lofarantpos package

lofarantpos.db

LOFAR antenna database

Module for manipulating LOFAR antenna databases. Typical usage is to create an instance of a LofarAntennaDatabase:

>>> import lofarantpos, numpy
>>> db = lofarantpos.db.LofarAntennaDatabase()
>>> db.phase_centres['CS001LBA']
array([3826923.942,  460915.117, 5064643.229])
>>> numpy.set_printoptions(suppress=True)
>>> db.antenna_pqr('RS210LBA')[:5]
array([[ 0.        ,  0.        ,  0.        ],
       [-0.00006...,  2.55059...,  0.00185...],
       [ 2.24997...,  1.3499502 ,  0.00130...],
       [ 2.24982..., -1.35031..., -0.0004149 ],
       [ 0.00006..., -2.55059..., -0.00185...]])
>>> db.cabinet_etrs['CS002']
array([3826609.602,  460990.583, 5064879.514])

class lofarantpos.db.Antenna(csv_row): Bases: object

class lofarantpos.db.ContainerLocation(csv_row): Bases: object

class lofarantpos.db.LofarAntennaDatabase(path_to_files=None)

Bases: object

Database with LOFAR antenna positions

This database contains the LOFAR antenna positions in both ETRS and the station/field specific pqr coordinate system. The upstream source is the LOFAR svn repository at https://svn.astron.nl/LOFAR.

antennas

all antenna information

Type:: list

phase_centres

ETRS phase centres for each antenna field

Type:: dict

hba_rotations

HBA rotations (in radians) for each antenna field

Type:: dict

pqr_to_etrs

Rotation matrix from PQR to ETRS for each antenna field

Type:: dict

lora_detector_pqr

PQR coordinates (in the PQR frame of CS002LBA) of LORA detectors

Type:: dict

antenna_etrs(field_name)

Return a list of all ETRS antenna coordinates for a given antenna field

Parameters:: field_name (str) – Field name (e.g. ‘CS001HBA0’)
Returns:: array of ETRS coordinates
Return type:: array

antenna_pqr(field_name)

Return a list of all PQR antenna coordinates for a given antenna field

Parameters:: field_name (str) – Field name (e.g. ‘CS001HBA0’)
Returns:: array of PQR coordinates
Return type:: array

hba_dipole_etrs(field_name)

Return a list of all ETRS dipole coordinates for a given HBA antenna field

Parameters:: field_name (str) – Field name (e.g. ‘CS001HBA0’)
Returns:: array of ETRS coordinates
Return type:: array

Example

>>> import lofarantpos.db
>>> import numpy
>>> db = lofarantpos.db.LofarAntennaDatabase()
>>> db.hba_dipole_etrs("IE613HBA")[:5]
array([[3801679.57332033, -528959.80788382, 5076969.80405122],
       [3801680.56726901, -528959.55814198, 5076969.08837304],
       [3801681.56121763, -528959.30839824, 5076968.37269509],
       [3801682.55516625, -528959.0586545 , 5076967.65701715],
       [3801679.7113895 , -528961.02799576, 5076969.57003303]])

hba_dipole_pqr(field_name)

Return a list of all PQR dipole coordinates for a given HBA antenna field

Parameters:: field_name (str) – Field name (e.g. “CS001HBA0”)
Returns:: array of PQR coordinates
Return type:: array

Example

>>> import lofarantpos.db
>>> import numpy
>>> db = lofarantpos.db.LofarAntennaDatabase()
>>> db.hba_dipole_pqr("CS001HBA0")[:5]
array([[ 1.9336444 , 15.284...  ,  0.00008769],
       [ 3.075576  , 14.776116  ,  0.00008769],
       [ 4.217508  , 14.267695  ,  0.00008769],
       [ 5.3594... , 13.7592745 ,  0.00008769],
       [ 1.4252236 , 14.142605  ,  0.00008769]], dtype=float32)

pqr_to_localnorth(field_name)

Compute a rotation matrix from local coordinates (pointing North) to PQR

Parameters:: field_name (str) – Field name (e.g. ‘IE613LBA’)

Example

>>> import lofarantpos.db
>>> db = lofarantpos.db.LofarAntennaDatabase()
>>> db.pqr_to_localnorth("IE613LBA")
array([[ 0.97847792, -0.20633485, -0.00262657],
       [ 0.20632893,  0.97847984, -0.00235784],
       [ 0.00305655,  0.00176516,  0.99999377]])

rotation_from_north(field_name)

Compute the angle in radians between the positive Q-axis (projected onto a local tangent to the WGS84 ellipsoid) and the local north. Positive means Q is East of North.

