remove _layer suffix from within files

doc/source/api_reference/abstraction_layer.rst

@@ -2,7 +2,7 @@
 Abstraction layer API
 =====================
 
-.. currentmodule:: nineml.abstraction_layer
+.. currentmodule:: nineml.abstraction
 
 The abstraction layer is intended to provide explicit mathematical descriptions of any components used in a
 neuronal network model, where such components may be neuron models, synapse models, synaptic plasticity
@@ -37,7 +37,7 @@ A number of :class:`Dimension`\s and :class:`Unit`\ have been pre-defined, for e
 
 .. code-block:: python
 
-    >>> from nineml.abstraction_layer.units import time, voltage, capacitance, nA, mol_per_cm3, Mohm
+    >>> from nineml.abstraction.units import time, voltage, capacitance, nA, mol_per_cm3, Mohm
     >>> voltage
     Dimension(name='voltage', i=-1, m=1, t=-3, l=2)
     >>> nA
@@ -47,7 +47,7 @@ A number of :class:`Dimension`\s and :class:`Unit`\ have been pre-defined, for e
 ComponentClass interface
 ------------------------
 
-.. autoclass:: nineml.abstraction_layer.ComponentClass
+.. autoclass:: nineml.abstraction.ComponentClass
    :members:
 
 .. autoclass:: Parameter

doc/source/api_reference/index.rst

@@ -4,7 +4,7 @@ API reference
 .. toctree::
    :maxdepth: 2
 
-   user_layer
-   abstraction_layer
+   user
+   abstraction
 
 

doc/source/api_reference/user_layer.rst

@@ -2,7 +2,7 @@
 User layer API
 ==============
 
-.. currentmodule:: nineml.user_layer
+.. currentmodule:: nineml.user
 
 A NineML model is made up of populations of cells, connected via synapses, which may exhibit plasticity. The models for the cells, synapses and plasticity mechanisms are all instances of :class:`Component`. Populations of cells are represented by :class:`Population`, the set of connections between two populations by :class:`Projection`. Finally, the entire model is encapsulated in :class:`Network`.
 
@@ -12,7 +12,7 @@ Components
 .. autoclass:: Component
    :show-inheritance:
 
-.. autoclass:: nineml.user_layer.components.BaseComponent
+.. autoclass:: nineml.user.components.BaseComponent
    :members: component_class, properties, initial_values, diff
 
 :class:`SpikingNodeType` and :class:`SynapseType` are subclasses of :class:`Component`. In the current version they
@@ -22,7 +22,7 @@ References
 ==========
 
 NineML has three closely-related objects used to refer to other NineML objects. :class:`Definition` is used inside
-:class:`Component`\s to refer to abstraction layer :class:`~nineml.abstraction_layer.ComponentClass` definitions.
+:class:`Component`\s to refer to abstraction layer :class:`~nineml.abstraction.ComponentClass` definitions.
 :class:`Prototype` is used inside :class:`Component`\s to refer to previously-defined :class:`Component`\s.
 :class:`Reference` is used inside :class:`Selection`\s to refer to :class:`Population` objects, and inside
 :class:`Projection`\s to refer to :class:`Population`\s and :class:`Selection`\s.
@@ -34,7 +34,7 @@ NineML has three closely-related objects used to refer to other NineML objects.
    :members: component
 
 .. autoclass:: Reference
-   :members: user_layer_object
+   :members: user_object
 
 
 Properties and physical quantities
@@ -57,7 +57,7 @@ Properties and physical quantities
 
       The value of the parameter (magnitude and units).
 
-.. currentmodule:: nineml.user_layer.values
+.. currentmodule:: nineml.user.values
 
 .. autoclass:: SingleValue
 
@@ -70,7 +70,7 @@ Properties and physical quantities
 .. autoclass:: ComponentValue
 
 
-.. currentmodule:: nineml.user_layer
+.. currentmodule:: nineml.user
 
 .. autoclass:: RandomDistribution
 

doc/source/conf.py

@@ -300,42 +300,42 @@
 .. |VISITATION| replace:: link to something about visitation.
 
