EVN Observation Planner. Helps you to plan a VLBI observation. Given a date, source coordinates, and a VLBI array, it will tell you when the source can be observed by each antenna, the reached rms noise level and resolution, among other details.
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#! /usr/bin/env python3
# -*- coding: utf-8 -*-
"""EVN Calculator.
Program to compute the source elevation visibility and expected thermal
noise level for a given EVN observation.
__author__ = "Benito Marcote"
__copyright__ = "Copyright 2020, Joint Insitute for VLBI-ERIC (JIVE)"
__credits__ = "Benito Marcote"
__license__ = "GPL"
__date__ = "2020/04/21"
__version__ = "0.0.1"
__maintainer__ = "Benito Marcote"
__email__ = "marcote@jive.eu"
__status__ = "Development" # Prototype, Development, Production.
from os import path
from time import sleep
import itertools
import datetime
import numpy as np
import dash
from dash.dependencies import Input, Output, State
import dash_core_components as dcc
import dash_html_components as html
import dash_bootstrap_components as dbc
import plotly.graph_objs as go
from datetime import datetime as dt
from astropy.time import Time
from astropy import coordinates as coord
from astropy import units as u
# Tweak to not let astroplan crashing...
from astropy.utils.data import clear_download_cache
clear_download_cache() # to be sure it is really working
from astropy.utils import iers
iers.conf.auto_download = False
iers.conf.iers_auto_url = None
from astroplan import FixedTarget
from src import freqsetups as fs
from src import stations
from src import functions as fx
from src import observation
current_directory = path.dirname(path.realpath(__file__))
# stationList = stations.Stations()
# stationList.add_from_file(current_directory+'/station_location.txt')
# iers.IERS.iers_table = iers.IERS.open(cache=True)
# iers.IERS.iers_table = iers.IERS_A.open(iers.IERS_A_URL)
# iers.Conf.iers_auto_url.set('ftp://cddis.gsfc.nasa.gov/pub/products/iers/finals2000A.all')
all_antennas = fx.get_stations_from_file(f"{current_directory}/data/station_location.txt")
sorted_networks = {'EVN': 'EVN: European VLBI Network', 'eMERLIN': 'eMERLIN',
'VLBA': 'VLBA: Very Long Baseline Array',
'LBA': 'LBA: Australian Long Baseline Array',
'KVN': 'Korean VLBI Network',
'Other': 'Other antennas'}
default_arrays = {'EVN': ['Ef', 'Hh', 'Jb2', 'Mc', 'Nt', 'Ur', 'On', 'Sr', 'T6', 'Tr',
'Ys', 'Wb', 'Bd', 'Sv', 'Zc', 'Ir'],
'e-EVN': ['Ef', 'Hh', 'Ir', 'Jb2', 'Mc', 'Nt', 'On', 'T6', 'Tr', 'Ys', 'Wb',
'Bd', 'Sv', 'Zc', 'Ir', 'Sr', 'Ur'],
'eMERLIN': ['Cm', 'Kn', 'Pi', 'Da', 'De'],
'LBA': ['ATCA', 'Pa', 'Mo', 'Ho', 'Cd', 'Td', 'Ww'],
'VLBA': ['Br', 'Fd', 'Hn', 'Kp', 'La', 'Mk', 'Nl', 'Ov', 'Pt', 'Sc'],
'KVN': ['Ky', 'Ku', 'Kt'],
'Global VLBI': ['Ef', 'Hh', 'Jb2', 'Mc', 'Nt', 'Ur', 'On', 'Sr', 'T6',
'Tr', 'Ys', 'Wb', 'Bd', 'Sv', 'Zc', 'Ir', 'Br', 'Fd', 'Hn',
'Kp', 'La', 'Mk', 'Nl', 'Ov', 'Pt', 'Sc'],
'HSA': ['Br', 'Fd', 'Hn', 'Kp', 'La', 'Mk', 'Nl', 'Ov', 'Pt', 'Sc', 'Ef', 'Ar',
'Gb', 'Y27'],
'GMVA': ['Ef', 'Mh', 'On', 'Ys', 'Pv', 'Br', 'Fd', 'Kp', 'La', 'Mk', 'Nl',
'Ov', 'Pt'],
'EHT': ['ALMA', 'Pv', 'LMT', 'PdB', 'SMA', 'JCMT', 'APEX', 'SMT', 'SPT']}
# Safety check that all these antennas are available in the file
for a_array in default_arrays:
for a_station in default_arrays[a_array]:
assert a_station in all_antennas.keys()
# Initial values
target_source = observation.Source('1h2m3s +50d40m30s', 'Source')
# obs_times = Time('1967-04-17 10:00') + np.arange(0, 600, 15)*u.min
selected_band = '18cm'
# external_stylesheets = ["https://stackpath.bootstrapcdn.com/bootstrap/4.5.0/css/bootstrap.min.css", "http://jive.eu/~marcote/style.css"]
# external_stylesheets = ["https://bmarcote.github.io/temp/style.css"]
external_stylesheets = []
