First major release

app.py

@@ -62,7 +62,7 @@ default_arrays = {'EVN': ['Ef', 'Hh', 'Jb2', 'Mc', 'Nt', 'Ur', 'On', 'Sr', 'T6',
                     'Bd', 'Sv', 'Zc', 'Ir', 'Sr', 'Ur'],
           'eMERLIN': ['Cm', 'Kn', 'Pi', 'Da', 'De'],
           'LBA': ['ATCA', 'Pa', 'Mo', 'Ho', 'Cd', 'Td', 'Ww'],
-          'VLBA': ['Br', 'Fd', 'Hh', 'Kp', 'La', 'Mk', 'Nl', 'Ov', 'Pt', 'Sc'],
+          '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',
@@ -83,36 +83,6 @@ 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'
 
-sensitivity_results_template = """
-
-{band:.2n} ({freq:.2n}) observations with the following antennas:
-
-{antennas}
-
-{sb} ({sbbw:.2n}) subbands with {ch} channels each and {pols} polarization.
-
-Total bandwidth of the observation: {bandwidth:.3n}
-({bandwidth_channel:.3n} per spectral channel)
-
-
-**Estimated image thermal noise** (assuming {ttarget:.3n} on target):  {noise:.3n}
-
-
-Estimated rms thernal noise per spectral channel: {noise_channel:.3n}
-
-**Resulting FITS file size**: {filesize:.3n}
-
-(note that this is only an estimation)
-
-
-**Smearing in the Field of View** (for a 10% loss):
-
-Field of View limited by bandwidth-smearing to: {bw_smearing:.3n}
-
-Field of View limited by time-smearing to: {t_smearing:.3n}
-
-"""
-
 
 
 
@@ -139,8 +109,17 @@ server = app.server
 
 #####################  This is the webpage layout
 app.layout = html.Div([
-    html.Div([
-        html.H1('EVN Source Visibility'),
+    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'),
@@ -149,14 +128,16 @@ app.layout = html.Div([
     dcc.ConfirmDialog(id='global-error', message=''),
     # Elements in second column (checkboxes with all stations)
     html.Div(className='container-fluid', children=[
-        dcc.Tabs([
-            dcc.Tab(label='Observation Setup', className='container', 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-cols-3', children=[
+                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'),
+                    #data-content="This popover appears on the right", data-toggle="popover"),
                         dcc.Dropdown(id='band', persistence=True,
                                  options=[{'label': fs.bands[b], 'value': b} for b \
                                 in fs.bands], value='18cm'),
@@ -169,7 +150,7 @@ app.layout = html.Div([
                     ]),
                     html.Div(className='input-group-prepend', children=[
                         dcc.Checklist(id='e-EVN', className='checkbox', persistence=True,
-                                      options=[{'label': ' e-EVN (real-time) mode?',
+                                      options=[{'label': ' e-EVN (real-time) mode',
                                                 'value': 'e-EVN'}], value=[]),
                     ]),
                     html.Div(className='form-group', children=[
@@ -238,7 +219,13 @@ app.layout = html.Div([
                     ])
                 ]),
                 # html.Div(style={'margin-top': '20px'}, children=[
-                html.Div(className='col-lg-7', style={'float': 'left'}, 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")],
+                                    type="dot")
+                    ]),
                     html.Div(id='antennas-div', className='container', children=[
                     # List with all antennas
                         html.Div(className='antcheck', children=[html.Br(),
@@ -254,23 +241,24 @@ app.layout = html.Div([
                         ]) for an_array in sorted_networks
                     ])
                 ]),
-                html.Div(className='col-sm-2', style={'float': 'left'}, children=[
-                    html.Button('Compute Observation', id='antenna-selection-button',
-                                className='btn btn-primary btn-lg',
-                                # style={'margin': '5px 5px 5px 5px'}),
-                                style={'padding': '5px', 'margin-top': '50px'}),
-                ])
+                # html.Div(className='col-sm-2', style={'float': 'left'}, children=[
+                # ])
                 ])
             ]),
 
-            dcc.Tab(label='Sensitivity', children=[
-                html.Div(className='col-md-8', 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.")
+                    # dcc.Markdown(id='sensitivity-output',
+                    #              children="Set the observation first.")
+                    html.Div(className='col-12', id='sensitivity-output',
+                            children=[html.Br(), html.P("Set the observation first.")])
                 ])
             ]),
-            dcc.Tab(label='Plots', children=[
+            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
                     html.Div([
@@ -280,22 +268,26 @@ app.layout = html.Div([
                     html.Div([
                         dcc.Graph(id='fig-ant-time')
                     ])
-                ])
+                ])])
             ]),
-            dcc.Tab(label='Images', children=[
+            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.""")
                     html.Div([dcc.Graph(id='fig-uvplane')])
-                ])
+                ])])
             ]),
-            dcc.Tab(label='Help', children=[
+            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.""")
-                ])
+                ])])
             ])
         ])
     ])
@@ -355,40 +347,89 @@ def optimal_units(value, units):
     return value.to(units[-1])
 
