Author: bugman
Date: Mon Oct 21 15:34:14 2013
New Revision: 21202
URL: http://svn.gna.org/viewcvs/relax?rev=21202&view=rev
Log:
The specific API calculate_r2eff() method for the dispersion analysis is now
private.
This is not part of the API, so it must be made private for the test suite to
pass.
Modified:
branches/relax_disp/specific_analyses/relax_disp/api.py
Modified: branches/relax_disp/specific_analyses/relax_disp/api.py
URL:
http://svn.gna.org/viewcvs/relax/branches/relax_disp/specific_analyses/relax_disp/api.py?rev=21202&r1=21201&r2=21202&view=diff
==============================================================================
--- branches/relax_disp/specific_analyses/relax_disp/api.py (original)
+++ branches/relax_disp/specific_analyses/relax_disp/api.py Mon Oct 21
15:34:14 2013
@@ -223,6 +223,65 @@
return results
+ def _calculate_r2eff(self):
+ """Calculate the R2eff values for fixed relaxation time period
data."""
+
+ # Data checks.
+ check_exp_type()
+ check_disp_points()
+ check_exp_type_fixed_time()
+
+ # Printouts.
+ print("Calculating the R2eff/R1rho values for fixed relaxation time
period data.")
+
+ # Loop over the spins.
+ for spin, spin_id in spin_loop(return_id=True, skip_desel=True):
+ # Spin ID printout.
+ print("Spin '%s'." % spin_id)
+
+ # Skip spins which have no data.
+ if not hasattr(spin, 'intensities'):
+ continue
+
+ # Initialise the data structures.
+ if not hasattr(spin, 'r2eff'):
+ spin.r2eff = {}
+ if not hasattr(spin, 'r2eff_err'):
+ spin.r2eff_err = {}
+
+ # Loop over all the data.
+ for exp_type, frq, point, time in loop_exp_frq_point_time():
+ # The three keys.
+ ref_keys = find_intensity_keys(exp_type=exp_type, frq=frq,
point=None, time=time)
+ int_keys = find_intensity_keys(exp_type=exp_type, frq=frq,
point=point, time=time)
+ param_key = return_param_key_from_data(frq=frq, point=point)
+
+ # Check for missing data.
+ missing = False
+ for i in range(len(ref_keys)):
+ if ref_keys[i] not in spin.intensities:
+ missing = True
+ for i in range(len(int_keys)):
+ if int_keys[i] not in spin.intensities:
+ missing = True
+ if missing:
+ continue
+
+ # Average the reference intensity data and errors.
+ ref_intensity = average_intensity(spin=spin,
exp_type=exp_type, frq=frq, point=None, time=time)
+ ref_intensity_err = average_intensity(spin=spin,
exp_type=exp_type, frq=frq, point=None, time=time, error=True)
+
+ # Average the intensity data and errors.
+ intensity = average_intensity(spin=spin, exp_type=exp_type,
frq=frq, point=point, time=time)
+ intensity_err = average_intensity(spin=spin,
exp_type=exp_type, frq=frq, point=point, time=time, error=True)
+
+ # Calculate the R2eff value.
+ spin.r2eff[param_key] =
calc_two_point_r2eff(relax_time=time, I_ref=ref_intensity, I=intensity)
+
+ # Calculate the R2eff error.
+ spin.r2eff_err[param_key] =
calc_two_point_r2eff_err(relax_time=time, I_ref=ref_intensity, I=intensity,
I_ref_err=ref_intensity_err, I_err=intensity_err)
+
+
def _cluster(self, cluster_id=None, spin_id=None):
"""Define spin clustering.
@@ -733,65 +792,6 @@
self._back_calc_r2eff(spin=spin, spin_id=spin_id)
- def calculate_r2eff(self):
- """Calculate the R2eff values for fixed relaxation time period
data."""
-
- # Data checks.
- check_exp_type()
- check_disp_points()
- check_exp_type_fixed_time()
-
- # Printouts.
- print("Calculating the R2eff/R1rho values for fixed relaxation time
period data.")
-
- # Loop over the spins.
- for spin, spin_id in spin_loop(return_id=True, skip_desel=True):
- # Spin ID printout.
- print("Spin '%s'." % spin_id)
-
- # Skip spins which have no data.
- if not hasattr(spin, 'intensities'):
- continue
-
- # Initialise the data structures.
- if not hasattr(spin, 'r2eff'):
- spin.r2eff = {}
- if not hasattr(spin, 'r2eff_err'):
- spin.r2eff_err = {}
-
- # Loop over all the data.
- for exp_type, frq, point, time in loop_exp_frq_point_time():
- # The three keys.
- ref_keys = find_intensity_keys(exp_type=exp_type, frq=frq,
point=None, time=time)
- int_keys = find_intensity_keys(exp_type=exp_type, frq=frq,
point=point, time=time)
- param_key = return_param_key_from_data(frq=frq, point=point)
-
- # Check for missing data.
- missing = False
- for i in range(len(ref_keys)):
- if ref_keys[i] not in spin.intensities:
- missing = True
- for i in range(len(int_keys)):
- if int_keys[i] not in spin.intensities:
- missing = True
- if missing:
- continue
-
- # Average the reference intensity data and errors.
- ref_intensity = average_intensity(spin=spin,
exp_type=exp_type, frq=frq, point=None, time=time)
- ref_intensity_err = average_intensity(spin=spin,
exp_type=exp_type, frq=frq, point=None, time=time, error=True)
-
- # Average the intensity data and errors.
- intensity = average_intensity(spin=spin, exp_type=exp_type,
frq=frq, point=point, time=time)
- intensity_err = average_intensity(spin=spin,
exp_type=exp_type, frq=frq, point=point, time=time, error=True)
-
- # Calculate the R2eff value.
- spin.r2eff[param_key] =
calc_two_point_r2eff(relax_time=time, I_ref=ref_intensity, I=intensity)
-
- # Calculate the R2eff error.
- spin.r2eff_err[param_key] =
calc_two_point_r2eff_err(relax_time=time, I_ref=ref_intensity, I=intensity,
I_ref_err=ref_intensity_err, I_err=intensity_err)
-
-
def constraint_algorithm(self):
"""Return the 'Log barrier' optimisation constraint algorithm.
r21202 - /branches/relax_disp/specific_analyses/relax_disp/api.py