def testDivsLength(self):
for m in range(2,self.m_max):
pm = mfng.simpleProbMeasure(m=m)
for K in range(1,self.K_max):
ipm = pm.iterate(K=K, maxdivs=4100)
length = len(ipm.divs)
self.assertEqual(length, m**K)
def testProbsShape(self):
for m in range(2,self.m_max):
pm = mfng.simpleProbMeasure(m=m)
for K in range(1,self.K_max):
ipm = pm.iterate(K=K, maxdivs=4100)
shape = ipm.probs.shape
self.assertEqual(shape, (m**K,m**K))
def testDivsLength(self):
for m in range(2, self.m_max):
pm = mfng.simpleProbMeasure(m=m)
for K in range(1, self.K_max):
ipm = pm.iterate(K=K, maxdivs=4100)
length = len(ipm.divs)
self.assertEqual(length, m**K)
def testProbsShape(self):
for m in range(2, self.m_max):
pm = mfng.simpleProbMeasure(m=m)
for K in range(1, self.K_max):
ipm = pm.iterate(K=K, maxdivs=4100)
shape = ipm.probs.shape
self.assertEqual(shape, (m**K, m**K))
def testProbsValues(self):
for m in range(2,self.m_max):
prob = 1./m**2
for i in range(m):
for j in range(m):
pm = mfng.simpleProbMeasure(m=m)
p = pm.probs[i,j]
self.assertAlmostEqual(p, prob)
def testMaxDivs(self):
for m in range(2, self.m_max):
pm = mfng.simpleProbMeasure(m=m)
for K in range(1, self.K_max):
self.assertRaises(ValueError,
pm.iterate,
K=K,
maxdivs=m**K - 1)
def testProbsValues(self):
for m in range(2, self.m_max):
prob = 1. / m**2
for i in range(m):
for j in range(m):
pm = mfng.simpleProbMeasure(m=m)
p = pm.probs[i, j]
self.assertAlmostEqual(p, prob)
def testDivsValues(self):
for m in range(2,self.m_max):
pm = mfng.simpleProbMeasure(m=m)
divs = pm.divs
value = 0.
delta = 1./m
for i in range(m):
value += delta
self.assertAlmostEqual(value, divs[i])
def testDivsValues(self):
for m in range(2, self.m_max):
pm = mfng.simpleProbMeasure(m=m)
divs = pm.divs
value = 0.
delta = 1. / m
for i in range(m):
value += delta
self.assertAlmostEqual(value, divs[i])
def testIteratedValue(self):
for value in self.known_values:
m = value["m"]
K = value["K"]
divs = value["divs"]
pm = mfng.simpleProbMeasure(m=m)
ipm = pm.iterate(K=K)
for i, j in zip(ipm.divs, divs):
self.assertAlmostEqual(i, j)
def testIteratedValue(self):
for value in self.known_values:
m = value["m"]
K = value["K"]
divs = value["divs"]
pm = mfng.simpleProbMeasure(m=m)
ipm = pm.iterate(K=K)
for i, j in zip(ipm.divs, divs):
self.assertAlmostEqual(i, j)
def probmeasure(self, iterated=True, initial=False, **kwargs):
"""Returns the link probability or the generator measure.
It can be plotted then.
Parameters:
`iterated`: boolean
If True it returns with the iterated measure.
(with the link probability measure)
`initial`: boolean
If True it returns with the initial measure.
`label`: string or None
If string, it will use this as label.
Example. In this example the link probability measure and the generator
measure will be plotted. ::
>>> pm=r.probmeasure()
>>> pm.plot(ticklabels=False)
<matplotlib.axes.AxesSubplot object at 0x8f05d0c>
>>> pm=r.probmeasure(iterated=False)
>>> pm.plot()
<matplotlib.axes.AxesSubplot object at 0x9632eec>
"""
label = kwargs.get("label")
if not label and (not isinstance(self.labels, list)
or not self.labels):
raise NoLabelsError
if not label:
label = self.labels[-1]
run = self.runs[label]
if initial:
pm = mfng.simpleProbMeasure(m=run["m"])
else:
divs = run["divs"]
probs = run["probs"]
pm = ProbMeasure(divs, probs)
if iterated:
K = run.get("K") or run.get(
"k") # Older files have k instead of K.
pm = pm.iterate(K)
return pm
def probmeasure(self, iterated=True, initial=False, **kwargs):
"""Returns the link probability or the generator measure.
It can be plotted then.
Parameters:
`iterated`: boolean
If True it returns with the iterated measure.
(with the link probability measure)
`initial`: boolean
If True it returns with the initial measure.
`label`: string or None
If string, it will use this as label.
Example. In this example the link probability measure and the generator
measure will be plotted. ::
>>> pm=r.probmeasure()
>>> pm.plot(ticklabels=False)
<matplotlib.axes.AxesSubplot object at 0x8f05d0c>
>>> pm=r.probmeasure(iterated=False)
>>> pm.plot()
<matplotlib.axes.AxesSubplot object at 0x9632eec>
"""
label = kwargs.get("label")
if not label and (not isinstance(self.labels, list) or not self.labels):
raise NoLabelsError
if not label:
label=self.labels[-1]
run = self.runs[label]
if initial:
pm = mfng.simpleProbMeasure(m=run["m"])
else:
divs = run["divs"]
probs = run["probs"]
pm = ProbMeasure(divs, probs)
if iterated:
K = run.get("K") or run.get("k") # Older files have k instead of K.
pm = pm.iterate(K)
return pm
def testAvgDegree(self):
pm = mfng.simpleProbMeasure(m=3)
self.assertAlmostEqual(pm.avg_degree(9001), 1000)
def testAvgDegree(self):
pm = mfng.simpleProbMeasure(m=3)
self.assertAlmostEqual(pm.avg_degree(9001), 1000)
def testProbsShape(self):
for m in range(2, self.m_max):
pm = mfng.simpleProbMeasure(m=m)
shape = pm.probs.shape
self.assertEqual(shape, (m, m))
def testDivsLength(self):
for m in range(2, self.m_max):
pm = mfng.simpleProbMeasure(m=m)
length = len(pm.divs)
self.assertEqual(length, m)
def testMaxDivs(self):
for m in range(2,self.m_max):
pm = mfng.simpleProbMeasure(m=m)
for K in range(1,self.K_max):
self.assertRaises(ValueError, pm.iterate, K=K, maxdivs=m**K-1)
def testTooManyDivs(self):
m = 4
pm = mfng.simpleProbMeasure(m=m)
K = 5
# 4**4 = 216
self.assertRaises(ValueError, pm.iterate, K=K)
def testTooManyDivs(self):
m = 4
pm = mfng.simpleProbMeasure(m=m)
K = 5
# 4**4 = 216
self.assertRaises(ValueError, pm.iterate, K=K)
def testDivsLength(self):
for m in range(2,self.m_max):
pm = mfng.simpleProbMeasure(m=m)
length = len(pm.divs)
self.assertEqual(length, m)
def testProbsShape(self):
for m in range(2,self.m_max):
pm = mfng.simpleProbMeasure(m=m)
shape = pm.probs.shape
self.assertEqual(shape, (m,m))
