Author: bugman
Date: Fri Aug 22 11:00:11 2014
New Revision: 25194
URL: http://svn.gna.org/viewcvs/relax?rev=25194&view=rev
Log:
Merged revisions 25188-25191 via svnmerge from
svn+ssh://[email protected]/svn/relax/trunk
........
r25188 | tlinnet | 2014-08-21 19:44:44 +0200 (Thu, 21 Aug 2014) | 10 lines
Inserted intermediate systemtest, to profile R2eff calculation for R1rho.
Systemtest is: Relax_disp.test_bug_9999_slow_r1rho_r2eff_error_with_mc
This systemtest actually fails, if one tries to do a Grid Search.
This is related to the R2eff values stored as dictionary, and
pipe_control.minimise.grid_setup() will fail.
The function 'isNaN(values[i])' cannot handle dictionary.
........
r25189 | tlinnet | 2014-08-21 22:57:45 +0200 (Thu, 21 Aug 2014) | 12 lines
Modified intermediate systemtest:
Relax_disp.test_bug_9999_slow_r1rho_r2eff_error_with_mc
to see if the initial Grid Search for 'i0' and 'R2eff' estimation can be
skipped.
This is done by converting the exponential curve, to a linear curve, and
calculate
the best parameters by a line of best fit by least squares.
This seems like a promising method as an initial estimator of 'i0' and
'r2eff'.
For 500 to 2000 Monte-Carlo simulations, this could have an influence on the
timings,
as all grid searchs could be skipped.
........
r25190 | tlinnet | 2014-08-22 00:37:46 +0200 (Fri, 22 Aug 2014) | 3 lines
Modified systemtest test_bug_9999_slow_r1rho_r2eff_error_with_mc to save data
arrays.
This is to prepare a profiling script.
........
r25191 | tlinnet | 2014-08-22 00:37:49 +0200 (Fri, 22 Aug 2014) | 1 line
Added start script with basic data for profiling the relax curve fit.
........
Added:
branches/frame_order_cleanup/test_suite/shared_data/curve_fitting/profiling/
- copied from r25191,
trunk/test_suite/shared_data/curve_fitting/profiling/
Modified:
branches/frame_order_cleanup/ (props changed)
branches/frame_order_cleanup/test_suite/system_tests/relax_disp.py
Propchange: branches/frame_order_cleanup/
------------------------------------------------------------------------------
--- svnmerge-integrated (original)
+++ svnmerge-integrated Fri Aug 22 11:00:11 2014
@@ -1 +1 @@
-/trunk:1-25186
+/trunk:1-25186,25188-25191
Modified: branches/frame_order_cleanup/test_suite/system_tests/relax_disp.py
URL:
http://svn.gna.org/viewcvs/relax/branches/frame_order_cleanup/test_suite/system_tests/relax_disp.py?rev=25194&r1=25193&r2=25194&view=diff
==============================================================================
--- branches/frame_order_cleanup/test_suite/system_tests/relax_disp.py
(original)
