Docs: cleanup doc; Sphinx bugfixes (wrong refs)

GeoStat-Framework · Feb 1, 2021 · 9092ef9 · 9092ef9
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Showing 9 changed files with 20 additions and 30 deletions.
diff --git a/docs/source/field.base.rst b/docs/source/field.base.rst
diff --git a/docs/source/field.rst b/docs/source/field.rst
@@ -2,10 +2,6 @@ gstools.field
 =============
 
 .. automodule:: gstools.field
-   :members:
-   :undoc-members:
-   :inherited-members:
-   :show-inheritance:
 
 .. raw:: latex
 
@@ -16,4 +12,3 @@ gstools.field
 
    field.generator.rst
    field.upscaling.rst
-   field.base.rst
diff --git a/docs/source/variogram.rst b/docs/source/variogram.rst
@@ -2,8 +2,6 @@ gstools.variogram
 =================
 
 .. automodule:: gstools.variogram
-   :members:
-   :undoc-members:
 
 .. raw:: latex
 

diff --git a/gstools/field/__init__.py b/gstools/field/__init__.py
@@ -10,19 +10,22 @@
 .. autosummary::
     generator
     upscaling
-    base
 
 Spatial Random Field
 ^^^^^^^^^^^^^^^^^^^^
 
 .. autosummary::
+   :toctree: generated
+
    SRF
    CondSRF
 
 Field Base Class
 ^^^^^^^^^^^^^^^^
 
 .. autosummary::
+   :toctree: generated
+
    Field
 
 ----

diff --git a/gstools/field/cond_srf.py b/gstools/field/cond_srf.py
@@ -29,8 +29,8 @@ class CondSRF(Field):
 
     Parameters
     ----------
-    model : :any:`CovModel`
-        Covariance Model of the spatial random field.
+    krige : :any:`Krige`
+        Kriging setup to condition the spatial random field.
     generator : :class:`str`, optional
         Name of the field generator to be used.
         At the moment, only the following generator is provided:
@@ -116,7 +116,7 @@ def get_scaling(self, krige_var, shape):
         -------
         var_scale : :class:`numpy.ndarray`
             Variance scaling factor for the random field.
-        nugget : :class:`numpy.ndarray` or `class:`int
+        nugget : :class:`numpy.ndarray` or :class:`int`
             Nugget to be added to the field.
         """
         if self.model.nugget > 0:

diff --git a/gstools/field/generator.py b/gstools/field/generator.py
@@ -41,7 +41,7 @@ class RandMeth:
     verbose : :class:`bool`, optional
         Be chatty during the generation.
         Default: :any:`False`
-    sampling :class:`str`, optional
+    sampling : :class:`str`, optional
         Sampling strategy. Either
 
             * "auto": select best strategy depending on given model
@@ -331,7 +331,7 @@ class IncomprRandMeth(RandMeth):
     verbose : :class:`bool`, optional
         State if there should be output during the generation.
         Default: :any:`False`
-    sampling :class:`str`, optional
+    sampling : :class:`str`, optional
         Sampling strategy. Either
 
             * "auto": select best strategy depending on given model

diff --git a/gstools/krige/base.py b/gstools/krige/base.py
@@ -105,7 +105,7 @@ class Krige(Field):
         Wheater to fit the given variogram model to the data.
         This is done by using isotropy settings of the given model,
         assuming the sill to be the data variance and with the
-        standard bins provided by the :any:`variogram` submodule.
+        standard bins provided by the :any:`standard_bins` routine.
         Default: False
 
     Notes
@@ -467,7 +467,7 @@ def set_condition(
             Wheater to fit the given variogram model to the data.
             This is done by using isotropy settings of the given model,
             assuming the sill to be the data variance and with the
-            standard bins provided by the :any:`variogram` submodule.
+            standard bins provided by the :any:`standard_bins` routine.
             Default: False
 
         Notes

diff --git a/gstools/krige/methods.py b/gstools/krige/methods.py
@@ -81,7 +81,7 @@ class Simple(Krige):
         Wheater to fit the given variogram model to the data.
         This is done by using isotropy settings of the given model,
         assuming the sill to be the data variance and with the
-        standard bins provided by the :any:`variogram` submodule.
+        standard bins provided by the :any:`standard_bins` routine.
         Default: False
     """
 
@@ -176,7 +176,7 @@ class Ordinary(Krige):
         Wheater to fit the given variogram model to the data.
         This is done by using isotropy settings of the given model,
         assuming the sill to be the data variance and with the
-        standard bins provided by the :any:`variogram` submodule.
+        standard bins provided by the :any:`standard_bins` routine.
         Default: False
     """
 
@@ -281,7 +281,7 @@ class Universal(Krige):
         Wheater to fit the given variogram model to the data.
         This is done by using isotropy settings of the given model,
         assuming the sill to be the data variance and with the
-        standard bins provided by the :any:`variogram` submodule.
+        standard bins provided by the :any:`standard_bins` routine.
         Default: False
     """
 
@@ -383,7 +383,7 @@ class ExtDrift(Krige):
         Wheater to fit the given variogram model to the data.
         This is done by using isotropy settings of the given model,
         assuming the sill to be the data variance and with the
-        standard bins provided by the :any:`variogram` submodule.
+        standard bins provided by the :any:`standard_bins` routine.
         Default: False
     """
 
@@ -475,7 +475,7 @@ class Detrended(Krige):
         Wheater to fit the given variogram model to the data.
         This is done by using isotropy settings of the given model,
         assuming the sill to be the data variance and with the
-        standard bins provided by the :any:`variogram` submodule.
+        standard bins provided by the :any:`standard_bins` routine.
         Default: False
     """
 

diff --git a/gstools/variogram/__init__.py b/gstools/variogram/__init__.py
@@ -8,13 +8,17 @@
 ^^^^^^^^^^^^^^^^^^^^
 
 .. autosummary::
+   :toctree: generated
+
    vario_estimate
    vario_estimate_axis
 
 Binning
 ^^^^^^^
 
 .. autosummary::
+   :toctree: generated
+
    standard_bins
 
 ----