subvs
Module Contents
Classes
subvs ---- Vector-subtraction in UV using selected time ranges and spectral channels as background |
Functions
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Attributes
- class subvs._subvs[source]
subvs —- Vector-subtraction in UV using selected time ranges and spectral channels as background
Split is the general purpose program to make a new data set that is a subset or averaged form of an existing data set. General selection parameters are included, and one or all of the various data columns (DATA, LAG_DATA and/or FLOAT_DATA, and possibly MODEL_DATA and/or CORRECTED_DATA) can be selected.
Split is often used after the initial calibration of the data to make a smaller measurement set with only the data that will be used in further flagging, imaging and/or self-calibration. split can average over frequency (channels) and time (integrations).
——— parameter descriptions ———————————————
vis Name of input measurement set outputvis Name of output measurement set timerange Select the time range of the input visbility to be subtracted from spw Select the spectral channels of the input visibility to be subtracted from mode Operation: linear, highpass subtime1 Select the first time range as the background for uv subtraction subtime2 Select the second time range as the background for uv subtraction smoothaxis Select the axis along which smooth is performed smoothtype Select the smooth type smoothwidth Select the width of the smoothing window splitsel Split the selected timerange and spectral channels as outputvis reverse Reverse the sign of the background-subtracted data (for absorptive structure) overwrite Overwrite the already existing output measurement set
——— examples ———————————————————–
Subvs is a task to do UV vector-subtraction, by selecting time ranges in the data as background. Subvs can be used to subtract the background continuum emission to separate the time-dependent emission, e.g. solar coherent radio bursts.
Keyword arguments: vis – Name of input visibility file (MS) default: none; example: vis=’ngc5921.ms’ outputvis – Name of output uv-subtracted visibility file (MS) default: none; example: outputvis=’ngc5921_src.ms’ timerange – Time range of performing the UV subtraction: default=’’ means all times. examples: timerange = ‘YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss’ timerange = ‘hh:mm:ss~hh:mm:ss’ spw – Select spectral window/channel. default = ‘’ all the spectral channels. Example: spw=’0:1~20’ mode – operation mode default ‘linear’ mode = ‘linear’: use a linear fit for the background to be subtracted mode = ‘lowpass’: act as a lowpass filter—smooth the data using different smooth types and smooth window size. Can be performed along either time or frequency axis mode = ‘highpass’: act as a highpass filter—smooth the data first, and subtract the smoothed data from the original. Can be performed along either time or frequency axis mode = ‘linear’ expandable parameters: subtime1 – Time range 1 of the background to be subtracted from the data default=’’ means all times. format: timerange = ‘YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss’ timerange = ‘hh:mm:ss~hh:mm:ss’ subtime2 – Time range 2 of the backgroud to be subtracted from the data default=’’ means all times. examples: timerange = ‘YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss’ timerange = ‘hh:mm:ss~hh:mm:ss’ mode = ‘lowpass’ or ‘highpass’ expandable parameters: smoothaxis – axis of smooth Default: ‘time’ smoothaxis = ‘time’: smooth is along the time axis smoothaxis = ‘freq’: smooth is along the frequency axis smoothtype – type of the smooth depending on the convolving kernel Default: ‘flat’ smoothtype = ‘flat’: convolving kernel is a flat rectangle, equivalent to a boxcar moving smooth smoothtype = ‘hanning’: Hanning smooth kernel. See numpy.hanning smoothtype = ‘hamming’: Hamming smooth kernel. See numpy.hamming smoothtype = ‘bartlett’: Bartlett smooth kernel. See numpy.bartlett smoothtype = ‘blackman’: Blackman smooth kernel. See numpy.blackman smoothwidth – width of the smooth kernel Default: 5 Examples: smoothwidth=5, meaning the width is 5 pixels splitsel – True or False. default = False. If splitsel = False, then the entire input measurement set is copied as the output measurement set (outputvis), with background subtracted at selected timerange and spectral channels. If splitsel = True,then only the selected timerange and spectral channels are copied into the output measurement set (outputvis). reverse – True or False. default = False. If reverse = False, then the times indicated by subtime1 and/or subtime2 are treated as background and subtracted; If reverse = True, then reverse the sign of the background-subtracted data. The option can be used for mapping absorptive structure. overwrite – True or False. default = False. If overwrite = True and outputvis already exists, the selected subtime and spw in the output measurment set will be replaced with background subtracted visibilities