import matplotlib.pyplot as plt
import datetime


def plot_distribution(
    x,
    y,
    labels,
    title,
    figsize=(10, 5),
    logscale=False,
    notes="",
    max_labels=-1,
    save=False,
    path=None,
):
    # sort values and labels accordingly
    y, labels = zip(*sorted(zip(y, labels), reverse=True))

    if max_labels != -1:
        x = x[:max_labels]
        y = y[:max_labels]
        labels = labels[:max_labels]

    plt.figure(figsize=figsize)
    plt.bar(x, y)
    plt.xticks(x, labels, rotation=90)

    if len(notes) != 0:
        _title = f"{title} - {notes}"
        if max_labels != -1:
            _title += f" - Showing {max_labels} top labels"

    plt.title(_title)

    if logscale:
        plt.yscale("symlog")

    plt.tight_layout()

    # plt.show()
    if save:
        now = datetime.datetime.now()
        path = f"{path}/{title}_{now.strftime('%m%d_%H%M')}.png"
        plt.savefig(path)
    plt.close()


def plot_histogram(x, title, figsize=(10, 5), save=False, path=None):
    plt.figure(figsize=figsize)
    plt.hist(x)
    # plt.xticks(x, lables, rotation=90)
    plt.yscale("symlog")
    plt.title(title)
    # plt.show()
    if save:
        now = datetime.datetime.now()
        path = f"{path}/{title}_{now.strftime('%m%d_%H%M')}.png"
        plt.savefig(path)
    plt.close()