Merge branch 'Sentinenl_hub_integration'

# Conflicts:
#	README.md
#	server/ModelFromNVE/icemodellingscripts/getIceThicknessLakes.py

README.md

@@ -174,6 +174,16 @@ should be updated to contain the newly added lake name.
 ![img.png](images/resulting-files.png)
 
 
+#### Adding an aree for ice run dates
+When adding a lake, a bounding box should also be added inside the ```/server/Sentinelhub/box.json``` file. To view and add new boxes copy and paste the current boxes into sentinel-hub.com/eo-browser, then mark a new area. Make sure the are covers an sufficient area (at least 1 km^2).
+
+![img.png](images/sentinelhub_adding_bboxes.png)
+![img.png](images/selecting-bbox.png)
+
+When updating the ice run dates, the corresponding files will be automatically created.
+This is necessary to do when creating a new lake, but can also be to add more boxes for large lakes. 
+
+
 ### Add test data
 ```
 Method: GET
@@ -241,4 +251,5 @@ This software was developed by Joakim Aleksandersen, Sara Savanovic Djordjevic,
 and Hoa Ben The Nguyen.
 
 ## Third-Party Software
-ModelFromNVE is a third party software provided by the Norwegian Energy Regulatory Authority.
\ No newline at end of file
+ModelFromNVE is a third party software provided by the Norwegian Energy Regulatory Authority.
+

server/ModelFromNVE/icemodellingscripts/getIceThicknessLakes.py

@@ -64,11 +64,12 @@ def ice_prognosis_raw_data(to_date=None, sub_div_id=0, x=10.70, y=60.81,
     observed_ice = [first_ice]
 
     # make the x and y into utm 33 from lon lat
-    cords = utm.from_latlon(y, x, 33)
+    cords = utm.from_latlon(x, y, 33)
     x, y = int(cords[0]), int(cords[1])
 
     # check if utm is valid
-    x, y = validate_cords(x, y)
+    if validate_cords(x, y) is False:
+        return None
 
     gridTemp = gts.getgts(x, y, 'tm', from_date, to_date)
     gridSno = gts.getgts(x, y, 'sdfsw', from_date, to_date)
@@ -151,17 +152,16 @@ def validate_cords(easting, northing):
         northing:
 
     Returns:
-        if the easting and northing is not acceptable at utm 33 returns middle of mjosa as new easting and northing values
+        if the easting and northing is not acceptable at utm 33 returns False else true
 
     """
-    default_x, default_y = 266707, 6749365
 
     if not (100000 <= easting <= 900000) or not (0 <= northing <= 10000000):
-        easting, northing = default_x, default_y
+        return False
+
     else:
-        print("cords are kept")
+        return True
 
-    return easting, northing
 
 
 def get_raw_dates(data, from_date=None, to_date=None):
@@ -174,6 +174,9 @@ def get_raw_dates(data, from_date=None, to_date=None):
     Returns:
         returns data for the specified time slot
     """
+    if data is None:
+        return []
+
     if from_date is None:
         from_date = (dt.datetime.now() - dt.timedelta(days=3)).strftime("%Y-%m-%d")
     if to_date is None:
@@ -212,7 +215,7 @@ def jsonify_data(data, name="temp", location=se.plot_folder):
     file_path = os.path.join(location, f"data_{name}.json")
 
     try:
-        with open(file_path, 'w') as json_file:
+        with open(file_path, 'w', encoding='utf-8') as json_file:
             json.dump(data, json_file, indent=4)
         print(f"Data successfully saved to {file_path}")
     except Exception as e:
@@ -239,7 +242,7 @@ def jsonify_data_sub_div_ids(lake_name, sub_div_and_data, location=se.plot_folde
     file_path = os.path.join(location, filename)
 
     try:
-        with open(file_path, 'w') as json_file:
+        with open(file_path, 'w', encoding='utf-8') as json_file:
             json.dump(aggregated_data, json_file, indent=4)
         print(f"All data successfully saved to {file_path}")
     except Exception as e:
@@ -260,7 +263,7 @@ def get_subdiv_ids_n_cords(file_path):
     # reads file and gets all ids and cords at this format [(id, x, y), (id, x, y) ... ]
     id_list = []
 
-    with open(file_path, 'r') as file:
