def exportBuildings(settlements, distance):
unnamed = 1
places = []
for node in settlements.nodes:
locCoord = (float(node.lat), float(node.lon))
placeName = "unnamed"
if "name:en" in node.tags:
placeName = node.tags["name:en"]
elif "name" in node.tags:
placeName = node.tags["name"]
else:
placeName += str(unnamed)
unnamed += 1
try:
buildings = ox.buildings_from_point(point=locCoord,
distance=distance)
ox.save_gdf_shapefile(buildings,
filename=placeName,
folder="SHP/Buildings")
places.append(placeName)
except KeyError as e:
print('error on ' + placeName)
except:
print('I got another exception')
return places
def Save_OSM_gdf_proj(placename=placename, network_type= 'walk', suffix=suffix, folder=OSM_folder):
"""
save a projected geodataframe from a projected graphml file
Parameters
----------
network_type : string
what type of street network to get. Default type is pedestrain network
placename: string
place name
suffix: string
output data date
folder : string
where to save the shapefile, specify local folder path for OSM resource
Returns
-------
none
"""
G_proj = ox.load_graphml(filename='{studyregion}_proj_{network_type}{suffix}.graphml'.format(
studyregion = placename, network_type=network_type, suffix = suffix), folder=folder)
#save projected network geodataframe as shapefile (project to UTM so we can use metres as a unit when buffering)
edges_proj_gdfs = ox.graph_to_gdfs(G_proj, nodes=False, edges=True, fill_edge_geometry=True)
ox.save_gdf_shapefile(edges_proj_gdfs, filename='{studyregion}_proj_{network_type}{suffix}'.format(
studyregion = placename, network_type=network_type, suffix = suffix), folder=folder)
#show network figure
fig, ax = plt.subplots(figsize=(5, 5))
ax = edges_proj_gdfs.plot(ax=ax)
ax.set_axis_off()
fig.suptitle('{} OSM {} street network'.format(placename, network_type), fontsize=14, fontweight='bold')
plt.show()
def getChangchunReign():
city = ox.gdf_from_places(
['南关区,长春,中国', '朝阳区,长春,中国', '二道区,长春,中国', '绿园区,长春,中国', '宽城区,长春,中国'])
city = ox.project_gdf(city)
ox.save_gdf_shapefile(city, filename='test1') #save
ox.plot_shape(city) #show
def test_gdf_shapefiles():
# test loading spatial boundaries, saving as shapefile, and plotting
city = ox.gdf_from_place('Manhattan, New York City, New York, USA')
city_projected = ox.project_gdf(city, to_crs={'init': 'epsg:3395'})
ox.save_gdf_shapefile(city_projected)
city = ox.gdf_from_place('Manhattan, New York City, New York, USA', buffer_dist=100)
ox.plot_shape(city)
def test_gdf_shapefiles():
city = ox.gdf_from_place('Manhattan, New York City, New York, USA')
city_projected = ox.project_gdf(city, to_crs={'init':'epsg:3395'})
ox.save_gdf_shapefile(city_projected)
city = ox.gdf_from_place('Manhattan, New York City, New York, USA', buffer_dist=100)
ox.plot_shape(city)
def test_gdf_shapefiles():
# test loading spatial boundaries, saving as shapefile, and plotting
city = ox.gdf_from_place('Manhattan, New York City, New York, USA')
city_projected = ox.project_gdf(city, to_crs={'init':'epsg:3395'})
ox.save_gdf_shapefile(city_projected)
city = ox.gdf_from_place('Manhattan, New York City, New York, USA', buffer_dist=100)
ox.plot_shape(city)
def test_gdf_shapefiles():
with httmock.HTTMock(get_mock_response_content()):
city = ox.gdf_from_place('Manhattan, New York City, New York, USA')
city_projected = ox.project_gdf(city, to_crs={'init':'epsg:3395'})
ox.save_gdf_shapefile(city_projected)
with httmock.HTTMock(get_mock_response_content()):
city = ox.gdf_from_place('Manhattan, New York City, New York, USA', buffer_dist=100)
ox.plot_shape(city)
def save(G, fName):
"""suggest different file formats"""
nx.write_gml(G, fName + ".gml")
# G = nx.read_gml(fName+".gml")
if False:
ox.save_graphml(G, filename=fName, folder=baseDir + "gis/graph/")
ox.save_gdf_shapefile(graph, filename=fName + ".gdf", folder=baseDir + "gis/graph/")
