Merge branch 'master' of github.com:oemof/feedinlib

feedinlib/powerplants.py

@@ -24,7 +24,7 @@ def __init__(self, model=models.Photovoltaic([]), **attributes):
           Defaults to an instance of :class:`feedinlib.models.Photovoltaic`
           with no requirements on the attributes needed to calculate the
           feedin.
-        \**attributes : hash
+        **attributes :
           The remaining attributes providing the technical specification of
           the powerplant. They will be added as regular attributes to this
           object, with keys as attribute names and initialized to the
@@ -60,127 +60,30 @@ def feedin_as_list(self, **kwargs):
 
     def feedin(self, **kwargs):
         r"""
-        Unless you override the default model, the following attributes are
-        required:
-
-         blablab...
+        Calculates the amount of energy fed in by this powerplant into the
+        energy system.
 
-        Should you opt to override the default model, the model parameter
-        is expected to have a property called 'required' containing a list
-        of parameters required for the model to calculate the feed.
-        Calculating the powerplants feed then calls into the model with the
-        given parameters.
+        This method delegates the actual computation to the :meth:`feedin`
+        method of this objects :attr:`model` while giving you the opportunity
+        to override some of the inputs used to calculate the feedin.
 
         Parameters
         ----------
-        var1 : array_like
-            Array_like means all those objects -- lists, nested lists, etc. --
-            that can be converted to an array.  We can also refer to
-            variables like `var1`.
-        var2 : int
-            The type above can either refer to an actual Python type
-            (e.g. ``int``), or describe the type of the variable in more
-            detail, e.g. ``(N,) ndarray`` or ``array_like``.
-        Long_variable_name : {'hi', 'ho'}, optional
-            Choices in brackets, default first when optional.
-        main_dt : dictionary
-            Main dictionary as described below [41]_
-        prob : pulp.lp-problem
-            LP-Problem-Variable, which contains the linear problem [42]_
+        **kwargs :
+          Keyword arguments. If not specified, all the paramters needed to
+          calculate the feedin are taken from this object. If any keyword
+          argument is present whose key matches one of the parameters needed
+          to calculate the feedin, it takes precedence over a matching
+          attribute of this object.
 
         Returns
         -------
-        type
-            Explanation of anonymous return value of type ``type``.
-        describe : type
-            Explanation of return value named `describe`.
-        out : type
-            Explanation of `out`.
-
-        Other Parameters
-        ----------------
-        only_seldom_used_keywords : type
-            Explanation
-        common_parameters_listed_above : type
-            Explanation
-        Timesteps [t] : main_dt['timesteps']
-            np-array with the timesteps according to the timeseries
-        Regions [r] : main_dt['energy_system']['regions']
-            See: solph.extenddc [4]_
-        Electric demand : main_dt['timeseries']['demand'][r]['lele'][t]
-            r = region, t = timesteps
-        main_dt['energy_system'] : dict-branch with lists of components
-            Definition of the 'energy_system' see: :py:mod:`solph.extenddc`
-        main_dt['lp'] : dict-branch with all lp-variables
-            Definition of lp-variables see: :py:mod:`solph.lp_definition`
-
-        Raises
-        ------
-        BadException
-            Because you shouldn't have done that.
-
-        See Also
-        --------
-        otherfunc : relationship (optional)
-        newfunc : Relationship (optional), which could be fairly long, in which
-                  case the line wraps here.
-        thirdfunc, fourthfunc, fifthfunc
-        solph.main_model.create_model_equations : Blubber
-
-        Notes
-        -----
-        Notes about the implementation algorithm (if needed).
-
-        This can have multiple paragraphs.
-
-        You may include some math:
-
-        .. math:: X(e^{j\omega } ) = x(n)e^{ - j\omega n}
+        feedin : Pandas dataframe
+          The feedin provided by this poweplant as a time series represented
+          by a :py:class:`pandas.DataFrame`.
 
-        And even use a greek symbol like :math:`omega` inline.
-
-        References
-        ----------
-        Cite the relevant literature, e.g. [43]_.  You may also cite these
-        references in the notes section above.
-
-        .. [41] Link to the description of the main_dt for solph.
-        .. [42] `PuLP <https://code.google.com/p/pulp-or/>`_, PuLP Docu.
-        .. [43] O. McNoleg, "The integration of GIS, remote sensing,
-           expert systems and adaptive co-kriging for environmental habitat
-           modelling of the Highland Haggis using object-oriented, fuzzy-logic
-           and neural-network techniques," Computers & Geosciences, vol. 22,
-           pp. 585-588, 1996.
-
-        Examples
-        --------
-        These are written in doctest format, and should illustrate how to
-        use the function.
-
-        >>> a=[1,2,3]
-        >>> print([x + 3 for x in a])
-        [4, 5, 6]
-        >>> print("a\nb")
-        a
-        b
-
-        .. code:: python
-
-            #!/usr/bin/python
-            # -*- coding: utf-8
-
-
-            def pg_db():
-                local_dict = {
-                    'ip': 'localhost_or_ip',
-                    'port': '5432',
-                    'db': 'name_of_db',
-                    'user': 'username',
-                    'password': 'password'}
-                return local_dict
         """
-        # TODO: add docstring documenting the attribute overriding behaviour
-        #    of this function.
+        # TODO: Document semantics of special keyword arguments.
         combined = {k: getattr(self, k) for k in self.model.required}
         combined.update(kwargs)
         if kwargs.get('number', None) is not None: