Spectral classes and functions

Classes and functions for managing and processing spectra

Core Functions

Core functions for spectral data.

dysh.spectra.core.average(data, axis=0, weights=None)

Average a group of spectra or scans.

Parameters:

datandarray

The spectral data, typically with shape (nspect,nchan).

axisint

The axis over which to average the data. Default axis=0 will return the average spectrum if shape is (nspect,nchan)

weightsndarray

The weights to use in averaging. These might typically be system temperature based. The weights array must be the length of the axis over which the average is taken. Default: None will use equal weights

Returns:

averagendarray

The average along the input axis

dysh.spectra.core.baseline(spectrum, order, exclude=None, **kwargs)

Fit a baseline for a spectrum

Parameters:

spectrumSpectrum

The input spectrum

orderint

The order of the polynomial series, a.k.a. baseline order

excludelist of 2-tuples of int or Quantity, or SpectralRegion

List of region(s) to exclude from the fit. The tuple(s) represent a range in the form [lower,upper], inclusive. Examples:

One channel-based region:

>>> [11,51]

Two channel-based regions:

>>> [(11,51),(99,123)]

One Quantity region:

>>> [110.198*u.GHz,110.204*u.GHz].

One compound SpectralRegion:

>>> SpectralRegion([(110.198*u.GHz,110.204*u.GHz),(110.196*u.GHz,110.197*u.GHz)]).
Default: no exclude region

modelstr

One of ‘polynomial’, ‘chebyshev’, ‘legendre’, ‘hermite’. Default: ‘chebyshev’

fitter_FitterMeta

The fitter to use. Default: LinearLSQFitter (with calc_uncertaintes=True). Be care when choosing a different fitter to be sure it is optimized for this problem.

Returns:

modelslist of Model

The list of models that contain the fitted model parameters. See fit_continuum.

dysh.spectra.core.exclude_to_mask(exclude, refspec)

dysh.spectra.core.exclude_to_region(exclude, refspec, fix_exclude=False)

Convert an exclude list to a list of ~specutuls.SpectralRegion.

Parameters:

excludelist of 2-tuples of int or Quantity, or SpectralRegion

List of region(s) to exclude from the fit. The tuple(s) represent a range in the form [lower,upper], inclusive. Examples:

One channel-based region:

>>> [11,51]

Two channel-based regions:

>>> [(11,51),(99,123)]

One Quantity region:

>>> [110.198*u.GHz,110.204*u.GHz].

One compound SpectralRegion:

>>> SpectralRegion([(110.198*u.GHz,110.204*u.GHz),(110.196*u.GHz,110.197*u.GHz)]).

refspec: `~spectra.spectrum.Spectrum`

The reference spectrum whose spectral axis will be used when converting between exclude and axis units (e.g. channels to GHz).

fix_exclude: bool

If True, fix exclude regions that are out of bounds of the specctral axis to be within the spectral axis. Default:False

Returns:

regionlistlist of SpectralRegion

A list of SpectralRegion corresponding to exclude with units of the refspec.spectral_axis.

dysh.spectra.core.find_non_blanks(data)

Finds the indices of blanked integrations.

Parameters:

datandarray

The spectral data, typically with shape (nspect,nchan).

Returns:

blanksndarray

Array with indices of blanked integrations.

dysh.spectra.core.get_spectral_equivalency(restfreq, velocity_convention)

dysh.spectra.core.mean_tsys(calon, caloff, tcal, mode=0, fedge=0.1, nedge=None)

Get the system temperature from the neighboring calon and caloff, which reflect the state of the noise diode. We define an extra way to set the edge size, nedge, if you prefer to use number of edge channels instead of the inverse fraction. This implementation recreates GBTIDL’s dcmeantsys.

Parameters:

calonndarray-like

ON calibration

caloffndarray-like

OFF calibration

tcalndarray-like

calibration temperature

modeint

mode=0 Do the mean before the division mode=1 Do the mean after the division

fedgefloat

Fraction of edge channels to exclude at each end, a number between 0 and 1. Default: 0.1, meaning the central 80% bandwidth is used

nedgeint

Number of edge channels to exclude. Default: None, meaning use fedge

Returns:

meanTsysndarray-like

The mean system temperature

dysh.spectra.core.region_to_axis_indices(region, refspec)

Parameters:

regionSpectralRegion

refspec: `~spectra.spectrum.Spectrum`

The reference spectrum whose spectral axis will be used when converting between exclude and axis units (e.g., channels to GHz).

