Tutorials and scripts for scientific visualization

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Web Molecular Dynamics (three.js)

Matplotlib Code snippets


# 1: blue | 2: red | 3: green | 4: yellow
colors = {1: '#4e7fad', 2: '#CF5955', 3: '#66AD9B', 4: '#EAC658'}
shades = {1: '#3B4C5C', 2: '#672C2A', 3: '#33564D', 4: '#75632C'}


A subplot example where a list of data is and a plot function is used to generate a grid of plots. The subplot function is used to arrange the grid. As input it takes the list of data to be plotted, the function that will be used to plot each data, additional arguments for that function and keyword arguments for the subplot function itself.

This structure allows you to use the same subplot function to plot any kind of data. You can just change the functionthat you use to plot your data without changing the subplot function itself.

import matplotlib.pyplot as plt
import numpy as np

def subplot(plot_fun, plot_args, nrow=1, width=4, height=3, dpi=200, save=None):
    n_plots = len(plot_args)
    ncol = np.ceil(n_plots / nrow)
    figsize = (ncol * width, nrow * height)
    fig = plt.figure(figsize=figsize, dpi=dpi)
    fig.subplots_adjust(hspace=.5, wspace=.25)
    for idx, args in enumerate(plot_args, start=1):
        args['ax'] = fig.add_subplot(nrow, ncol, idx)
    if save is not None:
        plt.savefig(save, dpi=dpi, transparent=True, bbox_inches='tight')

Here the plot_fun is your function that will be used to plot your data, plot_args is a list of dictionaries that will be fed to your plot function to be used as arguments. Here is an example for a scatter plot:

def scatter_plot(x, y, ax, markersize=100):
    ax.scatter(x, y, markersize=markersize)

Here our scatter_plot function takes x and y args as input data, the axis object from the subplot function and a markersize kwarg to set marker size. Here is an example for using these functions together:

plot_data = [dict(x=np.arange(10), y=np.random.random_sample(10), markersize=75),
             dict(x=np.arange(20), y=np.random.random_sample(20), markersize=150)]

subplot(scatter_plot, plot_data)

Subplot function arguments: