file: '''4_inspect_results.py'''.
<source lang="Python">
# Python module imports.
from os import getcwd, sep
import re
 
# relax module imports.
from pipe_control.mol_res_spin import generate_spin_string, return_spin, spin_loop
from specific_analyses.relax_disp.data import generate_r20_key, loop_exp_frq
from specific_analyses.relax_disp.variables import MODEL_R2EFF, MODEL_NOREX_R1RHO_FIT_R1, MODEL_DPL94_FIT_R1, MODEL_TP02_FIT_R1, MODEL_TAP03_FIT_R1, MODEL_MP05_FIT_R1
 
#########################################
#### Setup
results_dir = getcwd() + sep + 'results_models'
 
# Load the previous state
state.load(state='final_state.bz2', dir=results_dir)
 
# Display all pipes
pipe.display()
 
# Define models which have been analysed.
#MODELS = [MODEL_NOREX_R1RHO_FIT_R1, MODEL_DPL94_FIT_R1, MODEL_TP02_FIT_R1, MODEL_TAP03_FIT_R1, MODEL_MP05_FIT_R1]
MODELS = [MODEL_NOREX_R1RHO_FIT_R1, MODEL_DPL94_FIT_R1]
 
# Print results for each model.
print("\n################")
print("Printing results")
print("################\n")
 
for model in MODELS:
    # Skip R2eff model.
    if model == MODEL_R2EFF:
        continue
 
    # Switch to pipe.
    pipe.switch(pipe_name='%s - relax_disp' % (model))
    print("\nModel: %s" % (model))
 
    # Loop over the spins.
    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("\nOptimised parameters for spin: %s" % (spin_string))
        for param in cur_spin.params + ['chi2']:
            # Get the value.
            if param in ['r1_fit', 'r2']:
                for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True):
                    # Generate the R20 key.
                    r20_key = generate_r20_key(exp_type=exp_type, frq=frq)
 
                    # Get the value.
                    value = getattr(cur_spin, param)[r20_key]
 
                    # Print value.
                    print("%-10s %-6s %-6s %3.8f" % ("Parameter:", param, "Value:", value))
 
            # For all other parameters.
            else:
                # Get the value.
                value = getattr(cur_spin, param)
 
                # Print value.
                print("%-10s %-6s %-6s %3.8f" % ("Parameter:", param, "Value:", value))
 
 
# Print the final pipe.
pipe.switch(pipe_name='%s - relax_disp' % ('final'))
print("\nFinal pipe")
 
# Loop over the spins.
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("\nOptimised model for spin: %s" % (spin_string))
    param = 'model'
 
    # Get the value.
    value = getattr(cur_spin, param)
    print("%-10s %-6s %-6s %6s" % ("Parameter:", param, "Value:", value))
</source>
= See also =
[[Category:Tutorials]]