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https://github.com/tahoe-lafs/tahoe-lafs.git
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116 lines
4.1 KiB
Python
116 lines
4.1 KiB
Python
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import unittest
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from allmydata import provisioning
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ReliabilityModel = None
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try:
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from allmydata.reliability import ReliabilityModel
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except ImportError:
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pass # might not be importable, since it needs NumPy
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from nevow import inevow
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from zope.interface import implements
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class MyRequest(object):
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implements(inevow.IRequest)
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pass
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class Provisioning(unittest.TestCase):
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def getarg(self, name, astype=int):
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if name in self.fields:
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return astype(self.fields[name])
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return None
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def test_load(self):
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pt = provisioning.ProvisioningTool()
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self.fields = {}
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#r = MyRequest()
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#r.fields = self.fields
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#ctx = RequestContext()
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#unfilled = pt.renderSynchronously(ctx)
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lots_of_stan = pt.do_forms(self.getarg)
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self.failUnless(lots_of_stan is not None)
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self.fields = {'filled': True,
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"num_users": 50e3,
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"files_per_user": 1000,
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"space_per_user": 1e9,
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"sharing_ratio": 1.0,
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"encoding_parameters": "3-of-10-5",
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"num_servers": 30,
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"ownership_mode": "A",
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"download_rate": 100,
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"upload_rate": 10,
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"delete_rate": 10,
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"lease_timer": 7,
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}
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#filled = pt.renderSynchronously(ctx)
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more_stan = pt.do_forms(self.getarg)
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self.failUnless(more_stan is not None)
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# trigger the wraparound configuration
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self.fields["num_servers"] = 5
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#filled = pt.renderSynchronously(ctx)
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more_stan = pt.do_forms(self.getarg)
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# and other ownership modes
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self.fields["ownership_mode"] = "B"
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more_stan = pt.do_forms(self.getarg)
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self.fields["ownership_mode"] = "E"
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more_stan = pt.do_forms(self.getarg)
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def test_provisioning_math(self):
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self.failUnlessEqual(provisioning.binomial(10, 0), 1)
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self.failUnlessEqual(provisioning.binomial(10, 1), 10)
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self.failUnlessEqual(provisioning.binomial(10, 2), 45)
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self.failUnlessEqual(provisioning.binomial(10, 9), 10)
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self.failUnlessEqual(provisioning.binomial(10, 10), 1)
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DAY=24*60*60
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MONTH=31*DAY
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YEAR=365*DAY
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class Reliability(unittest.TestCase):
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def test_basic(self):
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if ReliabilityModel is None:
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raise unittest.SkipTest("reliability model requires NumPy")
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# test that numpy math works the way I think it does
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import numpy
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decay = numpy.matrix([[1,0,0],
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[.1,.9,0],
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[.01,.09,.9],
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])
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start = numpy.array([0,0,1])
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g2 = (start * decay).A[0]
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self.failUnlessEqual(repr(g2), repr(numpy.array([.01,.09,.9])))
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g3 = (g2 * decay).A[0]
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self.failUnlessEqual(repr(g3), repr(numpy.array([.028,.162,.81])))
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# and the dot product
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recoverable = numpy.array([0,1,1])
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P_recoverable_g2 = numpy.dot(g2, recoverable)
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self.failUnlessAlmostEqual(P_recoverable_g2, .9 + .09)
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P_recoverable_g3 = numpy.dot(g3, recoverable)
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self.failUnlessAlmostEqual(P_recoverable_g3, .81 + .162)
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r = ReliabilityModel.run(delta=100000,
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report_period=3*MONTH,
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report_span=5*YEAR)
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self.failUnlessEqual(len(r.samples), 20)
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last_row = r.samples[-1]
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#print last_row
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(when, unmaintained_shareprobs, maintained_shareprobs,
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P_repaired_last_check_period,
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cumulative_number_of_repairs,
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cumulative_number_of_new_shares,
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P_dead_unmaintained, P_dead_maintained) = last_row
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self.failUnless(isinstance(P_repaired_last_check_period, float))
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self.failUnless(isinstance(P_dead_unmaintained, float))
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self.failUnless(isinstance(P_dead_maintained, float))
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self.failUnlessAlmostEqual(P_dead_unmaintained, 0.033591004555395272)
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self.failUnlessAlmostEqual(P_dead_maintained, 3.2983995819177542e-08)
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if __name__=='__main__':
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unittest.main()
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