 
-def update_sensitivity(an_obs):
+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))
+    else:
+        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 update_sensitivity(obs):
     """Given the observation, it sets the text about all properties of the observation.
     """
-    rms = optimal_units(an_obs.thermal_noise(), [u.MJy, u.kJy, u.Jy, u.mJy, u.uJy])
-    rms_channel = optimal_units(rms*np.sqrt(an_obs.subbands*an_obs.channels),
+    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 = an_obs.is_visible()
+    ants_up = obs.is_visible()
     ant_no_obs = []
     for an_ant in ants_up:
         if len(ants_up[an_ant][0]) == 0:
             ant_no_obs.append(an_ant)
 
-    antennas_text = ', '.join(an_obs.stations.keys())
+    ant_text = ', '.join(obs.stations.keys()) + '.'
     if len(ant_no_obs) > 0:
-        antennas_text += f"\n (note that {', '.join(ant_no_obs)} cannot observe the source)."
-    return sensitivity_results_template.format(
-            band=optimal_units(an_obs.wavelength, [u.m, u.cm, u.mm]),
-            freq=optimal_units(an_obs.frequency, [u.GHz, u.MHz]),
-            antennas=antennas_text,
-            sb=an_obs.subbands,
-            sbbw=optimal_units(an_obs.bandwidth/an_obs.subbands, [u.GHz, u.MHz, u.kHz]),
-            ch=an_obs.channels,
-            pols={1: 'single', 2: 'dual', 4: 'full'}[an_obs.polarizations],
-            ttarget=optimal_units(an_obs.ontarget_fraction*(an_obs.times[-1]-an_obs.times[0]),
-                                  [u.h, u.min, u.s, u.ms]),
-            noise=rms,
-            noise_channel=rms_channel,
-            filesize=optimal_units(an_obs.datasize(), [u.TB, u.GB, u.MB, u.kB]),
-            bw_smearing=optimal_units(an_obs.bandwidth_smearing(), [u.arcmin, u.arcsec]),
-            t_smearing=optimal_units(an_obs.time_smearing(), [u.arcmin, u.arcsec]),
-            bandwidth=optimal_units(an_obs.bandwidth, [u.GHz, u.MHz, u.kHz]),
-            bandwidth_channel=optimal_units(an_obs.bandwidth/(an_obs.subbands*an_obs.channels),
-                                            [u.GHz, u.MHz, u.kHz, u.Hz]))
+        ant_text += f"<p class='text-danger'>Note that {', '.join(ant_no_obs)} cannot observe the source.</p>"
+
+    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 = optimal_units(((longest_bl*u.m)/obs.wavelength).to(u.m),
+                                      [u.Gm, u.Mm, u.km])
+    temp_msg = [f"{len(ants_up)-len(ant_no_obs)} participating antennas: {ant_text}"]
+    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']:.2n}."]
+    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)
+
+    # RMS
+    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)]
 
 
 
@@ -478,7 +519,8 @@ def get_source(source_coord):
 
 
 
-@app.callback([Output('sensitivity-output', 'children'),
+@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')],
@@ -506,34 +548,37 @@ def compute_observation(n_clicks, band, starttime, endtime, source, onsourcetime
     """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
+        return '', dash.no_update, dash.no_update, dash.no_update, \
+               dash.no_update, dash.no_update
     try:
         target_source = observation.Source(convert_colon_coord(source), 'Source')
     except ValueError as e:
-        return f"""Incorrect format for source coordinates:
+        return "Incorrect format for source coordinates", f"""Incorrect format for source coordinates:
         {source} found but 'hh:mm:ss dd:mm:ss' expected.
         """, dash.no_update, dash.no_update, dash.no_update, dash.no_update
     try:
         time0 = Time(datetime.datetime.strptime(starttime, '%d/%m/%Y %H:%M'),
-                     format='datetime')
+                     format='datetime', scale='utc')
     except ValueError as e:
-        return "Incorrect format for starttime.", dash.no_update, dash.no_update, \
-                dash.no_update, dash.no_update
+        return "Incorrect format for starttime", "Incorrect format for starttime.", \
+               dash.no_update, dash.no_update, dash.no_update, dash.no_update
 
