Merge branch 'master' of github.com:uber/causalml

.github/workflows/python-publish.yml

@@ -21,9 +21,9 @@ jobs:
         python-version: ['3.8']
 
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
     - name: Set up Python
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v4
       with:
         python-version: ${{ matrix.python-version }}
     - name: Install dependencies

.github/workflows/python-test.yaml

@@ -13,9 +13,9 @@ jobs:
         python-version: [3.7, 3.8, 3.9]
 
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v4
         with:
           python-version: ${{ matrix.python-version }}
       # You can test your matrix by printing the current Python version

causalml/inference/iv/iv_regression.py

@@ -1,5 +1,4 @@
 import numpy as np
-import pandas as pd
 
 from causalml.inference.meta.utils import convert_pd_to_np
 import statsmodels.api as sm

causalml/inference/meta/base.py

@@ -265,7 +265,7 @@ def plot_shap_values(
             features (optional, np.array): list/array of feature names. If None, an enumerated list will be used.
             shap_dict (optional, dict): a dict of shapley value matrices. If None, shap_dict will be computed.
         """
-        override_checks = False if shap_dict is None else True
+        override_checks = shap_dict is not None
         explainer = Explainer(
             method="shapley",
             control_name=self.control_name,

causalml/inference/meta/drlearner.py

@@ -8,7 +8,6 @@
 from xgboost import XGBRegressor
 
 from causalml.inference.meta.base import BaseLearner
-from causalml.inference.meta.explainer import Explainer
 from causalml.inference.meta.utils import (
     check_treatment_vector,
     check_p_conditions,

causalml/inference/meta/rlearner.py

@@ -14,7 +14,6 @@
     convert_pd_to_np,
     get_weighted_variance,
 )
-from causalml.inference.meta.explainer import Explainer
 from causalml.propensity import compute_propensity_score, ElasticNetPropensityModel
 
 

causalml/inference/meta/slearner.py

@@ -7,7 +7,6 @@
 from copy import deepcopy
 
 from causalml.inference.meta.base import BaseLearner
-from causalml.inference.meta.explainer import Explainer
 from causalml.inference.meta.utils import check_treatment_vector, convert_pd_to_np
 from causalml.metrics import regression_metrics, classification_metrics
 

causalml/inference/meta/tlearner.py

@@ -15,7 +15,6 @@
 from xgboost import XGBRegressor
 
 from causalml.inference.meta.base import BaseLearner
-from causalml.inference.meta.explainer import Explainer
 from causalml.inference.meta.utils import check_treatment_vector, convert_pd_to_np
 from causalml.metrics import regression_metrics, classification_metrics
 

causalml/inference/meta/tmle.py

@@ -160,7 +160,7 @@ def estimate_ate(self, X, treatment, y, p, segment=None, return_ci=False):
         ate_lb = []
         ate_ub = []
 
-        for i, group in enumerate(self.t_groups):
+        for _, group in enumerate(self.t_groups):
             logger.info("Estimating ATE for group {}.".format(group))
             w_group = (treatment == group).astype(int)
             p_group = p[group]

causalml/inference/tree/causal/_builder.pyx

@@ -58,7 +58,7 @@ cdef class DepthFirstCausalTreeBuilder(TreeBuilder):
         cdef int init_capacity
 
         if tree.max_depth <= 10:
-            init_capacity = (2 ** (tree.max_depth + 1)) - 1
+            init_capacity = int(2 ** (tree.max_depth + 1)) - 1
         else:
             init_capacity = 2047
 

causalml/match.py

@@ -130,7 +130,7 @@ def match(self, data, treatment_col, score_cols):
             (pandas.DataFrame): The subset of data consisting of matched
                 treatment and control group data.
         """
-        assert type(score_cols) is list, "score_cols must be a list"
+        assert isinstance(score_cols, list), "score_cols must be a list"
         treatment = data.loc[data[treatment_col] == 1, score_cols]
         control = data.loc[data[treatment_col] == 0, score_cols]
 

envs/environment-py37.yml

@@ -2,7 +2,7 @@ name: causalml-py37
 channels:
   - defaults
 dependencies:
-  - pip=21.0.1
+  - pip
   - python=3.7
   - setuptools=52.0.0
   - graphviz

envs/environment-py38.yml

@@ -2,7 +2,7 @@ name: causalml-py38
 channels:
   - defaults
 dependencies:
-  - pip=21.0.1
+  - pip
   - python=3.8
   - setuptools=52.0.0
   - pip:

envs/environment-py39.yml

@@ -2,9 +2,10 @@ name: causalml-py39
 channels:
   - defaults
 dependencies:
-  - pip=21.0.1
+  - pip
   - python=3.9
   - setuptools=52.0.0
+  - numpy=1.22
   - pip:
     - absl-py==0.12.0
     - appnope==0.1.2
@@ -66,7 +67,6 @@ dependencies:
     - nest-asyncio==1.5.1
     - notebook==6.3.0
     - numba==0.53.1
-    - numpy==1.20.3
     - oauthlib==3.1.0
     - opt-einsum==3.3.0
     - packaging==20.9
@@ -100,27 +100,27 @@ dependencies:
     - graphviz
     - python-utils==2.5.6
     - pytz==2021.1
-    - pyyaml==5.4.1
+    - pyyaml==6.0.0
     - pyzmq==22.0.3
     - qtconsole==5.0.3
     - qtpy==1.9.0
     - requests==2.25.1
     - requests-oauthlib==1.3.0
     - rsa==4.7.2
-    - scikit-learn==0.23.2
-    - scipy==1.4.1
+    - scikit-learn==1.0.2
+    - scipy==1.10.0
     - seaborn==0.11.1
     - send2trash==1.5.0
     - shap==0.37.0
     - six==1.15.0
     - slicer==0.0.3
-    - statsmodels==0.12.2
+    - statsmodels==0.13.1
     - termcolor==1.1.0
     - terminado==0.9.4
     - testpath==0.4.4
     - threadpoolctl==2.1.0
     - toml==0.10.2
-    - torch==1.8.1
+    - torch==1.9.0
     - tornado==6.1
     - tqdm==4.60.0
     - traitlets==5.0.5

pyproject.toml

@@ -32,7 +32,7 @@ dependencies = [
     "pandas>=0.24.1,<1.4.0",
     "scikit-learn<=1.0.2",
     "statsmodels>=0.9.0",
-    "Cython>=0.28.0",
+    "Cython<=0.29.34",
     "seaborn",
     "xgboost",
     "pydotplus",
@@ -61,7 +61,7 @@ tf = [
 requires = [
     "setuptools>=18.0",
     "wheel",
-    "Cython>=0.28.0",
+    "Cython<=0.29.34",
     "numpy<1.24",
     "scikit-learn<=1.0.2",
 ]

setup.py

@@ -4,7 +4,7 @@
 try:
     from Cython.Build import cythonize
 except ImportError:
-    dist.Distribution().fetch_build_eggs(["cython>=0.28.0"])
+    dist.Distribution().fetch_build_eggs(["cython<=0.29.34"])
     from Cython.Build import cythonize
 import Cython.Compiler.Options