An enhanced map interface for writing NASA CDF files

Wrapper class around cdflib to make CDF file creation less awkward.

This class presents a CDF files as an enhanced Map. Each member of the map represents a single variable in a CDF file. The data for each variable has more than one row if the Variable is Record Varying (a CDF term) and only a single row if it's a non record-varying variable.

Copy the +cdf folder somewhere to your MATLAB path. That's it.

A brief overview of how to use the +CDF module from mapCDF follows.

The storage type can be set when a Variable is created (see the subsasgn() function), or via the the cdf.Var.type function.

Data values are associated with a variable via indexed assignment. The following example creates a variable named status and assigns byte values to it:

   out = cdf.CDF()
   out('Status').data = zeros(1, 5000, 'int8')

The 'Status' variable would be saved as a record varying variable. This is because the size of the last dimension determines the record variability of an array. The zeros function above creates a row-vector of size:

  [1 5000]

Since the last dimension is > 1 then the array will be stored as a record varying variable when the .save() method is called.

For a slightly more complex example, consider the following set of column vectors:

   B_vec_array = [1 0.7071 0; 
                  0 0.7071 0; 
                  0 1      0 ]

The complete set has size [3 3]. Thus the call:

   out('B_gei').data = B_vec_array;

Creates a record varying variable that has 3 values per record. The following column vector:

   Frequency = [10; 
                20; 
                30]

has size [3 1]. Thus it is not a record varying variable, but does have 3 values for it's one, lone constant record. The following time array is record varying and has only one value per record:

   T = [datetime('2019-10-28') datetime('2019-10-28') datetime('2019-10-28')]

For various reasons matlab drops trailing dimensions of length 1, only if the variable is rank 3 or greater. Thus the language has a broken symmetry around rank 2 variables. Since a trailing rank of 1 is needed to indicate non-record-varying varibles, use the option Rank integer when assigning variables using mkVar() function or manually set the .rank parameter. For example

   Coefficents = [ 0.9946   -0.0393    0.0015   -2.4940; 
                   0.0416    1.0004    0.0450   -1.2780;
                   0.0016   -0.0491    0.9512    9.5738 ]

   out('Coeff').data = Coefficents
   out('Coeff').rank = 3    

To store strings as atomic items, use cell-arrays. Otherwise the count of characters along a string is one of the data variable dimensions.
For example:

   cdf.mkVar('char_data', ['Comp A'; 'Comp B'; 'Comp C']);

will generate a two dimensional CDF variable with three records and a size of 6 in the second dimension and an element size of 1. The atomic unit of this data array will be a single character.

On the other hand:

   cdf.mkVar('char_data', {'Comp A'; 'Comp B'; 'Comp C'});

will generate a 1 dimensional CDF variable with three records and with an element size of 6. The atomic uint of this variable is the whole 6-character string.

Global properties are accessed and set via the '.attrs' map. For ex:

   out = cdf.CDF();
   out.attr('Title') = 'Hyper accurate Irridium Mag vectors (GEI)';

Variable properties are accessed by first indexing to get the variable, and then setting a value for that variable's attrs map:

  out = cdf.CDF();
  out('Epoch').attr('Caution') = 'Leap seconds have been ignored';