[Scipy-svn] r6571 - in branches/0.8.x: doc/release scipy/optimize scipy/optimize/tests

Sun Jun 27 09:11:51 EDT 2010

Author: rgommers
Date: 2010-06-27 08:11:51 -0500 (Sun, 27 Jun 2010)
New Revision: 6571

Modified:
   branches/0.8.x/doc/release/0.8.0-notes.rst
   branches/0.8.x/scipy/optimize/minpack.py
   branches/0.8.x/scipy/optimize/tests/test_minpack.py
Log:
DOC: Add curve_fit and changes to fsolve/leastsq to release notes.

Also add the latter changes to their respective docstrings, and fix some
asserts in their tests.

Modified: branches/0.8.x/doc/release/0.8.0-notes.rst
===================================================================

--- branches/0.8.x/doc/release/0.8.0-notes.rst	2010-06-27 12:53:15 UTC (rev 6570)
+++ branches/0.8.x/doc/release/0.8.0-notes.rst	2010-06-27 13:11:51 UTC (rev 6571)
@@ -62,6 +62,7 @@
 
 Additional deprecations
 -----------------------
+
 * linalg: The function `solveh_banded` currently returns a tuple containing
   the Cholesky factorization and the solution to the linear system.  In
   SciPy 0.9, the return value will be just the solution.
@@ -109,6 +110,7 @@
 
 Additions and modification to LTI functions (scipy.signal)
 ----------------------------------------------------------
+
 * The functions `impulse2` and `step2` were added to `scipy.signal`.
   They use the function `scipy.signal.lsim2` to compute the impulse and
   step response of a system, respectively.
@@ -117,6 +119,7 @@
 
 Improved waveform generators (scipy.signal)
 -------------------------------------------
+
 Several improvements to the `chirp` function in `scipy.signal` were made:
 
 * The waveform generated when `method="logarithmic"` was corrected; it
@@ -132,14 +135,25 @@
 
 New functions and other changes in scipy.linalg
 -----------------------------------------------
+
 The functions `cho_solve_banded`, `circulant`, `companion`, `hadamard` and
 `leslie` were added to `scipy.linalg`.
 
 The function `block_diag` was enhanced to accept scalar and 1D arguments,
 along with the usual 2D arguments.
 
+New function and changes in scipy.optimize
+------------------------------------------
+
+The `curve_fit` function has been added; it takes a function and uses
+non-linear least squares to fit that to the provided data.
+
+The `leastsq` and `fsolve` functions now return an array of size one instead of
+a scalar when solving for a single parameter.
+
 New sparse least squares solver
 -------------------------------
+
 The `lsqr` function was added to `scipy.sparse`.  `This routine
 <http://www.stanford.edu/group/SOL/software/lsqr.html>`_ finds a
 least-squares solution to a large, sparse, linear system of equations.
@@ -153,6 +167,7 @@
 
 Alternative behavior available for `scipy.constants.find`
 ---------------------------------------------------------
+
 The keyword argument `disp` was added to the function `scipy.constants.find`,
 with the default value `True`.  When `disp` is `True`, the behavior is the
 same as in Scipy version 0.7.  When `False`, the function returns the list of
@@ -168,6 +183,7 @@
 
 Faster matlab file reader and default behavior change
 ------------------------------------------------------
+
 We've rewritten the matlab file reader in Cython and it should now read
 matlab files at around the same speed that Matlab does.
 
@@ -192,11 +208,11 @@
 -------------------------------------------
 
 Values of orthogonal polynomials can be evaluated with new vectorized functions
-in ``scipy.special``: ``eval_legendre``, ``eval_chebyt``, ``eval_chebyu``,
-``eval_chebyc``, ``eval_chebys``, ``eval_jacobi``, ``eval_laguerre``,
-``eval_genlaguerre``, ``eval_hermite``, ``eval_hermitenorm``,
-``eval_gegenbauer``, ``eval_sh_legendre``, ``eval_sh_chebyt``,
-``eval_sh_chebyu``, ``eval_sh_jacobi``. This is faster than constructing the
+in `scipy.special`: `eval_legendre`, `eval_chebyt`, `eval_chebyu`,
+`eval_chebyc`, `eval_chebys`, `eval_jacobi`, `eval_laguerre`,
+`eval_genlaguerre`, `eval_hermite`, `eval_hermitenorm`,
+`eval_gegenbauer`, `eval_sh_legendre`, `eval_sh_chebyt`,
+`eval_sh_chebyu`, `eval_sh_jacobi`. This is faster than constructing the
 full coefficient representation of the polynomials, which was previously the
 only available way.
 
