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==Importing / Exporting==


=Introduction=
[[faq_concatenate_multiple_files|How do I concatenate multiple files into a single DataSet?]]
Batch Statistical Process Control (BSPC) is the analysis of process data where the process is subdivided into "batches" (experiments) and may be further subdivided into "Steps" (sub-divisions of batch indicating processing segments or other divisions of batches). BSPC goes by many names, process monitoring, fault detection, anomaly detection, target detection. Methods generally rely on a model that describes normal and/or desirable operation. Often much is learned from the process of creating a model. Operating data is then compared to the process model to determine if the process condition is nominal.


=Getting Started=
[[faq_create_multivariate_image_from_separate_images|How do I create a multivariate image from separate images?]]
Data is derived directly from process data with the goal being to summarize high-dimensional data with a handful of factors that capture important directions in the data. Success is highly dependent upon the quantity and quality of process data.


Raw data is presumed to be in a 2 dimensional dataset with Variables as columns.
[[faq_export_PCA_scores_and_loadings_to_text_file|How do I export PCA scores and loadings to a text file (to read into MS Excel, for example)?]]


[[Image:bspc_data_config.png|200px|Data Configuration]]
[[faq_import_three-way_data|How do I import three-way data into Solo or PLS_Toolbox?]]


===Model Types===
[[faq_import_horiba_NGC_64bit |Why can't I import a Horiba NGC file on my 64-bit computer?]]


{| class="wikitable" border="1"
[[faq_SPCREADR_cant_read_multiple_files |Why can't SPCREADR read multiple files I've selected?]]
|+ BSPC Model Types
! Model !! Modes (Dimensions) !! Equal Length Batches !! Steps Aligned !! Data Shape !! Model Comments
|-
| Summary PCA || 2 || No || No || Batch x (Step/Summary) || PCA on summary statistics of variables over time
|-
| [[Batchmaturity|Batch Maturity]] || 2 || No || No || (Batch/Step) x Variable, Can have Y-Block to indicate maturity || PCA with heterogeneous confidence limits
|-
| [[Mpca|MPCA]] || 3 || Yes || Yes || Time (step) x Variable x Batch || Multiway PCA
|-
| [[Parafac|PARAFAC]] || 3 || Yes || Yes || Batch x Variable x Time (step) || Parallel Factor Analysis (multiway)
|-
| Summary PARAFAC || 3 || No || No ||  Batch x Step x Summary || PARAFAC on summary statistics of variables over time
|-
| [[Parafac2|PARAFAC2]] || 3 || No || No ||  Cell Array of Batches || PARAFAC with relaxed multiway structures (only available at PLS_Toolbox command line)
|}


See Also: [[batchmaturity|Batch Maturity]], [[mpca|MPCA]], [[MSPC_and_Identification_of_Finite_Impulse_Response_Models|MSPC]], [[parafac|PARAFAC]], [[parafac2|PARAFAC2]]
[[faq_some_EXCEL_files_fail_to_import |Why do some Excel files fail to import?]]


=Batch Processor Window=
==General==


The goal of the Batch Processor interface is to make it easier to assemble “batch” data for multivariate analysis. Because different analyses and conditions require different data manipulation, assembling data for batch analysis can be very difficult and [[media:Bspc_diagram_roadmap.png |‎ complicated]].
[[faq_PARALIND_in_PLS_Toolbox |Can I do PARALIND in PLS_Toolbox?]]


[[Image:BSPCGUI main.png| BSPC GUI]]
[[faq_install_on_more_than_one_PC | Can I install PLS_Toolbox (or Solo) on more than one PC, such as on my desktop and laptop computer?]]


The workflow of the interface flows from left to right. Loading data and choosing an Analysis Type will enable relevant tabs. Clicking the '''Next''' button will open the next enabled tab. Batches and steps are defined then alignment and summary information is added. When finished, "folded" data can be saved or exported to the [[Analysis GUI|analysis]] interface and or a model for folding new data can be saved.
[[faq_multiple_class_sets_together_in_SIMCA_PLSDA_LDA | Can I use multiple class sets (categorical variables) together in a SIMCA, PLSDA, or LDA model?]]


==Start==
[[faq_more_info_on_R_Squared_statistic | Can you give me more information on the R-Squared statistic?]]
Load, append, edit, and or clear data. Selecting the Analysis type will automatically enable/disable relevant tabs.


* Dropping data onto the status area will load data. If previously loaded data exists, a prompt for overwrite or augment will appear.
[[faq_how_RMSEC_and_RMSECV_related to R2Y_and_Q2Y_seen_other_software | How are RMSEC and RMSECV related to R2Y and Q2Y I see in other software?]]
** If augment is chosen, two options will be given, augment as new batch or not. Augment as new batch adds a class for the data being augmented otherwise a "normal" augment will occur and if the new dataset has a matching class it will be merged.
* Dragging and dropping multiple-selected (Excel) files from the system browser (e.g., Windows Explorer or Finder) will pre-augment the files and create a label indicating file name. This label can be used to identify batches in the '''Batches''' tab.
* Data can be edited in the [[DataSet Editor]] by clicking the '''Edit''' button. Editing will cause the model to be cleared.


==Batch==
[[faq_convergence_of_PARAFAC| Convergence of PARAFAC. How much variation between models is expected a particular PARAFAC is fit multiple times with the same settings?]]
Indicate source of Batch information in loaded dataset. Sources can be Class, Label, or Axisscale sets or a single Variable (column). If manually Loaded then a class is created. If the dataset contains a class with the default name of "BSPC Batch" then it will be automatically selected after loading.


* If variable is used, data for that column will be excluded (not deleted) so other mechanisms (preprocessing) can work.
[[faq_does_software_stop_working_if_maintenance_expires | Does the software stop working if my maintenance expires?]]
* Once Batches have been identified, one or more batches can be plotted in the lower plot.


==Steps==
[[faq_report_a_problem_with_PLS_Toolbox | How and where do I report a problem with PLS_Toolbox?]]
Steps (subdivisions of batches) can be indicated on the '''Steps''' tab. Steps can be created in the same manor as '''Batches''' or indicated manually.


Manual selection is done by selecting a primary variable and batch to align '''to''' then designating '''steps''' for the primary variable/batch. After the steps are set the [[batchalign]] function is used to "map" step location (as dataset class) for each batch.
[[faq_how_are_T_contributions_calculated | How are T-contributions calculated?]]


===Manually Selecting Steps===
[[faq_how_are_ROC_curves_calculated_for_PLSDA | How are the ROC curves calculated for PLSDA?]]


[[Image:bspc_manual_select.png|500px|Manual Selection Interface]]
[[faq_how_are_error_bars_calculated_regression_model | How are the error bars calculated for a regression model and can they be related to a confidence limit (confidence in the prediction)?]]


To manually select steps:
[[faq_improve_performance_with_PLS_Toolbx_and_Matlab_on_Mac | How can I improve performance with PLS_Toolbox and Matlab on the Mac platform?]]


# Select the variable and batch to use from the plot list boxes at the bottom of the interface. These will become the variable and batch to which all others are aligned to (designated by a "*" next to the list item.
[[faq_assign_classes_for_samples_in_a_DataSet | How do I assign classes for samples in a DataSet?]]
# Click the '''Select''' button and the interface will switch.
# Click the '''Add''' button to place the first step marker.
# Drag this marker to the first step location.
# Repeat until all steps are placed.
# Select different batch from list menu to display "aligned" step position.
# Adjust alignment algorithm as needed using toolbar button.
# Click check-mark button to finish and save steps.


===Selected Steps Menu===
[[faq_build_a_classification_model_from_class_set_other_than_the_first | How do I build a classification model from a class set other than the first?]]


[[Image:bspc_selected_steps.png|300px|]]
[[faq_choose_between_different_cross_validation_leave_out_options | How do I choose between the different cross-validation leave-out options?]]


Once steps have been designated, they will appear the '''Step Selection''' list. If one or more steps should be ignored they can be deselected in this menu. Selected steps will appear in the batch plot as solid green lines and unselected steps appear as red dashed lines.
[[faq_reference_Eigenvector| How do I cite/reference Eigenvector?]]


==Align==
[[faq_interpret_ROC_curves_and_Sensitivity_Specificity_plots_from_PLSDA | How do I interpret the ROC curves and Sensitivity / Specificity plots from PLSDA?]]


Methods that require equal length batches use the tools available on the '''Align''' tab from the [[batchalign]] function.
[[faq_make_DataSet_backwards_compatible | How do I make a DataSet backwards compatible?]]


[[Image:bspc_align_settings.png|Align Settings ]]
[[faq_obtain_or_use_recompilation_license_for_PLS_Toolbox | How do I obtain or use a recompilation license for PLS_Toolbox?]]


NOTE: In the image above, the alignment batch is Class 0 (the default) which has no members. This must be changed before alignment will work.
[[faq_use_custom_cross_validation_option | How do I use the "custom" cross-validation option?]]


# Select the type of alignment.
[[faq_out_of_memory_error_when_analyzing_data | I keep getting "out of memory" errors when analyzing my data. What can I do?]]
# Select the Batch and Variable or Load a vector.
# Select COW settings if using COW.
# Click Update Plot to see the results.


Alignment Types:
[[faq_java_lang_OutOfMemoryError| What can I do if I get a java.lang.OutOfMemoryError error?]]


* '''Linear''' - Linear interpolation based on selected variable and batch.
[[faq_why_get_negative_scores_when_all_modes_are_set_to_nonnegativity | Nonnegativity (PARAFAC, PARAFAC2, Tucker): Why do I get negative scores when all modes are set to nonnegativity?]]
* '''COW''' - [[cow|Correlation Optimized Warping]] with Alignment Settings values.
* '''Pad With NaN''' - Infill with NaN to make equal length.


Plots switch to displaying selected variables and batches pre aligned on top and post align on bottom. Must click '''Update Plots''' button to refresh plot.
[[faq_what_are_relative_contributions | What are "Relative Contributions"?]]


==Summarize==
[[faq_what_are_reduced_T^2_and_Q_Statistics | What are the "Reduced" T<sup>2</sup> and Q Statistics?]]


Available summary statistics as calculated by [[summary]] function.
[[faq_units_for_RMSEC_and_RMSECV_for_PLSDA | What are the units used for RMSEC and RMSECV when cross-validating PLSDA models?  Why do the cross-validation curves look strange for PLSDA?]]


[[Image:Bspc_summarize.png|Summary Options]]
[[faq_what_do_the_four_Fit_/_Unique_Fit_stats_mean_in_MCR_PARAFAC | What do the four Fit/Unique Fit statistics mean in MCR and PARAFAC models?]]


All stats summarize each column except for:
[[faq_internal_tests_used_to_select_suggested_number_of_PCs | What internal tests are used to select "suggested" number of PCs?]]
* '''Length''' Length of steps, single number.
* '''Five-Number Summary''' 10, 25, 50, 75, 90th percentile, 5 values per step.


For example with the [[Demonstration_Datasets | Dupont]] demo calibration data (dupont_cal), if you choose mean, std, slope, skewness, and length the size of your folded summary pca data will be:
[[faq_what_is_PLS1_v_PLS2_and_how_to_create_separate_PLS1_models_from_multi_column_y_block | What is PLS1 vs PLS2 and how do I create separate PLS1 models when I have a multi-column y-block?]]


10 variables x 4 stats + length = 41 values per step * 5 steps = 205 columns
[[faq_difference_between_a_loading_and_a_weighting | What is the difference between a loading and a weighting?]]


==Finish==
[[faq_why_some_axis_labels_and_titles_upside_down_in_MIA_Toolbox | Why are some axis labels and titles on my axes upside-down when I'm viewing images in MIA_Toolbox?]]


When completed there are 4 options:
[[faq_why_can't_I_recompile_PLS_Toolbox_functions | Why can't I recompile the PLS_Toolbox functions?]]


* Send data directly to a new [[Analysis]] window.
[[faq_why_get_missing_data_warning| Why do I get the warning/notice "Missing Data Found - Replacing with "best guess" from existing model. Results may be affected by this action."]]
* Save the data to the workspace.
 
* Save a model for future data application. NOTE: In some more complicated instances (loading outside information) the model may not be able to fully capture each step taken in the interface.
[[faq_why_PLS_Toolbox_have_a_boxplot_function_that_conflicts_with_Stats_Toolbox | Why does PLS_Toolbox have a "boxplot" function that conflicts with the Mathworks Statistics Toolbox function of the same name?]]
* Cancel and close the window.
 
[[faq_why_R2014b_give_error_cannot_convert_double_value_to_a_handle | Why does R2014b give me "Error using matlab.ui.Figure... Cannot convert double value to a handle" (or similar)?]]
 
==Command Line==
[[faq_specify_all_options_of_a_function_or_only_those_different_from_defaults | Do I have to specify all the options to a function or only the ones that are different from the defaults?]]
 
[[faq_how_are_Q_residuals_and_Hotellings_T2_calculated_in_PLS_models | How are the Q-residuals and Hotelling's T<sup>2</sup> values calculated for PLS models?]]
 
[[faq_how_to_automate_PCA_analysis_for_multiple_images  | How do I automate PCA analysis for multiple images?]]
 
[[faq_how_do_I_calculate_my_own_T2_and_Q_limits | How do I calculate my own T<sup>2</sup> and Q limits?]]
 
