Hi @gboeing. I'm happy to put forward the first version of the new clean_intersections() method. The method now returns the simplified graph instead of just the intersection centroids.

I've added comments to the code, which hopefully will be easy to follow, but I'm happy to write down the main steps of the algorithm. The method doesn't appear to be (too) slow, but there is probably room for improvement.

There are a few nuances to look out for, e.g. when choosing between multiple geometries, but I think that the final decision was sensible.

Finally, the simplified graph can end up having a lot of nodes of degree 2 (in its undirected version). Therefore, further simplification can be achieved by removing these nodes. I'm working on this, but maybe this should be a separate method.

I'm looking forward to your input. Cheers, Pedro.

Hi,

first of all, awesome work with the package! Highly useful and needed.

I was wondering if there would be interest to include separate functionalities to retrieve OpenStreetMap POIs with osmnx? I am currently starting to write such functionalities for my own project, and I think I will be using osmnx as a basis for fetching Points of interest from OpenStreetMap (such as restaurants etc.). I know that it is possible to work with other infrastructures than roads, but if I have understood correctly that function works only with graphs, not with point data such as POIs.

If you think this would be interesting, I would be happy to help implementing these functions.

Cheers, Henrikki

P.S. FYI: I introduce osmnx also with the fully open GIS course (Lesson 7) that can be found here http://autogis.github.io.

If we run this code:

import osmnx as ox
ox.config(log_console=True)
G = ox.graph_from_place('Baltimore, Maryland, USA', network_type='drive')

We get this error:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-1-afb511cf7347> in <module>()
      1 import osmnx as ox
      2 ox.config(log_console=True)
----> 3 G = ox.graph_from_place('Baltimore, Maryland, USA', network_type='drive')

C:\Anaconda\lib\site-packages\osmnx\osmnx.py in graph_from_place(query, network_type, simplify, retain_all, truncate_by_edge, name, which_result, buffer_dist, timeout, memory, max_query_area_size, clean_periphery)
   1815     # create graph using this polygon(s) geometry
   1816     G = graph_from_polygon(polygon, network_type=network_type, simplify=simplify, retain_all=retain_all, 
-> 1817                            truncate_by_edge=truncate_by_edge, name=name, timeout=timeout, memory=memory, max_query_area_size=max_query_area_size, clean_periphery=clean_periphery)
   1818 
   1819     log('graph_from_place() returning graph with {:,} nodes and {:,} edges'.format(len(G.nodes()), len(G.edges())))

C:\Anaconda\lib\site-packages\osmnx\osmnx.py in graph_from_polygon(polygon, network_type, simplify, retain_all, truncate_by_edge, name, timeout, memory, max_query_area_size, clean_periphery)
   1730         raise ValueError('Shape does not have a valid geometry')
   1731     if not isinstance(polygon, (Polygon, MultiPolygon)):
-> 1732         raise ValueError('Geometry must be a shapely Polygon or MultiPolygon')
   1733 
   1734     if clean_periphery and simplify:

ValueError: Geometry must be a shapely Polygon or MultiPolygon

I am trying to follow the article on the link here (awesome blog btw).

However, every time I try to get a graph from a place using graph_from_place I get the following error:

  File "/home/manuel/miniconda3/envs/test/lib/python3.5/site-packages/osmnx/osmnx.py", line 1815, in graph_from_place
    truncate_by_edge=truncate_by_edge, name=name, timeout=timeout, memory=memory, max_query_area_size=max_query_area_size, clean_periphery=clean_periphery)
  File "/home/manuel/miniconda3/envs/test/lib/python3.5/site-packages/osmnx/osmnx.py", line 1749, in graph_from_polygon
    G = truncate_graph_polygon(G_buffered, polygon, retain_all=retain_all, truncate_by_edge=truncate_by_edge)
  File "/home/manuel/miniconda3/envs/test/lib/python3.5/site-packages/osmnx/osmnx.py", line 1320, in truncate_graph_polygon
    G = get_largest_component(G)
  File "/home/manuel/miniconda3/envs/test/lib/python3.5/site-packages/osmnx/osmnx.py", line 1099, in get_largest_component
    if not nx.is_weakly_connected(G):
  File "<decorator-gen-62>", line 2, in is_weakly_connected
  File "/home/manuel/miniconda3/envs/test/lib/python3.5/site-packages/networkx/utils/decorators.py", line 68, in _not_implemented_for
    return f(*args,**kwargs)
  File "/home/manuel/miniconda3/envs/test/lib/python3.5/site-packages/networkx/algorithms/components/weakly_connected.py", line 178, in is_weakly_connected
    """Connectivity is undefined for the null graph.""")
networkx.exception.NetworkXPointlessConcept: Connectivity i