@@ -206,13 +222,13 @@
 Lambert W function
 ------------------
 
-``scipy.special.lambertw`` can now be used for evaluating the Lambert W
+`scipy.special.lambertw` can now be used for evaluating the Lambert W
 function.
 
 Improved hypergeometric 2F1 function
 ------------------------------------
 
-Implementation of ``scipy.special.hyp2f1`` for real parameters was revised.
+Implementation of `scipy.special.hyp2f1` for real parameters was revised.
 The new version should produce accurate values for all real parameters.
 
 Removed features
@@ -230,11 +246,11 @@
 arrays is located, while SciPy will house file readers and writers for
 various data formats (data, audio, video, images, matlab, etc.).
 
-Several functions in ``scipy.io`` are removed in the 0.8.0 release including:
-``npfile``, ``save``, ``load``, ``create_module``, ``create_shelf``,
-``objload``, ``objsave``, ``fopen``, ``read_array``, ``write_array``,
-``fread``, ``fwrite``, ``bswap``, ``packbits``, ``unpackbits``, and
-``convert_objectarray``.  Some of these functions have been replaced by NumPy's
+Several functions in `scipy.io` are removed in the 0.8.0 release including:
+`npfile`, `save`, `load`, `create_module`, `create_shelf`,
+`objload`, `objsave`, `fopen`, `read_array`, `write_array`,
+`fread`, `fwrite`, `bswap`, `packbits`, `unpackbits`, and
+`convert_objectarray`.  Some of these functions have been replaced by NumPy's
 raw reading and writing capabilities, memory-mapping capabilities, or array
 methods.  Others have been moved from SciPy to NumPy, since basic array reading
 and writing capability is now handled by NumPy.

Modified: branches/0.8.x/scipy/optimize/minpack.py
===================================================================
--- branches/0.8.x/scipy/optimize/minpack.py	2010-06-27 12:53:15 UTC (rev 6570)
+++ branches/0.8.x/scipy/optimize/minpack.py	2010-06-27 13:11:51 UTC (rev 6571)
@@ -106,6 +106,9 @@
     -----
     ``fsolve`` is a wrapper around MINPACK's hybrd and hybrj algorithms.
 
+    From scipy 0.8.0 `fsolve` returns an array of size one instead of a scalar
+    when solving for a single parameter.
+
     """
     if not warning :
         msg = "The warning keyword is deprecated. Use the warnings module."
@@ -257,6 +260,9 @@
     -----
     "leastsq" is a wrapper around MINPACK's lmdif and lmder algorithms.
 
+    From scipy 0.8.0 `leastsq` returns an array of size one instead of a scalar
+    when solving for a single parameter.
+
     """
     if not warning :
         msg = "The warning keyword is deprecated. Use the warnings module."

Modified: branches/0.8.x/scipy/optimize/tests/test_minpack.py
===================================================================
--- branches/0.8.x/scipy/optimize/tests/test_minpack.py	2010-06-27 12:53:15 UTC (rev 6570)
+++ branches/0.8.x/scipy/optimize/tests/test_minpack.py	2010-06-27 13:11:51 UTC (rev 6571)
@@ -131,8 +131,8 @@
         def func(x,a):
             return x**a
         popt, pcov = curve_fit(func, self.x, self.y)
-        assert len(popt)==1
-        assert pcov.shape==(1,1)
+        assert_(len(popt)==1)
+        assert_(pcov.shape==(1,1))
         assert_almost_equal(popt[0], 1.9149, decimal=4)
         assert_almost_equal(pcov[0,0], 0.0016, decimal=4)
 
@@ -140,8 +140,8 @@
         def func(x, a, b):
             return b*x**a
         popt, pcov = curve_fit(func, self.x, self.y)
-        assert len(popt)==2
-        assert pcov.shape==(2,2)
+        assert_(len(popt)==2)
+        assert_(pcov.shape==(2,2))
         assert_array_almost_equal(popt, [1.7989, 1.1642], decimal=4)
         assert_array_almost_equal(pcov, [[0.0852, -0.1260],[-0.1260, 0.1912]], decimal=4)
 


