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4_model_for_PGDL.yml
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4_model_for_PGDL.yml
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target_default: 4_model_for_PGDL
packages:
- yaml
- dplyr
- tidyr
- scipiper
sources:
- 4_model/src/EnKF_functions.R
- 4_model/src/get_sntemp_values.R
- 4_model/src/run_sntemp.R
- 4_model/src/update_sntemp.R
- 4_model/src/set_sntemp_output.R
- 4_model_for_PGDL/src/data_for_pgdl.R
- 4_model_for_PGDL/src/training_test_data.R
- 4_model_for_PGDL/src/get_segment_driver.R
- 4_model_calibrate/src/get_subbasins.R
- 4_model_calibrate/src/get_subbasin_obs.R
- 4_model_for_PGDL/src/subbasins_options.R
- 4_model_for_PGDL/src/get_prms_sntemp_model.R
targets:
4_model_for_PGDL:
depends:
- 4_model_for_PGDL/out/sntemp_input.feather.ind
- 4_model_for_PGDL/out/sntemp_output.feather.ind
##########################################
# uncalibrated SNTemp run for input to PGDL
##########################################
# need to make sure that 20191002_Delaware_streamtemp folder is in project on
# local machine; this is on GD if not on local machine
get_prms_sntemp:
command: get_prms_sntemp_model(
gd_zip_ind_file = 'prms_sntemp/20191002_Delaware_streamtemp.zip.ind',
unzip_loc = I('prms_sntemp'))
# moving model to temporary run location so that we can change parameters, etc.. while keeping
# original model preserved
move_model_to_run_dir:
command: copy_model_to_run_dir(
model_run_loc = I('4_model_for_PGDL/tmp'),
orig_model_loc = I('20191002_Delaware_streamtemp'))
uncal_settings:
command: read_yaml('4_model_for_PGDL/cfg/uncal_settings.yml')
sntemp_output_vars:
command: uncal_settings[I('sntemp_output')]
set_sntemp_output_vars:
command: set_sntemp_output(
output_names = sntemp_output_vars,
model_run_loc = '4_model_for_PGDL/tmp')
uncal_start:
command: uncal_settings[I('start')]
uncal_stop:
command: uncal_settings[I('stop')]
uncal_sntemp_run:
command: run_sntemp(
start = uncal_start,
stop = uncal_stop,
spinup = I('F'),
restart = I('F'),
model_run_loc = I('4_model_for_PGDL/tmp'))
depends: set_sntemp_output_vars
# input only contains tmin, tmax, prcp
# 4_model_for_PGDL/out/sntemp_input.feather.ind:
# command: get_segment_drivers(
# ind_file = target_name,
# model_run_loc = I('4_model_for_PGDL/tmp'),
# param_file = I('input/myparam.param'),
# start = uncal_start,
# stop = uncal_stop)
# 4_model_for_PGDL/out/sntemp_input.feather:
# command: gd_get('4_model_for_PGDL/out/sntemp_input.feather.ind')
#
# 4_model_for_PGDL/out/sntemp_input_subset.feather.ind:
# command: data_subset_for_pgdl(
# ind_file = target_name,
# full_data_file = '4_model_for_PGDL/out/sntemp_input.feather')
# 4_model_for_PGDL/out/sntemp_input_subset.feather:
# command: gd_get('4_model_for_PGDL/out/sntemp_input_subset.feather.ind')
# includes output in 4_model_for_PGDL/cfg/uncal_settings.yml
4_model_for_PGDL/out/uncal_sntemp_input_output_gridmet.feather.ind:
command: data_for_pgdl(
ind_file = target_name,
model_run_loc = I('4_model_for_PGDL/tmp'),
model_output_file = I('output/stream_temp.out.nsegment'),
model_fabric_file = I('GIS/Segments_subset.shp'),
sntemp_vars = sntemp_output_vars)
depends: uncal_sntemp_run
4_model_for_PGDL/out/uncal_sntemp_input_output_gridmet.feather:
command: gd_get('4_model_for_PGDL/out/uncal_sntemp_input_output_gridmet.feather.ind')
4_model_for_PGDL/out/uncal_sntemp_input_output_gridmet_subset.feather.ind:
