[polygons/osm] Adding a unified neighborhood reverse geocoder incorporating Zetashapes, OSM and Quattroshapes. Uses the new Soft TFIDF implementation to approximately match OSM names to Quattroshapes/Zetashapes names and geohash indices for more coarse point-in-polygon tests (OSM neighborhoods are stored as points not polygons, so need to match with a geometry from the other sources)

scripts/geodata/graph/scc.py

@@ -2,6 +2,13 @@ VISIT, VISIT_EDGE, POST_VISIT = range(3)
 
 
 def strongly_connected_components(graph):
+    '''
+    Find strongly connected components in a graph using iterative
+    depth-first search.
+
+    Based on:
+    http://code.activestate.com/recipes/578507-strongly-connected-components-of-a-directed-graph/
+    '''
     identified = set()
     stack = []
     index = {}

scripts/geodata/names/deduping.py

@@ -70,7 +70,7 @@ class NameDeduper(object):
         tokens2 = cls.content_tokens(s2)
 
         if not cls.possible_match(tokens1, tokens2):
-            return max(cls.dupe_threshold - 0.1, 0.0)
+            return 0.0
 
         tokens1_only = [t for t, c in tokens1]
         tokens2_only = [t for t, c in tokens2]
@@ -87,7 +87,7 @@ class NameDeduper(object):
         tokens2 = cls.content_tokens(s2)
 
         if not cls.possible_match(tokens1, tokens2):
-            return max(cls.dupe_threshold - 0.1, 0.0)
+            return 0.0
 
         tokens1_only = [t for t, c in tokens1]
         tokens2_only = [t for t, c in tokens2]

scripts/geodata/polygons/reverse_geocode.py

@@ -12,18 +12,33 @@ Usage:
 '''
 import argparse
 import logging
+import operator
 import os
+import re
+import requests
+import shutil
+import subprocess
 import sys
+import tempfile
 
 from functools import partial
 
 this_dir = os.path.realpath(os.path.dirname(__file__))
 sys.path.append(os.path.realpath(os.path.join(os.pardir, os.pardir)))
 
+from geodata.coordinates.conversion import latlon_to_decimal
 from geodata.encoding import safe_decode
+from geodata.file_utils import ensure_dir
+from geodata.i18n.unicode_properties import get_chars_by_script
+from geodata.i18n.word_breaks import ideographic_scripts
+from geodata.names.similarity import soft_tfidf
+from geodata.osm.extract import parse_osm, OSM_NAME_TAGS
 from geodata.osm.osm_admin_boundaries import OSMAdminPolygonReader
 from geodata.polygons.index import *
+from geodata.statistics.tf_idf import IDFIndex
 
+from postal.text.tokenize import tokenize, token_types
+from postal.text.normalize import *
 
 decode_latin1 = partial(safe_decode, encoding='latin1')
 
@@ -35,7 +50,345 @@ def str_id(v):
     return str(v)
 
