ValueError: zero-size array to reduction operation maximum which has no identity

[sn3fru]

Error with simple dataset:

ValueError Traceback (most recent call last)
in
1 from causal_impact import CausalImpact
2 ci = CausalImpact(test, 120, n_seasons=7)
----> 3 ci.run(max_iter=1000)
4 ci.plot()

~/anaconda3/envs/python3/lib/python3.6/site-packages/causal_impact/causal_impact.py in run(self, max_iter, return_df)
69 exog=self.data.loc[:self._inter_index - 1, self._reg_cols()].values,
70 level='local linear trend',
---> 71 seasonal=self.n_seasons,
72 )
73 self._fit = self._model.fit(maxiter=max_iter)

~/anaconda3/envs/python3/lib/python3.6/site-packages/statsmodels/tsa/statespace/structural.py in init(self, endog, level, trend, seasonal, freq_seasonal, cycle, autoregressive, exog, irregular, stochastic_level, stochastic_trend, stochastic_seasonal, stochastic_freq_seasonal, stochastic_cycle, damped_cycle, cycle_period_bounds, mle_regression, use_exact_diffuse, **kwargs)
571 # Setup the representation
572 super(UnobservedComponents, self).init(
--> 573 endog, k_states, k_posdef=k_posdef, exog=exog, **kwargs
574 )
575 self.setup()

~/anaconda3/envs/python3/lib/python3.6/site-packages/statsmodels/tsa/statespace/mlemodel.py in init(self, endog, k_states, exog, dates, freq, **kwargs)
136 super(MLEModel, self).init(endog=endog, exog=exog,
137 dates=dates, freq=freq,
--> 138 missing='none')
139
140 # Store kwargs to recreate model

~/anaconda3/envs/python3/lib/python3.6/site-packages/statsmodels/tsa/base/tsa_model.py in init(self, endog, exog, dates, freq, missing, **kwargs)
45 missing='none', **kwargs):
46 super(TimeSeriesModel, self).init(endog, exog, missing=missing,
---> 47 **kwargs)
48
49 # Date handling in indexes

~/anaconda3/envs/python3/lib/python3.6/site-packages/statsmodels/base/model.py in init(self, endog, exog, **kwargs)
234
235 def init(self, endog, exog=None, **kwargs):
--> 236 super(LikelihoodModel, self).init(endog, exog, **kwargs)
237 self.initialize()
238

~/anaconda3/envs/python3/lib/python3.6/site-packages/statsmodels/base/model.py in init(self, endog, exog, **kwargs)
75 hasconst = kwargs.pop('hasconst', None)
76 self.data = self._handle_data(endog, exog, missing, hasconst,
---> 77 **kwargs)
78 self.k_constant = self.data.k_constant
79 self.exog = self.data.exog

~/anaconda3/envs/python3/lib/python3.6/site-packages/statsmodels/base/model.py in _handle_data(self, endog, exog, missing, hasconst, **kwargs)
98
99 def _handle_data(self, endog, exog, missing, hasconst, **kwargs):
--> 100 data = handle_data(endog, exog, missing, hasconst, **kwargs)
101 # kwargs arrays could have changed, easier to just attach here
102 for key in kwargs:

~/anaconda3/envs/python3/lib/python3.6/site-packages/statsmodels/base/data.py in handle_data(endog, exog, missing, hasconst, **kwargs)
670 klass = handle_data_class_factory(endog, exog)
671 return klass(endog, exog=exog, missing=missing, hasconst=hasconst,
--> 672 **kwargs)

~/anaconda3/envs/python3/lib/python3.6/site-packages/statsmodels/base/data.py in init(self, endog, exog, missing, hasconst, **kwargs)
85 self.const_idx = None
86 self.k_constant = 0
---> 87 self._handle_constant(hasconst)
88 self._check_integrity()
89 self._cache = {}

~/anaconda3/envs/python3/lib/python3.6/site-packages/statsmodels/base/data.py in _handle_constant(self, hasconst)
175 (np.ones(self.exog.shape[0]), self.exog))
176 rank_augm = np.linalg.matrix_rank(augmented_exog)
--> 177 rank_orig = np.linalg.matrix_rank(self.exog)
178 self.k_constant = int(rank_orig == rank_augm)
179 self.const_idx = None

<array_function internals> in matrix_rank(*args, **kwargs)

~/anaconda3/envs/python3/lib/python3.6/site-packages/numpy/linalg/linalg.py in matrix_rank(M, tol, hermitian)
1902 S = svd(M, compute_uv=False, hermitian=hermitian)
1903 if tol is None:
-> 1904 tol = S.max(axis=-1, keepdims=True) * max(M.shape[-2:]) * finfo(S.dtype).eps
1905 else:
1906 tol = asarray(tol)[..., newaxis]

~/anaconda3/envs/python3/lib/python3.6/site-packages/numpy/core/_methods.py in _amax(a, axis, out, keepdims, initial, where)
37 def _amax(a, axis=None, out=None, keepdims=False,
38 initial=_NoValue, where=True):
---> 39 return umr_maximum(a, axis, None, out, keepdims, initial, where)
40
41 def _amin(a, axis=None, out=None, keepdims=False,

ValueError: zero-size array to reduction operation maximum which has no identity