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 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 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
######################## 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()
# Draw the Asian countries in yellow and print out a few features.
vp.plot(lyr, 'y')
pb.print_attributes(lyr, 4, ['name'], geom=False)
# You can still get a feature that is not in Asia by using its FID.
lyr.GetFeature(2).GetField('name')
# Set a new filter that selects South American countries and show the results
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()
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()
# 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')
######################### Esri file geodatabase ##############################
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
# falls within New Orleans city boundaries.
intersection = marsh_geom.Intersection(nola_geom)
vp.plot(intersection, 'yellow', hatch='x')
# Figure out how much of New Orleans is wetlands. Throw out lakes and anything
# not in the vicinity of New Orleans, and then loop through the remaining water
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()
# 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()
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')
web_mercator_sr = osr.SpatialReference()
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()
def show_line(self, line):
vp = VectorPlotter(False)
vp.plot(line, 'b-')
vp.draw()
def show_polygon(self, polygon):
vp = VectorPlotter(False)
vp.plot(polygon, fill=False, edgecolor='blue')
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()
# 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 #####################################
# Get the shapefile layers in a folder.
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')
def show_point(self, point):
vp = VectorPlotter(False)
vp.plot(point, 'bo')
vp.draw()
######################### 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)
# 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')
ds = ogr.Open(fn)
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.')
# Use the Germany polygon to set a spatial filter and draw the result as blue
# circles.
city_lyr.SetSpatialFilter(germany)
city_lyr.GetFeatureCount()
vp.plot(city_lyr, 'bo')
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)
######################### 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)
######################### 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 ##############################
# Open the large_cities data source.
######################## 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()
# Draw the Asian countries in yellow and print out a few features.
vp.plot(lyr, 'y')
pb.print_attributes(lyr, 4, ['name'], geom=False)
# You can still get a feature that is not in Asia by using its FID.
lyr.GetFeature(2).GetField('name')
# Set a new filter that selects South American countries and show the results
