Python shapely库的具体使用
作者：jiang_huixin
基本类型
基本几何类型包括: 点(Point), 线(LineString), 线环(LinearRing), 多边形(Polygon)
所有的基本几何对象均存在以下属性:
- 长度 x.length
- 面积 x.area
- 边界框 x.bounds 返回 (x_min, y_min, x_max, y_max)
- 坐标值 x.coords 返回可迭代对象(支持索引与切片), 元素为坐标元组 (x, y)
Point
Point 代表几何上的一个点
from shapely.geometry import Point
point_1 = Point(1, 1)
# 传递的参数为坐标元组
point_2 = Point((2, 2))
print(point_1, point_2)
# 具体坐标
print('x =', point_1.x, 'y =', point_1.y)
# 长度面积
print('length =', point_1.length, 'area =', point_1.area)
# 边界框
print('bounds of point:', point_1.bounds)
# 坐标值
print('coords of point:', list(point_1.coords))在几何对象的创建中, 一个坐标元组 (x, y[, z]) 代表一个点, 多个点的组合嵌套可以创建更复杂的几何对象
打印结果如下:
POINT (1 1) POINT (2 2)
x = 1.0 y = 1.0
length = 0.0 area = 0.0
bounds of point: (1.0, 1.0, 1.0, 1.0)
coords of point: [(1.0, 1.0)]
计算两个点的欧式距离:
# 1.4142135623730951 point_1.distance(point_2)
可以扩展为计算任意两个几何对象的最短距离
LineString
LineString 由多个点依次连接而成
from shapely.geometry import LineString, Point
line_1 = LineString([(0, 0), (0, 1), (1, 1)])
line_2 = LineString([Point(0, 0), Point(0, 1), Point(1, 1)])
print(line_1)
print(line_2)
# 长度面积
print('length =', line_1.length, 'area =', line_1.area)
# 边界框
print('bounds:', line_1.bounds)
# 坐标值-切片
print('coords:', line_1.coords[:])打印结果如下:
LINESTRING (0 0, 0 1, 1 1)
LINESTRING (0 0, 0 1, 1 1)
length = 2.0 area = 0.0
bounds: (0.0, 0.0, 1.0, 1.0)
coords: [(0.0, 0.0), (0.0, 1.0), (1.0, 1.0)]
LinearRing
LinearRing 是一个封闭的 LineString, 起始点与终止点的坐标相同, 创建方法与 LineString 一致
from shapely.geometry import LinearRing, Point
ring_1 = LinearRing([(0, 0), (0, 1), (1, 1), (1, 0), (0, 0)])
# 起始点与终止点没有显式封闭
ring_2 = LinearRing([Point(0, 0), Point(0, 1), Point(1, 1), Point(1, 0)])
print(ring_1)
print(ring_2)
# 长度面积
print('length =', ring_2.length, 'area =', ring_2.area)
# 边界框
print('bounds:', ring_2.bounds)
# 坐标值
print('coords:', ring_2.coords[:])在创建 LinearRing 时, 如果坐标点没有封闭, shapely 自动连接第一个点和最后一个点
打印结果如下:
LINEARRING (0 0, 0 1, 1 1, 1 0, 0 0)
LINEARRING (0 0, 0 1, 1 1, 1 0, 0 0)
length = 4.0 area = 0.0
bounds: (0.0, 0.0, 1.0, 1.0)
coords: [(0.0, 0.0), (0.0, 1.0), (1.0, 1.0), (1.0, 0.0), (0.0, 0.0)]
Polygon
Polygon 相当于 LinearRing 所围的内容, Polygon 的边界(外环和内环)均为 LinearRing 类型不带"洞"的多边形
from shapely.geometry import LinearRing, Point, Polygon
# 1. 坐标元组
polygon_1 = Polygon([(0, 0), (0, 1), (1, 1), (1, 0), (0, 0)])
# 2. Point
# 起始点与终止点没有显式封闭
polygon_2 = Polygon([Point(0, 0), Point(0, 1), Point(1, 1), Point(1, 0)])
# 3. LinearRing
polygon_3 = Polygon(LinearRing([(0, 0), (0, 1), (1, 1), (1, 0)]))
print("1.", polygon_1)
print("2.", polygon_2)
print("3.", polygon_3)
# 长度面积
print('length =', polygon_1.length, 'area =', polygon_1.area)
# 边界框
print('bounds:', polygon_1.bounds)
# 外环
print('exterior:', polygon_1.exterior)
# 外环的坐标值
print('coords of exterior:', polygon_1.exterior.coords[:])
# 所有内环
# 多边形没有"洞"时, 没有内环
print('interiors:', polygon_1.interiors[:])打印结果如下:
1. POLYGON ((0 0, 0 1, 1 1, 1 0, 0 0))
2. POLYGON ((0 0, 0 1, 1 1, 1 0, 0 0))
3. POLYGON ((0 0, 0 1, 1 1, 1 0, 0 0))
length = 4.0 area = 1.0
bounds: (0.0, 0.0, 1.0, 1.0)
exterior: LINEARRING (0 0, 0 1, 1 1, 1 0, 0 0)
coords of exterior: [(0.0, 0.0), (0.0, 1.0), (1.0, 1.0), (1.0, 0.0), (0.0, 0.0)]
interiors: []
带"洞"的多边形
- 长度: 外环和所有内环长度之和
- 面积: 外环面积减去所有内环的面积
- 内环: x.interiors 是一个迭代器(支持索引与切片), 其元素为内环
from shapely.geometry import Polygon
ex = [(0, 0), (0, 3), (3, 3), (3, 0), (0, 0)]
hole = [(1, 1), (1, 2), (2, 2), (2, 1)]
polygon = Polygon(ex, holes=[hole])
