nipype.interfaces.afni.svm module¶
AFNI’s svm interfaces.
SVMTest¶
Bases: AFNICommand
Wrapped executable:
3dsvm
.Temporally predictive modeling with the support vector machine SVM Test Only For complete details, see the 3dsvm Documentation.
Examples
>>> from nipype.interfaces import afni as afni >>> svmTest = afni.SVMTest() >>> svmTest.inputs.in_file= 'run2+orig' >>> svmTest.inputs.model= 'run1+orig_model' >>> svmTest.inputs.testlabels= 'run2_categories.1D' >>> svmTest.inputs.out_file= 'pred2_model1' >>> res = svmTest.run()
- in_filea pathlike object or string representing an existing file
A 3D or 3D+t AFNI brik dataset to be used for testing. Maps to a command-line argument:
-testvol %s
.- modela unicode string
Modname is the basename for the brik containing the SVM model. Maps to a command-line argument:
-model %s
.
- argsa unicode string
Additional parameters to the command. Maps to a command-line argument:
%s
.- classouta boolean
Flag to specify that pname files should be integer-valued, corresponding to class category decisions. Maps to a command-line argument:
-classout
.- environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’
Environment variables. (Nipype default value:
{}
)- multiclassa boolean
Specifies multiclass algorithm for classification. Maps to a command-line argument:
-multiclass %s
.- nodetrenda boolean
Flag to specify that pname files should not be linearly detrended. Maps to a command-line argument:
-nodetrend
.- nopredcensorda boolean
Flag to prevent writing predicted values for censored time-points. Maps to a command-line argument:
-nopredcensord
.- num_threadsan integer (int or long)
Set number of threads. (Nipype default value:
1
)- optionsa unicode string
Additional options for SVM-light. Maps to a command-line argument:
%s
.- out_filea pathlike object or string representing a file
Filename for .1D prediction file(s). Maps to a command-line argument:
-predictions %s
.- outputtype‘NIFTI’ or ‘AFNI’ or ‘NIFTI_GZ’
AFNI output filetype.
- testlabelsa pathlike object or string representing an existing file
true class category .1D labels for the test dataset. It is used to calculate the prediction accuracy performance. Maps to a command-line argument:
-testlabels %s
.
- out_filea pathlike object or string representing an existing file
Output file.
SVMTrain¶
Bases: AFNICommand
Wrapped executable:
3dsvm
.Temporally predictive modeling with the support vector machine SVM Train Only For complete details, see the 3dsvm Documentation.
Examples
>>> from nipype.interfaces import afni as afni >>> svmTrain = afni.SVMTrain() >>> svmTrain.inputs.in_file = 'run1+orig' >>> svmTrain.inputs.trainlabels = 'run1_categories.1D' >>> svmTrain.inputs.ttype = 'regression' >>> svmTrain.inputs.mask = 'mask.nii' >>> svmTrain.inputs.model = 'model_run1' >>> svmTrain.inputs.alphas = 'alphas_run1' >>> res = svmTrain.run()
- in_filea pathlike object or string representing an existing file
A 3D+t AFNI brik dataset to be used for training. Maps to a command-line argument:
-trainvol %s
.- ttypea unicode string
Tname: classification or regression. Maps to a command-line argument:
-type %s
.
- alphasa pathlike object or string representing a file
Output alphas file name. Maps to a command-line argument:
-alpha %s
.- argsa unicode string
Additional parameters to the command. Maps to a command-line argument:
%s
.- censora pathlike object or string representing an existing file
.1D censor file that allows the user to ignore certain samples in the training data. Maps to a command-line argument:
-censor %s
.- environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’
Environment variables. (Nipype default value:
{}
)- kernela unicode string
String specifying type of kernel function:linear, polynomial, rbf, sigmoid. Maps to a command-line argument:
-kernel %s
.- maska pathlike object or string representing an existing file
Byte-format brik file used to mask voxels in the analysis. Maps to a command-line argument:
-mask %s
(position: -1).- max_iterationsan integer (int or long)
Specify the maximum number of iterations for the optimization. Maps to a command-line argument:
-max_iterations %d
.- modela pathlike object or string representing a file
Basename for the brik containing the SVM model. Maps to a command-line argument:
-model %s
.- nomodelmaska boolean
Flag to enable the omission of a mask file. Maps to a command-line argument:
-nomodelmask
.- num_threadsan integer (int or long)
Set number of threads. (Nipype default value:
1
)- optionsa unicode string
Additional options for SVM-light. Maps to a command-line argument:
%s
.- out_filea pathlike object or string representing a file
Output sum of weighted linear support vectors file name. Maps to a command-line argument:
-bucket %s
.- outputtype‘NIFTI’ or ‘AFNI’ or ‘NIFTI_GZ’
AFNI output filetype.
- trainlabelsa pathlike object or string representing an existing file
.1D labels corresponding to the stimulus paradigm for the training data. Maps to a command-line argument:
-trainlabels %s
.- w_outa boolean
Output sum of weighted linear support vectors. Maps to a command-line argument:
-wout
.
- alphasa pathlike object or string representing a file
Output alphas file name.
- modela pathlike object or string representing a file
Brik containing the SVM model file name.
- out_filea pathlike object or string representing a file
Sum of weighted linear support vectors file name.