ox.save_graphml(G, filename=gName, folder=baseDir + "gis/graph/")
G = ox.load_graphml(filename=gName, folder=baseDir + "gis/graph/")
ox.save_gdf_shapefile(G, filename=fName + ".gdf", folder=baseDir + "gis/graph/")
G = ox.load_graphml(filename=fName + ".gdf", folder=baseDir + "gis/graph/")
nx.readwrite.write_shp(G, baseDir + "gis/graph/berlin_street")
nx.write_graphml_lxml(G, baseDir + "fName" + ".graphml")
def build_gdf(places, gdf_name, location=PATH_GDF, save_gdf=True):
places = [places] if isinstance(places, list) else places
state = False
print(f'Building GDF for {places}')
try:
gdf = ox.gdf_from_place(places, gdf_name=gdf_name)
ox.save_gdf_shapefile(gdf, gdf_name, location) if save_gdf else None
state = True
except Exception as exc:
print(exc)
return state
def get_osm_highways_in_bounds(bounds,
network_type='all',
simplify=True,
to_save=False,
out_dir=None):
"""
Args:
- bounds (tuple): min_x, min_y, max_x, max_y
Returns:
- gdf_e (geopandas DataFrame)
- (Optionally) saves to a shapefile
"""
bbox = to_osmbbox(bounds) #north, south, east, west (ie. max_lat, min_lat, max_lon, min_lon)
g = ox.graph_from_bbox(*bbox, network_type=network_type, simplify=simplify)
gdf_nodes, gdf_edges = ox.graph_to_gdfs(g)
# drop unnecessay columns
if 'ref' in gdf_nodes.columns:
gdf_nodes.drop('ref', axis=1, inplace=True)
edge_cols_keep = ['geometry', 'highway','length', 'osmid']
gdf_edges = gdf_edges[edge_cols_keep]
if to_save:
now = now_str()
out_dir = out_dir or f'/tmp/osmnx/highways/{now}'
if isinstance(out_dir, str):
out_dir = Path(out_dir)
if not out_dir.exists():
out_dir.mkdir(parents=True)
print(f'{out_dir} is created')
ox.save_gdf_shapefile(gdf_edges, 'osm_edges', str(out_dir))
ox.save_gdf_shapefile(gdf_nodes, 'osm_nodes', str(out_dir))
print(f"Saved gdf_edges to {out_dir}/osm_edges")
print(f"Saved gdf_nodes to {out_dir}/osm_nodes")
return gdf_nodes, gdf_edges
import shapefile
from json import dumps
import osmnx as ox
%matplotlib inline
ox.config(log_console=True, use_cache=True)
ox.__version__
place = 'Piedmont, California, USA'
gdf = ox.gdf_from_place(place)
gdf.loc[0, 'geometry']
ox.save_gdf_shapefile(gdf, filename='place-shape2', folder='data')
# read the shapefile
reader = shapefile.Reader("data/place-shape2/place-shape2.shp")
fields = reader.fields[1:]
field_names = [field[0] for field in fields]
buffer = []
for sr in reader.shapeRecords():
atr = dict(zip(field_names, sr.record))
geom = sr.shape.__geo_interface__
buffer.append(dict(type="Feature", \
geometry=geom, properties=atr))
# write the GeoJSON file
geojson = open("pyshp-demo.json", "w")
geojson.write(dumps({"type": "FeatureCollection", "features": buffer}, indent=2) + "\n")
geojson.close()
start_0 = time.time()
# Create and check the path
path = 'data/bikes_streets/{}/'.format(name)
assure_path_exists(path)
path_simple = 'data/bikes_streets/{}/simple/'.format(name)
assure_path_exists(path_simple)
print('Starting with: {}'.format(name))
# Download the shape
city_shape = area(city)
city_shape = ox.project_gdf(city_shape)
ox.save_gdf_shapefile(city_shape,
filename='{}_shape'.format(name),
folder=path)
print('Saved')
ox.plot_shape(city_shape)
# Drive
'''
G_drive = get_network(city, n_type='drive')
ox.save_graphml(G_drive, filename='{}_drive.graphml'.format(name), folder=path)
print('{} Drive downloaded and saved. Elapsed time {} s\nSimplifying the network...'.format(
name, round(time.time()-start_0, 2)))
G_simple = simplify_graph(G_drive)
nx.write_edgelist(G_simple, path=path_simple+'{}_drive_simple.txt'.format(name))
print('{} Drive simplified and saved. Elapsed time {} s'.format(
name, round(time.time()-start_0, 2)))
import osmnx as ox, geopandas as gpd
ox.config(log_file=True, log_console=True, use_cache=True)
location_point = (-17.1010286, 145.7753749)
