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Unfit
3.1.1
Data fitting and optimization software
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Fit the voltage dependence of a cardiac ion channel rate constant. More...
#include <CardiacAlphaN.hpp>
Public Member Functions | |
| CardiacAlphaN (const std::vector< double > &vm, const std::vector< double > &alpha_n) | |
| std::vector< double > | operator() (const std::vector< double > ¶m) |
Public Member Functions inherited from Unfit::GenericCostFunction | |
| virtual | ~GenericCostFunction () |
Private Attributes | |
| const std::vector< double > | vm_ |
| const std::vector< double > | alpha_n_ |
Fit the voltage dependence of a cardiac ion channel rate constant.
Here the goal is to fit the alpha_n rate constant as a function of the cell membrane potential (vm), given a set of experimental data (vm and alpha_n). This channel is a modified slow potassium channel from a cardiac muscle cell. The equation that has been chosen to fit the data is:
alpha_n = A / (1 + exp(B*vm + C))
The goal is to find the values of A, B & C that best fit the data. In terms of the model, A = param[0], B = param[1] and C = param[2].
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inline |
Create the cost function. Here the experimental data must be passed in, and cannot be changed (if you want to, just create another cost function object). Here the experimental data is two vectors, membrane potential (vm) and the rate constant alpha_m.
Intended use : CardiacAlphaN cost_func(vm, alpha_n);
| vm | A vector of membrane potentials |
| alpha_n | A vector of experimental alpha_n data |
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inlinevirtual |
Calculate the linear distance (residuals) between our model and the data. This method encapsulates the model, and expects the current estimates of the unknown parameters as an input. See the class documentation for details about the model.
Intended use : residuals = cost_func(param)
| param | A vector containing the current estimates of the parameters we are trying to fit |
Implements Unfit::GenericCostFunction.
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private |
A vector to store the experimental rate constant, alpha_n
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private |
A vector to store the experimental membrane potential, vm
1.8.13