def polygonReading(fn, pg_lyrName_r):
ds = ogr.Open(fn, 0) #0为只读模式，1为编辑模式
if ds is None:
sys.exit('Could not open{0}'.format(fn))
pg_lyr = ds.GetLayer(pg_lyrName_r) #可以直接数据层(文件)名或者指定索引
vp = VectorPlotter(True) #显示vector数据
vp.plot(pg_lyr)
pg_schema = pg_lyr.schema #查看属性表字段名和类型
for field in pg_schema:
print(field.name, field.GetTypeName())
i = 0
for feat in pg_lyr: #循环feature
print(
".................................................................."
)
atts = feat.items()
print(atts)
pg = feat.geometry() #获取feature的几何对象
# ring=
name = feat.GetField('NAME') #读取feature的属性
Shape_Area = feat.GetField('Shape_Area')
print(name, Shape_Area, '\n', pg, '\n')
for j in range(pg.GetGeometryCount()): #循环几何对象获取ring,获取顶点坐标
ring = pg.GetGeometryRef(j)
for coordi in ring.GetPoints():
print(coordi)
i += 1
if i == 12:
break
del ds
def lineReading(fn, ln_lyrName_r):
ds = ogr.Open(fn, 0) #0为只读模式，1为编辑模式
if ds is None:
sys.exit('Could not open{0}'.format(fn))
ln_lyr = ds.GetLayer(ln_lyrName_r) #可以直接数据层(文件)名或者指定索引
vp = VectorPlotter(True) #显示vector数据
vp.plot(ln_lyr, 'bo')
ln_schema = ln_lyr.schema #查看属性表字段名和类型
for field in ln_schema:
print(field.name, field.GetTypeName())
i = 0
for feat in ln_lyr: #循环feature
ln = feat.geometry() #获取feature的几何对象
name = feat.GetField('name') #读取feature的属性
Shape_Leng = feat.GetField('Shape_Leng')
print(name, Shape_Leng, '\n', ln, '\n', ln.GetPointCount())
for j in range(ln.GetPointCount()): #循环几何对象(线)d的vertex顶点
if j < 6:
print((i, ln.GetX(i), ln.GetY(i))) #只能通过GetX()和GetY()的方法获取顶点坐标
i += 1
if i == 12:
break
del ds
def pointReading(fn, pt_lyrName_r):
ds = ogr.Open(fn, 0) #0为只读模式，1为编辑模式
if ds is None:
sys.exit('Could not open{0}'.format(fn))
pt_lyr = ds.GetLayer(pt_lyrName_r) #可以直接数据层(文件)名或者指定索引
vp = VectorPlotter(True) #显示vector数据
vp.plot(pt_lyr, 'bo')
i = 0
for feat in pt_lyr: #循环feature
pt = feat.geometry()
pt_x = pt.GetX()
pt_y = pt.GetY()
name = feat.GetField('NAME')
kind = feat.GetField('KIND')
print(name, kind, (
pt_x,
pt_y,
))
i += 1
if i == 12:
break
del ds
def show_data(lyr):
"""
显示数据，提供图层参数
:param lyr:
:return:
"""
vp = VectorPlotter(False)
vp.plot(lyr, 'bo')
vp.draw()
def main(sample_shp, img_shp, description=None):
if description == None:
sys.exit("缺少‘描述’ 程序不能运行！")
vp = VectorPlotter(False)
# 打开样本矢量
sample_ds = ogr.Open(sample_shp, 1)
sample_lyr = sample_ds.GetLayer(0)
# 打开影像矢量
image_ds = ogr.Open(img_shp)
img_lyr = image_ds.GetLayer(0)
# 过滤描述信息
# sample_lyr.SetAttributeFilter('描述 = {}'.format(description))
sample_lyr.ResetReading()
sample_lyr.SetAttributeFilter("despict = {}".format("'" + description + "'"))
count = 1
total = sample_lyr.GetFeatureCount()
for feat in sample_lyr:
geom = feat.geometry().Clone()
# 对影像矢量进行筛选
img_lyr.ResetReading()
img_lyr.SetSpatialFilter(geom)
imgforfeat = []
for img_feat in img_lyr:
# 获取属性
img_name = img_feat.GetField('browsefile')
img_names = os.path.splitext(os.path.basename(img_name))[0].split("_")
name_id = "_".join([img_names[0], img_names[4], img_names[5]])
imgforfeat.append(name_id)
img_lyr.SetSpatialFilter(None)
str_name = "/".join(imgforfeat)
feat.SetField('image', str_name)
sample_lyr.SetFeature(feat)
progress(count / total)
count += 1
sample_lyr.SetAttributeFilter(None)
return None
from osgeo import ogr
from matplotlib import pyplot as plt
from ospybook.vectorplotter import VectorPlotter
ring = ogr.Geometry(ogr.wkbLinearRing)
g = ogr.Geometry(ogr.wkbMultiPolygon)
ring.AddPoint(45, 78)
ring.AddPoint(23, 78)
ring.AddPoint(12, 56)
ring.AddPoint(56, 24)
polygon = ogr.Geometry(ogr.wkbPolygon)
polygon.AddGeometry(ring)
polygon.CloseRings()
g.AddGeometry(polygon)
vp = VectorPlotter(True)
ring = polygon.GetGeometryRef(0)
for i in range(ring.GetPointCount()):
ring.SetPoint(i, ring.GetX(i) - 5, ring.GetY(i))
g.AddGeometry(polygon)
vp.plot(g, name='Polygon')
plt.ioff()
plt.show()
pb.print_attributes(fn, 3, ['NAME', 'POP_MAX'])
# Turn off geometries but skip field list parameters that come before the
# "geom" one.
#pb.print_attributes(fn, 3, geom=False)
# If you want to see what happens without the "geom" keyword in the last
# example, try this:
#pb.print_attributes(fn, 3, False)
# Import VectorPlotter and change directories
from ospybook.vectorplotter import VectorPlotter
os.chdir(os.path.join(data_dir, 'global'))
# Plot populated places on top of countries from an interactive session.
vp = VectorPlotter(True)
vp.plot('ne_50m_admin_0_countries.shp', fill=False)
vp.plot('ne_50m_populated_places.shp', 'bo')
# Plot populated places on top of countries non-interactively. Delete the vp
# variable if you tried the interactive one first.
del vp
vp = VectorPlotter(False)
vp.plot('ne_50m_admin_0_countries.shp', fill=False)
vp.plot('ne_50m_populated_places.shp', 'bo')
vp.draw()
######################### 3.4 Getting metadata ##############################
# Open the large_cities data source.
fn = os.path.join(data_dir, 'Washington', 'large_cities.geojson')
# Set this variable to your osgeopy-data directory so that the following
# examples will work without editing. We'll use the os.path.join() function
# to combine this directory and the filenames to make a complete path. Of
# course, you can type the full path to the file for each example if you'd
# prefer.
data_dir = r'D:\osgeopy-data'
# data_dir =
########################## 7.1 Overlay tools ###############################
# Look at New Orleans wetlands. First get a specific marsh feature near New
# Orleans.
vp = VectorPlotter(True)
water_ds = ogr.Open(os.path.join(data_dir, 'US', 'wtrbdyp010.shp'))
water_lyr = water_ds.GetLayer(0)
water_lyr.SetAttributeFilter('WaterbdyID = 1011327')
marsh_feat = water_lyr.GetNextFeature()
marsh_geom = marsh_feat.geometry().Clone()
vp.plot(marsh_geom, 'b')