 
-class QuattroshapesReverseGeocoder(RTreePolygonIndex):
+class NeighborhoodDeduper(NameDeduper):
+    # Lossless conversions only
+    replacements = {
+        u'saint': u'st',
+        u'and': u'&',
+    }
+
+    discriminative_words = set([
+        # Han numbers
+        u'〇', u'一',
+        u'二', u'三',
+        u'四', u'五',
+        u'六', u'七',
+        u'八', u'九',
+        u'十', u'百',
+        u'千', u'万',
+        u'億', u'兆',
+        u'京', u'第',
+
+        # Roman numerals
+        u'i', u'ii',
+        u'iii', u'iv',
+        u'v', u'vi',
+        u'vii', u'viii',
+        u'ix', u'x',
+        u'xi', u'xii',
+        u'xiii', u'xiv',
+        u'xv', u'xvi',
+        u'xvii', u'xviii',
+        u'xix', u'xx',
+
+        # English directionals
+        u'north', u'south',
+        u'east', u'west',
+        u'northeast', u'northwest',
+        u'southeast', u'southwest',
+
+        # Spanish, Portguese and Italian directionals
+        u'norte', u'nord', u'sur', u'sul', u'sud',
+        u'est', u'este', u'leste', u'oeste', u'ovest',
+
+        # New in various languages
+        u'new',
+        u'nova',
+        u'novo',
+        u'nuevo',
+        u'nueva',
+        u'nuovo',
+        u'nuova',
+
+        # Qualifiers
+        u'heights',
+        u'hills',
+
+        u'upper', u'lower',
+        u'little', u'great',
+
+        u'park',
+        u'parque',
+
+        u'village',
+
+    ])
+
+    stopwords = set([
+        u'cp',
+        u'de',
+        u'la',
+        u'urbanizacion',
+        u'do',
+        u'da',
+        u'dos',
+        u'del',
+        u'community',
+        u'bairro',
+        u'barrio',
+        u'le',
+        u'el',
+        u'mah',
+        u'раион',
+        u'vila',
+        u'villa',
+        u'kampung',
+        u'ahupua`a',
+
+    ])
+
+
+class NeighborhoodReverseGeocoder(RTreePolygonIndex):
+    '''
+    Neighborhoods are very important in cities like NYC, SF, Chicago, London
+    and many others. We want the address parser to be trained with addresses
+    that sufficiently capture variations in address patterns, including
+    neighborhoods. Quattroshapes neighborhood data (in the US at least)
+    is not great in terms of names, mostly becasue GeoPlanet has so many
+    incorrect names. The neighborhoods project, also known as Zetashapes
+    has very accurate polygons with correct names, but only for a handful
+    of cities. OSM usually lists neighborhoods and some other local admin
+    areas like boroughs as points rather than polygons.
+
+    This index merges all of the above data sets in prioritized order
+    (Zetashapes > OSM > Quattroshapes) to provide unified point-in-polygon
+    tests for neighborhoods. The properties vary by source but each has
+    source has least a "name" key which in practice is what we care about.
+    '''
+    NEIGHBORHOODS_REPO = 'https://github.com/blackmad/neighborhoods'
+
+    SCRATCH_DIR = '/tmp'
+
+    DUPE_THRESHOLD = 0.9
+
+    source_priorities = {
+        'zetashapes': 0,     # Best names/polygons
+        'osm': 1,            # OSM names with Quattroshapes/Zetashapes polygon
+        'quattroshapes': 2,  # Good results in some countries/areas
+    }
+
+    level_priorities = {
+        'neighborhood': 0,
+        'local_admin': 1,
+    }
+
+    @classmethod
+    def clone_repo(cls, path):
+        subprocess.check_call(['rm', '-rf', path])
+        subprocess.check_call(['git', 'clone', cls.NEIGHBORHOODS_REPO, path])
+
+    @classmethod
+    def create_zetashapes_neighborhoods_index(cls):
+        scratch_dir = cls.SCRATCH_DIR
+        repo_path = os.path.join(scratch_dir, 'neighborhoods')
+        cls.clone_repo(repo_path)
+
+        neighborhoods_dir = os.path.join(scratch_dir, 'neighborhoods', 'index')
+        ensure_dir(neighborhoods_dir)
+
+        index = GeohashPolygonIndex()
+
+        have_geonames = set()
+        is_neighborhood = set()
+
+        for filename in os.listdir(repo_path):
+            path = os.path.join(repo_path, filename)
+            base_name = filename.split('.')[0].split('gn-')[-1]
+            if filename.endswith('.geojson') and filename.startswith('gn-'):
+                have_geonames.add(base_name)
+            elif filename.endswith('metadata.json'):