 
-.. |COMPONENTCLASS| replace:: :class:`~nineml.abstraction_layer.ComponentClass`
-.. |Alias| replace:: :class:`~nineml.abstraction_layer.Alias`
-.. |TimeDerivative| replace:: :class:`~nineml.abstraction_layer.TimeDerivative`
-.. |AnalogPort| replace:: :class:`~nineml.abstraction_layer.AnalogPort`
-.. |StateAssignment| replace:: :class:`~nineml.abstraction_layer.StateAssignment`
-.. |Condition| replace:: :class:`~nineml.abstraction_layer.Condition`
-.. |OnCondition| replace:: :class:`~nineml.abstraction_layer.OnCondition`
-.. |OnEvent| replace:: :class:`~nineml.abstraction_layer.OnEvent`
-.. |StateVariable| replace:: :class:`~nineml.abstraction_layer.StateVariable`
-.. |EventPort| replace:: :class:`~nineml.abstraction_layer.EventPort`
-.. |Parameter| replace:: :class:`~nineml.abstraction_layer.Parameter`
-.. |NamespaceAddress| replace:: :class:`~nineml.abstraction_layer.NamespaceAddress`
-.. |DynamicsBlock| replace:: :class:`~nineml.abstraction_layer.DynamicsBlock`
-.. |Transition| replace:: :class:`~nineml.abstraction_layer.Transition`
-.. |AnalogReceivePort| replace:: :class:`~nineml.abstraction_layer.AnalogReceivePort`
-.. |AnalogSendPort| replace:: :class:`~nineml.abstraction_layer.AnalogSendPort`
-.. |AnalogReducePort| replace:: :class:`~nineml.abstraction_layer.AnalogReducePort`
-.. |EventSendPort| replace:: :class:`~nineml.abstraction_layer.EventSendPort`
-.. |EventReceivePort| replace:: :class:`~nineml.abstraction_layer.EventReceivePort`
-
-.. |ComponentFlattener| replace:: :class:`~nineml.abstraction_layer.flattening.ComponentFlattener`
-
-
-.. |Aliases| replace:: :class:`Aliases <nineml.abstraction_layer.Alias>`
-.. |TimeDerivatives| replace:: :class:`TimeDerivatives <nineml.abstraction_layer.TimeDerivative>`
-.. |AnalogPorts| replace:: :class:`AnalogPorts <nineml.abstraction_layer.AnalogPort>`
-.. |StateAssignments| replace:: :class:`StateAssignments <nineml.abstraction_layer.StateAssignment>`
-.. |Conditions| replace:: :class:`Conditions <nineml.abstraction_layer.Condition>`
-.. |StateVariables| replace:: :class:`StateVariables <nineml.abstraction_layer.StateVariable>`
-.. |EventPorts| replace:: :class:`EventPorts <nineml.abstraction_layer.EventPort>`
-.. |Parameters| replace:: :class:`Parameters <nineml.abstraction_layer.Parameter>`
-.. |NamespaceAddresses| replace:: :class:`NamespaceAddresses <nineml.abstraction_layer.NamespaceAddress>`
-.. |Transitions| replace:: :class:`Transitions <nineml.abstraction_layer.Transition>`
-.. |AnalogSendPorts| replace:: :class:`AnalogSendPorts <nineml.abstraction_layer.AnalogSendPort>`
-.. |EventSendPorts| replace:: :class:`EventSendPorts <nineml.abstraction_layer.EventSendPort>`
