docs cleanup

casact · Jan 19, 2021 · 0cb42c0 · 0cb42c0
1 parent eb98278
commit 0cb42c0
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Showing 20 changed files with 376 additions and 131 deletions.
diff --git a/chainladder/core/pandas.py b/chainladder/core/pandas.py
@@ -230,7 +230,7 @@ def tail(self, n=5):
         return self.iloc[-n:]
 
     def sort_index(self, *args, **kwargs):
-        return self.iloc[self.index.sort_values(self.key_labels).index]
+        return self.iloc[self.index.sort_values(self.key_labels, *args, **kwargs).index]
 
     def exp(self):
         xp = self.get_array_module()

diff --git a/chainladder/core/triangle.py b/chainladder/core/triangle.py
@@ -42,8 +42,8 @@ class Triangle(TriangleBase):
         omitted then date format will be inferred by pandas.
     cumulative : bool
         Whether the triangle is cumulative or incremental.  This attribute is
-        required to use the `grain` and `dev_to_val` methods and will be
-        automatically set when invoking `cum_to_incr` or `incr_to_cum` methods.
+        required to use the ``grain`` and ``dev_to_val`` methods and will be
+        automatically set when invoking ``cum_to_incr`` or ``incr_to_cum`` methods.
 
     Attributes
     ----------
@@ -56,16 +56,17 @@ class Triangle(TriangleBase):
     development : Series
         Represents all available levels of the development dimension.
     key_labels : list
-        Represents the `index` axis labels
+        Represents the ``index`` axis labels
+    virtual_columns : Series
+        Represents the subset of columns of the triangle that are virtual.
     valuation : DatetimeIndex
         Represents all valuation dates of each cell in the Triangle.
     origin_grain : str
         The grain of the origin vector ('Y', 'Q', 'M')
     development_grain : str
         The grain of the development vector ('Y', 'Q', 'M')
     shape : tuple
-        The 4D shape of the triangle instance with axes corresponding to (index,
-         columns, origin, development)
+        The 4D shape of the triangle instance with axes corresponding to (index, columns, origin, development)
     link_ratio, age_to_age
         Displays age-to-age ratios for the triangle.
     valuation_date : date
@@ -318,7 +319,9 @@ def dev_to_val(self, inplace=False):
 
         Returns
         -------
-            Updated instance of triangle with valuation periods.
+        Triangle
+            Updated instance of the triangle with valuation periods.
+
         """
         if self.is_val_tri:
             if inplace:

diff --git a/chainladder/tails/bondy.py b/chainladder/tails/bondy.py
@@ -21,7 +21,7 @@ class TailBondy(TailBase):
         age can be used.
     attachment_age: int (default=None)
         The age at which to attach the fitted curve.  If None, then the latest
-        age is used. Measures of variability from original `ldf_` are retained
+        age is used. Measures of variability from original ``ldf_`` are retained
         when being used in conjunction with the MackChainladder method.
 
     Attributes
@@ -41,7 +41,7 @@ class TailBondy(TailBase):
     std_err_ : Triangle
         std_err with tail factor applied
     earliest_ldf_ : DataFrame
-        Based on the `earliest_age` selection, this shows the seed `ldf_` used
+        Based on the ``earliest_age`` selection, this shows the seed ``ldf_`` used
         in fitting the Bondy exponent.
 
     See also

diff --git a/chainladder/tails/clark.py b/chainladder/tails/clark.py
@@ -17,7 +17,7 @@ class TailClark(TailBase):
         Options are 'loglogistic' and 'weibull'
     attachment_age: int (default=None)
         The age at which to attach the fitted curve.  If None, then the latest
-        age is used. Measures of variability from original `ldf_` are retained
+        age is used. Measures of variability from original ``ldf_`` are retained
         when being used in conjunction with the MackChainladder method.
 
