def test_NEWCONSENSUS_ends_with_OK_on_s(self):

        # bootstrap the TorState so we can send it a "real" 650
        # update

        self.protocol._set_valid_events(' '.join(self.state.event_map.keys()))
        self.state._bootstrap()

        self.send("250+ns/all=")
        self.send(".")
        self.send("250 OK")

        self.send("250+circuit-status=")
        self.send(".")
        self.send("250 OK")

        self.send("250-stream-status=")
        self.send("250 OK")

        self.send("250-address-mappings/all=")
        self.send('250 OK')

        for ignored in self.state.event_map.items():
            self.send("250 OK")

        self.send("250-entry-guards=")
        self.send("250 OK")

        self.send("250 OK")

        # state is now bootstrapped, we can send our NEWCONSENSUS update

        self.protocol.dataReceived('\r\n'.join('''650+NEWCONSENSUS
r Unnamed ABJlguUFz1lvQS0jq8nhTdRiXEk /zIVUg1tKMUeyUBoyimzorbQN9E 2012-05-23 01:10:22 219.94.255.254 9001 0
s Fast Guard Running Stable Valid
.
650 OK
'''.split('\n')))

        self.assertTrue('Unnamed' in self.state.routers)
        self.assertTrue('$00126582E505CF596F412D23ABC9E14DD4625C49' in self.state.routers)
Centers data to have mean zero along axis 0. If fit_intercept=False or if
dataset/ETHPy150Open meejah/txtorcon/test/test_torstate.py/StateTests.test_NEWCONSENSUS_ends_with_OK_on_s--crossover with--dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/linear_model/base.py/_preprocess_data