pycrtools.core.hftools.mImaging¶

pycrtools.core.hftools.mImaging.hCoordinateConvert()¶

hCoordinateConvert(source, sourceCoordinate, target, targetCoordinate, anglesInDegrees)

Converts a 3D spatial vector into a different Coordinate type (e.g. Spherical to Cartesian).

Parameters

source Coordinates of the source to be converted - vector of length 3

sourceCoordinate Type of the coordinates for the source

target Coordinates of the source to be converted - vector of length 3

targetCoordinate Type of the coordinates for the target (output vector)

anglesInDegrees True if the angles are in degree, otherwise in radians

Description

Available Coordinate Types are:

AzElHeight Azimuth-Elevation-Height $\vec x = (Az,El,H)$

AzElRadius Azimuth-Elevation-Radius $\vec x = (Az,El,R)$

Cartesian Cartesian coordinates $\vec x = (x,y,z)$

Cylindrical Cylindrical coordinates $\vec x = (r,\phi,h)$

Direction Direction on the sky $\vec x = (Lon,Lat)$

DirectionRadius Direction on the sky with radial distance $\vec x = (Lon,Lat,R)$

Frquency Frequency

LongLatRadius Longitude-Latitude-Radius

NorthEastHeight North-East-Height

Spherical Spherical coordinates $\vec x = (r,\phi,\theta)$

Time Time

Precede the Coordinate Types by CoordinateTypes., i.e., CoordinateTypes.AzElRadius.

Example

hCoordinateConvert(meandirection,CoordinateTypes.AzElRadius,azelr,CoordinateTypes.Cartesian,False)

pycrtools.core.hftools.mImaging.hCImageFromCCM()¶

hCImageFromCCM(image, ccm, weights, nofAntennas, nfreq)

Calculates a single complex pixel or a pixel vector (i.e., an image), from an cross correlation matrix and complex geometrical weights for each antenna by multiplying ccm and weights and summing over all baselines.

Parameters

image Image vector containing N_freq frequency bins in the order [power(pix0,bin0), power(pix0,bin1), ..., power(pix1,bin0), ...]. Size of vector is N_pixel * N_bins

ccm Upper half of the cross-correlation matrix (input) containing complex visibilities as a function of frequency. The ordering is ant0 * ant1, ant0 * ant2, ..., ant1 * ant2, ... - where each antN contains nfreq frequency bins.

weights Vector containing the weights to be applied for each pixel, antenna, and frequency bin (in that order, i.e. frequency index runs fastest).

nofAntennas Number of antennas used for weights and ccm

nfreq Number of frequency bins used for weights and ccm

Description

The image contains the power as a function of pixel and frequency bins. Each value is the sum over all baselines of the norm of the complex visibilities times complex weights for that pixel and frequency bin.

The results will be added to the image, hence for a new image the image must be initialized to 0! Otherwise an old image can be provided and the new data will simply be added to it.

The length of the ccm vector is (N-1)/2*N_freq, where N is the number of antennas and N_freq the number of frequency bins per antenna. The length of the weights vector is N_pixel*N_ant*N_freq.

Usage

hCrossCorrelationMatrix(ccm,fftdata,nfreq) -> ccm = ccm(old) + ccm(fftdata)

Example

>>> ccm=Vector(complex,file['nofSelectedAntennas']*(file['nofSelectedAntennas']-1)/2*file['fftLength'])
>>> cimage=Vector(complex,n_pixels*nbins,fill=0)
>>> image=hArray(float,[n_pixels,file['fftLength']])

>>> hCrossCorrelationMatrix(ccm,file_fft.vec(),file['fftLength'])
>>> hCImageFromCCM(cimage,ccm,weights.vec(),file['nofSelectedAntennas'],file['fftLength'])
>>> cimage.norm(image.vec())
>>> intimage=np.array(image[...].sum()) # convert to numpy array
>>> immax=intimage.max()
>>> intimage /= immax
>>> intimage.resize([n_az,n_el])

>>> plt.imshow(intimage,cmap=plt.cm.hot)

pycrtools.core.hftools.mImaging.hDelayToPhase()¶

hDelayToPhase(vec, frequencies, delays)

Coverts a vector of time delays and a vector of frequencies to a corresponding vector of phases (of a complex number).

