nmrglue.process.pipe_proc.lp
- nmrglue.process.pipe_proc.lp(dic, data, pred='default', x1='default', xn='default', ord=8, mode='f', append='after', bad_roots='auto', mirror=None, fix_mode='on', method='tls')[source]
Linear Prediction
- Parameters
- dicdict
Dictionary of NMRPipe parameters.
- datandarray
Array of NMR data.
- predint
Number of points to predict, “default” chooses the vector size for forward prediction, 1 for backward prediction
- x1int or ‘default’
First point in 1D vector to use to extract LP filter. ‘default’ will use the first or last point depending on the mode.
- xnint or ‘default’
Last point in 1D vector to use to extract LP filter. ‘default’ will use the first or last point depending on the mode.
- ordint
Prediction order, number of LP coefficients used in prediction.
- mode{‘f’, ‘b’, ‘fb’}
Mode to generate LP filter, ‘f’ for forward,’b’ for backward, ‘fb’ for forward-backward.
- append{‘before’ or ‘after’}
Location to append predicted data, ‘before’ or ‘after’ the existing data.
- bad_roots {‘incr’, ‘decr’, None, ‘auto’} :
Type of roots which are will be marked as bad and stabilized. Choices are ‘incr’ for increasing roots, ‘decr’ for decreasing roots, or None for not root stabilization. The default ‘auto’ will set this parameter based upon the LP mode parameter: ‘f’ and ‘fb’ will results in an ‘incr’ parameter. ‘b’ in ‘decr’.
- mirror{‘90-180’, ‘0-0’, None}
Mirror mode, option are ‘90-180’ for a one point shifted mirror image, ‘0-0’ for an exact mirror image, and None for no mirror imaging of the data.
- fix_mode{‘on’, ‘reflect’}
Method used to stabilize bad roots, ‘on’ moves bad roots onto the unit circle, ‘reflect’ reflect bad roots across the unit circle.
- method{‘svd’, ‘qr’, ‘choleskey’, ‘tls’}
Method to use to calculate the LP filter.
- Returns
- ndicdict
Dictionary of updated NMRPipe parameters.
- ndatandarray
Array of NMR data with linear prediction applied.
Notes
The results from this function do not match NMRPipe’s LP function. Also some additional parameter and different parameter in this function.