shapefile - Check if a point falls within a multipolygon with Python

I have tried several examples of code using libraries such as shapefile, fiona, and ogr to attempt to check whether a point (x, y) falls within the boundaries of a multipolygon created with ArcMap (and thus in shapefile format). However none of the examples work well with multipolygons, although they do fine with regular, single polygon shapefiles. Some snippets I tried are below:

# First example using shapefile and shapely:
from shapely.geometry import Polygon, Point, MultiPolygon
import shapefile


polygon = shapefile.Reader('shapefile.shp') 
polygon = polygon.shapes()  
shpfilePoints = []
for shape in polygon:
    shpfilePoints = shape.points 
polygon = shpfilePoints 
poly = Polygon(poly)

point = Point(x, y)

# point in polygon test
if polygon.contains(point):
    print 'inside'
else:
    print 'OUT'


# Second example using ogr and shapely:
from shapely.geometry import Polygon, Point, MultiPolygon
from osgeo import ogr, gdal


driver = ogr.GetDriverByName('ESRI Shapefile')
dataset = driver.Open("shapefile.shp", 0)

layer = dataset.GetLayer()
for index in xrange(layer.GetFeatureCount()):
    feature = layer.GetFeature(index)
    geometry = feature.GetGeometryRef()

polygon = Polygon(geometry)

print 'polygon points =', polygon  # this prints 'multipoint' + all the points fine

point = Point(x, y)
# point in polygon test
if polygon.contains(point):
    print 'inside'
else:
    print 'OUT'

The first example works fine with a single polygon at a time, but when I input a point within one of the shapes in my multipolygon shapefile it returns "out" even though it does fall inside one of the many parts.

For for the second example I get an error "object of type 'Geometry' has no len()" which I assume is because the geometry field can't be read as a normal, indexed list/array.

I additionally tried to replace the actual point in polygon code as suggested here to make sure it wasn't that part of the code that didn't work. And while that link's examples work fine with simple polygon shapefiles I can't get my complex multipolygon to test properly.

So I can't think of any other way to test whether a point falls within a multipolygon shapefile via python... Maybe there are other libraries out there I'm missing?

Answer

Shapefiles have no type MultiPolygon (type = Polygon), but they support them anyway (all rings are stored in one feature = list of polygons, look at Converting huge multipolygon to polygons)

The problem

If I open a MultiPolygon shapefile, the geometry is 'Polygon'

multipolys = fiona.open("multipol.shp")
multipolys.schema

{'geometry': 'Polygon', 'properties': OrderedDict([(u'id', 'int:10')])}
len(multipolys)
1

Solution 1 with Fiona

import fiona
from shapely.geometry import shape,mapping, Point, Polygon, MultiPolygon
multipol = fiona.open("multipol.shp")
multi= multipol.next() # only one feature in the shapefile
print multi

{'geometry': {'type': 'MultiPolygon', 'coordinates': [[[(-0.5275288092189501, 0.5569782330345711), (-0.11779769526248396, 0.29065300896286816), (-0.25608194622279135, 0.01920614596670933), (-0.709346991037132, -0.08834827144686286), (-0.8629961587708066, 0.18309859154929575), (-0.734955185659411, 0.39820742637644047), (-0.5275288092189501, 0.5569782330345711)]], [[(0.19974391805377723, 0.060179257362355965), (0.5480153649167734, 0.1293213828425096), (0.729833546734955, 0.03969270166453265), (0.8143405889884763, -0.13956466069142115), (0.701664532650448, -0.38540332906530095), (0.4763124199743918, -0.5006402048655569), (0.26888604353393086, -0.4238156209987196), (0.18950064020486557, -0.2291933418693981), (0.19974391805377723, 0.060179257362355965)]], [[(-0.3764404609475033, -0.295774647887324), (-0.11523687580025621, -0.3597951344430217), (-0.033290653008962945, -0.5800256081946222), (-0.11523687580025621, -0.7413572343149808), (-0.3072983354673495, -0.8591549295774648), (-0.58898847631242, -0.6927016645326505), (-0.6555697823303457, -0.4750320102432779), (-0.3764404609475033, -0.295774647887324)]]]}, 'type': 'Feature', 'id': '0', 'properties': OrderedDict([(u'id', 1)])}

