Author: bugman
Date: Tue Mar 5 14:04:05 2013
New Revision: 18637
URL: http://svn.gna.org/viewcvs/relax?rev=18637&view=rev
Log:
Removed all references to 'Monte Carlo integration' from the frame order
target functions.
This was replaced by the quasi-random numerical integration a long time ago.
Modified:
branches/frame_order_testing/maths_fns/frame_order/__init__.py
Modified: branches/frame_order_testing/maths_fns/frame_order/__init__.py
URL:
http://svn.gna.org/viewcvs/relax/branches/frame_order_testing/maths_fns/frame_order/__init__.py?rev=18637&r1=18636&r2=18637&view=diff
==============================================================================
--- branches/frame_order_testing/maths_fns/frame_order/__init__.py (original)
+++ branches/frame_order_testing/maths_fns/frame_order/__init__.py Tue Mar 5
14:04:05 2013
@@ -492,7 +492,7 @@
def func_free_rotor_qrint(self, params):
"""Target function for free rotor model optimisation.
- This function optimises the isotropic cone model parameters using
the RDC and PCS base data. Simple Monte Carlo integration is used for the
PCS.
+ This function optimises the isotropic cone model parameters using
the RDC and PCS base data. Simple numerical integration is used for the PCS.
@param params: The vector of parameter values. These are the
tensor rotation angles {alpha, beta, gamma, theta, phi}.
@@ -558,7 +558,7 @@
# Calculate and sum the single alignment chi-squared value
(for the RDC).
chi2_sum = chi2_sum + chi2(self.rdc[align_index],
self.rdc_theta[align_index], self.rdc_error[align_index])
- # PCS via Monte Carlo integration.
+ # PCS via numerical integration.
if self.pcs_flag_sum:
# Numerical integration of the PCSs.
pcs_numeric_int_rotor_qrint(points=self.sobol_angles,
sigma_max=pi, c=self.pcs_const, full_in_ref_frame=self.full_in_ref_frame,
r_pivot_atom=self.r_pivot_atom, r_pivot_atom_rev=self.r_pivot_atom_rev,
r_ln_pivot=self.r_ln_pivot, A=self.A_3D, R_eigen=self.R_eigen,
RT_eigen=RT_eigen, Ri_prime=self.Ri_prime, pcs_theta=self.pcs_theta,
pcs_theta_err=self.pcs_theta_err, missing_pcs=self.missing_pcs,
error_flag=False)
@@ -666,7 +666,7 @@
def func_iso_cone_qrint(self, params):
"""Target function for isotropic cone model optimisation.
- This function optimises the isotropic cone model parameters using
the RDC and PCS base data. Simple Monte Carlo integration is used for the
PCS.
+ This function optimises the isotropic cone model parameters using
the RDC and PCS base data. Simple numerical integration is used for the PCS.
@param params: The vector of parameter values {alpha, beta, gamma,
theta, phi, cone_theta, sigma_max} where the first 3 are the tensor rotation
Euler angles, the next two are the polar and azimuthal angles of the cone
axis, cone_theta is the cone opening half angle, and sigma_max is the torsion
angle.
@@ -732,7 +732,7 @@
# Calculate and sum the single alignment chi-squared value
(for the RDC).
chi2_sum = chi2_sum + chi2(self.rdc[align_index],
self.rdc_theta[align_index], self.rdc_error[align_index])
- # PCS via Monte Carlo integration.
+ # PCS via numerical integration.
if self.pcs_flag_sum:
# Numerical integration of the PCSs.
pcs_numeric_int_iso_cone_qrint(points=self.sobol_angles,
theta_max=cone_theta, sigma_max=sigma_max, c=self.pcs_const,
full_in_ref_frame=self.full_in_ref_frame, r_pivot_atom=self.r_pivot_atom,
r_pivot_atom_rev=self.r_pivot_atom_rev, r_ln_pivot=self.r_ln_pivot,
A=self.A_3D, R_eigen=self.R_eigen, RT_eigen=RT_eigen, Ri_prime=self.Ri_prime,
pcs_theta=self.pcs_theta, pcs_theta_err=self.pcs_theta_err,
missing_pcs=self.missing_pcs, error_flag=False)
@@ -842,7 +842,7 @@
def func_iso_cone_free_rotor_qrint(self, params):
"""Target function for free rotor isotropic cone model optimisation.