gdf = ox.buildings_from_point(point=location_point, distance=5000)
gdf_proj = ox.project_gdf(gdf)
bbox = ox.bbox_from_point(point=location_point,
distance=5000,
project_utm=True)
fig, ax = ox.plot_buildings(gdf_proj)
import osmnx as ox, geopandas as gpd
ox.config(log_file=True, log_console=True, use_cache=True)
place_names = ['Gordonvale, Queensland, Australia']
east_bay = ox.gdf_from_places(place_names)
ox.save_gdf_shapefile(east_bay)
east_bay = ox.project_gdf(east_bay)
fig, ax = ox.plot_shape(east_bay)
import osmnx as ox
ox.config(log_file=True, log_console=True, use_cache=True)
city = ox.gdf_from_place('Sydney, New South Wales, Australia')
city
ox.save_gdf_shapefile(city)
city = ox.project_gdf(city)
fig, ax = ox.plot_shape(city)
import osmnx as ox
from IPython.display import Image
ox.config(log_console=True, use_cache=True)
import osmnx as ox
%matplotlib inline
ox.config(log_console=True, use_cache=True)
ox.__version__
##Area by lat/long points listed below:
north, south, east, west = 40.0680, 40.0135, -111.7046, -111.7771
'''
place = 'Payson, Utah, USA'
gdf = ox.gdf_from_place(place)
#gdf.loc[0, 'geometry']
ox.save_gdf_shapefile(gdf, filename='place-shape2', folder='data')'''
print('hi')
B = ox.graph_from_bbox(north, south, east, west, network_type='drive')
ox.save_graph_shapefile(B, filename='the-place', folder='data')
print('hi hi')
'''B = ox.graph_from_bbox(north, south, east, west, network_type='drive')
gdf_nodes, gdf_edges = ox.graph_to_gdfs(
B,
nodes=True, edges=True,
node_geometry=True,
fill_edge_geometry=True)
ox.save_gdf_shapefile(gdf_nodes, filename='the_places_nodes', folder='data')
ox.save_gdf_shapefile(gdf_edges, filename='the_places_edges', folder='data')
# coding: utf-8
# In[5]:
import osmnx as ox
city = ox.gdf_from_place('Berkeley, California')
ox.plot_shape(ox.project_gdf(city))
# In[10]:
places = ox.gdf_from_places(['Botswana', 'Zambia', 'Zimbabwe'])
places = ox.project_gdf(places)
ox.save_gdf_shapefile(places)
ox.plot_shape(ox.project_gdf(places))
# In[11]:
G = ox.graph_from_bbox(37.79, 37.78, -122.41, -122.43, network_type='drive')
G_projected = ox.project_graph(G)
ox.plot_graph(G_projected)
# In[12]:
G = ox.graph_from_point((37.79, -122.41), distance=750, network_type='all')
for city_polygon,city_name,e,w,n,s in zip(dongSanSheng['geometry'],dongSanSheng['place_name'],dongSanSheng['bbox_east'],dongSanSheng['bbox_west'],dongSanSheng['bbox_north'],dongSanSheng['bbox_south']):
placeName = city_name.split(',')[0]
placeName = placeName.split('/')
print(placeName)
if len(placeName) > 1 and placeName[1].strip() == '白山市':
placeName = '白山市'
else:
placeName = placeName[0].strip()
if isinstance(city_polygon, (Polygon, MultiPolygon)):
x = (float(e) + float(w))/2
y = (float(n) + float(s))/2
city_point_df = GeoDataFrame([{'geometry' : Point(x, y).buffer(0.6)}])
city_point_polygon = city_point_df['geometry'][0]
print(placeName)
dongSanSheng_city_byPoint = GeoDataFrame([{'place_name':placeName, 'geometry':city_point_polygon}])
objectName = placeName + '坐标圆001'
ox.save_gdf_shapefile(dongSanSheng_city_byPoint,filename=objectName, folder='osmnx_data/city/')
filename1 = 'osmnx_data/city/'+objectName+'/'+placeName+'坐标圆001.shp'
filename2 = 'osmnx_data/city/shp/'+placeName+'001.shp'
elif isinstance(city_polygon, Point):
city_point_df = GeoDataFrame([{'geometry' : city_polygon.buffer(0.6)}])
city_point_polygon = city_point_df['geometry'][0]
print(placeName)
dongSanSheng_city_byPoint = GeoDataFrame([{'place_name':placeName, 'geometry':city_point_polygon}])
objectName = placeName + '坐标圆001'
ox.save_gdf_shapefile(dongSanSheng_city_byPoint,filename=objectName, folder='osmnx_data/city/')
filename1 = 'osmnx_data/city/'+objectName+'/'+placeName+'坐标圆001.shp'
filename2 = 'osmnx_data/city/shp/'+placeName+'001.shp'
else:
print('wrong datatype!')
