def generate_theta_dic():
# Get the field count
field_count = cdp.spectrometer_frq_count
# Get the spin_lock_field points
spin_lock_nu1 = return_spin_lock_nu1(ref_flag=False)
# Initialize data containers
all_spin_ids = get_spin_ids()
# Containers for only selected spins
cur_spin_ids = []
cur_spins = []
for curspin_id in all_spin_ids:
# Get the spin
curspin = return_spin(spin_id=curspin_id)
# Check if is selected
if curspin.select == True:
cur_spin_ids.append(curspin_id)
cur_spins.append(curspin)
# The offset and R1 data.
chemical_shifts, offsets, tilt_angles, Delta_omega, w_eff = return_offset_data(spins=cur_spins, spin_ids=cur_spin_ids, field_count=field_count, fields=spin_lock_nu1)
# Loop over the index of spins, then exp_type, frq, offset
print("Printing the following")
print("exp_type curspin_id frq offset{ppm} offsets[ei][si][mi][oi]{rad/s} ei mi oi si di cur_spin.chemical_shift{ppm} chemical_shifts[ei][si][mi]{rad/s} spin_lock_nu1{Hz} tilt_angles[ei][si][mi][oi]{rad}")
for si in range(len(cur_spin_ids)):
theta_spin_dic = dict()
curspin_id = cur_spin_ids[si]
cur_spin = cur_spins[si]
for exp_type, frq, offset, ei, mi, oi in loop_exp_frq_offset(return_indices=True):
# Loop over the dispersion points.
spin_lock_fields = spin_lock_nu1[ei][mi][oi]
for di in range(len(spin_lock_fields)):
print("%-8s %-10s %11.1f %8.4f %12.5f %i %i %i %i %i %7.3f %12.5f %12.5f %12.5f"%(exp_type, curspin_id, frq, offset, offsets[ei][si][mi][oi], ei, mi, oi, si, di, cur_spin.chemical_shift, chemical_shifts[ei][si][mi], spin_lock_fields[di], tilt_angles[ei][si][mi][oi][di]))
dic_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=spin_lock_fields[di])
theta_spin_dic["%s"%(dic_key)] = tilt_angles[ei][si][mi][oi][di]
# Store the data
cur_spin.theta = theta_spin_dic
print("\nThe theta data now resides in")
for curspin, mol_name, res_num, res_name, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True):
spin_index = find_index(selection=spin_id, global_index=False)
print("%s cdp.mol[%i].res[%i].spin[%i].theta"%(spin_id, spin_index[0], spin_index[1], spin_index[2]))
def generate_theta_dic():
# Get the field count
field_count = cdp.spectrometer_frq_count
# Get the spin_lock_field points
spin_lock_nu1 = return_spin_lock_nu1(ref_flag=False)
# Initialize data containers
all_spin_ids = get_spin_ids()
# Containers for only selected spins
cur_spin_ids = []
cur_spins = []
for curspin_id in all_spin_ids:
# Get the spin
curspin = return_spin(curspin_id)
# Check if is selected
if curspin.select == True:
cur_spin_ids.append(curspin_id)
cur_spins.append(curspin)
# The offset and R1 data.
chemical_shifts, offsets, tilt_angles, Delta_omega, w_eff = return_offset_data(spins=cur_spins, spin_ids=cur_spin_ids, field_count=field_count, fields=spin_lock_nu1)
# Loop over the index of spins, then exp_type, frq, offset
print("Printing the following")
print("exp_type curspin_id frq offset{ppm} offsets[ei][si][mi][oi]{rad/s} ei mi oi si di cur_spin.chemical_shift{ppm} chemical_shifts[ei][si][mi]{rad/s} spin_lock_nu1{Hz} tilt_angles[ei][si][mi][oi]{rad}")
for si in range(len(cur_spin_ids)):
theta_spin_dic = dict()
curspin_id = cur_spin_ids[si]
cur_spin = cur_spins[si]
for exp_type, frq, offset, ei, mi, oi in loop_exp_frq_offset(return_indices=True):
# Loop over the dispersion points.
spin_lock_fields = spin_lock_nu1[ei][mi][oi]
for di in range(len(spin_lock_fields)):
print("%-8s %-10s %11.1f %8.4f %12.5f %i %i %i %i %i %7.3f %12.5f %12.5f %12.5f"%(exp_type, curspin_id, frq, offset, offsets[ei][si][mi][oi], ei, mi, oi, si, di, cur_spin.chemical_shift, chemical_shifts[ei][si][mi], spin_lock_fields[di], tilt_angles[ei][si][mi][oi][di]))
dic_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=spin_lock_fields[di])
theta_spin_dic["%s"%(dic_key)] = tilt_angles[ei][si][mi][oi][di]
# Store the data
cur_spin.theta = theta_spin_dic
print("\nThe theta data now resides in")
for curspin, mol_name, res_num, res_name, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True):
spin_index = find_index(selection=spin_id, global_index=False)
print("%s cdp.mol[%i].res[%i].spin[%i].theta"%(spin_id, spin_index[0], spin_index[1], spin_index[2]))
def back_calc(ri_id=None, ri_type=None, frq=None):
"""Back calculate the relaxation data.
If no relaxation data currently exists, then the ri_id, ri_type, and frq args are required.
