Release Notes Version 8 0

Version 8.0 of PLS_Toolbox and Solo was released in June, 2015.

For general product information, see PLS_Toolbox Product Page. For information on Solo, see Solo Product Page.

(back to Release Notes PLS Toolbox and Solo)

New Features in Solo and PLS_Toolbox

Multi-Block, and Model and Data Fusion Tool

Multiblock Tool - Interface to view, manipulate, and join data. Can be used for data and model fusion, or multi-block modeling.

• Join multiple blocks of variables measured on the same samples (alignment based on labels, axis scales, or size).
• Automatically align and join time-based blocks of data (based on time axis scale).
• Optionally build models on one or more blocks and join outputs from those blocks (model fusion).
• Choose and apply block-specific preprocessing before joining.
• Save multiblock model to use to join new data, including application of defined preprocessing and models.
• After building model from joined data, Analysis automatically splits loadings into component block segments for ease of interpretation.

Analysis and Models

• MLSCA - Multi-level simultaneous component analysis method added.
• ASCA - Add model of residuals to help assess fit.

• Shortcuts to Data Fusion methods Multiblock Tool and Hierarchical Model Builder
• Re-designed Analysis and Preprocessing menus for ease-of-use and consistency.
• ANN now supports custom cross-validation.
• PLSDA variance captured plot now available.
• Add "Reduced" Q and T^2 statistics for all factor-based models (normalized to confidence limit.)
• Add quick-access to Genetic Algorithm variable selection from the iPLS, iPLSDA, and Stepwise Selection interfaces.
• confusionmatrix - Report additional quantities for each class: count, classification error, precision and F1 score.
  • Standardize terminology: TP = count, TPR = proportion (rate) for confusion matrix quantities, and labels shown.
• simca Better handling of full-rank PCA sub-models (where Q residuals are zero.)
• Nearest neighbor score distance now normalized to maximum calibration value (standard practice for inlier tests.)
• "Data" drill-down button in scores and loadings plots now automatically drills into preprocessed data and X_hat (fit, residuals) data if any plots of those types are already open.
• Add Q2Y and R2Y to statistics calculated for models (for comparison to other software)

Plotting

• Additional context-menu options for managing line width and symbol size.
• Add quick access to class symbol sets in context menu.
• Significantly faster selection display and "linking" between figures.
• Connect Classes and View Classes buttons now have drop-down menus to display options.
• Added Compress X-axis Gaps (click for example) toolbar button to remove gaps caused by excluded variables or samples.
• Improve handling of zoom status in newer versions of Matlab.
• Better handling of font sizes on different screen sizes and platforms.
• Fix shifting control position issues with newer versions of Matlab.

Importers

• Automatic reconciliation of mixed axis scales when importing multiple files (using matchvars). Data will automatically include as much of the original data as possible.
• omnicreadr New importer for OMNICix HDF5 image files.
• hjyreadr Support for importing on 64-bit Windows systems and for new LabSpec file formats.
• textreadr and xlsreadr Improved handling of multiple file import using graphically-selected parsing options. Options selected on first file/sheet are now used on ALL subsequent files/sheets.

Preprocessing

• glog Generalized Log Transform added to preprocessing options.
• pqnorm Probabilistic Quotient Normalization added to preprocessing options.
• Group Scale New features:
  • Added option to disable mean centering of block (scale only).
  • Added easier selection of class set to use when identifying blocks.
• Added "Block Variance Scaling" as new method based on gscale
• EEM Flitering (flucut) New features:
  • Added better Raman and Rayleigh filtering using interpolation (now the default).
  • Added support for blank subtraction (choose one sample as a blank).
• glsw Clarified how ELS/EMM and EPO options are related
• Add support for handling missing data in both normaliz and mscorr (median only).

Other Interfaces

• Model Optimizer - Better handling of numeric data in comparison table, additional statistics, and improved handling of include field.
  • Add better support for model groupings in PLSDA and SVMDA within model optimizer.
  • Add support for more LWR options
  • LWR models: Add "Survey" button to Analysis window to automatically survey over a range of "Local Points"
• Better help integration with newer version of Matlab.
• Hierarchical Model Builder - Add vertical scrolling.
• TrendTool Add "maximum between" option for markers: returns the maximum value between two markers (better identifies peak value when the peak shape may change)

Model Objects

• Build and change history now captured in history field of Model Object.
• Add .scoredistance and .esterror as virtual properties for models. These properties can now be accessed directly from models in PLS_Toolbox or Solo_Predictor scripts.

New Command-line Features and Functions

Misc New Functions

• eemoutlier - New function for automatically removing outliers in fluorescence PARAFAC models.
• glog Generalized Log variable scaling.
• kurtosis - Added kurtosis statistic function to distribution fitting toolbox.
• mlsca Multi-level Simultaneous Component Analysis.
• multiblock Create or apply a multiblock model for joining data.
• pqnorm Probability Quotient Normalization for samples.
• skewness - Added skewness statistic function to distribution fitting toolbox.

Command-Line Changes

• als - Sort components by variance captured (if no constraints otherwise defining order).
• comparemodels - Report the mean (class count weighted) of Classification Error, Precision, F1 Score for classification models.
• confusionmatrix - Report additional quantities for each class: count, classification error, precision and F1 score..
  • Standardize terminology: TP = count, TPR = proportion (rate) for confusion matrix quantities, and labels shown.
• cov_cv - Changed from SVDS to SVD to improve behavior with nearly-rank-deficient cases.
• crossval - Better handling of cross-validation when using PLSDA.
  • Convert plsda regression method input to be 'sim' (to speed it up).
  • Recognize when user has passed single-column (either logical or class) and force it to be multi-column logical.
• histaxes - Fix for when NaN's are present in data.
• jmlimit - Better handle degenerate cases when multiple confidence levels are requested (return VECTOR of zeros instead of single zero).
• matchvars - Add option to input a cell array of dataset objects which will be joined after reconciling variables to make the least changes in data.
• mdcheck - Allow use of KNN as data replacement method (replace missing data with data from sample(s) which are closest).