Update README.md

README.md

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-license: odbl
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+# OpenPathNet Dataset
+
+This README describes the **OpenPathNet** dataset (the release referred to as **Link 1** in the [OpenPathNet project](https://github.com/liu-lz/OpenPathNet) documentation). The dataset is generated by the OpenPathNet toolchain from real-world **Miami** and **Boston** urban areas based on OpenStreetMap (OSM), and then simulated with NVIDIA Sionna ray tracing for RF multipath propagation / channel modeling research and AI tasks.
+
+The dataset is also **carefully cleaned** to ensure **good building coverage** in every scene.
+
+- Project code / generator repository: <https://github.com/liu-lz/OpenPathNet>
+- City subsets: **Miami (806 scenes)** and **Boston (971 scenes)** (same directory layout across cities); each city subset is approximately **35 GB** in size
+
+## Directory Structure
+
+```
+.
+├── Miami/
+│   ├── scenes/
+│   │   └── scene_<lat>_<lon>/
+│   │       ├── scene.xml
+│   │       └── mesh/
+│   │           ├── building_*.ply
+│   │           └── ground.ply
+│   ├── raytracing_results/
+│   │   └── scene_<lat>_<lon>/
+│   │       ├── raytracing_results.csv
+│   │       ├── raytracing_results.pkl
+│   │       ├── deepmimo_format.npy
+│   │       ├── heatmaps/
+│   │       │   ├── azimuth_heatmap.png
+│   │       │   ├── channel_gain_heatmap.png
+│   │       │   ├── delay_heatmap.png  # Here “delay” refers to ToA (Time of Arrival); the latest OpenPathNet fixes this filename
+│   │       │   ├── elevation_heatmap.png
+│   │       │   └── ...
+│   │       ├── channel_gain_distribution.png
+│   │       ├── delay_distribution.png
+│   │       ├── path_type_distribution.png
+│   │       └── outdoor_receivers.png
+│   ├── generated_scenes.txt
+│   └── raytracing.log
+├── Boston/
+│   └── ... (same structure as Miami)
+└── README.md
+```
+
+### Naming
+
+- Each scene directory is named `scene_<lat>_<lon>`, where `<lat>` / `<lon>` are decimal latitude/longitude.
+- Scene folders under `scenes/` and `raytracing_results/` correspond one-to-one.
+
+## Files
+
+### generated_scenes.txt
+
+A generation manifest and metadata (tabular text).
+
+- The header records the total count, center coordinate, sampling radius, scene size, generation mode, etc.
+- Each (tab-separated) row includes:
+  - Scene file path (e.g., `data\scenes\scene_...\scene.xml`)
+  - Original / actual latitude & longitude
+  - Generation type (e.g., `OSM`)
+  - Attempts
+  - Offset distance (km)
+
+### raytracing.log
+
+A summary log for batched ray tracing (typically one line per scene), including runtime, number of receivers, and number of paths.
+
+### scenes/
+
+Geometry assets for each scene.
+
+- `scene.xml`: scene description file (digital-twin / renderer-compatible format).
+- `mesh/`: geometry meshes (e.g., buildings and ground) in `.ply`.
+
+### raytracing_results/
+
+Ray-tracing outputs and visualizations for each scene.
+
+For each receiver point in each scene, this dataset keeps and records the **top 5 paths with the highest channel gain**. The files below contain the full multipath attributes for those retained paths, including receiver location, carrier frequency, path type, channel gain, **ToA (Time of Arrival)**, and departure/arrival angles.
+
+- `raytracing_results.csv`: tabular results (easy to analyze/import).
+- `raytracing_results.pkl`: Python-serialized results (fast loading).
+- `deepmimo_format.npy`: DeepMIMO-style structured output for downstream ML pipelines.
+- `heatmaps/` and `*.png`: visualizations (e.g., channel gain / delay(ToA) / azimuth / elevation).
+
+#### Data schema: raytracing_results.csv / raytracing_results.pkl
+
+- Structure: tabular data; typically **one row = (receiver `rx_id`, one path)**, so each `rx_id` usually appears 5 times.
+- `raytracing_results.pkl` is a `pandas.DataFrame` with the same columns as `raytracing_results.csv`.
+
+Columns:
+
+- `rx_id`: receiver index (integer).
+- `type`: path type (e.g., `LoS` / `Reflected` / `Scattered`).
+- `channel_gain`: channel gain-related numeric value (scientific notation).
+- `tau`: **ToA (Time of Arrival)** in seconds.
+- `freq`: carrier frequency in Hz.
+- `rx_coord`: receiver coordinates, formatted as a string like `"[x, y, z]"`.
+- `phi_r`, `theta_r`: AoA azimuth / elevation angles.
+- `phi_t`, `theta_t`: AoD azimuth / elevation angles.
+
+#### Data schema: deepmimo_format.npy
+
+- File content: a scalar `numpy.ndarray` with `dtype=object`; `arr.item()` yields a `dict`.
+- Top-level keys:
+  - `user`: a list of length $N_{rx}$; each element corresponds to one receiver.
+  - `location`: a list used to describe scene / coordinate system information (may vary slightly across versions/configs).
+
+Each `user[i]` is a `dict` containing:
+
+- `location`: `numpy.ndarray` of shape `(3,)`, receiver coordinates `[x, y, z]`.
+- `paths`: a `dict` containing (arrays are length 5, i.e., Top-5 paths):
+  - `channel_gain`: `float32`, shape `(5,)`
+  - `ToA`: `float32`, shape `(5,)`
+  - `DoA_theta`: `float64`, shape `(5,)`
+  - `DoA_phi`: `float64`, shape `(5,)`
+  - `num_paths`: `int` (5 in this dataset)
+
+## Reproducibility / Regeneration
+
+This dataset is generated by the OpenPathNet toolchain. For generation scripts, ray-tracing entry points, and system requirements, please refer to:
+
+- <https://github.com/liu-lz/OpenPathNet>
+
+## Citation
+
+If you use OpenPathNet in your research, please refer to the citation information in the [OpenPathNet repository documentation](https://github.com/liu-lz/OpenPathNet).
+
+## License & Notes
+
+- This directory contains a dataset slice/subset. For licensing, the generator code license, and third-party data source statements (OSM, etc.), please follow the [OpenPathNet repository documentation](https://github.com/liu-lz/OpenPathNet).