Move matplotlib to an optional dependency (#243)

* removed matplotlib

Signed-off-by: Amit Sharma <amit_sharma@live.com>

* added new req file

Signed-off-by: Amit Sharma <amit_sharma@live.com>

.github/workflows/python-package.yml

@@ -28,6 +28,7 @@ jobs:
         python -m pip install --upgrade pip
         pip install flake8 pytest twine
         if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
+        if [ -f requirements-plotting.txt ]; then pip install -r requirements-plotting.txt; fi
         pip install causalml nbformat jupyter
         pip install econml
     - name: Lint with flake8

dowhy/causal_refuters/add_unobserved_common_cause.py

@@ -3,8 +3,6 @@ import logging
 import numpy as np
 import pandas as pd
 
-import matplotlib
-import matplotlib.pyplot as plt
 import math
 import statsmodels.api as sm
 
@@ -86,6 +84,8 @@ class AddUnobservedCommonCause(CausalRefuter):
                         self.logger.debug(refute)
                         results_matrix[i][j] = refute.estimated_effect # Populate the results
 
+                import matplotlib
+                import matplotlib.pyplot as plt
                 fig = plt.figure(figsize=(6,5))
                 left, bottom, width, height = 0.1, 0.1, 0.8, 0.8
                 ax = fig.add_axes([left, bottom, width, height])
@@ -115,6 +115,8 @@ class AddUnobservedCommonCause(CausalRefuter):
                     self.logger.debug(refute)
                     outcomes[i] = refute.estimated_effect # Populate the results
 
+                import matplotlib
+                import matplotlib.pyplot as plt
                 fig = plt.figure(figsize=(6,5))
                 left, bottom, width, height = 0.1, 0.1, 0.8, 0.8
                 ax = fig.add_axes([left, bottom, width, height])
@@ -142,6 +144,8 @@ class AddUnobservedCommonCause(CausalRefuter):
                     self.logger.debug(refute)
                     outcomes[i] = refute.estimated_effect # Populate the results
 
+                import matplotlib
+                import matplotlib.pyplot as plt
                 fig = plt.figure(figsize=(6,5))
                 left, bottom, width, height = 0.1, 0.1, 0.8, 0.8
                 ax = fig.add_axes([left, bottom, width, height])

dowhy/interpreters/confounder_distribution_interpreter.py

@@ -1,5 +1,4 @@
 import numpy as np
-import matplotlib.pyplot as plt
 
 from dowhy.interpreters.visual_interpreter import VisualInterpreter
 from dowhy.causal_estimators.propensity_score_weighting_estimator import PropensityScoreWeightingEstimator
@@ -83,6 +82,7 @@ class ConfounderDistributionInterpreter(VisualInterpreter):
         title1 = "Distribution of " + self.var_name + " before applying the weights"
         title2 = "Distribution of " + self.var_name + " after applying the weights"
 
+        import matplotlib.pyplot as plt
         fig, (ax1, ax2) = plt.subplots(1, 2, figsize=self.fig_size)
         iterable = zip([barplot_df_before, barplot_df_after], [ax1, ax2], [title1, title2])
         for plot_df, ax, title in iterable:

dowhy/interpreters/propensity_balance_interpreter.py

@@ -1,6 +1,5 @@
 import numpy as np
 import pandas as pd
-import matplotlib.pyplot as plt
 
 from dowhy.interpreters.visual_interpreter import VisualInterpreter
 from dowhy.causal_estimators.propensity_score_estimator import PropensityScoreEstimator
@@ -61,6 +60,8 @@ class PropensityBalanceInterpreter(VisualInterpreter):
         mean_diff_strata["sample"]="PropensityAdjusted"
         mean_diff_overall["sample"] = "Unadjusted"
         plot_df = pd.concat([mean_diff_overall, mean_diff_strata])
+
+        import matplotlib.pyplot as plt
         plt.style.use("seaborn-white")
         fig, ax = plt.subplots(1,1)
         for label, subdf in plot_df.groupby('common_cause_id'):

requirements-plotting.txt

@@ -0,0 +1 @@
+matplotlib

requirements.txt

@@ -3,7 +3,6 @@ scipy
 statsmodels
 pandas>=0.24
 networkx>=2.0
-matplotlib
 sympy>=1.4
 scikit-learn
 pydot>=1.4

setup.py

@@ -19,6 +19,14 @@ with open(path.join(here, 'README.rst'), encoding='utf-8') as f:
 with open(path.join(here, 'requirements.txt'), encoding='utf-8') as f:
     install_requires = f.read().splitlines()
 
+# Plotting packages are optional to install
+extras = ["plotting"]
+extras_require = dict()
+for e in extras:
+    req_file = "requirements-{0}.txt".format(e)
+    with open(req_file) as f:
+        extras_require[e] = [line.strip() for line in f]
+
 # Loading version number
 with open(path.join(here, 'dowhy', 'VERSION')) as version_file:
     version = version_file.read().strip()
@@ -45,6 +53,7 @@ setup(
     packages=find_packages(exclude=['docs', 'tests']),
     python_requires='>=3.5',
     install_requires=install_requires,
+    extras_require=extras_require,
     include_package_data=True,
     package_data={'dowhy':['VERSION']}
 )