Parameters:: field_name (str) – Field name (e.g. ‘IE613LBA’)
Returns:: angle (in radians)
Return type:: float

Example

>>> import lofarantpos.db
>>> import numpy
>>> db = lofarantpos.db.LofarAntennaDatabase()
>>> numpy.rad2deg(db.rotation_from_north("IE613LBA"))
-11.907669843448476

class lofarantpos.db.LoraDetector(csv_row): Bases: object

class lofarantpos.db.PhaseCentre(csv_row): Bases: object

class lofarantpos.db.RotationMatrix(csv_row): Bases: object

lofarantpos.db.getcol(rows, col_name)

lofarantpos.db.install_prefix()

lofarantpos.db.parse_csv(file_name, data_type)

Read a CSV file and convert the elements to a given data type

Parameters:

file_name (str) – name of file to be read
data_type (type) – type to convert each line of the CSV to (e.g. PhaseCentre)

Returns:

List of objects of the given type

Return type:

list

lofarantpos.db.parse_hba_rotations(file_name)

lofarantpos.geo

Functions for geographic transformations commonly used for LOFAR

lofarantpos.geo.geographic_array_from_xyz(xyz_m)

xyz_m is a (N,3) array. Compute lon, lat, and height Output an (N, 3) array with latitude (rad), longitude (rad) and height (m)

Examples

>>> xyz_m = [3836811, 430299, 5059823]
>>> geographic_array_from_xyz([xyz_m, xyz_m])
array([[ 0.11168349,  0.92223593, -0.28265955],
       [ 0.11168349,  0.92223593, -0.28265955]])

>>> geographic_array_from_xyz([[xyz_m, xyz_m]]).shape
(1, 2, 3)

lofarantpos.geo.geographic_from_xyz(xyz_m)

Compute longitude, latitude and height (from the WGS84 ellipsoid) of a given point or list: of points

Parameters:

xyz_m (Union[array, list]) – xyz-coordinates (in m) of the given point.

Returns:

Dictionary with ‘lon_rad’, ‘lat_rad’, ‘height_m’,: values are float for a single input, arrays for multiple inputs

Return type:

Dict[Union[array, float]

Examples

>>> from pprint import pprint
>>> xyz_m = [3836811, 430299, 5059823]
>>> pprint(geographic_from_xyz(xyz_m))
{'height_m': -0.28265954554080963,
...'lat_rad': 0.9222359279580563,
...'lon_rad': 0.11168348969295486}

>>> xyz2_m = array([3828615, 438754, 5065265])
>>> pprint(geographic_from_xyz([xyz_m, xyz2_m]))
{'height_m': array([-0.28265955, -0.74483879]),
...'lat_rad': array([0.92223593, 0.92365033]),
...'lon_rad': array([0.11168349, 0.11410087])}

>>> geographic_from_xyz([[xyz_m, xyz2_m]])['lon_rad'].shape
(1, 2)

lofarantpos.geo.localnorth_to_etrs(centerxyz_m)

Compute a matrix that transforms from a local coordinate system tangent to the WGS84 ellipsoid to ETRS89 ECEF XYZ coordinates.

