grid2demand


Namegrid2demand JSON
Version 0.6.4 PyPI version JSON
download
home_pagehttps://github.com/xyluo25/grid2demand
SummaryA tool for generating zone-to-zone travel demand based on grid cells or TAZs and gravity model
upload_time2024-09-22 22:46:24
maintainerNone
docs_urlNone
authorXiangyong Luo, Dr.Xuesong(Simon) Zhou
requires_python>=3.10
licenseApache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. "Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. "Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. "You" (or "Your") shall mean an individual or Legal Entity exercising permissions granted by this License. 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Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. 3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. 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keywords demand gravity model travel demand zone-to-zone demand grid cells tazs
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            ## Project description

GRID2DEMAND: A tool for generating zone-to-zone travel demand based on grid cells or TAZs and gravity model

## Introduction

Grid2demand is an open-source quick demand generation tool based on the trip generation and trip distribution methods of the standard 4-step travel model. By taking advantage of OSM2GMNS tool to obtain route-able transportation network from OpenStreetMap, Grid2demand aims to further utilize Point of Interest (POI) data to construct trip demand matrix aligned with standard travel models.

You can get access to the introduction video with the link: [https://www.youtube.com/watch?v=EfjCERQQGTs&t=1021s](https://www.youtube.com/watch?v=EfjCERQQGTs&t=1021s)

You can find base-knowledge tutorial with the link: [Base Knowledge such as transportation 4 stages planning](https://github.com/asu-trans-ai-lab/grid2demand/tree/main/docs)

You can find the tutorial code witht the link: [How To Use Grid2demand](https://github.com/asu-trans-ai-lab/grid2demand/tree/main/tutorial)

## Quick Start

Users can refer to the [code template and test data set](https://github.com/xyluo25/grid2demand/tree/main) to have a quick start.

## Installation

```
pip install grid2demand
```

If you meet installation issues, please reach out to our [developers](mailto:luoxiangyong01@gmail.com) for solutions.

## Demand Generation

[!IMPORTANT]
node.csv and poi.csv should follow the [GMNS](https://github.com/zephyr-data-specs/GMNS) standard and you can generate node.csv and poi.csv using [osm2gmns](https://osm2gmns.readthedocs.io/en/latest/quick-start.html).

### Generate Demand with node.csv and poi.csv

1. Create zone from node.csv (the boundary of nodes), this will generate grid cells (num_x_blocks, num_y_blocks, or x length and y length in km for each grid cell)
2. Generate demands for between zones (utilize nodes and pois)

```python
from __future__ import absolute_import
import grid2demand as gd

if __name__ == "__main__":

    # Specify input directory
    input_dir = "your-data-folder"

    # Initialize a GRID2DEMAND object
    net = gd.GRID2DEMAND(input_dir=input_dir)

    # load network: node and poi
    net.load_network()

    # Generate zone dictionary from node dictionary by specifying number of x blocks and y blocks
    net.net2zone(num_x_blocks=10, num_y_blocks=10)
    # net.net2zone(cell_width=10, cell_height=10, unit="km")

    # Calculate demand by running gravity model
    net.run_gravity_model()

    # Save demand, zone, updated node, updated poi to csv
    net.save_results_to_csv()
```

# Generate Demand with node.csv, poi.csv and zone.csv (zone_id, geometry or x_coord, y_coord fields in zone.csv)

```python
from __future__ import absolute_import
import grid2demand as gd

if __name__ == "__main__":

    # Specify input directory
    input_dir = "your-data-folder"

    # Initialize a GRID2DEMAND object
    net = gd.GRID2DEMAND(input_dir=input_dir)

    # load network: node and poi
    net.load_network()

    # Generate zone
    net.taz2zone()

    # Calculate demand by running gravity model
    net.run_gravity_model()

    # Save demand, zone, updated node, updated poi to csv
    net.save_results_to_csv(overwrite_file=True)
```

# # Generate Demand with node.csv and poi.csv (zone_id exist in node.csv)

```python
from __future__ import absolute_import
import grid2demand as gd

if __name__ == "__main__":

    # Specify input directory
    input_dir = "your-data-folder"
    # make sure you have zone_id field in node.csv

    # Initialize a GRID2DEMAND object
    net = gd.GRID2DEMAND(input_dir=input_dir, use_zone_id=True)

    # load network: node and poi
    net.load_network()

    # Generate zone dictionary from node dictionary by specifying number of x blocks and y blocks
    net.net2zone(num_x_blocks=10, num_y_blocks=10)
    # net.taz2zone()

    # Calculate demand by running gravity model
    net.run_gravity_model()

    # Save demand, zone, updated node, updated poi to csv
    net.save_results_to_csv(overwrite_file=True)
```

## Call for Contributions

The grid2demand project welcomes your expertise and enthusiasm!