# Get the New Orleans boundary.
nola_ds = ogr.Open(os.path.join(data_dir, 'Louisiana', 'NOLA.shp'))
nola_lyr = nola_ds.GetLayer(0)
nola_feat = nola_lyr.GetNextFeature()
nola_geom = nola_feat.geometry().Clone()
vp.plot(nola_geom, fill=False, ec='red', ls='dashed', lw=3)
# Intersect the marsh and boundary polygons to get the part of the marsh that
def show_point(self, point):
vp = VectorPlotter(False)
vp.plot(point, 'bo')
vp.draw()
# Try out the function.
print_layers(os.path.join(data_dir, 'Washington', 'large_cities.geojson'))
######################### 4.2.1 SpatiaLite ##################################
# Use the function in ospybook to look at a SpatiaLite database.
pb.print_layers(os.path.join(data_dir, 'global', 'natural_earth_50m.sqlite'))
# Get the populated_places layer.
ds = ogr.Open(os.path.join(data_dir, 'global', 'natural_earth_50m.sqlite'))
lyr = ds.GetLayer('populated_places')
# Plot the populated places layer in the SpatiaList database interactively.
vp = VectorPlotter(True)
vp.plot(lyr, 'bo')
# Plot the populated places layer in the SpatiaList database non-interactively.
vp = VectorPlotter(False)
vp.plot(lyr, 'bo')
vp.draw()
######################### 4.2.2 PostGIS #####################################
# Print out layers in a PostGIS database. This will not work for you unless
# you set up a PostGIS server.
pb.print_layers('PG:user=chris password=mypass dbname=geodata')
######################### 4.2.3 Folders #####################################
def show_polygon(self, polygon):
vp = VectorPlotter(False)
vp.plot(polygon, fill=False, edgecolor='blue')
vp.draw()
# trying this example.
out_fn = os.path.join(data_dir, 'output', 'testdata.shp')
# Create an empty shapefile that uses a UTM SRS. If you run this it will
# create the shapefile with a .prj file containing the SRS info.
sr = osr.SpatialReference()
sr.ImportFromEPSG(26912)
ds = ogr.GetDriverByName('ESRI Shapefile').CreateDataSource(out_fn)
lyr = ds.CreateLayer('counties', sr, ogr.wkbPolygon)
######################### 8.2.4 Projecting geometries #######################
# Get the world landmasses and plot them.
world = pb.get_shp_geom(os.path.join(data_dir, 'global', 'ne_110m_land_1p.shp'))
vp = VectorPlotter(True)
vp.plot(world)
# Create a point for the Eiffel Tower.
tower = ogr.Geometry(wkt='POINT (2.294694 48.858093)')
tower.AssignSpatialReference(osr.SpatialReference(osr.SRS_WKT_WGS84))
# Try to reproject the world polygon to Web Mercator. This should spit out
# an error.
web_mercator_sr = osr.SpatialReference()
web_mercator_sr.ImportFromEPSG(3857)
world.TransformTo(web_mercator_sr)
# Set a config variable and try the projection again.
from osgeo import gdal
gdal.SetConfigOption('OGR_ENABLE_PARTIAL_REPROJECTION', 'TRUE')
provence = sd.GetLayer(0)
provence.SetAttributeFilter('area>16000')
city = provence.GetNextFeature()
city_geo = city.geometry().Clone()
print(city.GetField('long'))
vp.plot(city_geo, 'b')
vp.draw()
return city_geo
def get_intersect():
highway = ogr.Open(r'G:\arcgis data\argis数据\12月16日数据\test_intersect.shp')
way = highway.GetLayer(0)
wayfeature = way.GetNextFeature()
waygeo = wayfeature.geometry().Clone()
vp.plot(waygeo, 'g')
vp.draw()
return waygeo
if __name__ == '__main__':
"""
1.通过两个图层获取两个要素
2.通过要素的geometry().Clone()方法获取几何对象
3.进行相交，获取相交后的几何对象"""
vp = VectorPlotter(False)
citygeo = get_city()
highgeo = get_intersect()
insect = citygeo.Intersection(highgeo)
vp.plot(insect, 'yellow')
vp.draw()
json_lyr.CreateField(pop_fld)
feat_defn = json_lyr.GetLayerDefn()
# Create an output feature to use repeatedly
json_feat = ogr.Feature(feat_defn)
for shp_feat in shp_lyr:
if shp_feat.GetField('CONTINENT') == 'Africa':
# Copy geometry and attribute values if in Africa
name = shp_feat.GetField('NAME')
pop = shp_feat.GetField('POP_EST')
json_feat.SetField('Name', name)
json_feat.SetField('Population', pop)
json_feat.SetGeometry(shp_feat.geometry())
# Insert the data into the GeoJSON file
json_lyr.CreateFeature(json_feat)
