Metadata-Version: 2.1
Name: pedpy
Version: 1.0.0b1
Summary: pedpy is a python module for pedestrian movement analysis.
Author: T. Schroedter
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: aenum (>=3.1.5)
Requires-Dist: numpy (>=1.21.4)
Requires-Dist: pandas (>=1.3.4)
Requires-Dist: Shapely (==2.0a1)
Requires-Dist: scipy (==1.8.0)

![ci workflow](https://github.com/PedestrianDynamics/pedestrian-trajectory-analyzer/actions/workflows/ci.yml/badge.svg)

# pedpy

`pedpy` is a python module for pedestrian movement analysis. 
It implements different measurement methods for density, velocity and flow.

This repo is a port from the original `JPSreport` to a Python implementation, and will provide the same functionalities.

## Getting started
### Setup Python
For setting up your Python Environment a Python version >= 3.8 is recommended (our code is tested with 3.8).
To avoid conflicts with other libraries/applications the usage of virtual environments is recommended, see [Python Documentation](https://docs.python.org/3/library/venv.html) for more detail.

### Installing pedpy
To install the latest **stable** version of `pedpy` and its dependencies from PyPI:
```bash
python3 -m pip install pedpy
```

If you want to install the current version in the repository which might be unstable, you can do so via:
```bash
python3 -m pip install --pre --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ pedpy
```

### Usage

The usage of `pedpy` is demonstrated in the [demo notebook](usage.ipynb).
You can either download the notebook and [demo files](demos/bottleneck/) 
from the GitHub repository or clone the whole repository with:

```bash 
git clone https://github.com/PedestrianDynamics/pedestrian-trajectory-analyzer.git
```

For using the notebook some additional libraries need to be installed, mainly 
for plotting.
You can install the needed libraries with:

```bash
python3 -m pip install jupyter matplotlib
```

Afterwards you can start a jupyter server with:
```bash
jupyter notebook
```

After navigating to the notebook, you can see how the library can be used 
for different kinds of analysis.

Some examples how the computed values can be visualized are also shown in the notebook, e.g., density/velocity profiles, fundamental diagrams, N-T-diagrams, etc.

![voronoi](figs/voronoi_diagrams.png)

![density](figs/density_comparison.png)
