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reliability.py: fix the numpy conversion, it was completely broken. Thanks to Terrell Russell for the help.

This commit is contained in:
Brian Warner 2009-02-19 13:55:15 -07:00
parent 268cd538e2
commit 790a10d1b2
3 changed files with 56 additions and 21 deletions
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41
src/allmydata/reliability.py
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@ -2,7 +2,7 @@
import math
from allmydata.util import statistics
from numpy import array
from numpy import array, matrix, dot
DAY=24*60*60
MONTH=31*DAY
@ -78,14 +78,14 @@ class ReliabilityModel:
#print "REPAIR:", repair
#print "DIFF:", (old_post_repair - decay * repair)
START = array([[0]*N + [1]])
ALIVE = array([[0]*k + [1]*(1+N-k)])
DEAD = array([[1]*k + [0]*(1+N-k)])
REPAIRp = array([[0]*k + [1]*(R-k) + [0]*(1+N-R)])
REPAIR_newshares = array([[0]*k +
[N-i for i in range(k, R)] +
[0]*(1+N-R)])
assert REPAIR_newshares.shape[1] == N+1
START = array([0]*N + [1])
ALIVE = array([0]*k + [1]*(1+N-k))
DEAD = array([1]*k + [0]*(1+N-k))
REPAIRp = array([0]*k + [1]*(R-k) + [0]*(1+N-R))
REPAIR_newshares = array([0]*k +
[N-i for i in range(k, R)] +
[0]*(1+N-R))
assert REPAIR_newshares.shape[0] == N+1
#print "START", START
#print "ALIVE", ALIVE
#print "REPAIRp", REPAIRp
@ -101,24 +101,25 @@ class ReliabilityModel:
report = ReliabilityReport()
for t in range(0, report_span+delta, delta):
unmaintained_state = unmaintained_state * decay
maintained_state = maintained_state * decay
# the .A[0] turns the one-row matrix back into an array
unmaintained_state = (unmaintained_state * decay).A[0]
maintained_state = (maintained_state * decay).A[0]
if (t-last_check) > check_period:
last_check = t
# we do a check-and-repair this frequently
need_repair = (maintained_state * REPAIRp).sum()
need_repair = dot(maintained_state, REPAIRp)
P_repaired_last_check_period = need_repair
new_shares = (maintained_state * REPAIR_newshares).sum()
new_shares = dot(maintained_state, REPAIR_newshares)
needed_repairs.append(need_repair)
needed_new_shares.append(new_shares)
maintained_state = maintained_state * repair
maintained_state = (maintained_state * repair).A[0]
if (t-last_report) > report_period:
last_report = t
P_dead_unmaintained = (unmaintained_state * DEAD).sum()
P_dead_maintained = (maintained_state * DEAD).sum()
P_dead_unmaintained = dot(unmaintained_state, DEAD)
P_dead_maintained = dot(maintained_state, DEAD)
cumulative_number_of_repairs = sum(needed_repairs)
cumulative_number_of_new_shares = sum(needed_new_shares)
report.add_sample(t, unmaintained_state, maintained_state,
@ -128,8 +129,8 @@ class ReliabilityModel:
P_dead_unmaintained, P_dead_maintained)
# record one more sample at the end of the run
P_dead_unmaintained = (unmaintained_state * DEAD).sum()
P_dead_maintained = (maintained_state * DEAD).sum()
P_dead_unmaintained = dot(unmaintained_state, DEAD)
P_dead_maintained = dot(maintained_state, DEAD)
cumulative_number_of_repairs = sum(needed_repairs)
cumulative_number_of_new_shares = sum(needed_new_shares)
report.add_sample(t, unmaintained_state, maintained_state,
@ -174,7 +175,7 @@ class ReliabilityModel:
assert len(decay_row) == (N+1), len(decay_row)
decay_rows.append(decay_row)
decay = array(decay_rows)
decay = matrix(decay_rows)
return decay
def build_decay_row(self, start_shares, P):
@ -205,7 +206,7 @@ class ReliabilityModel:
new_repair_row[start_shares] = 1
new_repair_rows.append(new_repair_row)
repair = array(new_repair_rows)
repair = matrix(new_repair_rows)
return repair
class ReliabilityReport:

34
src/allmydata/test/test_provisioning.py
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@ -71,7 +71,41 @@ class Reliability(unittest.TestCase):
def test_basic(self):
if ReliabilityModel is None:
raise unittest.SkipTest("reliability model requires NumPy")
# test that numpy math works the way I think it does
import numpy
decay = numpy.matrix([[1,0,0],
[.1,.9,0],
[.01,.09,.9],
])
start = numpy.array([0,0,1])
g2 = (start * decay).A[0]
self.failUnlessEqual(repr(g2), repr(numpy.array([.01,.09,.9])))
g3 = (g2 * decay).A[0]
self.failUnlessEqual(repr(g3), repr(numpy.array([.028,.162,.81])))
# and the dot product
recoverable = numpy.array([0,1,1])
P_recoverable_g2 = numpy.dot(g2, recoverable)
self.failUnlessAlmostEqual(P_recoverable_g2, .9 + .09)
P_recoverable_g3 = numpy.dot(g3, recoverable)
self.failUnlessAlmostEqual(P_recoverable_g3, .81 + .162)
r = ReliabilityModel.run(delta=100000,
report_period=3*MONTH,
report_span=5*YEAR)
self.failUnlessEqual(len(r.samples), 20)
last_row = r.samples[-1]
#print last_row
(when, unmaintained_shareprobs, maintained_shareprobs,
P_repaired_last_check_period,
cumulative_number_of_repairs,
cumulative_number_of_new_shares,
P_dead_unmaintained, P_dead_maintained) = last_row
self.failUnless(isinstance(P_repaired_last_check_period, float))
self.failUnless(isinstance(P_dead_unmaintained, float))
self.failUnless(isinstance(P_dead_maintained, float))
self.failUnlessAlmostEqual(P_dead_unmaintained, 0.033591004555395272)
self.failUnlessAlmostEqual(P_dead_maintained, 3.2983995819177542e-08)

2
src/allmydata/web/reliability.xhtml
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@ -38,7 +38,7 @@ repair bandwidth to configure on a Tahoe grid.</p>
check period.</li>
<li>P_dead (unmaintained): the chance that the file will be unrecoverable
without periodic check+repair</li>
<li>P_dead (maintained): the chance that the file will be recoverable even
<li>P_dead (maintained): the chance that the file will be unrecoverable even
with periodic check+repair</li>
</ul>