This is a maintenance release that adds compatibility with h5py 3.0 and includes numerous bug fixes and enhancements. See the milestones v1.6.1 for details.

This is a minor release with many new features, enhancements and bug fixes. See the User Guide for a list of changes.

This is a maintenance release that adds compatibility with Numpy 1.17 and Dask
2.3.0 and fixes a bug in the Brucker reader. See the issue tracker
for details.

This is a maintenance release that fixes some regressions introduced in v1.5.
Follow the following link for details on all the bugs fixed.

This is a minor release. See the User Guide for a list of changes.

This is a maintenance release. Follow the following links for details on all the bugs fixed and enhancements.

This is a maintenance release. Follow the following links for details on all the bugs fixed and enhancements.

This release fixes compatibility issues with Python 3.7.

This is the same as v1.1.0 but the distribution file size is smaller because one large file required for the tests was removed and is now downloaded when running the test

This is a minor release. Follow the following links for details on all the bugs
fixed, enhancements and new features.

NEW

• Support for three new file formats:

  • Reading FEI's Velox EMD file format based on the HDF5 open
    standard.
  • Reding Burcker's SPX format.
  • Reading and writing the mrcz open format.

• New artificial data module which contains functions for generating artificial data, for
  use in things like docstrings or for people to test HyperSpy functionalities.

• New fft and ifft signal methods.

• New statistics method to compute useful hologram parameters.

• Automatic axes units conversion and better units handling using pint.

• New Line2DROI.angle().

Enhancements

• plot_images improvements:
  • The cmap option of plot_images now supports iterable types, allowing the user to specify different colormaps for the different images that are plotted by providing a
    list or other generator.
  • Clicking on an individual image updates it.
• New customizable keyboard shortcuts to navigate multi-dimensional datasets.
• The remove_background method now operates much faster in multi-dimensional
  datasets and
  adds the options to interatively plot the remainder of the operation
  and to set the removed background to zero.
• The Signal2D.plot method now takes a norm keyword that can be "linear",
  "log", "auto" or a matplotlib norm. Moreover, there are three new extra
  keyword arguments, fft_shift and power_spectrum, that are useful
  whe plotting fourier transforms.
• The Signal2D.align2D and Signal2D.estimate_shift2D can operate
  with sub-pixel accuracy using skimage's upsampled matrix-multiplication DFT.

This is a minor release. Follow the following links for details on all the bugs
fixed, enhancements and new features.

NEW

• Support for three new file formats:

  • Reading FEI's Velox EMD file format based on the HDF5 open
    standard.
  • Reding Burcker's SPX format.
  • Reading and writing the mrcz open format.

• New artificial data module which contains functions for generating artificial data, for
  use in things like docstrings or for people to test HyperSpy functionalities.

• New fft and ifft signal methods.

• New statistics method to compute useful hologram parameters.

• Automatic axes units conversion and better units handling using pint.

• New Line2DROI.angle().

Enhancements

• plot_images improvements:
  • The cmap option of plot_images now supports iterable types, allowing the user to specify different colormaps for the different images that are plotted by providing a
    list or other generator.
  • Clicking on an individual image updates it.
• New customizable keyboard shortcuts to navigate multi-dimensional datasets.
• The remove_background method now operates much faster in multi-dimensional
  datasets and
  adds the options to interatively plot the remainder of the operation
  and to set the removed background to zero.
• The Signal2D.plot method now takes a norm keyword that can be "linear",
  "log", "auto" or a matplotlib norm. Moreover, there are three new extra
  keyword arguments, fft_shift and power_spectrum, that are useful
  whe plotting fourier transforms.
• The Signal2D.align2D and Signal2D.estimate_shift2D can operate
  with sub-pixel accuracy using skimage's upsampled matrix-multiplication DFT.

HyperSpy is an open source Python library which provides tools to facilitate the interactive data analysis of multi-dimensional datasets that can be described as multi-dimensional arrays of a given signal (e.g. a 2D array of spectra a.k.a spectrum image).

This is a maintenance release. Follow the following links for details on all the bugs fixed.

HyperSpy is an open source Python library which provides tools to facilitate the interactive data analysis of multi-dimensional datasets that can be described as multi-dimensional arrays of a given signal (e.g. a 2D array of spectra a.k.a spectrum image).

