In [1]:

    

%matplotlib inline
import shapefile
from functools import reduce

from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import numpy as np


    

In [2]:

    

sf = shapefile.Reader("Data/cb_2015_us_zcta510_500k/cb_2015_us_zcta510_500k")


    

In [3]:

    

def find_max_and_min(shape_records):
    points = map(lambda x: x.shape.points, shape_records)
    points = reduce(lambda x, y: x + y, points)
    points = np.array(points)
    lon_min, lon_max = points[:, 0].min() - .05, points[:, 0].max() + .05
    lat_min, lat_max = points[:, 1].min() - .05, points[:, 1].max() + .05
    return lon_min, lon_max, lat_min, lat_max

def sub_polys_in_poly(poly_points):
    polys = []
    poly = []
    for index, point in enumerate(poly_points):
        poly.append(point)
        if len(poly) >= 2 and poly[0] == poly[len(poly)-1]:
            polys.append(poly)
            poly = []
    return polys

def plotShapes(plt, shape_records, colors):
    lon_min, lon_max, lat_min, lat_max = find_max_and_min(shape_records)
    
    map = Basemap(projection='merc', 
    lat_0 = np.average([lat_min, lat_max]), lon_0 = np.average([lon_min, lon_max]),
    resolution = 'c', area_thresh = 0.1,
    llcrnrlon=lon_min, llcrnrlat=lat_min,
    urcrnrlon=lon_max, urcrnrlat=lat_max)
    
    map.drawcoastlines()
    map.drawstates()
    map.fillcontinents(color = 'coral')
    map.drawmapboundary()
    
    for index, shape_record in enumerate(shape_records):
        polys = sub_polys_in_poly(shape_record.shape.points)
        for poly in polys:
            points = np.array(poly)
            x, y = map(points[:, 0], points[:,1])
            map.plot(x, y, 'o-', color=colors[index])


    

In [4]:

    

shape_records = {}
for shape_record in sf.shapeRecords():
    zip_code = shape_record.record[0]
    shape_records[zip_code] = shape_record


    

In [5]:

    

# def of record fields
sf.fields


    

    
Out[5]:





[('DeletionFlag', 'C', 1, 0),
 ['ZCTA5CE10', 'C', 5, 0],
 ['AFFGEOID10', 'C', 14, 0],
 ['GEOID10', 'C', 5, 0],
 ['ALAND10', 'N', 14, 0],
 ['AWATER10', 'N', 14, 0]]

In [6]:

    

# number of shape records
len(shape_records)


    

    
Out[6]:





33144

In [7]:

    

# object toomsuba & cuba are shape records, each of them has a shape and a record property
toomsuba = shape_records['39364']
cuba = shape_records['36907']
ithaca = shape_records['14850']


    

In [8]:

    

toomsuba.record


    

    
Out[8]:





['39364', '8600000US39364', '39364', 191678251, 1426378]

In [9]:

    

plt.figure(figsize=(12, 12))
plotShapes(plt, [toomsuba, cuba], ['b', 'y'])
plt.show()


    

In [10]:

    

plt.figure(figsize=(12, 12))
plotShapes(plt, [ithaca], ['b'])
plt.show()


    

In [11]:

    

from shapely.geometry import Polygon
from shapely.ops import cascaded_union


    

In [12]:

    

# A Simple union example
triangle0 = Polygon([(0,0), (2,0), (0,2)])
triangle1 = Polygon([(1,0), (1,2), (3,0)])
triangle0.union(triangle1)


    

    
Out[12]:

In [13]:

    

polygon0 = Polygon(toomsuba.shape.points)
polygon1 = Polygon(cuba.shape.points)
union_poly = polygon0.union(polygon1)


    

In [14]:

    

polygon0


    

    
Out[14]:

In [15]:

    

polygon1


    

    
Out[15]:

In [16]:

    

union_poly


    

    
Out[16]:

In [17]:

    

# get coordinates of unoined shape
union_coords = union_poly.exterior.coords.xy
union_coords = list(zip(union_coords[0], union_coords[1]))
union_coords # [(lon, lat)]


    

    
Out[17]:





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 (-88.52830999999999, 32.342639),
 (-88.52753899999999, 32.344214),
 (-88.52936299999999, 32.347376),
 (-88.52942999999999, 32.351479),
 (-88.528452, 32.357115),
 (-88.526673, 32.359623),
 (-88.525041, 32.360577),
 (-88.525825, 32.363943),
 (-88.525678, 32.366068),
 (-88.523716, 32.369291),
 (-88.522931, 32.371739999999996),
 (-88.52412799999999, 32.376363),
 (-88.52617699999999, 32.378167),
 (-88.525185, 32.37937),
 (-88.52470699999999, 32.381845999999996),
 (-88.52207299999999, 32.382797),
 (-88.521278, 32.383939),
 (-88.51782399999999, 32.386272999999996),
 (-88.517764, 32.388007),
 (-88.51914699999999, 32.390758999999996),
 (-88.519599, 32.394106),
 (-88.518607, 32.395423),
 (-88.51933799999999, 32.399156),
 (-88.554482, 32.399238),
 (-88.55448, 32.403393),
 (-88.568834, 32.398997),
 (-88.572761, 32.402685999999996),
 (-88.57667599999999, 32.404179),
 (-88.580106, 32.408674),
 (-88.5938, 32.40379),
 (-88.593998, 32.404178),
 (-88.588346, 32.406771),
 (-88.583508, 32.409307999999996),
 (-88.57772299999999, 32.413264),
 (-88.57172399999999, 32.415158999999996),
 (-88.566484, 32.415611),
 (-88.562111, 32.414757),
 (-88.55762999999999, 32.413491),
 (-88.55431899999999, 32.413044),
 (-88.55458, 32.428957),
 (-88.55604699999999, 32.427789),
 (-88.559468, 32.426649999999995),
 (-88.55942, 32.424676999999996),
 (-88.560253, 32.423153),
 (-88.561815, 32.423102),
 (-88.563485, 32.421009999999995),
 (-88.56684, 32.419111),
 (-88.56969, 32.419948),
 (-88.57159899999999, 32.419987),
 (-88.57415999999999, 32.420944),
 (-88.578442, 32.421279),
 (-88.582641, 32.420538),
 (-88.586794, 32.418531),
 (-88.588594, 32.412008),
 (-88.591607, 32.411122),
 (-88.59195799999999, 32.405322),
 (-88.594088, 32.404354),
 (-88.59504299999999, 32.409997),
 (-88.596633, 32.411963),
 (-88.595203, 32.415568),
 (-88.596904, 32.417569),
 (-88.598233, 32.420924),
 (-88.598809, 32.420494999999995),
 (-88.602037, 32.418602),
 (-88.605504, 32.414477999999995),
 (-88.60497, 32.426228)]

In [18]:

    

# from osgeo import ogr


    

In [19]:

    

# dataSource = ogr.Open("cb_2015_us_zcta510_500k/cb_2015_us_zcta510_500k.shp")
# layer = dataSource.GetLayer()
# print(layer.GetGeomType()) # 3 means polygons


    

In [20]:

    

# print(layer.GetFeatureCount())


    

In [21]:

    

# geometries = []
# for feature in layer:
#     geom = feature.GetGeometryRef()
#     geometries.append(geom)


    

In [22]:

    

# geo0 = geometries[0]
# geo1 = geometries[1]
# union_poly = geo0.Union(geo1)