Parameters

vec Output vector returning real phases of complex numbers

frequencies Input vector with real delays in units of time [second]

delays Input vector with real delays in units of time [second]

Description

The frequencies always run fastest in the output vector. If input vectors are shorter they will be wrapped until the output vector is full.

Usage

hDelayToPhase(vec,frequencies,delays) -> vec = [phase(frequencies_0,delays_0),phase(frequencies_1,delays_0),...,phase(frequencies_n,delays_0),phase(frequencies_1,delays_1),...]

pycrtools.core.hftools.mImaging.hDelayToWeight()¶

hDelayToWeight(vec, frequencies, delays)

Coverts a vector of time delays and a vector of frequencies to a corresponding vector of weights.

Parameters

vec Output vector returning real phases of complex numbers

frequencies Input vector with real delays in units of time [second]

delays Input vector with real delays in units of time [second]

Description

The frequencies always run fastest in the output vector. If input vectors are shorter they will be wrapped until the output vector is full.

Usage

hDelayToWeight(vec,frequencies,delays) -> vec = [phase(frequencies_0,delays_0),phase(frequencies_1,delays_0),...,phase(frequencies_n,delays_0),phase(frequencies_1,delays_1),...]

pycrtools.core.hftools.mImaging.hGeometricDelayFarField()¶

hGeometricDelayFarField(antPosition, skyDirection, length)

Calculates the time delay in seconds for a signal received at an antenna position relative to a phase center from a source located in a certain direction in farfield (based on L. Bahren).

Parameters

antPosition Cartesian antenna positions (Meters) relative to a reference location (phase center) - vector of length 3

skyDirection Vector in Cartesian coordinates pointing towards a sky position from the antenna - vector of length 3

length Length of the skyDirection vector, used for normalization - provided to speed up calculation

pycrtools.core.hftools.mImaging.hGeometricDelayNearField()¶

hGeometricDelayNearField(antPosition, skyPosition, distance)

Calculates the time delay in seconds for a signal received at an antenna position relative to a phase center from a source located at a certain 3D space coordinate in nearfield (based on L. Bahren).

Parameters

antPosition Cartesian antenna positions [meter]) relative to a reference location (phase center) - vector of length 3

skyPosition Vector in Cartesian coordinates [meter] pointing towards a sky location, relative to phase center - vector of length 3

distance Distance of source, i.e. the length of skyPosition - provided to speed up calculation

pycrtools.core.hftools.mImaging.hGeometricDelays()¶

hGeometricDelays(delays, antPositions, skyPositions, farfield)

Calculates the time delay in seconds for signals received at various antenna positions relative to a phase center from sources located at certain 3D space coordinates in near or far field.

Parameters

delays Output vector containing the delays in seconds for all antennas and positions [antenna index runs fastest: (ant1, pos1), (ant2,pos1), ...] - length of vector has to be number of antennas times positions

antPositions Cartesian antenna positions [meter] relative to a reference location (phase center) - vector of length number of antennas times three

skyPositions Vector in Cartesian coordinates [meter] pointing towards a sky location, relative to phase center - vector of length number of skypositions times three

farfield Calculate in farfield approximation if true, otherwise do near field calculation

Example

>>> result=[]
>>> plt.clf()
>>> for j in range(29,30):
>>>     x=[]
>>>     y=[]
>>>     for i in range(177,178):
>>>         azel[0]=float(i)
>>>         azel[1]=float(j)
>>>         hCoordinateConvert(azel,CoordinateTypes.AzElRadius,cartesian,CoordinateTypes.Cartesian,True)
>>>         hGeometricDelays(delays,antenna_positions,hArray(cartesian),True)
>>>         delays *= 10^6
>>>         deviations=delays-obsdelays
>>>         deviations.abs()
>>>         sum=deviations.vec().sum()
>>>         x.append(i)
>>>         y.append(sum)
>>>     result.append(y)
>>>     plt.plot(x,y)

pycrtools.core.hftools.mImaging.hGeometricPhases()¶

hGeometricPhases(phases, frequencies, antPositions, skyPositions, farfield)

Calculates the phase gradients for signals received at various antenna positions relative to a phase center from sources located at certain 3D space coordinates in near or far field and for different frequencies.

