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fosanalysis
A framework to evaluate distributed fiber optic sensor data
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fosanalysis
A framework to evaluate distributed fiber optic sensor data
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Base class for algorithms to replace/remove missing data with plausible values. More...
Additional Inherited Members | |
 Public Member Functions inherited from fosanalysis.preprocessing.base.Base | |
| __init__ (self, *args, **kwargs) | |
| Construct an instance of the class. | |
| tuple | run (self, np.array x=None, np.array y=None, np.array z=None, bool make_copy=True, *args, **kwargs) |
Each preprocessing.Base object has a run() method to carry out the preprocessing task and return the preprocessed data. | |
| Public Member Functions inherited from fosanalysis.utils.base.Task | |
| __init__ (self, *args, **kwargs) | |
| Public Member Functions inherited from fosanalysis.utils.base.Base | |
| __init__ (self, *args, **kwargs) | |
| Construct the object and warn about unused/unknown arguments. | |
Base class for algorithms to replace/remove missing data with plausible values.
The sub-classes will take data containing dropouts (NaNs) and will return dropout-free data. This is done by replacing the dropouts by plausible values and/or removing dropouts. Because the shape of the arrays might be altered, run() expects and returns
x: array of the the positional data along the sensor.y: array of the time stamps, andz: array of the strain data. 
1.13.2