def test_sample_bounded_coal(self):
n = 1000
k = 5
T = 500
d = [coal.sample_bounded_coal(k, n, T) for i in xrange(2000)]
p = plotdistrib(d, 40)
p.plotfunc(lambda t: coal.prob_bounded_coal(t, k, n, T), 0, T, T/200)
eq_sample_pdf(d, lambda t: coal.prob_bounded_coal(t, k, n, T), 40)
def test_plot_prob_bounded_coal(self):
n = 1000
k = 4
t = 800
alltimes = []
# sample times
for i in xrange(5000):
while True:
times = [0]
for j in xrange(k, 1, -1):
times.append(times[-1] + coal.sample_coal(j, n))
if times[-1] >= t:
break
if times[-1] < t:
break
alltimes.append(times)
p = Gnuplot()
for i in range(1, 2):
x, y = distrib([q[i] - q[i-1] for q in alltimes], width=20)
p.plot(x, y, style="lines", xmax=500)
x = list(frange(0, 500, 10))
#for i in range(1, 2): #k):
y2 = [coal.prob_bounded_coal(j, k, n, t) for j in x]
p.plot(x, y2, style="lines", xmax=500)
fequals(y, y2, rel=.05, eabs=.01)
def test_plot_bounded_coal(self):
n = 1000
k = 6
T = 500
# plots should differ
p = plotfunc(lambda t: coal.prob_bounded_coal(t, k, n, T),
0, 1000, 10)
p.plotfunc(lambda t: coal.prob_coal(t, k, n),
0, 1000, 10)
def test_cdf_coal_bounded(self):
n = 1000
k = 4
t = 500
step = .1
x = list(frange(0, 500, step))
y = [coal.prob_bounded_coal(i, k, n, t) * step for i in x]
y2 = cumsum(y)
y3 = [coal.cdf_bounded_coal(i, k, n, t) for i in x]
p = plot(x, y2, style="lines")
p.plot(x, y3, style="lines")
p.plot([0, 500], [1, 1], style="lines")
fequals(y2, y3, eabs=.01)
def test_prob_coal_cond_counts_simple(self):
# when we condition on b=1, it is the same as the bounded coal
# PDF.
# prob_coal_cond_counts is actually a more general version of
# prob_bounded_coal
outdir = 'test/tmp/test_coal/Coal_test_prob_coal_counys_simple/'
make_clean_dir(outdir)
a = 5
b = 1
t = 2000
n = 1000
p = Gnuplot()
p.enableOutput(False)
for x in frange(0, 2000, 10):
y = coal.prob_coal_cond_counts_simple(x, a, b, t, n)
y2 = coal.prob_bounded_coal(x, a, n, t)
self.assertAlmostEqual(y, y2)