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No model attribute --> setting up standard HDDM
Set model to ddm
/home/jasongong/anaconda3/envs/hddm_test/lib/python3.7/site-packages/hddm/models/base.py:1310: UserWarning:
Your include statement misses either the v, a or t parameters.
Parameters not explicitly included will be set to the defaults,
which you can find in the model_config dictionary!
+ "which you can find in the model_config dictionary!"
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
/tmp/ipykernel_109359/1763651991.py in <module>
----> 1 m = hddm.HDDM(data)
2 # find a good starting point which helps with the convergence.
3 m.find_starting_values()
4 # start drawing 2000 samples and discarding 20 as burn-in (usually you want to have a longer burn-in period)
5 m.sample(2000, burn=20)
~/anaconda3/envs/hddm_test/lib/python3.7/site-packages/hddm/models/hddm_info.py in __init__(self, *args, **kwargs)
156 self.model_config = kwargs.pop("model_config")
157
--> 158 super(HDDM, self).__init__(*args, **kwargs)
159
160 # -------------------------------------------------------------------------------------
~/anaconda3/envs/hddm_test/lib/python3.7/site-packages/hddm/models/base.py in __init__(self, data, bias, include, wiener_params, p_outlier, **kwargs)
1390 )
1391
-> 1392 super(HDDMBase, self).__init__(data, **kwargs)
1393
1394 def __getstate__(self):
~/anaconda3/envs/hddm_test/lib/python3.7/site-packages/hddm/models/base.py in __init__(self, data, **kwargs)
72
73 self.std_depends = kwargs.pop("std_depends", False)
---> 74 super(AccumulatorModel, self).__init__(data, **kwargs)
75
76 def _create_an_average_model(self):
~/anaconda3/envs/hddm_test/lib/python3.7/site-packages/kabuki/hierarchical.py in __init__(self, data, is_group_model, depends_on, trace_subjs, plot_subjs, plot_var, group_only_nodes)
384 self.db = None
385
--> 386 self._setup_model()
387
388 def _setup_model(self):
~/anaconda3/envs/hddm_test/lib/python3.7/site-packages/kabuki/hierarchical.py in _setup_model(self)
395
396 # constructs pymc nodes etc and connects them appropriately
--> 397 self.create_model()
398
399 def __getstate__(self):
~/anaconda3/envs/hddm_test/lib/python3.7/site-packages/kabuki/hierarchical.py in create_model(self, max_retries)
486
487 # Check whether all user specified column names (via depends_on) where used by the depends_on.
--> 488 assert set(flatten(list(self.depends.values()))).issubset(
489 set(flatten(self.nodes_db.depends))
490 ), "One of the column names specified via depends_on was not picked up. Check whether you specified the correct parameter value."
~/anaconda3/envs/hddm_test/lib/python3.7/site-packages/kabuki/utils.py in flatten(l)
11
12 def flatten(l):
---> 13 return reduce(lambda x, y: list(x) + list(y), l)
14
15
TypeError: reduce() of empty sequence with no initial value
if you need additional information, please let me know.
I found the HDDMRegressor works fine.
Best,
Jason
The text was updated successfully, but these errors were encountered:
I recently installed the lasted version of HDDM (0.9.9).
I run the tutorial.
The code
m = hddm.HDDM(data)
give the following error:
if you need additional information, please let me know.
I found the HDDMRegressor works fine.
Best,
Jason
The text was updated successfully, but these errors were encountered: