HyperSpy User Guide

• Introduction
  • What is HyperSpy
  • HyperSpy extensions
  • Our vision
  • HyperSpy’s character
• What’s new
  • Current Version
• Changelog
  • Previous Versions
• Installing HyperSpy
  • HyperSpy Bundle for Microsoft Windows
  • Quick instructions to install HyperSpy using Anaconda (Linux, MacOs, Windows)
  • Install using Python installers
  • Install from a binary
  • Install from source
  • Installing the required libraries
  • Known issues
• Getting started
  • Starting Python in Windows
  • Starting Python in Linux and MacOS
  • Starting HyperSpy in the notebook (or terminal)
  • Getting help
  • Autocompletion
  • Loading data
  • “Loading” data from a numpy array
  • Loading example data and data from online databases
  • The navigation and signal dimensions
  • Setting axis properties
  • Saving Files
  • Accessing and setting the metadata
  • Configuring HyperSpy
  • Messages log
• Tools: the Signal class
  • The Signal class and its subclasses
  • Signal initialization
  • The navigation and signal dimensions
  • Binned and unbinned signals
  • Generic tools
  • Basic statistical analysis
  • Setting the noise properties
  • Speeding up operations
  • Interactive operations
  • Region Of Interest (ROI)
  • Handling complex data
• Signal1D Tools
  • Cropping
  • Background removal
  • Calibration
  • Alignment
  • Integration
  • Data smoothing
  • Spike removal
  • Peak finding
  • Other methods
• Signal2D Tools
  • Two dimensional signal registration (alignment)
  • Cropping an image
  • Add a linear ramp
• Data visualization
  • Multidimensional spectral data
  • Multidimensional image data
  • Customising image plot
  • Customizing the “navigator”
  • Using Mayavi to visualize 3D data
  • Plotting multiple signals
  • Markers
• Machine learning
  • Introduction
  • Nomenclature
  • Decomposition
  • Blind Source Separation
  • Visualizing results
  • Obtaining the results as BaseSignal instances
  • Saving and loading results
• Model fitting
  • Creating a model
  • Adding components to the model
  • Indexing the model
  • Getting and setting parameter values and attributes
  • Fitting the model to the data
  • Storing models
  • Batch setting of parameter attributes
  • Smart Adaptive Multi-dimensional Fitting (SAMFire)
• Electron Energy Loss Spectroscopy
  • Tools for EELS data analysis
  • EELS curve fitting
• Energy-Dispersive X-ray Spectrometry (EDS)
  • Spectrum loading and parameters
  • Describing the sample
  • Plotting
  • Geting the intensity of an X-ray line
  • EDS Quantification
  • EDS curve fitting
• Dielectric function tools
  • Number of effective electrons
  • Compute the electron energy-loss signal
• Electron Holography
  • The HologramImage class
• Loading and saving data
  • Loading files: the load function
  • Saving data to files
  • Supported formats
  • Reading data generated by HyperSpy using other software packages
• Events
  • Connecting to events
  • Suppressing events
  • Triggering events
• Working with big data
  • Creating Lazy Signals
  • Practical tips
  • Limitations
  • Behind the scenes –technical details
• Metadata structure
  • General
  • Acquisition_instrument
  • Sample
  • Signal
  • _Internal_parameters
• Bibliography
  • Bibliography
  • Peer-review articles with results obtained using HyperSpy