diff --git a/server/ModelFromNVE/icemodellingscripts/getIceThicknessLakes.py b/server/ModelFromNVE/icemodellingscripts/getIceThicknessLakes.py
index cdcd83b82bbd0f09425bca5f61f3a150b2ada2c0..42f05907e1c74abdf40ec98e431f9313b5ab5cfd 100644
--- a/server/ModelFromNVE/icemodellingscripts/getIceThicknessLakes.py
+++ b/server/ModelFromNVE/icemodellingscripts/getIceThicknessLakes.py
@@ -1,4 +1,3 @@
-
import copy
import datetime as dt
import utm
@@ -9,11 +8,41 @@ from server.ModelFromNVE.icemodelling import parameterization as dp, icethicknes
ice as ice
from server.ModelFromNVE.utilities import makeplots as pts, getgts as gts, getwsklima as gws
-def ice_prognosis_raw_data(to_date = None, sub_div_id = 0, met_stnr=0, x=10.709985478463118, y=60.810991171403316, altitude=0, awt=[], mf=0, icerun_dates=[]):
+
+def ice_prognosis_raw_data(to_date=None, sub_div_id=0, x=10.709985478463118, y=60.810991171403316,
+ altitude=0, awt=[], mf=0, icerun_dates=[]):
"""
- lon x
- lat y
- :return:
+
+ Args:
+ to_date: the end date for prognosis season, defaults to seven days into the future
+ sub_div_id:
+ x: lat
+ y: lon
+ altitude: in meters
+ awt: list of avrage water temperatures
+ mf: melt factor used by NVE, not much info on this variable
+ icerun_dates: date for ice of the lake
+
+ Returns:
+ a list of data at this format:
+ [
+ [
+ "Date": date.strftime("%Y-%m-%d"),
+ "Slush ice (m)": round(slush, 3),
+ "Black ice (m)": round(black, 3),
+ "Total ice (m)": round(total, 3),
+ "Snow depth (m)": round(snow2, 3),
+ "Total snow (m)": round(sno_tot2, 3),
+ "Cloud cover": round(cc2, 3),
+ "Temperature (c)": round(temp2, 3)
+ ]
+ ...
+ [
+ ...
+ ]
+ ]
+
+
"""
current_date = dt.datetime.now()
@@ -37,6 +66,9 @@ def ice_prognosis_raw_data(to_date = None, sub_div_id = 0, met_stnr=0, x=10.7099
cords = utm.from_latlon(y, x, 33)
x, y = int(cords[0]), int(cords[1])
+ # check if utm is valid
+ x, y = validate_cords(x, y)
+
gridTemp = gts.getgts(x, y, 'tm', from_date, to_date)
gridSno = gts.getgts(x, y, 'sdfsw', from_date, to_date)
gridSnoTot = gts.getgts(x, y, 'sd', from_date, to_date)
@@ -65,9 +97,9 @@ def ice_prognosis_raw_data(to_date = None, sub_div_id = 0, met_stnr=0, x=10.7099
# cumulated ammount of each ice type at a given date
slush_ice = []
black_ice = []
- total = []
+ total = []
total_ice = []
- dates = []
+ dates = []
for i in calculated_ice:
ice_type = -10
@@ -97,20 +129,51 @@ def ice_prognosis_raw_data(to_date = None, sub_div_id = 0, met_stnr=0, x=10.7099
sno_tot, cc, temp):
daily_data = {
"Date": date.strftime("%Y-%m-%d"),
- "Slush ice (m)": slush,
- "Black ice (m)": black,
- "Total ice (m)": total,
- "Snow depth (m)": snow2,
- "Total snow (m)": sno_tot2,
- "Cloud cover": cc2,
- "Temperature (c)": temp2
+ "Slush ice (m)": round(slush, 3),
+ "Black ice (m)": round(black, 3),
+ "Total ice (m)": round(total, 3),
+ "Snow depth (m)": round(snow2, 3),
+ "Total snow (m)": round(sno_tot2, 3),
+ "Cloud cover": round(cc2, 3),
+ "Temperature (c)": round(temp2, 3)
}
data.append(daily_data)
return data
# return [sub_div_id, x, y, data]
+
+def validate_cords(easting, northing):
+ """
+ Args:
+ easting:
+ northing:
+
+ Returns:
+ if the easting and northing is not acceptable at utm 33 returns middle of mjosa as new easting and northing values
+
+ """
+ default_x, default_y = 266707, 6749365
+
+ if not (100000 <= easting <= 900000) or not (0 <= northing <= 10000000):
+ print("cords given are made default to middle of lake mjosa")
+ easting, northing = default_x, default_y
+ else:
+ print("cords are kept")
+
+ return easting, northing
+
+
def get_raw_dates(data, from_date=None, to_date=None):
+ """
+ Args:
+ data: data from ice_prognosis_raw_data
+ from_date: if not given default to 4 days into future
+ to_date: if not given default to 3 days into the past
+
+ Returns:
+ returns data for the specified time slot
+ """
if from_date is None:
from_date = (dt.datetime.now() - dt.timedelta(days=3)).strftime("%Y-%m-%d")
if to_date is None:
@@ -119,10 +182,22 @@ def get_raw_dates(data, from_date=None, to_date=None):
filtred_data = [entry for entry in data if from_date <= entry["Date"] <= to_date]
return filtred_data
+
# change to take a list of data with an sub div id first followed by data [sub_div_id, data]
-def jsonify_data(data, location=se.plot_folder):
+def jsonify_data(data, name="temp", location=se.plot_folder):
+ """
+
+ Args:
+ data: the data to be put into file
+ name: name of file -> data_{name}.json
+ location: location, default to se.plot_folder
+
+ Returns:
+ creates a .json file
+
+ """
os.makedirs(location, exist_ok=True)
- file_path = os.path.join(location, "data_test_test1.json")
+ file_path = os.path.join(location, f"data_{name}.json")
try:
with open(file_path, 'w') as json_file:
@@ -131,12 +206,24 @@ def jsonify_data(data, location=se.plot_folder):
except Exception as e:
print(f"Failed to save data to JSON file. Error: {e}")
-def jsonify_data_sub_div_ids(sub_div_and_data, location=se.plot_folder):
+
+def jsonify_data_sub_div_ids(lake_name, sub_div_and_data, location=se.plot_folder):
+ """
+
+ Args:
+ lake_name: put as file name {lake_name}_sub_div.json
+ sub_div_and_data: all data at this format [(id, data) ... (...)]
+ location: plot folder defaults to se.plot_folder
+
+ Returns:
+ creates a .json file
+
+ """
aggregated_data = {entry[0]: entry[1] for entry in sub_div_and_data}
os.makedirs(location, exist_ok=True)
- filename = "aggregated_data_test_test.json"
+ filename = f"{lake_name}_sub_div.json"
file_path = os.path.join(location, filename)
try:
@@ -146,9 +233,32 @@ def jsonify_data_sub_div_ids(sub_div_and_data, location=se.plot_folder):
except Exception as e:
print(f"Failed to save data to JSON file. Error: {e}")
-def expose_data()
+
+# def expose_data()
+def get_subdiv_ids_n_cords(file_path):
+ """
+
+ Args:
+ file_path: path of the file with ids lat lon values
+
+ Returns:
+ a list of ids lat lon
+
+ """
+ # 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:
+ for line in file:
+ data = line.strip().split(',')
+ if len(data) == 3:
+ id_list.append((int(data[0]), float(data[1]), float(data[2])))
+
+ return id_list
+
if __name__ == "__main__":
+ '''
data = ice_prognosis_raw_data()
from_date = "2024-01-10"
@@ -156,10 +266,41 @@ if __name__ == "__main__":
filtered_dates = get_raw_dates(data, from_date, to_date)
jsonify_data(filtered_dates)
filtered_dates2 = get_raw_dates(data)
- all_will_be_one = [[1, filtered_dates2], [2, filtered_dates]]
+
+ all_will_be_one = [(1, filtered_dates2), [2, filtered_dates]]
jsonify_data_sub_div_ids(all_will_be_one)
+ '''
- #ice_prognosis()
+ sub_divs = get_subdiv_ids_n_cords('../../lake_relations/skumsjøen_centers.txt') # lokasjon for txt fil
- pass
\ No newline at end of file
+ from_date = "2024-01-10"
+ to_date = "2024-01-20"
+ #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 ]
+ filtered_data_for_dates = [(i[0], get_raw_dates(ice_prognosis_raw_data(sub_div_id=i[0], x=i[1], y=i[2]))) for i in sub_divs ]
+
+ jsonify_data_sub_div_ids("skumsjoen", filtered_data_for_dates, location = se.plot_folder)
+ '''
+ filtered_data_for_dates = []
+
+ # Iterate over each subdivision in the list
+ for subdivision in sub_divs:
+ # Unpack the ID, x-coordinate, and y-coordinate for the subdivision
+ sub_div_id = subdivision[0]
+ x_coordinate = subdivision[1]
+ y_coordinate = subdivision[2]
+
+ # Fetch the raw data for the subdivision
+ raw_data = ice_prognosis_raw_data(sub_div_id=sub_div_id, x=x_coordinate, y=y_coordinate) # <- problem
+
+ # Filter the raw data based on the specified date range
+ filtered_data = get_raw_dates(raw_data, from_date, to_date)
+
+ # Add the filtered data to the list
+ filtered_data_for_dates.append(filtered_data)
+ '''
+ print("hello world")
+
+ # ice_prognosis()
+
+ pass