This is a maintenance release. Follow the following links for details on all the bugs fixed.

Pre-release for the HyperSpy workshop at diamond.

This is a minor release. Follow the following links for details on all the bugs fixed, enhancement, documentation enhancements, and new features.

NEW

• rebin supports upscaling and rebinning to arbitrary sizes through linear interpolation. It also runs faster if numba is installed.
• AxesManager.signal_extent and AxesManager.navigation_extent properties to easily get the extent of each space.
• New IPywidgets Graphical User Interface (GUI) elements for the Jupyter Notebook. See the new hyperspy_gui_ipywidgets package. It is not installed by default.
• All the Regions of Interest now have a gui method to display a GUI if at least one of HyperSpy's GUI packgages are installed.

Enhancements

• Creating many markers is now much faster.
• New Stage metadata node.
• The Brucker file reader now supports the new version of the format.
• HyperSpy is now compatible with all matplotlib backends, including the nbagg which is particularly convenient for interactive data analysis in the Jupyter Notebook in combination with the new hyperspy_gui_ipywidgets package.
• The vmin and vmax arguments of the plot_images function now accept lists to enable setting these parameters for each plot individually.
• The plot_decomposition_results and plot_bss_results methods now makes a better guess of the number of navigators (if any) required to visualise the components. (Previously they were always plotting four figures by default.)
• All functions that take a signal range can now take SpanROI.
• The following ROIs can now be used for indexing or slicing: Point1DROI, Point2DROI, SpanROI and RectangularROI.

API changes

• Permanent markers (if any) are now displayed when plotting by default.
• HyperSpy no longer depends on traitsui (fixing many installation issues) and ipywidgets as the GUI elements based on these packages have now been splitted into separate packages and are not installed by default.
• The following methods now raise a ValueError when not providing the number of components if output_dimension was not specified when performing a decomposition. (Previously they would plot as many
  figures as available components, usually resulting in memory saturation): plot_decomposition_results and plot_decomposition_factors.
• The default extension when saving to HDF5 following HyperSpy's specification is now hspy instead of hdf5.
• The following methods are deprecated and will be removed in HyperSpy 2.0

• AxesManager.show. Use AxesManager.gui instead.
• All notebook_interaction methods. Use the equivalent gui method instead.
• integrate_in_range. Use integrate1D instead.

• The following items have been removed from
  preferences:

  • General.default_export_format
  • General.lazy
  • Model.default_fitter
  • Machine_learning.multiple_files
  • Machine_learning.same_window
  • Plot.default_style_to_compare_spectra
  • Plot.plot_on_load
  • Plot.pylab_inline
  • EELS.fine_structure_width
  • EELS.fine_structure_active
  • EELS.fine_structure_smoothing
  • EELS.synchronize_cl_with_ll
  • EELS.preedge_safe_window_width
  • EELS.min_distance_between_edges_for_fine_structure

• New Preferences.GUIs section to enable/disable the installed GUI toolkits.

For developers

• In addition to adding ipywidgets GUI elements, the traitsui GUI elements have been splitted into a separate package. See the new hyperspy_gui_traitsui package.
• The new ui_registry enables easy connection of external GUI elements to HyperSpy. This is the mechanism used to split the traitsui and ipywidgets GUI elements into separate packges.

HyperSpy is an open source Python library which provides tools to facilitate the interactive data analysis of multi-dimensional datasets that can be described as multi-dimensional arrays of a given signal (e.g. a 2D array of spectra a.k.a spectrum image).

This is a minor HyperSpy release. Follow the following links for details on all the bugs fixed, enhancements and new features.

NEW

• Lazy loading and evaluation.
• Parallel hs.signal.BaseSignal.map and all the functions that use
  it internally (a good fraction of HyperSpy's functionality).
• Electron holography image reconstruction.
• Support for reading EDAX TEAM SPD and SPC files.
• New signal methods hs.signal.BaseSignal.indexmin.
  and hs.signal.BaseSignal.valuemin.

Enhancements

• Easier creation of hs.model.components1D.Expression components using substitutions.
• hs.model.components2D.Expression takes two dimensional
  functions that can automatically include a rotation parameter.
• Better support for EMD files.
• The scree plot got a beauty treatment and some extra features.
• hs.signal.BaseSignal.map can now take functions that return
  differently-shaped arrays or arbitrary objects.
• Add support for stacking multi-signal files.
• Markers can now be saved to HDF5.
• Creating many markers is now easier and faster.
• Add option to save to HDF5 file using the ".hspy" extension instead
  of ".hdf5". This will be the default extension in
  HyperSpy 1.3.

For developers

• Most of HyperSpy plotting features are now covered by unittests.
• unittests migrated from nose to pytest.

HyperSpy is an open source Python library which provides tools to facilitate the interactive data analysis of multi-dimensional datasets that can be described as multi-dimensional arrays of a given signal (e.g. a 2D array of spectra a.k.a spectrum image).

This is a maintenance release. Follow the following links for details on all the bugs fixed and enhancements.

This is a maintenance release that fixes bugs and includes the following enhancements:

Enhancements

• Prettier X-ray lines labels.
• New metadata added to the HyperSpy metadata specifications: magnification, frame_number, camera_length, authors, doi, notes and quantity.
• The y-axis label (for 1D signals) and colorbar label (for 2D signals) are now taken from the new metadata.Signal.quantity.
• The time and date metadata are now stored in the ISO 8601 format.
• All metadata in the HyperSpy metadata specification is now read from all supported file formats when available.

HyperSpy is an open source Python library which provides tools to facilitate the interactive data analysis of multi-dimensional datasets that can be described as multi-dimensional arrays of a given signal (e.g. a 2D array of spectra a.k.a spectrum image).

This is a minor release that includes bug fixes and the following new features and enhancements.

NEW

• Transposing (changing signal spaces).
• Protochips log reader.

Enhancements

• fit() takes a new algorithm, the global optimizer differential evolution.
• fit() algorithm, leastsq, inherits SciPy’s bound constraints support (requires SciPy >= 0.17).
• fit() algorithm names changed to be consistent scipy.optimze.minimize() notation.

HyperSpy is an open source Python library which provides tools to facilitate the interactive data analysis of multi-dimensional datasets that can be described as multi-dimensional arrays of a given signal (e.g. a 2D array of spectra a.k.a spectrum image).

This is a maintenance release.

HyperSpy is an open source Python library which provides tools to facilitate the interactive data analysis of multi-dimensional datasets that can be described as multi-dimensional arrays of a given signal (e.g. a 2D array of spectra a.k.a spectrum image).

This is a major release. Here we only list the highlist. A detailed list of changes is available in github.

NEW

• Region Of Interest (ROI).
• Robust PCA (RPCA) and online RPCA algorithms.
• Numpy ufuncs can now operate on HyperSpy’s signals.
• ComplexSignal and specialised subclasses to operate on complex data.
• Events logging.
• Query and fetch spectra from The EELS Database.
• Interactive operations.
• Events.

Model

• Smart Adaptive Multi-dimensional Fitting (SAMFire).
• Store models in hdf5 files.
• Add fancy indexing to Model.
• Two-dimensional model fitting.

EDS

• Z-factors quantification.
• Cross section quantification.
• EDS curve fitting.
• X-ray absorption coefficient database.

IO

• Support for reading certain files without loading them to memory.
• Bruker’s composite file (bcf) reading support.
• Electron Microscopy Datasets (EMD) read and write support.
• SEMPER unf read and write support.
• DENS heat log read support.
• NanoMegas blockfile read and write support.

Enhancements

• More useful AxesManager repr string with html repr for Jupyter Notebook.
• Better progress bar (tqdm).
• Add support for writing/reading scale and unit to tif files to be read with ImageJ or DigitalMicrograph.

Documentation

• The following sections of the User Guide were revised and largely overwritten:
  • Installing HyperSpy.
  • Machine learning.
  • Energy-Dispersive X-ray Spectrometry (EDS).
• New Developer Guide.

API changes

• Split components into components1D and components2D.
• Remove record_by from metadata.
• Remove simulation classes.
• The Signal1D, Signal2D and BaseSignal classes deprecated the old Spectrum Image and Signal classes.