"""Set up the data pipe for testing optimisation against tm4 relaxation data.""" # relax module imports. from opt_tm_fns import create_sequence, opt_and_check, setup_data # The model-free parameters. tm = [2e-9, 10e-9, 21e-9] s2 = [0.2, 0.8, 0.95] te = [2e-12, 40e-12] rex = [0.5, 4] # Create the sequence. create_sequence(len(tm) * len(s2) * len(te) * len(rex)) # Set up the data. setup_data(dir='tm4_grid') # Residue index. res_index = 0 # Loop over the parameters. for rex_index in range(len(rex)): for te_index in range(len(te)): for s2_index in range(len(s2)): for tm_index in range(len(tm)): # Optimise and validate. opt_and_check(spin=cdp.mol[0].res[res_index].spin[0], tm=tm[tm_index], s2=s2[s2_index], te=te[te_index], rex=rex[rex_index])
# relax module imports. from opt_tm_fns import create_sequence, opt_and_check, setup_data # The model-free parameters. tm = [10e-9] s2 = [0.2, 0.8] s2f = [0.7, 0.8] tf = [2e-12, 40e-12] ts = [2e-11, 1.8e-9] rex = [0.5, 4] # Create the sequence. create_sequence(len(tm) * len(s2) * len(s2f) * len(tf) * len(ts) * len(rex)) # Set up the data. setup_data(dir='tm8_grid') # Residue index. res_index = 0 # Loop over the parameters. for rex_index in range(len(rex)): for ts_index in range(len(ts)): for tf_index in range(len(tf)): for s2f_index in range(len(s2f)): for s2_index in range(len(s2)): for tm_index in range(len(tm)): # Optimise and validate. opt_and_check(spin=cdp.mol[0].res[res_index].spin[0], tm=tm[tm_index], s2=s2[s2_index],
# # ############################################################################### """Set up the data pipe for testing optimisation against tm9 relaxation data.""" # relax module imports. from opt_tm_fns import create_sequence, opt_and_check, setup_data # The model-free parameters. tm = [2e-9, 10e-9, 80e-9] rex = [0.5, 4, 20] # Create the sequence. create_sequence(len(tm)*len(rex)) # Set up the data. setup_data(dir='tm9_grid') # Residue index. res_index = 0 # Loop over the parameters. for rex_index in range(len(rex)): for tm_index in range(len(tm)): # Optimise and validate. opt_and_check(spin=cdp.mol[0].res[res_index].spin[0], tm=tm[tm_index], rex=rex[rex_index]) # Increment the residue index. res_index += 1
# You should have received a copy of the GNU General Public License # # along with this program. If not, see <http://www.gnu.org/licenses/>. # # # ############################################################################### """Set up the data pipe for testing optimisation against tm0 relaxation data.""" # relax module imports. from opt_tm_fns import create_sequence, opt_and_check, setup_data # The model-free parameters. tm = [2e-9, 10e-9, 80e-9] # Create the sequence. create_sequence(len(tm)) # Set up the data. setup_data(dir='tm0_grid') # Residue index. res_index = 0 # Loop over tm. for tm_index in range(len(tm)): # Optimise and validate. opt_and_check(spin=cdp.mol[0].res[res_index].spin[0], tm=tm[tm_index]) # Increment the residue index. res_index += 1
# Module docstring. """Set up the data pipe for testing optimisation against tm1 relaxation data.""" # relax module imports. from opt_tm_fns import create_sequence, opt_and_check, setup_data # The model-free parameters. tm = [2e-9, 10e-9, 21e-9] s2 = [0.2, 0.8, 0.95] # Create the sequence. create_sequence(len(tm) * len(s2)) # Set up the data. setup_data(dir='tm1_grid') # Residue index. res_index = 0 # Loop over the parameters. for s2_index in range(3): for tm_index in range(3): # Optimise and validate. opt_and_check(spin=cdp.mol[0].res[res_index].spin[0], tm=tm[tm_index], s2=s2[s2_index]) # Increment the residue index. res_index += 1
"""Set up the data pipe for testing optimisation against tm3 relaxation data.""" # relax module imports. from opt_tm_fns import create_sequence, opt_and_check, setup_data # The model-free parameters. tm = [2e-9, 10e-9, 21e-9] s2 = [0.2, 0.8, 0.95] rex = [0.5, 4] # Create the sequence. create_sequence(len(tm)*len(s2)*len(rex)) # Set up the data. setup_data(dir='tm3_grid') # Residue index. res_index = 0 # Loop over the parameters. for rex_index in range(len(rex)): for s2_index in range(len(s2)): for tm_index in range(len(tm)): # Optimise and validate. opt_and_check(spin=cdp.mol[0].res[res_index].spin[0], tm=tm[tm_index], s2=s2[s2_index], rex=rex[rex_index]) # Increment the residue index. res_index += 1