+                data = json.load(open(os.path.join(repo_path, filename)))
+                if data.get('neighborhoodNoun', [None])[0] in (None, 'rione'):
+                    is_neighborhood.add(base_name)
+
+        for filename in os.listdir(repo_path):
+            if not filename.endswith('.geojson'):
+                continue
+            base_name = filename.rsplit('.geojson')[0]
+            if base_name in have_geonames:
+                f = open(os.path.join(repo_path, 'gn-{}'.format(filename)))
+            elif base_name in is_neighborhood:
+                f = open(os.path.join(repo_path, filename))
+            else:
+                continue
+            index.add_geojson_like_file(json.load(f)['features'])
+
+        return index
+
+    @classmethod
+    def count_words(cls, s):
+        doc = defaultdict(int)
+        for t, c in NeighborhoodDeduper.content_tokens(s):
+            doc[t] += 1
+        return doc
+
+    @classmethod
+    def create_from_osm_and_quattroshapes(cls, filename, quattroshapes_dir, output_dir, scratch_dir=SCRATCH_DIR):
+        '''
+        Given an OSM file (planet or some other bounds) containing neighborhoods
+        as points (some suburbs have boundaries)
+
+        and their dependencies, create an R-tree index for coarse-grained
+        reverse geocoding.
+
+        Note: the input file is expected to have been created using
+        osmfilter. Use fetch_osm_address_data.sh for planet or copy the
+        admin borders commands if using other geometries.
+        '''
+        index = cls(save_dir=output_dir)
+
+        ensure_dir(scratch_dir)
+
+        logger = logging.getLogger('neighborhoods')
+
+        qs_scratch_dir = os.path.join(scratch_dir, 'qs_neighborhoods')
+        ensure_dir(qs_scratch_dir)
+        logger.info('Creating Quattroshapes neighborhoods')
+
+        qs = QuattroshapesReverseGeocoder.create_neighborhoods_index(quattroshapes_dir, qs_scratch_dir)
+        logger.info('Creating Zetashapes neighborhoods')
+        zs = cls.create_zetashapes_neighborhoods_index()
+
+        logger.info('Creating IDF index')
+        idf = IDFIndex()
+
+        char_scripts = get_chars_by_script()
+
+        for idx in (zs, qs):
+            for i, (props, poly) in enumerate(idx.polygons):
+                name = props.get('name')
+                if name is not None:
+                    doc = cls.count_words(name)
+                    idf.update(doc)
+
+        for key, attrs, deps in parse_osm(filename):
+            for k, v in attrs.iteritems():
+                if any((k.startswith(name_key) for name_key in OSM_NAME_TAGS)):
+                    doc = cls.count_words(v)
+                    idf.update(doc)
+
+        qs.matched = [False] * qs.i
+        zs.matched = [False] * zs.i
+
+        logger.info('Matching OSM points to neighborhood polygons')
+        # Parse OSM and match neighborhood/suburb points to Quattroshapes/Zetashapes polygons
+        num_polys = 0
+        for node_id, attrs, deps in parse_osm(filename):
+            try:
+                lat, lon = latlon_to_decimal(attrs['lat'], attrs['lon'])
+            except ValueError:
+                continue
+
+            osm_name = attrs.get('name')
+            if not osm_name:
+                continue
+
+            is_neighborhood = attrs.get('place') == 'neighbourhood'
+
+            ranks = []
+            osm_names = []
+
+            for key in OSM_NAME_TAGS:
+                name = attrs.get(key)
+                if name:
+                    osm_names.append(name)
+
+            for name_key in OSM_NAME_TAGS:
+                osm_names.extend([v for k, v in attrs.iteritems() if k.startswith('{}:'.format(name_key))])
+
+            for idx in (zs, qs):
+                candidates = idx.get_candidate_polygons(lat, lon, all_levels=True)
+
+                if candidates:
+                    max_sim = 0.0
+                    arg_max = None
+
+                    for osm_name in osm_names:
+
+                        contains_ideographs = any(((char_scripts[ord(c)] or '').lower() in ideographic_scripts
+                                                   for c in safe_decode(osm_name)))
+
+                        for i in candidates:
+                            props, poly = idx.polygons[i]