gdf_from_place works, as well as graph_from_point .

I am using spatialindex=1.8.5

The environment's packages:

click==6.6
click-plugins==1.0.3
cligj==0.4.0
cycler==0.10.0
decorator==4.0.10
descartes==1.0.2
Fiona==1.7.1
geopandas==0.2.1
geopy==1.11.0
matplotlib==1.5.3
munch==2.0.4
networkx==1.11
numpy==1.11.2
OSMnx==0.1a1
pandas==0.19.1
pyparsing==2.1.10
pyproj==1.9.5.1
python-dateutil==2.6.0
pyttsx==1.1
pytz==2016.7
requests==2.12.1
Rtree==0.8.2
Shapely==1.5.17
six==1.10.0

My machine's watermark:

2016-11-28T15:33:21+01:00

CPython 3.5.1
IPython 4.2.0

compiler   : GCC 4.4.7 20120313 (Red Hat 4.4.7-1)
system     : Linux
release    : 4.4.0-47-generic
machine    : x86_64
processor  : x86_64
CPU cores  : 8
interpreter: 64bit

Resolves #478

Work in progress on a new geometries module that combines the capabilities of the existing pois and footprints modules and introduces conversion of ways to LineStrings or Polygons as appropriate.

Example:

# New geometries module
MK = ox.gdf_from_point((52.0430,-0.7590), dist=1000, tags={'highway':True, 'landuse':True, 'building':True})

# Presentation code
MK.to_crs(epsg=27700, inplace=True)

fig,ax = plt.subplots(figsize=(16,16))
MK[MK['landuse'].notna()].plot(ax=ax, column='landuse', cmap='tab20b', legend=True)
MK[MK['highway'].notna()].plot(ax=ax, color='white')
MK[MK['building'].notna()].plot(ax=ax, color='dimgrey', zorder=3)
ax.set_facecolor('darkgrey')
ax.axes.xaxis.set_visible(False)
ax.axes.yaxis.set_visible(False)

Adds tests for OpenStreetMap APIs designed to run on a schedule under AWS Lambda.

• [x] Test simple request to Nominatim
• [x] Test remaining sample calls

This is a stub and I’m looking for feedback on the approach. osm_api_tests.py is outside the normal project hierarchy, and gets deployed to Lambda as a standalone Python 3 script. It’s possible but slightly annoying to include 3rd party packages on Lambda, so I’m using only standard library functionality. If merged, the AWS deployment details will need to be updated.

Will close https://github.com/gboeing/osmnx/issues/107.

This PR consolidates testing and revisions to the work done by @AtelierLibre in #542. Closes #478.

It also incorporates the changes in #552 including:

• renames all the geometries.gdf_from_x functions -> geometries.geometries_from_x
• makes polygon_features module private
• deprecates the footprints module/functions with a user warning
• deprecates the pois module/functions with a user warning
• cleans up comments and docstrings
• autodocs the geometries module

Plus some refactoring/generalizing of code in the truncate and utils_geo modules to make pre-existing code more general for use in both graph construction as well as geometries GeoDataFrame construction.

I'm using osmnx and networkx for calculating shortest routes in Dubai and I'm having an issue when finding the closest road to a tracking location's coordinates. Even if I use coordinates that are right on a specific highway, sometimes it is matched to a close road due to the fact that I use the osmnx.get_nearest_node to find the closest road. This function will search for the closest graph node in the OSM map to that specific location. Due to the fact that for certain highways you have very large distances between consective node, the closest node might not be on the same road on which the tracking location was recorded. It would be nice if there was a method osmnx.get_nearest_edge that mapped each location to the closest road.