     try:
         time1 = Time(datetime.datetime.strptime(endtime, '%d/%m/%Y %H:%M'),
-                     format='datetime')
+                     format='datetime', scale='utc')
     except ValueError as e:
-        return "Incorrect format for endtime.", dash.no_update, dash.no_update, \
-                dash.no_update, dash.no_update
+        return "Incorrect format for endtime", "Incorrect format for endtime.", \
+               dash.no_update, dash.no_update, dash.no_update, dash.no_update
 
     if time0 >= time1:
-        return "The start time of the observation must be earlier than the end time.", \
-                dash.no_update, dash.no_update, dash.no_update, dash.no_update
+        return "The start time of the observation must be earlier than the end time", \
+               "The start time of the observation must be earlier than the end time.", \
+               dash.no_update, dash.no_update, dash.no_update, dash.no_update
 
     if (time1 - time0) > 5*u.d:
-        return "Please, put a time range smaller than 5 days.", \
-                dash.no_update, dash.no_update, dash.no_update, dash.no_update
+        return "Please, put a time range smaller than 5 days", \
+               "Please, put a time range smaller than 5 days.", \
+               dash.no_update, dash.no_update, dash.no_update, dash.no_update
 
     # try:
     # TODO: this should not be hardcoded...
@@ -550,8 +595,9 @@ def compute_observation(n_clicks, band, starttime, endtime, source, onsourcetime
 
 
     # return update_sensitivity(obs), dash.no_update, dash.no_update
-    return update_sensitivity(obs), get_fig_ant_elev(obs), get_fig_ant_up(obs), \
-          get_fig_uvplane(obs), dash.no_update
+    # TODO: parallelize all these functions
+    return 'You can check now the results in the different tabs', update_sensitivity(obs), \
+           get_fig_ant_elev(obs), get_fig_ant_up(obs), get_fig_uvplane(obs), dash.no_update
 
 
 
@@ -598,7 +644,7 @@ def get_fig_ant_up(obs):
                          'name': obs.stations[ant].name})
 
     return {'data': data_fig,
-            'layout': {'title': 'Source visible during the observation',
+            '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'},
@@ -619,7 +665,7 @@ def get_fig_uvplane(obs):
         uv[:len(bl_uv[bl_name]), :] = bl_uv[bl_name]
         uv[len(bl_uv[bl_name]):, :] = -bl_uv[bl_name]
         data_fig.append({'x': uv[:,0],
-                         'y': uv[:,1], 
+                         'y': uv[:,1],
                          # 'type': 'scatter', 'mode': 'lines',
                          'type': 'scatter', 'mode': 'markers',
                          'marker': {'symbol': '.', 'size': 2},

