def gen_task_ctrl():
tc = TaskControl(__file__)
year = 2006
model = 'al508'
dist_thresh = 100
dotprod_thresh = 0.05
inputs = {
f'al508_diag_{month:02}': fmtp(diag_orog_precip_path_tpl,
model=model,
year=year,
month=month)
for month in [6, 7, 8]
}
inputs['al508_direct'] = fmtp(orog_precip_mean_fields_tpl,
model='al508',
year=year,
season='jja',
dotprod_thresh=dotprod_thresh,
dist_thresh=dist_thresh)
inputs['ak543_direct'] = fmtp(orog_precip_mean_fields_tpl,
model='ak543',
year=year,
season='jja',
dotprod_thresh=dotprod_thresh,
dist_thresh=dist_thresh)
tc.add(Task(plot_fig2, inputs, [D23_fig2]))
tc.add(Task(plot_fig3, inputs, [D23_fig3]))
tc.add(Task(plot_fig4, inputs, [D23_fig4, D23_fig5]))
return tc
def gen_task_ctrl():
tc = TaskControl(__file__)
# /gws/nopw/j04/cosmic/mmuetz/data/era_interim_orog_precip
years = [2006]
# years = [2005, 2006, 2007, 2008]
models = ['al508', 'ak543']
months = [6, 7, 8]
for model, year, month in product(models, years, months):
# al508a.p9200606.asia_precip.nc
precip_path = fmtp(precip_path_tpl, model=model, year=year, month=month)
orog_precip_inputs = {
'extended_rclim_mask': extended_rclim_mask,
'land_sea_mask': land_sea_mask,
'precip': precip_path
}
diag_orog_precip_path = fmtp(diag_orog_precip_path_tpl, model=model, year=year, month=month)
tc.add(Task(calc_orog_precip,
orog_precip_inputs,
[diag_orog_precip_path],
func_args=(month - 1, )))
orog_precip_fracs_inputs = {
'extended_rclim_mask': extended_rclim_mask,
'land_sea_mask': land_sea_mask,
'orog_precip': diag_orog_precip_path
}
diag_orog_precip_frac_path = fmtp(diag_orog_precip_frac_path_tpl, model=model, year=year, month=month)
tc.add(Task(calc_orog_precip_fracs,
orog_precip_fracs_inputs,
[diag_orog_precip_frac_path],
func_args=(month - 1, )))
variables = list(product(models, months))
columns = ['model', 'month']
combine_inputs = [fmtp(diag_orog_precip_frac_path_tpl, model=model, year=year, month=month)
for model, month in variables]
combine_fracs_output = [diag_combine_frac_path]
tc.add(Task(combine_orog_precip_fracs,
combine_inputs,
combine_fracs_output,
func_args=(variables, columns)
))
return tc
def gen_task_ctrl():
tc = TaskControl(__file__)
models = ['al508', 'ak543']
# models = ['ak543']
dist_threshs = [100]
dotprod_threshs = [0.05]
months = [6, 7, 8]
# dist_threshs = [20, 100]
# dotprod_threshs = [0.05, 0.1]
year = 2006
for model, dotprod_thresh, dist_thresh in product(models, dotprod_threshs, dist_threshs):
# 1 model at a time.
orog_precip_paths = [fmtp(orog_precip_path_tpl, model=model, year=year, month=month,
dotprod_thresh=dotprod_thresh, dist_thresh=dist_thresh)
for month in months]
orog_precip_mean_fields = [fmtp(orog_precip_mean_fields_tpl, model=model, year=year, season='jja',
dotprod_thresh=dotprod_thresh, dist_thresh=dist_thresh)]
tc.add(Task(extract_precip_mean_fields, orog_precip_paths, orog_precip_mean_fields))
for model, dotprod_thresh, dist_thresh in product(models, dotprod_threshs, dist_threshs):
orog_precip_mean_fields = [fmtp(orog_precip_mean_fields_tpl, model=model, year=year, season='jja',
dotprod_thresh=dotprod_thresh, dist_thresh=dist_thresh)]
orog_precip_figs = [fmtp(orog_precip_fig_tpl, model=model, year=year, season='jja',
dotprod_thresh=dotprod_thresh, dist_thresh=dist_thresh,
precip_type=precip_type)
for precip_type in ['orog', 'non_orog', 'ocean', 'orog_frac']]
tc.add(Task(plot_mean_orog_precip, orog_precip_mean_fields, orog_precip_figs))
return tc
for dotprod_thresh, dist_thresh in product(dotprod_threshs, dist_threshs):