command: data_subset_for_pgdl(
ind_file = target_name,
full_data_file = '4_model_for_PGDL/out/uncal_sntemp_input_output_gridmet.feather')
4_model_for_PGDL/out/uncal_sntemp_input_output_gridmet_subset.feather:
command: gd_get('4_model_for_PGDL/out/uncal_sntemp_input_output_gridmet_subset.feather.ind')
4_model_for_PGDL/out/subbasin_options.feather.ind:
command: subbasin_options(
ind_file = target_name,
subbasin_file = '4_model_calibrate/out/drb_subbasins.rds',
uncal_sntemp_pred_file = '4_model_for_PGDL/out/sntemp_output.feather',
obs_file = '3_observations/in/obs_temp_full.rds')
### generating PRMS-SNTemp data for PGDL ensemble learning ###
# varying gw_tau only
4_model_for_PGDL/out/uncal_sntemp_input_output_subset_45[gw_tau]_6[ss_tau].feather.ind:
command: data_for_ensemble_pgdl(
ind_file = target_name,
model_run_loc = I('4_model_for_PGDL/tmp'),
model_output_file = I('output/stream_temp.out.nsegment'),
model_fabric_file = I('GIS/Segments_subset.shp'),
sntemp_vars = sntemp_output_vars,
sub_net_file = '4_model_for_PGDL/in/network_subset.rds',
subset = I('T'),
gw_tau = I(45),
ss_tau = I(6),
start = uncal_start,
stop = uncal_stop,
spinup = I('F'),
restart = I('F'))
4_model_for_PGDL/out/uncal_sntemp_input_output_subset_10[gw_tau]_6[ss_tau].feather.ind:
command: data_for_ensemble_pgdl(
ind_file = target_name,
model_run_loc = I('4_model_for_PGDL/tmp'),
model_output_file = I('output/stream_temp.out.nsegment'),
model_fabric_file = I('GIS/Segments_subset.shp'),
sntemp_vars = sntemp_output_vars,
sub_net_file = '4_model_for_PGDL/in/network_subset.rds',
subset = I('T'),
gw_tau = I(10),
ss_tau = I(6),
start = uncal_start,
stop = uncal_stop,
spinup = I('F'),
restart = I('F'))
4_model_for_PGDL/out/uncal_sntemp_input_output_subset_100[gw_tau]_6[ss_tau].feather.ind:
command: data_for_ensemble_pgdl(
ind_file = target_name,
model_run_loc = I('4_model_for_PGDL/tmp'),
model_output_file = I('output/stream_temp.out.nsegment'),
model_fabric_file = I('GIS/Segments_subset.shp'),
sntemp_vars = sntemp_output_vars,
sub_net_file = '4_model_for_PGDL/in/network_subset.rds',
subset = I('T'),
gw_tau = I(100),
ss_tau = I(6),
start = uncal_start,
stop = uncal_stop,
spinup = I('F'),
restart = I('F'))
# varying ss_tau only
4_model_for_PGDL/out/uncal_sntemp_input_output_subset_45[gw_tau]_1[ss_tau].feather.ind:
command: data_for_ensemble_pgdl(
ind_file = target_name,
model_run_loc = I('4_model_for_PGDL/tmp'),
model_output_file = I('output/stream_temp.out.nsegment'),
model_fabric_file = I('GIS/Segments_subset.shp'),
sntemp_vars = sntemp_output_vars,
sub_net_file = '4_model_for_PGDL/in/network_subset.rds',
subset = I('T'),
gw_tau = I(45),
ss_tau = I(1),
start = uncal_start,
stop = uncal_stop,
spinup = I('F'),
restart = I('F'))
4_model_for_PGDL/out/uncal_sntemp_input_output_subset_45[gw_tau]_20[ss_tau].feather.ind:
command: data_for_ensemble_pgdl(
ind_file = target_name,
model_run_loc = I('4_model_for_PGDL/tmp'),
model_output_file = I('output/stream_temp.out.nsegment'),
model_fabric_file = I('GIS/Segments_subset.shp'),
sntemp_vars = sntemp_output_vars,
sub_net_file = '4_model_for_PGDL/in/network_subset.rds',
subset = I('T'),
gw_tau = I(45),
ss_tau = I(20),
start = uncal_start,
stop = uncal_stop,
spinup = I('F'),
restart = I('F'))
