Signal1D Tools¶
The methods described in this section are only available for one-dimensional signals in the Signal1D class.
Cropping¶
The crop_signal1D()
crops the
spectral energy range in-place. If no parameter is passed, a user interface
appears in which to crop the one dimensional signal. For example:
s = hs.datasets.example_signals.EDS_TEM_Spectrum()
s.crop_signal1D(5, 15) # s is cropped in place
Additionally, cropping in HyperSpy can be performed using the Signal indexing syntax. For example, the following crops a spectrum to the 5 keV-15 keV region:
s = hs.datasets.example_signals.EDS_TEM_Spectrum()
sc = s.isig[5.:15.] # s is not cropped, sc is a "cropped view" of s
It is possible to crop interactively using Region Of Interest (ROI). For example:
s = hs.datasets.example_signals.EDS_TEM_Spectrum()
roi = hs.roi.SpanROI(left=5, right=15)
s.plot()
sc = roi.interactive(s)
Background removal¶
The remove_background()
method provides
background removal capabilities through both a CLI and a GUI. Current
background type supported are power law, offset, polynomial and gaussian.
By default the background is estimated, but a full fit can also be used.
The full fit is more accurate, but slower.
Calibration¶
The calibrate()
method provides a user
interface to calibrate the spectral axis.
Alignment¶
The following methods use sub-pixel cross-correlation or user-provided shifts to align spectra. They support applying the same transformation to multiple files.
Integration¶
Deprecated since version 1.3: integrate_in_range()
.
It will be removed in 2.0. Use integrate1D()
instead, possibly in combination with a Region Of Interest (ROI) if interactivity
is required.
Data smoothing¶
The following methods (that include user interfaces when no arguments are passed) can perform data smoothing with different algorithms:
smooth_lowess()
(requiresstatsmodels
to be installed)smooth_tv()
smooth_savitzky_golay()
Spike removal¶
New in version 0.5.
spikes_removal_tool()
provides an user
interface to remove spikes from spectra.
Peak finding¶
A peak finding routine based on the work of T. O’Haver is available in HyperSpy
through the find_peaks1D_ohaver()
method.
Other methods¶
- Interpolate the spectra in between two positions
interpolate_in_between()
- Convolve the spectra with a gaussian
gaussian_filter()
- Apply a hanning taper to the spectra
hanning_taper()