# 长度面积
print('length =', polygon.length, 'area =', polygon.area)
# 边界框
print('bounds:', polygon.bounds)
# 外环
print('exterior:', polygon.exterior)
# 外环的坐标值
print('coords of exterior:', polygon.exterior.coords[:])
# 所有内环
print('interiors:', list(polygon.interiors))
# 第一个内环
print('first interior:', polygon.interiors[0])
# 第一个内环的坐标
print('coords of first interior:', polygon.interiors[0].coords[:])打印结果如下:
length = 16.0 area = 8.0
bounds: (0.0, 0.0, 3.0, 3.0)
exterior: LINEARRING (0 0, 0 3, 3 3, 3 0, 0 0)
coords of exterior: [(0.0, 0.0), (0.0, 3.0), (3.0, 3.0), (3.0, 0.0), (0.0, 0.0)]
interiors: [<shapely.geometry.polygon.LinearRing object at 0x7fdf46c4d7c0>]
first interior: LINEARRING (1 1, 1 2, 2 2, 2 1, 1 1)
coords of first interior: [(1.0, 1.0), (1.0, 2.0), (2.0, 2.0), (2.0, 1.0), (1.0, 1.0)]
集合类型
Point, LineString, Polygon 对应的集合类型分别为 MultiPoint, MultiLineString, MultiPolygon
在创建时, 既可以使用坐标元组作为参数, 也可以使用对应的基本几何对象作为参数
from shapely.geometry import ( LineString, MultiLineString, MultiPoint, MultiPolygon, Point, Polygon ) # 坐标元组参数 mul_point_1 = MultiPoint([(1, 1), (2, 2)]) # 几何对象参数 mul_point_2 = MultiPoint([Point(1, 1), Point(2, 2)]) # 混合参数 mul_point_3 = MultiPoint([(1, 1), Point(2, 2)]) line_1 = LineString([(0, 0), (0, 1)]) line_2 = LineString([Point(1, 0), Point(1, 1)]) multi_line_1 = MultiLineString([[(0, 0), (0, 1)], [(1, 0), (1, 1)]]) multi_line_2 = MultiLineString([line_1, line_2]) polygon_1 = Polygon([(0, 0), (0, 1), (1, 1), (1, 0), (0, 0)]) polygon_2 = Polygon([Point(1, 1), Point(1, 2), Point(2, 2), Point(2, 1)]) # None 表示 holes=None multi_polygon_1 = MultiPolygon([ ([(0, 0), (0, 1), (1, 1), (1, 0), (0, 0)], None), ([(1, 1), (1, 2), (2, 2), (2, 1), (1, 1)], None) ]) multi_polygon_2 = MultiPolygon([polygon_1, polygon_2])
不同类型的基本几何对象也可以组成一个集合对象
from shapely.geometry import GeometryCollection, LineString, Point, Polygon
line = LineString([Point(0, 1), Point(0, 2)])
polygon = Polygon([Point(1, 1), Point(1, 2), Point(2, 2), Point(2, 1)])
c = GeometryCollection([Point(0, 0), line, polygon])
print(c)
# 长度面积
print('length =', c.length, 'area =', c.area)
# 边界框
print('bounds:', c.bounds)集合对象也具有长度, 面积, 边界框等属性
打印结果:
GEOMETRYCOLLECTION (POINT (0 0), LINESTRING (0 1, 0 2), POLYGON ((1 1, 1 2, 2 2, 2 1, 1 1)))
length = 5.0 area = 1.0
bounds: (0.0, 0.0, 2.0, 2.0)
导出
常用的数据格式包括 wkt(well-know text) 和 wkb(well-know binary)
import shapely
from shapely import Point, wkb, wkt
p = Point(1, 1)
print("initial wkb:", wkb.dumps(p))
print("initial wkt:", wkt.dumps(p))打印结果:
initial wkb: b'\x01\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\xf0?'
initial wkt: POINT (1.0000000000000000 1.0000000000000000)
可以稍微优化一下输出格式:
# 十六进制表示
print("wkb with hex:", wkb.dumps(p, hex=True))
# 移除多余的零
print("wkt trim zero:", wkt.dumps(p, trim=True))wkb with hex: 0101000000000000000000F03F000000000000F03F
wkt trim zero: POINT (1 1)
与此类似的 wkb.dump() 和 wkt.dump() 方法将数据导出到文件中
其他导出方法:
print("to_wkb:", shapely.to_wkb(p)) # 等价于 p.wkb
print("to_wkt:", shapely.to_wkt(p)) # 等价于 p.wkt还可以输出 svg 字符串:
print(p._repr_svg_())
在 jupyter notebook 环境下输出几何对象时自动调用 x._repr_svg_() 方法, 输出 svg 图形
导入
import shapely from shapely import wkb, wkt wkb_i = '0101000000000000000000F03F000000000000F03F' wkt_i = 'POINT (1 1)' print(shapely.from_wkb(wkb_i)) print(shapely.from_wkt(wkt_i)) print(wkb.loads(wkb_i)) print(wkt.loads(wkt_i))
打印结果:
POINT (1 1)
POINT (1 1)
POINT (1 1)
POINT (1 1)
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