# n_timestamps = 70 # Number of points (timestamps) for the whole observations.
# app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app = dash.Dash(__name__)
server = app.server
# app.config.requests_pathname_prefix = ''
# app.css.append_css({"external_url": "https://codepen.io/chriddyp/pen/bWLwgP.css"})
# app.css.append_css({"external_url": "https://codepen.io/chriddyp/pen/brPBPO.css"})
def tooltip(message, idname, trigger='?', placement='right', **kwargs):
"""Defines a tooltip (popover) that will be shown in the rendered page.
It will place a <sup>`trigger`</sup> in the page within a span tag.
Returns the list with all html elements.
return [html.Span(children=html.Sup(trigger, className='popover-link'), id=idname),
dbc.Tooltip(message, target=idname, placement=placement,
# className='tooltip-class', #innerClassName='tooltip-class-inner',
##################### This is the webpage layout
app.layout = html.Div([
$(document).ready(function() {
placement : 'bottom',
title : '<div style="text-align:center; color:red; text-decoration:underline; font-size:14px;"> Muah ha ha</div>', //this is the top title bar of the popover. add some basic css
html: 'true',
content : '<div id="popOverBox"><img src="http://www.hd-report.com/wp-content/uploads/2008/08/mr-evil.jpg" width="251" height="201" /></div>' //this is the content of the html box. add the image here or anything you want really.
html.Div(id='banner', className='navbar-brand d-flex p-3 shadow-sm', children=[
html.A(className='d-inline-block mr-md-auto', href="https://www.evlbi.org", children=[
html.Img(height='70px', src=app.get_asset_url("logo_evn.png"),
alt='European VLBI Network (EVN)',
className="d-inline-block align-top"),
html.H2('EVN Source Visibility', className='d-inline-block align-middle mx-auto'),
html.A(className='d-inline-block ml-auto pull-right', href="https://www.jive.eu", children=[
html.Img(src=app.get_asset_url("logo_jive.png"), height='70px',
alt='Joinst Institute for VLBI ERIC (JIVE)')
# html.Img(src='http://www.ira.inaf.it/evnnews/archive/evn.gif')
# ], className='banner'),
html.Div([html.Br()]), #style={'clear': 'both', 'margin-top': '20px'}),
# First row containing all buttons/options, list of telescopes, and button with text output
dcc.ConfirmDialog(id='global-error', message=''),
# Elements in second column (checkboxes with all stations)
html.Div(className='container-fluid', children=[
dcc.Tabs(parent_className='custom-tabs', className='custom-tabs-container', children=[
dcc.Tab(label='Observation Setup', className='custom-tab',
selected_className='custom-tab--selected', children=[
# Elements in first column ()
html.Div(className='row justify-content-center', children=[
html.Div(className='col-sm-3', style={'max-width': '300px','float': 'left',
'padding': '2%'}, children=[
html.Div(className='form-group', children=[
html.Label('Observing Band'),
*tooltip(idname='popover-band', message="First select the observing band. Antenna list will be updated and only the ones that can observe at this band will be enable."),
dcc.Dropdown(id='band', persistence=True,
options=[{'label': fs.bands[b], 'value': b} for b \
in fs.bands], value='18cm'),
html.Div(className='form-group', children=[
html.Label('Select default VLBI Network(s)'),
*tooltip(idname='popover-network', message="Automatically selects the default antennas for the selected VLBI network(s)."),
dcc.Dropdown(id='array', options=[{'label': n, 'value': n} \
for n in default_arrays if n != 'e-EVN'], value=['EVN'],
html.Div(className='input-group-prepend', children=[
dcc.Checklist(id='e-EVN', className='checkbox', persistence=True,
options=[{'label': ' e-EVN (real-time) mode',
'value': 'e-EVN'}], value=[]),
message="Only available for the EVN: real-time correlation mode.")
