def test_multiple_runs():
"test running multiple models through multiple tournaments"
d = testing.play_data()
models = [nx.logistic(), nx.fifty()]
with testing.HiddenPrints():
p = nx.production(models, d, 'bernie')
ok_(p.shape[1] == 2, 'wrong number of tournaments')
p = nx.backtest(models, d, 2)
ok_(p.shape[1] == 2, 'wrong number of tournaments')
p = nx.run(models, nx.ValidationSplitter(d), 'ken')
ok_(p.shape[1] == 2, 'wrong number of tournaments')
p = nx.production(models, d)
ok_(p.shape[1] == 10, 'wrong number of tournaments')
p = nx.backtest(models, d)
ok_(p.shape[1] == 10, 'wrong number of tournaments')
p = nx.run(models, nx.ValidationSplitter(d))
ok_(p.shape[1] == 10, 'wrong number of tournaments')
p = nx.production(models, d, [1, 5])
ok_(p.shape[1] == 4, 'wrong number of tournaments')
ok_(p.tournaments() == ['bernie', 'charles'], 'wrong tournaments')
p = nx.backtest(models, d, ['charles', 'bernie'])
ok_(p.shape[1] == 4, 'wrong number of tournaments')
ok_(p.tournaments() == ['bernie', 'charles'], 'wrong tournaments')
p = nx.run(models, nx.ValidationSplitter(d), ['ken'])
ok_(p.shape[1] == 2, 'wrong number of tournaments')
ok_(p.tournaments() == ['ken'], 'wrong tournaments')
def test_multiple_runs():
"""test running multiple models through multiple tournaments"""
d = testing.play_data()
models = [nx.linear(), nx.fifty()]
with testing.HiddenPrints():
p = nx.production(models, d, 'kazutsugi')
ok_(p.shape[1] == 2, 'wrong number of tournaments')
p = nx.backtest(models, d, 8)
ok_(p.shape[1] == 2, 'wrong number of tournaments')
p = nx.run(models, nx.ValidationSplitter(d), 'kazutsugi')
ok_(p.shape[1] == 2, 'wrong number of tournaments')
p = nx.production(models, d)
ok_(p.shape[1] == 2, 'wrong number of tournaments')
p = nx.backtest(models, d)
ok_(p.shape[1] == 2, 'wrong number of tournaments')
p = nx.run(models, nx.ValidationSplitter(d))
ok_(p.shape[1] == 2, 'wrong number of tournaments')
p = nx.production(models, d, [8])
ok_(p.shape[1] == 2, 'wrong number of tournaments')
ok_(p.tournaments() == ['kazutsugi'], 'wrong tournaments')
p = nx.backtest(models, d, ['kazutsugi'])
ok_(p.shape[1] == 2, 'wrong number of tournaments')
ok_(p.tournaments() == ['kazutsugi'], 'wrong tournaments')
p = nx.run(models, nx.ValidationSplitter(d), ['kazutsugi'])
ok_(p.shape[1] == 2, 'wrong number of tournaments')
ok_(p.tournaments() == ['kazutsugi'], 'wrong tournaments')
def test_run():
"Make sure run runs"
d = testing.play_data()
models = [nx.linear(), nx.fifty()]
splitters = [nx.TournamentSplitter(d),
nx.ValidationSplitter(d),
nx.CheatSplitter(d),
nx.CVSplitter(d, kfold=2),
nx.SplitSplitter(d, fit_fraction=0.5)]
for model in models:
for splitter in splitters:
p = nx.run(model, splitter, tournament=None, verbosity=0)
ok_(p.shape[1] == 1, 'wrong number of tournaments')
ok_(p.tournaments() == nx.tournament_all(), 'wrong tournaments')
assert_raises(ValueError, nx.run, None, nx.TournamentSplitter(d))
assert_raises(ValueError, nx.run, nx.fifty(), nx.TournamentSplitter(d), {})
def get_models():
models = [
nx.logistic(),
nx.ridge_mean(),
nx.extratrees(),
nx.randomforest(),
nx.mlpc(),
nx.logisticPCA(),
nx.example_predictions(),
nx.fifty()
]
return models
def test_backtest_production():
"Make sure backtest and production run"
d = testing.micro_data()
model = nx.fifty()
with testing.HiddenPrints():
p = nx.production(model, d)
ok_(p.shape[1] == 5, 'wrong number of tournaments')
ok_(p.tournaments() == nx.tournament_all(), 'wrong tournaments')
p = nx.backtest(model, d, kfold=2)
ok_(p.shape[1] == 5, 'wrong number of tournaments')
ok_(p.tournaments() == nx.tournament_all(), 'wrong tournaments')
for verbosity in (0, 1, 2, 3):
nx.backtest(model, d, tournament=3, kfold=2, verbosity=verbosity)
nx.production(model, d, tournament='ken', verbosity=verbosity)
nx.production(model, d, tournament=4, verbosity=verbosity)
nx.production(model, d, tournament=None, verbosity=verbosity)
if verbosity == 3:
nx.production(model, d, tournament=5, verbosity=verbosity)
nx.production(model,
d,
tournament='charles',
verbosity=verbosity)
def test_run_unique():
"name and tournament lists must be unique"
d = testing.micro_data()
assert_raises(ValueError, nx.production, [nx.fifty(), nx.fifty()], d)
assert_raises(ValueError, nx.production, nx.fifty(), d, [1, 'bernie'])