Returns:

indices2-tuple of int

The array indices in refspec corresponding to region.bounds

dysh.spectra.core.sq_weighted_avg(a, axis=0, weights=None)

Compute the mean square weighted average of an array (2nd moment).

\(v = \sqrt{\frac{\sum_i{w_i~a_i^{2}}}{\sum_i{w_i}}}\)

Parameters:

andarray

The data to average.

axisint

The axis over which to average the data. Default: 0

weightsndarray or None

The weights to use in averaging. The weights array must be the length of the axis over which the average is taken. Default: None will use equal weights.

Returns:

averagendarray

The square root of the squared average of a along the input axis.

dysh.spectra.core.tsys_weight(exposure, delta_freq, tsys)

Compute the system temperature based weight(s) using the expression:

\(w = t_{exp} \times \delta_\nu / T_{sys}^2,\)

If exposure, delta_freq, or tsys parameters are given as Quantity, they will be converted to seconds, Hz, K, respectively for the calculation. (Not that this really matters since weights are relative to each other)

>>> import astropy.units as u
>>> [3*u.s, 4*u.s]   ### WRONG

Rather, if using Quantity, they have to be Quantity objects, e.g.,

>>> [3, 4]*u.s ### RIGHT!

Parameters:

exposurendarray, float, or Quantity

The exposure time, typically given in seconds

delta_freqndarray, float, or Quantity

The channel width in frequency units

tsysndarray, float, or Quantity

The system temperature, typically in K

Returns:

weightndarray

The weights array

Spectrum

The Spectrum class to contain and manipulate spectra.

class dysh.spectra.spectrum.Spectrum(*args, **kwargs)

Bases: Spectrum1D

This class contains a spectrum and its attributes. It is built on Spectrum1D with added attributes like baseline model. Note that Spectrum1D can contain multiple spectra but we probably will not use that because the restriction that it can have only one spectral axis conflicts with slight Doppler shifts. See Spectrum1D for the instantiation arguments.

Attributes:

array_axis_physical_types

Returns the WCS physical types that vary along each array axis.

baseline_model

Returns the computed baseline model or None if it has not yet been computed.

bin_edges

combined_wcs

The WCS transform for the NDCube, including the coordinates specified in .extra_coords.

data

ndarray-like : The stored dataset.

dimensions

doppler_convention

String representation of the velocity (Doppler) convention

energy

The energy of the spectral axis as a Quantity in units of eV.

equivalencies

Get the spectral axis equivalencies that can be used in converting the axis

exclude_regions

extra_coords

Coordinates not described by NDCubeABC.wcs which vary along one or more axes.

flux

Converts the stored data and unit information into a quantity.

frequency

The spectral_axis as a Quantity in units of GHz

global_coords

Coordinate metadata which applies to the whole cube.

mask

any type : Mask for the dataset, if any.

meta

dict-like : Additional meta information about the dataset.

observer

Returns ——- observer : BaseCoordinateFrame or derivative The coordinate frame of the observer if present.

obstime

photon_flux

The flux density of photons as a Quantity, in units of

plotter

psf

Image representation of the PSF for the dataset.

radial_velocity

The radial velocity(s) of the objects represented by this spectrum.

redshift

The redshift(s) of the objects represented by this spectrum.

rest_value

shape

spectral_axis

Returns the SpectralCoord object.

spectral_axis_direction

spectral_axis_unit

Deprecated since version v1.1.

spectral_wcs

Returns the spectral axes of the WCS

target

uncertainty

any type : Uncertainty in the dataset, if any.

unit

Unit : Unit for the dataset, if any.

velocity

Converts the spectral axis array to the given velocity space unit given the rest value.

velocity_convention

Returns the velocity convention

velocity_frame

String representation of the velocity frame

wavelength

The spectral_axis as a Quantity in units of Angstroms

wcs

any type : A world coordinate system (WCS) for the dataset, if any.

