def test_categorical_forest_manual_inputs_errors():
state = State(
T, cctypes=CCTYPES, distargs=DISTARGS, rng=gu.gen_rng(1))
state.transition(N=1, progress=False)
cat_id = CCTYPES.index('categorical')
# Put 1201 into the first view.
view_idx = min(state.views)
state.incorporate_dim(
T[:,CCTYPES.index('categorical')], outputs=[1201],
cctype='categorical', distargs=DISTARGS[cat_id], v=view_idx)
# Updating cctype with completely invalid input should raise.
with pytest.raises(Exception):
distargs = DISTARGS[cat_id].copy()
distargs['inputs'] = [10000]
state.update_cctype(1201, 'random_forest', distargs=distargs)
# Updating cctype with input dimensions outside the view should raise.
cols_in_view = state.views[view_idx].dims.keys()
cols_out_view = [c for c in state.outputs if c not in cols_in_view]
assert len(cols_in_view) > 0 and len(cols_out_view) > 0
with pytest.raises(Exception):
distargs = DISTARGS[cat_id].copy()
distargs['inputs'] = cols_out_view
state.update_cctype(1201, 'random_forest', distargs=distargs)
# Updating cctype with no input dimensions should raise.
with pytest.raises(Exception):
distargs = DISTARGS[cat_id].copy()
distargs['inputs'] = []
state.update_cctype(1201, 'random_forest', distargs=distargs)
def test_categorical_forest():
state = State(
T, cctypes=CCTYPES, distargs=DISTARGS, rng=gu.gen_rng(1))
state.transition(N=1, progress=False)
cat_id = CCTYPES.index('categorical')
# If cat_id is singleton migrate first.
if len(state.view_for(cat_id).dims) == 1:
distargs = DISTARGS[cat_id].copy()
state.unincorporate_dim(cat_id)
state.incorporate_dim(
T[:,cat_id], outputs=[cat_id], cctype='categorical',
distargs=distargs, v=0)
state.update_cctype(cat_id, 'random_forest', distargs=distargs)
bernoulli_id = CCTYPES.index('bernoulli')
state.incorporate_dim(
T[:,bernoulli_id], outputs=[191], cctype='bernoulli',
v=state.Zv(cat_id))
state.update_cctype(191, 'random_forest', distargs={'k':2})
# Run valid transitions.
state.transition(
N=2, kernels=['rows','column_params','column_hypers'],
views=[state.Zv(cat_id)], progress=False)
# Running column transition should raise.
with pytest.raises(ValueError):
state.transition(N=1, kernels=['columns'], progress=False)
# Updating cctype in singleton View should raise.
distargs = DISTARGS[cat_id].copy()
state.incorporate_dim(
T[:,CCTYPES.index('categorical')], outputs=[98],
cctype='categorical', distargs=distargs, v=max(state.views)+1)
with pytest.raises(Exception):
state.update_cctype(98, 'random_forest', distargs=distargs)
def test_incorporate_state():
state = State(
T[:,:2], cctypes=CCTYPES[:2], distargs=DISTARGS[:2], rng=gu.gen_rng(0))
state.transition(N=5)
target = state.views.keys()[0]
# Incorporate a new dim into view[0].
state.incorporate_dim(
T[:,2], outputs=[2], cctype=CCTYPES[2], distargs=DISTARGS[2], v=target)
assert state.Zv(2) == target
state.transition(N=1)
# Incorporate a new dim into view[0] with a non-contiguous output.
state.incorporate_dim(
T[:,2], outputs=[10], cctype=CCTYPES[2], distargs=DISTARGS[2], v=target)
assert state.Zv(10) == target
state.transition(N=1)
# Some crash testing queries.
state.logpdf(-1, {10:1}, constraints={0:2, 1:1})
state.simulate(-1, [10], constraints={0:2})
# Incorporating with a duplicated output should raise.
with pytest.raises(ValueError):
state.incorporate_dim(
T[:,2], outputs=[10], cctype=CCTYPES[2], distargs=DISTARGS[2],
v=target)
# Multivariate incorporate should raise.
with pytest.raises(ValueError):
state.incorporate_dim(
T[:,2], outputs=[10, 2], cctype=CCTYPES[2],
distargs=DISTARGS[2], v=target)
# Missing output should raise.
with pytest.raises(ValueError):
state.incorporate_dim(
T[:,2], outputs=[], cctype=CCTYPES[2],
distargs=DISTARGS[2], v=target)
# Wrong number of rows should raise.
with pytest.raises(ValueError):
state.incorporate_dim(
T[:,2][:-1], outputs=[11], cctype=CCTYPES[2],
distargs=DISTARGS[2], v=target)
# Inputs should raise.
with pytest.raises(ValueError):
state.incorporate_dim(
T[:,2], outputs=[11], inputs=[2], cctype=CCTYPES[2],
distargs=DISTARGS[2], v=target)
# Incorporate dim into a newly created singleton view.
target = max(state.views)+1
state.incorporate_dim(
T[:,3], outputs=[3], cctype=CCTYPES[3],
distargs=DISTARGS[3], v=target)
assert state.Zv(3) == target
state.transition(N=1)
# Incorporate dim without specifying a view.
state.incorporate_dim(T[:,4], outputs=[4],
cctype=CCTYPES[4], distargs=DISTARGS[4])
state.transition(N=1)
# Unincorporate first dim.
previous = state.n_cols()
state.unincorporate_dim(0)
assert state.n_cols() == previous-1
state.transition(N=1)
# Reincorporate dim without specifying a view.
state.incorporate_dim(
T[:,0], outputs=[0], cctype=CCTYPES[0], distargs=DISTARGS[0])
state.transition(N=1)
# Incorporate dim into singleton view, remove it, assert destroyed.
target = max(state.views)+1
state.incorporate_dim(
T[:,5], outputs=[5], cctype=CCTYPES[5], distargs=DISTARGS[5],
v=target)
previous = len(state.views)
state.unincorporate_dim(5)
assert len(state.views) == previous-1
state.transition(N=1)
# Reincorporate dim into a singleton view.
target = max(state.views)+1
state.incorporate_dim(T[:,5], outputs=[5], cctype=CCTYPES[5],
distargs=DISTARGS[5], v=target)
state.transition(N=1)
# Incorporate the rest of the dims in the default way.
for i in xrange(6, len(CCTYPES)):
state.incorporate_dim(
T[:,i], outputs=[max(state.outputs)+1],
cctype=CCTYPES[i], distargs=DISTARGS[i])
state.transition(N=1)
# Unincorporating non-existent dim should raise.
with pytest.raises(ValueError):
state.unincorporate_dim(9999)
# Unincorporate all the dims, except the last one.
for o in state.outputs[:-1]:
state.unincorporate_dim(o)
assert state.n_cols() == 1
state.transition(N=1)
# Unincorporating last dim should raise.
with pytest.raises(ValueError):
state.unincorporate_dim(state.outputs[0])
