Small comment and value changes.

parameters/csv_files/params_samir_min_max.csv

@@ -8,20 +8,20 @@ Koffset,-1,1
 Kcmax,1,1.3
 NDVIsol,0,0.5
 NDVImax,0.3,1
-Zsoil,1,5000
+Zsoil,1,6000
 Ze,1,500
 Init_RU,0,1
 DiffE,0,30
 DiffR,0,30
 REW,0,1000
 minZr,0,2000
-maxZr,0,2000
+maxZr,0,4000
 p,0,1
 FW,0,1
 Irrig_auto,0,1
 Irrig_man,0,1
 Lame_max,0,200
-Lame_min,0,50,
+Lame_min,0,50
 Kcb_min_start_irrig,0,2
 frac_Kcb_stop_irrig,0,1
 frac_TAW,0,1
\ No newline at end of file

preprocessing/lib_era5_land_pixel.py

@@ -474,6 +474,7 @@ def combine_weather2netcdf(rain_file: str, ET0_tile: str, ndvi_path: str, save_p
         encod = {}
         encod['dtype'] = 'u2'
         encod['_FillValue'] = 0
+        # TODO: figure out optimal file chunk size
         file_chunksize = (1, dimensions['y'], dimensions['x'])
         encod['chunksizes'] = file_chunksize
         # TODO: check if compression affects reading speed

source/modspa_samir.py

@@ -76,7 +76,7 @@ def test_samir_parameter(table: pd.DataFrame, min_max_param_file: str) -> pd.Dat
         for class_name in table.columns[1:]:
             
             # Test if parameter is out of range
-            if table.at[parameter, class_name] >= min_max_table.at[parameter, 'max_value'] or table.at[parameter, class_name] <= min_max_table.at[parameter, 'min_value']:
+            if table.at[parameter, class_name] > min_max_table.at[parameter, 'max_value'] or table.at[parameter, class_name] < min_max_table.at[parameter, 'min_value']:
                 
                 # If parameter is out of range, print which parameter and for which class
                 print(f'\nParameter {parameter} is out of range for class {class_name}')
@@ -1447,6 +1447,7 @@ def run_samir(csv_param_file: str, ndvi_cube_path: str, weather_path: str, soil_
             encod['dtype'] = 'i2'
         else:
             encod['dtype'] = 'u2'
+        # TODO: figure out optimal file chunk size
         encod['chunksizes'] = (1, y_size, x_size)
         encoding_dict[variable] = encod