:Author: Casper van Elteren



.. _quickstart:

Quickstart
----------

Setting up the model
~~~~~~~~~~~~~~~~~~~~

Plexsim  relies on  ``networkx`` to  create a  graphical  structure  on which  to
simulate models.  Various models  are available  in ``plexsim.models``.  Below the
Ising model is used

.. code:: python

    from matplotlib import style

    style.use("seaborn-poster".split())
    import numpy as np, os, sys, networkx as nx, warnings, matplotlib.pyplot as plt

    warnings.simplefilter("ignore")
    from plexsim import models

    # init lattice graph with periodic bounds
    g = nx.grid_graph((64, 64), periodic=1)
    # create an ising model
    temperature = 2.5

    # async with sampleSize > 1, can be seen as sampleSize of glauberupdates in 1 simulation step
    settings = dict(
        graph=g,  # graph for the model
        t=temperature,  # temperature for the Ising model
        sampleSize=len(g),  # how many nodes to update per simulation step (default)
        updateType="async",  # the update buffers are not independent, use sync for dependency(default)
    )
    m = models.Ising(**settings)
    # create coords an visualize grid with periodic bounds
    # leverage the fact that grid returns tuples of coordinates
    pos = {i: np.array(eval(i)) for i in m.graph.nodes()}
    # create color map for the possible states of the model
    colors = plt.cm.viridis(np.linspace(0, 1, m.nStates))
    fig, ax = plt.subplots(constrained_layout=1, figsize=(5, 5))
    nx.draw(m.graph, pos=pos, ax=ax, node_color=colors[m.states.astype(int)], node_size=20)

    C = "#ADC3D1"
    fc = "#16161D"
    ax.margins(0.05)
    ax.set_title("Ising model with random initial condition", fontsize=21, color=C)
    # ax.axis('equal')
    ax.set_ylabel("Node", labelpad=1, color=C)
    ax.set_xlabel("Node", color=C)
    for i in "left right bottom top".split():
        ax.spines[i].set_visible(False)
    ax.axis(True)
    ax.set_xticks([])
    ax.set_yticks([])
    ax.set_facecolor(fc)
    fig.set_facecolor(fc)
    fig.show()

.. image:: ./figures/ising_example.png
    :alt: ising_example
    :align: center

Simulation
~~~~~~~~~~

.. code:: python

    n = int(1e2) # simulation steps
    m.reset() # reset model to random condition
    sim_results = m.simulate(n)
    # show averages
    spacing = np.linspace(0, n, 4, endpoint = False).astype(int)
    fig, ax = plt.subplots(2, 2, figsize = (10,10), constrained_layout = 1)
    for idx, axi in zip(spacing, ax.flat):
        tmp = sim_results[idx]
        nx.draw(m.graph, pos = pos, ax = axi, node_color = colors[tmp.astype(int)],
                node_size = 5)
        axi.axis('equal'); axi.axis(True); axi.grid(False)
        axi.margins(0)
        axi.set_title(f'T = {idx}', color = C)
    
        axi.set_facecolor(fc)
        axi.set_ylabel("Node",  labelpad = -5, color = C)
        axi.set_xlabel("Node", color = C)
    
        for i in "left right bottom top".split():
            axi.spines[i].set_visible(False)
    
    fig.subplots_adjust(wspace = .05, hspace = .4)
    fig.set_facecolor(fc)
    fig.show()


.. image:: ./figures/ising_time_example.png
    :align: center

Other parameters
~~~~~~~~~~~~~~~~

The documentation is  a work in progress.  Please check out the  source code for
different models.