finished the docs and updated conf.py

ronikobrosly · Apr 21, 2020 · 969bbbd · 969bbbd
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diff --git a/README.md b/README.md
@@ -11,13 +11,11 @@ Python tools to perform causal inference using observational data when the treat
 
 
 
-
 ## Table of Contents
 
 - [Overview](#overview)
-- [Documentation](#documentation)
 - [Installation](#installation)
-- [Usage](#usage)
+- [Documentation](#documentation)
 - [Contributing](#contributing)
 - [References](#references)
 
@@ -36,17 +34,13 @@ For example, when you would like to:
 
 This library attempts to address this gap, providing tools to estimate causal curves (AKA causal dose-response curves).
 
-## Documentation
-
-TBC
-
 ## Installation
 
-TBC
+`pip install causal-curve`
 
-## Usage
+## Documentation
 
-TBC
+[Documentation is available at readthedocs.org](causal-curve.readthedocs.io)
 
 ## Contributing
 

diff --git a/docs/CDRC_example.rst b/docs/CDRC_example.rst
@@ -70,6 +70,7 @@ The following code completes the data generation:
 With this dataframe, we can now calculate the GPS to estimate the causal relationship between
 treatment and outcome. Let's use the default settings of the CDRC tool:
 
+>>> from causal_curve import CDRC
 >>> cdrc = CDRC()
 >>> cdrc.fit(T = df['Treatment'], X = df[['X_1', 'X_2']], y = df['Outcome'])
 >>> cdrc_results = cdrc.calculate_CDRC(0.95)

diff --git a/docs/changelog.rst b/docs/changelog.rst
@@ -4,7 +4,7 @@
 Change Log
 ==========
 
-Version 0.0.1
+Version 0.0.7
 -------------
 
 - Project created
diff --git a/docs/conf.py b/docs/conf.py
@@ -22,7 +22,7 @@
 author = 'Roni Kobrosly'
 
 # The full version, including alpha/beta/rc tags
-release = '0.0.1'
+release = '0.0.7'
 
 
 # -- General configuration ---------------------------------------------------

diff --git a/docs/index.rst b/docs/index.rst
@@ -74,7 +74,7 @@ Quick example (of the ``CDRC`` tool)
 
 **causal-curve** uses a sklearn-like API that should feel familiar to python machine learning users.
 
->>> from causal_curve.cdrc import CDRC
+>>> from causal_curve import CDRC
 
 >>> cdrc = CDRC(treatment_grid_num = 200, random_seed = 512)
 

diff --git a/docs/install.rst b/docs/install.rst
@@ -9,12 +9,21 @@ Dependencies
 
 causal-curve requires:
 
-- Python (>= 3.7.6)
-- NumPy (>= 1.18.2)
-- Pandas (>= 1.0.3)
-- pyGAM (>= 0.8.0)
-- SciPy (>= 1.4.1)
-- Statsmodels (>= 0.11.1)
+- future
+- joblib
+- numpy
+- pandas
+- patsy
+- progressbar2
+- pygam
+- python-dateutil
+- python-utils
+- pytz
+- scikit-learn
+- scipy
+- six
+- statsmodels
+
 
 
 User installation

diff --git a/docs/requirements.txt b/docs/requirements.txt
@@ -0,0 +1,15 @@
+future
+joblib
+numpy
+numpydoc
+pandas
+patsy
+progressbar2
+pygam
+python-dateutil
+python-utils
+pytz
+scikit-learn
+scipy
+six
+statsmodels
diff --git a/requirements.txt b/requirements.txt
@@ -1,6 +1,7 @@
 future
 joblib
 numpy
+numpydoc
 pandas
 patsy
 progressbar2

diff --git a/setup.py b/setup.py
@@ -5,7 +5,7 @@
 
 setuptools.setup(
     name="causal-curve",
-    version="0.0.5",
+    version="0.0.7",
     author="Roni Kobrosly",
     author_email="[email protected]",
     description="A python library with tools to perform causal inference using \