Tutorial

Installation

In order to install the Countoscope Python tool, clone the repository using:

git clone https://github.com/Countoscope/countoscope.git

Install all the required Python packages using:

pip install -r requirements.txt

Then, type:

pip install .

Use

In a Python script or a Jupyter Notebook, define the path to the data trajectory file. For instance, using the 3D-closed dataset provided in the datasets repository:

path_to_data = "/mpath/datasets/datasets/3D-closed/trajectory.xyz"

Import the Countoscope as well as NumPy by typing:

from countoscope import Countoscope
import numpy as np

The trajectory file trajectory.xyz corresponds to a system of 190 particles in a \((30 Å)^3\) box. Let us define the system size as a NumPy array:

system_size = np.array([30, 30, 30])

Finally, let us choose a grid size for the Countoscope measurement:

box_size=np.array([10, 10, 10])

Then, launch the Countoscope calculation using trajectory_file, system_size, and box_size as input parameters:

results = Countoscope(trajectory_file = path_to_data,
                    system_size=system_size,
                    box_size=box_size)
results.run()

After the calculation is done, all the computed data can be obtained from the results object. For instance, for \(\langle N \rangle\), type:

print(np.round(results.mean_of_N,2))

which will return:

0.84

To plot \(\langle \Delta N^2 \rangle\), let us import Pyplot first:

import matplotlib.pyplot as plt
plt.loglog(results.delta_n2)