Relates to cadCAD tutorial, lecture 7.3, 21:00 minutes in.

drop_substes.py

# Get system events and attribute index
df = (pd.DataFrame(system_events)
        .assign(years=lambda df: df.timestep)
        .assign(temperature_celsius=lambda df: df.temperature - 273)
        .query('timestep > 0')
     )

# Clean substeps
first_ind = (df.substep == 0) & (df.timestep == 0)

class tcolors:
    HEADER = '\033[95m'
    OKBLUE = '\033[94m'
    OKCYAN = '\033[96m'
    OKGREEN = '\033[92m'
    WARNING = '\033[93m'
    FAIL = '\033[91m'
    ENDC = '\033[0m'
    BOLD = '\033[1m'
    UNDERLINE = '\033[4m'

    
    
print("first_ind evaluation: ")
print("--------------------")
for i in [0,1,2,3]:
    if i == 0:
        watch = tcolors.OKBLUE
    else:
        watch = ''
    print(f"{watch}df.substep == {i} TRUE count:", (df.substep == i).sum(), f"{tcolors.ENDC}")
print()
for i in [0,1,2,3,99,100,101]:
    if i == 0:
        watch = tcolors.OKBLUE
    else:
        watch = ''
    print(f"{watch}df.timestep == {i} TRUE count:", (df.timestep == i).sum(), f"{tcolors.ENDC}")

print()
print(f"{tcolors.OKBLUE}first_ind = (df.substep == 0) & (df.timestep == 0){tcolors.ENDC}")
print("first_ind total:", first_ind.count())
print("first_ind TRUE count:", (first_ind == True).sum())
print("first_ind FALSE count:", (first_ind == False).sum())
print()
print("-"*70)
print()


print("last_ind evaluation: ")
print("--------------------")
last_ind = df.substep == max(df.substep)
print(f"{tcolors.OKBLUE}last_ind = max(df.substep){tcolors.ENDC}")
print(last_ind[:10])
print()
print("last_ind total:", last_ind.count())
print("last_ind TRUE count:", (last_ind == True).sum())
print("last_ind FALSE count:", (last_ind == False).sum())
print()
print("-"*70)

print("inds_to_drop evaluation:")
print("------------------------")

print("# of True in first_ind: ", (first_ind == True).sum())
print("Length of first_ind", len(first_ind))
print("# of True last_ind: ", (last_ind == True).sum())
print("Length of last_ind", len(last_ind))
print()
print(f"{tcolors.OKBLUE}inds_to_drop = (first_ind | last_ind){tcolors.ENDC}")
inds_to_drop = (first_ind | last_ind)
print("inds_to_drop total: ", inds_to_drop.count())
print("inds_to_drop True count: ",(inds_to_drop == True).sum())
print("inds_to_drop False count: ",(inds_to_drop == False).sum())


df = df.loc[inds_to_drop].drop(columns=['substep'])

# Attribute parameters to each row
df = df.assign(**configs[0].sim_config['M'])
for i, (_, n_df) in enumerate(df.groupby(['simulation', 'subset', 'run'])):
    df.loc[n_df.index] = n_df.assign(**configs[i].sim_config['M'])