Merge pull request #91 from Quantmetry/chp_fix_docstrings

Chp fix docstrings

Author: JulienRoussel77

.github/workflows/test.yml

@@ -35,8 +35,6 @@ jobs:
         run: |
           conda install pytest
           make coverage
-      - name: Test docstrings examples
-        run: make doctest
       - name: typing with mypy
         run: |
           mypy qolmat

Makefile

@@ -4,6 +4,10 @@ coverage:
 doctest:
 	pytest --doctest-modules --pyargs qolmat
 
+doc:
+	make html -C docs
+
 clean:
 	rm -rf .mypy_cache .pytest_cache .coverage*
 	rm -rf **__pycache__
+	make clean -C docs

qolmat/imputations/em_sampler.py

@@ -664,14 +664,19 @@ class VARpEM(EM):
     Examples
     --------
     >>> import numpy as np
-    >>> import pandas as pd
     >>> from qolmat.imputations.em_sampler import VARpEM
-    >>> imputer = VARpEM(method="sample")
-    >>> X = pd.DataFrame(data=[[1, 1, 1, 1],
-    ...                        [np.nan, np.nan, 3, 2],
-    ...                        [1, 2, 2, 1], [2, 2, 2, 2]],
-    ...                        columns=["var1", "var2", "var3", "var4"])
-    >>> imputer.fit_transform(X) # doctest: +SKIP
+    >>> imputer = VARpEM(method="sample", random_state=11)
+    >>> X = np.array([[1, 1, 1, 1],
+    ...               [np.nan, np.nan, 3, 2],
+    ...               [1, 2, 2, 1], [2, 2, 2, 2]])
+    >>> imputer.fit_transform(X)
+    EM converged after 9 iterations.
+    EM converged after 20 iterations.
+    EM converged after 13 iterations.
+    array([[1.        , 1.        , 1.        , 1.        ],
+           [1.17054054, 1.49986137, 3.        , 2.        ],
+           [1.        , 2.        , 2.        , 1.        ],
+           [2.        , 2.        , 2.        , 2.        ]])
     """
 
     def __init__(

qolmat/imputations/imputers.py

@@ -1114,10 +1114,10 @@ class ImputerResiduals(_Imputer):
 
     Examples
     --------
-    TODO review/remake this exemple
     >>> import numpy as np
     >>> import pandas as pd
     >>> from qolmat.imputations.imputers import ImputerResiduals
+    >>> np.random.seed(100)
     >>> df = pd.DataFrame(index=pd.date_range('2015-01-01','2020-01-01'))
     >>> mean = 5
     >>> offset = 10
@@ -1127,11 +1127,24 @@ class ImputerResiduals(_Imputer):
     >>> noise_mean = 0
     >>> noise_var = 2
     >>> df['y'] = df['y'] + np.random.normal(noise_mean, noise_var, df.shape[0])
-    >>> np.random.seed(100)
     >>> mask = np.random.choice([True, False], size=df.shape)
     >>> df = df.mask(mask)
-    >>> imputor.fit_transform(df)  # doctest: +SKIP
     >>> imputor = ImputerResiduals(period=365, model_tsa="additive")
+    >>> imputor.fit_transform(df)
+                        y
+    2015-01-01   1.501210
+    2015-01-02   5.691061
+    2015-01-03   4.404106
+    2015-01-04   3.531540
+    2015-01-05   3.129532
+    ...               ...
+    2019-12-28  10.288054
+    2019-12-29  10.632659
+    2019-12-30  14.900671
+    2019-12-31  12.957837
+    2020-01-01  12.780517
+    <BLANKLINE>
+    [1827 rows x 1 columns]
     """
 
     def __init__(

qolmat/imputations/softimpute.py

@@ -46,12 +46,12 @@ class SoftImpute(BaseEstimator, TransformerMixin):
     >>> import numpy as np
     >>> from qolmat.imputations.softimpute import SoftImpute
     >>> X = np.array([[1, 2, np.nan, 4], [1, 5, 3, np.nan], [4, 2, 3, 2], [1, 1, 5, 4]])
-    >>> X_imputed = SoftImpute().fit_transform(X)
+    >>> X_imputed = SoftImpute(random_state=11).fit_transform(X)
     >>> print(X_imputed)
-    [[ 1.          2.          4.7369014   4.        ]
-     [ 1.          5.          3.         -0.52477073]
-     [ 4.          2.          3.          2.        ]
-     [ 1.          1.          5.          4.        ]]
+    [[1.         2.         3.7242757  4.        ]
+     [1.         5.         3.         1.97846028]
+     [4.         2.         3.         2.        ]
+     [1.         1.         5.         4.        ]]
     """
 
     def __init__(