import matplotlib.pyplot as plt
import numpy as np
import matplotlib.ticker as ticker

SMALL_SIZE = 10
MEDIUM_SIZE = 12
BIGGER_SIZE = 16

plt.rc('font', size=SMALL_SIZE)          # controls default text sizes
plt.rc('axes', titlesize=SMALL_SIZE)     # fontsize of the axes title
plt.rc('axes', labelsize=MEDIUM_SIZE)    # fontsize of the x and y labels
plt.rc('xtick', labelsize=SMALL_SIZE)    # fontsize of the tick labels
plt.rc('ytick', labelsize=SMALL_SIZE)    # fontsize of the tick labels
plt.rc('legend', fontsize=SMALL_SIZE)    # legend fontsize
plt.rc('figure', titlesize=BIGGER_SIZE)  # fontsize of the figure title
plt.rcParams['axes.linewidth'] = 1.5

def set_axis_style(ax, labels):
    ax.set_xticks(np.arange(1, len(labels) + 1), labels=labels, fontweight='bold', fontstretch='condensed', fontname='Bahnschrift')
    ax.set_xlabel('PES', fontweight='bold', fontstretch='condensed',fontname='Bahnschrift')
    ax.yaxis.set_major_locator(ticker.MultipleLocator(3))
    ax.set_ylim([-18.0,9.0])
    ax.yaxis.set_minor_locator(ticker.MultipleLocator(1))
    ax.grid(visible=True, which='major', axis='y')

data = [
	[-16.60102571,-6.699822806,-14.62564481,7.456503834,4.016659607,7.210896854,1.804969856,0.467860939],
    [-17.32762431,-6.081446527,-14.87504614,8.068733361,6.162393395,5.727964021,2.63439223,1.278821509],
	[-10.35923985,-3.819050878,-9.664667008,5.082031256,3.879507143,5.145900878,0.234401452,-0.866473206],
    [-11.0059302,-3.560643243,-9.808961668,5.689461703,5.9734276,3.684341201,1.02932442,-0.060885493],
	[3.427329458,3.58409437,0.391482303,0.330079435,2.898602566,1.53808872,1.063593669,3.281844567,-0.075796436,0.25954612],
    [3.691012844,2.388512547,0.626317599,1.167470753,3.415479718,0.73615229,2.157193802,0.457135001,0.093632333,0.395061974],
	[1.834710076,2.068101436,0.438865565,0.98388445,1.693632724,0.239971571,1.67850917,-0.368657719,-0.221180384,0.150743242],
	[-0.350021341,-0.151871497,0.065295165,-0.107972774,-0.253106388,2.553227692,1.090027229,4.109293976,0.051641275,0.045709255],
	[-2.909762523,-1.321763299,0.285956032,0.627310784,-2.347696693,1.308652494,2.247634606,0.387280379,0.081192904,0.074938114],
	[1.426280957,-0.253391384,1.610038134,1.178748087,-1.883853498,3.30948195,-0.369635367,-0.158668355],
	[-0.673590433,-0.865603666,-0.182107106,0.356435843,-0.307266771,0.010776048,-0.052132211,0.196368734],
	[1.216522788,-0.389357266,1.176203029,1.21521229,-1.953162885,3.036492967,-0.741968769,-0.546354717],
	[-1.119479317,-2.353230497,-1.1,-1.1,-0.487929244,-0.498971093,-1.81732571,-0.846761305,-1.018986275,-1.023515653],
	[2.263427409,1.705632712,0.407670257,0.862491961,2.09552031,-0.018730139,1.602867776,-0.34663782,-0.074009823,0.160711069]
]

fig, ax1 = plt.subplots(nrows=1, ncols=1, figsize=(15, 10))
ax1.set_ylabel('Deviation of optimized stationary point energy from benchmark (kcal/mol)', fontweight='bold', fontstretch='condensed', fontname='Bahnschrift')
parts1 = ax1.violinplot(data, bw_method=0.3, points=300, widths=0.9,showmeans=False, showmedians=False, showextrema=False,positions=np.arange(1, len(data) + 1))
ax1.boxplot(data,positions=np.arange(1, len(data) + 1))


labels = ['HF\n/DZ','HF\n/TZ','HF-D3(BJ)\n/DZ','HF-D3(BJ)\n/TZ','MP2\n/DZ','MP2\n/TZ','MP2-F12\n/DZ','CCSD\n/DZ','CCSD-F12b\n/DZ','CCSD(T)\n/DZ','CCSD(T)\n-F12b/DZ','OQVCCD(T)\n/DZ','OSC','MP2-F12\n/TZ']
set_axis_style(ax1, labels)
fig.savefig('bold_Cairo.png', transparent=False, dpi=300, bbox_inches="tight", backend='Cairo')
fig.savefig('bold_AGG.png', transparent=False, dpi=300, bbox_inches="tight", backend='AGG')