Methods

add(operand[, operand2])	Performs addition by evaluating self + operand.
axis_velocity([unit])	Get the spectral axis in velocity units.
axis_world_coords(*axes[, pixel_corners, wcs])	Returns objects representing the world coordinates of pixel centers for a desired axes.
axis_world_coords_values(*axes[, ...])	Returns the world coordinate values of all pixels for desired axes.
baseline(degree[, exclude, include])	Compute and optionally remove a baseline.
bshow()	Show the baseline model
collapse(method[, axis])	Collapse the flux array given a method.
crop(*points[, wcs])	Crop using real world coordinates.
crop_by_values(*points[, units, wcs])	Crop using real world coordinates.
divide(operand[, operand2])	Performs division by evaluating self / operand.
explode_along_axis(axis)	Separates slices of NDCubes along a given axis into an NDCubeSequence of (N-1)DCubes.
make_spectrum(data, meta[, use_wcs, ...])	Factory method to create a Spectrum object from a data and header.
multiply(operand[, operand2])	Performs multiplication by evaluating self * operand.
new_flux_unit(unit[, equivalencies, ...])	Converts the flux data to the specified unit.
plot(**kwargs)	Visualize the NDCube.
rebin(bin_shape[, operation, ...])	Downsample array by combining contiguous pixels into bins.
reproject_to(target_wcs[, algorithm, ...])	Reprojects the instance to the coordinates described by another WCS object.
savefig(file, **kwargs)	Save the plot
set_convention(doppler_convention)	Set the velocity convention of this Spectrum.
set_frame(toframe)	Set the sky coordinate and doppler tracking reference frame of this Spectrum.
set_radial_velocity_to(radial_velocity)	This sets the radial velocity of the spectrum to be radial_velocity without changing the values of the spectral_axis.
set_redshift_to(redshift)	This sets the redshift of the spectrum to be redshift without changing the values of the spectral_axis.
shift_spectrum_to(*[, redshift, radial_velocity])	This shifts in-place the values of the spectral_axis, given either a redshift or radial velocity.
stats()	Compute some statistics of this Spectrum.
subtract(operand[, operand2])	Performs subtraction by evaluating self - operand.
to(new_unit, **kwargs)	Convert instance to another unit.
undo_baseline()	Undo the most recently computed baseline.
velocity_axis_to([unit, toframe, ...])	Parameters:
with_frame(toframe)	Return a copy of this Spectrum with a new coordinate reference frame.
with_spectral_unit(unit[, ...])	Returns a new spectrum with a different spectral axis unit.
with_velocity_convention(doppler_convention)	Returns a copy of this Spectrum with the input velocity convention.

get_velocity_shift_to
list_to_spectral_region
max
mean
median
min
read
smooth
sum
write

axis_velocity(unit=Unit('km / s'))

Get the spectral axis in velocity units. Note: This is not the same as Spectrum.velocity, which includes the source radial velocity.

Parameters:

unitQuantity or str that can be converted to Quantity

The unit to which the axis is to be converted

Returns

——-

velocityQuantity

The converted spectral axis velocity

baseline(degree, exclude=None, include=None, **kwargs)

Compute and optionally remove a baseline. The model for the baseline can be either a 1D polynomial model or a 1D Chebyshev polynomial of the first kind. The code uses astropy.modeling and astropy.fitter to compute the baseline. See the documentation for those modules. This method will set the baseline_model attribute to the fitted model function which can be evaluated over a domain.

Note that include= and exclude= are mutually exclusive.

Parameters:

degreeint

The degree of the polynomial series, a.k.a. baseline order

excludelist of 2-tuples of int or ~astropy.units.Quantity, or ~specutils.SpectralRegion

List of region(s) to exclude from the fit. The tuple(s) represent a range in the form [lower,upper], inclusive. In channel units.

Examples:

One channel-based region: [11,51]

Two channel-based regions: [(11,51),(99,123)].

One ~astropy.units.Quantity region: [110.198*u.GHz,110.204*u.GHz].

One compound SpectralRegion: SpectralRegion([(110.198*u.GHz,110.204*u.GHz),(110.196*u.GHz,110.197*u.GHz)]).

Default: no exclude region

include: list of 2-tuples of int (currently units not supported yet, pending issue 251/260)

modelstr

One of ‘polynomial’ ‘chebyshev’, ‘legendre’, or ‘hermite’ Default: ‘chebyshev’

fitter_FitterMeta

The fitter to use. Default: LinearLSQFitter (with calc_uncertaintes=True). Be care when choosing a different fitter to be sure it is optimized for this problem.

removebool

If True, the baseline is removed from the spectrum. Default: False

normalizebool

If True, the frequency axis is internally rescaled from 0..1 to avoid roundoff problems (and make the coefficients slightly more understandable). This is usually needed for a polynomial, though overkill for the others who do their own normalization. CAVEAT: with normalize=True, you cannot undo a baseline fit. Default: False

property baseline_model

Returns the computed baseline model or None if it has not yet been computed.

bshow()

Show the baseline model

property doppler_convention

String representation of the velocity (Doppler) convention

property equivalencies

Get the spectral axis equivalencies that can be used in converting the axis between km/s and frequency or wavelength

property exclude_regions

get_velocity_shift_to(toframe)

list_to_spectral_region(inlist)

classmethod make_spectrum(data, meta, use_wcs=True, observer_location=None)

Factory method to create a Spectrum object from a data and header.

