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    Calculates the mean value of an image in bins of both radius and
    pie slices of azimuthal angle.



Calling Sequence

    Result = MEAN_BY_RADAZ(Image)


    Image: 2D image array.

Keyword Parameters

    RBIN: Size of radial bins (in pixels). Default: 1.
    NTHETA: Number of azimuthal bins. Default: 8.
    CENTER: Pixel co-ordinate to consider the center. May be
                non-integer, or even off the image (as long as
                /CROPCIRCLE is not set). Default: Image center.
    ROTATION: Start the first azimuthal bin at an angle ROTATION
                (in radians) from the x-axis. Default: 0.
    CROPCIRCLE: Set this keyword to crop out the corners of
                the image, i.e. use only those pixels within the largest
                circle that is fully enclosed in the image.
    NAN: Set this keyword to check for NaN or Infinity when
                calculating the means. Any such elements are treated
                as missing data.


    This function returns a structure containing the inner radii of each
    radial bin (tagged 'RADIAL_AXIS'), the image mean within each radial
    bin (tagged 'RADIAL_MEAN'), the starting azimuth of each azimuthal
    bin (tagged 'AZIMUTHAL_AXIS'), and the image mean within each azimuthal
    pie slice (tagged 'AZIMUTHAL_MEAN'). Note that azimuthal angle is
    calculated counterclockwise starting at the x-axis (unless ROTATION
    is specified).


    Calculate the radial and azimuthal means of some image data, cutting
    out the "corners" that aren't fully sampled to the same radii. Use
    radial bins 2 pixels wide and azimuthal bins 30 degrees wide.
    imagedata = dist(25,25)
    imagemeans = MEAN_BY_RADAZ(imagedata, RBIN=2, NTHETA=12, /CROPCIRCLE)

Modification History

    Written by: Jeremy Bailin, in response to a question by Andy Bohn.
    17 June 2008 Public release in JBIU
    18 June 2008 Fixed typo in documentation

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