# Compare 2 models.
orog_precip_paths = {(model, month): fmtp(orog_precip_path_tpl, model=model, year=year, month=month,
dotprod_thresh=dotprod_thresh, dist_thresh=dist_thresh)
for model in models
for month in months}
orog_precip_figs = [fmtp(orog_precip_fig_tpl, model='-'.join(models), year=year, season='jja',
dotprod_thresh=dotprod_thresh, dist_thresh=dist_thresh,
precip_type=precip_type)
for precip_type in ['orog', 'non_orog', 'ocean']]
tc.add(Task(plot_compare_mean_orog_precip, orog_precip_paths, orog_precip_figs,
func_args=(models, months)))
return tc
def gen_task_ctrl(test=False):
tc = TaskControl(__file__)
models = ['al508', 'ak543']
months = [6, 7, 8]
year = 2006
regions = ['TP_southern_flank', 'sichuan_basin']
days_in_month = 30
if test:
models = models[:1]
months = months[:1]
days_in_month = 2
# regions = regions[:1]
for model, month, region in product(models, months, regions):
surf_wind_path = fmtp(surf_wind_path_tpl,
model=model,
year=year,
month=month)
precip_path = fmtp(precip_path_tpl,
model=model,
year=year,
month=month)
orog_mask_path = fmtp(orog_mask_path_tpl,
model=model,
year=year,
month=month,
dotprod_thresh=0.05,
dist_thresh=100)
raw_data_fig_paths = [
fmtp(raw_data_fig_tpl,
model=model,
year=year,
month=month,
day=day,
hour=h,
region=region) for day in range(1, days_in_month + 1)
for h in range(0, 24)
]
tc.add(
Task(plot_precip_wind_region, {
'orog': orog_path,
'surf_wind': surf_wind_path,
'precip': precip_path,
'orog_mask': orog_mask_path,
},
raw_data_fig_paths,
func_args=(region, month)))
raw_data_dc_fig_paths = [
fmtp(raw_data_dc_fig_tpl,
model=model,
year=year,
month=month,
hour=h,
region=region) for h in range(24)
]
tc.add(
Task(plot_dc_region, {
'orog': orog_path,
'surf_wind': surf_wind_path,
'precip': precip_path,
'orog_mask': orog_mask_path,
},
raw_data_dc_fig_paths,
func_args=(region, 24)))
raw_data_dc_anom_wind_fig_paths = [
fmtp(raw_data_dc_anom_wind_fig_tpl,
model=model,
year=year,
month=month,
hour=h,
region=region) for h in range(24)
]
tc.add(
Task(plot_dc_anom_wind_region, {
'orog': orog_path,
'surf_wind': surf_wind_path,
'precip': precip_path,
'orog_mask': orog_mask_path,
},
raw_data_dc_anom_wind_fig_paths,
func_args=(region, 24)))
tc.add(
Task(create_animation, raw_data_dc_anom_wind_fig_paths, [
fmtp(anim_raw_data_dc_anom_wind_fig_tpl,
model=model,
year=year,
month=month,
region=region)
], (120, )))
return tc
def gen_task_ctrl():
tc = TaskControl(__file__)
years = [2006]
# years = [2005, 2006, 2007, 2008]
models = ['al508', 'ak543']
dist_threshs = [50, 100]
dotprod_threshs = [0.05]
months = [6, 7, 8]
# dist_threshs = [20, 100]
# dotprod_threshs = [0.05, 0.1]
for dist_thresh in dist_threshs:
cache_key = fmtp(cache_key_tpl, dist_thresh=dist_thresh)
tc.add(
Task(gen_dist_cache, {'orog': orog_path}, [cache_key],
func_args=(dist_thresh, )))
for year, model, dotprod_thresh, dist_thresh in product(
years, models, dotprod_threshs, dist_threshs):
cache_key = fmtp(cache_key_tpl, dist_thresh=dist_thresh)
for month in months:
surf_wind_path = fmtp(surf_wind_path_tpl,
model=model,
year=year,
month=month)
orog_mask_path = fmtp(orog_mask_path_tpl,
model=model,
year=year,
month=month,
dotprod_thresh=dotprod_thresh,
dist_thresh=dist_thresh)
inputs = {
'orog': orog_path,
'cache_key': cache_key,
'surf_wind': surf_wind_path
}
tc.add(
Task(gen_orog_mask,
inputs, [orog_mask_path],
func_args=(dotprod_thresh, dist_thresh)))
precip_path = fmtp(precip_path_tpl,
model=model,
year=year,
month=month)
orog_precip_path = fmtp(orog_precip_path_tpl,
model=model,
year=year,
month=month,
dotprod_thresh=dotprod_thresh,
dist_thresh=dist_thresh)
orog_precip_inputs = {
'orog_mask': orog_mask_path,
'land_sea_mask': land_sea_mask,
'precip': precip_path
}
tc.add(
Task(calc_orog_precip, orog_precip_inputs, [orog_precip_path]))
orog_precip_frac_inputs = {
'orog_mask': orog_mask_path,
'land_sea_mask': land_sea_mask,
'orog_precip': orog_precip_path
}
orog_precip_frac_path = fmtp(orog_precip_frac_path_tpl,
model=model,
year=year,
month=month,
dotprod_thresh=dotprod_thresh,
dist_thresh=dist_thresh)
tc.add(
Task(calc_orog_precip_fracs, orog_precip_frac_inputs,
[orog_precip_frac_path]))
variables = list(product(models, dotprod_threshs, dist_threshs, months))
columns = ['model', 'dotprod_thresh', 'dist_thresh', 'month']
combine_inputs = [
fmtp(orog_precip_frac_path_tpl,
model=model,
year=year,
month=month,
dotprod_thresh=dotprod_thresh,
dist_thresh=dist_thresh)
for model, dotprod_thresh, dist_thresh, month in variables
]
combine_fracs_output = [combine_frac_path]
tc.add(
Task(combine_orog_precip_fracs,
combine_inputs,
combine_fracs_output,
func_args=(variables, columns)))
return tc