assets/bootstrap-reboot.css

@@ -0,0 +1,330 @@
+/*!
+ * Bootstrap Reboot v4.0.0 (https://getbootstrap.com)
+ * Copyright 2011-2018 The Bootstrap Authors
+ * Copyright 2011-2018 Twitter, Inc.
+ * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
+ * Forked from Normalize.css, licensed MIT (https://github.com/necolas/normalize.css/blob/master/LICENSE.md)
+ */
+*,
+*::before,
+*::after {
+  box-sizing: border-box;
+}
+
+html {
+  font-family: sans-serif;
+  line-height: 1.15;
+  -webkit-text-size-adjust: 100%;
+  -ms-text-size-adjust: 100%;
+  -ms-overflow-style: scrollbar;
+  -webkit-tap-highlight-color: transparent;
+}
+
+@-ms-viewport {
+  width: device-width;
+}
+
+article, aside, dialog, figcaption, figure, footer, header, hgroup, main, nav, section {
+  display: block;
+}
+
+body {
+  margin: 0;
+  font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";
+  font-size: 1rem;
+  font-weight: 400;
+  line-height: 1.5;
+  color: #212529;
+  text-align: left;
+  background-color: #fff;
+}
+
+[tabindex="-1"]:focus {
+  outline: 0 !important;
+}
+
+hr {
+  box-sizing: content-box;
+  height: 0;
+  overflow: visible;
+}
+
+h1, h2, h3, h4, h5, h6 {
+  margin-top: 0;
+  margin-bottom: 0.5rem;
+}
+
+p {
+  margin-top: 0;
+  margin-bottom: 1rem;
+}
+
+abbr[title],
+abbr[data-original-title] {
+  text-decoration: underline;
+  -webkit-text-decoration: underline dotted;
+  text-decoration: underline dotted;
+  cursor: help;
+  border-bottom: 0;
+}
+
+address {
+  margin-bottom: 1rem;
+  font-style: normal;
+  line-height: inherit;
+}
+
+ol,
+ul,
+dl {
+  margin-top: 0;
+  margin-bottom: 1rem;
+}
+
+ol ol,
+ul ul,
+ol ul,
+ul ol {
+  margin-bottom: 0;
+}
+
+dt {
+  font-weight: 700;
+}
+
+dd {
+  margin-bottom: .5rem;
+  margin-left: 0;
+}
+
+blockquote {
+  margin: 0 0 1rem;
+}
+
+dfn {
+  font-style: italic;
+}
+
+b,
+strong {
+  font-weight: bolder;
+}
+
+small {
+  font-size: 80%;
+}
+
+sub,
+sup {
+  position: relative;
+  font-size: 75%;
+  line-height: 0;
+  vertical-align: baseline;
+}
+
+sub {
+  bottom: -.25em;
+}
+
+sup {
+  top: -.5em;
+}
+
+a {
+  color: #007bff;
+  text-decoration: none;
+  background-color: transparent;
+  -webkit-text-decoration-skip: objects;
+}
+
+a:hover {
+  color: #0056b3;
+  text-decoration: underline;
+}
+
+a:not([href]):not([tabindex]) {
+  color: inherit;
+  text-decoration: none;
+}
+
+a:not([href]):not([tabindex]):hover, a:not([href]):not([tabindex]):focus {
+  color: inherit;
+  text-decoration: none;
+}
+
+a:not([href]):not([tabindex]):focus {
+  outline: 0;
+}
+
+pre,
+code,
+kbd,
+samp {
+  font-family: monospace, monospace;
+  font-size: 1em;
+}
+
+pre {
+  margin-top: 0;
+  margin-bottom: 1rem;
+  overflow: auto;
+  -ms-overflow-style: scrollbar;
+}
+
+figure {
+  margin: 0 0 1rem;
+}
+
+img {
+  vertical-align: middle;
+  border-style: none;
+}
+
+svg:not(:root) {
+  overflow: hidden;
+}
+
+table {
+  border-collapse: collapse;
+}
+
+caption {
+  padding-top: 0.75rem;
+  padding-bottom: 0.75rem;
+  color: #6c757d;
+  text-align: left;
+  caption-side: bottom;
+}
+
+th {
+  text-align: inherit;
+}
+
+label {
+  display: inline-block;
+  margin-bottom: .5rem;
+}
+
+button {
+  border-radius: 0;
+}
+
+button:focus {
+  outline: 1px dotted;
+  outline: 5px auto -webkit-focus-ring-color;
+}
+
+input,
+button,
+select,
+optgroup,
+textarea {
+  margin: 0;
+  font-family: inherit;
+  font-size: inherit;
+  line-height: inherit;
+}
+
+button,
+input {
+  overflow: visible;
+}
+
+button,
+select {
+  text-transform: none;
+}
+
+button,
+html [type="button"],
+[type="reset"],
+[type="submit"] {
+  -webkit-appearance: button;
+}
+
+button::-moz-focus-inner,
+[type="button"]::-moz-focus-inner,
+[type="reset"]::-moz-focus-inner,
+[type="submit"]::-moz-focus-inner {
+  padding: 0;
+  border-style: none;
+}
+
+input[type="radio"],
+input[type="checkbox"] {
+  box-sizing: border-box;
+  padding: 0;
+}
+
+input[type="date"],
+input[type="time"],
+input[type="datetime-local"],
+input[type="month"] {
+  -webkit-appearance: listbox;
+}
+
+textarea {
+  overflow: auto;
+  resize: vertical;
+}
+
+fieldset {
+  min-width: 0;
+  padding: 0;
+  margin: 0;
+  border: 0;
+}
+
+legend {
+  display: block;
+  width: 100%;
+  max-width: 100%;
+  padding: 0;
+  margin-bottom: .5rem;
+  font-size: 1.5rem;
+  line-height: inherit;
+  color: inherit;
+  white-space: normal;
+}
+
+progress {
+  vertical-align: baseline;
+}
+
+[type="number"]::-webkit-inner-spin-button,
+[type="number"]::-webkit-outer-spin-button {
+  height: auto;
+}
+
+[type="search"] {
+  outline-offset: -2px;
+  -webkit-appearance: none;
+}
+
+[type="search"]::-webkit-search-cancel-button,
+[type="search"]::-webkit-search-decoration {
+  -webkit-appearance: none;
+}
+
+::-webkit-file-upload-button {
+  font: inherit;
+  -webkit-appearance: button;
+}
+
+output {
+  display: inline-block;
+}
+
+summary {
+  display: list-item;
+  cursor: pointer;
+}
+
+template {
+  display: none;
+}
+
+[hidden] {
+  display: none !important;
+}
+/*# sourceMappingURL=bootstrap-reboot.css.map */