+                            name = props.get('name')
+                            if not name:
+                                continue
+
+                            level = props.get(QuattroshapesReverseGeocoder.LEVEL)
+                            if is_neighborhood and level != 'neighborhood':
+                                continue
+
+                            if not contains_ideographs:
+                                sim = NeighborhoodDeduper.compare(osm_name, name, idf)
+                            else:
+                                # Many Han/Hangul characters are common, shouldn't use IDF
+                                sim = NeighborhoodDeduper.compare_ideographs(osm_name, name)
+
+                            if sim > max_sim:
+                                max_sim = sim
+                                arg_max = (max_sim, props, poly.context, idx, i)
+
+                    if arg_max:
+                        ranks.append(arg_max)
+
+            ranks.sort(key=operator.itemgetter(0), reverse=True)
+            if ranks and ranks[0][0] >= cls.DUPE_THRESHOLD:
+                score, props, poly, idx, i = ranks[0]
+                matches.append((score, [safe_decode(attrs[k]) for k in OSM_NAME_TAGS if k in attrs], safe_decode(props['name'])))
+
+                if idx is zs:
+                    attrs['polygon_type'] = 'neighborhood'
+                else:
+                    level = props.get(QuattroshapesReverseGeocoder.LEVEL, None)
+                    if level == 'neighborhood':
+                        attrs['polygon_type'] = 'neighborhood'
+                    else:
+                        attrs['polygon_type'] = 'local_admin'
+
+                attrs['source'] = 'osm'
+                index.index_polygon(poly)
+                index.add_polygon(poly, attrs)
+                idx.matched[i] = True
+            else:
+                if ranks:
+                    score, props, poly, idx, i = ranks[0]
+                    top_matches.append((ranks[0][0], [safe_decode(attrs[k]) for k in OSM_NAME_TAGS if k in attrs], safe_decode(props['name'])))
+
+                non_match.append((node_id, attrs))
+
+            num_polys += 1
+            if num_polys % 1000 == 0 and num_polys > 0:
+                logger.info('did {} neighborhoods'.format(num_polys))
+
+        for idx, source in ((zs, 'zetashapes'), (qs, 'quattroshapes')):
+            for i, (props, poly) in enumerate(idx.polygons):
+                if idx.matched[i]:
+                    continue
+                props['source'] = source
+                if idx is zs or props.get(QuattroshapesReverseGeocoder.LEVEL, None) == 'neighborhood':
+                    props['polygon_type'] = 'neighborhood'
+                else:
+                    props['polygon_type'] = 'local_admin'
+                index.index_polygon(poly.context)
+                index.add_polygon(poly.context, props)
+
+        return index
+
+    def priority(self, i):
+        props, p = self.polygons[i]
+        return (self.level_priorities[props['polygon_type']], self.source_priorities[props['source']])
+
+    def get_candidate_polygons(self, lat, lon):
+        candidates = super(NeighborhoodReverseGeocoder, self).get_candidate_polygons(lat, lon)
+        return sorted(candidates, key=self.priority)
+
+
+class QuattroshapesReverseGeocoder(GeohashPolygonIndex):
+    '''
+    Quattroshapes polygons, for levels up to localities, are relatively
+    accurate and provide concordance with GeoPlanet and in some cases
+    GeoNames (which is used in other parts of this project).
+    '''
     COUNTRIES_FILENAME = 'qs_adm0.shp'
     ADMIN1_FILENAME = 'qs_adm1.shp'
     ADMIN1_REGION_FILENAME = 'qs_adm1_region.shp'
@@ -134,18 +487,23 @@ class QuattroshapesReverseGeocoder(RTreePolygonIndex):
     def create_from_shapefiles(cls,
                                input_files,
                                output_dir,
-                               index_filename=DEFAULT_INDEX_FILENAME,
+                               index_filename=None,
-                               polys_filename=DEFAULT_POLYS_FILENAME):
+                               polys_filename=DEFAULT_POLYS_FILENAME,
+                               use_all_props=False):
 
