# coyote: CGHISTOGRAM

- coyote/General Programming
- [Source code]

Description

      This program is used as a wrapper to the Histogram command in IDL. It works around a bug
      in the Histogram command when byte data is binned in versions prior to IDL 8.2, and it takes
      care to match the data type of the `BinSize` keyword to the data type of the data being binned.
      If this matching is not done, Histogram silently returns incorrect results. I have added the ability to
      smooth the data (with the `Smooth` keyword) and to return the relative frequency of the histogram,
      rather than the histogram counts (with the `Frequency` keyword). The relative frequency is a
      number between 0 and 1. I have also added the ability to specify "missing" data that should not be
      binned.

Categories

      General

Params

      data: in, required,
         The data from which the histogram is created.

Keywords

      binsize: in, optional
         The binsize of the histogram. By default, Scott's Choice of bin size for histograms is used::
             binsize = (3.5 * StdDev(data)) / N_Elements(data)^(0.3333)
         If BINSIZE in not defined, and NBINS is defined, the BINSIZE is calcuated as::
              binsize = (Max(dataToHistogram) - Min(dataToHistogram)) / (NBINS -1)
         While it is pointed out in the HISTOGRAM documentation, it is extremely
         important that the BINSIZE be of the same data type as the data you are going to
         calculate the histogram of. If it is not, VERY strange things can happen, but the
         worst is that HISTOGRAM silently returns incorrect results. I try hard to avoid this
         result in this program.
      frequency: in, optional, type=boolean, default=0
         If this keyword is set, the relative frequency is returned, rather than the
         histogram counts. Relative frequency is a number between 0 and 1. The total of
         all the relative frequencies should equal 1.0.
      input: in, optional
         Set this keyword to a named variable that contains an array to be added to the
         output of cgHistogram. The density function of `data` is added to the existing
         contents of `Input` and returned as the result. The array is converted to
         longword type if necessary and must have at least as many elements as are
         required to form the histogram. Multiple histograms can be efficiently
         accumulated by specifying partial sums via this keyword.
      l64: in, optional, type=boolean, default=0
         If set, the return value of HISTOGRAM are 64-bit integers, rather than
         the default 32-bit integers. Set by default if 64-bit integers are passed in.
      locations: out, optional
         Starting locations of each bin. `Locations` has the same number of elements as the result,
         and has the same data type as the input data array.
      max: in, optional
         The maximum value to use in calculating input histogram.
      min: in, optional
         The minimum value to use in calculating input histogram.
      missing: in, optional
         The value that should be represented as "missing" and not used in the histogram.
         Be aware that if the input data is not of type "float" or "double" that the input
         data will be converted to floating point prior to calculating the histogram.
      nan: in, optional, type=boolean, default=0
         If set, ignore NAN values in calculating and plotting histogram. Set by default if the
         `Missing` keyword is used.
      nbins: in, optional, type=integer
         The number of output bins in the histogram. The meaning is slightly different from
         the meaning in the HISTOGRAM command. Used only to calculate BINSIZE when BINSIZE is
         not specified. In this case, binsize = rangeofData/(nbins-1). When the number of bins
         is low, the results can be non-intuitive. For this reason, I would discourage the use
         of `NBins` in favor of the `BinSize` keyword.
      omax: out, optional
         The maximum output value used to construct the histogram. (See HISTOGRAM documentation.)
      omin: out, optional
         The minimum output value used to construct the histogram. (See HISTOGRAM documentation.)
      reverse_indices: out, optional
         The list of reverse indices returned from the HISTOGRAM command. (See HISTOGRAM documentation.)
      smooth: in, optional, type=integer, default=0
         Set this keyword to an odd positive integer to smooth the histogram output before plotting.
         The integer will set the width of a smoothing box to be applied to the histogram data with
         the Smooth function. This keyword is ignored if the `Frequency` keyword is set.

Examples

      Create a normal distribution of random numbers and take the histogram::
         numbers = RandomU(-3L, 1000, /Normal)
         histResults = cgHistogram(numbers, Binsize=0.25)
         cgPlot, histResults
      Additional examples of histogram plots can be found here::
          http://www.idlcoyote.com/gallery/index.html

Author

      FANNING SOFTWARE CONSULTING::
          David W. Fanning
          1645 Sheely Drive
          Fort Collins, CO 80526 USA
          Phone: 970-221-0438
          E-mail: david@idlcoyote.com
          Coyote's Guide to IDL Programming: http://www.idlcoyote.com

History

      Change History::
         Written by:  David W. Fanning, 7 March 2013.

Copyright

      Copyright (c) 2013, Fanning Software Consulting, Inc.