-.. |EventReceivePorts| replace:: :class:`EventReceivePorts <nineml.abstraction_layer.EventReceivePort>`
+.. |COMPONENTCLASS| replace:: :class:`~nineml.abstraction.ComponentClass`
+.. |Alias| replace:: :class:`~nineml.abstraction.Alias`
+.. |TimeDerivative| replace:: :class:`~nineml.abstraction.TimeDerivative`
+.. |AnalogPort| replace:: :class:`~nineml.abstraction.AnalogPort`
+.. |StateAssignment| replace:: :class:`~nineml.abstraction.StateAssignment`
+.. |Condition| replace:: :class:`~nineml.abstraction.Condition`
+.. |OnCondition| replace:: :class:`~nineml.abstraction.OnCondition`
+.. |OnEvent| replace:: :class:`~nineml.abstraction.OnEvent`
+.. |StateVariable| replace:: :class:`~nineml.abstraction.StateVariable`
+.. |EventPort| replace:: :class:`~nineml.abstraction.EventPort`
+.. |Parameter| replace:: :class:`~nineml.abstraction.Parameter`
+.. |NamespaceAddress| replace:: :class:`~nineml.abstraction.NamespaceAddress`
+.. |DynamicsBlock| replace:: :class:`~nineml.abstraction.DynamicsBlock`
+.. |Transition| replace:: :class:`~nineml.abstraction.Transition`
+.. |AnalogReceivePort| replace:: :class:`~nineml.abstraction.AnalogReceivePort`
+.. |AnalogSendPort| replace:: :class:`~nineml.abstraction.AnalogSendPort`
+.. |AnalogReducePort| replace:: :class:`~nineml.abstraction.AnalogReducePort`
+.. |EventSendPort| replace:: :class:`~nineml.abstraction.EventSendPort`
+.. |EventReceivePort| replace:: :class:`~nineml.abstraction.EventReceivePort`
+
+.. |ComponentFlattener| replace:: :class:`~nineml.abstraction.flattening.ComponentFlattener`
+
+
+.. |Aliases| replace:: :class:`Aliases <nineml.abstraction.Alias>`
+.. |TimeDerivatives| replace:: :class:`TimeDerivatives <nineml.abstraction.TimeDerivative>`
+.. |AnalogPorts| replace:: :class:`AnalogPorts <nineml.abstraction.AnalogPort>`
+.. |StateAssignments| replace:: :class:`StateAssignments <nineml.abstraction.StateAssignment>`
+.. |Conditions| replace:: :class:`Conditions <nineml.abstraction.Condition>`
+.. |StateVariables| replace:: :class:`StateVariables <nineml.abstraction.StateVariable>`
+.. |EventPorts| replace:: :class:`EventPorts <nineml.abstraction.EventPort>`
+.. |Parameters| replace:: :class:`Parameters <nineml.abstraction.Parameter>`
+.. |NamespaceAddresses| replace:: :class:`NamespaceAddresses <nineml.abstraction.NamespaceAddress>`
+.. |Transitions| replace:: :class:`Transitions <nineml.abstraction.Transition>`
+.. |AnalogSendPorts| replace:: :class:`AnalogSendPorts <nineml.abstraction.AnalogSendPort>`
+.. |EventSendPorts| replace:: :class:`EventSendPorts <nineml.abstraction.EventSendPort>`
+.. |EventReceivePorts| replace:: :class:`EventReceivePorts <nineml.abstraction.EventReceivePort>`
 """
 
