Comments (3)
Looking at source I assumed from the help statement I could use 'None' as the method.
"""Refute an estimated causal effect. If method_name is provided, uses the provided method. Else, finds a suitable method to use. :param estimate: an instance of the CausalEstimate class. :returns: an instance of the RefuteResult class """
This throws an UnboundLocalError
UnboundLocalError: local variable 'refuter_class' referenced before assignment
This makes sense when I look at the code:
if method_name is None: pass else: refuter_class = causal_refuters.get_class_object(method_name)
refuter = refuter_class( self._data, identified_estimand=estimand, estimate=estimate, **kwargs ) res = refuter.refute_estimate() return res
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Thanks for raising this, @steunenberg . For some reason, I am unable to reproduce this bug. Can you share your python version and any other system details?
For instance, it works on the online Binder notebook here: https://mybinder.org/v2/gh/microsoft/dowhy/master?filepath=docs%2Fsource%2Fdowhy_simple_example.ipynb
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Thanks for getting back to me. System Info:
Python version 3.6.3 :: Anaconda custom (64-bit)
OS Ubuntu 16.04
I noticed that the Notebook examples under docs/source do work on my local system.
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Related Issues (20)
- Clear documentation on identification methods HOT 2
- Backdoor path HOT 4
- Linear dataset functionality and parameters HOT 1
- Simple constraints for the SCM HOT 1
- How can I get more log messages from dowhy? HOT 4
- Identify effect not showing backdoor variable HOT 5
- numpy has no attribute 'long' HOT 1
- No common causes/confounders present. HOT 3
- Сausal effect for non-linear relationship HOT 1
- Compatability with networkx is broken HOT 8
- Continuous Treatment Variable HOT 1
- CausalEstimator reporting a 90% instead of 95% confidence interval for bootstrapping? HOT 5
- Hanging when refuting right after calculating confidence interval HOT 2
- Incomplete `method_name` argument documentation in `estimate_effect` HOT 4
- Add accessor to CausalModel._estimator_cache HOT 4
- Evaluation Metrics for Causal Graphs HOT 4
- Inconsistent encoding with pandas get_dummies causes prediction and effect estimation errors HOT 6
- Falsification of given DAG: not working on simulated data? HOT 4
- Causal Graph not provided. DoWhy will construct a graph based on data inputs. HOT 1
- how to use the function of estimate_effect of CausalModel class? HOT 4
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