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Dimension Data Type

MDSplus provides a dimension data type which provides a compact mechanism for expressing signal dimensions (See: DTYPE_SIGNAL). The dimension data type was implemented as a way to represent data such as the timebase for signals recorded by data acquisition equipment such as transient recorders. These devices typically have a clock (either a separate external device or built into the transient recorder) which tells the device to record a sample into its internal cyclic memory buffer. In many cases this clock is a single speed clock which means each clock pulse occurs at a constant delta time from the previous clock pulse. A transient digitizer has another input called a trigger which tells the device to stop recording samples (either immediately or after some number of subsequent clock pulses). If one knows when the clock began running and the delta time between each clock pulse along with the time the trigger took place, one could compute the time that each sample in the digitizers internal memory was recorded. MDSplus could compute these times when storing the data for the device and store these times along with the data in a signal however it is much more efficient to store a representation of this timebase which could be evaluated as needed. This is the purpose of the dimension data type.

A dimension data type is a structure which has two parts, a window and an axis. The axis part is a representation of a series of values (i.e. time stamps) and is generally represented by a DTYPE_RANGE data item. If this was a single speed clock, for example, the axis would be represented by a range consisting or an optional start time, an optional end time and a single delta time value. This range could represent a series of clock pulses which began some time infinitely in the past and continuing to some time infinitely in the future. The window portion of the dimention is used to select a set of these infinite stream of clock pulses that represent those clock pulses which match the samples that were recorded in the digitizers internal memory. The window portion is usually represented by a DTYPE_WINDOW data item. A window consists of a start index, and end index and a value at index 0. For a transient digitizer, the samples in the memory were recorded at a known number of clock pulses before the trigger (the start index) and continuing a known number of clock pulses after the trigger. The time the module was triggered is the value at index 0 part of the window.

The best way to explain how a dimension works is to give an example. Let us imagine we had an external clock that just ticks continously every second. If we hooked this clock to a transient digitizer and told that digitizer to start recording, every second it would record the voltage level of its inputs into its circular memory buffer. It would continue to record these samples for ever until told to stop. We can represent this unbounded time base using a DTYPE_RANGE data item:

 * : * : 1.0



If we asked MDSplus to evaluate this time base we would get an error since it represents an infinite stream of values with each value being one larger than the previous value.

Now if the digitizer is configured to stop recording values when it receives a trigger input it should be possible to compute when each sample in its buffer was recorded (approximately since in this example we don't know the exact time of each clock pulse). If we label the trigger time in this example as time 0.0 and for purposes of illustration say the digitizer can record ten samples, we can represent the time base using:

_CLOCK = * : * : 1.0
_TRIGGER = 0.0

The clock pulses occurring close to the time the module was triggered would be be times such as ...,-19,-18,-17,-16,...,-4,-3,-2,-1,0,1,2,3,... an so on. Since the device was told to stop recording approximately at the time 0.0, the ten samples that have been recorded in the digitizers memory would have occurred at -9,-8,-7,-6,-5,-4,-3,-2,-1,0. These are the values that MDSplus would return if the above dimension was evaluated.

Of course, there are numerous ways this same information could have been represented. However, one thing the special about the dimension concept is that the trigger time and the clock representation does not need to be known when the dimension item is stored. They can be simply node references to pieces of information which is stored by other devices which are responsible for generating the trigger and clocks. The implementation of a transient digitizer in MDSplus can be implemented independently of trigger devices and clock devices. It knows only the number of pre-trigger and post-trigger samples it takes and therefore can store a dimension item with a window indicating the start index and end index and simply use node references for the trigger and clock.

The dimension data type can obviously be used for more than just representing time stamps of data recorded by transient digitizers. This compact representation can be used for storing dimension information of almost any kind of signals. The axis portion of the dimension does not have to be a regular continuous range. It can be an unbounded or bounded range, an simple array of values or an expression returning a range or array of values. The window portion of a dimension can be missing if the axis portion is finite.

The dimension data type is very important when you use the MDSplus subscripting capability. MDSplus signals can be subscripted using bounds expressed in units of its dimensions. For example:


This would extract the subset of the signal which has dimension values between .3 and .9. MDSplus subscripting behaves slightly different when subscripting a signal which as an array of values for the dimension versus a dimension item. A signal that looks like build_signal(y-values,*,x-values-array) is treated like a list of discrete values while a signal such as
build_signal(y-values, *, build_dim(*,x-values-array)) is treated as a continous signal. If a range without a delta is used to subscript the former signal it evaluates the range with the default increment of one and uses the result to pick the discrete values from the signal. In the latter case, it treats the range as a beginning and ending and extracts the portion of the signal within this range. In most cases the latter behavior is desired so you should take care to store signals using dimension items for the dimensions.


result = build_signal([2],*,[.2])


result = build_signal([2,3,4],*,[.2,.3,.4])

The following table lists some of the functions available for creating or accessing dimensions:

Function Description
AXIS_OF Return axis portion of dimension
BUILD_DIM Build a dimension structure
BUILD_SIGNAL Build a signal structure
BUILD_WINDOW Build a window structure
DATA Evaluates dimension item converting to one of integer, float or text
DIM_OF Return one of the dimension parts of a signal structure
MAKE_DIM Make a dimension structure
WINDOW_OF Return the window field of a dimension structure