# Delete the datasource. Python will write it to disk and close the file when
# the variable isn't needed anymore.
del json_ds
# Visualize the output
pb.print_attributes(json_fn)
vp = VectorPlotter(False)
vp.plot(shp_fn, fc='0.9')
vp.plot(json_fn, 'y')
vp.draw()
from osgeo import ogr from ospybook.vectorplotter import VectorPlotter from matplotlib import pyplot as plt Point = ogr.Geometry(ogr.wkbPoint) Line = ogr.Geometry(ogr.wkbLineString) Line.AddPoint(12,34) Line.AddPoint(15,56) Line.AddPoint(34,37) Point.AddPoint(12,34) BufferDistance = 50 Poly1 = Point.Buffer(BufferDistance) Poly2 = Line.Buffer(10) vp = VectorPlotter(True) vp.plot(Poly1,symbol='b') vp.plot(Poly2,symbol='r') plt.ioff() plt.show()
def show_line(self, line):
vp = VectorPlotter(False)
vp.plot(line, 'b-')
vp.draw()
from osgeo import ogr from matplotlib import pyplot as plt from ospybook.vectorplotter import VectorPlotter line = ogr.Geometry(ogr.wkbLineString) line.AddPoint(1111.7655,65432.88) line.AddPoint(2244.544,87654.86) line.AddPoint(3216.877,5434.097) line.AddPoint(5444.766,6559.98) print(line.ExportToWkt()) vp = VectorPlotter(True) vp.plot(line,symbol='yellow') plt.ioff() plt.show()
# examples will work without editing. We'll use the os.path.join() function # to combine this directory and the filenames to make a complete path. Of # course, you can type the full path to the file for each example if you'd # prefer. # data_dir = r'D:\osgeopy-data' data_dir = ######################### 4.3 Viewing your data ############################## # Set a filename to use for the next several examples. fn = os.path.join(data_dir, 'Washington', 'large_cities.geojson') # Print name and population attributes. import ospybook as pb pb.print_attributes(fn, fields=['NAME', 'POPULATION']) # Import VectorPlotter from ospybook.vectorplotter import VectorPlotter # Plot large_cities on top of counties from an interactive session. vp = VectorPlotter(True) vp.plot(os.path.join(data_dir, 'Washington', 'counties.shp'), fill=False) vp.plot(os.path.join(data_dir, 'Washington', 'large_cities.geojson'), 'bo', ms=8) # Plot big_cities on top of counties non-interactively. vp = VectorPlotter(False) vp.plot(os.path.join(data_dir, 'Washington', 'counties.shp'), fill=False) vp.plot(os.path.join(data_dir, 'Washington', 'large_cities.geojson'), 'bo', ms=8) vp.draw()
print "Tipo geometria features {0}".format(lyr.GetGeomType())
feat = lyr.GetFeature(0)
print "Tipo geometria feature zero {0}".format(feat.geometry().GetGeometryName())
print "Spatial Reference {0}".format(lyr.GetSpatialRef())
#Name and type of field
for field in lyr.schema:
print field.name, field.GetTypeName()
i = 0
for feat in lyr:
pt = feat.geometry()
x = pt.GetX()
y = pt.GetY()
name = feat.GetField('NAME')
pop = feat.GetField('POP_MAX')
# print(name, pop, x, y)
i += 1
if i == 10:
break
del ds
from ospybook.vectorplotter import VectorPlotter
vp = VectorPlotter(True)
vp.plot(fn, 'bo')
vp.show('test')
from osgeo import ogr
from matplotlib import pyplot as plt
from ospybook.vectorplotter import VectorPlotter
point = ogr.Geometry(ogr.wkbPoint)
point.AddPoint(11.34, 63.09)
print(point.ExportToWkt())
x = point.GetX()
y = point.GetY()
vp = VectorPlotter(True)
vp.plot(point, 'rs')
plt.title('CreatePoint')
plt.ioff()
plt.show()
