fab.preprocessing.filters

 1from .preprocessor import preprocessor
 2import numpy as np
 3
 4@preprocessor
 5def integrate(data, dims=None): 
 6    """ Returns sum of data along dimension dims"""         
 7    return data.sum(dim=dims)
 8
 9@preprocessor
10def mean(data, dims=None):      
11    """ Returns mean of data along dimension dims"""  
12    return data.mean(dim=dims)
13
14@preprocessor
15def normalize(data, method='L2', dims=None): 
16    """ Normalizes data according to method
17        
18        Args:
19            method: one of "L2", "area" or "max". Defaults to "L2".
20                Determines how the normalization factor is calculated
21                - "L2": square root of sum of squared values
22                - "area": area under the curve 
23                - "max": largest absolute value
24    """
25    match method:
26        case 'L2':
27            factor = np.sqrt((data**2).sum(dim=dims))
28        case 'area':
29            factor = np.abs(data).sum(dim=dims)
30        case 'max':
31            factor = np.abs(data).max(dim=dims)
32    return data / factor
33
34@preprocessor
35def moving_avg(data, dim=None, window=10):      
36    """ Returns moving average of data along dimension dims.
37        The window parameter determines the window size in samples."""
38    return data.rolling(**{dim: window}).mean()
39    
40@preprocessor
41def rescale(data, factor=1, offset=0):   
42    """ returnns data*factor + offset """     
43    return data*factor + offset
44
45@preprocessor
46def mathexpr(data, expr):
47    ''' Evaluates a string as a mathematical expression
48    
49        Args: 
50            expr: A string representing a mathematical expression
51                to be evaluated on the data. To refer to the 
52                loaded data in the expression, use the symbol `x`.
53                Numpy and xarray can be accessed as `np` and `xr`
54                respectively.
55        
56        Examples:
57            To calculate the the inverse of the data, use:
58            `__preprocess__ = [ {__name__='fab.preprocessing.mathexpr', expr= "1/x"`
59
60            The maximum value can be calcluded by:
61            `__preprocess__ = [ {__name__='fab.preprocessing.mathexpr', expr= "x.max()"`
62    '''
63    import asteval
64    import numpy as np
65    import xarray as xr
66
67    interp = asteval.Interpreter(minimal=True, 
68                                 usersyms={'x': data,
69                                           'np' : np,
70                                           'xr' : xr})
71    output = interp.eval(expr, raise_errors=True)
72    
73    if not (isinstance(output, xr.DataArray) or isinstance(output, xr.Dataset)):
74        raise ValueError("mathexpr preprocessor must return a xr.DataArray or xr.Dataset")
75    return output