Parameters:: centerxyz_m (array) – xyz-coordinates of the center of the local coordinate system
Returns:: 3x3 rotation matrix
Return type:: array

Example

>>> set_printoptions(suppress=True)
>>> station1_etrs = [3801633.868, -529022.268, 5076996.892]
>>> station2_etrs = [3826577.462,  461022.624, 5064892.526]
>>> localnorth_to_etrs(array(station1_etrs))
array([[ 0.13782846, -0.79200355,  0.59475516],
       [ 0.99045611,  0.11021248, -0.08276408],
       [ 0.        ,  0.60048613,  0.79963517]])
>>> localnorth_to_etrs([[station1_etrs, station2_etrs]]).shape
(1, 2, 3, 3)

lofarantpos.geo.normal_vector_ellipsoid(lon_rad, lat_rad)

Make a vector normal to the ellipsoid at given longitude and latitude

Examples

>>> normal_vector_ellipsoid(0.12, 0.92)
array([0.60146348, 0.07252407, 0.79560162])
>>> normal_vector_ellipsoid([[0.12, 0.13]], [[0.92, 0.93]]).shape
(1, 2, 3)

lofarantpos.geo.normal_vector_meridian_plane(xyz_m)

Return a unit vector normal to the meridian plane. If a vector of xyz’s is given, xyz should be the fastest varying axis.

Example

>>> test_coord = [3802111.6, -528822.8, 5076662.2]
>>> normal_vector_meridian_plane(test_coord)
array([-0.1377605 , -0.99046557,  0.        ])

>>> normal_vector_meridian_plane(array(test_coord))
array([-0.1377605 , -0.99046557,  0.        ])

>>> normal_vector_meridian_plane(array([test_coord, test_coord]))
array([[-0.1377605 , -0.99046557,  0.        ],
       [-0.1377605 , -0.99046557,  0.        ]])

lofarantpos.geo.normalized_earth_radius(latitude_rad): Compute the normalized radius of the WGS84 ellipsoid at a given latitude

lofarantpos.geo.projection_matrix(xyz0_m, normal_vector)

Create a projection matrix that will project a vector to the plane orthogonal to normal_vector, with local north defined at xyz0_m. The xyz should be the fastest varying axis.

Example

>>> test_coord = [3802111.6, -528822.8, 5076662.2]
>>> cs002_normal = [0.59866826, 0.07212702, 0.79774307]
>>> projection_matrix(test_coord, cs002_normal)
array([[ 0.04616828, -0.79966543,  0.59866826],
       [ 0.99117465,  0.11122275,  0.07212702],
       [-0.12426302,  0.59005482,  0.79774307]])
>>> projection_matrix([[test_coord, test_coord]],
...                   [[cs002_normal, cs002_normal]]).shape
(1, 2, 3, 3)

lofarantpos.geo.transform(xyz_m, xyz0_m, mat)

Perform a coordinate transformation on an array of points

Parameters:

xyz_m (array) – Array of points
xyz0_m (array) – Origin of transformation
mat (array) – Transformation matrix

Returns:

Array of transformed points

Return type:

array

lofarantpos.geo.xyz_from_geographic(lon_rad, lat_rad, height_m)

Compute cartesian xyz coordinates from a longitude, latitude and height (from the WGS84 ellipsoid)

Parameters:

lon_rad (Union[float, array]) – longitude in radians
lat_rad (Union[float, array]) – latitude in radians
height_m (Union[float, array]) – height in meters

Returns:

xyz coordinates in meters

Return type:

array

Examples

>>> xyz_from_geographic(-0.1382, 0.9266, 99.115)
array([3802111.62491437, -528822.82583168, 5076662.15079859])
>>> coords = array([[-0.1382, 0.9266,  99.115],                            [ 0.2979, 0.9123, 114.708]])
>>> xyz_from_geographic(coords[:,0], coords[:,1], coords[:,2]).T
array([[3802111.62491437, -528822.82583168, 5076662.15079859],
       [3738960.12012956, 1147998.32536741, 5021398.44437063]])

lofarantpos.plotutil

Functions for plotting LOFAR stations with matplotlib

lofarantpos.plotutil.add_background(ax, centre, background, zoom=18)

Add openstreetmap background to axes. Assumes the axes extents are given in metres w.r.t. a local coordinates system with origin centre (given in ETRS XYZ)

