cdflib.computeTT2000

Convert time components to CDF_TIME_TT2000 timestamp

Since R2022b

Syntax

tt2000 = cdflib.computeTT2000(timeVec)

Description

tt2000 = cdflib.computeTT2000(timeVec) converts individual UTC-based time components to a CDF_TIME_TT2000 timestamp.

• If timeVec is a vector, then tt2000 is an integer scalar.

• If timeVec is a matrix, then tt2000 is an integer vector whose length equals the number of columns of timeVec.

For more information about CDF_TIME_TT2000 timestamps, see the More About section.

Examples

Find CDF_TIME_TT2000 Timestamp

Find the CDF_TIME_TT2000 timestamp for the beginning of the third millennium CE.

timeVec = [2001;1;1;0;0;0;0;0;0];
newMillennium = cdflib.computeTT2000(timeVec)

newMillennium = int64

31579264184000000

Read and Convert Sample CDF_TIME_TT2000 Data

Open the example_364.cdf CDF file and prepare to read CDF_TIME_TT2000 data.

cdfid = cdflib.open("example_364.cdf");
varID = 7;                                          % Contains CDF_TIME_TT2000 data
numRecs = cdflib.getVarNumRecsWritten(cdfid,varID); % Read all records
tt2000Data = zeros(1,numRecs,"int64");              % Preallocate array

Read CDF_TIME_TT2000 data in native int64 form.

for i = 0:numRecs-1
    tt2000Data(i+1) = cdflib.getVarData(cdfid,varID,i);
end
tt2000Data' % Display as column vector for readability

ans = 8×1 int64 column vector

   536500865284200300
   536500866284200300
   536500867284200300
   536500868284200300
   536500869284200300
   536500870284200300
   536500871284200300
   536500872284200300

Decompose the eight dates into their individual time components.

timeArr = cdflib.breakdownTT2000(tt2000Data)

timeArr = 9×8

        2016        2016        2016        2016        2017        2017        2017        2017
          12          12          12          12           1           1           1           1
          31          31          31          31           1           1           1           1
          23          23          23          23           0           0           0           0
          59          59          59          59           0           0           0           0
          57          58          59          60           0           1           2           3
         100         100         100         100         100         100         100         100
         200         200         200         200         200         200         200         200
         300         300         300         300         300         300         300         300

Compute the corresponding CDF_TIME_TT2000 timestamps of the third through sixth entries.

cdfTimestamps = cdflib.computeTT2000(timeArr(:,3:6))

cdfTimestamps = 1×4 int64 row vector

   536500867284200300   536500868284200300   536500869284200300   536500870284200300

Input Arguments

timeVec — Individual time components

vector | matrix

Individual time components, specified as a 9-by-1 or 1-by-9 vector, or a 9-by-n matrix, where n is the number of timestamps converted.

When timeVec is a matrix, each column contains the individual time components of one particular time. Each row of timeVec is a time component, according to this list:

Row	Value	Range
1	Year (CE)	[1707, 2292]
2	Month	[1, 12]
3	Day	[1, 31]
4	Hour	[0, 23]
5	Minute	[0, 59]
6	Second	[0, 59] (or [0, 60] if leap second)
7	Millisecond	[0, 999]
8	Microsecond	[0, 999]
9	Nanosecond	[0, 999]

Example: [2000;1;1;0;0;0;0;0;0]

Example: [2001 2001; 1 1; 1 1; 0 0; 0 0; 0 0; 0 0; 0 0; 0 1]

Data Types: double

More About

CDF_TIME_TT2000 Timestamp

A CDF_TIME_TT2000 timestamp represents the number of nanoseconds elapsed since J2000. J2000 represents January 1, 2000, 12:00:00 Terrestrial Time (TT). TT differs slightly from Coordinated Universal Time (UTC). A TT time can be derived from a UTC time by adding n + 32.184 s to the UTC time, where n is the number of leap seconds that were added between 1960 and the UTC time. For more information, see Requirements for handling leap seconds in CDF and Leap second table.

Tips

• This function corresponds to the CDF library C API routine computeTT2000.

• To use this function, you must be familiar with the CDF C interface. You can access the CDF documentation at the CDF website.

Version History

Introduced in R2022b