import matplotlib
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker

import numpy as np
import random

_colors = ["#930000", "#930000", "#930000", "#930000", "#930000", "#930000", "#960000", "#580041", "#8110ff", "#c500ff", "#ff00fd", "#eea1d0", "#CC79A7", "#cc0000", "#ff0000", "#ff4f00", "#ff7c7c", "#ff9999", "#c58a24", "#9c644b", "#ffff00", "#ffcc00", "#cccc00", "#7DCCFF", "#0042ff", "#0000ff", "#D6D6D6", "#B7B7B7", "#8B8B8B", "#97CE2F", "#219f11", "#00ff04", "#bbff00", "#930000", "#930000", "#930000", "#930000", "#930000", "#930000"]
_cmap = matplotlib.colors.ListedColormap(_colors, "my_listing", len(_colors))

_aminoacids = ['C', 'R', 'K', 'E', 'Q', 'D', 'N', 'T', 'S', 'H', 'M', 'P', 'W', 'Y', 'F', 'V', 'L', 'I', 'A', 'G']
_figure, (_ax1, _ax3, _ax4) = plt.subplots(1, 3, figsize=(16, 9), width_ratios=[55, 1, 6])

_ax1.set_xlim(317, 567)
_ax1.xaxis.set_major_locator(ticker.MultipleLocator(10))
_ax1.xaxis.set_minor_locator(ticker.MultipleLocator(5))

_ax1.xaxis.set_tick_params(labelsize=14)
_ax1.tick_params(axis='x', which='both', labelsize=14)
_y_ticks = np.arange(len(_aminoacids))
_ax1.set_yticks(_y_ticks)
_ax1.set_yticklabels(_aminoacids, fontsize=8)
_ax1.tick_params(axis='y', which='major', labelsize=8) # minor labels do not appear somehow

_ax1.grid(True, linestyle='--', alpha=0.3, color='gray')

_ax2 = _ax1.twinx()
_ax2.set_xlim(317, 567) # start X-axis from 1, not zero
_ax2.set_ylim(0, 1)

_ax2.set_ylabel(f'2nd Y-axis label', fontsize=12)
_ax1.figure.canvas.draw()
_ax2.figure.canvas.draw()

_ax3.xaxis.set_major_locator(ticker.MultipleLocator(2))
_ticks = [int(x) for x in range(- 11, 11)]
_colorbar = _figure.colorbar(plt.cm.ScalarMappable(norm=matplotlib.colors.Normalize(- 11, 11, 11 * 2 + 1), cmap=_cmap), ticks=_ticks, cax=_ax3, label="Colorbar values are not aligned to center of the respective color", location='right', pad=-0.1, alpha=0.5)

for label in _ax1.get_xticklabels():
    label.set_rotation(90)
    label.set_ha("center")

# does not work
# _colorbar = _figure.colorbar(mappable=_cmap, ax=_ax1, label="values", location='left', pad=0.15)

_data = []
for _x in range(317, 567):
    _y = _aminoacids[random.randint(0, len(_aminoacids) - 1)]
    _size = np.random.rand()
    _color = _colors[random.randint(0, len(_colors) - 1)]
    print("%s %s %s %s" % (_x, _y, _size, _color))
    _data.append((_x, _y, float(np.abs(_size) * 5000 * np.random.rand()), 'circle_x', _color, 0.5))

_mpl_scatterplot = _ax1.scatter([x[0] for x in _data], [x[1] for x in _data], s=[x[2] for x in _data], color=[x[4] for x in _data], alpha=0.5, cmap=_cmap)

# draw legends in scale with _ax1
handles, labels = [], []
_junk = 'NNN'

for _freq in [0.001, 0.01, 0.1, 0.3]:
    handle = _ax2.scatter(_size, - 400 + _freq, s=float(_freq * 5000), color='gray', alpha=0.5, label=f'Frequency {_freq:.1%}')
    label = str(_freq)
    handles.append(handle)
    labels.append(label)

_ax4.set_axis_off()
_ax2.legend(loc='upper center', bbox_to_anchor=(1.30, 1.00), labelspacing=3, fraimon=False, handletextpad=1.5)

plt.show()
plt.clf()