I am running into an numpy type error (see below) whenever I set value for the parameters mcmc==True or ci==0.95 in any convoys model. This is consistent across data sources and even occurs when using the example data sets. If I remove these parameters the code runs as expected with no errors. Is this something anyone else has come across? Any help is much appreciated!
TypeError: 'numpy.float64' object cannot be interpreted as an integer
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-160-acdf74229cef> in <module>
----> 1 model_test.fit(X,B,T)
~/opt/anaconda3/lib/python3.8/site-packages/convoys/multi.py in fit(self, G, B, T)
29 for i, group in enumerate(G):
30 X[i,group] = 1
---> 31 self.base_model.fit(X, B, T)
32
33 def _get_x(self, group):
~/opt/anaconda3/lib/python3.8/site-packages/convoys/regression.py in fit(self, X, B, T, W)
267 ' %d walkers [' % n_walkers,
268 progressbar.AdaptiveETA(), ']'])
--> 269 for i, _ in enumerate(sampler.sample(p0, iterations=n_iterations)):
270 bar.update(i+1)
271 result['samples'] = sampler.chain[:, n_burnin:, :] \
~/opt/anaconda3/lib/python3.8/site-packages/emcee/ensemble.py in sample(self, initial_state, log_prob0, rstate0, blobs0, iterations, tune, skip_initial_state_check, thin_by, thin, store, progress, progress_kwargs)
377 checkpoint_step = thin_by
378 if store:
--> 379 self.backend.grow(iterations, state.blobs)
380
381 # Set up a wrapper around the relevant model functions
~/opt/anaconda3/lib/python3.8/site-packages/emcee/backends/backend.py in grow(self, ngrow, blobs)
173 self._check_blobs(blobs)
174 i = ngrow - (len(self.chain) - self.iteration)
--> 175 a = np.empty((i, self.nwalkers, self.ndim), dtype=self.dtype)
176 self.chain = np.concatenate((self.chain, a), axis=0)
177 a = np.empty((i, self.nwalkers), dtype=self.dtype)
TypeError: 'numpy.float64' object cannot be interpreted as an integer
I am running into an numpy type error (see below) whenever I set value for the parameters
mcmc==True
orci==0.95
in any convoys model. This is consistent across data sources and even occurs when using the example data sets. If I remove these parameters the code runs as expected with no errors. Is this something anyone else has come across? Any help is much appreciated!