update feature backend when lat/lon empty, store URL

add_new_features.py

@@ -0,0 +1,38 @@
+## Developer Note: Update Pydar's backend when new features are updated
+## New offically named features: https://planetarynames.wr.usgs.gov/#nomenclature-news
+import pydar
+import os
+import pandas as pd
+
+if __name__ == "__main__":
+	os.system('python pydar/updateCsvCORADARJPLOptions.py.py')
+	os.system('python pydar/updateCsvFeatureNameDetails.py')
+	os.system('python pydar/updateCsvSwathCoverage.py.py')
+
+	print("New Features (diff):")
+	os.system("git diff pydar/data/feature_name_details.csv | grep '^[+-][^+-]'")
+
+	# read in all feature names from CSV
+	features_df = pd.read_csv("pydar/data/feature_name_details.csv")
+	features_in_csv = list(features_df["Feature Name"])
+
+	# list of all features that exist (with both latitude/longitude values)
+	retrieved_features = pydar.retrieveFeaturesFromLatitudeLongitudeRange(min_latitude=-90, max_latitude=90, min_longitude=0, max_longitude=360)
+
+	# check if all features in CSV have both latitude/longitude values
+	if not features_in_csv == retrieved_features: 
+		print("\nMissing features to Fix or Ignore:")
+		all_missing_features = [x for x in features_in_csv if x not in retrieved_features]
+		for feature_missing in all_missing_features:
+			print(feature_missing)
+			feature_row = features_df[features_df["Feature Name"] ==  feature_missing]
+			missing_lat_long = feature_row.columns[feature_row.isna().any()].tolist()
+			print(f"\tMissing: {missing_lat_long}")
+			print(f"\t{feature_row['URL'].iloc[0]}")
+
+	print("\nAll features in CSV with latitude/longitude values")
+	print("New Total Feature List to Copy in README and Test:")
+	print(retrieved_features)
+	print("Update README.md")
+	print("Update 'feature_name_full_list' in pydar/pytests/test_error_retrieve_ids_by_time_position.py")
+	print("Run: python -m pytest")

pydar/retrieve_ids_by_time_position.py

@@ -28,6 +28,7 @@ def latitudeLongitudeWithFeatureNameFromCSV():
 	flyby_dataframe = pd.read_csv(flyby_csv_file)
 
 	for index, row in flyby_dataframe.iterrows():
+		if not pd.isnull(row).any(): # ignore rows where Latitude/Longitude are empty
 			feature_name_dict[row["Feature Name"]] = {"Southmost Latitude": row["Southmost Latitude"],
 													"Northmost Latitude": row["Northmost Latitude"], 
 													"Eastmost Longitude": row["Eastmost Longitude"], 

pydar/updateCsvFeatureNameDetails.py

@@ -62,11 +62,13 @@ def updateCsvFeatureNameDetails():
 		logger.info(f"[{i+1}/{len(ahref_lst)}] Retrieving: {base_url + feature_ahref}")
 		soup = BeautifulSoup(feature_html, 'html.parser')
 		tables = soup.find_all('table', class_='usa-table')
+		# [Feature Name, Northmost Latitude, Southmost Latitude, Eastmost Longitude, Westmost Longitude, Center Latitude, Center Longitude, URL]
 		feature_object = [None, None, None, None, None, None, None, None]
 		for table in tables:
 			for row in table.tbody.find_all("tr"):
 				feature_row = ((row.text).lstrip()).split("\n")
 				feature_row = [f.strip() for f in feature_row if f != '' and re.search(r'[a-zA-Z-?\d+]', f)]
+				feature_object[7] = base_url + feature_ahref
 				if len(feature_row) == 2:
 					if feature_row[0] == "Feature Name":
 						feature_object[0] = feature_row[1]
@@ -82,8 +84,6 @@ def updateCsvFeatureNameDetails():
 						feature_object[5] = feature_row[1].split(" ")[0]
 					if feature_row[0] == "Center Longitude":
 						feature_object[6] = feature_row[1].split(" ")[0]
-					if feature_row[0] == "Origin":
-						feature_object[7] = feature_row[1]
 		feature_options.append(feature_object)
 
 	# Add Huygens landing site manually
@@ -94,7 +94,7 @@ def updateCsvFeatureNameDetails():
 							"167.547",
 							"-10.576",
 							"167.547",
-							"where the Huygens probe landed east Adiri"]
+							"https://pds-imaging.jpl.nasa.gov/documentation/Cassini_RADAR_Users_Guide_2nd_Ed_191004_cmp_200421.pdf#page=165"]
 	feature_options.append(huygens_landing_site)
 
 	# Write to CSV
@@ -105,7 +105,7 @@ def updateCsvFeatureNameDetails():
 					"Westmost Longitude",
 					"Center Latitude",
 					"Center Longitude", 
-					"Origin of Name"]
+					"URL"]
 	df = pd.DataFrame(feature_options, columns=header_options)
 	df = df.sort_values(by=["Feature Name"])
 	df.to_csv(os.path.join(os.path.dirname(__file__), 'data', 'feature_name_details.csv'), header=header_options, index=False)