assets/bootstrap-reboot.min.css

@@ -0,0 +1,8 @@
+/*!
+ * Bootstrap Reboot v4.0.0 (https://getbootstrap.com)
+ * Copyright 2011-2018 The Bootstrap Authors
+ * Copyright 2011-2018 Twitter, Inc.
+ * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
+ * Forked from Normalize.css, licensed MIT (https://github.com/necolas/normalize.css/blob/master/LICENSE.md)
+ */*,::after,::before{box-sizing:border-box}html{font-family:sans-serif;line-height:1.15;-webkit-text-size-adjust:100%;-ms-text-size-adjust:100%;-ms-overflow-style:scrollbar;-webkit-tap-highlight-color:transparent}@-ms-viewport{width:device-width}article,aside,dialog,figcaption,figure,footer,header,hgroup,main,nav,section{display:block}body{margin:0;font-family:-apple-system,BlinkMacSystemFont,"Segoe UI",Roboto,"Helvetica Neue",Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji","Segoe UI Symbol";font-size:1rem;font-weight:400;line-height:1.5;color:#212529;text-align:left;background-color:#fff}[tabindex="-1"]:focus{outline:0!important}hr{box-sizing:content-box;height:0;overflow:visible}h1,h2,h3,h4,h5,h6{margin-top:0;margin-bottom:.5rem}p{margin-top:0;margin-bottom:1rem}abbr[data-original-title],abbr[title]{text-decoration:underline;-webkit-text-decoration:underline dotted;text-decoration:underline dotted;cursor:help;border-bottom:0}address{margin-bottom:1rem;font-style:normal;line-height:inherit}dl,ol,ul{margin-top:0;margin-bottom:1rem}ol ol,ol ul,ul ol,ul ul{margin-bottom:0}dt{font-weight:700}dd{margin-bottom:.5rem;margin-left:0}blockquote{margin:0 0 1rem}dfn{font-style:italic}b,strong{font-weight:bolder}small{font-size:80%}sub,sup{position:relative;font-size:75%;line-height:0;vertical-align:baseline}sub{bottom:-.25em}sup{top:-.5em}a{color:#007bff;text-decoration:none;background-color:transparent;-webkit-text-decoration-skip:objects}a:hover{color:#0056b3;text-decoration:underline}a:not([href]):not([tabindex]){color:inherit;text-decoration:none}a:not([href]):not([tabindex]):focus,a:not([href]):not([tabindex]):hover{color:inherit;text-decoration:none}a:not([href]):not([tabindex]):focus{outline:0}code,kbd,pre,samp{font-family:monospace,monospace;font-size:1em}pre{margin-top:0;margin-bottom:1rem;overflow:auto;-ms-overflow-style:scrollbar}figure{margin:0 0 1rem}img{vertical-align:middle;border-style:none}svg:not(:root){overflow:hidden}table{border-collapse:collapse}caption{padding-top:.75rem;padding-bottom:.75rem;color:#6c757d;text-align:left;caption-side:bottom}th{text-align:inherit}label{display:inline-block;margin-bottom:.5rem}button{border-radius:0}button:focus{outline:1px dotted;outline:5px auto -webkit-focus-ring-color}button,input,optgroup,select,textarea{margin:0;font-family:inherit;font-size:inherit;line-height:inherit}button,input{overflow:visible}button,select{text-transform:none}[type=reset],[type=submit],button,html [type=button]{-webkit-appearance:button}[type=button]::-moz-focus-inner,[type=reset]::-moz-focus-inner,[type=submit]::-moz-focus-inner,button::-moz-focus-inner{padding:0;border-style:none}input[type=checkbox],input[type=radio]{box-sizing:border-box;padding:0}input[type=date],input[type=datetime-local],input[type=month],input[type=time]{-webkit-appearance:listbox}textarea{overflow:auto;resize:vertical}fieldset{min-width:0;padding:0;margin:0;border:0}legend{display:block;width:100%;max-width:100%;padding:0;margin-bottom:.5rem;font-size:1.5rem;line-height:inherit;color:inherit;white-space:normal}progress{vertical-align:baseline}[type=number]::-webkit-inner-spin-button,[type=number]::-webkit-outer-spin-button{height:auto}[type=search]{outline-offset:-2px;-webkit-appearance:none}[type=search]::-webkit-search-cancel-button,[type=search]::-webkit-search-decoration{-webkit-appearance:none}::-webkit-file-upload-button{font:inherit;-webkit-appearance:button}output{display:inline-block}summary{display:list-item;cursor:pointer}template{display:none}[hidden]{display:none!important}
+/*# sourceMappingURL=bootstrap-reboot.min.css.map */

assets/style.css

@@ -45,7 +45,8 @@
 html {
     font-family: sans-serif;
     line-height: 1.15;
-    -webkit-text-size-adjust: 100%;
+    text-size-adjust: 90%;
+    -webkit-text-size-adjust: 90%;
     -webkit-tap-highlight-color:rgba(0, 0, 0, 0)
 }
 
