Merge branch 'master' into development

Author: pollaro

+nla/NetworkAtlas.m

@@ -11,9 +11,9 @@
     % :param parcels: Optional MATLAB struct field for surface parcellations. Contains two sub-fields ``ctx_l`` and ``ctx_r``. N\ :sub:`verts`\ x 1 vectors. Each element of a vector corresponds to a vertex within the spatial mesh and contains the index of the ROI for that vertex.
     % :param space: Optional The mesh that the atlas` ROI locations/parcels are in. Two options - ``TT`` or ``MNI``
 
-    
-    properties
-        nets
+    properties (SetAccess = private)
+        nets % This is the net_names
+
         ROIs
         ROI_order
         name

.github/workflows/run_matlab_tests.yml

@@ -27,4 +27,4 @@ jobs:
         uses: matlab-actions/run-command@v2
         with:
           command: addpath(genpath(pwd)); results = runTests(); assertSuccess(results)
-          use-parallel: true
+          use-parallel: true

docs/source/edge_level_tests.rst

@@ -73,6 +73,64 @@ Provided Tests
   :Permuted p: ``.mat`` file containing N\ :sub:`ROI_pairs`\ x N\ :sub:`permutations`\ of logical values. Observed, thresholded, permuted p-values.
   :Permuted coeff: ``.mat`` file containing N\ :sub:`ROI_pairs`\ x N\ :sub:`permutations`\ of permuted edge-level coefficients.
 
-Creating additional edge-level tests
------------------------------------------------
+Creating an edge-level test
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
+1. All test objects must inherit from the ``nla.edge.test.Base`` class.
+2. All test objects must be saved into the ``+nla/+edge/+test`` directory
+3. There are a few required properties and methods that are required:
+   
+  * **name**
+    * All tests must be given a name. Example::
+  
+      properties (Constant)
+        name = "Kendall's tau"
+      end
+
+  * **result**
+    * This is a method. The function handle is::
+
+      function result = run(obj, test_options)
+
+  * **test_options**
+    * This is a structure with options that are used either in the test or visualizing results
+
+  * **requiredInputs**
+    * This is a static function to define the inputs for the test::
+      
+      methods (Static)
+        function inputs = requiredInputs()
+          inputs = {nla.inputField.Number('prob_max', 'P <', 0, 0.05, 1), nla.inputField.NetworkAtlas(), nla.inputField.Behavior()};
+        end
+      end
+
+    * This defines a number field ``prob_max`` from [0, 1] with a default of 0.05. It also specifies a network atlas (:ref:`NetworkAtlas() <network_atlases>` input field, and a behavior input field.
+    * These are all required. If the user does not supply them, the test not run in the GUI.
+  
+4. If the test is located in the correct folder, after a GUI restart (not MATLAB GUI) the test will populate in the Edge Level test list.
+
+In addition to creating the test, a result object will also need to be created.
+
+Creating a result
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+1. ``nla.edge.BaseResult`` will work if custom data fields are not required.
+2. The result must inherit from ``nla.edge.BaseResult``
+3. This result must be placed in ``+nla/+edge/+result/``
+4. Methods and properties
+
+  * **output**
+    * This is the data that will be passed to create a figure of the data::
+
+      function output(obj, network_atlas, flags)
+
+    * Network atlas :ref:`NetworkAtas() <network_atlases>`
+    * flags - a MATLAB structure that currently only has a field ``display_sig`` which is a boolean to determine if displayed p-values are thresholded
+  
+  * **merge**
+    * This is an optional method
+    * It is used to merge blocks of results together (like in a parallel processing environment)::
+
+      function merge(obj, results)
+
+    * The ``results`` argument is a result to merge the object with. Afterwards, the current object will be the two merged blocks

docs/source/network_level_tests.rst

@@ -0,0 +1,53 @@
+Network-level Statistical Tests
+======================================
+
+Methods
+--------------------------
+
+The non-permuted method measures how significant each network is compared to the entire connectome using
+the given statistical test.
+
+The full connectome method ranks the non-permuted (observed) significance of each network against the
+significance of the same network calculated over many permutations using the same test.
+I DON"T KNOW HOW TO EXPLAIN THE PROBABILITY BEING CALCULATED - Jim
+
+The within network-pair method measures how significant each network is compared to all permutations of
+only the selected network.
+
+Common Inputs
+------------------------
+
+:P: Network level p-value threshold
+:Behavior Count: Number of different behavior vectors intended to test.
+
+Provided Tests
+---------------------------
+
+* **Hypergeomtric**
+
+  * MATLAB's `hypercdf <https://www.mathworks.com/help/stats/hygecdf.html>` used to find the probablity
+* **Chi-squred**
+
+  * Runs a :math:`\chi`\ :sup:`2` test. 
+
+.. math::
+
+    \chi^2 = \sum_{n=1}^n \frac{O_i - E_i)^2}{E_i}
+
+* **Kolmogorov-Smirnov**
+  
+  * MATLAB's `kstest2 <https://www.mathworks.com/help/stats/kstest2.html>`
+* **Wilcoxon**
+
+  * MATLAB's `ranksum <https://www.mathworks.com/help/stats/ranksum.html>`
+* **Welch's t-test**
+
+  * Uses a modified version of MATLAB's t-test found in `+nla/WelchT`
+
+.. math::
+
+    t = \frac{\overline{X_1} - \overline{X_2}}{\sqrt{s_{\overline{X_1}}^2 - s_{\overline{X_2}}^2}}
+    where
+    s_{\overline{X_i}} = \frac{s_i}{\sqrt{N_i}}
+
+*