html.Div(className='form-group', children=[
html.Label('Start of observation (UTC)'),
# dcc.Input(id='starttime', value='DD/MM/YYYY HH:MM', type='text',
dcc.Input(id='starttime', value='17/04/1967 10:00', type='text',
className='form-control', placeholder="dd/mm/yyyy HH:MM",
html.Small(id='error_starttime', style={'color': 'red'},
className='form-text text-muted')
2 years ago
html.Div(className='form-group', children=[
html.Label('End of observation (UTC)'),
# dcc.Input(id='endtime', value='DD/MM/YYYY HH:MM', type='text',
dcc.Input(id='endtime', value='17/04/1967 20:00', type='text',
className='form-control', placeholder="dd/mm/yyyy HH:MM",
html.Small(id='error_endtime', style={'color': 'red'},
className='form-text text-muted')
html.Div(className='form-group', children=[
html.Label('Target Source Coordinates'),
message="J2000 coordinates are assumed."),
# dcc.Input(id='source', value='hh:mm:ss dd:mm:ss', type='text',
dcc.Input(id='source', value='12:29:06.7 +02:03:08.6', type='text',
className='form-control', placeholder="hh:mm:ss dd:mm:ss",
html.Small(id='error_source', style={'color': 'red'},
className='form-text text-muted'),
html.Div(className='form-group', children=[
children='% of on-target time'),
message="Assumes that you will only spend this amount of the total observing time on the given target source. It affects the expected sensitivity."),
dcc.Slider(id='onsourcetime', min=20, max=100, step=5, value=75,
marks= {i: str(i) for i in range(20, 101, 10)},
html.Div(className='form-group', children=[
html.Label('Datarate per station (in Mbps)'),
message=["Expected datarate for each station, assuming all of them run at the same rate.",
html.Li("The EVN can run typically at up to 2 Gbps (1 Gbps at L band), although a few antennas may observe at lower datarates."),
html.Li("The VLBA can now observe up to 4 Gbps."),
html.Li("The LBA typically observes at 512 Mbps but can run up to 1 Gbps."),
html.Li("Check the documentation from other networks to be sure about their capabilities.")])]),
dcc.Dropdown(id='datarate', placeholder="Select a datarate...",
options=[{'label': str(dr), 'value': dr} \
for dr in fs.data_rates], value=1024, persistence=True),
html.Div(className='form-group', children=[
html.Label('Number of subbands'),
message="In how many subbands the total band will be split during correlation."),
dcc.Dropdown(id='subbands', placeholder="Select no. subbands...",
options=[{'label': str(sb), 'value': sb} \
for sb in fs.subbands], value=8, persistence=True),
html.Div(className='form-group', children=[
html.Label('Number of spectral channels'),
message="How many channels per subband will be produced after correlation."),
dcc.Dropdown(id='channels', placeholder="Select no. channels...",
options=[{'label': str(ch), 'value': ch} \
for ch in fs.channels], value=32, persistence=True),
html.Div(className='form-group', children=[
html.Label('Number of polarizations'),
message="Number of polarizations to correlate. Note that VLBI observes circular polarizations. Full polarization implies the four stokes: RR, LL, RL, LR; while dual polarization implies RR and LL only."),
dcc.Dropdown(id='pols', placeholder="Select polarizations...",
options=[{'label': fs.polarizations[p], 'value': p} \
for p in fs.polarizations], value=4, persistence=True),
html.Div(className='form-group', children=[
html.Label('Integration time (s)'),
message="Integration time to compute each visibility. Note that for continuum observations values of 1-2 seconds are typical."),
dcc.Dropdown(id='inttime', placeholder="Select integration time...",
options=[{'label': fs.inttimes[it], 'value': it} \
for it in fs.inttimes], value=2, persistence=True),
