Development¶
[3]:
import os
try:
import sirius
print('SiRIUS version',sirius.__version__,'already installed.')
except ImportError as e:
print(e)
print('Installing SiRIUS')
os.system("pip install sirius")
import sirius
print('SiRIUS version',sirius.__version__,' installed.')
SiRIUS version 0.0.19 already installed.
[4]:
import pkg_resources
import xarray as xr
import numpy as np
from astropy.coordinates import SkyCoord
xr.set_options(display_style="html")
import os
try:
from google.colab import output
output.enable_custom_widget_manager()
IN_COLAB = True
except:
IN_COLAB = False
%matplotlib widget
Organization¶
Architecture¶
Data Structures¶
tel.zarr¶
[7]:
########## Telescope layout ##########
tel_dir = pkg_resources.resource_filename('sirius_data', 'telescope_layout/data/vla.d.tel.zarr')
tel_xds = xr.open_zarr(tel_dir,consolidated=False)
tel_xds
[7]:
<xarray.Dataset> Dimensions: (ant_name: 27, pos_coord: 3) Coordinates: * ant_name (ant_name) <U3 'W01' 'W02' 'W03' 'W04' ... 'N07' 'N08' 'N09' * pos_coord (pos_coord) int64 0 1 2 Data variables: ANT_POS (ant_name, pos_coord) float64 dask.array<chunksize=(27, 3), meta=np.ndarray> DISH_DIAMETER (ant_name) float64 dask.array<chunksize=(27,), meta=np.ndarray> Attributes: site_pos: [{'m0': {'unit': 'm', 'value': -1601185.3650000016}, 'm1... telescope_name: VLA
xarray.Dataset
- ant_name: 27
- pos_coord: 3
- ant_name(ant_name)<U3'W01' 'W02' 'W03' ... 'N08' 'N09'
array(['W01', 'W02', 'W03', 'W04', 'W05', 'W06', 'W07', 'W08', 'W09', 'E01', 'E02', 'E03', 'E04', 'E05', 'E06', 'E07', 'E08', 'E09', 'N01', 'N02', 'N03', 'N04', 'N05', 'N06', 'N07', 'N08', 'N09'], dtype='<U3')
- pos_coord(pos_coord)int640 1 2
array([0, 1, 2])
- ANT_POS(ant_name, pos_coord)float64dask.array<chunksize=(27, 3), meta=np.ndarray>
Array Chunk Bytes 648 B 648 B Shape (27, 3) (27, 3) Count 2 Tasks 1 Chunks Type float64 numpy.ndarray - DISH_DIAMETER(ant_name)float64dask.array<chunksize=(27,), meta=np.ndarray>
Array Chunk Bytes 216 B 216 B Shape (27,) (27,) Count 2 Tasks 1 Chunks Type float64 numpy.ndarray
- site_pos :
- [{'m0': {'unit': 'm', 'value': -1601185.3650000016}, 'm1': {'unit': 'm', 'value': -5041977.546999999}, 'm2': {'unit': 'm', 'value': 3554875.8700000006}, 'refer': 'ITRF', 'type': 'position'}]
- telescope_name :
- VLA
zpc.zarr¶
[8]:
########## Zernike Polynomial Dish Aperture Models ##########
zpc_dir = pkg_resources.resource_filename('sirius_data', 'zernike_dish_models/data/EVLA_avg_zcoeffs_SBand_lookup.zpc.zarr')
zpc_xds = xr.open_zarr(zpc_dir,consolidated=False)
zpc_xds
[8]:
<xarray.Dataset> Dimensions: (pol: 4, chan: 16, coef_indx: 66) Coordinates: * chan (chan) float64 2.052e+09 2.18e+09 ... 3.844e+09 3.972e+09 * coef_indx (coef_indx) int64 0 1 2 3 4 5 6 7 8 ... 58 59 60 61 62 63 64 65 * pol (pol) int64 5 6 7 8 Data variables: ETA (pol, chan, coef_indx) float64 dask.array<chunksize=(4, 16, 66), meta=np.ndarray> ZC (pol, chan, coef_indx) complex128 dask.array<chunksize=(4, 16, 66), meta=np.ndarray> Attributes: conversion_date: 2022-01-03 dish_diam: 25 max_rad_1GHz: 0.014946999714079439 telescope_name: EVLA zpc_file_name: EVLA_avg_zcoeffs_SBand_lookup.csv
xarray.Dataset
- pol: 4
- chan: 16
- coef_indx: 66
- chan(chan)float642.052e+09 2.18e+09 ... 3.972e+09
array([2.052e+09, 2.180e+09, 2.308e+09, 2.436e+09, 2.564e+09, 2.692e+09, 2.820e+09, 2.948e+09, 3.076e+09, 3.204e+09, 3.332e+09, 3.460e+09, 3.588e+09, 3.716e+09, 3.844e+09, 3.972e+09])
- coef_indx(coef_indx)int640 1 2 3 4 5 6 ... 60 61 62 63 64 65
array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65])
- pol(pol)int645 6 7 8
array([5, 6, 7, 8])
- ETA(pol, chan, coef_indx)float64dask.array<chunksize=(4, 16, 66), meta=np.ndarray>
Array Chunk Bytes 33.00 kiB 33.00 kiB Shape (4, 16, 66) (4, 16, 66) Count 2 Tasks 1 Chunks Type float64 numpy.ndarray - ZC(pol, chan, coef_indx)complex128dask.array<chunksize=(4, 16, 66), meta=np.ndarray>
Array Chunk Bytes 66.00 kiB 66.00 kiB Shape (4, 16, 66) (4, 16, 66) Count 2 Tasks 1 Chunks Type complex128 numpy.ndarray
- conversion_date :
- 2022-01-03
- dish_diam :
- 25
- max_rad_1GHz :
- 0.014946999714079439
- telescope_name :
- EVLA
- zpc_file_name :
- EVLA_avg_zcoeffs_SBand_lookup.csv