This package of utilities is a wrapper around the network_wrangler package for MetCouncil. It aims to have the following functionality:
- parse Cube log files and base highway networks and create ProjectCards for Network Wrangler
- parse two Cube transit line files and create ProjectCards for NetworkWrangler
- refine Network Wrangler highway networks to contain specific variables and settings for Metropolitan Council and export them to a format that can be read in by Citilab's Cube software.
Lasso uses Python 3.6 and above. Requirements are stored in requirements.txt but are automatically installed when using pip as are development requirements (for now) which are located in dev-requirements.txt
If you are managing multiple python versions, we suggest using virtualenv or conda virtual environments. All commands should executed in a conda command prompt, not powershell or the system command prompt. Do not add conda to the system path during installation. This may cause problems with other programs that require python 2.7 to be placed in the system path.
Example using a conda environment (recommended):
conda create python=3.7 -n <my_lasso_environment>
source activate <my_lasso_environment>
conda install rtree
conda install shapely
conda install fiona
pip install git+https://github.com/wsp-sag/network_wrangler.git@master#egg=network_wrangler
pip install git+https://github.com/wsp-sag/Lasso@master#egg=lasso
Lasso can be installed in several ways depending on the user's needs. The above installation is the simplest method and is appropriate when the user does not anticipate needing to update lasso. An update will require rebuilding the network wrangler environment. Installing from clone is slightly more involved and requires the user to have a git manager on their machine, but permits the user to install lasso with the -e, edit, option so that their lasso installation can be updated through pulling new commits from the lasso repo without a full reinstallation.
Use the package manager pip to install Lasso from the source on GitHub.
conda install rtree
conda install shapely
pip install -e git+https://github.com/wsp-sag/network_wrangler.git@master#egg=network_wrangler
pip install -e git+https://github.com/wsp-sag/Lasso@master#egg=lasso
Note: if you wanted to install from a specific tag/version number or branch, replace @master with @<branchname> or @tag
If you are going to be working on Lasso locally, you might want to clone it to your local machine and install it from the clone. The -e will install it in editable mode.
if you plan to do development on both network wrangler and lasso locally, consider installing network wrangler from a clone as well!
conda create python=3.7 -n <my_lasso_environment>
source activate <my_lasso_environment>
conda install rtree
conda install shapely
conda install fiona
conda install folium
conda install osmnx
git clone https://github.com/wsp-sag/Lasso
git clone https://github.com/wsp-sag/network_wrangler
cd network_wrangler
pip install -e .
cd ..
cd lasso
pip install -e .Note: if you are not part of the project team and want to contribute code bxack to the project, please fork before you clone and then add the original repository to your upstream origin list per these directions on github.
https://wsp-sag.github.io/Lasso/
Documentation requires the sphinx package and can be built from the /docs folder using the command: make html
To learn basic lasso functionality, please refer to the following jupyter notebooks in the /notebooks directory:
Lasso Project Card Creation Quickstart.ipynbLasso Scenario Creation Quickstart.ipynb
Jupyter notebooks can be started by activating the lasso conda environment and typing jupyter notebook:
conda activate <my_lasso_environment>
jupyter notebookA few other very basic API tips:
Parse a cube line file
import lasso
# read in the transit route information in cube line file format
# this will either read in a string or a filename containing the text
base_transit_lines = CubeTransit.create_from_cube(test_lin)
# Explore the base transit lines
print("Read {} LINES:\n{}".format(len(base_transit_lines.lines), "\n - ".join(base_transit_lines.lines)))
ex_line_name = base_transit_lines.lines[1]
print("Line: {}".format(ex_line_name))
print("Properties: ", base_transit_lines.line_properties[ex_line_name])
print("Nodes: ", base_transit_lines.shapes[ex_line_name])Compare two lines to create a project card describing their differences
import lasso
test_project = Project.create_project(
base_transit_source=my_file_with_base_lines,
build_transit_source=my_file_with_build_lines,
project_name="My awesome project that will save the koalas.",
)
test_project.write_project_card(os.path.join("project_card_transit.yml"))Read a Network Wrangler TransitNetwork standard and write it to Cube
from network_wrangler import TransitNetwork
wrangler_transit_network = TransitNetwork.read(feed_path=BASE_TRANSIT_DIR_WITH_GTFS)
cube_transit_net = StandardTransit.fromTransitNetwork(wrangler_transit_network)
cube_transit_net.write_as_cube_lin(os.path.join(SCRATCH_DIR, "t_transit_test.lin"))Read a GTFS (frequency only, not schedule-based) network and write it to Cube
from Lasso import StandardTransit
from network_wrangler import TransitNetwork
cube_transit_net = StandardTransit.read_gtfs(BASE_TRANSIT_DIR)
cube_transit_net.write_as_cube_lin(os.path.join(SCRATCH_DIR, "t_transit_test.lin"))Read a wrangler roadway network standard network from file and write it to fixed width format that cube can read
Note that this calculates MetCouncil specific variables and also by default will create a "model-ready" network which separates out managed lanes as parallel links.
from Lasso import ModelRoadwayNetwork
net = ModelRoadwayNetwork.read(
link_file=STPAUL_LINK_FILE,
node_file=STPAUL_NODE_FILE,
shape_file=STPAUL_SHAPE_FILE,
fast=True,
)
net.write_roadway_as_fixedwidth()Read a Cube Log File of changes and produce project cards
from Lasso import Project
lf = Project.read_logfile(logfilename)
my_project = Project.create_project(
roadway_log_file=logfilename, base_roadway_dir=directory_with_roadway_files
)
my_project .write_project_card("my_awesome_project.yml",Issue: Conda is unable to install a library or to update to a specific library version Try installing libraries from conda-forge
conda install -c conda-forge *library*Issue: User does not have permission to install in directories Try running Anaconda Prompt as an administrator.
Repository created in support of Met Council Network Rebuild project. Project lead on the client side is Rachel Wiken. WSP team member responsible for this repository is David Ory.
This project is built upon the ideas and concepts implemented in the network wrangler project by the San Francisco County Transportation Authority and expanded upon by the Metropolitan Transportation Commission.