+++ branches/frame_order_cleanup/test_suite/system_tests/relax_disp.py Fri Aug
22 11:00:11 2014
@@ -23,7 +23,7 @@
# Python module imports.
from os import F_OK, access, getcwd, path, sep
-from numpy import array, median
+from numpy import array, exp, median, log, save, sum, zeros
import re, math
from tempfile import mkdtemp
@@ -35,7 +35,7 @@
from lib.io import get_file_path
from pipe_control.mol_res_spin import generate_spin_string, return_spin,
spin_loop
from specific_analyses.relax_disp.checks import check_missing_r1
-from specific_analyses.relax_disp.data import generate_r20_key,
get_curve_type, has_r1rho_exp_type, loop_exp_frq, loop_exp_frq_offset_point,
return_grace_file_name_ini, return_param_key_from_data
+from specific_analyses.relax_disp.data import average_intensity,
generate_r20_key, get_curve_type, has_exponential_exp_type, has_r1rho_exp_type,
loop_exp_frq, loop_exp_frq_offset_point, loop_exp_frq_offset_point_time,
loop_time, return_grace_file_name_ini, return_param_key_from_data
from specific_analyses.relax_disp.data import INTERPOLATE_DISP,
INTERPOLATE_OFFSET, X_AXIS_DISP, X_AXIS_W_EFF, X_AXIS_THETA, Y_AXIS_R2_R1RHO,
Y_AXIS_R2_EFF
from specific_analyses.relax_disp.model import models_info, nesting_param
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, EXP_TYPE_R1RHO,
MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94, MODEL_IT99,
MODEL_LIST_ANALYTIC_CPMG, MODEL_LIST_FULL, MODEL_LIST_NUMERIC_CPMG, MODEL_LM63,
MODEL_M61, MODEL_M61B, MODEL_MP05, MODEL_NOREX, MODEL_NS_CPMG_2SITE_3D_FULL,
MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_NS_CPMG_2SITE_STAR_FULL,
MODEL_NS_R1RHO_2SITE, MODEL_NS_R1RHO_3SITE, MODEL_NS_R1RHO_3SITE_LINEAR,
MODEL_PARAMS, MODEL_R2EFF, MODEL_TP02, MODEL_TAP03
@@ -158,8 +158,8 @@
# Now loop over the experiments, to set the variables in relax.
exp_ids = []
- for exp in exps:
- sfrq, time_T2, ncycs, r2eff_errs = exp
+ for exp_i in exps:
+ sfrq, time_T2, ncycs, r2eff_errs = exp_i
exp_id = 'CPMG_%3.1f' % (sfrq/1E6)
exp_ids.append(exp_id)
@@ -193,8 +193,8 @@
# Now read data in.
for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True):
exp_id = exp_ids[mi]
- exp = exps[mi]
- sfrq, time_T2, ncycs, r2eff_errs = exp
+ exp_i = exps[mi]
+ sfrq, time_T2, ncycs, r2eff_errs = exp_i
# Then loop over the spins.
for res_name, res_num, spin_name, params in spins:
@@ -1352,6 +1352,236 @@
# Assert that the number of columns is equal, plus 1 for "#".
self.assertEqual(nr_split_header, len(line_split_val) + 1)
+
+
+ def test_bug_9999_slow_r1rho_r2eff_error_with_mc(self):
+ """Catch U{bug #9999<https://gna.org/bugs/?9999>}, The slow
optimisation of R1rho R2eff error estimation with Monte Carlo simulations."""
+
+ # Define path to data
+ prev_data_path = status.install_path +
sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'
+sep+ "check_graphs" +sep+ "mc_2000" +sep+ "R2eff"
+
+ # Read data.
+ self.interpreter.results.read(prev_data_path + sep + 'results')
+
+ # Now count number
+ graph_nr = 1
+ for exp_type, frq, offset, point in
loop_exp_frq_offset_point(return_indices=False):
+ print("\nGraph nr %i" % graph_nr)
+ for time in loop_time(exp_type=exp_type, frq=frq, offset=offset,
point=point):
+ print(exp_type, frq, offset, point, time)
+ graph_nr += 1
+
+ ## Possibly do an error analysis.
+
+ # Check if intensity errors have already been calculated by the user.
+ precalc = True
+ for spin in spin_loop(skip_desel=True):
+ # No structure.
+ if not hasattr(spin, 'peak_intensity_err'):
+ precalc = False
+ break
+
+ # Determine if a spectrum ID is missing from the list.
+ for id in cdp.spectrum_ids:
+ if id not in spin.peak_intensity_err:
+ precalc = False
+ break
+
+ # Skip.
+ if precalc:
+ print("Skipping the error analysis as it has already been
performed.")
+
+ else:
+ # Loop over the spectrometer frequencies.
+ for frq in loop_frq():
+ # Generate a list of spectrum IDs matching the frequency.
+ ids = []
+ for id in cdp.spectrum_ids:
+ # Check that the spectrometer frequency matches.
+ match_frq = True
+ if frq != None and cdp.spectrometer_frq[id] != frq:
+ match_frq = False
+
+ # Add the ID.
+ if match_frq:
+ ids.append(id)
+
+ # Run the error analysis on the subset.
+ self.interpreter.spectrum.error_analysis(subset=ids)
+
+ print("has_exponential_exp_type:", has_exponential_exp_type())
+
+ model = 'R2eff'
+ self.interpreter.relax_disp.select_model(model)
+
+ for spin, spin_id in spin_loop(return_id=True, skip_desel=True):
+ #delattr(spin, 'r2eff')
+ #delattr(spin, 'r2eff_err')
+ #delattr(spin, 'i0')
+ #delattr(spin, 'i0_err')
+ setattr(spin, 'r2eff', {})
+ setattr(spin, 'r2eff_err', {})
+ setattr(spin, 'i0', {})
+ setattr(spin, 'i0_err', {})
+
+ # Do Grid Search
+ self.interpreter.minimise.grid_search(lower=None, upper=None, inc=21,
constraints=True, verbosity=1)
+
+ # Start dic.
+ my_dic = {}
+
+ # Define counter for maximum elements in the numpy array list
+ NE = 0
+ NS = 1
+ NM = 0
+ NO = 0
+ ND = 0
+ NT = 0
+
+ for exp_type, frq, offset, point, ei, mi, oi, di in
loop_exp_frq_offset_point(return_indices=True):
+ # Save to counter.
+ if ei > NE:
+ NE = ei
+ if mi > NM:
+ NM = mi
+ if oi > NO:
+ NO = oi
+ if di > ND:
+ ND = di
+
+ for time, ti in loop_time(exp_type=exp_type, frq=frq,
offset=offset, point=point, return_indices=True):
+ # Save to counter.
+ if ti > NT:
+ NT = ti
+
+ # Add 1 to counter, since index start from 0.
+ NE = NE + 1
+ NM = NM + 1
+ NO = NO + 1
+ ND = ND + 1
+ NT = NT + 1
+
+ # Make data array.
+ values_arr = zeros([NE, NS, NM, NO, ND, NT])
+ errors_arr = zeros([NE, NS, NM, NO, ND, NT])
+ times_arr = zeros([NE, NS, NM, NO, ND, NT])
+ struct_arr = zeros([NE, NS, NM, NO, ND, NT])
+ param_key_list = []
+
+
+ # Loop over each spectrometer frequency and dispersion point.
+ for cur_spin, mol_name, resi, resn, spin_id in
spin_loop(full_info=True, return_id=True, skip_desel=True):
+ # Add key to dic.
+ my_dic[spin_id] = {}
+
+ # Generate spin string.
+ spin_string = generate_spin_string(spin=cur_spin,
mol_name=mol_name, res_num=resi, res_name=resn)
+
+ # Loop over the parameters.
+ #print("Grid optimised parameters for spin: %s" % (spin_string))
+
+ for exp_type, frq, offset, point, ei, mi, oi, di in
loop_exp_frq_offset_point(return_indices=True):
+ # Generate the param_key.
+ param_key = return_param_key_from_data(exp_type=exp_type,
frq=frq, offset=offset, point=point)
+
+ # Append key.
+ param_key_list.append(param_key)
+
+ # Add key to dic.
+ my_dic[spin_id][param_key] = {}
+
+ # Get the value.
+ R2eff_value = getattr(cur_spin, 'r2eff')[param_key]
+ i0_value = getattr(cur_spin, 'i0')[param_key]
+
+ # Save to dic.
+ my_dic[spin_id][param_key]['R2eff_value_grid'] = R2eff_value
+ my_dic[spin_id][param_key]['i0_value_grid'] = i0_value
+
+ ## Now try do a line of best fit by least squares.
+ # The peak intensities, errors and times.
+ values = []
+ errors = []
+ times = []
+ for time, ti in loop_time(exp_type=exp_type, frq=frq,
offset=offset, point=point, return_indices=True):
+ value = average_intensity(spin=cur_spin,
exp_type=exp_type, frq=frq, offset=offset, point=point, time=time,
sim_index=None)
+ values.append(value)
+
+ error = average_intensity(spin=cur_spin,
exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True)
+ errors.append(error)
+ times.append(time)
+
+ # Save to numpy arrays.
