HDFMapDigiSISCrate¶

class bapsflib._hdf.maps.digitizers.siscrate.HDFMapDigiSISCrate(group: Group)¶

Bases: HDFMapDigiTemplate

Mapping class for the ‘SIS crate’ digitizer.

Simple group structure looks like:

+-- SIS crate
|   +-- config01
|   |   +-- SIS crate 3302 calibration[0]
|   |   |   +--
.
|   |   +-- SIS crate 3302 configurations[0]
|   |   |   +--
.
|   |   +-- SIS crate 3305 calibration[0]
|   |   |   +--
.
|   |   +-- SIS crate 3305 configurations[0]
|   |   |   +--
.
.
|   |   +-- SIS crate 3820 configurations[0]
|   |   |   +--
|   +-- config01 [Slot 5: SIS 3302 ch 1]
|   +-- config01 [Slot 5: SIS 3302 ch 1] headers
.
.
.
|   +-- config01 [Slot 13: SIS 3305 FPGA 1 ch 1]
|   +-- config01 [Slot 13: SIS 3305 FPGA 1 ch 1] headers
.
|   +-- config01 [Slot 13: SIS 3305 FPGA 2 ch 1]
|   +-- config01 [Slot 13: SIS 3305 FPGA 2 ch 1] headers
.
.
.

Parameters:: group – the HDF5 digitizer group

Attributes Summary

`active_configs`	List of active digitizer configurations
`configs`	Dictionary containing al the relevant mapping information to translate the HDF5 data into a numpy array by `HDFReadData`.
`device_adcs`	Tuple of the analog-digital-convert (adc) names integrated into the digitizer.
`device_name`	Name of digitizer
`group`	Instance of the HDF5 digitizer group
`info`	Digitizer dictionary of meta-info. For example, ::.
`slot_info`	Slot info dictionary.

Methods Summary

`construct_dataset_name`(board, channel[, ...])	Construct the name of the HDF5 dataset containing digitizer data. The dataset naming follows two formats based on their associated adc::.
`construct_header_dataset_name`(board, channel)	Construct the name of the HDF5 header dataset associated with the digitizer dataset. The header dataset stores shot numbers and other shot number specific meta-data. It also has a one- to-one row correspondence with the digitizer dataset. The header dataset name follows the format::.
`deduce_config_active_status`(config_name)	Determines if data was recorded using the configuration specified by `config_name`.
`get_adc_info`(board, channel[, adc, config_name])	Get adc setup info dictionary associated with board and channel.
`get_slot`(brd, adc)	Get slot number for given board number and adc.

Attributes Documentation

active_configs¶: List of active digitizer configurations

configs¶

Dictionary containing al the relevant mapping information to translate the HDF5 data into a numpy array by HDFReadData.

– Constructing configs –

The configs dict is a nested dictionary where the first level of keys represents the digitizer configuration names. Each configuration dictionary then consists of a set of non-polymorphic and polymorphic keys. Any additional keys are currently ignored. The non-polymorphic keys are as follows:

Required Non-Polymorphic keys for `config=configs['config name']`¶
Key	Description
config['active']	`True` or `False` indicating if this configuration was used in recording the digitizer datasets
config['adc']	Tuple of strings naming the adc’s used for this configuration. For example, ('SIS 3301', )
config['config group path']	Internal HDF5 path to the digitizer configuration group. For example, '/foo/bar/SIS 3301/Configuration: first_run'
config['shotnum']	Dictionary defining how the digitzier shot numbers are recorded. It is assumed, the shot numbers are recorded in the header dataset associated with the main dataset. The dictionary should look like, config['shotnum'] = { 'dset field': ('Shot number',), 'shape': (), 'dtype': numpy.uint32, } where `'dset field'` is the field name of the header dataset containing shot numbers, `'shape'` is the numpy shape of the shot number data, and `'dtype'` is the numpy `dtype` of the data. This all defines the numpy `dtype` of the `'shotnum'` field in the `HDFReadData` constructed numpy array.

