Preprocessiterator: Difference between revisions
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imported>Scott (Created page with "===Purpose=== Create array of preprocessing combinations. ===Synopsis=== : pplist = preprocessiterator(inpp);%Shows gui for iterator settings. : pplist = preprocessiterator...") |
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===Purpose=== | ===Purpose=== | ||
Create array of preprocessing combinations. | Create array of preprocessing combinations for use with [[modeloptimizer]]. | ||
===Synopsis=== | ===Synopsis=== | ||
| Line 10: | Line 10: | ||
===Description=== | ===Description=== | ||
For given input preprocessing structure (inpp), create combinations of preprocessing based on PP methods that can be iterated over using simple min/steps/max values. If iteration matrix (imatrix) is not provided a window will appear allowing user to specify iterations. | For given input preprocessing structure (inpp), create combinations of preprocessing based on PP methods that can be iterated over using simple min/steps/max values. If iteration matrix (imatrix) is not provided a window will appear allowing user to specify iterations. Some of the methods are discussed in [[Advanced_Preprocessing:_Noise,_Offset,_and_Baseline_Filtering | Advanced Preprocessing]]. | ||
Supported Preprocessing Methods: | Supported Preprocessing Methods: | ||
# Derivative | # Derivative ([[Savgol]]) | ||
# Normalize | # [[Normaliz | Normalize]] | ||
# GLS Weighting | # [[glsw | GLS Weighting]] | ||
# Whittaker | # [[glsw | EPO Filter]] | ||
# Gapsegment | # [[wlsbaseline | Baseline (Automatic Whittaker Filter)]] | ||
# | # [[baseline | Detrend]] | ||
# Poisson ( | # [[Gapsegment | Gap Segment Derivative]] | ||
# [[Auto | Autoscale]] | |||
# [[poissonscale | Poisson (Sqrt Mean) Scaling]] | |||
Iterator Matrix (imatrix) example. Cell array n x 9 with following | Iterator Matrix (imatrix) example. Cell array n x 9 with following columns: | ||
# | # Relative Index - Relative index of given method. | ||
# | # Preprocess Name - Name of preprocess method. | ||
# | # Parameter Name - Name of .userdata parameter. | ||
# | # Parameter Variable - Name of .userdata field. | ||
# | # Data Type - Allowed values for Min and Max. | ||
# Min - First value. | # Min - First value. | ||
# | # Step - Size of interval of each step. | ||
# Max - Last value. | # Max - Last value. | ||
# | # Use Log - Use a log scale to create values. | ||
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NOTE: If the original preprocess structure contains 2 Normalize steps, the second Normalize will be iterated over. | NOTE: If the original preprocess structure contains 2 Normalize steps, the second Normalize will be iterated over. | ||
===See Also=== | ===See Also=== | ||
[[preprocess]], [[preprouser]] | [[preprocess]], [[preprouser]] | ||
Latest revision as of 10:37, 18 October 2013
Purpose
Create array of preprocessing combinations for use with modeloptimizer.
Synopsis
- pplist = preprocessiterator(inpp);%Shows gui for iterator settings.
- pplist = preprocessiterator(inpp,imatrix);%Command line call.
Description
For given input preprocessing structure (inpp), create combinations of preprocessing based on PP methods that can be iterated over using simple min/steps/max values. If iteration matrix (imatrix) is not provided a window will appear allowing user to specify iterations. Some of the methods are discussed in Advanced Preprocessing.
Supported Preprocessing Methods:
- Derivative (Savgol)
- Normalize
- GLS Weighting
- EPO Filter
- Baseline (Automatic Whittaker Filter)
- Detrend
- Gap Segment Derivative
- Autoscale
- Poisson (Sqrt Mean) Scaling
Iterator Matrix (imatrix) example. Cell array n x 9 with following columns:
- Relative Index - Relative index of given method.
- Preprocess Name - Name of preprocess method.
- Parameter Name - Name of .userdata parameter.
- Parameter Variable - Name of .userdata field.
- Data Type - Allowed values for Min and Max.
- Min - First value.
- Step - Size of interval of each step.
- Max - Last value.
- Use Log - Use a log scale to create values.
inpp = preprocess('default','mean center','derivative','normalize', 'mean center','sqmnsc','normalize','log10','whittaker');
imatrix = { 1 'derivative' 'Width' 'width' 'int(1:inf)' 1 1 1 0;
1 'derivative' 'Derivative' 'deriv' 'int(1:inf)' 1 1 1 0;...
1 'derivative' 'Order' 'order' 'int(1:inf)' 1 1 1 0;
2 'Normalize' 'Norm Type' 'normtype' 'int(1:inf)' 1 2 2 0;...
1 'GLS Weighting' 'Alpha' 'a' 'float(0:inf)' 1 1 1 1};
pplist = preprocessiterator(inpp,imatrix)
NOTE: If the original preprocess structure contains 2 Normalize steps, the second Normalize will be iterated over.