prettyplots.py

from matplotlib import pyplot as plt


def bar_plot(ax, data, colors=None, total_width=0.8, single_width=1, legend=True):
    """Draws a bar plot with multiple bars per data point.

    Parameters
    ----------
    ax : matplotlib.pyplot.axis
        The axis we want to draw our plot on.

    data: dictionary
        A dictionary containing the data we want to plot. Keys are the names of the
        data, the items is a list of the values.

        Example:
        data = {
            "x":[1,2,3],
            "y":[1,2,3],
            "z":[1,2,3],
        }

    colors : array-like, optional
        A list of colors which are used for the bars. If None, the colors
        will be the standard matplotlib color cyle. (default: None)

    total_width : float, optional, default: 0.8
        The width of a bar group. 0.8 means that 80% of the x-axis is covered
        by bars and 20% will be spaces between the bars.

    single_width: float, optional, default: 1
        The relative width of a single bar within a group. 1 means the bars
        will touch eachother within a group, values less than 1 will make
        these bars thinner.

    legend: bool, optional, default: True
        If this is set to true, a legend will be added to the axis.
    """
    colors = ["#65cbe9","#68b6ef","#6c8dfa","#37474f","#6e78ff"]
    # Check if colors where provided, otherwhise use the default color cycle
    if colors is None:
        colors = plt.rcParams['axes.prop_cycle'].by_key()['color']

    # Number of bars per group
    n_bars = len(data)

    # The width of a single bar
    bar_width = total_width / n_bars

    # List containing handles for the drawn bars, used for the legend
    bars = []

    # Iterate over all data
    for i, (name, values) in enumerate(data.items()):
        # The offset in x direction of that bar
        x_offset = (i - n_bars / 2) * bar_width + bar_width / 2

        # Draw a bar for every value of that type
        for x, y in enumerate(values):
            bar = ax.bar(x + x_offset, y, width=bar_width * single_width, color=colors[i % len(colors)])

        # Add a handle to the last drawn bar, which we'll need for the legend
        bars.append(bar[0])

    # Draw legend if we need
    if legend:
        ax.legend(bars, data.keys(), loc="lower right")


if __name__ == "__main__":
    # Usage example:
    data = {
        # order is GZIP, GCC, JPEG
        "Smith": [67.7, 58.8, 55.5],
        "Bimodal": [73.8, 80.4, 86.7],
        "GShare": [72.4, 75.1, 86.2],
        "BPTP": [75.6, 80.7, 87.0], # Branch Prediction Technique Predictor (OURS)
        "Oracle": [77.9, 83.7, 90.0],
    }

    fig, ax = plt.subplots()
    bar_plot(ax, data, total_width=.8, single_width=.9)
    plt.xticks(range(3), ["GZIP", "GCC", "JPEG"])
    plt.ylabel("Prediction Accuracy (%)")
    plt.show()