 # Remove the copyright notice from docstrings:

doc/source/getting_started.rst

@@ -23,7 +23,7 @@ To read a file containing only abstraction layer elements:
     'voltage': Dimension(name='voltage', i=-1, m=1, t=-3, l=2)}
 
 This gives us a :class:`~nineml.Document` instance, a dictionary-like object containing a
-:class:`~nineml.abstraction_layer.ComponentClass` definition of an integrate-and-fire
+:class:`~nineml.abstraction.ComponentClass` definition of an integrate-and-fire
 neuron model, together with the definitions of the physical dimensions of parameters
 and state variables used in the model.
 
@@ -35,14 +35,14 @@ containing the abstraction layer definitions):
     >>> all_items = nineml.read("brunel_network_alpha_AI.xml")
     >>> from pprint import pprint
     >>> pprint(all_items)
-    {'All neurons': <nineml.user_layer.containers.Selection object at 0x105c49cd0>,
+    {'All neurons': <nineml.user.containers.Selection object at 0x105c49cd0>,
      'Exc': Population(name='Exc', number=4000, cell=nrn),
-     'Excitation': Projection(name="Excitation", source=Population(name='Exc', number=4000, cell=nrn), destination=<nineml.user_layer.containers.Selection object at 0x105c49cd0>, connectivity=BaseComponent(name="RandomExc", componentclass="RandomFanIn"), response=BaseComponent(name="syn", componentclass="AlphaPSR")plasticity=BaseComponent(name="ExcitatoryPlasticity", componentclass="StaticConnection"), delay=Delay(value=1.5, unit=ms), with 2 port-connections),
+     'Excitation': Projection(name="Excitation", source=Population(name='Exc', number=4000, cell=nrn), destination=<nineml.user.containers.Selection object at 0x105c49cd0>, connectivity=BaseComponent(name="RandomExc", componentclass="RandomFanIn"), response=BaseComponent(name="syn", componentclass="AlphaPSR")plasticity=BaseComponent(name="ExcitatoryPlasticity", componentclass="StaticConnection"), delay=Delay(value=1.5, unit=ms), with 2 port-connections),
      'Ext': Population(name='Ext', number=5000, cell=stim),
-     'External': Projection(name="External", source=Population(name='Ext', number=5000, cell=stim), destination=<nineml.user_layer.containers.Selection object at 0x105c49cd0>, connectivity=BaseComponent(name="OneToOne", componentclass="OneToOne"), response=BaseComponent(name="syn", componentclass="AlphaPSR")plasticity=BaseComponent(name="ExternalPlasticity", componentclass="StaticConnection"), delay=Delay(value=1.5, unit=ms), with 2 port-connections),
+     'External': Projection(name="External", source=Population(name='Ext', number=5000, cell=stim), destination=<nineml.user.containers.Selection object at 0x105c49cd0>, connectivity=BaseComponent(name="OneToOne", componentclass="OneToOne"), response=BaseComponent(name="syn", componentclass="AlphaPSR")plasticity=BaseComponent(name="ExternalPlasticity", componentclass="StaticConnection"), delay=Delay(value=1.5, unit=ms), with 2 port-connections),
      'Hz': Unit(name='Hz', dimension='per_time', power=0),
      'Inh': Population(name='Inh', number=1000, cell=nrn),
-     'Inhibition': Projection(name="Inhibition", source=Population(name='Inh', number=1000, cell=nrn), destination=<nineml.user_layer.containers.Selection object at 0x105c49cd0>, connectivity=BaseComponent(name="RandomInh", componentclass="RandomFanIn"), response=BaseComponent(name="syn", componentclass="AlphaPSR")plasticity=BaseComponent(name="InhibitoryPlasticity", componentclass="StaticConnection"), delay=Delay(value=1.5, unit=ms), with 2 port-connections),
+     'Inhibition': Projection(name="Inhibition", source=Population(name='Inh', number=1000, cell=nrn), destination=<nineml.user.containers.Selection object at 0x105c49cd0>, connectivity=BaseComponent(name="RandomInh", componentclass="RandomFanIn"), response=BaseComponent(name="syn", componentclass="AlphaPSR")plasticity=BaseComponent(name="InhibitoryPlasticity", componentclass="StaticConnection"), delay=Delay(value=1.5, unit=ms), with 2 port-connections),
      'Mohm': Unit(name='Mohm', dimension='resistance', power=6),
      'current': Dimension(name='current', i=1),
      'mV': Unit(name='mV', dimension='voltage', power=-3),
@@ -54,16 +54,16 @@ containing the abstraction layer definitions):
      'voltage': Dimension(name='voltage', i=-1, m=1, t=-3, l=2)}
 
 Again we get a dictionary-like object containing all the NineML objects in the XML file. An alternative
-representation can be obtained by reading the file as a :class:`~nineml.user_layer.Network` object:
+representation can be obtained by reading the file as a :class:`~nineml.user.Network` object:
 
 .. code-block:: python
 
-    >>> from nineml.user_layer import Network
+    >>> from nineml.user import Network
     >>> net = Network.read("brunel_network_alpha_AI.xml")
     >>> print(net)
-    <nineml.user_layer.containers.Network object at 0x106442690>
+    <nineml.user.containers.Network object at 0x106442690>
 
-This gives a much more structured representation. For example, all the :class:`~nineml.user_layer.Population`\s within the model are
+This gives a much more structured representation. For example, all the :class:`~nineml.user.Population`\s within the model are
 available through the ``populations`` attribute:
 
 .. code-block:: python
@@ -170,7 +170,7 @@ The refractory regime can be introspected in a similar way.
 Introspecting user layer models
 -------------------------------
 
-As shown above, once a complete network model has been loaded as a :class:`~nineml.user_layer.Network` object, we
+As shown above, once a complete network model has been loaded as a :class:`~nineml.user.Network` object, we
 can look at its neuron populations and the connections between these populations ("projections"):
 
 .. code-block:: python
@@ -181,9 +181,9 @@ can look at its neuron populations and the connections between these populations
      'Inh': Population(name='Inh', number=1000, cell=nrn)}
 
