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.
MATLAB Type | CDF Type |
---|---|
datetime | CDF_EPOCH |
double | CDF_REAL8 |
float | CDF_REAL4 |
string | CDF_CHAR |
char array | CDF_CHAR |
integers | CDF_INT of the same size and sign |
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';
引用格式
Chris Piker (2024). mapCDF (https://github.com/mag-noise/mapCDF/releases/tag/v1.0), GitHub. 检索来源 .
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版本 | 已发布 | 发行说明 | |
---|---|---|---|
1.0 |