pipeline.domain.datatable.DataTableImpl

class DataTableImpl(name=None, readonly=None)[source]

Bases: object

DataTable is an object to hold meta data of scantable on memory.

row layout: [Row, Scan, IF, Pol, Beam, Date, Time, ElapsedTime,

0, 1, 2, 3, 4, 5, 6, 7,

Exptime, RA, DEC, Az, El, nchan, Tsys, TargetName,: 8, 9, 10, 11, 12, 13, 14, 15,
Statistics, Flags, PermanentFlags, SummaryFlag, Nmask, MaskList, NoChange, Ant]: 16, 17, 18, 19, 20, 21, 22, 23

Statistics: DataTable[ID][16] =

[LowFreqRMS, NewRMS, OldRMS, NewRMSdiff, OldRMSdiff, ExpectedRMS, ExpectedRMS]: 0, 1, 2, 3, 4, 5, 6

Flags: DataTable[ID][17] =

[LowFrRMSFlag, PostFitRMSFlag, PreFitRMSFlag, PostFitRMSdiff, PreFitRMSdiff, PostFitExpRMSFlag, PreFitExpRMSFlag]: 0, 1, 2, 3, 4, 5, 6

PermanentFlags: DataTable[ID][18] =

[WeatherFlag, TsysFlag, UserFlag]: 0, 1, 2

Note for Flags: 1 is valid, 0 is invalid

Methods

`addrows`
`colnames`
`export_rwtable_exclusive`	Export "on-memory" RW table to the one on disk.
`exportdata`	name -- name of exported DataTable overwrite -- overwrite existing DataTable
`get_posdict`
`get_rotable_name`
`get_rwtable_name`
`get_timegap`
`get_timetable`
`getcell`
`getcellslice`
`getcol`
`getcolkeyword`
`getcolslice`
`getkeyword`	name -- keyword name
`haskeyword`
`importdata`	name -- name of DataTable to be imported
`importdata2`	name -- name of DataTable to be imported
`keywordnames`	return table keyword names
`putcell`	name -- column name idx -- row index val -- value to be put
`putcellslice`
`putcol`
`putcolslice`
`putkeyword`	name -- keyword name val -- keyword value
`set_timetable`
`sync`	Sync with DataTable on disk.

Attributes

`REFKEY`
`direction_ref`
`name`
`nrow`
`position_group_id`
`time_group_id_large`
`time_group_id_small`

__init__(name=None, readonly=None)[source]: name (optional) -- name of DataTable

export_rwtable_exclusive(dirty_rows=None, cols=None)[source]

Export "on-memory" RW table to the one on disk.

To support parallel operation, the method will acquire a lock for RW table to ensure the operation in one process doesn't overwrite the changes made by other processes.

dirty_rows -- list of row numbers that are updated. If None, everything: including unchanged rows will be flushed. Default is None.
cols -- list of columns that are updated. If None, all rows will be flushed.: default is None.

exportdata(name=None, minimal=True, overwrite=False)[source]: name -- name of exported DataTable overwrite -- overwrite existing DataTable

getkeyword(name)[source]: name -- keyword name

importdata(name, minimal=True, readonly=True)[source]: name -- name of DataTable to be imported

importdata2(name, minimal=True, readonly=True)[source]: name -- name of DataTable to be imported

keywordnames()[source]: return table keyword names

putcell(name, idx, val)[source]: name -- column name idx -- row index val -- value to be put

putkeyword(name, val)[source]: name -- keyword name val -- keyword value

sync(minimal=True)[source]: Sync with DataTable on disk.