@@ -3199,7 +3200,7 @@ input[type="submit"].btn-block, input[type="reset"].btn-block, input[type="butto
 
 
 /* Custom styles */
- 
+
 input[type=checkbox] {
     -webkit-appearance: none;
     -moz-appearance: none;
@@ -3208,9 +3209,11 @@ input[type=checkbox] {
 }
 
 input[type=checkbox] {
-    width: 25px;
-    height: 20px;
-    margin-right: 8px;
+    width: 17px;
+    height: 17px;
+    line-height: 17px;
+    margin-right: 0px;
+    margin-bottom: 20px;
     cursor: pointer;
     font-size: 17px;
     visibility: hidden;
@@ -3222,12 +3225,13 @@ input[type=checkbox]:after {
     background-color: #fff;
     display: inline-block;
     color: #00BFF0;
-    width: 19px;
-    height: 19px;
+    width: 17px;
+    height: 17px;
     visibility: visible;
     border: 1px solid #00BFF0;
     padding-left: 5px;
     border-radius: 5px;
+    margin-bottom: 0px;
 }
 
 input[type=checkbox]:not(:disabled):after {
@@ -3235,45 +3239,146 @@ input[type=checkbox]:not(:disabled):after {
     font-weight: bold;
     color: #00BFF0;
     border: 1px solid #00BFF0;
-} 
+}
 
-input[type=checkbox]:hover:after {
-    content: " ";
+input[type=checkbox]:not(:disabled):not(checked):hover:after {
+    content: "";
     color: gray;
     background-color: rgb(232, 222, 222);
-} 
+}
 
 input[type=checkbox]:checked:after {
     content: "\2714";
+    font-family: "FontAwesome";
+    /* content: "\f00c"; */
     font-weight: bold;
     color: green;
-    border: 1px solid green;
-    background-color: rgb(176, 225, 176);
+    font-size: 1.1rem;
+    -moz-font-size: 1.1rem;
+    /* line-height: 0px; */
+    border: none;
+    background-color: none;
+    margin-left: -0.1rem;
 }
-                            
-input[type=checkbox]:disabled:after {
-    content: "X";
-    border: 1px solid #FF304F;
-    color: red;
-    /* background-color: #dc3545; */
-    background-color: rgba(234, 116, 113);
+
+input[type=checkbox]:not(:disabled):checked:hover:after {
+    content: " ";
+    color: gray;
+    background-color: rgb(232, 222, 222);
+    content: "\2714";
+    font-weight: bold;
+    color: green;
+    font-size: 1.5rem;
 }
 
-/* input[type=checkbox]:disabled:before+label { */
-/*     color: red; */
-/* } */
+
+input[type=checkbox]:disabled:after {
+    /* content: "X"; */
+    font-family: "FontAwesome";
+    content: "\2715";
+    border: none;
+    /* color: #a01d26; */
+    color: #F0959B;
+    background-color: none;
+    margin-left: -0.1rem;
+}
 
 
 .antcheck label {
-    padding-left: 10pt; 
-    padding-right: 10pt; 
+    padding-left: 10pt;
+    padding-right: 10pt;
     width: 135pt;
 }
 
 
+.card {
+    min-width: 19rem;
+    max-width: 19rem;
+    border: 1px solid #CCCCCC;
+    border-left: 5px solid #a01d26;
+}
+
+.card-title {
+   color: #a01d26;
+}
+
+.btn-primary {
+    color: #a01d26;
+    background-color: #F0959B;
+    border-color: #F0959B;
+    margin-top: 50px;
+    width: 20rem;
+}
+
+.btn-primary:hover {
+    color: #fff;
+    background-color: #a01d26;
+    border-color: #a01d26;
+}
+
+.btn-primary:focus, .btn-primary.focus {
+    box-shadow:0 0 0 .2rem rgba(255, 79, 105, 0.5)
+}
+
+.custom-tab:active {
+    color: #586069;
+/*     border-top-left-radius: 3px; */
+/*     border-top-right-radius: 3px; */
+/*     border-top: 3px solid transparent !important; */
+/*     border-left: 0px !important; */
+/*     border-right: 0px !important; */
+/*     border-bottom: 0px !important; */
+    background-color: #f4f4ef;
+    border-color: #a01d26;
+    /* border-bottom: 3px solid #a01d26; */
+/*     padding: 12px !important; */
+/*     font-family: "system-ui"; */
+/*     display: flex !important; */
+/*     align-items: center; */
+/*     justify-content: center; */
+}
+
+.custom-tabs-container .tab--selected {
+    background-color: #F0959B;
+    color: #a01d26;
+    border-color: #a01d26;
+    border-top: 3px solid #a01d26 !important;
+
+}
+
+.navbar-brand {
+    height: 70px;
+    width: 100%;
+    margin: 0 auto;
+    padding: 0 20px;
+    border: none;
+    text-align: right;
+    min-height: 50px;
+    background: #f4f4ef;
+}
+
+.banner:after {
+    content: " ";
+    display: table;
+    clear: both;
+}
+
+.navbar-brand a {
+    margin: 0;
+    padding: 0;
+}
+
+.navbar-brand img {
+    margin: 0;
+    padding: 0;
+    margin-top: -15px;
+}
+
 /* FOR TEXT INPUTS I SHOULD ADD AN OFFSET SHADOW (REFACTORING UI TRICKS):
 box-shadow: inset 0 2px 4px 0 hsla(0 0% 0& 0.08);
-*/)
+*/
+
+/* evlbi.org color:  #a01d26 */
 