- This function optimises the isotropic cone model parameters using
the RDC and PCS base data. Simple Monte Carlo integration is used for the
PCS.
+ This function optimises the isotropic cone model parameters using
the RDC and PCS base data. Simple numerical integration is used for the PCS.
@param params: The vector of parameter values {beta, gamma, theta,
phi, s1} where the first 2 are the tensor rotation Euler angles, the next two
are the polar and azimuthal angles of the cone axis, and s1 is the isotropic
cone order parameter.
@@ -911,7 +911,7 @@
# Calculate and sum the single alignment chi-squared value
(for the RDC).
chi2_sum = chi2_sum + chi2(self.rdc[align_index],
self.rdc_theta[align_index], self.rdc_error[align_index])
- # PCS via Monte Carlo integration.
+ # PCS via numerical integration.
if self.pcs_flag_sum:
# Numerical integration of the PCSs.
pcs_numeric_int_iso_cone_qrint(points=self.sobol_angles,
theta_max=theta_max, sigma_max=pi, c=self.pcs_const,
full_in_ref_frame=self.full_in_ref_frame, r_pivot_atom=self.r_pivot_atom,
r_pivot_atom_rev=self.r_pivot_atom_rev, r_ln_pivot=self.r_ln_pivot,
A=self.A_3D, R_eigen=self.R_eigen, RT_eigen=RT_eigen, Ri_prime=self.Ri_prime,
pcs_theta=self.pcs_theta, pcs_theta_err=self.pcs_theta_err,
missing_pcs=self.missing_pcs, error_flag=False)
@@ -1018,7 +1018,7 @@
def func_iso_cone_torsionless_qrint(self, params):
"""Target function for torsionless isotropic cone model optimisation.
- This function optimises the isotropic cone model parameters using
the RDC and PCS base data. Simple Monte Carlo integration is used for the
PCS.
+ This function optimises the isotropic cone model parameters using
the RDC and PCS base data. Simple numerical integration is used for the PCS.
@param params: The vector of parameter values {beta, gamma, theta,
phi, cone_theta} where the first 2 are the tensor rotation Euler angles, the
next two are the polar and azimuthal angles of the cone axis, and cone_theta
is cone opening angle.
@@ -1084,7 +1084,7 @@
# Calculate and sum the single alignment chi-squared value
(for the RDC).
chi2_sum = chi2_sum + chi2(self.rdc[align_index],
self.rdc_theta[align_index], self.rdc_error[align_index])
- # PCS via Monte Carlo integration.
+ # PCS via numerical integration.
if self.pcs_flag_sum:
# Numerical integration of the PCSs.
pcs_numeric_int_iso_cone_torsionless_qrint(points=self.sobol_angles,
theta_max=cone_theta, c=self.pcs_const,
full_in_ref_frame=self.full_in_ref_frame, r_pivot_atom=self.r_pivot_atom,
r_pivot_atom_rev=self.r_pivot_atom_rev, r_ln_pivot=self.r_ln_pivot,
A=self.A_3D, R_eigen=self.R_eigen, RT_eigen=RT_eigen, Ri_prime=self.Ri_prime,
pcs_theta=self.pcs_theta, pcs_theta_err=self.pcs_theta_err,
missing_pcs=self.missing_pcs, error_flag=False)
@@ -1251,7 +1251,7 @@
# Calculate and sum the single alignment chi-squared value
(for the RDC).
chi2_sum = chi2_sum + chi2(self.rdc[align_index],
self.rdc_theta[align_index], self.rdc_error[align_index])
- # PCS via Monte Carlo integration.