+ values_arr[ei, 0, mi, oi, di, ti] = value
+ errors_arr[ei, 0, mi, oi, di, ti] = error
+ times_arr[ei, 0, mi, oi, di, ti] = time
+ struct_arr[ei, 0, mi, oi, di, ti] = 1.0
+
+ # y= A exp(x * k)
+ # w[i] = ln(y[i])
+ # int[i] = i0 * exp( - times[i] * r2eff);
+ w = log(array(values))
+ x = - array(times)
+ n = len(times)
+
+ b = (sum(x*w) - 1./n * sum(x) * sum(w) ) / ( sum(x**2) - 1./n
* (sum(x))**2 )
+ a = 1./n * sum(w) - b * 1./n * sum(x)
+ R2eff_est = b
+ i0_est = exp(a)
+
+ my_dic[spin_id][param_key]['R2eff_est'] = R2eff_est
+ my_dic[spin_id][param_key]['i0_est'] = i0_est
+
+ # Print value.
+ #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:",
'R2eff', "Value : Estimated:", R2eff_value, R2eff_est))
+ #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'i0',
"Value: Estimated:", i0_value, i0_est))
+
+
+ # Do minimisation.
+ set_func_tol = 1e-25
+ set_max_iter = int(1e7)
+ self.interpreter.minimise.execute(min_algor='simplex',
func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True,
verbosity=1)
+
+ # Loop over each spectrometer frequency and dispersion point.
+ for cur_spin, mol_name, resi, resn, spin_id in
spin_loop(full_info=True, return_id=True, skip_desel=True):
+ # Generate spin string.
+ spin_string = generate_spin_string(spin=cur_spin,
mol_name=mol_name, res_num=resi, res_name=resn)
+
+ # Loop over the parameters.
+ print("Optimised parameters for spin: %s" % (spin_string))
+
+ for exp_type, frq, offset, point in loop_exp_frq_offset_point():
+ # Generate the param_key.
+ param_key = return_param_key_from_data(exp_type=exp_type,
frq=frq, offset=offset, point=point)
+
+ # Get the value.
+ R2eff_value = getattr(cur_spin, 'r2eff')[param_key]
+ i0_value = getattr(cur_spin, 'i0')[param_key]
+
+ # Extract from dic.
+ R2eff_value_grid =
my_dic[spin_id][param_key]['R2eff_value_grid']
+ i0_value_grid = my_dic[spin_id][param_key]['i0_value_grid']
+ R2eff_est = my_dic[spin_id][param_key]['R2eff_est']
+ i0_est = my_dic[spin_id][param_key]['i0_est']
+
+ # Print value.
+ #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:",
'R2eff', "Value : Estimated:", R2eff_value, R2eff_est))
+ #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'i0',
"Value: Estimated:", i0_value, i0_est))
+
+ print("%-10s %-6s %-6s %3.1f : %3.1f: %3.1f" % ("Parameter:",
'R2eff', "Grid : Min : Estimated:", R2eff_value_grid, R2eff_value, R2eff_est))
+ print("%-10s %-6s %-6s %3.1f : %3.1f: %3.1f" % ("Parameter:",
'i0', "Grid : Min : Estimated:", i0_value_grid, i0_value, i0_est))
+
+ print(NE, NS, NM, NO, ND, NT)
+ for param_key in param_key_list:
+ print(" '%s'," % param_key)
+ print(values_arr.shape)
+
+ # Save arrays to profiling.
+ data_path = status.install_path +
sep+'test_suite'+sep+'shared_data'+sep+'curve_fitting'+sep+'profiling'+sep
+ #save(data_path + "values_arr", values_arr)
+ #save(data_path + "errors_arr", errors_arr)
+ #save(data_path + "times_arr", times_arr)
+ #save(data_path + "struct_arr", struct_arr)
def test_check_missing_r1(self):
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