 /*     --blue: #007bff; */
 /*     --indigo: #6610f2; */

data/station_location.txt

@@ -25,7 +25,7 @@ Tianma          T6       EVN -2826708.6030   4679237.0770   3274667.5510    -1
 Shanghai        Sh       EVN -2826708.6030   4679237.0770   3274667.5510    -1       -1       -1       -1       670      800      720     1500    800       -1        -1   -1  -1
 Urumqi          Ur       EVN 228310.2129     4631922.7656   4367064.0638    -1       -1       -1       300      300      560      250     -1      350       850       -1   -1  -1
 Yebes           Ys       EVN 4848780.1314    -261701.7668   4123035.9350    -1       -1       -1       -1       -1       1400     160     160     200       200       480   -1  -1
-Zelenchkaya     Zc       EVN 3451207.5353    3060375.4139   4391915.0384    -1       -1       -1       300      300      330      400     -1      200       710       -1   -1  -1
+Zelenchukskaya  Zc       EVN 3451207.5353    3060375.4139   4391915.0384    -1       -1       -1       300      300      330      400     -1      200       710       -1   -1  -1
 JVLA_1          VLA      VLBA -1601185.4286   -5041977.1754  3554875.6231    3900     -1       -1       420      420      370      310     310     250       350       560  -1  -1
 JVLA_27         Y27      VLBA -1601185.4286   -5041977.1754  3554875.6231    167      -1       -1       17.9     17.9     15.8     13.2    13.2    10.7      15        23.9  -1  -1
 Robledo_70      Ro7      EVN 4849336.6927    -360488.7857   4114748.8272    -1       -1       -1       -1       35       20       -1      -1      18        83        -1    -1  -1

doc/notes.md

@@ -76,6 +76,7 @@ Observation
     - target : FixedTarget
     - times : Time
     - gstimes :  Longitude (hourangle)
+	- duration : Time
     - band : str
     - wavelength : u.Quantity
     - frequency : u.Quantity
@@ -85,6 +86,7 @@ Observation
     - polarizations : int
     - inttime : u.Quantity
     - ontarget_fraction : float
+	- ontarget_time : Time
     - bandwidth : u.Quantity
     - bitsampling : u.Quantity
     - stations : Stations
@@ -94,6 +96,8 @@ Observation
     + elevations() --> dict[codename]: list
     + altaz() --> dict[codename]: list
     + is_visible() --> dict[codename]: list
+	+ longest_baseline() --> (str, u.Quantity)
+	+ shortest_baseline() --> (str, u.Quantity)
     + bandwidth_smearing() --> u.Quantity
     + time_smearing() --> u.Quantity
     + datasize() --> u.Quantity
@@ -113,11 +117,9 @@ Observation
 
 + get_stations_from_file(filename) --> dict
 + stations_with_band(networks : dict/Stations, band) --> Stations
++ print_obs_times(obs, dateformat='%d &m &Y')
 
 
-+ get_bandwidth_smearing()
-+ get_time_smearing()
-
 
 
 ### freqsetups.py
@@ -143,8 +145,8 @@ Bands([fromfile])
 
 - Strike antenna name text if does not have the given frequency.
 - Put some "loading" times.
-- Add GST times.
-- In sensitivity: highlight antennas that cannot observe the source.
+X Add GST times.
+X In sensitivity: highlight antennas that cannot observe the source.
 - Add some pop up (`card` on Bootstrap) on each antenna with info: picture?, codename, country, etc.
 - observation.Observation.thermal_noise() can be highly optimized.
 - Help buttons and explanatory dialog.