The required polymorphic keys are the names of each adc listed in configs['config name']['adc']. These entries contain the adc board and channel hookup configuration, as well as, the adc setup configuration for each connected board. Continuing with the example above, this key would look something like

>>> type(config['SIS 3301'])
tuple
>>> type(config['SIS 3301'][0])
tuple
>>> len(config['SIS 3301'][0])
3

where each nested tuple represents one board connection to the adc and is 3 elements long. The breakdown of the nested tuple follows:

Breakdown of Polymorphic Key. (`config=configs['config name']`)¶
Key	Description
config['SIS 3301'][0][0]	`int` representing the connected board number
config['SIS 3301'][0][1]	`Tuple[int, ...]` representing the connected channel numbers associated with the board number
config['SIS 3301'][0][2]	`Dict[str, Any]` representing the setup configuration of the adc. The dictionary should look like: config['SIS 3301'][0][2] = { 'bit: 10, 'clock rate': astropy.units.Quantity(100.0, unit='MHz'), 'nshotnum': 10, 'nt': 10000, 'sample average (hardware)': None, 'shot average (software)': None, } where `'bit'` represents the bit resolution of the adc, `'clock rate'` represents the base clock rate of the adc, `'nshotnum'` is the number of shot numbers recorded, `'nt'` is the number of time samples recorded, `'sample average (hardware)'` is the number of time samples averaged together (this and the `'clock rate'` make up the `'sample rate'`), and `'shot average (software)'` is the number of shots intended to be average together.

device_adcs¶: Tuple of the analog-digital-convert (adc) names integrated into the digitizer.

device_name¶: Name of digitizer

group¶: Instance of the HDF5 digitizer group

info¶

Digitizer dictionary of meta-info. For example,

info = {
    'group name': 'Digitizer',
    'group path': '/foo/bar/Digitizer',
}

slot_info¶: Slot info dictionary. Contains relationship between slot number and the associated board number and adc name.

Methods Documentation

construct_dataset_name(board: int, channel: int, config_name=None, adc=None, return_info=False) → str | Tuple[str, Dict[str, Any]]¶

Construct the name of the HDF5 dataset containing digitizer data. The dataset naming follows two formats based on their associated adc:

# for 'SIS 3302'
'<config_name> [Slot <slot>: SIS 3302 ch <ch>]'

# for 'SIS 3305'
'<config_name> [Slot <slot>: SIS 3305 FPGA <num> ch <ch>]'

where <config_name> is the digitizer configuration name, <slot> is the slot number in the digitizer crate that is associated with the board number, <ch> is the requested channel number, and <num> is the FPGA number. Only the ‘SIS 3305’ utilizes the FPGA nomenclature, where channels 1-4 reside on ‘FPGA 1’ and channels 5-8 reside on ‘FPGA 2’.

Parameters:

board – board number
channel – channel number
config_name (str) – digitizer configuration name
adc (str) – analog-digital-converter name
return_info (bool) – True will return a dictionary of meta-info associated with the digitizer data (DEFAULT False)

Returns:

digitizer dataset name. If return_info=True, then returns a tuple of (dataset name, dictionary of meta-info)

The returned adc information dictionary looks like:

adc_dict = {
    'adc': str,
    'bit': int,
    'clock rate': astropy.units.Quantity,
    'configuration name': str,
    'digitizer': str,
    'nshotnum': int,
    'nt': int,
    'sample average (hardware)': int,
    'shot average (software)': int,
}

construct_header_dataset_name(board: int, channel: int, config_name=None, adc=None, **kwargs) → str¶

Construct the name of the HDF5 header dataset associated with the digitizer dataset. The header dataset stores shot numbers and other shot number specific meta-data. It also has a one- to-one row correspondence with the digitizer dataset. The header dataset name follows the format:

'<dataset name> headers'

where <dataset name> is the digitizer dataset name specified by the input arguments and constructed by construct_dataset_name().

Parameters:

board – board number
channel – channel number
config_name (str) – digitizer configuration name
adc (str) – analog-digital-converter name

Returns:

header dataset name associated with the digitizer dataset

deduce_config_active_status(config_name: str) → bool¶

Determines if data was recorded using the configuration specified by config_name. This is done by comparing the configuration name against the dataset names.

Parameters:: config_name – digitizer configuration name
Returns:: True if the configuration was used in recording the group datasets; otherwise, False

Note

If the digitizer does not use the configuration name in the name of the created datasets, then the subclassing digitzier mapping class should override this method with a rule that is appropriate for the digitizer the class is being designed for.

get_adc_info(board: int, channel: int, adc=None, config_name=None) → Dict[str, Any]¶

Get adc setup info dictionary associated with board and channel.

Parameters:

board – board number
channel – channel number
adc (str) – analog-digital-converter name
config_name – digitizer configuration name

Returns:

dictionary of adc setup info (bit, clock rate, averaging, etc.) associated with board* and **channel

get_slot(brd: int, adc: str) → None | int¶

Get slot number for given board number and adc.

Parameters:

brd – board number
adc – digitizer analog-digital-converter name

Returns:

slot number, or None if there is no associated slot number