         index = cls(save_dir=output_dir, index_filename=index_filename)
 
-        i = 0
-
         for input_file in input_files:
             f = fiona.open(input_file)
 
             filename = os.path.split(input_file)[-1]
-            include_props = cls.polygon_properties.get(filename)
+
+            aliases = cls.polygon_properties.get(filename)
+
+            if not use_all_props:
+                include_props = aliases
+            else:
+                include_props = None
 
             for rec in f:
                 if not rec or not rec.get('geometry') or 'type' not in rec['geometry']:
@@ -156,9 +514,8 @@ class QuattroshapesReverseGeocoder(RTreePolygonIndex):
                 if filename == cls.NEIGHBORHOODS_FILENAME:
                     properties['qs_level'] = 'neighborhood'
 
-                if include_props:
                 have_all_props = False
-                    for k, (prop, func) in include_props.iteritems():
+                for k, (prop, func) in aliases.iteritems():
                     v = properties.get(prop, None)
                     if v is not None:
                         try:
@@ -173,7 +530,7 @@ class QuattroshapesReverseGeocoder(RTreePolygonIndex):
                 poly_type = rec['geometry']['type']
                 if poly_type == 'Polygon':
                     poly = Polygon(rec['geometry']['coordinates'][0])
-                    index.index_polygon(i, poly)
+                    index.index_polygon(poly)
                     poly = index.simplify_polygon(poly)
                     index.add_polygon(poly, dict(rec['properties']), include_only_properties=include_props)
                 elif poly_type == 'MultiPolygon':
@@ -181,20 +538,19 @@ class QuattroshapesReverseGeocoder(RTreePolygonIndex):
                     for coords in rec['geometry']['coordinates']:
                         poly = Polygon(coords[0])
                         polys.append(poly)
-                        index.index_polygon(i, poly)
+                        index.index_polygon(poly)
 
                     multi_poly = index.simplify_polygon(MultiPolygon(polys))
                     index.add_polygon(multi_poly, dict(rec['properties']), include_only_properties=include_props)
                 else:
                     continue
 
-                i += 1
         return index
 
     @classmethod
     def create_with_quattroshapes(cls, quattroshapes_dir,
                                   output_dir,
-                                  index_filename=DEFAULT_INDEX_FILENAME,
+                                  index_filename=None,
                                   polys_filename=DEFAULT_POLYS_FILENAME):
 
         admin0_filename = os.path.join(quattroshapes_dir, cls.COUNTRIES_FILENAME)
@@ -212,16 +568,41 @@ class QuattroshapesReverseGeocoder(RTreePolygonIndex):
                                           output_dir, index_filename=index_filename,
                                           polys_filename=polys_filename)
 
+    @classmethod
+    def create_neighborhoods_index(cls, quattroshapes_dir,
+                                   output_dir,
+                                   index_filename=None,
+                                   polys_filename=DEFAULT_POLYS_FILENAME):
+        local_admin_filename = os.path.join(quattroshapes_dir, cls.LOCAL_ADMIN_FILENAME)
+        neighborhoods_filename = os.path.join(quattroshapes_dir, cls.NEIGHBORHOODS_FILENAME)
+        return cls.create_from_shapefiles([local_admin_filename, neighborhoods_filename],
+                                          output_dir, index_filename=index_filename,
+                                          polys_filename=polys_filename)
+
     def sort_level(self, i):
         props, p = self.polygons[i]
         return self.sort_levels.get(props[self.LEVEL], 0)
 
-    def get_candidate_polygons(self, lat, lon):
+    def get_candidate_polygons(self, lat, lon, all_levels=False):
-        candidates = OrderedDict.fromkeys(self.index.intersection((lon, lat, lon, lat))).keys()
+        candidates = super(QuattroshapesReverseGeocoder, self).get_candidate_polygons(lat, lon, all_levels=all_levels)
         return sorted(candidates, key=self.sort_level, reverse=True)
 
 
 class OSMReverseGeocoder(RTreePolygonIndex):
+    '''
+    OSM has among the best, most carefully-crafted, accurate administrative
+    polygons in the business in addition to using local language naming
+    conventions which is desirable for creating a truly multilingual address
+    parser.
+
+    The storage of these polygons is byzantine. See geodata.osm.osm_admin_boundaries
+    for more details.
+
+    Suffice to say, this reverse geocoder builds an R-tree index on OSM planet
+    in a reasonable amount of memory using arrays of C integers and binary search
+    for the dependency lookups and Tarjan's algorithm for finding strongly connected
+    components to stitch together the polygons.
+    '''
     include_property_patterns = set([
         'name',
         'name:*',
@@ -237,27 +618,6 @@ class OSMReverseGeocoder(RTreePolygonIndex):
         'wikipedia:*',
     ])
 