# -- creating synthetic training datasets --
# file naming == site_realOrSynthetic_train_percentSegmentsObserved_temporalResolution(days)_obsType.feather
4_model_for_PGDL/out/drb_synthetic_train_60_21_inSitu.feather.ind:
command: build_synthetic_training(
ind_file = target_name,
data_file = '4_model_for_PGDL/out/sntemp_input_output.feather',
percent_sites = I(60),
temporal_res = I(21),
obs_type = I('in_situ'),
exp_n = I(5),
test_yrs = I(12))
4_model_for_PGDL/out/drb_subset_synthetic_train_60_21_inSitu.feather.ind:
command: subset_training(
ind_file = target_name,
full_training_file = '4_model_for_PGDL/out/drb_synthetic_train_60_21_inSitu.feather',
sub_net_file = '4_model_for_PGDL/in/network_subset.rds')
4_model_for_PGDL/out/drb_synthetic_train_10_1_inSitu.feather.ind:
command: build_synthetic_training(
ind_file = target_name,
data_file = '4_model_for_PGDL/out/sntemp_input_output.feather',
percent_sites = I(10),
temporal_res = I(1),
obs_type = I('in_situ'),
exp_n = I(5),
test_yrs = I(12))
4_model_for_PGDL/out/drb_subset_synthetic_train_10_1_inSitu.feather.ind:
command: subset_training(
ind_file = target_name,
full_training_file = '4_model_for_PGDL/out/drb_synthetic_train_10_1_inSitu.feather',
sub_net_file = '4_model_for_PGDL/in/network_subset.rds')
4_model_for_PGDL/out/drb_synthetic_train_100_14_rs.feather.ind:
command: build_synthetic_training(
ind_file = target_name,
data_file = '4_model_for_PGDL/out/sntemp_input_output.feather',
percent_sites = I(100),
temporal_res = I(14),
obs_type = I('rs'),
exp_n = I(5),
test_yrs = I(12))
4_model_for_PGDL/out/drb_subset_synthetic_train_100_14_rs.feather.ind:
command: subset_training(
ind_file = target_name,
full_training_file = '4_model_for_PGDL/out/drb_synthetic_train_100_14_rs.feather',
sub_net_file = '4_model_for_PGDL/in/network_subset.rds')
# -- creating real obs training datasets --
# file naming == site_fullOrSubset_realOrSynthetic_train_percentObs.feather
4_model_for_PGDL/out/drb_full_real_train_100.feather.ind:
command: build_real_training(
ind_file = target_name,
data_file = '4_model_for_PGDL/out/sntemp_input_output.feather',
obs_file = '3_observations/in/obs_temp_full.rds',
percent_obs = I(100),
exp_n = I(5),
test_yrs = I(12))
4_model_for_PGDL/out/drb_subset_real_train_100.feather.ind:
command: subset_training(
ind_file = target_name,
full_training_file = '4_model_for_PGDL/out/drb_full_real_train_100.feather',
sub_net_file = '4_model_for_PGDL/in/network_subset.rds')
4_model_for_PGDL/out/drb_full_real_train_50.feather.ind:
command: build_real_training(
ind_file = target_name,
data_file = '4_model_for_PGDL/out/sntemp_input_output.feather',
obs_file = '3_observations/in/obs_temp_full.rds',
percent_obs = I(50),
exp_n = I(5),
test_yrs = I(12))
4_model_for_PGDL/out/drb_subset_real_train_50.feather.ind:
command: subset_training(
ind_file = target_name,
full_training_file = '4_model_for_PGDL/out/drb_full_real_train_50.feather',
sub_net_file = '4_model_for_PGDL/in/network_subset.rds')
4_model_for_PGDL/out/drb_full_real_train_20.feather.ind:
command: build_real_training(
ind_file = target_name,
data_file = '4_model_for_PGDL/out/sntemp_input_output.feather',
obs_file = '3_observations/in/obs_temp_full.rds',
percent_obs = I(20),
exp_n = I(5),
test_yrs = I(12))
4_model_for_PGDL/out/drb_subset_real_train_20.feather.ind:
command: subset_training(
ind_file = target_name,
full_training_file = '4_model_for_PGDL/out/drb_full_real_train_20.feather',
sub_net_file = '4_model_for_PGDL/in/network_subset.rds')
