Fix documentation and update pandas.

Author: MaxBlesch

.readthedocs.yml

@@ -7,5 +7,5 @@ python:
   version: 3.7
 
 conda:
-  environment: docs/environment.yml
+  environment: environment.yml
 

docs/environment.yml

@@ -13,6 +13,7 @@
 import sys
 
 sys.path.insert(0, os.path.abspath("../.."))
+print(sys.path)
 
 # -- Project information -----------------------------------------------------
 
@@ -50,11 +51,10 @@
     "sphinx.ext.mathjax",
     "sphinx.ext.todo",
     "sphinx.ext.viewcode",
-    "nbsphinx",
     "numpydoc",
 ]
 
-napoleon_google_docstring = True
+
 napoleon_numpy_docstring = True
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ["_templates"]

docs/source/conf.py

@@ -311,5 +311,4 @@ In the promotion folder of the repository are two demonstration jupyter notebook
 `replication
 <https://github.com/OpenSourceEconomics/ruspy/blob/kantevorich/promotion/replication/replication.ipynb>`_
 notebook allows to easily experiment with the estimation methods described here. If you
-have have everything setup, then it should be easy to run it. If not, there is soon
-coming a mybinder link and you should keep your eyes open!
+have have everything setup, then it should be easy to run it.

docs/source/estimation.rst

@@ -84,5 +84,4 @@ Demonstration
 
 In the promotion folder of the repository are two demonstration jupyter notebooks. The
 `simulation <https://github.com/OpenSourceEconomics/ruspy/blob/kantevorich/promotion/simulation/simulation_convergence.ipynb>`_ notebook allows to easily experiment with the estimation methods described
-here. If you have have everything setup, then it should be easy to run it. If not there
-is soon coming a mybinder link and you should keep your `eyes open <https://gph.is/2rY1Er1>`_ !
+here. If you have have everything setup, then it should be easy to run it.

docs/source/simulation.rst

@@ -4,13 +4,14 @@ dependencies:
   - python
   - numpy
   - sphinx
-  - pandas=0.25.3
+  - pandas=1.0.0
   - statsmodels
   - pytest
   - pytest-xdist
   - scipy
   - matplotlib
   - pytest-cov
+  - numpydoc
   - jupyter
   - numba
   - mpmath

environment.yml

@@ -40,8 +40,8 @@ def estimate(init_dict, df):
 
     transition_results = estimate_transitions(df)
 
-    endog = df.loc[(slice(None), slice(1, None)), "decision"].to_numpy()
-    states = df.loc[(slice(None), slice(1, None)), "state"].to_numpy()
+    endog = df.loc[(slice(None), slice(1, None)), "decision"].to_numpy(int)
+    states = df.loc[(slice(None), slice(1, None)), "state"].to_numpy(int)
 
     (
         disc_fac,

promotion/replication/group_4.pkl

@@ -41,8 +41,8 @@ def inputs():
     out["params_est"] = result_fixp["x"]
     out["trans_ll"] = result_trans["fun"]
     out["cost_ll"] = result_fixp["fun"]
-    out["states"] = df.loc[:, "state"].to_numpy()
-    out["decisions"] = df.loc[:, "decision"].to_numpy()
+    out["states"] = df.loc[:, "state"].to_numpy(int)
+    out["decisions"] = df.loc[:, "decision"].to_numpy(int)
     out["disc_fac"] = disc_fac
     out["num_states"] = num_states
     out["scale"] = scale

ruspy/estimation/estimation.py

@@ -41,8 +41,8 @@ def inputs():
     out["params_est"] = result_fixp["x"]
     out["trans_ll"] = result_trans["fun"]
     out["cost_ll"] = result_fixp["fun"]
-    out["states"] = df.loc[(slice(None), slice(1, None)), "state"].to_numpy()
-    out["decisions"] = df.loc[(slice(None), slice(1, None)), "decision"].to_numpy()
+    out["states"] = df.loc[(slice(None), slice(1, None)), "state"].to_numpy(int)
+    out["decisions"] = df.loc[(slice(None), slice(1, None)), "decision"].to_numpy(int)
     out["disc_fac"] = disc_fac
     out["num_states"] = num_states
     out["scale"] = scale