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