import numpy as np
import matplotlib.pyplot as plt

plt.rc('text', usetex=True)

E = np.arange(-.1, 1.0, 0.0001)
mu = -.1
f = 1/(np.exp(10*(E-mu))-1)

fig = plt.figure(figsize=(4,3))

plt.plot(E, f, label='$T>0$')
plt.xlabel(r'$\varepsilon$')
plt.ylabel(r'$f(\varepsilon)$')
plt.xlim(min(E)-.1,max(E))
plt.ylim(0, 1.1)

plt.xticks((0,mu,))
fig.axes[0].set_xticklabels(('$0$', r'$\mu$',))
plt.yticks([1])
fig.axes[0].set_yticklabels(('$1$',))
plt.legend(loc='best')

def save_twice(name):
    plt.tight_layout()
    plt.savefig('../web/figs/' + name, dpi=600, format='png')
    plt.savefig(name + '.pdf')
    plt.savefig(name + '.svg')
    plt.figure(figsize=(4,3))

save_twice('bose-einstein-distribution')

D = np.sqrt(E)

fig = plt.figure(figsize=(4,3))

plt.plot(E, f*D, label='$T>0$')
plt.xlabel(r'$\varepsilon$')
plt.ylabel(r'$D(\varepsilon)f(\varepsilon)$')
plt.xlim(min(E)-.1,max(E))
plt.ylim(0,.08)

plt.xticks((mu,0,))
fig.axes[0].set_xticklabels((r'$\mu$',r'$0$',))
plt.yticks([])
fig.axes[0].set_yticklabels([])
plt.legend(loc='best')

save_twice('bose-gas-product')