     Attributes
@@ -33,7 +33,7 @@ class TailClark(TailBase):
     omega_ : DataFrame
         Estimates of the omega parameter of the growth curve.
     elr_ : DataFrame
-        The Expected Loss Ratio parameter. This only exists when a `sample_weight`
+        The Expected Loss Ratio parameter. This only exists when a ``sample_weight``
         is provided to the Estimator.
     scale_ : DataFrame
         The scale parameter of the model.

diff --git a/chainladder/tails/constant.py b/chainladder/tails/constant.py
@@ -18,7 +18,7 @@ class TailConstant(TailBase):
         of each successive LDF to 50% of the previous LDF.
     attachment_age: int (default=None)
         The age at which to attach the fitted curve.  If None, then the latest
-        age is used. Measures of variability from original `ldf_` are retained
+        age is used. Measures of variability from original ``ldf_`` are retained
         when being used in conjunction with the MackChainladder method.
 
     Attributes

diff --git a/chainladder/tails/curve.py b/chainladder/tails/curve.py
@@ -28,7 +28,7 @@ class TailCurve(TailBase):
         in either the ``exponential`` or ``inverse_power`` fits.
     attachment_age: int (default=None)
         The age at which to attach the fitted curve.  If None, then the latest
-        age is used. Measures of variability from original `ldf_` are retained
+        age is used. Measures of variability from original ``ldf_`` are retained
         when being used in conjunction with the MackChainladder method.
 
     Attributes

diff --git a/docs/conf.py b/docs/conf.py
@@ -42,9 +42,8 @@
 
 extensions = ['sphinx.ext.autodoc', 'numpydoc', 'sphinx_gallery.gen_gallery',
               'sphinx.ext.githubpages', 'nbsphinx', 'sphinx.ext.mathjax',
-              'sphinx.ext.autosummary', 'sphinx_gallery.load_style']
-
-numpydoc_class_members_toctree = False
+              'sphinx.ext.autosummary', 'sphinx_gallery.load_style',
+              'IPython.sphinxext.ipython_console_highlighting']
 
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ['_templates']
@@ -146,7 +145,7 @@
 # Add any paths that contain custom static files (such as style sheets) here,
 # relative to this directory. They are copied after the builtin static files,
 # so a file named "default.css" will overwrite the builtin "default.css".
-html_static_path = ['images']
+html_static_path = ['_static/images']
 
 # -- Options for HTMLHelp output ------------------------------------------
 # If false, no module index is generated.
@@ -239,8 +238,8 @@ def make_carousel_thumbs(app, exception):
 
 def setup(app):
     # to hide/show the prompt in code examples:
-    app.add_javascript('js/copybutton.js')
-    app.add_javascript('js/extra.js')
+    app.add_js_file('js/copybutton.js')
+    app.add_js_file('js/extra.js')
     app.connect('build-finished', make_carousel_thumbs)
 
 

diff --git a/docs/install.rst b/docs/install.rst
diff --git a/docs/modules/classes.rst b/docs/modules/classes.rst
@@ -25,7 +25,7 @@ Classes
 
 .. autosummary::
   :toctree: generated/
-  :template: class.rst
+  :template: class_inherited.rst
 
