The peak detection appplication is a browser-based framework for automatically detecting peaks in 1-D XRD data set. The user can choose from several different algorithms to guide detection, which differ in the amount of user intervention vs. automation that can be performed.
Currently, the 1D XRD demo accepts a 2 column comma-separated (.csv) files, with no header row, for example
1.502500072169232093e+00,1.333536761775019386e+01
1.507500072883772191e+00,1.558678643552360654e+01
1.512500073598311845e+00,1.727255455621030933e+01
1.517500074312851721e+00,1.817530381724509425e+01
While this application was designed for 1-D XRD data, any 1-D dataset can benefit from this implementation as long as its peaks present a Gaussian- or Voigt-like shape.
The 1D XRD application lets you provide a file, label detect peaks, and store the those peaks as features in the SplashML database.
Steps:
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Click on the "Select Files" link
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Browse to a file on your file system.
The application displays a plot of the file, with two panes, the full plot and plot with selectors to zoom into a particular section
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Optional: select Apply Baseline to Peak Fitting
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Choose a peak detection method:
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Enter a tag name. This name will be used to generate the names of the tags added to SplashML.
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Choose the Peak Shape.
The application displays the detected peaks in the graph and Current Tags table. Each tag in the Current Tags can be saved into SplashML as a new tag, with the Peak location (midpoint and amplitude) and the estimated Full Width Half Max of the peak. A color was assigned to each tag, which matches the color in the graph.
Additionally, the plot displays the unfit, fit, residual, and, if selected, baseline curves.
One can now Download Tags, which downloads the table of detected peaks as a csv file or Save Tags to SplashML, which inserts them into SplashML.
A future feature which allows the user to bulk detect peaks on a number of files all at once.