def test_boltzman(self):
from scipy.stats import boltzmann
import matplotlib.pyplot as plt
fig, ax = plt.subplots(1, 1)
lambda_, N = 1.4, 19
mean, var, skew, kurt = boltzmann.stats(lambda_, N, moments='mvsk')
x = np.arange(boltzmann.ppf(0.01, lambda_, N),
boltzmann.ppf(0.99, lambda_, N))
ax.plot(x,
boltzmann.pmf(x, lambda_, N),
'bo',
ms=8,
label='boltzmann pmf')
ax.vlines(x,
0,
boltzmann.pmf(x, lambda_, N),
colors='b',
lw=5,
alpha=0.5)
rv = boltzmann(lambda_, N)
ax.vlines(x,
0,
rv.pmf(x),
colors='k',
linestyles='-',
lw=1,
label='frozen pmf')
ax.legend(loc='best', frameon=False)
self.assertEqual("AxesSubplot(0.125,0.11;0.775x0.77)", str(ax))
def test_boltzmann_upper_bound():
k = np.arange(-3, 5)
N = 1
p = boltzmann.pmf(k, 0.123, N)
expected = k == 0
assert_equal(p, expected)
lam = np.log(2)
N = 3
p = boltzmann.pmf(k, lam, N)
expected = [0, 0, 0, 4 / 7, 2 / 7, 1 / 7, 0, 0]
assert_allclose(p, expected, rtol=1e-13)
c = boltzmann.cdf(k, lam, N)
expected = [0, 0, 0, 4 / 7, 6 / 7, 1, 1, 1]
assert_allclose(c, expected, rtol=1e-13)
def test_boltzmann_upper_bound():
k = np.arange(-3, 5)
N = 1
p = boltzmann.pmf(k, 0.123, N)
expected = k == 0
assert_equal(p, expected)
lam = np.log(2)
N = 3
p = boltzmann.pmf(k, lam, N)
expected = [0, 0, 0, 4/7, 2/7, 1/7, 0, 0]
assert_allclose(p, expected, rtol=1e-13)
c = boltzmann.cdf(k, lam, N)
expected = [0, 0, 0, 4/7, 6/7, 1, 1, 1]
assert_allclose(c, expected, rtol=1e-13)
def temperature(time):
delta = temp - time
print("Temperatura: ", time, delta)
lambda_, n = 1.4, time
return boltzmann.pmf(delta, lambda_, n)