# # ############################################################################### """Set up the data pipe for testing optimisation against tm1 relaxation data.""" # relax module imports. from opt_tm_fns import create_sequence, opt_and_check, setup_data # The model-free parameters. tm = [2e-9, 10e-9, 21e-9] s2 = [0.2, 0.8, 0.95] # Create the sequence. create_sequence(len(tm)*len(s2)) # Set up the data. setup_data(dir='tm1_grid') # Residue index. res_index = 0 # Loop over the parameters. for s2_index in range(3): for tm_index in range(3): # Optimise and validate. opt_and_check(spin=cdp.mol[0].res[res_index].spin[0], tm=tm[tm_index], s2=s2[s2_index]) # Increment the residue index. res_index += 1
# Module docstring. """Set up the data pipe for testing optimisation against tm3 relaxation data.""" # relax module imports. from opt_tm_fns import create_sequence, opt_and_check, setup_data # The model-free parameters. tm = [2e-9, 10e-9, 21e-9] s2 = [0.2, 0.8, 0.95] rex = [0.5, 4] # Create the sequence. create_sequence(len(tm)*len(s2)*len(rex)) # Set up the data. setup_data(dir='tm3_grid') # Residue index. res_index = 0 # Loop over the parameters. for rex_index in range(len(rex)): for s2_index in range(len(s2)): for tm_index in range(len(tm)): # Optimise and validate. opt_and_check(spin=cdp.mol[0].res[res_index].spin[0], tm=tm[tm_index], s2=s2[s2_index], rex=rex[rex_index]) # Increment the residue index. res_index += 1
# relax module imports. from opt_tm_fns import create_sequence, opt_and_check, setup_data # The model-free parameters. tm = [2e-9, 10e-9, 21e-9] s2 = [0.2, 0.8, 0.95] te = [2e-12, 40e-12] rex = [0.5, 4] # Create the sequence. create_sequence(len(tm)*len(s2)*len(te)*len(rex)) # Set up the data. setup_data(dir='tm4_grid') # Residue index. res_index = 0 # Loop over the parameters. for rex_index in range(len(rex)): for te_index in range(len(te)): for s2_index in range(len(s2)): for tm_index in range(len(tm)): # Optimise and validate. opt_and_check(spin=cdp.mol[0].res[res_index].spin[0], tm=tm[tm_index], s2=s2[s2_index], te=te[te_index], rex=rex[rex_index]) # Increment the residue index. res_index += 1
# Module docstring. """Set up the data pipe for testing optimisation against tm9 relaxation data.""" # relax module imports. from opt_tm_fns import create_sequence, opt_and_check, setup_data # The model-free parameters. tm = [2e-9, 10e-9, 80e-9] rex = [0.5, 4, 20] # Create the sequence. create_sequence(len(tm) * len(rex)) # Set up the data. setup_data(dir='tm9_grid') # Residue index. res_index = 0 # Loop over the parameters. for rex_index in range(len(rex)): for tm_index in range(len(tm)): # Optimise and validate. opt_and_check(spin=cdp.mol[0].res[res_index].spin[0], tm=tm[tm_index], rex=rex[rex_index]) # Increment the residue index. res_index += 1
# Module docstring. """Set up the data pipe for testing optimisation against tm2 relaxation data.""" # relax module imports. from opt_tm_fns import create_sequence, opt_and_check, setup_data # The model-free parameters. tm = [2e-9, 10e-9, 21e-9] s2 = [0.2, 0.8, 0.95] te = [2e-12, 40e-12, 1e-9] # Create the sequence. create_sequence(len(tm) * len(s2) * len(te)) # Set up the data. setup_data(dir='tm2_grid') # Residue index. res_index = 0 # Loop over the parameters. for te_index in range(3): for s2_index in range(3): for tm_index in range(3): # Optimise and validate. opt_and_check(spin=cdp.mol[0].res[res_index].spin[0], tm=tm[tm_index], s2=s2[s2_index], te=te[te_index]) # Increment the residue index.