     >>> net.projections
-    {'Excitation': Projection(name="Excitation", source=Population(name='Exc', number=4000, cell=nrn), destination=<nineml.user_layer.containers.Selection object at 0x1097f39d0>, connectivity=BaseComponent(name="RandomExc", componentclass="RandomFanIn"), response=BaseComponent(name="syn", componentclass="AlphaPSR")plasticity=BaseComponent(name="ExcitatoryPlasticity", componentclass="StaticConnection"), delay=Delay(value=1.5, unit=ms), with 2 port-connections),
-    'External': Projection(name="External", source=Population(name='Ext', number=5000, cell=stim), destination=<nineml.user_layer.containers.Selection object at 0x1097f39d0>, connectivity=BaseComponent(name="OneToOne", componentclass="OneToOne"), response=BaseComponent(name="syn", componentclass="AlphaPSR")plasticity=BaseComponent(name="ExternalPlasticity", componentclass="StaticConnection"), delay=Delay(value=1.5, unit=ms), with 2 port-connections),
-    'Inhibition': Projection(name="Inhibition", source=Population(name='Inh', number=1000, cell=nrn), destination=<nineml.user_layer.containers.Selection object at 0x1097f39d0>, connectivity=BaseComponent(name="RandomInh", componentclass="RandomFanIn"), response=BaseComponent(name="syn", componentclass="AlphaPSR")plasticity=BaseComponent(name="InhibitoryPlasticity", componentclass="StaticConnection"), delay=Delay(value=1.5, unit=ms), with 2 port-connections)}
+    {'Excitation': Projection(name="Excitation", source=Population(name='Exc', number=4000, cell=nrn), destination=<nineml.user.containers.Selection object at 0x1097f39d0>, connectivity=BaseComponent(name="RandomExc", componentclass="RandomFanIn"), response=BaseComponent(name="syn", componentclass="AlphaPSR")plasticity=BaseComponent(name="ExcitatoryPlasticity", componentclass="StaticConnection"), delay=Delay(value=1.5, unit=ms), with 2 port-connections),
+    'External': Projection(name="External", source=Population(name='Ext', number=5000, cell=stim), destination=<nineml.user.containers.Selection object at 0x1097f39d0>, connectivity=BaseComponent(name="OneToOne", componentclass="OneToOne"), response=BaseComponent(name="syn", componentclass="AlphaPSR")plasticity=BaseComponent(name="ExternalPlasticity", componentclass="StaticConnection"), delay=Delay(value=1.5, unit=ms), with 2 port-connections),
+    'Inhibition': Projection(name="Inhibition", source=Population(name='Inh', number=1000, cell=nrn), destination=<nineml.user.containers.Selection object at 0x1097f39d0>, connectivity=BaseComponent(name="RandomInh", componentclass="RandomFanIn"), response=BaseComponent(name="syn", componentclass="AlphaPSR")plasticity=BaseComponent(name="InhibitoryPlasticity", componentclass="StaticConnection"), delay=Delay(value=1.5, unit=ms), with 2 port-connections)}
 
 NineML also supports "selections", groupings of neurons which span populations:
 
@@ -196,7 +196,7 @@ NineML also supports "selections", groupings of neurons which span populations:
           versions it will be possible to select and combine sub-populations.
 
 Looking more closely at a population, we can see its name, the number of neurons it contains and
-the neuron model used (:class:`~nineml.user_layer.Component`):
+the neuron model used (:class:`~nineml.user.Component`):
 
 .. code-block:: python
 
@@ -209,7 +209,7 @@ the neuron model used (:class:`~nineml.user_layer.Component`):
     BaseComponent(name="nrn", componentclass="BrunelIaF")
 
 In the neuron model component we can see its abstraction layer definition
-(:class:`~nineml.abstraction_layer.dynamics.ComponentClass`), it's properties (parameter values), and the initial
+(:class:`~nineml.abstraction.dynamics.ComponentClass`), it's properties (parameter values), and the initial
 values of its state variables.
 
 .. note:: the handling of initial values is likely to change in future versions of NineML.
@@ -244,9 +244,9 @@ Turning from a population to a projection:
     [PortConnection('plasticity', 'response', 'weight', 'q'),
      PortConnection('response', 'destination', 'Isyn', 'Isyn')]
 
-Note that the :attr:`source` and :attr:`destination` attributes point to :class:`~nineml.user_layer.Population`\s or
-:class:`~nineml.user_layer.Projection`\s, the :attr:`connectivity` rule, the post-synaptic :attr:`response` model and
-the synaptic :attr:`plasticity` model are all :class:`~nineml.user_layer.Component`\s. The :attr:`port_connections`
+Note that the :attr:`source` and :attr:`destination` attributes point to :class:`~nineml.user.Population`\s or
+:class:`~nineml.user.Projection`\s, the :attr:`connectivity` rule, the post-synaptic :attr:`response` model and
+the synaptic :attr:`plasticity` model are all :class:`~nineml.user.Component`\s. The :attr:`port_connections`
 attribute indicates which ports in the different components should be connected together.