Author: semor
Date: Wed Jan 16 17:31:11 2008
New Revision: 4795
URL: http://svn.gna.org/viewcvs/relax?rev=4795&view=rev
Log:
Merged revisions 4778-4780,4785,4787,4792 via svnmerge from
svn+ssh://semor@xxxxxxxxxxx/svn/relax/1.3
........
r4778 | bugman | 2008-01-16 05:30:55 -0500 (Wed, 16 Jan 2008) | 3 lines
Converted the maths_fns.chi2 module from Numeric to numpy.
........
r4779 | bugman | 2008-01-16 06:00:28 -0500 (Wed, 16 Jan 2008) | 5 lines
Updated the docstrings of the chi-squared value, gradient, and Hessian
functions.
They are now in epydoc format.
........
r4780 | bugman | 2008-01-16 06:04:34 -0500 (Wed, 16 Jan 2008) | 3 lines
Added a module docstring to the chi2 module.
........
r4785 | semor | 2008-01-16 10:08:42 -0500 (Wed, 16 Jan 2008) | 5 lines
Corrected a function spacing so it has 2 preceding empty lines.
This was pointed by the 'code_validator' script.
........
r4787 | bugman | 2008-01-16 10:37:07 -0500 (Wed, 16 Jan 2008) | 3 lines
Shifted all the dummy return_conversion_factor() methods which return 1
into the base class.
........
r4792 | bugman | 2008-01-16 11:01:15 -0500 (Wed, 16 Jan 2008) | 3 lines
Temporarily shifted the model-free code from using the 'minimise' directory
to using minfx.
........
Modified:
branches/consistency_tests_1.3/ (props changed)
branches/consistency_tests_1.3/maths_fns/chi2.py
branches/consistency_tests_1.3/specific_fns/base_class.py
branches/consistency_tests_1.3/specific_fns/jw_mapping.py
branches/consistency_tests_1.3/specific_fns/model_free/mf_minimise.py
branches/consistency_tests_1.3/specific_fns/noe.py
branches/consistency_tests_1.3/specific_fns/relax_fit.py
Propchange: branches/consistency_tests_1.3/
------------------------------------------------------------------------------
--- svnmerge-integrated (original)
+++ svnmerge-integrated Wed Jan 16 17:31:11 2008
@@ -1,1 +1,1 @@
-/1.3:1-3320,3333-4175,4223,4241-4335,4338-4433,4440-4461,4473,4476-4493,4523-4551,4567-4577,4579,4585-4586,4618-4623,4659,4662-4693,4698-4759
+/1.3:1-3320,3333-4175,4223,4241-4335,4338-4433,4440-4461,4473,4476-4493,4523-4551,4567-4577,4579,4585-4586,4618-4623,4659,4662-4693,4698-4759,4778-4792
Modified: branches/consistency_tests_1.3/maths_fns/chi2.py
URL:
http://svn.gna.org/viewcvs/relax/branches/consistency_tests_1.3/maths_fns/chi2.py?rev=4795&r1=4794&r2=4795&view=diff
==============================================================================
--- branches/consistency_tests_1.3/maths_fns/chi2.py (original)
+++ branches/consistency_tests_1.3/maths_fns/chi2.py Wed Jan 16 17:31:11 2008
@@ -1,6 +1,6 @@
###############################################################################
#
#
-# Copyright (C) 2003, 2004 Edward d'Auvergne
#
+# Copyright (C) 2003, 2004, 2008 Edward d'Auvergne
#
#
#
# This file is part of the program relax.
#
#
#
@@ -20,9 +20,10 @@
#
#
###############################################################################
+"""Module containing functions for calculating the chi-squared value,
gradient, and Hessian."""
# Python module imports.
-from Numeric import Float64, sum, transpose, zeros
+from numpy import sum
# Chi-squared value.
@@ -33,19 +34,29 @@
"""Function to calculate the chi-squared value.
The chi-sqared equation
- ~~~~~~~~~~~~~~~~~~~~~~~
- _n_
- \ (yi - yi()) ** 2
- Chi2 = > ----------------
- /__ sigma_i ** 2
- i=1
+ =======================
+
+ _n_
+ \ (yi - yi(theta)) ** 2
+ chi^2(theta) = > ---------------------
+ /__ sigma_i ** 2
+ i=1
where:
+ theta is the parameter vector.
yi are the values of the measured data set.