4_model_for_PGDL/out/drb_full_real_train_10.feather.ind:
command: build_real_training(
ind_file = target_name,
data_file = '4_model_for_PGDL/out/sntemp_input_output.feather',
obs_file = '3_observations/in/obs_temp_full.rds',
percent_obs = I(10),
exp_n = I(5),
test_yrs = I(12))
4_model_for_PGDL/out/drb_subset_real_train_10.feather.ind:
command: subset_training(
ind_file = target_name,
full_training_file = '4_model_for_PGDL/out/drb_full_real_train_10.feather',
sub_net_file = '4_model_for_PGDL/in/network_subset.rds')
4_model_for_PGDL/out/drb_full_real_train_02.feather.ind:
command: build_real_training(
ind_file = target_name,
data_file = '4_model_for_PGDL/out/sntemp_input_output.feather',
obs_file = '3_observations/in/obs_temp_full.rds',
percent_obs = I(2),
exp_n = I(5),
test_yrs = I(12))
4_model_for_PGDL/out/drb_subset_real_train_02.feather.ind:
command: subset_training(
ind_file = target_name,
full_training_file = '4_model_for_PGDL/out/drb_full_real_train_02.feather',
sub_net_file = '4_model_for_PGDL/in/network_subset.rds')
# -- creating real obs training datasets with max of 100 obs per segment during training period --
# file naming == site_fullOrSubset_realOrSynthetic_train_nObsPerSegment.feather
4_model_for_PGDL/out/drb_full_real_train_100obs.feather.ind:
command: build_real_training(
ind_file = target_name,
data_file = '4_model_for_PGDL/out/sntemp_input_output.feather',
obs_file = '3_observations/in/obs_temp_full.rds',
max_obs = I(100),
n_obs = I(100),
exp_n = I(5),
test_yrs = I(12))
4_model_for_PGDL/out/drb_subset_real_train_100obs.feather.ind:
command: subset_training(
ind_file = target_name,
full_training_file = '4_model_for_PGDL/out/drb_full_real_train_100obs.feather',
sub_net_file = '4_model_for_PGDL/in/network_subset.rds')
4_model_for_PGDL/out/drb_full_real_train_50obs.feather.ind:
command: build_real_training(
ind_file = target_name,
data_file = '4_model_for_PGDL/out/sntemp_input_output.feather',
obs_file = '3_observations/in/obs_temp_full.rds',
max_obs = I(100),
n_obs = I(50),
exp_n = I(5),
test_yrs = I(12))
4_model_for_PGDL/out/drb_subset_real_train_50obs.feather.ind:
command: subset_training(
ind_file = target_name,
full_training_file = '4_model_for_PGDL/out/drb_full_real_train_50obs.feather',
sub_net_file = '4_model_for_PGDL/in/network_subset.rds')
4_model_for_PGDL/out/drb_full_real_train_10obs.feather.ind:
command: build_real_training(
ind_file = target_name,
data_file = '4_model_for_PGDL/out/sntemp_input_output.feather',
obs_file = '3_observations/in/obs_temp_full.rds',
max_obs = I(100),
n_obs = I(10),
exp_n = I(5),
test_yrs = I(12))
4_model_for_PGDL/out/drb_subset_real_train_10obs.feather.ind:
command: subset_training(
ind_file = target_name,
full_training_file = '4_model_for_PGDL/out/drb_full_real_train_10obs.feather',
sub_net_file = '4_model_for_PGDL/in/network_subset.rds')
4_model_for_PGDL/out/drb_full_real_train_2obs.feather.ind:
command: build_real_training(
ind_file = target_name,
data_file = '4_model_for_PGDL/out/sntemp_input_output.feather',
obs_file = '3_observations/in/obs_temp_full.rds',
max_obs = I(100),
n_obs = I(2),
exp_n = I(5),
test_yrs = I(12))
4_model_for_PGDL/out/drb_subset_real_train_2obs.feather.ind:
command: subset_training(
ind_file = target_name,
full_training_file = '4_model_for_PGDL/out/drb_full_real_train_2obs.feather',
sub_net_file = '4_model_for_PGDL/in/network_subset.rds')