cmougan#10, cmougan#20 Adds information for command line app for nig…

…ht lights to README.md

README.md

@@ -257,15 +257,18 @@ Add [this](https://github.com/cmougan/WRI_WellBeing_Data_Layer) repository as a
 
 For further instructions for setting up, please follow the steps [here](./dssg/README.md)
 ### Main Components
-The main modules are as follows:
-- `osm_data_extraction` module, which has the following features :
+The main components are as follows:
+- Module `osm_data_extraction`, which has the following features :
   - Extract GeoDataFrame of a district from a country GADM Level 2 shapefile.
   - Plots the boundary of a given district along with the corresponding map tile from Open Street Maps.
   - Retrieves and writes the map tile corresponding to the geo dataframe to a geotiff file.
   - Plots a geotiff file.
   - Creates the polygon and the corresponding graph for a given geo dataframe of a district. This is finally used to visualize the knots and edges model.
   - A dictionary of tags, `default_tags = {amenity': True, 'building': True, 'emergency': True,
                 'highway': True, 'footway': True, 'landuse': True, 'water': True}` is used to extract relevant features and ammenities from the OSM API for a given district. 
+
+- Module `ntl_data_extraction` and command line app `download-nightlights.py`
+  - The command line app uses the methods in the module to download night time light hdf5 files for a given district and a specific time range and convert them to geotiff format. Since the hdf5 files cover a large area and may contain many districts we have added a check and it is downloaded only if it has not been downloaded earlier for another district. 
 ### Contribution Guidelines
 In general we follow the [GitHub Forking Workflow](https://guides.github.com/activities/forking/)
 #### On GitHub

dssg/dataio/ntl_data_extraction.py

@@ -9,7 +9,16 @@
 from gdalconst import *
 
 
-def download_url(url: str):
+def download_url(url: str) -> str:
+    """Given a url for h5 file checks if the file exists in the pre-defined NTL_HDF5_DIR
+    and downloads it if it does not exist.
+
+    Args:
+        url (str): web url of the hdf5 file
+
+    Returns:
+        str: url
+    """
     print("downloading: ", url)
     # assumes that the last segment after the / represents the file name
     filepath = os.environ.get("NTL_HDF5_DIR")
@@ -25,7 +34,21 @@ def download_url(url: str):
     return url
 
 
-def get_ntl_file_urls(district_gdf: gpd.geodataframe.GeoDataFrame, products: str, startTime: str, endTime: str, collection: int, district_json_file: str):
+def get_ntl_file_urls(district_gdf: gpd.geodataframe.GeoDataFrame, products: str, startTime: str, endTime: str,
+                      collection: int, district_json_file: str) -> list:
+    """Given a district geo dataframe and a specific product 
+
+    Args:
+        district_gdf (gpd.geodataframe.GeoDataFrame): [description]
+        products (str): [description]
+        startTime (str): [description]
+        endTime (str): [description]
+        collection (int): [description]
+        district_json_file (str): [description]
+
+    Returns:
+        list: [description]
+    """
     (w, s, e, n) = ode.district_extents(district_gdf)
     # Create a ModapsClient object
     a = modapsclient.ModapsClient()