SMLM models¶
- class @SMLMModel.SMLMModel¶
SMLMModel
is a super-class for defining how to deal with a geometric model.- ParentObject = '[]'¶
Parental SMLMModelFit object.
- ID = None¶
The model’s ID in the parental SMLMModelFit object.
- img = None¶
Model image.
- parVal = None¶
[obsolete].
- mPars = None¶
Model parameters.
- modelObj = None¶
Source geometric model object.
- modelFun = None¶
The function for creating coordinates based on the geometric model.
- sourcePath = None¶
The path of the m file of the geometric model.
- dimension = None¶
Dimension of the geometric model.
- modelType = None¶
Type of the model, either discrete, discretized, continuous, intensity, or image.
- fixSigma = 'false'¶
Fix the sigma to a specific value.
- displayLut = "'red hot'"¶
The lookup table for the model.
- layer = '1'¶
The layer that this model is fitted to.
- addParent(parent)¶
Add the parental SMLMModelFit object.
- exportMPars()¶
Export model parameters and their default values.
- class @functionModel.functionModel(model2load)¶
A sub-class of
SMLMModel
. functionModel class handles any geometric model in the form of a function.functionModel
handles the function differently based on its modelType. The modelType is per geometric model and defined in modelType of thegeometricModel
.- Last update:
14.10.2021
See also
- pixelSize = '5'¶
Pixel size of the model
- sigma = '15'¶
Standard deviation of the gaussian kernel used for smoothing the model.
- sigmaFactor = '1'¶
The scaling factor of the kernel’s standard deviation.
- samplingFactor = '0.75'¶
For continuous model, deciding the distance between ref points. In the unit of sigma. 0.75 means 0.75*sigma.
- sigmaSet = None¶
The set of sigma.
- sigmaZSet = None¶
The set of sigma in Z.
- extraBlurr = None¶
This is a parameter determined by lPars.variation.
- locsPrecFactor = None¶
The min sqrt(locprec^2+varation^2)
- functionModel(model2load)¶
The constructor of the functional model object. This function fetches the default values from the geometric model.
- updateMParsArg()¶
This function updates the mPars’ arguments based on the change of the geometric model.
- getPoint(mPars, varargin)¶
Getting sampled points from the model.
- fun(mPars, dx)¶
convert the output of model for voxelblurr
- deriveSigma(locs, varargin)¶
deriveSigma()
derives the final sigma used for fitting. WhenfixSigma
is set as true, sigmas are derived based on pre-defined values. Otherwise, sigmas are derived based on localization precisions. For a continuous model, the minimum sigma is defined as the median of localization precisions.- Uasage:
obj.deriveSigma(locs)
- Inputs:
obj (
functionModel
) – an object created byfunctionModel()
.
locs (structure array) – a typical localization structure array used in SMAP.
- Output:
sigmaFactor (numeric vector) – a 1-by-2 vector that determines the fold of localization precisions used for fitting.
sigmaSet (numeric vector | numeric scalar) – sigma used for fitting. A N-by-1 vector, where N is the number of localiztions when
fixSigma
is true.sigmaZSet (numeric vector | numeric scalar) – z sigma used for fitting. A N-by-1 vector, where N is the number of localiztions when
fixSigma
is true.
- Last update:
28.04.2022
See also