SmartPlot

Analysis Functions

Use SmartPlot analysis tools to clean signals, correct baselines, fit peaks and trends, and turn selected ranges into results that can be plotted, styled, and exported.

Recommended analysis workflow

Most analysis actions work best after the figure layer is visible, because you can use the plot preview to judge whether the selected range and parameters make scientific sense.

  1. Import or prepare the data table.
  2. Create or select the target plot layer.
  3. Select the meaningful x-range or data region.
  4. Choose the analysis method from the Analyze menu.
  5. Adjust parameters while checking the preview.
  6. Apply the result and keep the original data available for comparison.
  7. Style, annotate, export, or save the project.

UI entry and key parameters

Select data or a figure layer -> Analyze -> Choose a method -> Set ROI and parameters -> Preview -> Apply

  • ROI / selected range
  • Method
  • Baseline or fitting model
  • Peak count
  • Smoothing window
  • Preview state
  • Result output

Analysis method guide

Baseline correction

Purpose: Remove slowly changing background from spectra or curves before comparing signal intensity.

Use when: Use it when the whole curve has drift, sloped background, or offset that should not be counted as signal.

Main settings

  • ROI or full range
  • Baseline model
  • Anchor points or endpoint behavior
  • Preview overlay

Workflow

  1. Select the curve.
  2. Choose Baseline Correction.
  3. Adjust the range and model.
  4. Preview the corrected curve.
  5. Apply as a derived result.

Shirley background correction

Purpose: Estimate XPS-style background under a peak region caused by inelastic scattering.

Use when: Use it for XPS spectra where the background rises or falls across the peak envelope.

Main settings

  • Peak ROI
  • Endpoint mode
  • Negative clipping
  • Corrected spectrum output

Workflow

  1. Import XPS data.
  2. Select the peak region.
  3. Apply Shirley correction.
  4. Check corrected baseline.
  5. Continue with peak fitting if needed.

Peak fitting

Purpose: Fit one or more peaks to estimate peak position, height, area, and width.

Use when: Use it when overlapping peaks need to be separated or reported quantitatively.

Main settings

  • Peak count
  • Peak model
  • Initial peak positions
  • Fit range
  • Residual preview

Workflow

  1. Correct the baseline first when needed.
  2. Choose the fit range.
  3. Set peak count and starting positions.
  4. Preview the fit and residual.
  5. Apply and label key peaks.

Trend fitting

Purpose: Fit a mathematical relationship such as linear, polynomial, exponential, or power-law trend.

Use when: Use it when the goal is to summarize a trend, calibration curve, or kinetic relationship.

Main settings

  • Model type
  • Fit range
  • Parameter display
  • Equation / R-squared label

Workflow

  1. Select paired X/Y data.
  2. Choose Trend Fitting.
  3. Pick a model that matches the science.
  4. Preview the curve.
  5. Add equation labels only when useful.

Smoothing

Purpose: Reduce visual noise while keeping the main curve shape readable.

Use when: Use it for noisy measured curves where the raw signal remains available for comparison.

Main settings

  • Window size
  • Method
  • Edge behavior
  • Preview against raw data

Workflow

  1. Select the curve.
  2. Choose Smoothing.
  3. Start with a small window.
  4. Compare with raw data.
  5. Apply only when features are not distorted.

Derivative and integration

Purpose: Extract rate-like changes or area-like quantities from selected regions.

Use when: Use derivatives to reveal slope changes, and integration to quantify area under a curve.

Main settings

  • Selected range
  • Derivative order
  • Integration baseline
  • Output table or curve

Workflow

  1. Select the range.
  2. Choose Derivative or Integration.
  3. Set parameters.
  4. Preview the result.
  5. Annotate the region if exporting the figure.

Before applying a result

  • Confirm the x-range contains the signal you intend to analyze.
  • Check that units and column roles are correct.
  • Preview the output and compare it with the raw curve.
  • Save the project before replacing or adding derived results.
  • Record important parameters when the figure is used in a paper or report.

What to do after analysis

  1. Keep raw and processed curves visually distinguishable.
  2. Add labels, reference lines, or annotations for fitted peaks and integration regions.
  3. Use consistent colors and legends before export.
  4. Save the project so the analysis state can be reopened later.

Notes / limitations

  • Analysis results depend on data quality, selected range, and method parameters.
  • Keep a copy of the original curve visible until the correction or fit is checked.
  • Use narrow, meaningful ranges for local operations such as peak fitting or integration.
  • Do not interpret smoothing as a replacement for raw data.