Parameters:

ax – existing matplotlib Axes object
centre – ETRS XYZ coordinates of the centre
background – name of background to draw, e.g. “openstreetmap” or “luchtfoto” (Dutch stations only)
zoom – zoom level for the background tiles

Example

>>> from lofarantpos.plotutil import plot_station, add_background
>>> from lofarantpos.db import LofarAntennaDatabase
>>> db = LofarAntennaDatabase()
>>> centre = db.phase_centres["CS002LBA"]
>>> fig, ax = plt.subplots()
>>> plot_station("CS002", ax=ax)
>>> plot_station("CS001", ax=ax, centre=centre)
>>> add_background(ax, centre, 'osm')

lofarantpos.plotutil.plot_core(ax=None, labels=False, circle=True, centre=None, tilestyle='lines', background=None)

Plot the LOFAR core

Parameters:

ax – existing matplotlib axes object to use
labels – add labels for each dipole
circle – plot a circle around the superterp
centre – ETRS xyz coordinates of centre (default is centre of the superterp)
tilestyle – style for HBA tiles (“lines”, “filled”, or None)
background – name of background to draw, e.g. “openstreetmap” or “luchtfoto”

Example

>>> from lofarantpos.plotutil import plot_core
>>> plot_core()

lofarantpos.plotutil.plot_hba(station_name, ax=None, centre=None, subfield='', labels=False, tilestyle='lines', **kwargs)

Plot LOFAR HBA tiles for one station. If keyword-arguments are given, they are passed to a scatter plot with the tile centers.

Parameters:

station_name – Station name, without suffix. E.g. “CS001”
ax – existing matplotlib axes object to use
centre – etrs coordinates of origin. Default: HBA phase centre of station.
subfield – ‘0’, ‘1’ or ‘’to suffix after ‘HBA’ for e.g. CS002HBA1)
labels – add labels

Example

>>> from lofarantpos.plotutil import plot_hba
>>> plot_hba("CS001")
>>> plot_hba("CS001", c=list(range(48)))

lofarantpos.plotutil.plot_lba(station_name, ax=None, centre=None, labels=False, **kwargs)

Plot LOFAR LBA locations for one station

Parameters:

station_name – Station name, without suffix. E.g. “CS001”
ax – existing matplotlib axes object to use
centre – etrs coordinates of origin. Default: LBA phase centre of station.
labels – add labels
kwargs – all other keyword-arguments are passed to matplotlib.scatter

Example

>>> from lofarantpos.plotutil import plot_lba
>>> plot_lba("IE613", labels=True)
>>> plot_lba("CS001", c=list(range(96)))

lofarantpos.plotutil.plot_station(station_name, ax=None, centre=None, labels=False, tilestyle='lines', background=None, **kwargs)

Plot a LOFAR station

Parameters:

station_name – Station name, without suffix. E.g. “CS001”
ax – existing matplotlib axes object to use
labels – add labels
centre – centre of projection, as ETRS xyz coordinate. Default is station’s LBA phase centre.
tilestyle – style for HBA tiles (“filled”, “lines” or None)
background – name of background to draw, e.g. “openstreetmap” or “luchtfoto” (Dutch stations only)

Example

>>> from lofarantpos.plotutil import plot_station
>>> plot_station("CS002")
>>> plot_station("CS011", background="openstreetmap", c=list(range(96 + 48)))
>>> plot_station("RS210", background="luchtfoto")

lofarantpos.plotutil.plot_superterp(ax=None, labels=False, circle=True, centre=None, tilestyle='lines', background=None)

Plot the LOFAR superterp

Parameters:

ax – existing matplotlib axes object to use
labels – add labels
circle – plot a surrounding circle
centre – ETRS xyz coordinates of centre (default is the centre of the superterp)
tilestyle – style for HBA tiles (“lines”, “filled” or None)
background – name of background to draw, e.g. “openstreetmap” or “luchtfoto” (Dutch stations only)

Example

>>> from lofarantpos.plotutil import plot_superterp
>>> plot_superterp(background='openstreetmap', tilestyle=None)