopt, which offers a unified syntax to call this and
other solvers
-
        fmin, fmin_powell, fmin_cg,
               fmin_bfgs, fmin_ncg -- multivariate local optimizers
        leastsq -- nonlinear least squares minimizer
@@ -138,6 +136,9 @@

        fixed_point -- scalar fixed-point finder

+        OpenOpt -- a tool which offers a unified syntax to call this and
+         other solvers with possibility of automatic differentiation
+
    """
    n = len(x0)


Modified: trunk/scipy/optimize/minpack.py
===================================================================
--- trunk/scipy/optimize/minpack.py     2010-02-08 15:18:27 UTC (rev 6220)
+++ trunk/scipy/optimize/minpack.py     2010-02-09 08:41:34 UTC (rev 6221)
@@ -102,8 +102,6 @@

    See Also
    --------
-    scikits.openopt : offers a unified syntax to call this and other
solvers
-
    fmin, fmin_powell, fmin_cg, fmin_bfgs, fmin_ncg : multivariate local
optimizers

    leastsq : nonlinear least squares minimizer
@@ -118,6 +116,9 @@

    fixed_point : scalar and vector fixed-point finder

+    OpenOpt : a tool which offers a unified syntax to call this and
+     other solvers with possibility of automatic differentiation
+
    """
    if not warning :
        msg = "The warning keyword is deprecated. Use the warnings module."
@@ -263,7 +264,6 @@

    See Also
    --------
-    scikits.openopt: offers a unified syntax to call this and other solvers
    fmin, fmin_powell, fmin_cg, fmin_bfgs, fmin_ncg: multivariate local
optimizers
    fmin_l_bfgs_b, fmin_tnc, fmin_cobyla: constrained multivariate
optimizers
    anneal, brute: global optimizers
@@ -272,6 +272,9 @@
    brentq, brenth, ridder, bisect, newton: one-dimensional root-finding
    fixed_point: scalar and vector fixed-point finder
    curve_fit: find parameters for a curve-fitting problem.
+    OpenOpt : a tool which offers a unified syntax to call this and
+     other solvers with possibility of automatic differentiation
+
    """
    if not warning :
        msg = "The warning keyword is deprecated. Use the warnings module."

Modified: trunk/scipy/optimize/nnls.py
===================================================================
--- trunk/scipy/optimize/nnls.py        2010-02-08 15:18:27 UTC (rev 6220)
+++ trunk/scipy/optimize/nnls.py        2010-02-09 08:41:34 UTC (rev 6221)
@@ -16,6 +16,8 @@

    wrapper around NNLS.F code below nnls/ directory

+    Check OpenOpt for more LLSP solvers
+
    """

    A,b = map(asarray_chkfinite, (A,b))

Modified: trunk/scipy/optimize/optimize.py
===================================================================
--- trunk/scipy/optimize/optimize.py    2010-02-08 15:18:27 UTC (rev 6220)
+++ trunk/scipy/optimize/optimize.py    2010-02-09 08:41:34 UTC (rev 6221)
@@ -156,7 +156,8 @@

        Uses a Nelder-Mead simplex algorithm to find the minimum of
        function of one or more variables.
-
+        Check OpenOpt - a tool which offers a unified syntax to call
+        this and other solvers with possibility of automatic
differentiation.
    """
    fcalls, func = wrap_function(func, args)
    x0 = asfarray(x0).flatten()
@@ -694,8 +695,8 @@

    *See Also*:

-      scikits.openopt : SciKit which offers a unified syntax to call
-                        this and other solvers.
+      OpenOpt : a tool which offers a unified syntax to call
+                this and other solvers with possibility of automatic
differentiation.

    """
    x0 = asarray(x0).squeeze()
@@ -862,7 +863,8 @@
        using the nonlinear conjugate gradient algorithm of Polak and
        Ribiere See Wright, and Nocedal 'Numerical Optimization',
        1999, pg. 120-122.
-
+        Check OpenOpt - a tool which offers a unified syntax to call
+        this and other solvers with possibility of automatic
differentiation.
    """
    x0 = asarray(x0).flatten()
    if maxiter is None:
@@ -1018,8 +1020,7 @@
            If True, return a list of results at each iteration.

    :Notes:
-      1. scikits.openopt offers a unified syntax to call this and other
solvers.
-      2. Only one of `fhess_p` or `fhess` need to be given.  If `fhess`
+      1. Only one of `fhess_p` or `fhess` need to be given.  If `fhess`
      is provided, then `fhess_p` will be ignored.  If neither `fhess`
      nor `fhess_p` is provided, then the hessian product will be
      approximated using finite differences on `fprime`. `fhess_p`
@@ -1027,6 +1028,8 @@
      given, finite-differences on `fprime` are used to compute
      it. See Wright, and Nocedal 'Numerical Optimization', 1999,
      pg. 140.
+      2. Check OpenOpt - a tool which offers a unified syntax to call
+      this and other solvers with possibility of automatic differentiation.

    """
    x0 = asarray(x0).flatten()
@@ -1179,8 +1182,9 @@
        Finds a local minimizer of the scalar function `func` in the
        interval x1 < xopt < x2 using Brent's method.  (See `brent`
        for auto-bracketing).
+        Check OpenOpt - a tool which offers a unified syntax to call
+        this and other solvers with possibility of automatic
differentiation.

-
    """
    # Test bounds are of correct form

@@ -1722,7 +1726,8 @@

        Uses a modification of Powell's method to find the minimum of
        a function of N variables.
-
+        Check OpenOpt - a tool which offers a unified syntax to call
+        this and other solvers with possibility of automatic
differentiation.
    """
    # we need to use a mutable object here that we can update in the
    # wrapper function

Modified: trunk/scipy/optimize/slsqp.py
===================================================================
--- trunk/scipy/optimize/slsqp.py       2010-02-08 15:18:27 UTC (rev 6220)
+++ trunk/scipy/optimize/slsqp.py       2010-02-09 08:41:34 UTC (rev 6221)
@@ -146,6 +146,11 @@

    for examples see :ref:`in the tutorial <tutorial-sqlsp>`

+    See also
+    --------
+    OpenOpt - a tool which offers a unified syntax to call this
+    and other solvers with possibility of automatic differentiation.
+
    """

    exit_modes = { -1 : "Gradient evaluation required (g & a)",

Modified: trunk/scipy/optimize/tnc.py
===================================================================
--- trunk/scipy/optimize/tnc.py 2010-02-08 15:18:27 UTC (rev 6220)
+++ trunk/scipy/optimize/tnc.py 2010-02-09 08:41:34 UTC (rev 6221)
@@ -164,8 +164,6 @@
            Return code as defined in the RCSTRINGS dict.

    :SeeAlso:
-      - scikits.openopt, which offers a unified syntax to call this and
other solvers
-
      - fmin, fmin_powell, fmin_cg, fmin_bfgs, fmin_ncg :
         multivariate local optimizers

@@ -184,6 +182,9 @@

      - fixed_point : scalar fixed-point finder

+      - OpenOpt : a tool which offers a unified syntax to call this and
+         other solvers with possibility of automatic differentiation.
+
 """
    x0 = asarray(x0, dtype=float).tolist()
    n = len(x0)

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