Parameters:

datandarray

The data array. See Spectrum1D

metadict

The metadata, typically derived from an SDFITS header. Required items in meta are ‘CTYPE[123]’,’CRVAL[123]’, ‘CUNIT[123]’, ‘VELOCITY’, ‘EQUINOX’, ‘RADESYS’

use_wcsbool

If True, create a WCS object from meta

observer_locationEarthLocation

Location of the observatory. See Observatory. This will be transformed to ITRS using the time of observation DATE-OBS or MJD-OBS in meta.

Returns:

spectrumSpectrum

The spectrum object

property observer

Returns:

observerBaseCoordinateFrame or derivative

The coordinate frame of the observer if present.

property obstime

plot(**kwargs)

Visualize the NDCube.

Parameters:

axes: `~astropy.visualization.wcsaxes.WCSAxes` or None:, optional

The axes to plot onto. If None the current axes will be used.

plot_axes: `list`, optional

A list of length equal to the number of pixel dimensions in array axis order. This list selects which cube axes are displayed on which plot axes. For an image plot this list should contain 'x' and 'y' for the plot axes and None for all the other elements. For a line plot it should only contain 'x' and None for all the other elements.

axes_unit: `list`, optional

A list of length equal to the number of world dimensions specifying the units of each axis, or None to use the default unit for that axis.

axes_coordinates: `list`, optional

A list of length equal to the number of pixel dimensions. For each axis the value of the list should either be a string giving the world axis type or None to use the default axis from the WCS.

data_unit: `astropy.units.Unit`

The data is changed to the unit given or the NDCube.unit if not given.

wcs: `astropy.wcs.wcsapi.BaseHighLevelWCS`

The WCS object to define the coordinates of the plot axes.

kwargs

Additional keyword arguments are given to the underlying plotting infrastructure which depends on the dimensionality of the data and whether 1 or 2 plot_axes are defined: - Animations: mpl_animators.ArrayAnimatorWCS - Static 2-D images: matplotlib.pyplot.imshow - Static 1-D line plots: matplotlib.pyplot.plot

property plotter

savefig(file, **kwargs)

Save the plot

set_convention(doppler_convention)

Set the velocity convention of this Spectrum. The spectral axis of this Spectrum will be replaced with a new spectral axis with the input velocity convention. The header ‘VELDEF’ value will be changed accordingly.

To make a copy of this Spectrum with a new velocity convention instead, use with_velocity_convention.

Parameters:

doppler_convention - str

The velocity convention, one of ‘radio’, ‘optical’, ‘relativistic’

set_frame(toframe)

Set the sky coordinate and doppler tracking reference frame of this Spectrum. The header ‘CTYPE1’ will be changed accordingly.

To make a copy of this Spectrum with new coordinate referece frmae instead, use with_frame.

Parameters:

toframe - str

The coordinate reference frame identifying string, as used by astropy, e.g. ‘hcrs’, ‘icrs’, etc.

smooth()

stats()

Compute some statistics of this Spectrum. The mean, rms, data minimum and data maximum are calculated. Note this works with slicing, so, e.g., myspectrum[45:153].stats() will return the statistics of the slice.

Returns:

statstuple

Tuple consisting of (mean,rms,datamin,datamax)

property target

undo_baseline()

Undo the most recently computed baseline. If the baseline has been subtracted, it will be added back. The baseline_model attribute is set to None. Exclude regions are untouched.

velocity_axis_to(unit=Unit('km / s'), toframe=None, doppler_convention=None)

Parameters:

unitQuantity or str that can be converted to Quantity

The unit to which the axis is to be converted

toframestr

The coordinate frame to convert to, e.g. ‘hcrs’, ‘icrs’

doppler_conventionstr

The Doppler velocity covention to use, one of ‘optical’, ‘radio’, or ‘rest’

Returns:

velocityQuantity

The converted spectral axis velocity

property velocity_frame

String representation of the velocity frame

with_frame(toframe)

Return a copy of this Spectrum with a new coordinate reference frame.

Parameters:

toframe - str

The coordinate reference frame identifying string, as used by astropy, e.g. ‘hcrs’, ‘icrs’, etc.

