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doc/release/release_0.1.rst

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+Announcement: KikuchiPy 0.1.0
+=============================
+
+We're happy to announce the release of KikuchiPy v0.1.0!
+
+KikuchiPy is an open-source Python library for processing and analysis of
+electron backscatter diffraction (EBSD) patterns. The library builds upon the
+tools for multi-dimensional data analysis provided by the HyperSpy library.
+
+For more information, a user guide, and the full reference API documentation,
+please visit: https://kikuchipy.readthedocs.io
+
+This is the initial pre-release, where things start to get serious...
+
+Features
+--------
+- Load EBSD patterns and metadata from the NORDIF binary format (.dat) and
+  Bruker Nano and EDAX TSL's h5ebsd formats (.h5) into an `EBSD` object, e.g.
+  `s`, based upon HyperSpy's `Signal2D` class, using `s = kp.load()`. This
+  ensures easy access to patterns and metadata in the attributes `s.data` and
+  `s.metadata`, respectively.
+- Save EBSD patterns to the NORDIF binary format (.dat) and our own h5ebsd
+  format (.h5), using `s.save()`. Both formats are readable by EMsoft's NORDIF
+  and EMEBSD readers, respectively.
+- Visualize patterns easily with HyperSpy's powerful and versatile `s.plot()`.
+  Any image, e.g. a virtual backscatter electron image, quality map, phase map
+  or orientation map, can be used to navigate in. Multiple scans of the same
+  size, e.g. best matching simulated patterns to a scan, can be plotted
+  simultaneously alongside the experimental patterns with HyperSpy's
+  `plot_signals()`.
+- Virtual backscatter electron (VBSE) imaging is easily performed with
+  `s.virtual_backscatter_electron_imaging()` based upon similar functionality
+  in pyXem. Arbitrary region of interests can be used, and the corresponding
+  VBSE image can be inspected interactively. Finally, the VBSE image can be
+  obtained in a new `EBSD` object with `vbse = s.get_virtual_image()`, before
+  writing the data to an image file in your desired format with matplotlib's
+  `imsave('filename.png', vbse.data)`.
+- Change scan and pattern size, e.g. by cropping on the detector or extracting
+  a region of interest, by using `s.isig` or `s.inav`, respectively.
+  Patterns can be binned (upscaled or downscaled) using `s.rebin`. These
+  methods are provided by HyperSpy.
+- Perform static and dynamic background correction by subtraction or division
+  with `s.static_background_correction()` and
+  `s.dynamic_background_correction()`. For the former connection, relative
+  intensities between patterns can be kept if desired.
+- Perform adaptive histogram equalization by setting an appropriate contextual
+  region (kernel size) with `s.adaptive_histogram_equalization()`.
+- Rescale pattern intensities to desired data type and range using
+  `s.rescale_intensities()`.
+- Multivariate statistical analysis, like principal component analysis and many
+  other decomposition algorithms, can be easily performed with
+  `s.decomposition()`, provided by HyperSpy.
+- Since the `EBSD` class is based upon HyperSpy's `Signal2D` class, which itself
+  is based upon their `BaseSignal` class, all functionality available to
+  `Signal2D` is also available to the `EBSD` class. See HyperSpy's user guide
+  (http://hyperspy.org/hyperspy-doc/current/user_guide/tools.html) for details.
+
+Contributions to this release (alphabetical by first name)
+----------------------------------------------------------
+- Håkon Wiik Ånes
+- Tina Bergh