[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
-------
More information about the Scipy-svn
mailing list