######################### 6.2 Working with points ##########################
########################### 6.2.1 Single points ############################
# Create the firepit point.
firepit = ogr.Geometry(ogr.wkbPoint)
firepit.AddPoint(59.5, 11.5)
# Try out GetX and GetY.
x, y = firepit.GetX(), firepit.GetY()
print('{}, {}'.format(x, y))
# Take a look at the point.
print(firepit)
vp = VectorPlotter(True)
vp.plot(firepit, 'bo')
# Edit the point coordinates.
firepit.AddPoint(59.5, 13)
vp.plot(firepit, 'rs')
print(firepit)
# Or edit the point using SetPoint instead of AddPoint.
firepit.SetPoint(0, 59.5, 13)
print(firepit)
# Make a 2.5D point.
firepit = ogr.Geometry(ogr.wkbPoint25D)
firepit.AddPoint(59.5, 11.5, 2)
print(firepit)
def main(sample_shp1, out_shp):
vp = VectorPlotter(False)
water_ds = ogr.Open(sample_shp1)
water_lyr = water_ds.GetLayer(0)
# 准备输出的shp
out_shp_ds = water_ds.GetDriver().CreateDataSource(out_shp)
out_lyr = out_shp_ds.CreateLayer('category', srs=water_lyr.GetSpatialRef(), geom_type=water_lyr.GetGeomType())
# 写入属性字段
out_lyr.CreateFields(water_lyr.schema)
# 新增字段
coor_fld = ogr.FieldDefn('相交面', ogr.OFTString)
coor_fld.SetWidth(50)
out_lyr.CreateField(coor_fld)
coor_fld.SetName("总品类")
out_lyr.CreateField(coor_fld)
# 创建初始要素
out_defn = out_lyr.GetLayerDefn()
out_feat = ogr.Feature(out_defn)
mem_dri = ogr.GetDriverByName('Memory')
mem_ds = mem_dri.CreateDataSource(' ')
temp_lyr = mem_ds.CopyLayer(water_lyr, 'temp_lyr')
water_lyr.ResetReading()
for feat in water_lyr:
geometry = feat.geometry().Clone()
temp_lyr.SetSpatialFilter(geometry)
for freq in range(temp_lyr.GetFeatureCount() - 1):
pass
# 拷贝feat
category = new_feat.GetField('地类')
objectid = new_feat.GetField('OBJECTID')
for i in range(new_feat.GetFieldCount()):
value = feat.GetField(i)
out_feat.SetField(i, value)
out_feat.SetField(out_feat.GetFieldCount() - 2, objectid)
out_feat.SetField(out_feat.GetFieldCount() - 1, category)
out_feat.SetGeometry(geometry)
out_lyr.CreateFeature(out_feat)
objectids = []
categorys = []
intersection_geom = []
intersection_geom_temp = []
objectids.append(str(objectid))
categorys.append(category)
intersection_geom_temp.append(geometry.Clone())
for igeom in intersection_geom:
for new_feat in temp_lyr:
if new_feat.GetField('OBJECTID') in objectids:
continue
category = new_feat.GetField('地类')
objectid = new_feat.GetField('OBJECTID')
new_geom = new_feat.geometry().Clone()
intersection = new_geom.Intersection(geometry)
if intersection.Area() != 0.0:
intersection_geom.append(intersection.Clone)
for i in range(new_feat.GetFieldCount()):
value = feat.GetField(i)
out_feat.SetField(i, value)
if category not in categorys:
categorys.append(category)
if objectid not in objectids:
objectids.append(str(objectid))
objectids.sort()
all_category = '/'.join(categorys)
all_objectid = '/'.join(objectids)
geometry = intersection.Clone()
out_feat.SetField(out_feat.GetFieldCount() - 2, all_objectid)
out_feat.SetField(out_feat.GetFieldCount() - 1, all_category)
out_feat.SetGeometry(intersection)
out_lyr.CreateFeature(out_feat)
temp_lyr.SetSpatialFilter(None)
out_shp_ds.SyncToDisk()
