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Remove use of CausalModel from notebooks and test files #1220

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Remove use of CausalModel from notebooks and test files #1220

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7ebe273
Change do_sampled_demo
rahulbshrestha Jun 28, 2024
b980adb
Refactor for dowhy_confounder_example
rahulbshrestha Jul 2, 2024
8fb4960
Removed unnnecessary dependency
rahulbshrestha Jul 2, 2024
598f428
Added changes for estimate_effect
rahulbshrestha Jul 9, 2024
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22 changes: 14 additions & 8 deletions docs/source/example_notebooks/do_sampler_demo.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -119,17 +119,21 @@
"metadata": {},
"outputs": [],
"source": [
"from dowhy import CausalModel\n",
"from dowhy.causal_graph import CausalGraph\n",
"\n",
"\n",
"causes = ['D']\n",
"outcomes = ['Y']\n",
"common_causes = ['Z']\n",
"\n",
"model = CausalModel(df, \n",
" causes,\n",
" outcomes,\n",
" common_causes=common_causes)\n",
"nx_graph = model._graph._graph"
"graph = CausalGraph(\n",
" causes,\n",
" outcomes,\n",
" common_cause_names=common_causes,\n",
" observed_node_names=df.columns.tolist(),\n",
")\n",
"\n",
"nx_graph = graph._graph"
]
},
{
Expand All @@ -145,7 +149,9 @@
"metadata": {},
"outputs": [],
"source": [
"identification = model.identify_effect(proceed_when_unidentifiable=True)"
"from dowhy.causal_identifier import identify_effect\n",
"\n",
"identification = identify_effect(nx_graph, action_nodes=causes, outcome_nodes=outcomes, observed_nodes=list(graph.get_all_nodes(include_unobserved=False)))"
]
},
{
Expand Down Expand Up @@ -225,7 +231,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
"version": "3.11.8"
},
"toc": {
"base_numbering": 1,
Expand Down
426 changes: 404 additions & 22 deletions docs/source/example_notebooks/dowhy_confounder_example.ipynb
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686 changes: 654 additions & 32 deletions docs/source/example_notebooks/dowhy_interpreter.ipynb
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