Author: tlinnet
Date: Tue Aug 5 20:47:27 2014
New Revision: 24970
URL: http://svn.gna.org/viewcvs/relax?rev=24970&view=rev
Log:
Split target function of model MP05, into a calc and two func_MP05* variants.
One target function will use measured R1 values, while one target function
will use the fitted R1 values.
They will use the same calculation function.
sr #3135(https://gna.org/support/?3135): Optimisation of the R1 relaxation
rate for the off-resonance R1rho relaxation dispersion models.
Modified:
branches/R1_fitting/target_functions/relax_disp.py
Modified: branches/R1_fitting/target_functions/relax_disp.py
URL:
http://svn.gna.org/viewcvs/relax/branches/R1_fitting/target_functions/relax_disp.py?rev=24970&r1=24969&r2=24970&view=diff
==============================================================================
--- branches/R1_fitting/target_functions/relax_disp.py (original)
+++ branches/R1_fitting/target_functions/relax_disp.py Tue Aug 5 20:47:27
2014
@@ -55,7 +55,7 @@
from lib.errors import RelaxError
from lib.float import isNaN
from target_functions.chi2 import chi2_rankN
-from specific_analyses.relax_disp.variables import EXP_TYPE_CPMG_DQ,
EXP_TYPE_CPMG_MQ, EXP_TYPE_CPMG_PROTON_MQ, EXP_TYPE_CPMG_PROTON_SQ,
EXP_TYPE_CPMG_SQ, EXP_TYPE_CPMG_ZQ, EXP_TYPE_LIST_CPMG, EXP_TYPE_R1RHO,
MODEL_B14, MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94,
MODEL_DPL94_FIT_R1, MODEL_IT99, MODEL_LIST_CPMG, MODEL_LIST_FULL,
MODEL_LIST_MMQ, MODEL_LIST_MQ_CPMG, MODEL_LIST_NUMERIC, MODEL_LIST_R1RHO,
MODEL_LIST_R1RHO_FULL, MODEL_LIST_R1RHO_FIT_R1, MODEL_LIST_R1RHO_W_R1,
MODEL_LM63, MODEL_LM63_3SITE, MODEL_M61, MODEL_M61B, MODEL_MP05,
MODEL_MMQ_CR72, MODEL_NOREX, MODEL_NOREX_R1RHO, MODEL_NOREX_R1RHO_FIT_R1,
MODEL_NS_CPMG_2SITE_3D, MODEL_NS_CPMG_2SITE_3D_FULL,
MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_NS_CPMG_2SITE_STAR,
MODEL_NS_CPMG_2SITE_STAR_FULL, MODEL_NS_MMQ_2SITE, MODEL_NS_MMQ_3SITE,
MODEL_NS_MMQ_3SITE_LINEAR, MODEL_NS_R1RHO_2SITE, MODEL_NS_R1RHO_3SITE,
MODEL_NS_R1RHO_3SITE_LINEAR, MODEL_PARAM_DW_MIX_DOUBLE,
MODEL_PARAM_DW_MIX_QUADRUPLE, MODEL_PARAM_INV_RELAX_TIMES, MODEL_PARAM_R20B,
MODEL_TAP03, MODEL_TAP03_FIT_R1, MODEL_TP02, MODEL_TP02_FIT_R1, MODEL_TSMFK01
+from specific_analyses.relax_disp.variables import EXP_TYPE_CPMG_DQ,
EXP_TYPE_CPMG_MQ, EXP_TYPE_CPMG_PROTON_MQ, EXP_TYPE_CPMG_PROTON_SQ,
EXP_TYPE_CPMG_SQ, EXP_TYPE_CPMG_ZQ, EXP_TYPE_LIST_CPMG, EXP_TYPE_R1RHO,
MODEL_B14, MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94,
MODEL_DPL94_FIT_R1, MODEL_IT99, MODEL_LIST_CPMG, MODEL_LIST_FULL,
MODEL_LIST_MMQ, MODEL_LIST_MQ_CPMG, MODEL_LIST_NUMERIC, MODEL_LIST_R1RHO,
MODEL_LIST_R1RHO_FULL, MODEL_LIST_R1RHO_FIT_R1, MODEL_LIST_R1RHO_W_R1,
MODEL_LM63, MODEL_LM63_3SITE, MODEL_M61, MODEL_M61B, MODEL_MP05,
MODEL_MP05_FIT_R1, MODEL_MMQ_CR72, MODEL_NOREX, MODEL_NOREX_R1RHO,
MODEL_NOREX_R1RHO_FIT_R1, MODEL_NS_CPMG_2SITE_3D,
MODEL_NS_CPMG_2SITE_3D_FULL, MODEL_NS_CPMG_2SITE_EXPANDED,
MODEL_NS_CPMG_2SITE_STAR, MODEL_NS_CPMG_2SITE_STAR_FULL, MODEL_NS_MMQ_2SITE,
MODEL_NS_MMQ_3SITE, MODEL_NS_MMQ_3SITE_LINEAR, MODEL_NS_R1RHO_2SITE,
MODEL_NS_R1RHO_3SITE, MODEL_NS_R1RHO_3SITE_LINEAR, MODEL_PARAM_DW_MIX_DOUBLE,
MODEL_PARAM_DW_MIX_QUADRUPLE, MODEL_PARAM_INV_RELAX_TIMES, MODEL_PARAM_R20B,
MODEL_TAP03, MODEL_TAP03_FIT_R1, MODEL_TP02, MODEL_TP02_FIT_R1, MODEL_TSMFK01
class Dispersion:
@@ -530,6 +530,8 @@
self.func = self.func_TAP03_fit_r1
if model == MODEL_MP05:
self.func = self.func_MP05
+ if model == MODEL_MP05_FIT_R1:
+ self.func = self.func_MP05_fit_r1
if model == MODEL_NS_R1RHO_2SITE:
self.func = self.func_ns_r1rho_2site
if model == MODEL_NS_R1RHO_3SITE:
@@ -648,6 +650,44 @@
# Back calculate the R2eff values.
r1rho_DPL94(r1rho_prime=self.r1rho_prime_struct,
phi_ex=self.phi_ex_struct, kex=kex, theta=self.tilt_angles, R1=R1,
spin_lock_fields2=self.spin_lock_omega1_squared, back_calc=self.back_calc)
+
+ # Clean the data for all values, which is left over at the end of
arrays.