out_shp_ds = None
return None
# Set a new filter that selects South American countries and show the results
# in blue. The old filter is no longer in effect.
lyr.SetAttributeFilter('continent = "South America"')
vp.plot(lyr, 'b')
# Clear all attribute filters.
lyr.SetAttributeFilter(None)
lyr.GetFeatureCount()
########################## 5.2 Spatial filters #############################
# Set up an interactive plotter.
vp = VectorPlotter(True)
# Get the Germany polygon. Make sure to plot the full layer before setting the
# filter, or you'll only plot Germany (or you could clear the filter and then
# plot).
ds = ogr.Open(os.path.join(data_dir, 'global'))
country_lyr = ds.GetLayer('ne_50m_admin_0_countries')
vp.plot(country_lyr, fill=False)
country_lyr.SetAttributeFilter('name = "Germany"')
feat = country_lyr.GetNextFeature()
germany = feat.geometry().Clone()
# Plot world cities as yellow dots.
city_lyr = ds.GetLayer('ne_50m_populated_places')
city_lyr.GetFeatureCount()
vp.plot(city_lyr, 'y.')
from osgeo import ogr, osr, gdal
import ospybook
from ospybook.vectorplotter import VectorPlotter
import pyproj
vp = VectorPlotter(False) # 用于显示几何成果
# 创建控件参考对象
# sr = osr.SpatialReference() # 创建一个空的空间参考对象
# sr.ImportFromEPSG() # 使用EPSG码来定义空间参考系统，26912代表NAD83 UTM 12N
# # 使用proj4来定义空间参考系统
# #sr.ImportFromProj4('''+proj=utm +zone=12 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs ''')
# print(sr.GetAttrValue('PROJCS'))
# 自定义空间坐标系
# sr = osr.SpatialReference()
# sr.SetProjCS('USER Albers') # 定义投影的名称
# sr.SetWellKnownGeogCS('NAD83') # 设定基准
# sr.SetACEA(29.5, 45.5, 23, -96, 0, 0) # 设定参数：标准平行线1， 标准平行线2， 中央纬线， 中央经线， 东移假定值， 北移假定值
# sr.Fixup() # 该函数用于为缺少的参数添加默认值，并重新排序项目，以使它们与标准匹配
# print(sr.Validate()) # 该函数用于确保没有缺少任何东西，返回一个0表示一切正常
# 几何对象重投影
# file_path = r"C:\Users\think\Desktop\python\python-for-GIS-DATA\osgeopy-data\osgeopy-data\global\ne_110m_land_1p.shp"
# world = ospybook.get_shp_geom(file_path) # 该方法可以从shape file中获得第一个几何对象
# tower = ogr.Geometry(wkt='POINT (2.294694 48.858093)') # 获取艾弗尔铁塔的位置
# # 使用AssignSpatialReference函数为几何对象分配SRS，但是它并不会将数据转换到该坐标系下，仅仅是提供空间信息
# tower.AssignSpatialReference(osr.SpatialReference(osr.SRS_WKT_WGS84)) # 因为WGS84坐标系很常用，所以在OSR模块中有一个常量，
# # 用于表示该地理坐标系统的WKT。
# gdal.SetConfigOption('OGR_ENABLE_PARTIAL_REPROJECTION', 'TRUE') # 该方式可以修复，在进行web墨卡托投影时，南北极投影出错的问题
# web_mercator_sr = osr.SpatialReference() # 第一步还是创建空的空间参考对象
# web_mercator_sr.ImportFromEPSG(3857)
shp_row.SetField('timestamp', timestamp)
shp_lyr.CreateFeature(shp_row)
del csv_ds # 再使用完CSV数据后将其删除
# 剔除图层中GPS定位错误的点
shp_lyr.SetSpatialFilterRect(-1, -1, 1, 1)
for shp_row in shp_lyr:
shp_lyr.DeleteFeature(shp_row.GetFID())
shp_lyr.SetSpatialFilter(None)
shp_ds.ExecuteSQL("REPACK " + shp_lyr.GetName()) # 使用REPACK永久的删除错误点
shp_ds.ExecuteSQL("RECOMPUTE EXTENT ON " +
shp_lyr.GetName()) # 重新计算shapefile的空间范围
# 绘制结果
vp = VectorPlotter(False)
