Spectral Python 0.15.0 adds Minimum Noise Fraction (MNF)

New Features

• Added Minimum Noise Fraction (mnf) algorithm (a.k.a., Noise-Adjusted
  Principal Components). An associated noise_from_diffs function enables
  estimation of image noise from a homogeneous region of the image.

Changes

• When calling envi.save_image, assume an ndarray with two dimensions is
  a single-band image (i.e., don't require an explicit third dimension).
• [Issue #9] All SpyFile subclass read methods now have an optional
  use_memmap argument to indicate whether the memmap interface should be
  used (vice direct file read) on a per-call basis. Default values are
  specific to the particular method and file interleave.

Bug Fixes

• [Issue #7] Handle recognize comment lines in ENVI headers and accept blank
  parameter values in the header. Thanks to Don March (http://ohspite.net)
• [Issue #2] Garbage results were being generated for several algorithms when
  a NaN value was present in the image data. Reasonable checks are now
  performed in several algorithms and an optional allow_nan argument (False
  by default) was added to calc_stats.
• [Issue #1] For images with more rows than columns, the row/col of the pixel
  under the mouse cursor did not display if the row index was greater than
  the image width.

Performance Improvements

• [Issue #5] Improved BilFile.read_bands performance. Thanks to Don March
  (http://ohspite.net)
• [Issue #8] Faster creation/display of RGB images for display. Thanks to
  Don March (http://ohspite.net)