2.1.1.0 autoflag.settimemed

autoflag.settimemed - Function

2.1.1 Sets up the time-median flagging method
Description

The timemed method uses a median-in-time filter. It works by computing a sliding median of some value d_cbt (where c is frequency channel, b is baseline, and t is time slot), as specified by the expr parameter (see the general autoflag module description for details of how expr determines d.) The sliding median is computed in time, on a per-channel, per-baseline basis:

mxcbt = median{dxcbt′, where |t′ - t| ≤ δ}

(where δ is given by the hw parameter.) Then, a median absolute deviation (MAD) of the data with respect to the median is computed on a per-row basis:

M xbt = median{|dxcbt- mxcbt|, for all c}

(For single-channel data, M_bt ≡ m_0bt.) M_bt is then smoothed by applying a sliding median in time:

˜ ′ ′ ˜ M xbt = median{M xbt, where |t- t| ≤ δ}

(where is given by the rowhw parameter.) All points where

|dxcbt - mxcbt| > θM ˜ xbt

are then flagged. The threshold level θ is given by the thr parameter.

In addition, timemed can also flag entire rows based on their MAD. This is only performed for line data (specifically, when there are at least 10 channels per row), and may be explicitly disabled by specifying norow=T. To do this, it first computes a per-baseline MAD of the MAD:

Mˆxb = median{|M xbt- M˜xbt|, for all t}

and flags rows where |M_bt -_bt| > _b, where is given by the rowthr parameter.

Timemed will iterate over the measurement set – and compute m_cbt – only once. Existing flags are taken into account at this time (unless fignore is specified). MADs are then computed and recomputed iteratively, dropping flagged points and rows, until convergence is achieved (i.e. no more flags are raised). Since m_cbt is not recomputed as new flags are raised, running this method a second time may sometimes be of use.

Arguments


Inputs
thr	Flagging threshold
	allowed:	double
	Default:	5.0
hw	Half-window for the sliding median, if time slots is less than 4 times half window, ignoring this chunk
	allowed:	int
	Default:	10
rowthr	Row flagging threshold
	allowed:	double
	Default:	10.0
rowhw	Half-window for the sliding median of the MAD
	allowed:	int
	Default:	10
norow	Disable row flagging
	allowed:	bool
	Default:	false
column	Which column to base flagging on
	allowed:	string
	Default:	MODEL CORR DATA
expr	Expression to use
	allowed:	string
	Default:	ABS I
fignore	Ignore existing flags
	allowed:	bool
	Default:	false

Returns
bool

Example

- af:=autoflag(’3C273XC1.MS’)
- af.setdata()
- af.settimemed(thr=5,hw=5,expr="- ABS RR LL")

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