# vp.plot(shp_lyr, 'r.')
# 定义一个从属性列表中获得唯一值的方法
def get_unique(datasource, layer_name, field_name):
sql = "SELECT DISTINCT {0} FROM {1}".format(field_name, layer_name)
lyr = datasource.ExecuteSQL(sql)
values = []
for row in lyr:
values.append(row.GetField(field_name))
datasource.ReleaseResultSet(lyr)
return values
# Try out the function.
print_layers(os.path.join(data_dir, 'Washington', 'large_cities.geojson'))
######################### SpatiaLite #########################################
# Use the function in ospybook to look at a SpatiaLite database.
pb.print_layers(os.path.join(data_dir, 'global', 'natural_earth_50m.sqlite'))
# Get the populated_places layer.
ds = ogr.Open(os.path.join(data_dir, 'global', 'natural_earth_50m.sqlite'))
lyr = ds.GetLayer('populated_places')
# Plot the populated places layer in the SpatiaList database interactively.
vp = VectorPlotter(True)
vp.plot(lyr)
# Plot the populated places layer in the SpatiaList database non-interactively.
vp = VectorPlotter(False)
vp.plot(lyr)
vp.draw()
######################### PostGIS ############################################
# Print out layers in a PostGIS database. This will not work for you unless
# you set up a PostGIS server.
pb.print_layers('PG:user=chris password=mypass dbname=geodata')
######################### 6.2 Working with points ##########################
########################### 6.2.1 Single points ############################
# Create the firepit point.
firepit = ogr.Geometry(ogr.wkbPoint)
firepit.AddPoint(59.5, 11.5)
# Try out GetX and GetY.
x, y = firepit.GetX(), firepit.GetY()
print('{}, {}'.format(x, y))
# Take a look at the point.
print(firepit)
vp = VectorPlotter(True)
vp.plot(firepit, 'bo')
# Edit the point coordinates.
firepit.AddPoint(59.5, 13)
vp.plot(firepit, 'rs')
print(firepit)
# Or edit the point using SetPoint instead of AddPoint.
firepit.SetPoint(0, 59.5, 13)
print(firepit)
# Make a 2.5D point.
firepit = ogr.Geometry(ogr.wkbPoint25D)
firepit.AddPoint(59.5, 11.5, 2)
print(firepit)
box2 = ogr.Geometry(ogr.wkbLinearRing)
box2.AddPoint(89, 23)
box2.AddPoint(92, 23)
box2.AddPoint(92, 22)
box2.AddPoint(89, 22)
garden2 = ogr.Geometry(ogr.wkbPolygon)
garden2.AddGeometry(box2)
# 因为复合多边形是由一个人或多个多边形构成的，所以创建复合多边形向其中添加的是多边形。
gardens = ogr.Geometry(ogr.wkbMultiPolygon)
gardens.AddGeometry(garden1)
gardens.AddGeometry(garden2)
gardens.CloseRings() # 一次性关闭所有的环
print(gardens)
vp = VectorPlotter(False)
vp.plot(gardens)
# 整体移动复合多边形
for i in range(gardens.GetGeometryCount()):
ring = gardens.GetGeometryRef(i).GetGeometryRef(0)
for j in range(ring.GetPointCount()):
ring.SetPoint(j, ring.GetX(j) + 1, ring.GetY(j) + 0.5)
vp.plot(gardens, fill=False, ec='red', ls='dashed')
# 创建带有岛的多边形
lot = ogr.Geometry(ogr.wkbLinearRing)
lot.AddPoint(58, 38.5)
lot.AddPoint(53, 6)
lot.AddPoint(99.5, 19)
lot.AddPoint(73, 42)