Returns:

spectrumSpectrum

A new Spectrum object

with_velocity_convention(doppler_convention)

Returns a copy of this Spectrum with the input velocity convention. The header ‘VELDEF’ value will be changed accordingly.

Parameters:

doppler_convention - str

The velocity convention, one of ‘radio’, ‘optical’, ‘relativistic’

Returns:

spectrumSpectrum

A new Spectrum object

dysh.spectra.spectrum.ascii_spectrum_writer_basic(spectrum, fileobj, **kwargs)

dysh.spectra.spectrum.ascii_spectrum_writer_commented_header(spectrum, fileobj, **kwargs)

dysh.spectra.spectrum.ascii_spectrum_writer_fixed_width(spectrum, fileobj, **kwargs)

dysh.spectra.spectrum.ascii_spectrum_writer_ipac(spectrum, fileobj, **kwargs)

dysh.spectra.spectrum.spectrum_writer_votable(spectrum, fileobj, **kwargs)

Scan

The classes that define various types of Scan and their calibration methods.

class dysh.spectra.scan.FSScan(gbtfits, scan, sigrows, calrows, bintable, calibrate=True, fold=True, use_sig=True, observer_location=<EarthLocation (882593.9465029, -4924896.36541728, 3943748.74743984) m>, debug=False)

Bases: ScanMixin

GBT specific version of Frequency Switch Scan

Parameters:

gbtfitsGBFITSLoad

input GBFITSLoad object

scanint

scan number that contains integrations with a series of sig/ref and calon/caloff states

sigrows: dict

dictionary containing with keys ‘ON’ and ‘OFF’ containing list of rows in sdfits corresponding to sig=T (ON) and sig=F (OFF) integrations.

calrowsdict

dictionary containing with keys ‘ON’ and ‘OFF’ containing list of rows in sdfits corresponding to cal=T (ON) and cal=F (OFF) integrations.

bintableint

the index for BINTABLE in sdfits containing the scans

calibrate: bool

whether or not to calibrate the data. If true, data will be calibrated as TSYS*(ON-OFF)/OFF. Default: True

fold: bool

whether or not to fold the spectrum. Default: True

use_sigbool

whether to use the sig as the sig, or the ref as the sig. Default: True

observer_locationEarthLocation

Location of the observatory. See Observatory. This will be transformed to ITRS using the time of observation DATE-OBS or MJD-OBS in the SDFITS header. The default is the location of the GBT.

Attributes:

delta_freq

Get the array of channel frequency width

exposure

Get the array of exposure (integration) times for FSscan

fdnum

The feed number

folded

Has the FSscan been folded?

ifnum

The IF number

nchan

The number of channels in this scan

npol

The number of polarizations in this Scan

nrows

The number of rows in this Scan

pols

The polarization number(s)

scan

The scan number

tsys

The system temperature array.

Methods

calibrate(**kwargs)	Frequency switch calibration, following equations .
calibrated(i)	Return the calibrated Spectrum of this FSscan
finalspectrum([weights])	Average all times and polarizations in this Scan
polaverage([weights])	Average all polarizations in this Scan
timeaverage([weights])	Compute the time-averaged spectrum for this set of FSscans.

calibrate(**kwargs)

Frequency switch calibration, following equations … fold=True or fold=False is required

calibrated(i)

Return the calibrated Spectrum of this FSscan

Parameters:

iint

The index into the calibrated array

Returns:

spectrumSpectrum

property delta_freq

Get the array of channel frequency width

df = [ 0.5*(df_ref_on + df_ref_off) + 0.5*(df_sig_on + df_sig_off) ] / 2

Returns:

delta_freq: ~numpy.ndarray

The channel frequency width in units of the CDELT1 keyword in the SDFITS header

property exposure

Get the array of exposure (integration) times for FSscan

exposure = [ 0.5*(exp_ref_on + exp_ref_off) + 0.5*(exp_sig_on + exp_sig_off) ] / 2

Returns:

exposure~numpy.ndarray

The exposure time in units of the EXPOSURE keyword in the SDFITS header

property folded

Has the FSscan been folded?

Returns:

boolean

True if the signal and reference integrations have been folded. False if not.

timeaverage(weights='tsys')

Compute the time-averaged spectrum for this set of FSscans.

Parameters:

weights: str

‘tsys’ or None. If ‘tsys’ the weight will be calculated as:

\(w = t_{exp} \times \delta\nu/T_{sys}^2\)

Default: ‘tsys’

Returns

——-

spectrumSpectrum

The time-averaged spectrum

property tsys

The system temperature array. This will be None until calibration is done.