+ # PCS via numerical integration.
if self.pcs_flag_sum:
# Numerical integration of the PCSs.
pcs_numeric_int_pseudo_ellipse_qrint(points=self.sobol_angles,
theta_x=cone_theta_x, theta_y=cone_theta_y, sigma_max=cone_sigma_max,
c=self.pcs_const, full_in_ref_frame=self.full_in_ref_frame,
r_pivot_atom=self.r_pivot_atom, r_pivot_atom_rev=self.r_pivot_atom_rev,
r_ln_pivot=self.r_ln_pivot, A=self.A_3D, R_eigen=self.R_eigen,
RT_eigen=RT_eigen, Ri_prime=self.Ri_prime, pcs_theta=self.pcs_theta,
pcs_theta_err=self.pcs_theta_err, missing_pcs=self.missing_pcs,
error_flag=False)
@@ -1355,7 +1355,7 @@
def func_pseudo_ellipse_free_rotor_qrint(self, params):
"""Target function for free_rotor pseudo-elliptic cone model
optimisation.
- This function optimises the isotropic cone model parameters using
the RDC and PCS base data. Simple Monte Carlo integration is used for the
PCS.
+ This function optimises the isotropic cone model parameters using
the RDC and PCS base data. Simple numerical integration is used for the PCS.
@param params: The vector of parameter values {alpha, beta, gamma,
eigen_alpha, eigen_beta, eigen_gamma, cone_theta_x, cone_theta_y} where the
first 3 are the average position rotation Euler angles, the next 3 are the
Euler angles defining the eigenframe, and the last 2 are the free_rotor
pseudo-elliptic cone geometric parameters.
@@ -1522,7 +1522,7 @@
def func_pseudo_ellipse_torsionless_qrint(self, params):
"""Target function for torsionless pseudo-elliptic cone model
optimisation.
- This function optimises the isotropic cone model parameters using
the RDC and PCS base data. Simple Monte Carlo integration is used for the
PCS.
+ This function optimises the isotropic cone model parameters using
the RDC and PCS base data. Simple numerical integration is used for the PCS.
@param params: The vector of parameter values {alpha, beta, gamma,
eigen_alpha, eigen_beta, eigen_gamma, cone_theta_x, cone_theta_y} where the
first 3 are the average position rotation Euler angles, the next 3 are the
Euler angles defining the eigenframe, and the last 2 are the torsionless
pseudo-elliptic cone geometric parameters.
@@ -1585,7 +1585,7 @@
# Calculate and sum the single alignment chi-squared value
(for the RDC).
chi2_sum = chi2_sum + chi2(self.rdc[align_index],
self.rdc_theta[align_index], self.rdc_error[align_index])
- # PCS via Monte Carlo integration.
+ # PCS via numerical integration.
if self.pcs_flag_sum:
# Numerical integration of the PCSs.
pcs_numeric_int_pseudo_ellipse_torsionless_qrint(points=self.sobol_angles,
theta_x=cone_theta_x, theta_y=cone_theta_y, c=self.pcs_const,
full_in_ref_frame=self.full_in_ref_frame, r_pivot_atom=self.r_pivot_atom,
r_pivot_atom_rev=self.r_pivot_atom_rev, r_ln_pivot=self.r_ln_pivot,
A=self.A_3D, R_eigen=self.R_eigen, RT_eigen=RT_eigen, Ri_prime=self.Ri_prime,
pcs_theta=self.pcs_theta, pcs_theta_err=self.pcs_theta_err,
missing_pcs=self.missing_pcs, error_flag=False)
@@ -1831,7 +1831,7 @@
# Calculate and sum the single alignment chi-squared value
(for the RDC).
chi2_sum = chi2_sum + chi2(self.rdc[align_index],
self.rdc_theta[align_index], self.rdc_error[align_index])
- # PCS via Monte Carlo integration.
+ # PCS via numerical integration.
if self.pcs_flag_sum:
# Numerical integration of the PCSs.
pcs_numeric_int_rotor_qrint(points=self.sobol_angles,
sigma_max=sigma_max, c=self.pcs_const,
full_in_ref_frame=self.full_in_ref_frame, r_pivot_atom=self.r_pivot_atom,
r_pivot_atom_rev=self.r_pivot_atom_rev, r_ln_pivot=self.r_ln_pivot,
A=self.A_3D, R_eigen=self.R_eigen, RT_eigen=RT_eigen, Ri_prime=self.Ri_prime,
pcs_theta=self.pcs_theta, pcs_theta_err=self.pcs_theta_err,
missing_pcs=self.missing_pcs, error_flag=False)
r18637 - /branches/frame_order_testing/maths_fns/frame_order/__init__.py