# to combine this directory and the filenames to make a complete path. Of
# course, you can type the full path to the file for each example if you'd
# prefer.
# data_dir = r'D:\osgeopy-data'
data_dir =r'C:\Users\westshell_ASUS\Documents\GisData\osgeopy-data'
######################## 5.1 Attribute filters #############################
# Set up an interactive plotter. Because this is the most fun if you do it
# interactively, you'll probably want to do it from the Python interactive
# prompt. If you're going to run it as a script instead, you might want to use
# a non-interactive plotter instead. Just remember to call draw() when you're
# done.
vp = VectorPlotter(True)
# Get the countries shapefile layer
ds = ogr.Open(os.path.join(data_dir, 'global'))
lyr = ds.GetLayer('ne_50m_admin_0_countries')
# Plot the countries with no fill and also print out the first 4 attribute
# records.
vp.plot(lyr, fill=False)
pb.print_attributes(lyr, 4, ['name'], geom=False)
# Apply a filter that finds countries in Asia and see how many records there
# are now.
lyr.SetAttributeFilter('continent = "Asia"')
lyr.GetFeatureCount()
print(feat.GetField('Name'), pt.GetX(), pt.GetY())
######################### 3.3.2 Viewing your data ###########################
# Print name and population attributes.
import ospybook as pb
fn = os.path.join(data_dir, 'global', 'ne_50m_populated_places.shp')
pb.print_attributes(fn, 3, ['NAME', 'POP_MAX'])
# Import VectorPlotter and change directories
from ospybook.vectorplotter import VectorPlotter
os.chdir(os.path.join(data_dir, 'global'))
# Plot populated places on top of countries from an interactive session.
vp = VectorPlotter(True)
vp.plot('ne_50m_admin_0_countries.shp', fill=False)
vp.plot('ne_50m_populated_places.shp', 'bo')
# Plot populated places on top of countries non-interactively. Delete the vp
# variable if you tried the interactive one first.
del vp
vp = VectorPlotter(False)
vp.plot('ne_50m_admin_0_countries.shp', fill=False)
vp.plot('ne_50m_populated_places.shp', 'bo')
vp.draw()
######################### 3.4 Getting metadata ##############################
# Set this variable to your osgeopy-data directory so that the following
# examples will work without editing. We'll use the os.path.join() function
# to combine this directory and the filenames to make a complete path. Of
# course, you can type the full path to the file for each example if you'd
# prefer.
# data_dir = r'D:\osgeopy-data'
data_dir = r""
######################## 5.1 Attribute filters #############################
# Set up an interactive plotter. Because this is the most fun if you do it
# interactively, you'll probably want to do it from the Python interactive
# prompt. If you're going to run it as a script instead, you might want to use
# a non-interactive plotter instead. Just remember to call draw() when you're
# done.
vp = VectorPlotter(True)
# Get the countries shapefile layer
ds = ogr.Open(os.path.join(data_dir, 'global'))
lyr = ds.GetLayer('ne_50m_admin_0_countries')
# Plot the countries with no fill and also print out the first 4 attribute
# records.
vp.plot(lyr, fill=False)
pb.print_attributes(lyr, 4, ['name'], geom=False)
# Apply a filter that finds countries in Asia and see how many records there
# are now.
lyr.SetAttributeFilter('continent = "Asia"')
lyr.GetFeatureCount()