- yi() are the values of the back calculated data set.
+ yi(theta) are the values of the back calculated data set.
sigma_i are the values of the error set.
- The chi-squared value is returned.
+
+ @param data: The vector of yi values.
+ @type data: numpy array
+ @param back_calc_vals: The vector of yi(theta) values.
+ @type back_calc_vals: numpy array
+ @param errors: The vector of sigma_i values.
+ @type errors: numpy array
+ @return: The chi-squared value.
+ @rtype: float
"""
# Calculate the chi-squared statistic.
@@ -60,19 +71,31 @@
"""Function to create the chi-squared gradient.
The chi-sqared gradient
- ~~~~~~~~~~~~~~~~~~~~~~~
- _n_
- dChi2 \ / yi - yi() dyi() \
- ------- = -2 > | ---------- . ------- |
- dthetaj /__ \ sigma_i**2 dthetaj /
- i=1
+ =======================
+
+ _n_
+ dchi^2(theta) \ / yi - yi(theta) dyi(theta) \
+ ------------- = -2 > | -------------- . ---------- |
+ dthetaj /__ \ sigma_i**2 dthetaj /
+ i=1
where:
+ theta is the parameter vector.
yi are the values of the measured data set.
- yi() are the values of the back calculated data set.
+ yi(theta) are the values of the back calculated data set.
+ dyi(theta)/dthetaj are the values of the back calculated gradient.
sigma_i are the values of the error set.
- The chi-squared gradient vector is returned.
+ @param data: The vector of yi values.
+ @type data: numpy array
+ @param back_calc_vals: The vector of yi(theta) values.
+ @type back_calc_vals: numpy array
+ @param back_calc_grad: The matrix of dyi(theta)/dthetaj values.
+ @type back_calc_grad: numpy matrix
+ @param errors: The vector of sigma_i values.
+ @type errors: numpy array
+ @return: The chi-squared gradient.
+ @rtype: numpy array
"""
# Calculate the chi-squared gradient.
@@ -87,17 +110,37 @@
"""Function to create the chi-squared Hessian.
The chi-squared Hessian
- ~~~~~~~~~~~~~~~~~~~~~~~
+ =======================
+
_n_
- d2chi2 \ 1 / dyi() dyi()
d2yi() \
- --------------- = 2 > ---------- | ------- . ------- - (yi - yi())
. --------------- |
- dthetaj.dthetak /__ sigma_i**2 \ dthetaj dthetak
dthetaj.dthetak /
+ d2chi^2(theta) \ 1 / dyi(theta) dyi(theta)
d2yi(theta) \
+ --------------- = 2 > ---------- | ---------- . ---------- -
(yi-yi(theta)) . --------------- |
+ dthetaj.dthetak /__ sigma_i**2 \ dthetaj dthetak
dthetaj.dthetak /
i=1
where:
+ theta is the parameter vector.
yi are the values of the measured relaxation data set.
- yi() are the values of the back calculated relaxation data set.
+ yi(theta) are the values of the back calculated relaxation data set.
+ dyi(theta)/dthetaj are the values of the back calculated gradient.
+ d2yi(theta)/dthetaj.dthetak are the values of the back calculated
Hessian.
sigma_i are the values of the error set.
+
+
+ @param data: The vector of yi values.
+ @type data: numpy array
+ @param back_calc_vals: The vector of yi(theta) values.
+ @type back_calc_vals: numpy array
+ @param back_calc_grad_j: The matrix of dyi(theta)/dthetaj values.
+ @type back_calc_grad_j: numpy matrix
+ @param back_calc_grad_k: The matrix of dyi(theta)/dthetak values.
+ @type back_calc_grad_k: numpy matrix
+ @param back_calc_hess: The 3rd rank tensor of
d2yi(theta)/dthetaj.dthetak values.
+ @type back_calc_hess: numpy matrix
+ @param errors: The vector of sigma_i values.
+ @type errors: numpy array
+ @return: The chi-squared Hessian.
+ @rtype: numpy 3rd rank tensor
"""
# Calculate the chi-squared Hessian.
Modified: branches/consistency_tests_1.3/specific_fns/base_class.py
URL:
http://svn.gna.org/viewcvs/relax/branches/consistency_tests_1.3/specific_fns/base_class.py?rev=4795&r1=4794&r2=4795&view=diff
==============================================================================
--- branches/consistency_tests_1.3/specific_fns/base_class.py (original)
+++ branches/consistency_tests_1.3/specific_fns/base_class.py Wed Jan 16
17:31:11 2008
@@ -70,6 +70,12 @@
def overfit_deselect(self):
"""Dummy function, nornally for deselecting spins with insufficient
data for minimisation."""
