Added first function to download AIS data from Kystverket

wavy/ais_module.py

@@ -0,0 +1,83 @@
+from wavy.credentials import credentials_from_netrc
+import requests
+import xarray as xr
+import pandas as pd
+import os
+import json
+
+
+def get_AIS_data(bbox, sd, ed, minspeed=0.5):
+    '''
+    Args:
+        bbox: list of strings [lon min, lat min,
+                               lon max, lat max]
+        sd, ed: start and end dates, as strings
+                under "yyyymmddHHMM" format
+    '''
+    # get token
+    auth = credentials_from_netrc('kystdatahuset.no')
+    url = "https://kystdatahuset.no/ws/api/auth/login"
+    data = {"username": auth[0], "password": auth[1]}
+    headers = {'accept': '*/*', 'Content-Type': 'application/json'}
+    response = requests.post(url, json=data, headers=headers, auth=auth)
+    resp_json = response.json()
+    token = resp_json['data']['JWT']
+
+    # prepare curl request
+    curl_com = "curl -X 'POST' "
+    url_req = "'https://kystdatahuset.no/ws/api/ais/positions/within-bbox-time' "
+    head_1 = "-H 'accept: text/plain' "
+    head_2 = "-H 'Authorization: Bearer " + token + "' "
+    head_3 = "-H 'Content-Type: application/json' "
+
+    dict_data = {
+                 "bbox": ",".join(bbox),
+                 "start": sd,
+                 "end": ed,
+                 "minSpeed": minspeed
+                }
+
+    data = "-d '" + str(dict_data).replace("'", '"') + "'"
+
+    curl_request = curl_com + url_req + head_1 + head_2 + head_3 + data
+
+    # get result content of curl request
+    stream = os.popen(curl_request)
+    output = stream.read()
+    dict_output = json.loads(output)
+
+    df_request = pd.DataFrame(
+        data=dict_output["data"],
+        columns=["mmsi", "datetime", "lon",
+                 "lat", "x1", "x2", "x3", "x4",
+                 "x5", "x6"])
+
+    # Get ship info
+    unique_mmsi = [int(mm) for mm in df_request["mmsi"].unique()]
+    url_ships_nsr = 'https://kystdatahuset.no/ws/api/ship/data/nsr/for-mmsis-imos'
+    json_ships_nsr = {"mmsi": unique_mmsi, "imo": [], "callsign": []}
+    headers_ships_nsr = {'accept': 'test/plain',
+                         'Content-Type': 'application/json'}
+    response_ships_nsr = requests.post(url_ships_nsr,
+                                       json=json_ships_nsr,
+                                       headers=headers_ships_nsr)
+    resp_ships_json_nsr = response_ships_nsr.json()
+    ships_df = pd.DataFrame(resp_ships_json_nsr['data'])
+    ships_df = ships_df[['mmsino', 'grosstonnage', 'dwt', 'length',
+                         'breadth', 'draught', 'shiptypeeng']]
+
+    # Merge the two dataframes
+    df_merge = pd.merge(df_request, ships_df, left_on="mmsi",
+                        right_on="mmsino", how="left")
+    df_merge = df_merge[['mmsi', 'datetime', 'lon', 'lat',
+                         'grosstonnage', 'dwt', 'length', 'breadth',
+                         'draught', 'shiptypeeng']]
+    df_merge = df_merge.rename(columns={'lon': 'lons', 'lat': 'lats',
+                                        'datetime': 'time'})
+
+    # Turn the dataframe into a dataset
+    df_merge['time'] = pd.to_datetime(df_merge['time'])
+    ds = df_merge.set_index(['time'])
+    ds = ds.to_xarray().sortby("time")
+
+    return ds