Parameters

phases Output vector containing the phases in radians for all frequencies, antennas and positions [frequency index, runs fastest, then antenna index: (nu1, ant1, pos1), (nu2, ant1, pos1), ...] - length of vector has to be number of antennas times positions time frequency bins

frequencies Vector of frequencies [Hz] to calculate phases for

antPositions Cartesian antenna positions [meter] relative to a reference location (phase center) - vector of length number of antennas times three

skyPositions Vector in Cartesian coordinates [meter] pointing towards a sky location, relative to phase center - vector of length number of skypositions times three

farfield Calculate in farfield approximation if true, otherwise do near field calculation

pycrtools.core.hftools.mImaging.hGeometricWeights()¶

hGeometricWeights(weights, frequencies, antPositions, skyPositions, farfield)

Calculates the phase gradients as complex weights for signals received at various antenna positions relative to a phase center from sources located at certain 3D space coordinates in near or far field and for different frequencies.

Parameters

weights Output vector containing the phases in radians for all frequencies, antennas and positions [frequency index, runs fastest, then antenna index: (nu1, ant1, pos1), (nu2, ant1, pos1), ...] - length of vector has to be number of antennas times positions time frequency bins

frequencies Vector of frequencies [Hz] to calculate phases for

antPositions Cartesian antenna positions [meter] relative to a reference location (phase center) - vector of length number of antennas times three

skyPositions Vector in Cartesian coordinates [meter] pointing towards a sky location, relative to phase center - vector of length number of skypositions times three

farfield Calculate in farfield approximation if true, otherwise do near field calculation

pycrtools.core.hftools.mImaging.hWorld2Pixel()¶

hWorld2Pixel(pixel, world, refcode, projection, refLong, refLat, incLon, incLat, refX, refY)

Get pixel coordinates for given vector of world coordinates

Parameters

pixel Pixel coordinates

world World coordinates

refcode reference code for coordinate system e.g. AZEL,``J2000``, ...

projection the projection used e.g. SIN`, ``STG, ...

refLong reference value for longtitude (CRVAL)

refLat reference value for latitude (CRVAL)

incLon incLon increment value for longtitude (CDELT)

incLat incLon increment value for latitude (CDELT)

refX refX reference $x$ -pixel (CRPIX)

refY refY reference $y$ -pixel (CRPIX)

pycrtools.core.hftools.mImaging.hPixel2World()¶

hPixel2World(world, pixel, refcode, projection, refLong, refLat, incLon, incLat, refX, refY, lonPole, latPole)

Get world coordinates for given vector of pixel coordinates.

Parameters

world World coordinates

pixel Pixel coordinates

refcode reference code for coordinate system e.g. AZEL, J2000, ...

projection the projection used e.g. SIN, STG, ...

refLong reference value for longtitude (CRVAL)

refLat reference value for latitude (CRVAL)

incLon incLon increment value for longtitude (CDELT)

incLat incLon increment value for latitude (CDELT)

refX refX reference $x$ - pixel (CRPIX)

refY refY reference $y$ -pixel (CRPIX)

lonPole (LONPOLE)

latPole (LATPOLE)

pycrtools.core.hftools.mImaging.hEquatorial2Horizontal()¶

hEquatorial2Horizontal(hc, ec, utc, ut1_utc, L, phi)

Convert array of equatorial J2000 coordinates to horizontal, AZEL coordinates.

Parameters

hc array with horizontal coordiates [radians] (alt, az, alt, az, ...) altitude positive eastwards from north.

ec array with equatorial coordinates [radians] (ra, dec, ra, dec, ...).

utc UTC as Julian Day.

ut1_utc difference UT1-UTC (as obtained from IERS bulletin A) if 0 a maximum error of 0.9 seconds is made.