Returns:

tsysndarray

System temperature values in K

class dysh.spectra.scan.PSScan(gbtfits, scans, scanrows, calrows, bintable, calibrate=True, observer_location=<EarthLocation (882593.9465029, -4924896.36541728, 3943748.74743984) m>)

Bases: ScanMixin

GBT specific version of Position Switch Scan. A position switch scan object has one IF, one feed, and one or more polarizations.

Parameters:

gbtfitsGBFITSLoad

input GBFITSLoad object

scansdict

dictionary with keys ‘ON’ and ‘OFF’ containing unique list of ON (signal) and OFF (reference) scan numbers NOTE: there should be one ON and one OFF, a pair

scanrowsdict

dictionary with keys ‘ON’ and ‘OFF’ containing the list of rows in sdfits corresponding to ON (signal) and OFF (reference) integrations

calrowsdict

dictionary containing with keys ‘ON’ and ‘OFF’ containing list of rows in sdfits corresponding to cal=T (ON) and cal=F (OFF) integrations.

bintableint

the index for BINTABLE in sdfits containing the scans

calibrate: bool

whether or not to calibrate the data. If true, data will be calibrated as TSYS*(ON-OFF)/OFF. Default: True

observer_locationEarthLocation

Location of the observatory. See Observatory. This will be transformed to ITRS using the time of observation DATE-OBS or MJD-OBS in the SDFITS header. The default is the location of the GBT.

Attributes:

delta_freq

Get the array of channel frequency width

exposure

Get the array of exposure (integration) times

fdnum

The feed number

ifnum

The IF number

nchan

The number of channels in this scan

npol

The number of polarizations in this Scan

nrows

The number of rows in this Scan

pols

The polarization number(s)

scan

The scan number

scans

The dictionary of the ON and OFF scan numbers in the PSScan.

tsys

The system temperature array.

Methods

calibrate(**kwargs)	Position switch calibration, following equations 1 and 2 in the GBTIDL calibration manual
calibrated(i)	Return the calibrated Spectrum.
finalspectrum([weights])	Average all times and polarizations in this Scan
polaverage([weights])	Average all polarizations in this Scan
timeaverage([weights])	Compute the time-averaged spectrum for this set of scans.

calibrate(**kwargs)

Position switch calibration, following equations 1 and 2 in the GBTIDL calibration manual

calibrated(i)

Return the calibrated Spectrum.

Parameters:

iint

The index into the calibrated array

Returns:

spectrumSpectrum

property delta_freq

Get the array of channel frequency width

df = [ 0.5*(df_ref_on + df_ref_off) + 0.5*(df_sig_on + df_sig_off) ] / 2

Returns:

delta_freq: ~numpy.ndarray

The channel frequency width in units of the CDELT1 keyword in the SDFITS header

property exposure

Get the array of exposure (integration) times

exposure = [ 0.5*(exp_ref_on + exp_ref_off) + 0.5*(exp_sig_on + exp_sig_off) ] / 2

Returns:

exposure~numpy.ndarray

The exposure time in units of the EXPOSURE keyword in the SDFITS header

property scans

The dictionary of the ON and OFF scan numbers in the PSScan.

Returns:

scansdict

The scan number dictionary

timeaverage(weights='tsys')

Compute the time-averaged spectrum for this set of scans.

Parameters:

weights: str

‘tsys’ or None. If ‘tsys’ the weight will be calculated as:

\(w = t_{exp} \times \delta\nu/T_{sys}^2\)

Default: ‘tsys’

Returns

——-

spectrumSpectrum

The time-averaged spectrum

property tsys

The system temperature array. This will be None until calibration is done.

Returns:

tsysndarray

System temperature values in K

class dysh.spectra.scan.ScanBlock(*args)

Bases: UserList

This class contains a list of Scan objects, typically returned from e.g. gettp. Each Scan object may have different spectral characteristics. In order to access the i-th Scan object, use ScanBlock[i].