# html.Div(style={'margin-top': '20px'}, children=[
html.Div(className='col-9', children=[
html.Div(className='col-9 text-center justify-content-center', children=[
html.Button('Compute Observation', id='antenna-selection-button',
className='btn btn-primary btn-lg'),
dcc.Loading(id="loading", children=[html.Div(id="loading-output")],
html.Div(id='antennas-div', className='container', children=[
# List with all antennas
html.Div(className='antcheck', children=[html.Br(),
options=[{'label': s.name, 'value': s.codename,
'disabled': not s.has_band(selected_band)}
for s in all_antennas if s.network == an_array], value=[])
]) for an_array in sorted_networks
# html.Div(className='col-sm-2', style={'float': 'left'}, children=[
# ])
dcc.Tab(label='Summary', className='custom-tab',
selected_className='custom-tab--selected', children=[
html.Div(className='row justify-content-center', children=[
# Sensitivity calculations
# dcc.Markdown(id='sensitivity-output',
# children="Set the observation first.")
html.Div(className='col-12', id='sensitivity-output',
children=[html.Div(className='col-6 justify-content-center',
html.P("You need to set the observation and click in the 'Compute Observation' buttom first (go to the previous tab).")])
dcc.Tab(label='Elevations', className='custom-tab',
selected_className='custom-tab--selected', children=[
html.Div(className='row justify-content-center', children=[
html.Div(className='col-md-8', children=[
# Elevation VS time
# Antenna VS time (who can observe)
dcc.Tab(label='Imaging', className='custom-tab',
selected_className='custom-tab--selected', children=[
# Images
html.Div(className='row justify-content-center', children=[
html.Div(className='col-md-8', children=[
# dcc.Markdown(children="""To be implemented.
# The uv coverage and expected dirty images will go here.""")
dcc.Tab(label='Documentation', className='custom-tab',
selected_className='custom-tab--selected', children=[
# Documentation
html.Div(className='row justify-content-center', children=[
html.Div(className='col-md-8', children=[
dcc.Markdown(children="""The Help/doc.
All explanations and technical details will go here.""")
def error_text(an_error):
"""Message written in a modal error window.
return f"An error occured.\n{an_error}.\nPlease report to marcote@jive.eu."
def convert_colon_coord(colon_coord):
"""Converts some coordinates given in a str format 'HH:MM:SS DD:MM:SS' to
If ':' are not present in colon_coord, then it returns the same str.
if ':' not in colon_coord:
return colon_coord
for l in ('h', 'm', 'd', 'm'):
colon_coord = colon_coord.replace(':', l, 1)
return colon_coord.replace(' ', 's ')+'s'
def get_selected_antennas(list_of_selected_antennas):
"""Given a list of antenna codenames, it returns a Stations object containing
all given antennas.
selected_antennas = stations.Stations('Observation', [])
for ant in list_of_selected_antennas:
return selected_antennas
def optimal_units(value, units):
"""Given a value (with some units), returns the unit choice from all
`units` possibilities that better suits the value.
It is meant for the following use:
Given 0.02*u.Jy and units = [u.kJy, u.Jy, u.mJy, u.uJy], it will
return 20*u.mJy.
units should have a decreasing-scale of units, and all of them
compatible with the units in `value`.
for a_unit in units:
if 0.8 < value.to(a_unit).value <= 800:
return value.to(a_unit)
# Value too high or too low
if value.to(units[0]).value > 1:
return value.to(units[0])
return value.to(units[-1])
def create_sensitivity_card(title, message):
"""Defines one of the cards that are shown in the Sensitivity tab. Each tab
shows a title `title` and a message `message`.