nx.write_shp(g, baseDir + "gis/graph/network_de")
pg = nx.to_pandas_edgelist(g)
pg = gpd.GeoDataFrame(pg)
pg.to_file(baseDir + "gis/graph/network_de.geojson")
nx.set_edge_attributes(graph, keys)
nx.write_shp(graph, baseDir + "gis/graph/")
nx.write_gml(graph, baseDir + "gis/graph/network_de")
nx.write_gexf(g, baseDir + "gis/graph/network_de.gexf")
ox.save_graphml(graph,
filename="routes_germany.graphml",
folder=baseDir + "gis/graph/")
ox.save_gdf_shapefile(graph,
filename="routes_germany.gdf",
folder=baseDir + "gis/graph/")
pg = nx.to_pandas_edgelist(graph)
pg = gpd.GeoDataFrame(pg)
pg.to_file(baseDir + "gis/graph/network_de.geojson")
pg.to_file(baseDir + "gis/graph/network_de.shp", driver='ESRI Shapefile')
print(fiona.supported_drivers)
zipN = pd.read_csv(baseDir + 'gis/graph/zip_node.csv')
nodeG = list(graph.nodes(data=True))
nodeD = pd.DataFrame(nodeG)
nodeL = []
for g in nodeG:
kDict = g[1]
kDict['id'] = g[0]
import networkx as nx
import numpy as np
import pandas as pd
import matplotlib.cm as cm
# filter residential and unclassified roads road
filter = (
'["highway"!~"residential|unclassified|living_street|track|abandoned|path|footway|service|pedestrian|road|'
'raceway|cycleway|steps|construction"]')
Catania = ox.graph_from_address('Catania, Italy',
distance=20000,
network_type='drive',
custom_filter=filter)
# check what is inside the edges (type of roads)
edge_file = Catania.edges(keys=True, data=True)
ox.plot_graph(Catania)
Catania_shp = ox.gdf_from_place('Catania, Italy')
ox.save_gdf_shapefile(Catania_shp)
# save street network as GraphML file
# Catania_projected = ox.project_graph(Catania)
# ox.save_graphml(Catania_projected, filename='network_Catania_20km_epgs4326.graphml')
ox.save_graphml(Catania, filename='network_Catania_20km_epgs4326.graphml')
# save street network as ESRI shapefile (includes NODES and EDGES)
# ox.save_graph_shapefile(Catania_projected, filename='networkCatania_20km__shape')
ox.save_graph_shapefile(Catania, filename='networkCatania_20km__shape')
place_names = ['Ho Chi Minh City, Vietnam',
#'Beijing, China',
#'Jakarta, Indonesia',
'London, UK',
'Los Angeles, California, USA',
'Manila, Philippines',
#'Mexico City, Mexico',
'New Delhi, India',
'Sao Paulo, Brazil',
'New York, New York, USA',
'Seoul',
'Singapore',
#'Tokyo, Japan',
#'Nairobi, Kenya',
#'Bangalore, India'
]
