Comments (2)
Turns out this is the result of the underlying data, the edge jump happens to be relatively high in the background. This motivated the development of a second form of masking, named (contrast mask). @WilliamJudge94 is developing this.
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Code was completed with 0646af2, but the documentation needs a little cleaning up. 40f9779 added documentation on how to use the contrast mask, and lists one drawback of the absorption edge masking approach. We should list the benefits of XAS edge masking and the benefits and drawbacks of contrast masking.
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Related Issues (20)
- Reconcile parameters names for giving an HDF filename HOT 1
- Make sure a pip install actually works
- Merge fit_kedge with fit_spectra HOT 1
- Make sure the xanes_math.kedge_jump handles timesteps properly
- xp.XanesFrameset.line_spectra does not work and does not have a test HOT 1
- Apply merge maps to master xanespy HOT 1
- Add support for BNL FXI beamline data HOT 1
- write tests for ``TxmStore.validate_parent_group()``
- nanosurveryor.py has no logging import
- Standardize the parameters for the various importer functions
- Calculate a K-edge mask when there are NaN's in the data
- Make the TXM store try a default HDF parent_group if given None
- Make sure all the importers can accept Path objects
- Reconcile parameter naming for "timestep". HOT 1
- Rename fs.plot_xanes_spectrum to fs.plot_spectrum HOT 1
- no module named sklearn HOT 1
- Standardize the use of ``edge_filter`` and ``edge_filter_kw`` for all methods. HOT 2
- Allow XanesFrameset to accept an edge as either an object or a class HOT 1
- Xanespy K edge mask fails with (222, 207) imaginary numbers
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