Parallel extract/filter OS data

.gitignore

@@ -11,3 +11,4 @@ app/start.sh
 etl/cache/*
 etl/images/*
 etl/*.geojson
+etl/*.txt

etl/0_extract_addressbase.py

@@ -1,54 +0,0 @@
-"""Extract address points from CSV in *.zip
-
-Relevant CSV columns::
-0 - UPRN
-1 - TOID (may not match given version of OS MasterMap)
-16 - OSGB Easting
-17 - OSGB Northing
-18 - Latitude
-19 - Longitude
-"""
-import csv
-import glob
-import io
-import os
-import sys
-from zipfile import ZipFile
-
-def main(source_dir, output_file):
-    with open(output_file, 'w', encoding='utf8', newline='') as fh:
-        w = csv.writer(fh)
-        w.writerow(('UPRN', 'easting', 'northing', 'lat', 'lng'))
-        for address in read_addresses(source_dir):
-            w.writerow(address)
-
-
-def read_addresses(source_dir):
-    zips = glob.glob(os.path.join(source_dir, '*.zip'))
-    n = len(zips)
-    for i, zipname in enumerate(zips):
-        with ZipFile(zipname) as zipfile:
-            names = zipfile.namelist()
-            csvname = names[0]
-            print("Processing {} ({} of {})".format(csvname, i+1, n))
-
-            with zipfile.open(csvname) as csvfile:
-                fh = io.TextIOWrapper(csvfile)
-                r = csv.reader(fh)
-                for line in r:
-                    uprn = line[0]
-                    # toid = line[1]  # skip - we do our own matching to geometries
-                    easting = line[16]
-                    northing = line[17]
-                    lat = line[18]
-                    lng = float(line[19])
-                    yield uprn, easting, northing, lat, lng
-
-
-if __name__ == '__main__':
-    if len(sys.argv) != 3:
-        print("Usage: {} ./path/to/source/dir ./path/to/output/file".format(
-            os.path.basename(__file__)
-        ))
-        exit()
-    main(sys.argv[1], sys.argv[2])

etl/0_extract_addressbase.sh

@@ -0,0 +1,40 @@
+#!/usr/bin/env bash
+
+#
+# Extract address points from OS Addressbase GML
+# - as supplied in 5km tiles, zip/gz archives
+#
+: ${1?"Usage: $0 ./path/to/data/dir"}
+
+data_dir=$1
+
+#
+# Unzip to GML
+#
+
+# find $data_dir -name '*.zip' -print0 | xargs -0 -P 4 -n 1 unzip
+
+#
+# Extract (subset) to CSV
+#
+# Relevant fields:
+# WKT
+# crossReference (list of TOID/other references)
+# source (list of cross-reference sources: 7666MT refers to MasterMap Topo)
+# uprn
+# parentUPRN
+# logicalStatus: 1 (one) is approved (otherwise historical, provisional)
+#
+
+# find $data_dir -type f -name '*.gml' -printf "%f\n"  | \
+# parallel \
+# ogr2ogr -f CSV \
+#     -select crossReference,source,uprn,parentUPRN,logicalStatus \
+#     {}.csv {} BasicLandPropertyUnit \
+#     -lco GEOMETRY=AS_WKT
+
+rm $data_dir/*.gml
+
+find $data_dir -type f -name '*.gml.csv' -printf "$data_dir%f\n"  | \
+parallel \
+python filter_addressbase_csv.py {}

etl/0_extract_mastermap.sh

@@ -1,20 +1,30 @@
-# Extract buildings from *.gml.gz
+#!/usr/bin/env bash
+
+#
+# Extract buildings from *.gz to CSV
 #
 # Features where::
 #     descriptiveGroup = '(1:Building)'
 #
 # Use `fid` as source ID, aka TOID.
+#
 
-: ${1?"Usage: $0 ./path/to/input/dir ./path/to/ouput/dir"}
+: ${1?"Usage: $0 ./path/to/data/dir"}
 
-: ${2?"Usage: $0 ./path/to/input/dir ./path/to/ouput/dir"}
+data_dir=$1
 
-find $1 -type f -name '*.gz' -printf "%f\n" | \
+find $data_dir -type f -name '*.gz' -printf "%f\n" | \
 parallel \
 ogr2ogr \
-    -select fid \
+    -select fid,descriptiveGroup \
-    -where "\"descriptiveGroup='(1:Building)'\"" \
+    -f CSV $data_dir/{}.csv \
-    -t_srs "EPSG:3857" \
+    $data_dir/{} \
-    -f "GeoJSON" $2/{}.geojson \
+    TopographicArea \
-    $1/{} \
+    -lco GEOMETRY=AS_WKT
-    TopographicArea
+
+# then filter
+# -where "\"descriptiveGroup='(1:Building)'\"" \
+# OR toid in addressbase_toids
+
+# finally load
+# -t_srs "EPSG:3857" \

etl/check_ab_mm_match.py

@@ -0,0 +1,56 @@
+"""Check if AddressBase TOIDs will match MasterMap
+"""
+import csv
+import glob
+import os
+import sys
+
+from multiprocessing import Pool
+
+csv.field_size_limit(sys.maxsize)
+
+def main(ab_path, mm_path):
+    ab_paths = sorted(glob.glob(os.path.join(ab_path, "*.gml.csv.filtered")))
+    mm_paths = sorted(glob.glob(os.path.join(mm_path, "*.gz.csv")))
+
+    assert len(ab_paths) == len(mm_paths)
+    zipped_paths = zip(ab_paths, mm_paths)
+
+    with Pool(4) as p:
+        p.starmap(check, zipped_paths)
+
+def check(ab_path, mm_path):
+    tile = str(os.path.basename(ab_path)).split(".")[0]
+    print(tile)
+    ab_toids = set()
+    mm_toids = set()
+
+    with open(ab_path, 'r') as fh:
+        r = csv.DictReader(fh)
+        for line in r:
+            ab_toids.add(line['toid'])
+
+    with open(mm_path, 'r') as fh:
+        r = csv.DictReader(fh)
+        for line in r:
+            mm_toids.add(line['fid'])
+
+    print("MasterMap", len(mm_toids))
+    print("Addressbase", len(ab_toids))
+    missing = ab_toids - mm_toids
+    print("in AB but not MM", len(missing))
+
+    with open('missing_toids_{}.txt'.format(tile), 'w') as fh:
+        for toid in missing:
+            fh.write("{}\n".format(toid))
+
+    with open('ab_toids_{}.txt'.format(tile), 'w') as fh:
+        for toid in ab_toids:
+            fh.write("{}\n".format(toid))
+
+
+if __name__ == '__main__':
+    if len(sys.argv) != 3:
+        print("Usage: filter_addressbase_csv.py ./path/to/addressbase/dir ./path/to/mastermap/dir")
+        exit(-1)
+    main(sys.argv[1], sys.argv[2])

etl/filter_addressbase_csv.py

@@ -0,0 +1,85 @@
+#!/usr/bin/env python
+"""Read ogr2ogr-converted CSV, filter to get OSMM TOID reference, only active addresses
+"""
+import csv
+import json
+import sys
+
+from collections import defaultdict
+
+def main(input_path):
+    output_path = "{}.filtered".format(input_path)
+    fieldnames = (
+        'toid', 'uprn', 'wkt', 'uprn_relations'
+    )
+    by_toid = defaultdict(list)
+
+    with open(input_path) as input_fh:
+        r = csv.DictReader(input_fh)
+        for line in r:
+            if line['logicalStatus'] != "1":
+                continue
+
+            refs = eval(line['crossReference'])
+            sources = eval(line['source'])
+            toid = ""
+            for ref, source in zip(refs, sources):
+                if source == "7666MT":
+                    toid = ref
+
+            by_toid[toid].append({
+                'uprn': line['uprn'],
+                'parent': line['parentUPRN'],
+                'wkt': line['WKT']
+            })
+
+    with open(output_path, 'w') as output_fh:
+        w = csv.DictWriter(output_fh, fieldnames=fieldnames)
+        w.writeheader()
+        for toid, uprns in by_toid.items():
+            if toid == "":
+                print(len(uprns), "not matched")
+                continue
+            if len(uprns) == 1:
+                # if there's only one, pick that as the 'primary' uprn for the toid
+                uprn = uprns[0]['uprn']
+            else:
+                # else try picking a top-level match (i.e. uprn with no parent)
+                orphans = set(u['uprn'] for u in uprns if not u['parent'])
+                if orphans:
+                    uprn = orphans.pop()
+                # else climb to a root of the current tree (forest?)
+                else:
+                    uprn_tree = {}
+                    for u in uprns:
+                        uprn_tree[u['uprn']] = u['parent']
+
+                    uprn = uprns[0]['uprn']
+                    while True:
+                        if uprn in uprn_tree and uprn_tree[uprn]:
+                            uprn = uprn_tree[uprn]
+                        else:
+                            break
+
+            # pick out wkt
+            wkt = ''
+            for item in uprns:
+                if item['uprn'] == uprn:
+                    wkt = item['wkt']
+
+            w.writerow({
+                'toid': toid,
+                'wkt': wkt,
+                'uprn': uprn,
+                'uprn_relations': json.dumps([{
+                    'uprn': u['uprn'],
+                    'parent': u['parent']
+                } for u in uprns])
+            })
+
+
+if __name__ == '__main__':
+    if len(sys.argv) != 2:
+        print("Usage: filter_addressbase_csv.py ./path/to/data.csv")
+        exit(-1)
+    main(sys.argv[1])