If message is a list (of strings), it is assumed as different paragraphs.
It returns the HTML code of the card.
ps = []
if type(message) is list:
for a_msg in message:
ps.append(html.P(className='card-text', children=a_msg))
ps = [html.P(className='card-text', children=message)]
# return [html.Div(className='card', style={'min-width': '15rem', 'max-width': '25rem'}, children=[
return [html.Div(className='card m-3', children=[
html.Div(className='card-body', children=[
html.H5(className='card-title', children=title)] + ps)])
def alert_message(message, title="Warning!"):
"""Produces an alert-warning message.
message can be either a string or a list with different string/dash components.
if type(message) == str:
return [html.Br(), \
dbc.Alert([html.H4(title, className='alert-heading'), message], \
color='warning', dismissable=True)]
return [html.Br(), \
dbc.Alert([html.H4(title, className='alert-heading'), *message], \
color='warning', dismissable=True)]
def update_sensitivity(obs):
"""Given the observation, it sets the text about all properties of the observation.
pol_dict = {1: 'single', 2: 'dual', 4: 'full'}
rms = optimal_units(obs.thermal_noise(), [u.MJy, u.kJy, u.Jy, u.mJy, u.uJy])
rms_time = optimal_units(obs.thermal_noise()/np.sqrt(obs.inttime/obs.duration),
[u.MJy, u.kJy, u.Jy, u.mJy, u.uJy])
rms_channel = optimal_units(rms*np.sqrt(obs.subbands*obs.channels),
[u.MJy, u.kJy, u.Jy, u.mJy, u.uJy])
ants_up = obs.is_visible()
ant_no_obs = []
for an_ant in ants_up:
if len(ants_up[an_ant][0]) == 0:
ant_text = ', '.join(obs.stations.keys()) + '.'
cards = []
# The time card
temp_msg = [f"{fx.print_obs_times(obs)}."]
temp_msg += [f"Observing for {optimal_units(obs.duration, [u.h, u.min, u.s, u.ms]):.3n} in total, with {optimal_units(obs.ontarget_time, [u.h, u.min, u.s, u.ms]):.3n} on target."]
temp_msg += [f"With a time integration of {optimal_units(obs.inttime, [u.s,u.ms,u.us]):.2n} the expected FITS file size is {optimal_units(obs.datasize(), [u.TB, u.GB, u.MB, u.kB]):.3n}."]
cards += create_sensitivity_card('Observing Time', temp_msg)
# Antennas
longest_bl = obs.longest_baseline()[1]
# Using dummy units to allow the conversion
longest_bl_lambda = longest_bl/obs.wavelength
longest_bl_lambda = optimal_units(longest_bl_lambda*u.m, [u.Gm, u.Mm, u.km])
temp_msg = [f"{len(ants_up)-len(ant_no_obs)} participating antennas: {ant_text}"]
if len(ant_no_obs) > 0:
temp_msg += [html.P(className='text-danger', children=f"Note that {', '.join(ant_no_obs)} cannot observe the source.")]
temp_msg += [f"The longest (projected) baseline is {optimal_units(longest_bl, [u.km, u.m]):.5n} ({longest_bl_lambda.value:.3n} {longest_bl_lambda.unit.name[0]}lambda)."]
synthbeam = obs.synthesized_beam()
synthbeam_units = optimal_units(synthbeam['bmaj'], [u.arcsec, u.mas, u.uas]).unit
temp_msg += [f"The expected synthesized beam will be approx. {synthbeam['bmaj'].to(synthbeam_units).value:.2n} x {synthbeam['bmin'].to(synthbeam_units):.2n}^2, PA = {synthbeam['pa']:.3n}."]
cards += create_sensitivity_card('Antennas', temp_msg)
# Frequency
temp_msg = [f"Observing at a central frequency of {optimal_units(obs.frequency, [u.GHz, u.MHz]):.3n} ({optimal_units(obs.wavelength, [u.m, u.cm, u.mm]):.2n})."]
