[Scipy-svn] r5547 - trunk/scipy/optimize

scipy-svn@scip... scipy-svn@scip...
Thu Feb 12 22:15:51 CST 2009


Author: oliphant
Date: 2009-02-12 22:15:48 -0600 (Thu, 12 Feb 2009)
New Revision: 5547

Modified:
   trunk/scipy/optimize/minpack.py
Log:
Correct docstring for curve_fit.

Modified: trunk/scipy/optimize/minpack.py
===================================================================
--- trunk/scipy/optimize/minpack.py	2009-02-13 01:57:30 UTC (rev 5546)
+++ trunk/scipy/optimize/minpack.py	2009-02-13 04:15:48 UTC (rev 5547)
@@ -342,7 +342,7 @@
         can be determined using introspection, otherwise a ValueError is raised). 
     sigma : None or N-length sequence
         If not None, it represents the standard-deviation of ydata.  This
-        vector, if given, will be used as weights in the least-squares problem. 
+        vector, if given, will be used to weight the least-squares problem. 
 
     Returns
     -------
@@ -350,13 +350,13 @@
         Optimal values for the parameters so that the sum of the squared error of
         f(xdata, *popt) - ydata is minimized
     pcov : 2d array
-        The estimated covariance of popt.  The diagonals provide the variance of
-        the parameter estimate. 
+        A covariance matrix shouwing the curvature of the sum-of-squares 
+        residual near the returned solution.  Returned directly from the call
+        to scipy.optimize.leastsq.
 
     Notes
     -----
-    The algorithm uses the Levenburg-Marquardt algorithm (scipy.optimize.leastsq)
-    under the hood. 
+    The algorithm uses the Levenburg-Marquardt algorithm: scipy.optimize.leastsq
 
     Example
     -------



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