Methods

append(item)	S.append(value) -- append value to the end of the sequence
calibrate(**kwargs)	Calibrate all scans in this ScanBlock
clear()
count(value)
extend(other)	S.extend(iterable) -- extend sequence by appending elements from the iterable
finalspectrum([weights])	Average all times and polarizations in all scans this ScanBlock
index(value, [start, [stop]])	Raises ValueError if the value is not present.
insert(i, item)	S.insert(index, value) -- insert value before index
polaverage([weights])	Average all polarizations in all scans in this ScanBlock
pop([index])	Raise IndexError if list is empty or index is out of range.
remove(item)	S.remove(value) -- remove first occurrence of value.
reverse()	S.reverse() -- reverse IN PLACE
timeaverage([weights, mode])	Compute the time-averaged spectrum for all scans in this ScanBlock.

copy
sort

calibrate(**kwargs)

Calibrate all scans in this ScanBlock

finalspectrum(weights='tsys')

Average all times and polarizations in all scans this ScanBlock

Parameters:

weights: str

‘tsys’ or None. If ‘tsys’ the weight will be calculated as:

\(w = t_{exp} \times \delta\nu/T_{sys}^2\)

Default: ‘tsys’

Returns

——-

finalspectra: list of `~spectra.spectrum.Spectrum`

List of all the time- and polarization-averaged spectra

polaverage(weights='tsys')

Average all polarizations in all scans in this ScanBlock

Parameters:

weights: str

‘tsys’ or None. If ‘tsys’ the weight will be calculated as:

\(w = t_{exp} \times \delta\nu/T_{sys}^2\)

Default: ‘tsys’

Returns

——-

polaverage: list of `~spectra.spectrum.Spectrum`

List of all the polarization-averaged spectra

timeaverage(weights='tsys', mode='old')

Compute the time-averaged spectrum for all scans in this ScanBlock.

Parameters:

weights: str

‘tsys’ or None. If ‘tsys’ the weight will be calculated as:

\(w = t_{exp} \times \delta\nu/T_{sys}^2\)

Default: ‘tsys’

Returns

——-

timeaverage: list of `~spectra.spectrum.Spectrum`

List of all the time-averaged spectra

class dysh.spectra.scan.ScanMixin

Bases: object

This class describes the common interface to all Scan classes. A Scan represents one IF, one feed, and one or more polarizations. Derived classes must implement calibrate().

Attributes:

fdnum

The feed number

ifnum

The IF number

nchan

The number of channels in this scan

npol

The number of polarizations in this Scan

nrows

The number of rows in this Scan

pols

The polarization number(s)

scan

The scan number

Methods

calibrate(**kwargs)	Calibrate the Scan data
finalspectrum([weights])	Average all times and polarizations in this Scan
polaverage([weights])	Average all polarizations in this Scan
timeaverage([weights])	Compute the time-averaged spectrum for this scan.

calibrate(**kwargs)

Calibrate the Scan data

property fdnum

The feed number

Returns:

int

The index of the Feed

finalspectrum(weights=None)

Average all times and polarizations in this Scan

property ifnum

The IF number

Returns:

int

The index of the Intermediate Frequency

property nchan

The number of channels in this scan

Returns:

int

The number of channels in this scan

property npol

The number of polarizations in this Scan

Returns:

int

The number of polarizations in this Scan

property nrows

The number of rows in this Scan

Returns:

int

The number of rows in this Scan

polaverage(weights=None)

Average all polarizations in this Scan

property pols

The polarization number(s)

Returns:

list

The list of integer polarization number(s)

property scan

The scan number

Returns:

int

The scan number of the integrations in the Scan object

timeaverage(weights=None)

Compute the time-averaged spectrum for this scan.

Parameters:

weights: str

‘tsys’ or None. If ‘tsys’ the weight will be calculated as:

\(w = t_{exp} \times \delta\nu/T_{sys}^2\)

Default: ‘tsys’

Returns

——-

spectrumSpectrum

The time-averaged spectrum

class dysh.spectra.scan.SubBeamNodScan(sigtp, reftp, fulltp=None, method='cycle', calibrate=True, observer_location=<EarthLocation (882593.9465029, -4924896.36541728, 3943748.74743984) m>, **kwargs)

Bases: ScanMixin

Parameters:

sigtp: list of ~spectra.scan.TPScan

Signal total power scans

reftp: list ~spectra.scan.TPScan

Reference total power scans

fulltp: ~spectra.scan.TPScan

A full (sig+ref) total power scans, used only for method=’scan’

method: str

Method to use when processing. One of ‘cycle’ or ‘scan’. ‘cycle’ is more accurate and averages data in each SUBREF_STATE cycle. ‘scan’ reproduces GBTIDL’s snodka function which has been shown to be less accurate. Default:’cycle’

calibrate: bool

Whether or not to calibrate the data.

observer_locationEarthLocation

Location of the observatory. See Observatory. This will be transformed to ITRS using the time of observation DATE-OBS or MJD-OBS in the SDFITS header. The default is the location of the GBT.