temp_msg += [f"The total bandwidth of {optimal_units(obs.bandwidth, [u.GHz, u.MHz, u.kHz]):.3n} will be divided into {obs.subbands} subbands of {optimal_units(obs.bandwidth/obs.subbands, [u.GHz, u.MHz, u.kHz]):.3n} each, with {obs.channels} channels ({optimal_units(obs.bandwidth/(obs.subbands*obs.channels), [u.GHz, u.MHz, u.kHz, u.Hz]):.3n} wide)."]
temp_msg += [f"Recording {pol_dict[obs.polarizations]} circular polarization."]
cards += create_sensitivity_card('Frequency Setup', temp_msg)
temp_msg = [f"Considering the sensitivities of the antennas, the estimated thermal noise is {rms:.3n}/beam."]
temp_msg += [f"This would imply a rms of {rms_channel:.3n}/beam per spectral channel, or approx. {rms_time:.3n}/beam per time integration ({optimal_units(obs.inttime, [u.s,u.ms,u.us]):.3n})."]
cards += create_sensitivity_card('Sensitivity', temp_msg)
# resolution and FITS files
# temp_msg = [f""]
# cards += create_sensitivity_card('Resolution')
# FoV smearing
shortest_bl = obs.shortest_baseline()[1]
largest_ang_scales = ((2.063e8*u.mas)*(obs.wavelength/shortest_bl)).to(u.mas)
temp_msg = [f"The Field of View would be limited by time smearing to {optimal_units(obs.time_smearing(), [u.arcmin, u.arcsec]):.3n} and by frequency smearing to {optimal_units(obs.bandwidth_smearing(), [u.arcmin, u.arcsec]):.3n} (for a 10% loss)."]
temp_msg += [f"Considering the shortest baseline in the array ({optimal_units(shortest_bl, [u.km, u.m]):.5n}), you will filter out emission on angular scales larger than {optimal_units(largest_ang_scales, [u.arcmin, u.arcsec, u.mas]):.3n}."]
cards += create_sensitivity_card('FoV limitations', temp_msg)
return [html.Div(className='card-deck col-12', children=cards)]
@app.callback(Output('onsourcetime-label', 'children'),
[Input('onsourcetime', 'value')])
def update_onsourcetime_label(onsourcetime):
return f"% of on-target time ({onsourcetime}%)"
@app.callback(Output('antennas-div', 'children'),
[Input('band', 'value'), Input('array', 'value'), Input('e-EVN', 'value')])
def select_antennas(selected_band, selected_networks, is_eEVN):
"""Given a selected band and selected default networks, it selects the associated
antennas from the antenna list.
selected_antennas = []
if is_eEVN:
selected_antennas = [ant for ant in default_arrays['e-EVN'] \
if (all_antennas[ant].has_band(selected_band) and \
(all_antennas[ant].network == 'EVN'))]
return [html.Div([html.Br(),
options=[{'label': s.name, 'value': s.codename,
'disabled': (not s.has_band(selected_band)) or \
(not s.codename in default_arrays['e-EVN'])}
for s in all_antennas if s.network == an_array],
value=selected_antennas if an_array=='EVN' else [],
className='antcheck', labelClassName='form-check-label',
inputClassName='form-check-input')]) for an_array in sorted_networks]
for an_array in selected_networks:
selected_antennas += [ant for ant in default_arrays[an_array] \
if all_antennas[ant].has_band(selected_band)]
return [html.Div([html.Br(),
options=[{'label': s.name, 'value': s.codename,
'disabled': not s.has_band(selected_band)}
for s in all_antennas if s.network == an_array],
value=[s.codename for s in all_antennas \
if (s.codename in selected_antennas) and (s.network == an_array)],
className='antcheck', labelClassName='form-check-label',
inputClassName='form-check-input')]) for an_array in sorted_networks]
@app.callback([Output('error_starttime', 'children'),
Output('error_endtime', 'children')],
[Input('starttime', 'value'), Input('endtime', 'value')])
def check_obstime(starttime, endtime):
if starttime != 'DD/MM/YYYY HH:MM':
time0 = Time(datetime.datetime.strptime(starttime, '%d/%m/%Y %H:%M'),
except ValueError as e:
return 'Incorrect format (dd/mm/YYYY HH:MM)', dash.no_update
if endtime != 'DD/MM/YYYY HH:MM':
time1 = Time(datetime.datetime.strptime(endtime, '%d/%m/%Y %H:%M'),
except ValueError as e:
return dash.no_update, 'Incorrect format (dd/mm/YYYY HH:MM)'
if ('time1' in locals()) and ('time0' in locals()):
if (time1 - time0) > 5*u.d:
return ["Please, put an observation shorter than 5 d"]*2
elif (time0 - time1) >= 0*u.d:
return ["Start time must be earlier than end time"]*2
return '', ''
@app.callback(Output('error_source', 'children'),
[Input('source', 'value')])
def get_source(source_coord):
if source_coord != 'hh:mm:ss dd:mm:ss':
dummy_target = observation.Source(convert_colon_coord(source_coord), 'Source')
return ''
except ValueError as e:
return "Use 'hh:mm:ss dd:mm:ss' format"
return dash.no_update
@app.callback([Output('loading-output', 'children'),
Output('sensitivity-output', 'children'),
Output('fig-elev-time', 'figure'),
Output('fig-ant-time', 'figure'),
Output('fig-uvplane', 'figure'), Output('global-error', 'message')],
[Input('antenna-selection-button', 'n_clicks')],
[State('band', 'value'),
State('starttime', 'value'),
State('endtime', 'value'),
State('source', 'value'),
State('onsourcetime', 'value'),
State('datarate', 'value'),
State('subbands', 'value'),
State('channels', 'value'),
State('pols', 'value'),
State('inttime', 'value'),
State('list_stations_EVN', 'value'),
State('list_stations_eMERLIN', 'value'),
State('list_stations_VLBA', 'value'),
State('list_stations_LBA', 'value'),
State('list_stations_KVN', 'value'),
State('list_stations_Other', 'value')])
def compute_observation(n_clicks, band, starttime, endtime, source, onsourcetime, datarate,
subbands, channels, pols, inttime, *ants):
# subbands, channels, pols, inttime, ants_evn, ants_emerlin,
# ants_vlba, ants_lba, ants_kvn, ants_other):
"""Computes all products to be shown concerning the set observation.
if n_clicks is None:
return '', dash.no_update, dash.no_update, dash.no_update, \
dash.no_update, dash.no_update
target_source = observation.Source(convert_colon_coord(source), 'Source')
except ValueError as e:
return alert_message(["Incorrect format for source coordinates.", html.Br(),
f"{'Empty value' if source=='' else source} found but 'hh:mm:ss dd:mm:ss' expected."]),\
"First, set correctly an observation in the previous tab.", \
dash.no_update, dash.no_update, dash.no_update, dash.no_update
time0 = Time(datetime.datetime.strptime(starttime, '%d/%m/%Y %H:%M'),
format='datetime', scale='utc')
except ValueError as e:
return alert_message("Incorrect format for starttime."), \
"First, set correctly an observation in the previous tab.", \
dash.no_update, dash.no_update, dash.no_update, dash.no_update
time1 = Time(datetime.datetime.strptime(endtime, '%d/%m/%Y %H:%M'),
format='datetime', scale='utc')
except ValueError as e:
return alert_message("Incorrect format for endtime."), \
"First, set correctly an observation in the previous tab.", \
dash.no_update, dash.no_update, dash.no_update, dash.no_update
if time0 >= time1:
return alert_message("The start time must be earlier than the end time"), \
"First, set correctly an observation in the previous tab.", \
dash.no_update, dash.no_update, dash.no_update, dash.no_update
if (time1 - time0) > 5*u.d:
return alert_message("Please, set an observation that last for less than 5 days."), \