Small improvements or fixes are always appreciated. If you are considering larger contributions to the source code, please contact us through email: [Xiangyong Luo](mailto:luoxiangyong01@gmail.com), [Dr. Xuesong Simon Zhou](mailto:xzhou74@asu.edu)

Writing code isn't the only way to contribute to grid2demand. You can also:

* review pull requests
* help us stay on top of new and old issues
* develop tutorials, presentations, and other educational materials
* develop graphic design for our brand assets and promotional materials
* translate website content
* help with outreach and onboard new contributors
* write grant proposals and help with other fundraising efforts

For more information about the ways you can contribute to grid2demand, visit [our GitHub](https://github.com/asu-trans-ai-lab/grid2demand). If you' re unsure where to start or how your skills fit in, reach out! You can ask by opening a new issue or leaving a comment on a relevant issue that is already open on GitHub.

## Citing Grid2demand

If you use grid2demand in your research please use the following BibTeX entry:

Xiangyong Luo, Dustin Carlino, and Xuesong Simon Zhou. (2023). [xyluo25/grid2demand](https://github.com/xyluo25/grid2demand/): Zenodo. https://doi.org/10.5281/zenodo.11212556

            

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    "name": "grid2demand",
    "maintainer": null,
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    "requires_python": ">=3.10",
    "maintainer_email": "Xiangyong Luo <luoxiangyong01@gmail.com>",
    "keywords": "demand, gravity model, travel demand, zone-to-zone demand, grid cells, TAZs",
    "author": "Xiangyong Luo, Dr.Xuesong(Simon) Zhou",
    "author_email": "Xiangyong Luo <luoxiangyong01@gmail.com>, Xuesong Simon Zhou <xzhou74@asu.edu>",
    "download_url": "https://files.pythonhosted.org/packages/54/bb/5e0aac819629547a1e0bf7f25ae0831e46b28d9e6a843174bd6c6f7b9f1f/grid2demand-0.6.4.tar.gz",
    "platform": null,
    "description": "## Project description\r\n\r\nGRID2DEMAND: A tool for generating zone-to-zone travel demand based on grid cells or TAZs and gravity model\r\n\r\n## Introduction\r\n\r\nGrid2demand is an open-source quick demand generation tool based on the trip generation and trip distribution methods of the standard 4-step travel model. By taking advantage of OSM2GMNS tool to obtain route-able transportation network from OpenStreetMap, Grid2demand aims to further utilize Point of Interest (POI) data to construct trip demand matrix aligned with standard travel models.\r\n\r\nYou can get access to the introduction video with the link: [https://www.youtube.com/watch?v=EfjCERQQGTs&amp;t=1021s](https://www.youtube.com/watch?v=EfjCERQQGTs&t=1021s)\r\n\r\nYou can find base-knowledge tutorial with the link: [Base Knowledge such as transportation 4 stages planning](https://github.com/asu-trans-ai-lab/grid2demand/tree/main/docs)\r\n\r\nYou can find the tutorial code witht the link: [How To Use Grid2demand](https://github.com/asu-trans-ai-lab/grid2demand/tree/main/tutorial)\r\n\r\n## Quick Start\r\n\r\nUsers can refer to the [code template and test data set](https://github.com/xyluo25/grid2demand/tree/main) to have a quick start.\r\n\r\n## Installation\r\n\r\n```\r\npip install grid2demand\r\n```\r\n\r\nIf you meet installation issues, please reach out to our [developers](mailto:luoxiangyong01@gmail.com) for solutions.\r\n\r\n## Demand Generation\r\n\r\n[!IMPORTANT]\r\nnode.csv and poi.csv should follow the [GMNS](https://github.com/zephyr-data-specs/GMNS) standard and you can generate node.csv and poi.csv using [osm2gmns](https://osm2gmns.readthedocs.io/en/latest/quick-start.html).\r\n\r\n### Generate Demand with node.csv and poi.csv\r\n\r\n1. Create zone from node.csv (the boundary of nodes), this will generate grid cells (num_x_blocks, num_y_blocks, or x length and y length in km for each grid cell)\r\n2. Generate demands for between zones (utilize nodes and pois)\r\n\r\n```python\r\nfrom __future__ import absolute_import\r\nimport grid2demand as gd\r\n\r\nif __name__ == \"__main__\":\r\n\r\n    # Specify input directory\r\n    input_dir = \"your-data-folder\"\r\n\r\n    # Initialize a GRID2DEMAND object\r\n    net = gd.GRID2DEMAND(input_dir=input_dir)\r\n\r\n    # load network: node and poi\r\n    net.load_network()\r\n\r\n    # Generate zone dictionary from node dictionary by specifying number of x blocks and y blocks\r\n    net.net2zone(num_x_blocks=10, num_y_blocks=10)\r\n    # net.net2zone(cell_width=10, cell_height=10, unit=\"km\")\r\n\r\n    # Calculate demand by running gravity model\r\n    net.run_gravity_model()\r\n\r\n    # Save demand, zone, updated node, updated poi to csv\r\n    net.save_results_to_csv()\r\n```\r\n\r\n# Generate Demand with node.csv, poi.csv and zone.csv (zone_id, geometry or x_coord, y_coord fields in zone.csv)\r\n\r\n```python\r\nfrom __future__ import absolute_import\r\nimport grid2demand as gd\r\n\r\nif __name__ == \"__main__\":\r\n\r\n    # Specify input directory\r\n    input_dir = \"your-data-folder\"\r\n\r\n    # Initialize a GRID2DEMAND object\r\n    net = gd.GRID2DEMAND(input_dir=input_dir)\r\n\r\n    # load network: node and poi\r\n    net.load_network()\r\n\r\n    # Generate zone\r\n    net.taz2zone()\r\n\r\n    # Calculate demand by running gravity model\r\n    net.run_gravity_model()\r\n\r\n    # Save demand, zone, updated node, updated poi to csv\r\n    net.save_results_to_csv(overwrite_file=True)\r\n```\r\n\r\n# # Generate Demand with node.csv and poi.csv (zone_id exist in node.csv)\r\n\r\n```python\r\nfrom __future__ import absolute_import\r\nimport grid2demand as gd\r\n\r\nif __name__ == \"__main__\":\r\n\r\n    # Specify input directory\r\n    input_dir = \"your-data-folder\"\r\n    # make sure you have zone_id field in node.csv\r\n\r\n    # Initialize a GRID2DEMAND object\r\n    net = gd.GRID2DEMAND(input_dir=input_dir, use_zone_id=True)\r\n\r\n    # load network: node and poi\r\n    net.load_network()\r\n\r\n    # Generate zone dictionary from node dictionary by specifying number of x blocks and y blocks\r\n    net.net2zone(num_x_blocks=10, num_y_blocks=10)\r\n    # net.taz2zone()\r\n\r\n    # Calculate demand by running gravity model\r\n    net.run_gravity_model()\r\n\r\n    # Save demand, zone, updated node, updated poi to csv\r\n    net.save_results_to_csv(overwrite_file=True)\r\n```\r\n\r\n## Call for Contributions\r\n\r\nThe grid2demand project welcomes your expertise and enthusiasm!\r\n\r\nSmall improvements or fixes are always appreciated. If you are considering larger contributions to the source code, please contact us through email: [Xiangyong Luo](mailto:luoxiangyong01@gmail.com), [Dr. Xuesong Simon Zhou](mailto:xzhou74@asu.edu)\r\n\r\nWriting code isn't the only way to contribute to grid2demand. You can also:\r\n\r\n* review pull requests\r\n* help us stay on top of new and old issues\r\n* develop tutorials, presentations, and other educational materials\r\n* develop graphic design for our brand assets and promotional materials\r\n* translate website content\r\n* help with outreach and onboard new contributors\r\n* write grant proposals and help with other fundraising efforts\r\n\r\nFor more information about the ways you can contribute to grid2demand, visit [our GitHub](https://github.com/asu-trans-ai-lab/grid2demand). If you' re unsure where to start or how your skills fit in, reach out! You can ask by opening a new issue or leaving a comment on a relevant issue that is already open on GitHub.\r\n\r\n## Citing Grid2demand\r\n\r\nIf you use grid2demand in your research please use the following BibTeX entry:\r\n\r\nXiangyong Luo, Dustin Carlino, and Xuesong Simon Zhou. (2023). [xyluo25/grid2demand](https://github.com/xyluo25/grid2demand/): Zenodo. https://doi.org/10.5281/zenodo.11212556\r\n",
    "bugtrack_url": null,
    "license": "Apache License Version 2.0, January 2004 http://www.apache.org/licenses/  TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION  1. Definitions.  \"License\" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document.  \"Licensor\" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License.  \"Legal Entity\" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, \"control\" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity.  \"You\" (or \"Your\") shall mean an individual or Legal Entity exercising permissions granted by this License.  \"Source\" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files.  \"Object\" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types.  \"Work\" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below).  \"Derivative Works\" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof.  \"Contribution\" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. 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Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form.  3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed.  4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions:  (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and  (b) You must cause any modified files to carry prominent notices stating that You changed the files; and  (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and  (d) If the Work includes a \"NOTICE\" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License.  You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License.  5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. 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