weights: str

Weighting scheme to use when averaging the signal and reference scans ‘tsys’ or None. If ‘tsys’ the weight will be calculated as:

\(w = t_{exp} \times \delta\nu/T_{sys}^2\)

Default: ‘tsys’

Attributes:

delta_freq

exposure

fdnum

The feed number

ifnum

The IF number

nchan

The number of channels in this scan

npol

The number of polarizations in this Scan

nrows

The number of rows in this Scan

pols

The polarization number(s)

scan

The scan number

tsys

Methods

calibrate(**kwargs)	Calibrate the Scan data
finalspectrum([weights])	Average all times and polarizations in this Scan
polaverage([weights])	Average all polarizations in this Scan
timeaverage([weights])	Compute the time-averaged spectrum for this scan.

calibrated

calibrate(**kwargs)

Calibrate the Scan data

calibrated(i)

property delta_freq

property exposure

timeaverage(weights='tsys')

Compute the time-averaged spectrum for this scan.

Parameters:

weights: str

‘tsys’ or None. If ‘tsys’ the weight will be calculated as:

\(w = t_{exp} \times \delta\nu/T_{sys}^2\)

Default: ‘tsys’

Returns

——-

spectrumSpectrum

The time-averaged spectrum

property tsys

class dysh.spectra.scan.TPScan(gbtfits, scan, sigstate, calstate, scanrows, calrows, bintable, calibrate=True, observer_location=<EarthLocation (882593.9465029, -4924896.36541728, 3943748.74743984) m>)

Bases: ScanMixin

GBT specific version of Total Power Scan

Parameters:

gbtfitsGBFITSLoad

input GBFITSLoad object

scan: int

scan number

sigstatestr

one of ‘SIG’ or ‘REF’ to indicate if this is the signal or reference scan or ‘BOTH’ if it contains both

calstatestr

one of ‘ON’ or ‘OFF’ to indicate the calibration state of this scan, or ‘BOTH’ if it contains both

scanrowslist-like

the list of rows in sdfits corresponding to sig_state integrations

calrowsdict

dictionary containing with keys ‘ON’ and ‘OFF’ containing list of rows in sdfits corresponding to cal=T (ON) and cal=F (OFF) integrations for scan

bintableint

the index for BINTABLE in sdfits containing the scans

calibrate: bool

whether or not to calibrate the data. If True, the data will be (calon - caloff)*0.5, otherwise it will be SDFITS row data. Default:True

Attributes:

calstate

delta_freq

Get the array of channel frequency width

exposure

Get the array of exposure (integration) times

fdnum

The feed number

ifnum

The IF number

nchan

The number of channels in this scan

npol

The number of polarizations in this Scan

nrows

The number of rows in this Scan

pols

The polarization number(s)

scan

The scan number

sigstate

tsys

The system temperature array.

Methods

calc_tsys(**kwargs)	Calculate the system temperature array
calibrate(**kwargs)	Calibrate the Scan data
finalspectrum([weights])	Average all times and polarizations in this Scan
polaverage([weights])	Average all polarizations in this Scan
timeaverage([weights])	Compute the time-averaged spectrum for this set of scans.
total_power(i)	Return the total power spectrum

tpmeta

calc_tsys(**kwargs)

Calculate the system temperature array

property calstate

property delta_freq

Get the array of channel frequency width

df = 0.5*(df_ref_on + df_ref_off)

Note we only have access to the refon and refoff row indices so can’t use sig here. This is probably incorrect

Returns:

delta_freq: ndarray

The channel frequency width in units of the CDELT1 keyword in the SDFITS header

property exposure

Get the array of exposure (integration) times

exposure = 0.5*(exp_ref_on + exp_ref_off)

Note we only have access to the refon and refoff row indices so can’t use sig here. This is probably incorrect

Returns:

exposurendarray

The exposure time in units of the EXPOSURE keyword in the SDFITS header

property sigstate

timeaverage(weights='tsys')

Compute the time-averaged spectrum for this set of scans.

Parameters:

weights: str

‘tsys’ or None. If ‘tsys’ the weight will be calculated as:

\(w = t_{exp} \times \delta\nu/T_{sys}^2\)

Default: ‘tsys’

Returns

——-

spectrumSpectrum

The time-averaged spectrum

total_power(i)

Return the total power spectrum

Parameters:

iint

The index into the data array

Returns:

spectrumSpectrum

tpmeta(i)

property tsys

The system temperature array.

Returns:

tsysndarray

System temperature values in K