falsify_graph about dowhy HOT 8 CLOSED

The column conversion needs to happen before calling the assignment and fit, otherwise the variables are expected to be integers, but are strings. I had similar issues before due to integer column names. So, maybe just change:

data_pd.columns = [i for i in range(len(data_pd.columns))] #define the columns as integer

to

data_pd.columns = [str(i) for i in range(len(data_pd.columns))]

But you also need to make sure that the node names in the graph are strings of integers instead of raw integers themselves.

from dowhy.

Might be an issue with the variable names in the dataframe. Can you try the following after loading/creating the data:
data_pd.columns = [str(col) for col in data_pd.columns]

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Thnks, I tried but now I had as error:
AssertionError: 2 must be list, set or str. Got <class 'int'> instead!

the type of variable names in the dataframe is:
Index(['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10'], dtype='object')
<class 'pandas.core.indexes.base.Index'>

so I don't know if this is the problem, many tks

from dowhy.

Ok, do you think you can provide a small example snippet to reproduce this (you probably don't need the streamlit context here)? I can take a closer look then.

from dowhy.

Ok , thanks

I had a nx.graph (the nodes are int) I compute scm:

scm = gcm.StructuralCausalModel(st.session_state["pc_graph_nx"])

then for assigning causal mechanism I run:

data_pd = pd.DataFrame(data_agg) #dataframe of my data
data_pd.columns = [i for i in range(len(data_pd.columns))] #define the columns as integer
data_pd = check_and_convert_categorical(data_pd, threshold=2) #use a function to get categorical variables
auto_assignment_summary = gcm.auto.assign_causal_mechanisms(
scm, data_pd, override_models=True, quality=gcm.auto.AssignmentQuality.GOOD
)
gcm.fit(scm, data_pd)
st.text(auto_assignment_summary) #until now no problem

def convert_nodes_to_str(nx_graph): #convert nodes in string

mapping = {node: str(node) for node in nx_graph.nodes}

nx_graph = nx.relabel_nodes(nx_graph, mapping)
return nx_graph

data_pd.columns = [str(col) for col in data_pd.columns] #as suggested

and finally the code (in streamlit):

  pc_graph_nx=convert_nodes_to_str(st.session_state["pc_graph_nx"])
  print(pc_graph_nx.nodes)
  result = falsify_graph((st.session_state["pc_graph_nx"]), data_pd, plot_histogram=False, suggestions=True, n_permutations=100)
  st.text(result)

with the error:
AssertionError: 1 must be list, set or str. Got <class 'int'> instead!
Traceback:
File "C:\Users\11612880\Anaconda3\envs\causal\lib\site-packages\streamlit\runtime\scriptrunner\script_runner.py", line 600, in run_script
exec(code, module.dict)
File "C:\Users\11612880\Desktop\Causal-Discovery-PoC\pages\9_📊 SCM.py", line 167, in
result = falsify_graph((st.session_state["pc_graph_nx"]), data_pd, plot_histogram=False, suggestions=True, n_permutations=100)
File "C:\Users\11612880\Anaconda3\envs\causal\lib\site-packages\dowhy\gcm\falsify.py", line 618, in falsify_graph
summary_given = run_validations(
File "C:\Users\11612880\Anaconda3\envs\causal\lib\site-packages\dowhy\gcm\falsify.py", line 412, in run_validations
m_summary = m(causal_graph=causal_graph)
File "C:\Users\11612880\Anaconda3\envs\causal\lib\site-packages\dowhy\gcm\falsify.py", line 138, in validate_lmc
if not (node, non_desc, parents) in p_values_memory:
File "C:\Users\11612880\Anaconda3\envs\causal\lib\site-packages\dowhy\gcm\falsify.py", line 89, in contains
X, Y = (_to_frozenset(i) for i in item[:2])
File "C:\Users\11612880\Anaconda3\envs\causal\lib\site-packages\dowhy\gcm\falsify.py", line 89, in
X, Y = (_to_frozenset(i) for i in item[:2])
File "C:\Users\11612880\Anaconda3\envs\causal\lib\site-packages\dowhy\gcm\falsify.py", line 979, in _to_frozenset
assert (

any idea? thanks

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Now it works, thanks very appreciated

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This issue is stale because it has been open for 14 days with no activity.

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This issue was closed because it has been inactive for 7 days since being marked as stale.

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