Here is an example with 2 orig_coordinates that were recorded on the same highway but the second one is matched to a node on a different road. I recommend using jupyter notebooks to visualize the problem on the map

import networkx as nx
import osmnx as ox
import requests
from matplotlib import pyplot as plt
import matplotlib.cm as cm
import matplotlib.colors as colors
ox.config(use_cache=True, log_console=True)
ox.__version__

# get a graph for some city
SMALL_MARINA = [25.09, 25.06, 55.16, 55.11]
G2 = ox.graph_from_bbox(
    *SMALL_MARINA,
    simplify=False,
    retain_all=True,
    network_type='drive',

)
fig2, ax2 = ox.plot_graph(G2, fig_height=20, fig_width=20)

# get the nearest network node to each point

good_orig_node = ox.get_nearest_node(G2, (25.070661, 55.137911), method='euclidean')
bad_orig_node = ox.get_nearest_node(G2, (25.071764, 55.138978), method='euclidean')
dest_node = ox.get_nearest_node(G2, (25.079223, 55.146241), method='euclidean')



# find the route between these nodes then plot it
route = nx.shortest_path(G2, good_orig_node, dest_node, weight='length')
fig, ax = ox.plot_graph_route(G2, route, fig_height=20, fig_width=20)


# find the route between these nodes then plot it
route = nx.shortest_path(G2, bad_orig_node, dest_node, weight='length')
fig, ax = ox.plot_graph_route(G2, route, fig_height=20, fig_width=20)

Coordinate(South-West) is matched to the right road

Coordinate(South-West) is matched to the wrong road

Over time, the pois and footprints modules have expanded their functionality and grown more similar to each other. I believe they are approximately redundant now and should be merged together to simplify the codebase.

The following methods are approximately equivalent:

import osmnx as ox
ox.config(use_cache=True, log_console=True)
place = 'Emeryville, CA, USA'

# use pois module
po = ox.pois_from_place(place, tags={'building':True})
po.shape #(1117, 73)

# use footprints module
fp = ox.footprints_from_place(place)
fp.shape #(1127, 55)

Minor differences would have to be reconciled between these modules (especially the detailed handling of relations in footprints) to account for the differences between the resulting GeoDataFrames.

Hello all,

I am new here thus excuse me if I am asking something simple.

I have been trying to get osmnx going with that: import osmnx as ox city = ox.gdf_from_place('Berkeley, CA') ox.plot_shape(ox.project_gdf(city))

But I am getting this output error all the time: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed (_ssl.c:590)

Please could you suggest any solutions cause the ones I have seen so far are not working.

Thanks a lot.

Refactor of #343 to use demquery.

Overview:

• I split my code into a new Python package on PyPI.
• Since learning about Virtual Rasters, the code to find elevations is an order of magnitude simpler. I don't do any joining of nearby rasters; GDAL does all of that.
• I discovered that interp2d gives those warnings only when the grid is not the expected size for the type of interpolation: 3x3 for linear interpolation, 5x5 for cubic interpolation, and 7x7 for quintic interpolation. So I removed the option to manually choose the size of the interpolation region. If interp_kind is linear, it creates a 3x3 grid.
• Checks for nodata values; the virtual raster can have regions with no data that are inside the file's bounds, if the provided files didn't create an exact rectangle. My package raises an error if it sees those values in the interpolation region.
• I'm working on writing tests in the demquery package. ~~I'm having issues with rasterio working on Travis CI~~ the osmnx .travis.yml was quite helpful.
• Do you have plans to deprecate Python 2.7 and 3.4? Python 3.4 is already end of life, and 2.7 is in a month. I made demquery 3.5+ compatible, but haven't tested Python 2.7.
• Right now, demquery is only on PyPI, and I think that's why the current Travis build is failing.

