---------------------------------------------------------------------------
ZeroProbability Traceback (most recent call last)
<ipython-input-3-4d628ff3ae4e> in <module>()
3 data = hddm.load_csv('data/combined_clean.csv')
4
----> 5 model = hddm.HDDM(data, depends_on={'v': ['stim', 'subj_type'], 'a': 'subj_type'})
6 model.find_starting_values()
7 model.sample(6000, burn=20)
~/anaconda/envs/lang-dec/lib/python3.5/site-packages/hddm/models/hddm_info.py in __init__(self, *args, **kwargs)
111 self.is_informative = kwargs.pop('informative', True)
112
--> 113 super(HDDM, self).__init__(*args, **kwargs)
114
115 def _create_stochastic_knodes(self, include):
~/anaconda/envs/lang-dec/lib/python3.5/site-packages/hddm/models/base.py in __init__(self, data, bias, include, wiener_params, p_outlier, **kwargs)
687 self.wfpt_class = hddm.likelihoods.generate_wfpt_stochastic_class(wp, cdf_range=self.cdf_range)
688
--> 689 super(HDDMBase, self).__init__(data, **kwargs)
690
691 def __getstate__(self):
~/anaconda/envs/lang-dec/lib/python3.5/site-packages/hddm/models/base.py in __init__(self, data, **kwargs)
38 self.std_depends = kwargs.pop('std_depends', False)
39
---> 40 super(AccumulatorModel, self).__init__(data, **kwargs)
41
42
~/anaconda/envs/lang-dec/lib/python3.5/site-packages/kabuki/hierarchical.py in __init__(self, data, is_group_model, depends_on, trace_subjs, plot_subjs, plot_var, group_only_nodes)
346 self.db = None
347
--> 348 self._setup_model()
349
350 def _setup_model(self):
~/anaconda/envs/lang-dec/lib/python3.5/site-packages/kabuki/hierarchical.py in _setup_model(self)
357
358 # constructs pymc nodes etc and connects them appropriately
--> 359 self.create_model()
360
361 def __getstate__(self):
~/anaconda/envs/lang-dec/lib/python3.5/site-packages/kabuki/hierarchical.py in create_model(self, max_retries)
437 else:
438 print("After %f retries, still no good fit found." %(tries))
--> 439 _create()
440
441 # create node container
~/anaconda/envs/lang-dec/lib/python3.5/site-packages/kabuki/hierarchical.py in _create()
427 def _create():
428 for knode in self.knodes:
--> 429 knode.create()
430
431 for tries in range(max_retries):
~/anaconda/envs/lang-dec/lib/python3.5/site-packages/kabuki/hierarchical.py in create(self)
166 kwargs['doc'] = node_name
167
--> 168 node = self.create_node(node_name, kwargs, grouped_data)
169
170 if node is not None:
~/anaconda/envs/lang-dec/lib/python3.5/site-packages/kabuki/hierarchical.py in create_node(self, node_name, kwargs, data)
174 def create_node(self, node_name, kwargs, data):
175 #actually create the node
--> 176 return self.pymc_node(name=node_name, **kwargs)
177
178 def create_tag_and_subj_idx(self, cols, uniq_elem):
~/anaconda/envs/lang-dec/lib/python3.5/site-packages/pymc/distributions.py in __init__(self, *args, **kwds)
318 logp_partial_gradients=logp_partial_gradients,
319 dtype=dtype,
--> 320 **arg_dict_out)
321
322 new_class.__name__ = name
~/anaconda/envs/lang-dec/lib/python3.5/site-packages/pymc/PyMCObjects.py in __init__(self, logp, doc, name, parents, random, trace, value, dtype, rseed, observed, cache_depth, plot, verbose, isdata, check_logp, logp_partial_gradients)
773 if check_logp:
774 # Check initial value
--> 775 if not isinstance(self.logp, float):
776 raise ValueError(
777 "Stochastic " +
~/anaconda/envs/lang-dec/lib/python3.5/site-packages/pymc/PyMCObjects.py in get_logp(self)
930 (self._value, self._parents.value))
931 else:
--> 932 raise ZeroProbability(self.errmsg)
933
934 return logp
ZeroProbability: Stochastic wfpt(18439.control).1.5451359127328033's value is outside its support,
or it forbids its parents' current values.