# relax module imports. from opt_tm_fns import create_sequence, opt_and_check, setup_data # The model-free parameters. tm = [2e-9, 10e-9] s2 = [0.2, 0.8] s2f = [0.7, 0.8] tf = [2e-12, 40e-12] ts = [2e-11, 1.8e-9] # Create the sequence. create_sequence(len(tm)*len(s2)*len(s2f)*len(tf)*len(ts)) # Set up the data. setup_data(dir='tm6_grid') # Residue index. res_index = 0 # Loop over the parameters. for ts_index in range(len(ts)): for tf_index in range(len(tf)): for s2f_index in range(len(s2f)): for s2_index in range(len(s2)): for tm_index in range(len(tm)): # Optimise and validate. opt_and_check(spin=cdp.mol[0].res[res_index].spin[0], tm=tm[tm_index], s2=s2[s2_index], s2f=s2f[s2f_index], tf=tf[tf_index], ts=ts[ts_index]) # Increment the residue index. res_index += 1
# relax module imports. from opt_tm_fns import create_sequence, opt_and_check, setup_data # The model-free parameters. tm = [2e-9, 10e-9] s2 = [0.2, 0.4, 0.65] s2f = [0.7, 0.8] ts = [2e-12, 40e-12, 1e-9] # Create the sequence. create_sequence(len(tm)*len(s2)*len(s2f)*len(ts)) # Set up the data. setup_data(dir='tm5_grid') # Residue index. res_index = 0 # Loop over the parameters. for ts_index in range(len(ts)): for s2f_index in range(len(s2f)): for s2_index in range(len(s2)): for tm_index in range(len(tm)): # Optimise and validate. opt_and_check(spin=cdp.mol[0].res[res_index].spin[0], tm=tm[tm_index], s2=s2[s2_index], s2f=s2f[s2f_index], ts=ts[ts_index]) # Increment the residue index. res_index += 1
from opt_tm_fns import create_sequence, opt_and_check, setup_data # The model-free parameters. tm = [10e-9] s2 = [0.2, 0.8] s2f = [0.7, 0.8] tf = [2e-12, 40e-12] ts = [2e-11, 1.8e-9] rex = [0.5, 4] # Create the sequence. create_sequence(len(tm)*len(s2)*len(s2f)*len(tf)*len(ts)*len(rex)) # Set up the data. setup_data(dir='tm8_grid') # Residue index. res_index = 0 # Loop over the parameters. for rex_index in range(len(rex)): for ts_index in range(len(ts)): for tf_index in range(len(tf)): for s2f_index in range(len(s2f)): for s2_index in range(len(s2)): for tm_index in range(len(tm)): # Optimise and validate. opt_and_check(spin=cdp.mol[0].res[res_index].spin[0], tm=tm[tm_index], s2=s2[s2_index], s2f=s2f[s2f_index], tf=tf[tf_index], ts=ts[ts_index], rex=rex[rex_index]) # Increment the residue index.
# relax module imports. from opt_tm_fns import create_sequence, opt_and_check, setup_data # The model-free parameters. tm = [2e-9, 10e-9] s2 = [0.2, 0.8] s2f = [0.7, 0.8] ts = [2e-12, 40e-12] rex = [0.5, 4] # Create the sequence. create_sequence(len(tm) * len(s2) * len(s2f) * len(ts) * len(rex)) # Set up the data. setup_data(dir='tm7_grid') # Residue index. res_index = 0 # Loop over the parameters. for rex_index in range(len(rex)): for ts_index in range(len(ts)): for s2f_index in range(len(s2f)): for s2_index in range(len(s2)): for tm_index in range(len(tm)): # Optimise and validate. opt_and_check(spin=cdp.mol[0].res[res_index].spin[0], tm=tm[tm_index], s2=s2[s2_index], s2f=s2f[s2f_index],
# relax module imports. from opt_tm_fns import create_sequence, opt_and_check, setup_data # The model-free parameters. tm = [2e-9, 10e-9] s2 = [0.2, 0.8] s2f = [0.7, 0.8] ts = [2e-12, 40e-12] rex = [0.5, 4] # Create the sequence. create_sequence(len(tm)*len(s2)*len(s2f)*len(ts)*len(rex)) # Set up the data. setup_data(dir='tm7_grid') # Residue index. res_index = 0 # Loop over the parameters. for rex_index in range(len(rex)): for ts_index in range(len(ts)): for s2f_index in range(len(s2f)): for s2_index in range(len(s2)): for tm_index in range(len(tm)): # Optimise and validate. opt_and_check(spin=cdp.mol[0].res[res_index].spin[0], tm=tm[tm_index], s2=s2[s2_index], s2f=s2f[s2f_index], ts=ts[ts_index], rex=rex[rex_index]) # Increment the residue index. res_index += 1
# You should have received a copy of the GNU General Public License # # along with this program. If not, see <http://www.gnu.org/licenses/>. # # # ############################################################################### # Module docstring. """Set up the data pipe for testing optimisation against tm0 relaxation data.""" # relax module imports. from opt_tm_fns import create_sequence, opt_and_check, setup_data # The model-free parameters. tm = [2e-9, 10e-9, 80e-9] # Create the sequence. create_sequence(len(tm)) # Set up the data. setup_data(dir='tm0_grid') # Residue index. res_index = 0 # Loop over tm. for tm_index in range(len(tm)): # Optimise and validate. opt_and_check(spin=cdp.mol[0].res[res_index].spin[0], tm=tm[tm_index]) # Increment the residue index. res_index += 1