# update with reviews comments

# counties.zip: delete unnecessary county json file which contains all the county and make the zip file containing the json file directly without a container folder

src/data/README.md

@@ -6,19 +6,19 @@ SAS reference implementation.
 ## Geo Data for propagation models and county
 
 The geo data used by propagation models are stored 
-in Git LFS (Large File Storage) on the [separate SAS-Data WinnForum repository](https://github.com/Wireless-Innovation-Forum/SAS-Data).
+in Git LFS (Large File Storage) on the [separate Common-Data WinnForum repository](https://github.com/Wireless-Innovation-Forum/Common-Data).
 
 ### Integration
 
 The process to plug the data into the environment is:
 
- - Clone the [`SAS-Data`]((https://github.com/Wireless-Innovation-Forum/SAS-Data)
+ - Clone the [`SAS-Data`]((https://github.com/Wireless-Innovation-Forum/Common-Data)
  repository.
  - Unzip the files, by using the `extract_geo.py` script provided in that repository.
  - Point your reference models to that repository, by one of the following options:
    + create soft links for:
-      * `data/geo/ned` -> `SAS_Data/ned`
-      * `data/geo/nlcd` -> SAS_Data/nlcd`
+      * `data/geo/ned` -> `Common_Data/ned`
+      * `data/geo/nlcd` -> Common_Data/nlcd`
    + or modify geo pointers in file `reference_models/geo/CONFIG.py`
 
 ### Process for creating NED terrain database
@@ -40,7 +40,7 @@ Tiles are simply retrieved using the two scripts:
   - `retrieve_alaska_ned_extra.py`: complete the previous set with missing Alaska tiles
     using Alaska 2-arcsec database and a resampling to 1 arcsec. 
     Final tiles are put in a folder `data/geo/ned_out2/'
-  - add manually the data in SAS-Data repository
+  - add manually the data in Common-Data repository
 
 Please note that these 2 scripts keep track of the original downloaded data in 
 directories `data/geo/orig_ned` and `data/geo/orig_ned2`. Subsequent run of the script

src/harness/reference_models/geo/README.md

@@ -9,7 +9,7 @@ models:
  - `vincenty.py`: precise methods for deriving geodesic between two points in the earth
  modeled as ellipsoid
  - `utils.py`: utility routines for computing polygon area, gridding a polygon, etc..
- - `county.py`: county driver to read JSON coutnies geometries.
+ - `county.py`: county driver to read JSON counties geometries.
  - `tiles.py`: list of all expected tiles, for proper error management of IO issues
  - `drive.py`: maintains the singleton drivers to all database
  - `zones.py`: provide access to all zone files provided in KML format.

src/harness/reference_models/ppa/ppa_test.py

@@ -98,7 +98,7 @@ def test_ClippedPpaByCountyWithSmallHoles(self):
     ppa_zone = json.loads(ppa_zone)
 
     county_zone = utils.ToShapely(
-        drive.county_driver.GetCounty('06027000100')
+        drive.county_driver.GetCounty('06027')
         ['features'][0]['geometry'])
     self.assertTrue(utils.ToShapely(ppa_zone).buffer(-1e-6).within(county_zone))
 

src/harness/reference_models/ppa/test_data/pal_record_0.json

@@ -1,6 +1,6 @@
 {
-  "censusYear": 2010,
-  "fipsCode": 123456789,
+  "censusYear": 2017,
+  "fipsCode": 12345,
   "licensee": "CBSD Operator No.1",
   "registrationInformation": {
     "frn": "test_fcc_frn_pal_0",

src/harness/reference_models/ppa/test_data/pal_record_1.json

@@ -1,6 +1,6 @@
 {
-  "censusYear": 2010,
-  "fipsCode": 111111111,
+  "censusYear": 2017,
+  "fipsCode": 11111,
   "licensee": "CBSD Operator No.1",
   "registrationInformation": {
     "frn": "test_fcc_frn_pal_0",

src/harness/reference_models/ppa/test_data/pal_record_2.json

@@ -1,6 +1,6 @@
 {
-  "censusYear": 2010,
-  "fipsCode": "06027000100",
+  "censusYear": 2017,
+  "fipsCode": "06027",
   "licensee": "CBSD Operator No.1",
   "registrationInformation": {
     "frn": "test_fcc_frn_pal_0",