@keyword ri_id: The relaxation data ID string. If not given, all relaxation data will be back calculated.
@type ri_id: None or str
@keyword ri_type: The relaxation data type. This should be one of 'R1', 'R2', or 'NOE'.
@type ri_type: None or str
@keyword frq: The spectrometer proton frequency in Hz.
@type frq: None or float
"""
# Test if the current pipe exists.
check_pipe()
# Test if sequence data is loaded.
if not exists_mol_res_spin_data():
raise RelaxNoSequenceError
# Check that ri_type and frq are supplied if no relaxation data exists.
if ri_id and (not hasattr(cdp, 'ri_ids') or ri_id
not in cdp.ri_ids) and (ri_type == None or frq == None):
raise RelaxError(
"The 'ri_type' and 'frq' arguments must be supplied as no relaxation data corresponding to '%s' exists."
% ri_id)
# Check if the type is valid.
if ri_type and ri_type not in VALID_TYPES:
raise RelaxError("The relaxation data type '%s' must be one of %s." %
(ri_type, VALID_TYPES))
# Frequency checks.
frequency_checks(frq)
# Initialise the global data for the current pipe if necessary.
if not hasattr(cdp, 'ri_type'):
cdp.ri_type = {}
if not hasattr(cdp, 'ri_ids'):
cdp.ri_ids = []
# Update the global data if needed.
if ri_id and ri_id not in cdp.ri_ids:
cdp.ri_ids.append(ri_id)
cdp.ri_type[ri_id] = ri_type
set_frequency(id=ri_id, frq=frq)
# The specific analysis API object.
api = return_api()
# The IDs to loop over.
if ri_id == None:
ri_ids = cdp.ri_ids
else:
ri_ids = [ri_id]
# The data types.
if ri_type == None:
ri_types = cdp.ri_type
else:
ri_types = {ri_id: ri_type}
# The frequencies.
if frq == None:
frqs = cdp.spectrometer_frq
else:
frqs = {ri_id: frq}
# Loop over the spins.
for spin, spin_id in spin_loop(return_id=True):
# Skip deselected spins.
if not spin.select:
continue
# The global index.
spin_index = find_index(spin_id)
# Initialise the spin data if necessary.
if not hasattr(spin, 'ri_data_bc'):
spin.ri_data_bc = {}
# Back-calculate the relaxation value.
for ri_id in ri_ids:
spin.ri_data_bc[ri_id] = api.back_calc_ri(spin_index=spin_index,
ri_id=ri_id,
ri_type=ri_types[ri_id],
frq=frqs[ri_id])
def back_calc(ri_id=None, ri_type=None, frq=None):
"""Back calculate the relaxation data.
If no relaxation data currently exists, then the ri_id, ri_type, and frq args are required.
@keyword ri_id: The relaxation data ID string. If not given, all relaxation data will be back calculated.
@type ri_id: None or str
@keyword ri_type: The relaxation data type. This should be one of 'R1', 'R2', or 'NOE'.
@type ri_type: None or str
@keyword frq: The spectrometer proton frequency in Hz.
@type frq: None or float
"""
# Test if the current pipe exists.
pipes.test()
# Test if sequence data is loaded.
if not exists_mol_res_spin_data():
raise RelaxNoSequenceError
# Check that ri_type and frq are supplied if no relaxation data exists.
if ri_id and (not hasattr(cdp, 'ri_ids') or ri_id not in cdp.ri_ids) and (ri_type == None or frq == None):
raise RelaxError("The 'ri_type' and 'frq' arguments must be supplied as no relaxation data corresponding to '%s' exists." % ri_id)
# Check if the type is valid.
if ri_type and ri_type not in VALID_TYPES:
raise RelaxError("The relaxation data type '%s' must be one of %s." % (ri_type, VALID_TYPES))
# Frequency checks.
frequency_checks(frq)
# Initialise the global data for the current pipe if necessary.
if not hasattr(cdp, 'ri_type'):
cdp.ri_type = {}
if not hasattr(cdp, 'ri_ids'):
cdp.ri_ids = []
# Update the global data if needed.
if ri_id and ri_id not in cdp.ri_ids:
cdp.ri_ids.append(ri_id)
cdp.ri_type[ri_id] = ri_type
set_frequency(id=ri_id, frq=frq)
# Specific Ri back calculate function setup.
back_calculate = specific_analyses.setup.get_specific_fn('back_calc_ri', pipes.get_type())
# The IDs to loop over.
if ri_id == None:
ri_ids = cdp.ri_ids
else:
ri_ids = [ri_id]
# The data types.
if ri_type == None:
ri_types = cdp.ri_type
else:
ri_types = {ri_id: ri_type}
# The frequencies.
if frq == None:
frqs = cdp.spectrometer_frq
else:
frqs = {ri_id: frq}
# Loop over the spins.
for spin, spin_id in spin_loop(return_id=True):
# Skip deselected spins.
if not spin.select:
continue
# The global index.
spin_index = find_index(spin_id)
# Initialise the spin data if necessary.
if not hasattr(spin, 'ri_data_bc'):
spin.ri_data_bc = {}
# Back-calculate the relaxation value.
for ri_id in ri_ids:
spin.ri_data_bc[ri_id] = back_calculate(spin_index=spin_index, ri_id=ri_id, ri_type=ri_types[ri_id], frq=frqs[ri_id])