-    @classmethod
-    def fix_polygon(cls, poly):
-        '''
-        Coerce to valid polygon
-        '''
-        if not poly.is_valid:
-            poly = poly.buffer(0)
-            if not poly.is_valid:
-                return None
-        return poly
-
-    @classmethod
-    def to_polygon(cls, coords):
-        '''
-        Create shapely polygon from list of coordinate tuples if valid
-        '''
-        if not coords or len(coords) < 3:
-            return None
-        poly = Polygon(coords)
-        return cls.fix_polygon(poly)
-
     @classmethod
     def create_from_osm_file(cls, filename, output_dir,
                              index_filename=DEFAULT_INDEX_FILENAME,
@@ -269,7 +629,7 @@ class OSMReverseGeocoder(RTreePolygonIndex):
 
         Note: the input file is expected to have been created using
         osmfilter. Use fetch_osm_address_data.sh for planet or copy the
-        admin borders commands if using other geometries.
+        admin borders commands if using other bounds.
         '''
         index = cls(save_dir=output_dir, index_filename=index_filename)
 
@@ -282,8 +642,6 @@ class OSMReverseGeocoder(RTreePolygonIndex):
 
         logger = logging.getLogger('osm.reverse_geocode')
 
-        polygon_index = 0
-
         for relation_id, props, outer_polys, inner_polys in polygons:
             props = {k: v for k, v in props.iteritems() if k in cls.include_property_patterns
                      or (':' in k and '{}:*'.format(k.split(':', 1)[0]) in cls.include_property_patterns)}
@@ -298,10 +656,10 @@ class OSMReverseGeocoder(RTreePolygonIndex):
                 if poly is None or not poly.bounds or len(poly.bounds) != 4:
                     continue
                 if poly.type != 'MultiPolygon':
-                    index.index_polygon(polygon_index, poly)
+                    index.index_polygon(poly)
                 else:
                     for p in poly:
-                        index.index_polygon(polygon_index, p)
+                        index.index_polygon(p)
             else:
                 multi = []
                 inner = []
@@ -331,11 +689,11 @@ class OSMReverseGeocoder(RTreePolygonIndex):
                             continue
                     # R-tree only stores the bounding box, so add the whole polygon
                     if poly.type != 'MultiPolygon':
-                        index.index_polygon(polygon_index, poly)
+                        index.index_polygon(poly)
                         multi.append(poly)
                     else:
                         for p in poly:
-                            index.index_polygon(polygon_index, p)
+                            index.index_polygon(p)
                         multi.extend(poly)
 
                 if len(multi) > 1:
@@ -351,6 +709,7 @@ class OSMReverseGeocoder(RTreePolygonIndex):
 
         return index
 
+
 if __name__ == '__main__':
     # Handle argument parsing here
     parser = argparse.ArgumentParser()
@@ -361,15 +720,25 @@ if __name__ == '__main__':
     parser.add_argument('-a', '--osm-admin-file',
                         help='Path to OSM borders file (with dependencies, .osm format)')
 
+    parser.add_argument('-n', '--osm-neighborhoods-file',
+                        help='Path to OSM neighborhoods file (no dependencies, .osm format)')
+
     parser.add_argument('-o', '--out-dir',
                         default=os.getcwd(),
                         help='Output directory')
 
     args = parser.parse_args()
-    if args.quattroshapes_dir:
+    if args.osm_admin_file:
+        index = OSMReverseGeocoder.create_from_osm_file(args.osm_admin_file, args.out_dir,
+                                                        quattroshapes_dir=args.quattroshapes_dir)
+    elif args.osm_neighborhoods_filename and args.quattroshapes_dir:
+        index = NeighborhoodReverseGeocoder.create_from_osm_and_quattroshapes(
+            args.osm_neighorhoods_file,
+            args.quattroshapes_dir,
+            args.out_dir
+        )
+    elif args.quattroshapes_dir:
         index = QuattroshapesReverseGeocoder.create_with_quattroshapes(args.quattroshapes_dir, args.out_dir)
-    elif args.osm_admin_file:
-        index = OSMReverseGeocoder.create_from_osm_file(args.osm_admin_file, args.out_dir)
     else:
         parser.error('Must specify quattroshapes dir or osm admin borders file')