import numpy as np
import matplotlib.pyplot as plt
import atompy as ap
from math import nextafter

_, axs = plt.subplots(2, 3)

data = 2 * np.random.default_rng(42).integers(-10, 11, 100)

# histogram with fixed number of bins
nbins = 10
hist1 = ap.Hist1d(*np.histogram(data, bins=nbins))

axs[0, 0].set_title("fixed number of bins")
axs[0, 0].bar(*hist1.for_plot, width=hist1.binwidths)
axs[1, 0].step(*hist1.for_step)


# histogram with fixed width of bins
binwidth = 1.0
start = data.min() - binwidth / 2.0
stop = data.max() + binwidth
bin_edges = np.arange(start, stop, binwidth)
hist2 = ap.Hist1d(*np.histogram(data, bins=bin_edges))

axs[0, 1].set_title(f"fixed bin width")
axs[0, 1].bar(*hist2.for_plot, width=hist2.binwidths)
axs[1, 1].step(*hist2.for_step)

# histogram counting the occurance of values
axs[0, 2].set_title(f"numpy.unique")
axs[0, 2].bar(*np.unique(data, return_counts=True), width=1)
axs[1, 2].step(*np.unique(data, return_counts=True), where="mid")


for ax in axs.flat:
    ap.set_axes_size(2.5, 2.5, ax)
    ax.set_xlim(-21, 21)
    ax.set_ylim(bottom=0)

for ax in axs[0]:
    ax.text(0.05, 0.95, "plt.bar()", transform=ax.transAxes, va="top")

for ax in axs[1]:
    ax.text(0.05, 0.95, "plt.step()", transform=ax.transAxes, va="top")

ap.add_abc(anchor="top right", ha="right", xoffset_pts=-2, rowsfirst=False)
ap.make_me_nice(fix_figwidth=False)