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MAINT: update data folder description
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Gui-FernandesBR committed Jan 5, 2023
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- [Motivation](#motivation)
- [Features](#features)
- [Installation](#installation)
- [Getting started with examples](#getting-started-with-examples)
- [Read the documentation](#read-the-documentation)
- [Directory Structure](#directory-structure)
- [Data folder description](#data-folder-description)
- [Contributing](#contributing)
- [License](#license)
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- Node degree
- Polar plots of street orientation


## Installation

First you need to certify that you have [Python 3.9](https://www.python.org/downloads/release/python-380/) installed.

Then you can install the package using pip:

```bash
```bash
pip install git+https://github.com/Gui-FernandesBR/Last-Mile-Routing-Analyzer/lmr_analyzer.git
```

```

The package will automatically install the dependencies listed at [requirements.txt]() file.

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The lmr_analyzer package is organized as follows:

__init__.py - Main module
amz_serializer.py - Amazon S3 data serializer
analysis.py - Analysis module, to analyze a set of routes
distance_matrix.py - Distance Matrix module
geometry.py - Handle with spatial information from shapefiles
package.py - Store package information
route.py - Store route information
stop.py - Store stop information
utils.py - Utilities module to be used on other modules
vehicle.py - Store vehicle information
`__init__.py` - Main module
amz_serializer.py - Amazon S3 data serializer
analysis.py - Analysis module, to analyze a set of routes
distance_matrix.py - Distance Matrix module
geometry.py - Handle with spatial information from shapefiles
package.py - Store package information
route.py - Store route information
stop.py - Store stop information
utils.py - Utilities module to be used on other modules
vehicle.py - Store vehicle information

The architecture of the package is represented by the following diagram:

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Due to the large amount of information, the data folder can be a bit confusing, so here is a brief description of what each folder contains:

* data/driving_distances:
* A set of csv files containing the driving distances between some pairs of points in the dataset. The files are named as follows: `driving_distances_{dataset_name}.csv`. The dataset name is the same as the name of the folder containing the dataset.
* data/shapefiles:
* `los_angeles_majors`: Shapefile containing the major neighborhoods of Los Angeles.
* `los_angeles_minors`: Shapefile containing the minor neighborhoods of Los Angeles.
* `guarulhos_osm` : geospatial data describing boundaries of all neighborhoods of the Guarulhos city. source: _OpenStreetMap_
* `urban_regions_Sao_Paulo`: geospatial data describing land use over state of Sao Paulo. source: unknown
```bash
data/
├── driving_distances/ - Driving distances to be used with Amazon dataset
│ ├── austin.csv
│ ├── boston.csv
│ ├── ...
│ └── seattle.csv
├── results/ - Results from the examples
│ ├── dataframes/ - all .csv or .txt files
│ ├── graph_shapefile/ - gespatial data files
│ ├── graphs/ - Report of the Graphs generated with the examples
│ ├── pickles/ - Objects saved as pickle files
│ └── polar_plots/ - Polar plots generated with the examples
└── shapefiles/ - geospatial data files
├── austin/ - Neighborhoods of Austin county
├── los_angeles_minors/ - Neighborhoods of Los Angeles county
├── guarulhos_osm/ - Neighborhoods of Guarulhos city
├── ...
└── urban_regions_Sao_Paulo/ - Urban regions of Sao Paulo state

```

## Contributing

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