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#exps = [exp_1, exp_2] #exps = [exp_1]
print cur_id
#print cur_spin.model, cur_spin.name, cur_spin.isotope
#if ds.print_res: print as # Now set the parameters.("For spin: '%s'"%cur_spin_id)
no edit summary
# Collect all exps
# Add more spins here.
spins = [
['Ala', 1, 'N', {'r2': {r20_key_1: 2025.0, r20_key_2: 2024.0}, 'r2a': {r20_key_1: 2025.0, r20_key_2: 2024.0}, 'r2b': {r20_key_1: 2025.0, r20_key_2: 2024.0}, 'kex': 2200.0, 'pA': 0.993, 'dw': 1.5} ] #['Ala', 2, 'N', {'r2': {r20_key_1: 1315.0, r20_key_2: 14.50}, 'r2a': {r20_key_1: 1315.0, r20_key_2: 14.50}, 'r2b': {r20_key_1: 1315.0, r20_key_2: 14.50}, 'kex': 2200.0, 'pA': 0.993, 'dw': 1.5} ]
]
if not hasattr(ds, 'opendx'):
ds.opendx = True
if not hasattr(ds, 'dx_inc'):
ds.dx_inc = 5020if not hasattr(ds, 'dx_params'): ds.dx_params = ['dw', 'pA', 'kex']
# The set r2eff err.
# Create the data pipe.
ds.pipe_name = 'base pipe'ds.pipe_type = 'relax_disp'ds.pipe_bundle = 'relax_disp'ds.pipe_name_r2eff = "%s_%s_R2eff"%(model_create, ds.pipe_name)pipe.create(pipe_name=ds.pipe_name, pipe_type=ds.pipe_type, bundle = ds.pipe_bundle)
# Generate the sequence.
nu_cpmg = ncyc / time_T2
cur_id = '%s_%.1f' % (exp_id, nu_cpmg)
ids.append(cur_id)
## Now prepare to calculate the synthetic R2eff values.
pipe.copy(pipe_from=ds.pipe_name, pipe_to=ds.pipe_name_r2eff, bundle_to = ds.pipe_bundle)pipe.switch(pipe_name=ds.pipe_name_r2eff)
# Then select model.
relax_disp.select_model(model=model_create)
# First loop over the defined spins and set the model parameters.for i in range(len(cur_spins)): res_name, res_num, spin_name, params in = cur_spins:[i]
cur_spin_id = ":%i@%s"%(res_num, spin_name)
cur_spin = return_spin(cur_spin_id)
for mo_param in cur_spin.params:
# The R2 is a dictionary, depending on spectrometer frequency.
if isinstance(getattr(cur_spin, mo_param), dict):
set_r2 = params[mo_param]
for key, val in set_r2getattr(cur_spin, mo_param).items():
# Update value to float
set_r2.update({ key : float(val) })
print (cur_spin.model, res_name, cur_spin_id, mo_param, key, float(val)) # Set it back
setattr(cur_spin, mo_param, set_r2)
else:
setattr(cur_spin, mo_param, float(params[mo_param]))
after = getattr(cur_spin, mo_param)
print (cur_spin.model, res_name, cur_spin_id, mo_param, before)
## Now doing the back calculation of R2eff values.
print("Did following number of iterations: %i"%i)
# Do a dx map.# To map the hypersurface of chi2, when altering kex, dw and pA.if ds.opendx: # First switch pipe, since dx.map will go through parameters and end up a "bad" place. :-) pipe_name_MODEL_MAP = "%s_%s_map"%(pipe_name, model_analyse) pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_MODEL_MAP, bundle_to = pipe_bundle) pipe.switch(pipe_name=pipe_name_MODEL_MAP) # Copy R2eff, but not the original parameters value.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL_MAP, param='r2eff') # Then select model. relax_disp.select_model(model=model_analyse) # Define dx parameters dx_params = ['dw', 'pA', 'kex'] for res_name, res_num, spin_name, params in cur_spins: cur_spin_id = ":%i@%s"%(res_num, spin_name) cur_spin = return_spin(cur_spin_id) dx_point = [] # Now get the parameters. for dx_param in dx_params: set_value = float(params[dx_param ]) dx_point.append(set_value) print("Params for dx map is") print(dx_params) print("Point param for dx map is") print(dx_point) file_name_map = "map%s" % (cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_')) file_name_point = "point%s" % (cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_')) dx.map(params=dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=ds.dx_inc, lower=None, upper=None, axis_incs=5, file_prefix=file_name_map, dir=ds.resdir, point=dx_point, point_file=file_name_point, remap=None) #vp_exec: A flag specifying whether to execute the visual program automatically at start-up. #dx.execute(file_prefix=file_name, dir=ds.resdir, dx_exe='dx', vp_exec=True) # Now do fitting.