   Triangle
   DevelopmentCorrelation
@@ -155,3 +155,19 @@ Classes
    Tabs
    CSpacer
    RSpacer
+
+Functions
+---------
+.. currentmodule:: chainladder
+
+.. autosummary::
+   :toctree: generated/
+   :template: function.rst
+
+   load_sample
+   read_pickle
+   read_json
+   concat
+   load_sample
+   minimum
+   maximum
diff --git a/docs/modules/index.rst b/docs/modules/index.rst
@@ -0,0 +1,81 @@
+..
+    File to ..include in a document with a very big table of content, to
+    give it 'style'
+
+.. raw:: html
+
+  <style type="text/css">
+    div.bodywrapper blockquote {
+        margin: 0 ;
+    }
+
+    div.toctree-wrapper ul {
+	margin: 0 ;
+	padding-left: 0px ;
+    }
+
+    li.toctree-l1 {
+        padding: 0 ;
+        list-style-type: none;
+        font-size: 150% ;
+	font-family: Arial, sans-serif;
+	background-color: #BED4EB;
+	font-weight: normal;
+	color: #212224;
+	margin-left : 0;
+	font-weight: bold;
+        }
+
+    li.toctree-l1 a {
+        padding: 0 0 0 10px ;
+    }
+
+    li.toctree-l2 {
+        padding: 0.25em 0 0.25em 0 ;
+        list-style-type: none;
+	background-color: #FFFFFF;
+        font-size: 90% ;
+	font-weight: bold;
+        }
+
+    li.toctree-l2 ul {
+	padding-left: 40px ;
+    }
+
+    li.toctree-l3 {
+        font-size: 70% ;
+        list-style-type: none;
+	font-weight: normal;
+        }
+
+    li.toctree-l4 {
+        font-size: 85% ;
+        list-style-type: none;
+	font-weight: normal;
+        }
+
+  </style>
+
+
+
+:parenttoc: True
+
+.. title:: User guide: contents
+
+.. _user_guide:
+
+=======================
+Chainladder User guide
+=======================
+
+
+.. toctree::
+   :numbered:
+   :maxdepth: 2
+
+   triangle
+   development
+   tails
+   methods
+   workflow
+   utilities
diff --git a/docs/modules/methods.rst b/docs/modules/methods.rst
@@ -8,8 +8,8 @@ Common Properties
 =================
 All IBNR estimators have ``ibnr_``, ``ultimate_``, ``full_triangle_`` and
 ``full_expectation_`` attributes.  In addition, they carry over the transformed
-triangle as `X_` along with all of its properties.  Finally, the following
-estimators implement the `predict` method which allows them to be used on
+triangle as ``X_`` along with all of its properties.  Finally, the following
+estimators implement the ``predict`` method which allows them to be used on
 different Triangles.
 
 .. _chainladder:
@@ -58,7 +58,7 @@ Mack Chainladder
 The :class:`MackChainladder` model can be regarded as a special form of a
 weighted linear regression through the origin for each development period. By using
 a regression framework, statistics about the variability of the data and the parameter
-estimates allows for the estimation of prediciton errors.  The Mack Chainladder
+estimates allows for the estimation of prediction errors. The Mack Chainladder
 method is the most basic of stochastic methods.
 
 
@@ -130,8 +130,8 @@ The generalized formula is:
 .. math::
    \sum_{k=0}^{n-1}(1-\frac{1}{CDF}) + Apriori\times (1-\frac{1}{CDF})^{n}
 
-`n=0` yields the expected loss method, `n=1` yields the traditional BF method,
-and finally when `n` is sufficiently large, the method converges to the
+``n=0`` yields the expected loss method, ``n=1`` yields the traditional BF method,
+and finally when ``n`` is sufficiently large, the method converges to the
 traditional CL method.
 
 .. figure:: /auto_examples/images/sphx_glr_plot_benktander_001.png

diff --git a/docs/modules/tails.rst b/docs/modules/tails.rst
@@ -86,10 +86,10 @@ are supported.
 
 In general, ``inverse_power`` fit produce more conservative tail estimates than
 the ``exponential`` fit.  Both are fit using basic OLS regression on transformed
-`X` and `y` values.
+``X`` and ``y`` values.
 
 For exponential curve fitting, we use fit a regression to the natural log of
-the development portion of a link-ratio, `f`.
+the development portion of a link-ratio, ``f``.
 
 
 Extrapolation Period
@@ -106,22 +106,22 @@ asymptotic value.
 
 Regression parameters
 ----------------------
-Underlying the curve fit is an OLS regression which generates both a `slope_`
-and `intercept_` term.
+Underlying the curve fit is an OLS regression which generates both a ``slope_``
+and ``intercept_`` term.
 
-For the `exponential` curve fit with slope, b and intercept a, the tail factor
+For the ``exponential`` curve fit with slope, b and intercept a, the tail factor
 is:
 
 .. math::
    \prod_{i}^{N}1+exp(\beta X+\alpha )
 
-For the `inverse_power` curve, the tail factor is:
+For the ``inverse_power`` curve, the tail factor is:
 
 .. math::
    \prod_{i}^{N}1+exp(\alpha) X^{\beta}
 
 
-Deriving the `tail_` factor manually:
+Deriving the ``tail_`` factor manually:
 
   >>> import chainladder as cl
   >>> import numpy as np