Example:

Download both the files USGS_NED_13_n33w117_IMG USGS_NED_13_n34w117_IMG 450MB extracted each

import osmnx as ox
west = -116.66587829589844
south = 32.90120475753773
north = 33.094201303793194
east = -116.46263122558594
G = ox.graph_from_bbox(north=north, south=south, west=west, east=east)
dem_paths = ['USGS_NED_13_n33w117_IMG.img', 'USGS_NED_13_n34w117_IMG.img']
# interp_kind can be None, linear, cubic, or quintic
G = add_node_elevations_from_dem(G, dem_paths, interp_kind=None)
G = add_edge_grades(G)

Somewhat related to issue #915.

Commits are quite self-explanatory, but this fixes a few things:

1. A bug where non-existent tags would get written to the XML file when they shouldn't.
2. Adds a way to specify the OSM version to write in the header
3. Adds a way to specify how many decimals to keep when writing lat-long coordinates
4. Sets the encoding to UTF-8. This is useful for areas that have non-ascii characters in the name (for example, in Québec)

Thanks

OSMnx currently depends on GDAL directly in the elevation module to build VRTs, because rasterio doesn't expose equivalent functionality directly. However, it's not a good idea to import both rasterio and GDAL into the same working environment (see https://github.com/rasterio/rasterio/issues/2573#issuecomment-1368135052).

Rasterio devs are currently proposing new functionality that would allow us to build VRTs directly with rasterio. If so, we could drop the GDAL dependency. See this issue and this PR.

Do not delete the following template. Fill it out completely.

• [x] I have read the OSMnx contributing guidelines
• [x] I have read the OSMnx documentation and usage examples
• [x] I have searched the open/closed issues and pull requests for others similar to mine

Is your feature proposal related to a problem?

The save_graph_xml function adds a lot of (unnecessary?) data to the resulting XML file: https://github.com/gboeing/osmnx/blob/586cf2651af80c2cdb1c6e30b94d8176beea7c4a/osmnx/osm_xml.py#L207-L212

The resulting XML file has a lot of extra fields compared to regular OSM XML files :

<?xml version="1.0"?>
<osm version="0.6" generator="OSMnx">
  <node id="0" timestamp="2017-01-01T00:00:00Z" uid="1" user="osmnx" version="1" changeset="1" lat="45.5571316" lon="-73.5963673">
    <tag k="highway" v="nan"/>
  </node>
  <node id="1" timestamp="2017-01-01T00:00:00Z" uid="1" user="osmnx" version="1" changeset="1" lat="nan" lon="nan">
    <tag k="highway" v="nan"/>
  </node>
  <node id="2" timestamp="2017-01-01T00:00:00Z" uid="1" user="osmnx" version="1" changeset="1" lat="nan" lon="nan">
    <tag k="highway" v="nan"/>
  </node>
  <node id="3" timestamp="2017-01-01T00:00:00Z" uid="1" user="osmnx" version="1" changeset="1" lat="45.5575365" lon="-73.5889391">
    <tag k="highway" v="nan"/>
  </node>
  ...
</osm>

In addition, what's the point of the timestamp if it's always the same date in 2017?

Describe the solution you'd like to propose

Either:

1. Adding a parameter to save_graph_xml to decide whether or not these extra fields should be added to the xml file, or:
2. Removing this code altogether.

Thanks!

Hi @gboeing! I'm working on a streamlit project where users can get bbox coordinates by clicking on a web map. The main goal is to let them create their own street networks and get some relevant stats to study the mobility in the target area.

The folium module looks great to add some interactivity to the analysis but I faced that it only supports LineStrings geometries. And since I do not want to only describe the graph with edges but also with nodes, I was looking for some extra methods to allow plotting them based on their connectivity attributes.

Specifically, I needed to render Point geometries on a Leaflet web map and get them colored by some attribute (betweenness centrality, degree centrality, node degree, etc) with the cmap bar legend/reference. Something like this:

Below I share you the code and some examples:

1. build a Point geoms gdf and add node colors based on some attribute
2. create a circle marker map based on color attributes
3. some examples can be found here

If you find this could be an interesting feature to add in the folium.py module we can have some further discussions about the CircleMarker map implementation.

Thanks!