Fiona interprets the feature as a MultiPolygon and you can apply the solution presented in More Efficient Spatial join in Python without QGIS, ArcGIS, PostGIS, etc (1)

points= ([pt for pt  in fiona.open("points.shp")])
for i, pt in enumerate(points):
    point = shape(pt['geometry'])
    if point.within(shape(multi['geometry'])):
         print i, shape(points[i]['geometry'])
1 POINT (-0.58898847631242 0.17797695262484)
3 POINT (0.4993597951344431 -0.06017925736235585)

5 POINT (-0.3764404609475033 -0.4750320102432779)
6 POINT (-0.3098591549295775 -0.6312419974391805)

Solution 2 with pyshp (shapefile) and the geo_interface (GeoJSON like) protocol

This is a supplement to the answer of xulnik.

import shapefile
pts = shapefile.Reader("points.shp")
polys = shapefile.Reader("multipol.shp")
points = [pt.shape.__geo_interface__ for pt in pts.shapeRecords()]
multi = shape(polys.shapeRecords()[0].shape.__geo_interface__) # 1 polygon

print multi
MULTIPOLYGON (((-0.5275288092189501 0.5569782330345711, -0.117797695262484 0.2906530089628682, -0.2560819462227913 0.01920614596670933, -0.7093469910371319 -0.08834827144686286, -0.8629961587708066 0.1830985915492958, -0.734955185659411 0.3982074263764405, -0.5275288092189501 0.5569782330345711)), ((0.1997439180537772 0.06017925736235596, 0.5480153649167734 0.1293213828425096, 0.729833546734955 0.03969270166453265, 0.8143405889884763 -0.1395646606914211, 0.701664532650448 -0.3854033290653009, 0.4763124199743918 -0.5006402048655569, 0.2688860435339309 -0.4238156209987196, 0.1895006402048656 -0.2291933418693981, 0.1997439180537772 0.06017925736235596)), ((-0.3764404609475033 -0.295774647887324, -0.1152368758002562 -0.3597951344430217, -0.03329065300896294 -0.5800256081946222, -0.1152368758002562 -0.7413572343149808, -0.3072983354673495 -0.8591549295774648, -0.58898847631242 -0.6927016645326505, -0.6555697823303457 -0.4750320102432779, -0.3764404609475033 -0.295774647887324)))
for i, pt in enumerate(points):
    point = shape(pt)
    if point.within(multi): 
        print i, shape(points[i])
1 POINT (-0.58898847631242 0.17797695262484)
3 POINT (0.4993597951344431 -0.06017925736235585)
5 POINT (-0.3764404609475033 -0.4750320102432779)
6 POINT (-0.3098591549295775 -0.6312419974391805)

Solution 3 with ogr and the geo_interface protocol (Python Geo_interface applications)

from osgeo import ogr
import json
def records(file):  
    # generator 
    reader = ogr.Open(file)
    layer = reader.GetLayer(0)
    for i in range(layer.GetFeatureCount()):
        feature = layer.GetFeature(i)

        yield json.loads(feature.ExportToJson())

points  = [pt for pt in records("point_multi_contains.shp")]
multipol = records("multipol.shp")
multi = multipol.next() # 1 feature
for i, pt in enumerate(points):
     point = shape(pt['geometry'])
     if point.within(shape(multi['geometry'])):
          print i, shape(points[i]['geometry'])


1 POINT (-0.58898847631242 0.17797695262484)
3 POINT (0.499359795134443 -0.060179257362356)
5 POINT (-0.376440460947503 -0.475032010243278)
6 POINT (-0.309859154929577 -0.631241997439181)

Solution 4 with GeoPandas as in More Efficient Spatial join in Python without QGIS, ArcGIS, PostGIS, etc (2)

import geopandas
point = geopandas.GeoDataFrame.from_file('points.shp') 
poly  = geopandas.GeoDataFrame.from_file('multipol.shp')
from geopandas.tools import sjoin

pointInPolys = sjoin(point, poly, how='left')
grouped = pointInPolys.groupby('index_right')
list(grouped)
[(0.0,      geometry                               id_left  index_right id_right  

1  POINT (-0.58898847631242 0.17797695262484)       None      0.0        1.0 
3  POINT (0.4993597951344431 -0.06017925736235585)  None      0.0        1.0
5  POINT (-0.3764404609475033 -0.4750320102432779)  None      0.0        1.0 
6  POINT (-0.3098591549295775 -0.6312419974391805)  None      0.0        1.0 ]
print grouped.groups

{0.0: [1, 3, 5, 6]} 

The points 1,3,5,6 falls within the boundaries of the MultiPolygon