"First, set correctly an observation in the previous tab.", \
dash.no_update, dash.no_update, dash.no_update, dash.no_update
# try:
# TODO: this should not be hardcoded...
obs_times = time0 + np.linspace(0, (time1-time0).to(u.min).value, 50)*u.min
# obs_times = time0 + np.arange(0, (time1-time0).to(u.min).value, 15)*u.min
all_selected_antennas = list(itertools.chain.from_iterable(ants))
obs = observation.Observation(target=target_source, times=obs_times, band=band,
datarate=datarate, subbands=subbands, channels=channels,
polarizations=pols, inttime=inttime, ontarget=onsourcetime/100.0,
sensitivity_results = update_sensitivity(obs)
except observation.SourceNotVisible:
return alert_message([
html.P(["Your source cannot be observed within the arranged observation.",
"The source is not visible for any of the selected antennas " \
+ "in the given observing time."]),
html.P("Modify the observing time of select a different array to observe" \
+ " this source.")], title="Warning!"), \
dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update
# return update_sensitivity(obs), dash.no_update, dash.no_update
# TODO: parallelize all these functions
return [html.Br(),
dbc.Alert("You can check now the results in the different tabs", color='info', \
dismissable=True)], sensitivity_results, \
get_fig_ant_elev(obs), get_fig_ant_up(obs), get_fig_uvplane(obs), dash.no_update
def get_fig_ant_elev(obs):
data_fig = []
data_dict = obs.elevations()
# Some reference lines at low elevations
for ant in data_dict:
data_fig.append({'x': obs.times.datetime, 'y': data_dict[ant].value,
'mode': 'lines', 'hovertemplate': "Elev: %{y:.2n}º",
'name': obs.stations[ant].name})
data_fig.append({'x': obs.times.datetime, 'y': np.zeros_like(obs.times)+10,
'mode': 'lines', 'hoverinfo': 'skip', 'name': 'Elev. limit 10º',
'line': {'dash': 'dash', 'opacity': 0.5, 'color': 'gray'}})
data_fig.append({'x': obs.gstimes.value, 'y': np.zeros_like(obs.times)+20, 'xaxis': 'x2',
'mode': 'lines', 'hoverinfo': 'skip', 'name': 'Elev. limit 20º',
'line': {'dash': 'dot', 'opacity': 0.5, 'color': 'gray'}})
return {'data': data_fig,
'layout': {'title': 'Source elevation during the observation',
'hovermode': 'closest',
'xaxis': {'title': 'Time (UTC)', 'showgrid': False,
'ticks': 'inside', 'showline': True, 'mirror': False,
'hovermode': 'closest', 'color': 'black'},
'xaxis2': {'title': {'text': 'Time (GST)', 'standoff': 0},
'showgrid': False, 'overlaying': 'x',
'ticks': 'inside', 'showline': True, 'mirror': False,
'hovermode': 'closest', 'color': 'black', 'side': 'top'},
'yaxis': {'title': 'Elevation (degrees)', 'range': [0., 92.],
'ticks': 'inside', 'showline': True, 'mirror': "all",
'showgrid': False, 'hovermode': 'closest'},
'zeroline': True, 'zerolinecolor': 'k'}}
def get_fig_ant_up(obs):
data_fig = []
data_dict = obs.is_visible()
for i,ant in enumerate(data_dict):
data_fig.append({'x': obs.times.datetime[data_dict[ant]],
'y': np.zeros_like(data_dict[ant][0])-i, 'type': 'scatter',
# 'mode': 'markers', 'hoverinfo': "skip",
'mode': 'markers', 'marker': {'symbol': "41"}, 'hoverinfo': "skip",
'name': obs.stations[ant].name})
return {'data': data_fig,
'layout': {'title': 'Source visible (>10 deg) during the observation',
'xaxis': {'title': 'Time (UTC)', 'showgrid': False,
'ticks': 'inside', 'showline': True, 'mirror': "all",
'hovermode': 'closest', 'color': 'black'},
'yaxis': {'ticks': '', 'showline': True, 'mirror': True,
'showticklabels': False, 'zeroline': False,
2 years ago
'showgrid': False, 'hovermode': 'closest',