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Update of SA-xTRCA algorithm #89
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I added the SA-xTRCA class in cca.py and implemented a demo for phase alignment and classification using SA-xTRCA. In addition, I provided a portion of the experimental data (from 10 subjects) used in my research, which is included in the SA-xTRCA_demo folder. All data files are in .mat format.
Modified some comments
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请查看review内容,需要进行修改
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如果需要提交数据集,需要创建一个数据集类,请参考metabci/brainda/datasets下的数据集构建方式,继承BaseDataset构建一个数据集。数据集原始数据可以上传到zendo平台https://zenodo.org/。
请麻烦修改,感谢!
self.T_min = 1 | ||
self.t_i = [] | ||
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def trca_kernel(self, X: ndarray): |
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该文件存在一个_trac_kernel函数,请考虑服用。观察到还需要对特征值进行一定操作,如果无法复用,请修改类函数名。
labels = self.classes_[np.argmax(feat, axis=-1)] | ||
return labels | ||
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def trca_train(self, X: ndarray, y: ndarray): |
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这个函数和trca_kernel是否存在重复?
I added the SA-xTRCA class in cca.py and implemented a demo for phase alignment and classification using SA-xTRCA. In addition, I provided a portion of the experimental data (from 10 subjects) used in my research, which is included in the SA-xTRCA_demo folder. All data files are in .mat format.