+ self.back_calc = self.back_calc*self.disp_struct
+
+ # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
+ if self.has_missing:
+ # Replace with values.
+ self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
+
+ # Return the total chi-squared value.
+ return chi2_rankN(self.values, self.back_calc, self.errors)
+
+
+ def calc_MP05(self, R1=None, r1rho_prime=None, dw=None, pA=None,
kex=None):
+ """Calculation function for the Miloushev and Palmer (2005) R1rho
off-resonance 2-site model.
+
+ @keyword R1: The R1 value.
+ @type R1: list of float
+ @keyword r1rho_prime: The R1rho value for all states in the
absence of exchange.
+ @type r1rho_prime: list of float
+ @keyword dw: The chemical shift differences in ppm for
each spin.
+ @type dw: list of float
+ @keyword pA: The population of state A.
+ @type pA: float
+ @keyword kex: The rate of exchange.
+ @type kex: float
+ @return: The chi-squared value.
+ @rtype: float
+ """
+
+ # Reshape r1rho_prime to per experiment, spin and frequency.
+ self.r1rho_prime_struct[:] = multiply.outer(
r1rho_prime.reshape(self.NE, self.NS, self.NM), self.no_nd_ones )
+
+ # Convert dw from ppm to rad/s. Use the out argument, to pass
directly to structure.
+ multiply( multiply.outer( dw.reshape(1, self.NS), self.nm_no_nd_ones
), self.frqs, out=self.dw_struct )
+
+ # Back calculate the R1rho values.
+ r1rho_MP05(r1rho_prime=self.r1rho_prime_struct,
omega=self.chemical_shifts, offset=self.offset, pA=pA, dw=self.dw_struct,
kex=kex, R1=R1, spin_lock_fields=self.spin_lock_omega1,
spin_lock_fields2=self.spin_lock_omega1_squared, back_calc=self.back_calc)
# Clean the data for all values, which is left over at the end of
arrays.
self.back_calc = self.back_calc*self.disp_struct
@@ -1386,30 +1426,40 @@
params = dot(params, self.scaling_matrix)
# Unpack the parameter values.
- R20 = params[:self.end_index[0]]
+ r1rho_prime = params[:self.end_index[0]]
dw = params[self.end_index[0]:self.end_index[1]]
pA = params[self.end_index[1]]
kex = params[self.end_index[1]+1]
- # Convert dw from ppm to rad/s. Use the out argument, to pass
directly to structure.
- multiply( multiply.outer( dw.reshape(1, self.NS), self.nm_no_nd_ones
), self.frqs, out=self.dw_struct )
-
- # Reshape R20 to per experiment, spin and frequency.
- self.r20_struct[:] = multiply.outer( R20.reshape(self.NE, self.NS,
self.NM), self.no_nd_ones )
-
- # Back calculate the R1rho values.
- r1rho_MP05(r1rho_prime=self.r20_struct, omega=self.chemical_shifts,
offset=self.offset, pA=pA, dw=self.dw_struct, kex=kex, R1=self.r1,
spin_lock_fields=self.spin_lock_omega1,
spin_lock_fields2=self.spin_lock_omega1_squared, back_calc=self.back_calc)
-
- # Clean the data for all values, which is left over at the end of
arrays.
- self.back_calc = self.back_calc*self.disp_struct
-
- # For all missing data points, set the back-calculated value to the
measured values so that it has no effect on the chi-squared value.
- if self.has_missing:
- # Replace with values.
- self.back_calc[self.mask_replace_blank.mask] =
self.values[self.mask_replace_blank.mask]
-
- # Return the total chi-squared value.
- return chi2_rankN(self.values, self.back_calc, self.errors)
+ # Calculate and return the chi-squared value.
+ return self.calc_MP05(R1=self.r1, r1rho_prime=r1rho_prime, dw=dw,
pA=pA, kex=kex)
+
+
+ def func_MP05_fit_r1(self, params):
+ """Target function for the Miloushev and Palmer (2005) R1rho
off-resonance 2-site model, where R1 is fitted.
+
+ @param params: The vector of parameter values.
+ @type params: numpy rank-1 float array
+ @return: The chi-squared value.
+ @rtype: float
+ """
+
+ # Scaling.
+ if self.scaling_flag:
+ params = dot(params, self.scaling_matrix)
+
+ # Unpack the parameter values.
+ r1 = params[:self.end_index[0]]
+ r1rho_prime = params[self.end_index[0]:self.end_index[1]]
+ dw = params[self.end_index[1]:self.end_index[2]]
+ pA = params[self.end_index[2]]
+ kex = params[self.end_index[2]+1]
+
+ # Reshape R1 to per experiment, spin and frequency.
+ self.r1_struct[:] = multiply.outer( r1.reshape(self.NE, self.NS,
self.NM), self.no_nd_ones )
+
+ # Calculate and return the chi-squared value.
+ return self.calc_MP05(R1=self.r1_struct, r1rho_prime=r1rho_prime,
dw=dw, pA=pA, kex=kex)
def func_mmq_CR72(self, params):
r24970 - /branches/R1_fitting/target_functions/relax_disp.py