Merge db5becb into 84dd102

docs/api_structure.rst

@@ -10,7 +10,7 @@ Fitting 101
 Fitting a model to data is, at it's most basic, a parameter optimisation, and
 depending on whether you do a least-squares fit or a loglikelihood fit your
 objective function changes. This means we can split the process of fitting in
-three distint, isolated parts:: the :class:`~symfit.core.fit.Model`, the
+three distint, isolated parts:: the :class:`~symfit.core.models.Model`, the
 Objective and the Minimizer. 
 
 In practice, :class:`~symfit.core.fit.Fit` will choose an appropriate objective

docs/examples/ex_CallableNumericalModel.rst

@@ -2,7 +2,7 @@ Example: CallableNumericalModel
 ===============================
 
 Below is an example of how to use the
-:class:`symfit.core.fit.CallableNumericalModel`. This class allows you to
+:class:`symfit.core.models.CallableNumericalModel`. This class allows you to
 provide custom callables as your model, while still allowing clean interfacing
 with the :mod:`symfit` API.
 

docs/examples/ex_ODEModel.rst

@@ -1,8 +1,8 @@
 Example: ODEModel for Reaction Kinetics
 =======================================
 
-Below is an example of how to use the :class:`symfit.core.fit.ODEModel`. In this
-example we will fit reaction kinetics data, taken from libretexts_.
+Below is an example of how to use the :class:`symfit.core.models.ODEModel`. In
+this example we will fit reaction kinetics data, taken from libretexts_.
 
 The data is from a first-order reaction :math:`\text{A} \rightarrow \text{B}`.
 

docs/fitting_types.rst

@@ -228,7 +228,7 @@ this::
     fit = Fit(ode_model, t=tdata, a=adata, b=None)
     fit_result = fit.execute()
 
-That's it! An :class:`~symfit.core.fit.ODEModel` behaves just like any other
+That's it! An :class:`~symfit.core.models.ODEModel` behaves just like any other
 model object, so :class:`~symfit.core.fit.Fit` knows how to deal with it! Note
 that since we don't know the concentration of B, we explicitly set ``b=None``
 when calling :class:`~symfit.core.fit.Fit` so it will be ignored.

docs/module_docs.rst

@@ -14,6 +14,15 @@ Fit
    :exclude-members: __weakref__
    :show-inheritance:
 
+Models
+------
+
+.. automodule:: symfit.core.models
+   :members:
+   :special-members:
+   :exclude-members: __weakref__
+   :show-inheritance:
+
 Argument
 --------
 

docs/tutorial.rst

@@ -143,7 +143,7 @@ One thing to note about such models is that now ``model(x=xdata)`` obviously no
 longer works as ``type(model) == dict``. There is a preferred way to resolve
 this. If any kind of fitting object has been initiated, it will have a
 `.model` atribute containing an instance of
-:class:`~symfit.core.fit.Model`. This can again be called::
+:class:`~symfit.core.models.Model`. This can again be called::
 
     a, b = parameters('a, b')
     y_1, y_2, x = variables('y_1, y_2, x')
@@ -161,7 +161,7 @@ returned :func:`~collections.namedtuple`. Alternatively, the unpacking can be
 performed explicitly.
 
 If for some reason no :class:`~symfit.core.fit.Fit` is initiated you can make a
-:class:`~symfit.core.fit.Model` object yourself::
+:class:`~symfit.core.models.Model` object yourself::
 
     model = Model(model_dict)
     y_1_result, y_2_result = model(x=xdata, a=2.4, b=0.1)

symfit/api.py

@@ -2,9 +2,10 @@
 import symfit.core.operators
 
 # Expose useful objects.
-from symfit.core.fit import (
-    Fit, Model, ODEModel, ModelError, CallableModel,
-    CallableNumericalModel, GradientModel
+from symfit.core.fit import Fit
+from symfit.core.models import (
+    Model, ODEModel, ModelError, CallableModel, CallableNumericalModel,
+    GradientModel
 )
 from symfit.core.fit_results import FitResults
 from symfit.core.argument import Variable, Parameter