# Tutorial

# Choosing your level of expertise

Depending on the tasks that you are working on and on your level of expirience with preprocessing and analizing Raman spectroscopic data, you should select one of the following expertise levels:

Expertise level menu

Level 1 is the most suitable for the test and identification tasks. This expertise level allows to import the *.rspa model file, import the data (see Data Input) and perform the prediction in a single click without adjusting any parameters. For more details see Predicting test data.

Level 3, additionally to the functionality of a first level, makes possible to preprocess training data and build a model on the training data with preset parameters. Either default parameters or parameters saved as a “.txt” file may be applied to the data. Only few options, such as presence of 2 spectra for each point (typical for BPE data) and a validation type (batch-out or 10-fold cross-validation) can be changed at this level of expertise.

Level 5 (default). Besides the options available on previous levels, this level provides controls for tuning spectral ranges at different steps of preprocessing routine and a number of components used after the dimension reduction. Starting from this level of expertise, a step-by step execution of the data processing workflow is possible.

Level 7 makes possible to choose algorithms for baseline correction, normalization and model construction. Advanced functionality becomes available to a user at this level, including a possibility to control data quality by setting various thresholds and averaging spectra according to a specified grouping.

Level 9 makes all the parameters, accessible. For example, advanced parameters for calibration step, or a peak range for integrated intensity thresholding. At the model construction step, number of epochs for CNN dimension reduction, SVM cost and kernel become available.

# Analyzing training data

The data analysis functionality is available for expertise levels above 1 (see Choosing your level of expertise). If a lower experience level is set, only the testing is possible (see Predicting test data).

Stepper

To import the training data, find a panel named “Training data”, click Import --> Training data and select a pre-structured ZIP file (see Data Input).

To analyze data in a single click, use Analyze button on a left panel named "Training data". After clicking the button the analysis process will begin step by step and the results for each data processing step can be accessed by clicking on the icons at the stepper panel at the top of the program window:

Stepper

The summary of the analysis can be also accessed in a form of a complete report by clicking at the “Report” icon at the stepper panel. Other results can be exported through the “Export” menu at “Training data” panel.

Specific pre-set parameters can be imported as a text file through "Import -> Parameters". Furthermore, parameters can be manually adjusted for each data processing step. A set of the adjustable parameters depends on the selected expertise level (see Choosing your level of expertise).

# Predicting test data

To import the test data, find a panel named “Test data”, click Import  Test data and select a pre-structured ZIP file (see Data Input)

Stepper

The test data predictions can be generated using either a model constructed from training data or using a pre-stored model. How to construct the model is described in Analyzing training data. To import a pre-built model, find a panel named “Test data”, click Import  Model and select *.rspa file. The pretreatment and the preprocessing of the test data are performed with the same parameters that were used for the training data. When a pre-stored model is used, these parameters are embedded in the model and cannot be changed by user.

After importing or generating the model and importing the test data, simply click “Predict” at the “Test data” panel. To see more details, please click at the icons “Test data” and “Prediction” at upper stepper panel.

Stepper

The summary for preprocessed data can be found in a form of a report. Other results can be exported through the “Export” menu at “Test data” panel.

# Interactive plots

To change the styles of the graphs before saving and highlight the information of interest, the following tools can be used:

  1. Zoom: click on the canvas and hold to expand area that should be zoomed in. Work in both vertical and horizontal directions. Double click – reset to initial scale.

  2. Lock one spectrum: click on one spectrum to highlight it (R.terrigena DSM 2687) and click on the empty space on the canvas to unlock it.

    Interactive plots

  3. Remove/Add spectra: hover on Legend area and use checkboxes to hide/add spectra

  4. Legend: hover on spectrum label to highlight it on the canvas. Come back to the canvas to examine value in a hovered point.

  5. Top toolbar functionality:

Icon Action
Save plot as a PNG file Save high quality image in a PNG format.
Save plot as a CSV file Save data in a CSV format to plot it by yourself in a different program
Add offset on Y-axis Add offset on Y-axis to better distinguish nearby spectra
Colored area visibility Make invisible a colored area on the canvas which shows selected wavenumbers range
SD visibility Add/remove standard deviation
Background grid Add/remove grid on the background