---
license: mit
tags:
- numpy
- Non-interacting random-walkers
- Dean-Kawasaki
configs:
- config_name: default
  data_files:
  - split: test
    path:
    - "preview.csv"
---

# Dataset Card

## Dataset Description

This dataset consists of number density for 5120 realizations of a 100 cell one-dimensional system subjected to an external potential.
The system is modeled with 4 different methods, namely, random-walker particles (`Random-Walkers.npy`), Dean-Kawasaki model (`Dean-Kawasaki.npy`),
Markovian ML model (`Markovian-ML.npy`), and non-Markovian ML model (`Non-Markovian-ML.npy`). Simulation time step is 3.0e-6 and cell size is 1.0e-2.
The data is saved at 50 time step intervals.

Each NumPy binary file (`.npy`) contains multidimensional arrays of shape `(200, 100, 5120)`.
The ordering of data is time, spatial positions, and independent realizations.

The Dataset Viewer is configured against `preview.csv`, which provides one metadata row per `.npy` file. The `.npy` files remain the canonical dataset artifacts.

## Array Structure

| Axis | Dimension | Description |
|------|-----------|-------------|
| 0 | 200 | Time steps |
| 1 | 100 | System (spatial) direction |
| 2 | 5120 | Realizations (ensemble members) |

## Usage

```python
import numpy as np

data = np.load("file_name.npy")
print(data.shape)  # (200, 100, 5120)

n_time, n_space, n_realizations = data.shape
dt_saved = 1.5e-4
dx = 0.01
```