# Change pipe.
ds.pipe_name_MODEL = "%s_%s"%(ds.pipe_name, model_analyse)pipe.copy(pipe_from=ds.pipe_name, pipe_to=ds.pipe_name_MODEL, bundle_to = ds.pipe_bundle)pipe.switch(pipe_name=ds.pipe_name_MODEL)
# Copy R2eff, but not the original parameters
value.copy(pipe_from=ds.pipe_name_r2eff, pipe_to=ds.pipe_name_MODEL, param='r2eff')
# Then select model.
if ds.do_cluster:
# Change pipe.
ds.pipe_name_MODEL_CLUSTER = "%s_%s_CLUSTER"%(ds.pipe_name, model_create) pipe.copy(pipe_from=ds.pipe_name, pipe_to=ds.pipe_name_MODEL_CLUSTER) pipe.switch(pipe_name=ds.pipe_name_MODEL_CLUSTER)
# Copy R2eff, but not the original parameters
value.copy(pipe_from=ds.pipe_name_r2eff, pipe_to=ds.pipe_name_MODEL_CLUSTER, param='r2eff')
# Then select model.
# Copy the parameters from before.
relax_disp.parameter_copy(pipe_from=ds.pipe_name_MODEL, pipe_to=ds.pipe_name_MODEL_CLUSTER)
# Now minimise.
print("########################\n")
# Looping over data, to collect the results.
# Define which dx_params to collect for.
ds.dx_set_val = list(range(len(ds.dx_params)))
ds.dx_clust_val = list(range(len(ds.dx_params)))
for i in range(len(cur_spins)):
res_name, res_num, spin_name, params = cur_spins[i]
cur_spin = return_spin(cur_spin_id)
# Fetch data.
grid_params = ds.grid_results[i][3]
min_params = ds.min_results[i][3]
clust_params = ds.clust_results[i][3]
# Now read the parameters.
if ds.print_res:
print("For spin: '%s'"%cur_spin_id)
print("WARNING: %s Have relative change above %.2f, and is %.4f."%(mo_param, ds.rel_change, rel_change))
print("###################################\n")
# Store to dx map.
if mo_param in ds.dx_params:
ds.dx_set_val[ds.dx_params.index(mo_param)] = set_val
ds.dx_clust_val[ds.dx_params.index(mo_param)] = clust_val
## Do a dx map.
# To map the hypersurface of chi2, when altering kex, dw and pA.
if ds.opendx:
# First switch pipe, since dx.map will go through parameters and end up a "bad" place. :-)
ds.pipe_name_MODEL_MAP = "%s_%s_map"%(ds.pipe_name, model_analyse)
pipe.copy(pipe_from=ds.pipe_name , pipe_to=ds.pipe_name_MODEL_MAP, bundle_to = ds.pipe_bundle)
pipe.switch(pipe_name=ds.pipe_name_MODEL_MAP)
# Copy R2eff, but not the original parameters
value.copy(pipe_from=ds.pipe_name_r2eff, pipe_to=ds.pipe_name_MODEL_MAP, param='r2eff')
# Then select model.
relax_disp.select_model(model=model_analyse)
# First loop over the defined spins and set the model parameters.
for i in range(len(cur_spins)):
res_name, res_num, spin_name, params = cur_spins[i]
cur_spin_id = ":%i@%s"%(res_num, spin_name)
cur_spin = return_spin(cur_spin_id)
if ds.print_res:
print("Params for dx map is")
print(ds.dx_params)
print("Point param for dx map is")
print(ds.dx_set_val)
cur_model = model_analyse.replace(' ', '_')
file_name_map = "%s_map%s" % (cur_model, cur_spin_id.replace('#', '_').replace(':', '_').replace('@', '_'))
file_name_point = "%s_point%s" % (cur_model, cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_'))
dx.map(params=ds.dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=ds.dx_inc, lower=None, upper=None, axis_incs=10, file_prefix=file_name_map, dir=ds.resdir, point=[ds.dx_set_val, ds.dx_clust_val], point_file=file_name_point, remap=None)
#vp_exec: A flag specifying whether to execute the visual program automatically at start-up.
#dx.execute(file_prefix=file_name, dir=ds.resdir, dx_exe='dx', vp_exec=True)
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