+    with open(file_path, 'r', encoding='utf-8') as file:
         for line in file:
             data = line.strip().split(',')
             if len(data) == 3:
@@ -299,8 +302,12 @@ def update_data(from_date=None, to_date=None, lake_name="skumsjoen",
             # Add the filtered data to the list
             filtered_data_for_dates.append((sub_div_id, filtered_data))
 
+        filtered_data_for_dates.sort(key=lambda x: x[0])
+
         jsonify_data_sub_div_ids(lake_name, filtered_data_for_dates, location=se.plot_folder)
-        return
+        return filtered_data_for_dates
+
+
 
 if __name__ == "__main__":
     ''' 
@@ -321,13 +328,13 @@ if __name__ == "__main__":
     from_date = "2024-01-10"
     to_date = "2024-01-20"
 
-    update_data(from_date, to_date, lake_name="skumsjoen",
+    update_data(from_date, to_date, lake_name="skumsjøen",
                 sub_divs_folder='../../map_handler/lake_relations/skumsjøen_centers.txt', update_all_bboxes=True)
 
     # filtered_data_for_dates = [(i[0], get_raw_dates(ice_prognosis_raw_data(sub_div_id=i[0], x=i[1], y=i[2])), from_date, to_date) for i in sub_divs ]
 
     # without iceruns
-    # filtered_data_for_dates1 = [(i[0], get_raw_dates(ice_prognosis_raw_data(sub_div_id=i[0], x=i[1], y=i[2]), from_date, to_date)) for i in sub_divs ]
+    #filtered_data_for_dates1 = [(i[0], get_raw_dates(ice_prognosis_raw_data(sub_div_id=i[0], x=i[1], y=i[2]), from_date, to_date)) for i in sub_divs ]
 
     #getAreaInfo.update_all_polynomials()
 

server/ModelFromNVE/icemodellingscripts/plotlakes.py

@@ -349,7 +349,7 @@ def run_newsite(from_date, to_date, startmonth, startday, make_plots=True, plot_
 
         # Save to array for check
         # Open an output file
-        outf3 = open('{0}{1}_smelting.txt'.format(plot_folder, location_name), 'w')
+        outf3 = open('{0}{1}_smelting.txt'.format(plot_folder, location_name), 'w', encoding='utf-8')
         outf3.write('maksdato   ')
         for i in range(len(temp)):
             outf3.write(str(date[i]) + f'{temp[i]:6.2f}' + f'{(melt[i]/melt_factor):6.2f}' + '\n')
@@ -451,9 +451,9 @@ if __name__ == "__main__":
     # outf = open('{0}{1}_is_ekstremer.txt'.format(se.plot_folder, location_name), 'w')
 
     # Create csv-file to store solid ice data
-    outf4 = open('{0}{1}_is_fast.csv'.format(se.plot_folder, location_name), 'w')
+    outf4 = open('{0}{1}_is_fast.csv'.format(se.plot_folder, location_name), 'w', encoding='utf-8')
     # Create csv-file to store air temperature data
-    outf5 = open('{0}{1}_lufttemp.csv'.format(se.plot_folder, location_name), 'w')
+    outf5 = open('{0}{1}_lufttemp.csv'.format(se.plot_folder, location_name), 'w', encoding='utf-8')
 
     # Overskrift
     outf.write('Maksdato - Dato for største tykkelse av ett lag solid is\n')

server/ModelFromNVE/utilities/makepickle.py

@@ -30,7 +30,7 @@ def unpickle_anything(file_name_and_path, print_message=True):
     :return something_to_unpickle:
     """
 
-    something_to_unpickle = pickle.load( open(file_name_and_path, 'rb') )
+    something_to_unpickle = pickle.load( open(file_name_and_path, 'rb', encoding='utf-8') )
 
     if print_message is True:
         ml.log_and_print("[info] makepickle.py -> unpickle_anything: {0} unpickled.".format(file_name_and_path))

server/Sentinelhub/box_funcitons.py

@@ -25,7 +25,7 @@ def get_all_box():
     dir_path = os.path.dirname(os.path.realpath(__file__))
     file_path = os.path.join(dir_path, 'box.json')
 
-    with open(file_path, 'r') as file:
+    with open(file_path, 'r', encoding='utf-8') as file:
         data = json.load(file)
 
     box_list = []

server/Sentinelhub/getAreaInfo.py

@@ -78,7 +78,7 @@ def statistical_request_sentinel(config, evalscript, time_interval, maxcc, bbox)
         return None
 
 def classify_ice(data):
-    """ set a label in data based on st deviation >11 cloud, >6 no ice, >2 some ice, <=2 ice"""
+    """ set a label in data based on st deviation"""
 
     ice_conditions = []