[[faq_how_do_manually_calculate_the_limits_for_scores | How do I manually calculate the limits for scores?]]
 
[[faq_how_do_I_calculate_scores_from_a_PLS_or_PLSDA_model | How do I calculate scores from a PLS or PLSDA model?]]
 
[[faq_how_do_I_change_the_default_options_for_a_function | How do I change the default options for a function?]]
 
[[faq_how_do_I_interpret_the_misclassification_results_reported_by_crossval | How do I interpret the Misclassification results reported by crossval?]]
 
[[faq_how_do_I_make_PlotGUI_send_plot_to_a_new_figure_and_not_overwrite_current_figure | How do I make PlotGUI send its plot to a new figure and not overwrite the current figure?]]
 
[[faq_how_do_I_retrieve_and_display_predictions_from_a_model_structure_in_command_window | How do I retrieve and display predictions from a model structure in the command window?]]
 
==Manual==
==GUI==
==Installation==
 
 
 
 
 
 
 
[[Category:FAQ]]

Revision as of 13:26, 5 December 2018

_

Importing / Exporting

How do I concatenate multiple files into a single DataSet?

How do I create a multivariate image from separate images?

How do I export PCA scores and loadings to a text file (to read into MS Excel, for example)?

How do I import three-way data into Solo or PLS_Toolbox?

Why can't I import a Horiba NGC file on my 64-bit computer?

Why can't SPCREADR read multiple files I've selected?

Why do some Excel files fail to import?

General

Can I do PARALIND in PLS_Toolbox?

Can I install PLS_Toolbox (or Solo) on more than one PC, such as on my desktop and laptop computer?

Can I use multiple class sets (categorical variables) together in a SIMCA, PLSDA, or LDA model?

Can you give me more information on the R-Squared statistic?

How are RMSEC and RMSECV related to R2Y and Q2Y I see in other software?

Convergence of PARAFAC. How much variation between models is expected a particular PARAFAC is fit multiple times with the same settings?

Does the software stop working if my maintenance expires?

How and where do I report a problem with PLS_Toolbox?

How are T-contributions calculated?

How are the ROC curves calculated for PLSDA?

How are the error bars calculated for a regression model and can they be related to a confidence limit (confidence in the prediction)?

How can I improve performance with PLS_Toolbox and Matlab on the Mac platform?

How do I assign classes for samples in a DataSet?

How do I build a classification model from a class set other than the first?

How do I choose between the different cross-validation leave-out options?

How do I cite/reference Eigenvector?

How do I interpret the ROC curves and Sensitivity / Specificity plots from PLSDA?

How do I make a DataSet backwards compatible?

How do I obtain or use a recompilation license for PLS_Toolbox?

How do I use the "custom" cross-validation option?

I keep getting "out of memory" errors when analyzing my data. What can I do?

What can I do if I get a java.lang.OutOfMemoryError error?

Nonnegativity (PARAFAC, PARAFAC2, Tucker): Why do I get negative scores when all modes are set to nonnegativity?

What are "Relative Contributions"?

What are the "Reduced" T2 and Q Statistics?

What are the units used for RMSEC and RMSECV when cross-validating PLSDA models? Why do the cross-validation curves look strange for PLSDA?

What do the four Fit/Unique Fit statistics mean in MCR and PARAFAC models?

What internal tests are used to select "suggested" number of PCs?

What is PLS1 vs PLS2 and how do I create separate PLS1 models when I have a multi-column y-block?

What is the difference between a loading and a weighting?

Why are some axis labels and titles on my axes upside-down when I'm viewing images in MIA_Toolbox?

Why can't I recompile the PLS_Toolbox functions?

Why do I get the warning/notice "Missing Data Found - Replacing with "best guess" from existing model. Results may be affected by this action."

Why does PLS_Toolbox have a "boxplot" function that conflicts with the Mathworks Statistics Toolbox function of the same name?

Why does R2014b give me "Error using matlab.ui.Figure... Cannot convert double value to a handle" (or similar)?

Command Line

Do I have to specify all the options to a function or only the ones that are different from the defaults?

How are the Q-residuals and Hotelling's T2 values calculated for PLS models?

How do I automate PCA analysis for multiple images?

How do I calculate my own T2 and Q limits?

How do I manually calculate the limits for scores?

How do I calculate scores from a PLS or PLSDA model?

How do I change the default options for a function?

How do I interpret the Misclassification results reported by crossval?

How do I make PlotGUI send its plot to a new figure and not overwrite the current figure?

How do I retrieve and display predictions from a model structure in the command window?

Manual

GUI

Installation

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