L longitude of telescope [radians]. L is observer’s longitude (positive east, negative west of Greenwhich).

phi latitude of telescope [radians].

pycrtools.core.hftools.mImaging.hBeamformImage()¶

hBeamformImage(image, fftdata, frequencies, antpos, skypos)

Beamform image

Parameters

image Array to store resulting image. Stored as [I(x_0, y_0, f_0), I(x_0, y_0, f_1), ... I(x_nx, y_ny, f_nf)] e.g. the rightmost (frequency) index runs fastest. This array may contain an existing image.

fftdata Array with FFT data of each antenna. Expects data to be stored as [f(0,0), f(0,1), ..., f(0,nf), f(1,0), f(1,1), ..., f(1,nf), ..., f(na, 0), f(na,1), ..., f(na,nf)] e.g. f(i,j) where i is the antenna number and j is the frequency.

frequencies Array with frequencies [Hz] stored as [f_0, f_1, ..., f_n].

antpos Array with antenna positions in the local Cartesian frame [meter]. Stored as [x_0, y_0, z_0, x_1, y_1, z_1, ... x_na, y_na, z_na] where na is the number of antennas.

skypos Array with sky positions in the local cartesian frame [Hz]. Stored as [x_0, y_0, z_0, x_1, y_1, z_1, ... x_np, y_np, z_np] where np is the number of pixels in the image. Storage order for the pixels is the same as for the image e.g. runs faster in y.

hBeamformImage(image, fftdata, frequencies, delays)

Beamform image

Parameters

image Array to store resulting image. Stored as [I(x_0, y_0, f_0), I(x_0, y_0, f_1), ... I(x_nx, y_ny, f_nf)], e.g. the rightmost (frequency) index runs fastest. This array may contain an existing image.

fftdata Array with FFT data of each antenna. Expects data to be stored as [f(0,0), f(0,1), ..., f(0,nf), f(1,0), f(1,1), ..., f(1,nf), ..., f(na, 0), f(na,1), ..., f(na,nf)] e.g. f(i,j) where i is the antenna number and j is the frequency.

frequencies Array with frequencies [Hz] stored as [f_0, f_1, ..., f_n].

delays Array containing the delays [s] for all antennas and positions (antenna index runs fastest: (ant1, pos1), (ant2, pos1), ...) - length of vector has to be number of antennas times positions as calculated by hGeometricDelays().

hBeamformImage(image, fftdata, frequencies, antpos, skypos, step)

Beamform image

Parameters

image Array to store resulting image. Stored as [I(x_0, y_0, f_0), I(x_0, y_0, f_1), ... I(x_nx, y_ny, f_nf)] e.g. the rightmost (frequency) index runs fastest. This array may contain an existing image.

fftdata Array with FFT data of each antenna. Expects data to be stored as [f(0,0), f(0,1), ..., f(0,nf), f(1,0), f(1,1), ..., f(1,nf), ..., f(na, 0), f(na,1), ..., f(na,nf)] e.g. f(i,j) where i is the antenna number and j is the frequency.

frequencies Array with frequencies [Hz] stored as [f_0, f_1, ..., f_n].

antpos Array with antenna positions in the local Cartesian frame [meter]. Stored as [x_0, y_0, z_0, x_1, y_1, z_1, ... x_na, y_na, z_na] where na is the number of antennas.

skypos Array with sky positions in the local cartesian frame [Hz]. Stored as [x_0, y_0, z_0, x_1, y_1, z_1, ... x_np, y_np, z_np] where np is the number of pixels in the image. Storage order for the pixels is the same as for the image e.g. runs faster in y.

step Array with steps to take for stepping though the frequency channels (used to efficiently skip bad channels).

pycrtools.core.hftools.mImaging.hBeamformImage()

hBeamformImage(image, fftdata, frequencies, antpos, skypos)

Beamform image

Parameters

image Array to store resulting image. Stored as [I(x_0, y_0, f_0), I(x_0, y_0, f_1), ... I(x_nx, y_ny, f_nf)] e.g. the rightmost (frequency) index runs fastest. This array may contain an existing image.

fftdata Array with FFT data of each antenna. Expects data to be stored as [f(0,0), f(0,1), ..., f(0,nf), f(1,0), f(1,1), ..., f(1,nf), ..., f(na, 0), f(na,1), ..., f(na,nf)] e.g. f(i,j) where i is the antenna number and j is the frequency.

frequencies Array with frequencies [Hz] stored as [f_0, f_1, ..., f_n].

