Added lookup zip creator code lipimpacts.py

mdx/granule_metadata_extractor/src/helpers/creators/lipimpacts.py

@@ -0,0 +1,82 @@
+# Create lookup zip for lipimpacts
+# for all future collections
+from datetime import datetime, timedelta
+from utils.mdx import MDX
+import cProfile
+import time
+import math
+import re
+
+short_name = "lipimpacts"
+provider_path = "lipimpacts/fieldCampaigns/impacts/LIP/data/"
+file_type = "ASCII"
+
+
+class MDXProcessing(MDX):
+
+    def __init__(self):
+        super().__init__()
+
+    def process(self, filename, file_obj_stream) -> dict:
+        """
+        Individual collection processing logic for spatial and temporal 
+        metadata extraction
+        :param filename: name of file to process
+        :type filename: str
+        :param file_obj_stream: file object stream to be processed
+        :type file_obj_stream: botocore.response.StreamingBody
+        """
+        return self.read_metadata_ascii(filename, file_obj_stream)
+
+    def read_metadata_ascii(self,filename, file_obj_stream):
+        """
+        Extract temporal and spatial metadata from ascii files
+        """
+        lines = []
+        for encoded_line in file_obj_stream.iter_lines():
+            lines.append(encoded_line.decode("utf-8"))
+
+        dt = []
+        lat = []
+        lon = []
+
+        #First line is the header beginning with 'Time'
+        for i in range(1,len(lines)):
+            tkn = lines[i].split() #tkn[0] i.e., '23-Feb-2020T13:16:00.000''
+            if 'NaN' in [tkn[8], tkn[9]]:
+               continue #ignore this data line
+            else:
+               dt.append(datetime.strptime(tkn[0],'%d-%b-%YT%H:%M:%S.%f'))
+               lat.append(float(tkn[8]))
+               lon.append(float(tkn[9]))
+
+        minTime = min(dt)
+        maxTime = max(dt)
+        maxlat = max(lat)
+        minlat = min(lat)
+        maxlon = max(lon)
+        minlon = min(lon)
+
+        return {
+            "start": minTime,
+            "end": maxTime,
+            "north": maxlat,
+            "south": minlat,
+            "east": maxlon,
+            "west": minlon,
+            "format": file_type
+        }
+
+    def main(self):
+        # start_time = time.time()
+        self.process_collection(short_name, provider_path)
+        # elapsed_time = time.time() - start_time
+        # print(f"Elapsed time in seconds: {elapsed_time}")
+        self.shutdown_ec2()
+
+
+if __name__ == '__main__':
+    MDXProcessing().main()
+    # The below can be use to run a profiler and see which functions are
+    # taking the most time to process
+    # cProfile.run('MDXProcessing().main()', sort='tottime')