Transformation PluginsΒΆ

Data transformation plugins provide functionality to transform input data from one scale/space to another. The most basic example is a logarithmic transform which converts linear data to a logarithmic scale. The registration method for these plugins looks like the following:

def transform_register():
      return (transformMethod, MethodTransformScaleClass)

The transformMethod reference performs the actual transformation of user data. The MethodTransformScaleClass is an instance of the ScaleBase class found in the matplotlib.scale module. It is not required, so the register method can simply place None in the second slot of the tuple. However, if you wish to provide a plugin that is also automatically applicable to graphs/plots, then you will need to provide a subclass of ScaleBase. An example of creating your own scale for plots is available at the matplotlib website. If you provide this class, FIND will automatically register your scale with the matplotlib engine, and it will be available to specify for any matplotlib plot that accepts scale requests.

The transformMethod method signature and doc string should look like the following:

def transformMethod(data, **kwargs):
   string-ID; transformMethod name; Method description string
   return transformed_data

The data parameter is (as with other plugins) an m x n array (numpy ndarray) with m data points (events), and n dimensions (channels). The **kwargs parameter is a dictionary containing options for use by the transform method. For example, FIND’s built-in log transform accepts base and min_clip parameters indicating, respectively, the base of the log transform (2, 10, e) and the lower end the data should be clipped to when negative values are encountered (default: 10e-5).

Finally, as mentioned in the section on Graphing Plugins, the internal transforms package provides within its methods module, the means for any FIND code to use registered transforms. Specifically, the module provides a getMethod(strID) method that returns the method specified by the string identifier of the transformation method/plugin. So to apply a log transform to your data with the built-in log method you might use the following lines:

import transforms.methods as tm
logData = tm.getMethod('log')(data, base=10, min_clip=10e-8)