# In this for-loop, we save all the shapefiles for the valid cities.
for city in place_names:
city_admin_20kmbuff = ox.gdf_from_place(city, gdf_name = 'global_cities', buffer_dist = 20000)
fig, ax = ox.plot_shape(city_admin_20kmbuff)
ox.save_gdf_shapefile(city_admin_20kmbuff, filename = city)
# In this for-loop, we save all the street networks for the valid cities.
for city in place_names:
grid = ox.graph_from_place(city, network_type = 'drive', retain_all = True)
grid_projected = ox.project_graph(grid)
ox.save_graph_shapefile(grid_projected, filename = city + '_grid')
ox.plot_graph(grid_projected)
@file: osmnxTest.py
@time: 2018/05/{DAY}
描述:
"""
import osmnx as ox
from folium import folium
ox.config(log_file=True, log_console=True, use_cache=True)
# from some place name, create a GeoDataFrame containing the geometry of the place
city = ox.gdf_from_place('雁塔区, 西安, 中国')
#lding = ox.buildings.buildings_from_place('陕西省, 中国')
# save the retrieved data as a shapefile
ox.save_gdf_shapefile(city, u'雁塔区', r'./data/')
#Get building footprints within the boundaries of some place.
aaaBuilding = ox.buildings.buildings_from_place(place=u'雁塔区, 西安, 中国')
#gdf = ox.buildings_from_place(place='Piedmont, California, USA')
ox.save_gdf_shapefile(aaaBuilding, 'test', r'./data/')
#Get building footprints within some distance north, south, east, and west of an address.
#address_rect = ox.buildings.buildings_from_address('钟楼, 南大街, 南院门街道, 碑林区, 西安市, 陕西省, 710001, 中国', 3000)
point_rect = ox.buildings.buildings_from_point((34.374944, 107.129382),
300,
retain_invalid=False)
#Get building footprints within some distance north, south, east, and west of a lat-long point.
ox.plot_shape(point_rect)
# 8. STORE RESULTS TO DISK
edges = generate_xtra_conveyal_tags(edges)
# project the edges back to lat/lon coordinate system
edges = edges.to_crs('EPSG:4326')
if save_as == 'shp':
out_path = os.path.join(data_dir, out_fname)
# turn the edges back to a graph to save as shapefile
logger.info('Saving graph as shapefile. This might take a while...')
nodes.gdf_name = 'nodes'
# ox.save_gdf_shapefile(nodes, 'nodes', out_path)
edges.gdf_name = 'edges'
ox.save_gdf_shapefile(edges, 'edges', out_path)
elif save_as in ['osm', 'pbf']:
logger.info('Saving graph as OSM XML. This might take a while...')
ox.save_as_osm([nodes, edges],
filename=out_fname + '.osm',
folder=data_dir,
node_tags=ox.settings.osm_xml_node_tags,
node_attrs=ox.settings.osm_xml_node_attrs,
edge_tags=ox.settings.osm_xml_way_tags,
edge_attrs=ox.settings.osm_xml_way_attrs,
merge_edges=False)
if save_as == 'pbf':
logger.info('Converting OSM XML to .pbf')
os.system("osmconvert {0}.osm -o={0}.osm.pbf".format(
#Load package ####################################################
import osmnx as ox, geopandas as gpd
import os, sys
#os.chdir('./BRInE/') #Uncomment if running from Atom
from IPython.display import Image
ox.config(log_file=True,log_console=True,use_cache=True)
# Define functions ###############################################
def make_plot(place, point, network_type='drive', bldg_color='orange', dpi=250,dist=1000, default_width=4, street_widths=None):
gdf=ox.buildings_from_point(point=point, distance=dist)
gdf_proj=ox.project_gdf(gdf)
fig, ax=ox.plot_figure_ground(point=point, dist=dist, network_type=network_type, default_width=default_width,street_widths=None, save=False, show=False, close=True)
fig, ax=ox.plot_buildings(gdf_proj, fig=fig, ax=ax, color=bldg_color, set_bounds=False,save=True, show=False, close=True, filename=place, dpi=dpi)
clArguments=sys.argv[1:]
# Location #######################################################
locCoord=(float(clArguments[1]),float(clArguments[2]))
placeName=clArguments[0]
distance=int(clArguments[3])
size=1000