antpos Array with antenna positions in the local Cartesian frame [meter]. Stored as [x_0, y_0, z_0, x_1, y_1, z_1, ... x_na, y_na, z_na] where na is the number of antennas.

skypos Array with sky positions in the local cartesian frame [Hz]. Stored as [x_0, y_0, z_0, x_1, y_1, z_1, ... x_np, y_np, z_np] where np is the number of pixels in the image. Storage order for the pixels is the same as for the image e.g. runs faster in y.

hBeamformImage(image, fftdata, frequencies, delays)

Beamform image

Parameters

image Array to store resulting image. Stored as [I(x_0, y_0, f_0), I(x_0, y_0, f_1), ... I(x_nx, y_ny, f_nf)], e.g. the rightmost (frequency) index runs fastest. This array may contain an existing image.

fftdata Array with FFT data of each antenna. Expects data to be stored as [f(0,0), f(0,1), ..., f(0,nf), f(1,0), f(1,1), ..., f(1,nf), ..., f(na, 0), f(na,1), ..., f(na,nf)] e.g. f(i,j) where i is the antenna number and j is the frequency.

frequencies Array with frequencies [Hz] stored as [f_0, f_1, ..., f_n].

delays Array containing the delays [s] for all antennas and positions (antenna index runs fastest: (ant1, pos1), (ant2, pos1), ...) - length of vector has to be number of antennas times positions as calculated by hGeometricDelays().

hBeamformImage(image, fftdata, frequencies, antpos, skypos, step)

Beamform image

Parameters

image Array to store resulting image. Stored as [I(x_0, y_0, f_0), I(x_0, y_0, f_1), ... I(x_nx, y_ny, f_nf)] e.g. the rightmost (frequency) index runs fastest. This array may contain an existing image.

fftdata Array with FFT data of each antenna. Expects data to be stored as [f(0,0), f(0,1), ..., f(0,nf), f(1,0), f(1,1), ..., f(1,nf), ..., f(na, 0), f(na,1), ..., f(na,nf)] e.g. f(i,j) where i is the antenna number and j is the frequency.

frequencies Array with frequencies [Hz] stored as [f_0, f_1, ..., f_n].

antpos Array with antenna positions in the local Cartesian frame [meter]. Stored as [x_0, y_0, z_0, x_1, y_1, z_1, ... x_na, y_na, z_na] where na is the number of antennas.

skypos Array with sky positions in the local cartesian frame [Hz]. Stored as [x_0, y_0, z_0, x_1, y_1, z_1, ... x_np, y_np, z_np] where np is the number of pixels in the image. Storage order for the pixels is the same as for the image e.g. runs faster in y.

step Array with steps to take for stepping though the frequency channels (used to efficiently skip bad channels).

pycrtools.core.hftools.mImaging.hBeamformImage()

hBeamformImage(image, fftdata, frequencies, antpos, skypos)

Beamform image

Parameters

image Array to store resulting image. Stored as [I(x_0, y_0, f_0), I(x_0, y_0, f_1), ... I(x_nx, y_ny, f_nf)] e.g. the rightmost (frequency) index runs fastest. This array may contain an existing image.

fftdata Array with FFT data of each antenna. Expects data to be stored as [f(0,0), f(0,1), ..., f(0,nf), f(1,0), f(1,1), ..., f(1,nf), ..., f(na, 0), f(na,1), ..., f(na,nf)] e.g. f(i,j) where i is the antenna number and j is the frequency.

frequencies Array with frequencies [Hz] stored as [f_0, f_1, ..., f_n].

antpos Array with antenna positions in the local Cartesian frame [meter]. Stored as [x_0, y_0, z_0, x_1, y_1, z_1, ... x_na, y_na, z_na] where na is the number of antennas.

skypos Array with sky positions in the local cartesian frame [Hz]. Stored as [x_0, y_0, z_0, x_1, y_1, z_1, ... x_np, y_np, z_np] where np is the number of pixels in the image. Storage order for the pixels is the same as for the image e.g. runs faster in y.

hBeamformImage(image, fftdata, frequencies, delays)

