From 5c64448322863708a359c347043fb22623e24664 Mon Sep 17 00:00:00 2001 From: RY4GIT <400mhs2@gmail.com> Date: Sun, 26 Nov 2023 12:29:08 -0800 Subject: [PATCH 1/2] add: save satdk and Cgw --- src/agents/DifferentiableCFE.py | 12 +++++++++--- src/config.yaml | 2 +- src/models/config/base.yaml | 2 +- 3 files changed, 11 insertions(+), 5 deletions(-) diff --git a/src/agents/DifferentiableCFE.py b/src/agents/DifferentiableCFE.py index b488c5d..2e23e72 100644 --- a/src/agents/DifferentiableCFE.py +++ b/src/agents/DifferentiableCFE.py @@ -77,6 +77,9 @@ def __init__(self, cfg: DictConfig) -> None: ] ) + self.Cgw_record = np.empty([self.data.num_basins, self.data.n_timesteps]) + self.satdk_record = np.empty([self.data.num_basins, self.data.n_timesteps]) + # # Prepare for the DDP # free_port = find_free_port() # os.environ["MASTER_ADDR"] = "localhost" @@ -126,6 +129,8 @@ def train(self) -> None: self.run_model(run_mlp=False) for epoch in range(1, self.cfg.models.hyperparameters.epochs + 1): + # TODO: Loop through basins + # Run dCFE for all basins ... log.info(f"Epoch #: {epoch}/{self.cfg.models.hyperparameters.epochs}") self.loss_record[epoch - 1] = self.train_one_epoch() self.current_epoch += 1 @@ -167,6 +172,8 @@ def run_model(self, run_mlp=False): for t, (x, y_t) in enumerate(tqdm(self.data_loader, desc="Processing data")): if run_mlp: self.model.mlp_forward(t) # Instead + self.Cgw_record[:, t] = self.model.Cgw.detach().numpy() + self.satdk_record[:, t] = self.model.satdk.detach().numpy() runoff = self.model(x, t) y_hat[:, t] = runoff @@ -305,9 +312,6 @@ def save_checkpoint(self, file_name="checkpoint.pth.tar", is_best=0): def save_result(self, y_hat, y_t, out_filename, plot_figure=False): # Save all basin runs - Cgw = self.model.Cgw.detach().numpy() - satdk_ = self.model.satdk.detach().numpy() - warmup = self.cfg.models.hyperparameters.warmup for i, basin_id in enumerate(self.data.basin_ids): @@ -318,6 +322,8 @@ def save_result(self, y_hat, y_t, out_filename, plot_figure=False): data = { "y_hat": y_hat[i, warmup:].squeeze(), "y_t": y_t[i, warmup:].squeeze(), + "Cgw": self.Cgw_record[i, warmup:], + "satdk": self.satdk_record[i, warmup:], } df = pd.DataFrame(data) df.to_csv( diff --git a/src/config.yaml b/src/config.yaml index 499e53e..0d0bef2 100644 --- a/src/config.yaml +++ b/src/config.yaml @@ -12,7 +12,7 @@ num_processes: 1 ################## CHANGE HERE ####################### -run_type: ML_synthetic_test # Choose from: "generate_synthetic" or "ML" or "ML_synthetic_test" +run_type: ML # Choose from: "generate_synthetic" or "ML" or "ML_synthetic_test" soil_scheme: classic # Choose from: "ode" or "classic" ###################################################### diff --git a/src/models/config/base.yaml b/src/models/config/base.yaml index 63bfa13..1f285be 100644 --- a/src/models/config/base.yaml +++ b/src/models/config/base.yaml @@ -1,5 +1,5 @@ hyperparameters: - epochs: 30 #1000 #50 + epochs: 3 #1000 #50 learning_rate: 1.0e-2 #0.1 # 0.001 warmup: 2000 step_size: 1 From 6c1e034c7633d4cadcbcc8efd4c17449e1d70c28 Mon Sep 17 00:00:00 2001 From: RY4GIT <400mhs2@gmail.com> Date: Sun, 26 Nov 2023 13:10:07 -0800 Subject: [PATCH 2/2] debug: unit conversion in ML mode --- .../DEEP_GW_TO_CHANNEL_FLUX.csv | 8784 ++++++++++++++++ data/synthetic_case/DIRECT_RUNOFF.csv | 8784 ++++++++++++++++ data/synthetic_case/GIUH_RUNOFF.csv | 8784 ++++++++++++++++ data/synthetic_case/NASH_LATERAL_RUNOFF.csv | 8784 ++++++++++++++++ .../SOIL_CONCEPTUAL_STORAGE.csv | 8786 ++++++++++++++++- data/synthetic_case/config.yml | 13 +- .../land_surface_water__runoff_depth.csv | 8784 ++++++++++++++++ ...land_surface_water__runoff_volume_flux.csv | 8784 ++++++++++++++++ data/synthetic_case/synthetic_classic.csv | 8784 ++++++++++++++++ src/agents/DifferentiableCFE.py | 28 +- src/config.yaml | 3 + src/data/Data.py | 3 +- src/models/config/base.yaml | 2 +- 13 files changed, 70302 insertions(+), 21 deletions(-) diff --git a/data/synthetic_case/DEEP_GW_TO_CHANNEL_FLUX.csv b/data/synthetic_case/DEEP_GW_TO_CHANNEL_FLUX.csv index 684623a..cf31c27 100644 --- a/data/synthetic_case/DEEP_GW_TO_CHANNEL_FLUX.csv +++ b/data/synthetic_case/DEEP_GW_TO_CHANNEL_FLUX.csv @@ -8759,3 +8759,8787 @@ 6.232735232121734e-07,2.178071891734135e-12,3.144966443770472e-05 6.227255137936539e-07,2.1712040343402353e-12,3.1475797422181305e-05 6.221780144412504e-07,2.1643578329566538e-12,3.150041645189934e-05 +6.216310246305935e-07,2.1575332187495634e-12,3.1529889364943984e-05 +6.210845438379399e-07,2.1507301228851364e-12,3.157729134991277e-05 +6.205385715401724e-07,2.143948478749991e-12,3.163312199473833e-05 +6.199931072148024e-07,2.137188219730746e-12,3.17405875122693e-05 +6.194481503399563e-07,2.1304492747731276e-12,3.187171965734627e-05 +6.189037003943931e-07,2.1237315817046466e-12,3.2008322266300935e-05 +6.183597568574895e-07,2.1170350694710295e-12,3.21469912528923e-05 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diff --git a/data/synthetic_case/config.yml b/data/synthetic_case/config.yml index a28474b..da71cf5 100644 --- a/data/synthetic_case/config.yml +++ b/data/synthetic_case/config.yml @@ -34,19 +34,20 @@ data: json_params_dir: ${data.data_dir}\cat_{}_bmi_config_cfe.json partition_scheme: Schaake start_time: '2010-10-01 00:00:00' - end_time: '2011-09-30 23:00:00' + end_time: '2012-09-30 23:00:00' models: hyperparameters: - epochs: 10 - learning_rate: 1 + epochs: 30 + learning_rate: 0.01 warmup: 2000 step_size: 1 - gamma: 0.7 + gamma: 0.92 mlp: - hidden_size: 6 + hidden_size: 256 num_attrs: 3 num_params: 2 num_states: 2 + lag_hrs: 24 transformation: Cgw: - 1.8e-06 @@ -56,4 +57,4 @@ models: - 0.000726 initial_params: Cgw: 0.000255 - satdk: 1.82e-08 + satdk: 0.0182 diff --git a/data/synthetic_case/land_surface_water__runoff_depth.csv b/data/synthetic_case/land_surface_water__runoff_depth.csv index 6698b0f..de9cd1c 100644 --- a/data/synthetic_case/land_surface_water__runoff_depth.csv +++ b/data/synthetic_case/land_surface_water__runoff_depth.csv @@ -8759,3 +8759,8787 @@ 6.279729118061375e-07,2.178071891734135e-12,5.379061694196822e-05 6.237324438719915e-07,2.1712040343402353e-12,5.52049873557595e-05 6.23184944519588e-07,2.1643578329566538e-12,5.659543964322075e-05 +6.216310246305935e-07,2.1575332187495634e-12,5.828095486897019e-05 +6.210845438379399e-07,2.1507301228851364e-12,6.28777981916165e-05 +6.205385715401724e-07,2.143948478749991e-12,6.479479833276387e-05 +6.199931072148024e-07,2.137188219730746e-12,9.096791939120006e-05 +6.194481503399563e-07,2.1304492747731276e-12,9.571122587071211e-05 +6.189037003943931e-07,2.1237315817046466e-12,9.156276932800824e-05 +1.4591182405733348e-06,2.1170350694710295e-12,8.639136840523516e-05 +1.2443817231425296e-06,2.110359671458895e-12,8.242206923392864e-05 +1.0072861925347922e-06,2.103705323275307e-12,7.88430048577899e-05 +8.120906740560862e-07,2.0970719583068845e-12,7.747077665340312e-05 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+2012-09-30 23:00:00,0.11034128345119648,0.0003017736246735016,0.011471870673387957 diff --git a/src/agents/DifferentiableCFE.py b/src/agents/DifferentiableCFE.py index 2e23e72..dab8f0e 100644 --- a/src/agents/DifferentiableCFE.py +++ b/src/agents/DifferentiableCFE.py @@ -24,7 +24,7 @@ from data.metrics import calculate_nse from models.dCFE import dCFE from utils.ddp_setup import find_free_port, cleanup - +import shutil log = logging.getLogger("agents.DifferentiableCFE") @@ -89,8 +89,9 @@ def create_output_dir(self): current_date = datetime.now().strftime("%Y-%m-%d") dir_name = f"{current_date}_output" output_dir = os.path.join(self.cfg.output_dir, dir_name) - if not os.path.exists(output_dir): - os.makedirs(output_dir) + if os.path.exists(output_dir): + shutil.rmtree(output_dir) + os.makedirs(output_dir) return output_dir def run(self): @@ -130,7 +131,6 @@ def train(self) -> None: for epoch in range(1, self.cfg.models.hyperparameters.epochs + 1): # TODO: Loop through basins - # Run dCFE for all basins ... log.info(f"Epoch #: {epoch}/{self.cfg.models.hyperparameters.epochs}") self.loss_record[epoch - 1] = self.train_one_epoch() self.current_epoch += 1 @@ -282,12 +282,17 @@ def save_loss(self): df.to_csv(file_path) fig, axes = plt.subplots() - axes.plot(self.loss_record, "-") + # Create the x-axis values + epoch_list = list(range(1, len(self.loss_record) + 1)) + + # Plotting + fig, axes = plt.subplots() + axes.plot(epoch_list, self.loss_record, "-") axes.set_title( f"Initial learning rate: {self.cfg.models.hyperparameters.learning_rate}" ) axes.set_ylabel("loss") - axes.set_xlabel("epoch-1") + axes.set_xlabel("epoch") fig.tight_layout() plt.savefig(os.path.join(self.output_dir, f"final_result_loss.png")) plt.close() @@ -316,9 +321,6 @@ def save_result(self, y_hat, y_t, out_filename, plot_figure=False): for i, basin_id in enumerate(self.data.basin_ids): # Save the timeseries of runoff and the best dynamic parametersers - # TODO: Save Cgw and satdk later - # "Cgw": Cgw[i, warmup:], - # "satdk": satdk_[i, warmup:], data = { "y_hat": y_hat[i, warmup:].squeeze(), "y_t": y_t[i, warmup:].squeeze(), @@ -335,8 +337,12 @@ def save_result(self, y_hat, y_t, out_filename, plot_figure=False): # Plot eval_metrics = he.evaluator(he.kge, y_hat[i], y_t[i])[0] fig, axes = plt.subplots(figsize=(5, 5)) - axes.plot(y_t[i, warmup:], "-", label="eval (synthetic)", alpha=0.5) - axes.plot(y_hat[i, warmup:], "--", label="sim (recovery)", alpha=0.5) + if self.cfg.run_type == "ML_synthetic_test": + eval_label = "evaluation (synthetic)" + elif self.cfg.run_type == "ML": + eval_label = "observed" + axes.plot(y_t[i, warmup:], "-", label=eval_label, alpha=0.5) + axes.plot(y_hat[i, warmup:], "--", label="predicted", alpha=0.5) axes.set_title(f"Classic (KGE={float(eval_metrics):.2})") plt.legend() plt.savefig( diff --git a/src/config.yaml b/src/config.yaml index 0d0bef2..d618bda 100644 --- a/src/config.yaml +++ b/src/config.yaml @@ -13,6 +13,9 @@ num_processes: 1 ################## CHANGE HERE ####################### run_type: ML # Choose from: "generate_synthetic" or "ML" or "ML_synthetic_test" +# ML: runn ML against observed data +# ML_synthetic_test: runn ML against synthetic data +# generate_synthetic: generate synthetic data for ML_synthetic_test soil_scheme: classic # Choose from: "ode" or "classic" ###################################################### diff --git a/src/data/Data.py b/src/data/Data.py index 974547a..166b592 100644 --- a/src/data/Data.py +++ b/src/data/Data.py @@ -121,8 +121,7 @@ def get_observations(self, cfg: DictConfig): obs_q_ = pd.read_csv(cfg.data.compare_results_file.format(basin_id)) obs_q_.set_index(pd.to_datetime(obs_q_["date"]), inplace=True) q = torch.tensor( - obs_q_["QObs(mm/h)"][self.start_time : self.end_time].copy().values - / cfg.conversions.m_to_mm, + obs_q_["QObs(mm/h)"][self.start_time : self.end_time].copy().values, device=cfg.device, ) y_ = torch.stack([q]) diff --git a/src/models/config/base.yaml b/src/models/config/base.yaml index 1f285be..63bfa13 100644 --- a/src/models/config/base.yaml +++ b/src/models/config/base.yaml @@ -1,5 +1,5 @@ hyperparameters: - epochs: 3 #1000 #50 + epochs: 30 #1000 #50 learning_rate: 1.0e-2 #0.1 # 0.001 warmup: 2000 step_size: 1