made a new example that makes a pyloric net

cleaned up some demos

+xolotl/+examples/PyloricNet.m

@@ -0,0 +1,64 @@
+
+
+%{
+              _       _   _
+   __  _____ | | ___ | |_| |
+   \ \/ / _ \| |/ _ \| __| |
+    >  < (_) | | (_) | |_| |
+   /_/\_\___/|_|\___/ \__|_|
+
+## PyloricNet
+
+**Syntax**
+
+```matlab
+x = xolotl.examples.PyloricNet();
+```
+
+**Description**
+
+makes a three-cell model of the pyloric network
+following Prinz et al. Nat. Neuro. 
+
+
+%}
+
+
+function x = PyloricNet()
+
+
+% the order here doesn't matter -- everything will be re-arranged
+% alphabetically 
+channels = {'prinz/NaV','prinz/CaT','prinz/CaS','prinz/ACurrent','prinz/KCa','prinz/Kd','prinz/HCurrent','Leak'};
+
+
+x = xolotl;
+
+x.add('compartment','AB');
+x.AB.add('prinz/CalciumMech');
+
+for i = 1:length(channels)
+	x.AB.add(channels{i});
+end
+
+x.add(copy(x.AB),'LP')
+x.add(copy(x.AB),'PY')
+
+% configure gbars
+x.AB.set('*gbar', [500,  60,  25,   .1,   50, 1000,   0,   1000])
+x.LP.set('*gbar', [200,  40,   0,   .5,   0,  250,    0.3, 1000])
+x.PY.set('*gbar', [500,  20,  24,   .5,   0,  1250,   0.1, 1000])
+
+x.set('*Leak.E',-50)
+
+
+% set up synapses as in Fig. 2e
+x.connect('AB','LP','Chol','gmax',30);
+x.connect('AB','PY','Chol','gmax',3);
+x.connect('AB','LP','Glut','gmax',30);
+x.connect('AB','PY','Glut','gmax',10);
+x.connect('LP','PY','Glut','gmax',1);
+x.connect('PY','LP','Glut','gmax',30);
+x.connect('LP','AB','Glut','gmax',30);
+
+x.t_end = 5e3;

@xolotl/add.m

@@ -14,6 +14,7 @@
 % x.add('compartment','comp_name')
 % x.add(compartment,'comp_name')
 % x.add('compartment','comp_name',...)
+% x.add(Compartment,'comp_name')
 % ```
 %
 % **Description**
@@ -26,6 +27,8 @@
 %
 % - **`x.add('compartment','comp_name',...)`** adds a compartment to the xolotl object and names it `comp_name`. The compartment is then additionally configured using the parameters specified using Name Value syntax.
 %
+% - **`x.add(Compartment, 'comp_name')`** adds a pre-defined cpplab object of class "compartment" to the xolotl object and names it `comp_name`. You cannot pass additional name-value arguments using this syntax.
+%
 % **Technical Details**
 %
 % `xolotl.add` checks that the compartment being added has a legal name
@@ -41,6 +44,7 @@
 
 function add(self,obj_type, obj_name,varargin)
 
+
 msg = ['You tried to add a compartment without a label, which is not allowed. Every compartment must be labeled. \n\n<a href="https://xolotl.readthedocs.io/en/master/reference/matlab/xolotl/#add">Click here to read the documentation on how to use this method</a>'];
 assert(nargin > 2,'xolotl:add:no_label',msg)
 

docs/how-to/run-simulations.md

@@ -74,7 +74,7 @@ Currents are ordered exactly the same as in the `xolotl` object,
 meaning by compartment and then alphabetically.
 
 !!! Note "Plotting mechanisms and currents"
-    The example script `demo_stg` contains code that plots currents vs. time and `demo_integral_control` contains code that plots mechanisms vs. time.
+    The example script `demo_pyloric_net` contains code that plots currents vs. time and `demo_integral_control` contains code that plots mechanisms vs. time.
 