Beamform image

Parameters

image Array to store resulting image. Stored as [I(x_0, y_0, f_0), I(x_0, y_0, f_1), ... I(x_nx, y_ny, f_nf)], e.g. the rightmost (frequency) index runs fastest. This array may contain an existing image.

fftdata Array with FFT data of each antenna. Expects data to be stored as [f(0,0), f(0,1), ..., f(0,nf), f(1,0), f(1,1), ..., f(1,nf), ..., f(na, 0), f(na,1), ..., f(na,nf)] e.g. f(i,j) where i is the antenna number and j is the frequency.

frequencies Array with frequencies [Hz] stored as [f_0, f_1, ..., f_n].

delays Array containing the delays [s] for all antennas and positions (antenna index runs fastest: (ant1, pos1), (ant2, pos1), ...) - length of vector has to be number of antennas times positions as calculated by hGeometricDelays().

hBeamformImage(image, fftdata, frequencies, antpos, skypos, step)

Beamform image

Parameters

image Array to store resulting image. Stored as [I(x_0, y_0, f_0), I(x_0, y_0, f_1), ... I(x_nx, y_ny, f_nf)] e.g. the rightmost (frequency) index runs fastest. This array may contain an existing image.

fftdata Array with FFT data of each antenna. Expects data to be stored as [f(0,0), f(0,1), ..., f(0,nf), f(1,0), f(1,1), ..., f(1,nf), ..., f(na, 0), f(na,1), ..., f(na,nf)] e.g. f(i,j) where i is the antenna number and j is the frequency.

frequencies Array with frequencies [Hz] stored as [f_0, f_1, ..., f_n].

antpos Array with antenna positions in the local Cartesian frame [meter]. Stored as [x_0, y_0, z_0, x_1, y_1, z_1, ... x_na, y_na, z_na] where na is the number of antennas.

skypos Array with sky positions in the local cartesian frame [Hz]. Stored as [x_0, y_0, z_0, x_1, y_1, z_1, ... x_np, y_np, z_np] where np is the number of pixels in the image. Storage order for the pixels is the same as for the image e.g. runs faster in y.

step Array with steps to take for stepping though the frequency channels (used to efficiently skip bad channels).

pycrtools.core.hftools.mImaging.hDedispersionShifts()¶

hDedispersionShifts(shifts, frequencies, reference, dm, dt)

Generate shifts for dedispersion

Parameters

shifts Shifts.

frequencies Frequencies in Hz.

reference Reference frequency in Hz.

dm Dispersion Measure.

dt Time sampling step in seconds.

pycrtools.core.hftools.mImaging.hBeamformBlock()¶

hBeamformBlock(out, fftdata, frequencies, antpos, skypos)

Beamform block

Parameters

out Beamformer output.

fftdata Array with FFT data of each antenna. Expects data to be stored as [f(0,0), f(0,1), ..., f(0,nf), f(1,0), f(1,1), ..., f(1,nf), ..., f(na, 0), f(na,1), ..., f(na,nf)] e.g. f(i,j) where i is the antenna number and j is the frequency.

frequencies Array with frequencies [Hz] stored as [f_0, f_1, ..., f_n].

antpos Array with antenna positions in the local Cartesian frame [meter]. Stored as [x_0, y_0, z_0, x_1, y_1, z_1, ... x_na, y_na, z_na] where na is the number of antennas.

skypos Array with sky position in the local cartesian frame [Hz]. Stored as [x, y, z].

hBeamformBlock(out, fftdata, frequencies, delays)

Beamform block

Parameters

out Beamformer output.

fftdata Array with FFT data of each antenna. Expects data to be stored as [f(0,0), f(0,1), ..., f(0,nf), f(1,0), f(1,1), ..., f(1,nf), ..., f(na, 0), f(na,1), ..., f(na,nf)] e.g. f(i,j) where i is the antenna number and j is the frequency.

frequencies Array with frequencies [Hz] stored as [f_0, f_1, ..., f_n].

delays Array containing the delays [s] for all antennas

pycrtools.core.hftools.mImaging.hBeamformBlock()

hBeamformBlock(out, fftdata, frequencies, antpos, skypos)

Beamform block

Parameters

out Beamformer output.

