From 1c18f35214889403d9f1fc2c813afd80613c7134 Mon Sep 17 00:00:00 2001 From: "gitlab@srinivas.gs" Date: Fri, 23 Aug 2019 15:44:56 -0400 Subject: [PATCH] sorted xfit prop names --- docs/reference/matlab/xfit-head.md | 95 ++++++++++++++++-------------- docs/reference/matlab/xfit.md | 95 ++++++++++++++++-------------- 2 files changed, 100 insertions(+), 90 deletions(-) diff --git a/docs/reference/matlab/xfit-head.md b/docs/reference/matlab/xfit-head.md index db43f52b..62f8d749 100644 --- a/docs/reference/matlab/xfit-head.md +++ b/docs/reference/matlab/xfit-head.md @@ -27,36 +27,49 @@ using the built-in `properties` command: properties(xf) ``` -### `x` +### `best_cost` + + +The best cost holds the lowest value computed by the simulation function during an optimization procedure. This is a read-only property. + + + +### `data` | Default | Allowed values | Type | | ------- | ----- | ----- | -| [] | scalar values | xolotl | +| [] | any | any | -This property contains a xolotl object. Since xfit uses -xolotl to run actual simulations, this is necessary for all projects. +The `data` property can hold any user-defined data. You may want to use this if your cost function required additional data to measure the cost. For example, if you want to fit a neuron to a specifiy voltage trace, you would store it here. -### `SimFcn` +### `engine` + +This option determines the optimization algorithm used. + +| Engine Name | Engine Keyword | +| ----------- | -------------- | +| Pattern Search | `patternsearch` | +| Particle Swarm | `particleswarm` | +| Genetic Algorithm | `ga` | + + + +### `lb` & `ub` | Default | Allowed values | Type | | ------- | ----- | ----- | -| [] | any | function_handle | +| [] | vectors | double | -A function handle to the simulation function used to evaluate the model cost. -The simulation function can be any MATLAB function, -provided that the following are true: +`lb` and `ub` are $n$ x 1 vectors of numerical lower bound and upper bound values. During optimization, parameters are bounded between their upper and lower bounds. -* The first output must be the cost, which is a positive, real-valued scalar. -* The function accepts two arguments, the first of which is a xolotl object. -The function thus has the (minimal) signature: +### `nonlcon` -``` -function [cost, ...] = functionName(xolotl_object, data) -``` +Nonlinear inequality and equaity constraints, only supported for engines that support them. To understand how to use these constraints, look at MATLAB's documentation [here](https://www.mathworks.com/help/optim/ug/nonlinear-constraints.html) -When xfit performs a parameter optimization routine, -it calls the `SimFcn` using the xolotl object stored in the `x` property, which has been set up with trial parameters. +### `options` + +This property is a struct that holds options for the selected optimization engine. It is automatically generated from MATLAB's built-in [optimoptions](https://www.mathworks.com/help/optim/ug/optimization-options-reference.html) function. ### `parameter_names` @@ -68,6 +81,8 @@ This cell array of character vectors contains the names of xolotl parameters to The `find` method of xolotl is the best way to populate this list. `seed`, `lb`, and `ub` share one-to-one correspondence with `parameter_names`, so all should be the same dimensions. + + ### `seed` | Default | Allowed values | Type | @@ -78,51 +93,41 @@ The seed is an $n$ x 1 vector of numerical parameter values for starting an optimization protocol, where $n$ is the number of parameters to optimize over. -### `lb` & `ub` + +### `SimFcn` | Default | Allowed values | Type | | ------- | ----- | ----- | -| [] | vectors | double | - -`lb` and `ub` are $n$ x 1 vectors of numerical lower bound and upper bound values. During optimization, parameters are bounded between their upper and lower bounds. - -### `options` - +| [] | any | function_handle | +A function handle to the simulation function used to evaluate the model cost. +The simulation function can be any MATLAB function, +provided that the following are true: -This property is a struct that holds options for the selected optimization engine. It is automatically generated from MATLAB's built-in [optimoptions](https://www.mathworks.com/help/optim/ug/optimization-options-reference.html) function. +* The first output must be the cost, which is a positive, real-valued scalar. +* The function accepts two arguments, the first of which is a xolotl object. +The function thus has the (minimal) signature: -### `engine` +``` +function [cost, ...] = functionName(xolotl_object, data) +``` -This option determines the optimization algorithm used. +When xfit performs a parameter optimization routine, +it calls the `SimFcn` using the xolotl object stored in the `x` property, which has been set up with trial parameters. -| Engine Name | Engine Keyword | -| ----------- | -------------- | -| Pattern Search | `patternsearch` | -| Particle Swarm | `particleswarm` | -| Genetic Algorithm | `ga` | ### `timestamp` This property keeps track of the duration of a simulation. This is a read-only property. -### `best_cost` - - -The best cost holds the lowest value computed by the simulation function during an optimization procedure. This is a read-only property. - -### `data` +### `x` | Default | Allowed values | Type | | ------- | ----- | ----- | -| [] | any | any | - -The `data` property can hold any user-defined data. You may want to use this if your cost function required additional data to measure the cost. For example, if you want to fit a neuron to a specifiy voltage trace, you would store it here. - - -### 'nonlcon' +| [] | scalar values | xolotl | -Nonlinear inequality and equaity constraints, only supported for engines that support them. To understand how to use these constraints, look at MATLAB's documentation [here](https://www.mathworks.com/help/optim/ug/nonlinear-constraints.html) +This property contains a xolotl object. Since xfit uses +xolotl to run actual simulations, this is necessary for all projects. ## Methods \ No newline at end of file diff --git a/docs/reference/matlab/xfit.md b/docs/reference/matlab/xfit.md index ab7c4922..bfba8f84 100644 --- a/docs/reference/matlab/xfit.md +++ b/docs/reference/matlab/xfit.md @@ -27,36 +27,49 @@ using the built-in `properties` command: properties(xf) ``` -### `x` +### `best_cost` + + +The best cost holds the lowest value computed by the simulation function during an optimization procedure. This is a read-only property. + + + +### `data` | Default | Allowed values | Type | | ------- | ----- | ----- | -| [] | scalar values | xolotl | +| [] | any | any | -This property contains a xolotl object. Since xfit uses -xolotl to run actual simulations, this is necessary for all projects. +The `data` property can hold any user-defined data. You may want to use this if your cost function required additional data to measure the cost. For example, if you want to fit a neuron to a specifiy voltage trace, you would store it here. -### `SimFcn` +### `engine` + +This option determines the optimization algorithm used. + +| Engine Name | Engine Keyword | +| ----------- | -------------- | +| Pattern Search | `patternsearch` | +| Particle Swarm | `particleswarm` | +| Genetic Algorithm | `ga` | + + + +### `lb` & `ub` | Default | Allowed values | Type | | ------- | ----- | ----- | -| [] | any | function_handle | +| [] | vectors | double | -A function handle to the simulation function used to evaluate the model cost. -The simulation function can be any MATLAB function, -provided that the following are true: +`lb` and `ub` are $n$ x 1 vectors of numerical lower bound and upper bound values. During optimization, parameters are bounded between their upper and lower bounds. -* The first output must be the cost, which is a positive, real-valued scalar. -* The function accepts two arguments, the first of which is a xolotl object. -The function thus has the (minimal) signature: +### `nonlcon` -``` -function [cost, ...] = functionName(xolotl_object, data) -``` +Nonlinear inequality and equaity constraints, only supported for engines that support them. To understand how to use these constraints, look at MATLAB's documentation [here](https://www.mathworks.com/help/optim/ug/nonlinear-constraints.html) -When xfit performs a parameter optimization routine, -it calls the `SimFcn` using the xolotl object stored in the `x` property, which has been set up with trial parameters. +### `options` + +This property is a struct that holds options for the selected optimization engine. It is automatically generated from MATLAB's built-in [optimoptions](https://www.mathworks.com/help/optim/ug/optimization-options-reference.html) function. ### `parameter_names` @@ -68,6 +81,8 @@ This cell array of character vectors contains the names of xolotl parameters to The `find` method of xolotl is the best way to populate this list. `seed`, `lb`, and `ub` share one-to-one correspondence with `parameter_names`, so all should be the same dimensions. + + ### `seed` | Default | Allowed values | Type | @@ -78,51 +93,41 @@ The seed is an $n$ x 1 vector of numerical parameter values for starting an optimization protocol, where $n$ is the number of parameters to optimize over. -### `lb` & `ub` + +### `SimFcn` | Default | Allowed values | Type | | ------- | ----- | ----- | -| [] | vectors | double | - -`lb` and `ub` are $n$ x 1 vectors of numerical lower bound and upper bound values. During optimization, parameters are bounded between their upper and lower bounds. - -### `options` - +| [] | any | function_handle | +A function handle to the simulation function used to evaluate the model cost. +The simulation function can be any MATLAB function, +provided that the following are true: -This property is a struct that holds options for the selected optimization engine. It is automatically generated from MATLAB's built-in [optimoptions](https://www.mathworks.com/help/optim/ug/optimization-options-reference.html) function. +* The first output must be the cost, which is a positive, real-valued scalar. +* The function accepts two arguments, the first of which is a xolotl object. +The function thus has the (minimal) signature: -### `engine` +``` +function [cost, ...] = functionName(xolotl_object, data) +``` -This option determines the optimization algorithm used. +When xfit performs a parameter optimization routine, +it calls the `SimFcn` using the xolotl object stored in the `x` property, which has been set up with trial parameters. -| Engine Name | Engine Keyword | -| ----------- | -------------- | -| Pattern Search | `patternsearch` | -| Particle Swarm | `particleswarm` | -| Genetic Algorithm | `ga` | ### `timestamp` This property keeps track of the duration of a simulation. This is a read-only property. -### `best_cost` - - -The best cost holds the lowest value computed by the simulation function during an optimization procedure. This is a read-only property. - -### `data` +### `x` | Default | Allowed values | Type | | ------- | ----- | ----- | -| [] | any | any | - -The `data` property can hold any user-defined data. You may want to use this if your cost function required additional data to measure the cost. For example, if you want to fit a neuron to a specifiy voltage trace, you would store it here. - - -### 'nonlcon' +| [] | scalar values | xolotl | -Nonlinear inequality and equaity constraints, only supported for engines that support them. To understand how to use these constraints, look at MATLAB's documentation [here](https://www.mathworks.com/help/optim/ug/nonlinear-constraints.html) +This property contains a xolotl object. Since xfit uses +xolotl to run actual simulations, this is necessary for all projects. ## Methods