+
+
+ def return_conversion_factor(self, stat_type):
+ """Dummy function for returning 1.0."""
+
+ return 1.0
def return_data(self, spin):
Modified: branches/consistency_tests_1.3/specific_fns/jw_mapping.py
URL:
http://svn.gna.org/viewcvs/relax/branches/consistency_tests_1.3/specific_fns/jw_mapping.py?rev=4795&r1=4794&r2=4795&view=diff
==============================================================================
--- branches/consistency_tests_1.3/specific_fns/jw_mapping.py (original)
+++ branches/consistency_tests_1.3/specific_fns/jw_mapping.py Wed Jan 16
17:31:11 2008
@@ -272,12 +272,6 @@
continue
- def return_conversion_factor(self, stat_type):
- """Dummy function for returning 1.0."""
-
- return 1.0
-
-
def return_data_name(self, name):
"""
Reduced spectral density mapping data type string matching patterns
Modified:
branches/consistency_tests_1.3/specific_fns/model_free/mf_minimise.py
URL:
http://svn.gna.org/viewcvs/relax/branches/consistency_tests_1.3/specific_fns/model_free/mf_minimise.py?rev=4795&r1=4794&r2=4795&view=diff
==============================================================================
--- branches/consistency_tests_1.3/specific_fns/model_free/mf_minimise.py
(original)
+++ branches/consistency_tests_1.3/specific_fns/model_free/mf_minimise.py Wed
Jan 16 17:31:11 2008
@@ -31,13 +31,14 @@
from float import isNaN, isInf
from generic_fns.selection import spin_loop
from maths_fns.mf import Mf
-from minimise.generic import generic_minimise
+from minfx.generic import generic_minimise
from relax_errors import RelaxError, RelaxInfError, RelaxLenError,
RelaxNaNError, RelaxNoModelError, RelaxNoPdbError, RelaxNoResError,
RelaxNoSequenceError, RelaxNoTensorError, RelaxNoValueError,
RelaxNoVectorsError, RelaxNucleusError
class Mf_minimise:
"""Class containing functions specific to model-free optimisation."""
+
def back_calc(self, run=None, index=None, ri_label=None, frq_label=None,
frq=None):
"""Back-calculation of relaxation data from the model-free parameter
values."""
Modified: branches/consistency_tests_1.3/specific_fns/noe.py
URL:
http://svn.gna.org/viewcvs/relax/branches/consistency_tests_1.3/specific_fns/noe.py?rev=4795&r1=4794&r2=4795&view=diff
==============================================================================
--- branches/consistency_tests_1.3/specific_fns/noe.py (original)
+++ branches/consistency_tests_1.3/specific_fns/noe.py Wed Jan 16 17:31:11
2008
@@ -231,12 +231,6 @@
data.noe_err = None
- def return_conversion_factor(self, stat_type):
- """Dummy function for returning 1.0."""
-
- return 1.0
-
-
def return_data_name(self, name):
"""
NOE calculation data type string matching patterns
Modified: branches/consistency_tests_1.3/specific_fns/relax_fit.py
URL:
http://svn.gna.org/viewcvs/relax/branches/consistency_tests_1.3/specific_fns/relax_fit.py?rev=4795&r1=4794&r2=4795&view=diff
==============================================================================
--- branches/consistency_tests_1.3/specific_fns/relax_fit.py (original)
+++ branches/consistency_tests_1.3/specific_fns/relax_fit.py Wed Jan 16
17:31:11 2008
@@ -883,12 +883,6 @@
self.relax.generic.intensity.read(run=run, file=file, dir=dir,
format=format, heteronuc=heteronuc, proton=proton, int_col=int_col,
assign_func=self.assign_function)
- def return_conversion_factor(self, stat_type):
- """Dummy function for returning 1.0."""
-
- return 1.0
-
-
def return_data(self, run, i):
"""Function for returning the peak intensity data structure."""
r4795 - in /branches/consistency_tests_1.3: ./ maths_fns/ specific_fns/ specific_fns/model_free/