fftdata Array with FFT data of each antenna. Expects data to be stored as [f(0,0), f(0,1), ..., f(0,nf), f(1,0), f(1,1), ..., f(1,nf), ..., f(na, 0), f(na,1), ..., f(na,nf)] e.g. f(i,j) where i is the antenna number and j is the frequency.

frequencies Array with frequencies [Hz] stored as [f_0, f_1, ..., f_n].

antpos Array with antenna positions in the local Cartesian frame [meter]. Stored as [x_0, y_0, z_0, x_1, y_1, z_1, ... x_na, y_na, z_na] where na is the number of antennas.

skypos Array with sky position in the local cartesian frame [Hz]. Stored as [x, y, z].

hBeamformBlock(out, fftdata, frequencies, delays)

Beamform block

Parameters

out Beamformer output.

fftdata Array with FFT data of each antenna. Expects data to be stored as [f(0,0), f(0,1), ..., f(0,nf), f(1,0), f(1,1), ..., f(1,nf), ..., f(na, 0), f(na,1), ..., f(na,nf)] e.g. f(i,j) where i is the antenna number and j is the frequency.

frequencies Array with frequencies [Hz] stored as [f_0, f_1, ..., f_n].

delays Array containing the delays [s] for all antennas

pycrtools.core.hftools.mImaging.hFrequencyIntegratedImage()¶

hFrequencyIntegratedImage(out, in)

Calculates the square of the absolute value and add it to output vector.

Parameters

out Numpy vector

in Input vector

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pycrtools.core.hftools.mImaging¶

source	Coordinates of the source to be converted - vector of length 3
sourceCoordinate	Type of the coordinates for the source
target	Coordinates of the source to be converted - vector of length 3
targetCoordinate	Type of the coordinates for the target (output vector)
anglesInDegrees	True if the angles are in degree, otherwise in radians

AzElHeight	Azimuth-Elevation-Height	$\vec x = (Az,El,H)$
AzElRadius	Azimuth-Elevation-Radius	$\vec x = (Az,El,R)$
Cartesian	Cartesian coordinates	$\vec x = (x,y,z)$
Cylindrical	Cylindrical coordinates	$\vec x = (r,\phi,h)$
Direction	Direction on the sky	$\vec x = (Lon,Lat)$
DirectionRadius	Direction on the sky with radial distance	$\vec x = (Lon,Lat,R)$
Frquency	Frequency
LongLatRadius	Longitude-Latitude-Radius
NorthEastHeight	North-East-Height
Spherical	Spherical coordinates	$\vec x = (r,\phi,\theta)$
Time	Time

image	Image vector containing `N_freq` frequency bins in the order `[power(pix0,bin0), power(pix0,bin1), ..., power(pix1,bin0), ...]`. Size of vector is `N_pixel * N_bins`
ccm	Upper half of the cross-correlation matrix (input) containing complex visibilities as a function of frequency. The ordering is `ant0 * ant1, ant0 * ant2, ..., ant1 * ant2, ...` - where each `antN` contains `nfreq` frequency bins.
weights	Vector containing the weights to be applied for each pixel, antenna, and frequency bin (in that order, i.e. frequency index runs fastest).
nofAntennas	Number of antennas used for `weights` and `ccm`
nfreq	Number of frequency bins used for `weights` and `ccm`

vec	Output vector returning real phases of complex numbers
frequencies	Input vector with real delays in units of time [second]
delays	Input vector with real delays in units of time [second]

antPosition	Cartesian antenna positions (Meters) relative to a reference location (phase center) - vector of length 3
skyDirection	Vector in Cartesian coordinates pointing towards a sky position from the antenna - vector of length 3
length	Length of the `skyDirection` vector, used for normalization - provided to speed up calculation

antPosition	Cartesian antenna positions [meter]) relative to a reference location (phase center) - vector of length 3
skyPosition	Vector in Cartesian coordinates [meter] pointing towards a sky location, relative to phase center - vector of length 3
distance	Distance of source, i.e. the length of `skyPosition` - provided to speed up calculation

