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()
- Mandatory Inputs:
in_file (a 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
.model (a string) – Modname is the basename for the brik containing the SVM model. Maps to a command-line argument:
-model %s
.- Optional Inputs:
args (a string) – Additional parameters to the command. Maps to a command-line argument:
%s
.classout (a boolean) – Flag to specify that pname files should be integer-valued, corresponding to class category decisions. Maps to a command-line argument:
-classout
.environ (a 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:
{}
)multiclass (a boolean) – Specifies multiclass algorithm for classification. Maps to a command-line argument:
-multiclass %s
.nodetrend (a boolean) – Flag to specify that pname files should not be linearly detrended. Maps to a command-line argument:
-nodetrend
.nopredcensord (a boolean) – Flag to prevent writing predicted values for censored time-points. Maps to a command-line argument:
-nopredcensord
.num_threads (an integer) – Set number of threads. (Nipype default value:
1
)options (a string) – Additional options for SVM-light. Maps to a command-line argument:
%s
.out_file (a 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.
testlabels (a 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
.- Outputs:
out_file (a 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()
- Mandatory Inputs:
in_file (a 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
.ttype (a string) – Tname: classification or regression. Maps to a command-line argument:
-type %s
.- Optional Inputs:
alphas (a pathlike object or string representing a file) – Output alphas file name. Maps to a command-line argument:
-alpha %s
.args (a string) – Additional parameters to the command. Maps to a command-line argument:
%s
.censor (a 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
.environ (a 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:
{}
)kernel (a string) – String specifying type of kernel function:linear, polynomial, rbf, sigmoid. Maps to a command-line argument:
-kernel %s
.mask (a 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_iterations (an integer) – Specify the maximum number of iterations for the optimization. Maps to a command-line argument:
-max_iterations %d
.model (a pathlike object or string representing a file) – Basename for the brik containing the SVM model. Maps to a command-line argument:
-model %s
.nomodelmask (a boolean) – Flag to enable the omission of a mask file. Maps to a command-line argument:
-nomodelmask
.num_threads (an integer) – Set number of threads. (Nipype default value:
1
)options (a string) – Additional options for SVM-light. Maps to a command-line argument:
%s
.out_file (a 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.
trainlabels (a 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_out (a boolean) – Output sum of weighted linear support vectors. Maps to a command-line argument:
-wout
.- Outputs:
alphas (a pathlike object or string representing a file) – Output alphas file name.
model (a pathlike object or string representing a file) – Brik containing the SVM model file name.
out_file (a pathlike object or string representing a file) – Sum of weighted linear support vectors file name.