# Buildings ######################################################
buildings=ox.buildings_from_point(point=locCoord,distance=distance)
ox.save_gdf_shapefile(buildings,filename=placeName,folder="SHP/Buildings")
# Roads ##########################################################
#roads=ox.graph_from_point(locCoord,distance=distance,network_type='drive')
#ox.save_graphml(roads,filename=placeName,folder="NTW/Roads")
#ox.save_graph_shapefile(roads, filename=placeName,folder="SHP/Roads")
# Image ##########################################################
# make_plot(placeName,locCoord,dpi=500,dist=distance,default_width=1)
place_name = 'Dakar, Senegal'
G = ox.graph_from_place(place_name, which_result=3)
G_proj = ox.project_graph(G, to_crs=CRS("EPSG:3857"))
nodes_proj, edges_proj = ox.graph_to_gdfs(G_proj)
ox.save_graph_shapefile(G_proj, filename='graph')
#retrieve saved graph and use (if necessary)
edges_saved = "data/graph/edges/edges.shp"
nodes_saved = "data/graph/nodes/nodes.shp"
edges_proj = gpd.read_file(edges_saved)
nodes_proj = gpd.read_file(nodes_saved)
###get boundary of study area
boundary = ox.gdf_from_place(place_name, which_result=3)
boundary_proj = boundary.to_crs(edges_proj.crs)
ox.save_gdf_shapefile(boundary_proj, filename='boundary')
boundary_saved = "data/boundary/boundary.shp"
boundary_proj = gpd.read_file(boundary_saved)
###points-of-interest of study area
### hospitals
hospitals = ox.pois_from_place(place_name,
which_result=3,
amenities=['hospital'])[[
'osmid', 'geometry', 'amenity', 'name',
'element_type'
]]
hospitals = hospitals[hospitals.element_type == 'way']
# walk - get all streets and paths that pedestrians can use (this network type ignores one-way directionality)
# bike - get all streets and paths that cyclists can use
# all - download all non-private OSM streets and paths
# all_private - download all OSM streets and paths, including private-access ones
basic_stats = ox.basic_stats(B)
print(basic_stats['circuity_avg'])
# ans: [1.1167206203103612]
# In this street network, the streets are 12% more circuitous than the straight-lines paths would be.
extended_stats = ox.extended_stats(B)
print(extended_stats['pagerank_max_node'])
# Create place boundary shapefiles from OpenStreetMap
Bracciano_shp = ox.gdf_from_place('Bracciano, Italy')
ox.save_gdf_shapefile(Bracciano_shp)
# using NetworkX to calculate the shortest path between two random nodes
route = nx.shortest_path(B, np.random.choice(B.nodes),
np.random.choice(B.nodes))
ox.plot_graph_route(B, route, fig_height=10, fig_width=10)
# save street network as GraphML file
B_projected = ox.project_graph(B)
ox.save_graphml(B_projected, filename='network_Bracciano_6km_epgs4326.graphml')
# save street network as ESRI shapefile (includes NODES and EDGES)
ox.save_graph_shapefile(B_projected, filename='networkBracciano-shape')
#street network from bounding box
#G = ox.graph_from_bbox(42.2511, 41.3860, 11.6586, 13.4578, network_type='drive_service')
ox.plot_graph(ox.graph_from_place('Houston, Texas, USA'))
plt.savefig("ss.jpg")
plt.plot()
# %%
import geopandas as gpd
os.environ["PROJ_LIB"] = r"C:\Users\User\Anaconda3\Library\share"
import matplotlib.pyplot as plt
import osmnx as ox
ox.config(log_console=True, use_cache=True)
print(ox.__version__)
city = ox.gdf_from_place('Manhattan Island, New York, New York, USA')
ox.save_gdf_shapefile(city)
city = ox.project_gdf(city)
fig, ax = ox.plot_shape(city, figsize=(3, 3))
plt.plot()
# %% http://ericmjl.github.io/Network-Analysis-Made-Simple/2-networkx-basics-instructor.html
out = pd.read_csv(os.path.join("two_component", "moreno_seventh",
"out.moreno_seventh_seventh"),
skiprows=2,
sep=" ",
names=["from", "to", "w"])
with open(
os.path.join("two_component", "moreno_seventh",
"ent.moreno_seventh_seventh.student.gender")) as f:
gender = f.read()
gender = gender.split("\n")