delays	Output vector containing the delays in seconds for all antennas and positions [antenna index runs fastest: `(ant1, pos1), (ant2,pos1), ...`] - length of vector has to be number of antennas times positions
antPositions	Cartesian antenna positions [meter] relative to a reference location (phase center) - vector of length number of antennas times three
skyPositions	Vector in Cartesian coordinates [meter] pointing towards a sky location, relative to phase center - vector of length number of `skypositions` times three
farfield	Calculate in farfield approximation if `true`, otherwise do near field calculation

phases	Output vector containing the phases in radians for all frequencies, antennas and positions [frequency index, runs fastest, then antenna index: `(nu1, ant1, pos1), (nu2, ant1, pos1), ...`] - length of vector has to be number of antennas times positions time frequency bins
frequencies	Vector of frequencies [Hz] to calculate phases for
antPositions	Cartesian antenna positions [meter] relative to a reference location (phase center) - vector of length number of antennas times three
skyPositions	Vector in Cartesian coordinates [meter] pointing towards a sky location, relative to phase center - vector of length number of `skypositions` times three
farfield	Calculate in farfield approximation if `true`, otherwise do near field calculation

pixel	Pixel coordinates
world	World coordinates
refcode	reference code for coordinate system e.g. `AZEL`,``J2000``, ...
projection	the projection used e.g. SIN`, ``STG, ...
refLong	reference value for longtitude (`CRVAL`)
refLat	reference value for latitude (`CRVAL`)
incLon	incLon increment value for longtitude (`CDELT`)
incLat	incLon increment value for latitude (`CDELT`)
refX	refX reference $x$ -pixel (`CRPIX`)
refY	refY reference $y$ -pixel (`CRPIX`)

hc	array with horizontal coordiates [radians] `(alt, az, alt, az, ...)` altitude positive eastwards from north.
ec	array with equatorial coordinates [radians] `(ra, dec, ra, dec, ...)`.
utc	UTC as Julian Day.
ut1_utc	difference UT1-UTC (as obtained from IERS bulletin A) if 0 a maximum error of 0.9 seconds is made.
L	longitude of telescope [radians]. `L` is observer’s longitude (positive east, negative west of Greenwhich).
phi	latitude of telescope [radians].

image	Array to store resulting image. Stored as `[I(x_0, y_0, f_0), I(x_0, y_0, f_1), ... I(x_nx, y_ny, f_nf)]` e.g. the rightmost (frequency) index runs fastest. This array may contain an existing image.
fftdata	Array with FFT data of each antenna. Expects data to be stored as `[f(0,0), f(0,1), ..., f(0,nf), f(1,0), f(1,1), ..., f(1,nf), ..., f(na, 0), f(na,1), ..., f(na,nf)]` e.g. `f(i,j)` where `i` is the antenna number and `j` is the frequency.
frequencies	Array with frequencies [Hz] stored as `[f_0, f_1, ..., f_n]`.
antpos	Array with antenna positions in the local Cartesian frame [meter]. Stored as `[x_0, y_0, z_0, x_1, y_1, z_1, ... x_na, y_na, z_na]` where `na` is the number of antennas.
skypos	Array with sky positions in the local cartesian frame [Hz]. Stored as `[x_0, y_0, z_0, x_1, y_1, z_1, ... x_np, y_np, z_np]` where `np` is the number of pixels in the image. Storage order for the pixels is the same as for the image e.g. runs faster in `y`.

shifts	Shifts.
frequencies	Frequencies in Hz.
reference	Reference frequency in Hz.
dm	Dispersion Measure.
dt	Time sampling step in seconds.

out	Beamformer output.
fftdata	Array with FFT data of each antenna. Expects data to be stored as `[f(0,0), f(0,1), ..., f(0,nf), f(1,0), f(1,1), ..., f(1,nf), ..., f(na, 0), f(na,1), ..., f(na,nf)]` e.g. `f(i,j)` where `i` is the antenna number and `j` is the frequency.
frequencies	Array with frequencies [Hz] stored as `[f_0, f_1, ..., f_n]`.
antpos	Array with antenna positions in the local Cartesian frame [meter]. Stored as `[x_0, y_0, z_0, x_1, y_1, z_1, ... x_na, y_na, z_na]` where `na` is the number of antennas.
skypos	Array with sky position in the local cartesian frame [Hz]. Stored as `[x, y, z]`.

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pycrtools.core.hftools.mImaging¶

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