 ## Inject current into compartments
 Injected current is mediated by the `I_ext` property of the `xolotl` object.

docs/how-to/voltage-clamp.md

@@ -69,7 +69,7 @@ We can also voltage clamp a single cell in a network. To demonstrate this, we wi
 
 ```matlab
 xolotl.go_to_examples
-demo_stg
+demo_pyloric_net
 ```
 
 Here, let's voltage clamp one cell to another cell's voltage dynamics.

docs/reference/matlab/xolotl.md

@@ -209,6 +209,7 @@ the model.
 x.add('compartment','comp_name')
 x.add(compartment,'comp_name')
 x.add('compartment','comp_name',...)
+x.add(Compartment,'comp_name')
 ```
 
 **Description**
@@ -221,6 +222,8 @@ Adds a `cpplab` object to a `xolotl` object. The `add` method is the most import
 
 - **`x.add('compartment','comp_name',...)`** adds a compartment to the xolotl object and names it `comp_name`. The compartment is then additionally configured using the parameters specified using Name Value syntax.
 
+- **`x.add(Compartment, 'comp_name')`** adds a pre-defined cpplab object of class "compartment" to the xolotl object and names it `comp_name`. You cannot pass additional name-value arguments using this syntax.
+
 **Technical Details**
 
 `xolotl.add` checks that the compartment being added has a legal name

docs/tutorials/built-in-demos.md

@@ -55,5 +55,5 @@ Xolotl comes with several example scripts that illustrate various features of th
 | [demo_multi_compartment](https://github.com/sg-s/xolotl/blob/master/examples/demo_multi_compartment.m) | This example sets up a multi-compartment model, where different compartments have different levels of channels |
 | [demo_finite_size](https://github.com/sg-s/xolotl/blob/master/examples/demo_finite_size.m) | This example varies the size of a neuron, and shows that smaller neurons are more dominated by noise due to the finite number of ion channels |
 | [demo_rk4](https://github.com/sg-s/xolotl/blob/master/examples/demo_rk4.m) | This demo shows you how to use the [`solver_order`](https://xolotl.readthedocs.io/en/master/reference/xolotl/#solver_order) property of xolotl to use a Runge-Kutta 4 ODE solver to simulate the model|
-| [demo_stg](https://github.com/sg-s/xolotl/blob/master/examples/demo_stg.m) | In this example, we set up a small network of three neurons, demonstrating how synapses work in xolotl |
+| [demo_pyloric_net](https://github.com/sg-s/xolotl/blob/master/examples/demo_pyloric_net.m) | In this example, we set up a small network of three neurons, demonstrating how synapses work in xolotl |
 | [demo_stg_temperature](https://github.com/sg-s/xolotl/blob/master/examples/demo_stg_temperature.m)  | Here, we vary the temperature of the simulation, showing how we can make the model sensitive to temperature. |

docs/tutorials/first-network.md

@@ -1,6 +1,6 @@
 In this tutorial, we will walk through the process of creating a network model of three neurons connected together by synapses. We will integrate the model to find the membrane potential over time and view the output.
 
-Code equivalent to this tutorial can be found in `../xolotl/examples/demo_stg.m`.
+Code equivalent to this tutorial can be found in `../xolotl/examples/demo_pyloric_net.m`.
 
 ### A high-level view of the network
 
@@ -199,4 +199,4 @@ You should see something like this:
 ![](../images/stg-trace.png)
 
 !!! Note "A shortcut through this tutorial"
-    You can reproduce the model we created here by running the `demo_stg` script. Make sure you run `xolotl.go_to_examples` first so that you're in the right folder.
+    You can reproduce the model we created here by running the `demo_pyloric_net` script. Make sure you run `xolotl.go_to_examples` first so that you're in the right folder.

examples/demo_pyloric_net.m

@@ -0,0 +1,52 @@
+% test script for matlab wrapper
+
+% this sets up the pyloric network
+% as in Fig 2e of this paper:
+% Prinz ... Marder Nat Neuro 2004
+% http://www.nature.com/neuro/journal/v7/n12/abs/nn1352.html
+
+x = xolotl.examples.PyloricNet;
+
+x.integrate;
+
+
+[V, ~, ~, currs, syns] = x.integrate;
+
+
+C = x.find('compartment');
+
+x.plot;
+drawnow
+
+figure('outerposition',[100 100 1000 900],'PaperUnits','points','PaperSize',[1000 900]); hold on
+subplot(3,1,1); hold on
+plot(currs(:,1:7))
+ylabel('I (nA)')
+title(C{1})
+legend(x.(C{1}).find('conductance'))
+
+subplot(3,1,2); hold on
+plot(currs(:,8:15))
+title(C{2})
+ylabel('I (nA)')
+legend(x.(C{2}).find('conductance'))
+
+subplot(3,1,3); hold on
+plot(currs(:,16:23))
+title(C{3})
+ylabel('I (nA)')
+legend(x.(C{3}).find('conductance'))
+
+
+drawnow
+
+figure('outerposition',[100 100 1000 500],'PaperUnits','points','PaperSize',[1000 500]); hold on
+
+plot(syns)
+ylabel('I (nA)')
+title('synaptic currents')
+
+drawnow
+
+
+figlib.pretty()