comments addressed

src/bmi_DAforcing.py

@@ -132,6 +132,7 @@ def initialize(self, bmi_cfg_file=None):
         self._values['reservoir_usace_df'] = self._model._reservoir_usace_df
         self._values['rfc_timeseries_df'] = self._model._rfc_timeseries_df
 
+        self._values['write_lite_restart'] = self._model._write_lite_restart
         if not self._model._lastobs_df.empty:
             self._values['lastobs_df'] = self._model._lastobs_df.values.flatten()
             self._values['lastobs_df_ids'] = self._model._lastobs_df.index

src/model_DAforcing.py

@@ -21,7 +21,7 @@ def __init__(self, bmi_cfg_file=None):
         """
         __slots__ = ['_data_assimilation_parameters', '_forcing_parameters', '_compute_parameters',
                      '_output_parameters', '_usgs_df', 'reservoir_usgs_df', 'reservoir_usace_df', 
-                     '_rfc_timeseries_df', '_lastobs_df', '_t0', '_q0', '_waterbody_df']
+                     '_rfc_timeseries_df', '_lastobs_df', '_t0', '_q0', '_waterbody_df', '_write_lite_restart']
 
         if bmi_cfg_file:
             (compute_parameters,
@@ -34,9 +34,9 @@ def __init__(self, bmi_cfg_file=None):
             self._forcing_parameters = forcing_parameters
             self._data_assimilation_parameters = data_assimilation_parameters
             self._output_parameters = output_parameters
-
+            
             self._t0 = self._compute_parameters['restart_parameters']['start_datetime']
-
+            self._write_lite_restart = 0
             #############################
             # Read DA files:
             #############################
@@ -316,18 +316,19 @@ def run(self, values: dict):
         """
         output_parameters = self._output_parameters
         da_parameters = self._data_assimilation_parameters
-
+        write_lite_restart = values.get('write_lite_restart')
         q0 = values.get('q0')
         waterbody_df = values.get('waterbody_df')
         lastobs_df = values.get('lastobs_df')
-        if len(q0) != 0 and len(waterbody_df) != 0 and len(lastobs_df) != 0:
-            if output_parameters['lite_restart'] is not None:
+
+        if write_lite_restart == 1:
+            if output_parameters and output_parameters['lite_restart'] is not None:
                 _write_lite_restart(
                     values,
                     self._t0,
                     output_parameters['lite_restart']
                 )   
-
+            values['write_lite_restart'] = 0
         lastobs_output_folder = da_parameters.get('streamflow_da',{}).get('lastobs_output_folder', None)
         if lastobs_output_folder:
             _write_lastobs(
@@ -336,7 +337,6 @@ def run(self, values: dict):
                 lastobs_output_folder
             )
 
-        # if output_parameters.get('stream_output',{}) is not None and output_parameters.get('stream_output',{}).get('qvd_nudge'):
         if output_parameters.get('stream_output',{}):
 
             t0 = self._t0
@@ -1109,16 +1109,17 @@ def write_flowveldepth_netcdf(values,
     new_order = [(i, attr) for i in range(nsteps) for attr in ['q', 'v', 'd', 'ndg']]
     # Reorder the columns
     qvd_ndg = qvd_ndg[new_order]
-    # renaming the columns based on timestamp
-    column_name_timeStamp = [t0 + timedelta(minutes=(i * 5)) for i in range(nsteps)]
-    new_column_name_timeStamp = [(attr + '_' +str(cnt) + '_' + times.strftime('%Y%m%d%H%M')) for cnt, times in enumerate(column_name_timeStamp) for attr in ['q', 'v', 'd', 'ndg']]
-    qvd_ndg.columns = new_column_name_timeStamp
 
     hr = values.get('t-route_model_time') // 3600 - 1
     # Create time step values based on t0
     time_steps = [t0 + timedelta(hours= hr)]
     time_dim = [t * stream_output_internal_frequency*60 for t in range(1, int(1 * 60 / stream_output_internal_frequency) + 1)]
 
+    # renaming the columns based on timestamp
+    column_name_timeStamp = [t0 + timedelta(hours= hr) + timedelta(minutes=(i * 5)) for i in range(nsteps)]
+    new_column_name_timeStamp = [(attr + '_' +str(cnt) + '_' + times.strftime('%Y%m%d%H%M')) for cnt, times in enumerate(column_name_timeStamp) for attr in ['q', 'v', 'd', 'ndg']]
+    qvd_ndg.columns = new_column_name_timeStamp
+
     for counter, i in enumerate(range(0, nsteps, nstep_nc)):
         # Define the range of columns for this file
         start_col = i * 4
@@ -1130,7 +1131,7 @@ def write_flowveldepth_netcdf(values,
         columns_to_keep = [col for col in qvd_ndg.columns[start_col:end_col] if int(col.split('_')[1]) % selected_col == 0]
         subset_df = qvd_ndg[columns_to_keep]
         subset_df.columns = ['_'.join([col.split('_')[0], col.split('_')[2]]) for col in subset_df.columns]
-
+        
         # Create the file name based on the current time step
         current_time_step = time_steps[counter].strftime('%Y%m%d%H%M')
         if stream_output_directory:

test/LowerColorado_TX_v4/run_all_configs_with_BMI_V2.py → test/LowerColorado_TX_v4/run_with_BMI.py

@@ -1,11 +1,8 @@
 import sys
 import os
-import glob
 import numpy as np
 import pandas as pd
-import geopandas as gpd
-import pickle
-from datetime import datetime, timedelta
+from datetime import timedelta
 import time
 
 # Compute the base path relative to this script's location
@@ -14,7 +11,6 @@
 t_route_src_path = os.path.join(script_dir, '../../', 'src')
 sys.path.append(os.path.abspath(t_route_src_path))
 
-
 import bmi_troute
 import bmi_DAforcing
 import model_DAforcing
@@ -107,6 +103,7 @@ def run_troute(config):
 
             DAforcing.set_value('waterbody_df', troute.get_value('waterbody_df'))
             DAforcing.set_value('waterbody_df_ids', troute.get_value('waterbody_df_index'))
+            DAforcing.set_value('write_lite_restart', 1)
 
             DAforcing.set_value('lastobs_df', troute.get_value('lastobs_df'))
             DAforcing.set_value('lastobs_df_ids', troute.get_value('lastobs_df_index'))