src/freqsetups.py

@@ -11,14 +11,14 @@ import enum
 #
 #     def __init__(self, fromfile='../data/frequency_setups.py'):
 
-bands = {'92cm': 'P - 92 cm / 0.33 GHz', '49cm': 'P - 49 cm / 0.6 GHz',
-         '30cm': 'UHF - 30 cm /  1 GHz', '21cm': 'L - 21 cm / 1.4 GHz',
-         '18cm': 'L - 18 cm / 1.7 GHz', '13cm': 'S - 13 cm / 2.3 GHz',
-         '6cm': 'C - 6cm / 5 GHz', '5cm': 'C - 5 cm / 6 GHz',
-         '3.6cm': 'X - 3.6 cm / 8.3 GHz', '2cm': 'U - 2 cm / 15 GHz',
-         '1.3cm': 'K - 1.3 cm / 23 GHz', '0.9cm': 'Ka - 0.9 cm / 33 GHz',
-         '0.7cm': 'Q - 0.7 cm / 43 GHz', '0.3cm': 'W - 0.3 cm / 100 GHz',
-         '0.1cm': '0.1 cm / 300 GHz'}
+bands = {'92cm': 'P band (92 cm - 0.33 GHz)', '49cm': 'P band (49 cm - 0.6 GHz)',
+         '30cm': 'UHF band (30 cm -  1 GHz)', '21cm': 'L band (21 cm - 1.4 GHz)',
+         '18cm': 'L band (18 cm - 1.7 GHz)', '13cm': 'S band (13 cm - 2.3 GHz)',
+         '6cm': 'C band (6cm - 5 GHz)', '5cm': 'M band (5 cm - 6 GHz)',
+         '3.6cm': 'X band (3.6 cm - 8.3 GHz)', '2cm': 'U band (2 cm - 15 GHz)',
+         '1.3cm': 'K band (1.3 cm - 23 GHz)', '0.9cm': 'Ka band (0.9 cm - 33 GHz)',
+         '0.7cm': 'Q band (0.7 cm - 43 GHz)', '0.3cm': 'W band (0.3 cm - 100 GHz)',
+         '0.1cm': '0.1 cm - 300 GHz'}
 
 data_rates = (2**i for i in range(13, 2, -1)) # from 4 to 4096
 subbands = (2**i for i in range(5, 0, -1)) # from 1 to 16

src/functions.py

@@ -114,3 +114,41 @@ def stations_with_band(networks, band, output_network_name=None):
     return antennas
 
 
+def print_obs_times(obs, date_format='%d %b %Y'):
+    """Given an observation, it returns the time range (starttime-endtime) in a smart
+    way. If the observation lasts for less than one day it omits the end date:
+            20 Jan 1971 10:00-20:00UT
+
+    Input:
+        - obs : observation.Observation
+            It must already have set the .times part with an array of astropy.Time times.
+        - date_format : str [optional]
+            Format for the date part (only the date part) of the string to represent
+            the time range.
+    Output:
+        - printed_time : str
+            A string showing the time-range of the observation.
+
+    """
+    if obs.times[0].datetime.date() == obs.times[-1].datetime.date():
+        return "{} {}-{} UTC".format(obs.times[0].datetime.strftime(date_format),
+                                    obs.times[0].datetime.strftime('%H:%M'),
+                                    obs.times[-1].datetime.strftime('%H:%M'))
+    else:
+        return "{} {} to {} {} UTC".format(obs.times[0].datetime.strftime(date_format),
+                                    obs.times[0].datetime.strftime('%H:%M'),
+                                    obs.times[-1].datetime.strftime(date_format),
+                                    obs.times[-1].datetime.strftime('%H:%M'))
+        
+
+
+
+
+
+
+
+
+
+
+
+

src/observation.py

@@ -77,6 +77,10 @@ class Observation(object):
     def gstimes(self):
         return self._gstimes
 
+    @property
+    def duration(self):
+        return self.times[-1]-self.times[0]
+
     @property
     def band(self):
         return self._band
@@ -167,6 +171,10 @@ class Observation(object):
         assert 0.0 < ontarget <= 1.0
         self._ontarget = ontarget
 
+    @property
+    def ontarget_time(self):
+        return self.duration*self.ontarget_fraction
+
     @property
     def bandwidth(self):
         """Returns the total bandwidth of the observation.
@@ -227,9 +235,31 @@ class Observation(object):
         It retuns the tuple ((ant1,ant2), length)
         where `ant1,ant2` are the antennas in such baseline, and `length` its length.
         """
-        # TODO: To Implement
-        return ('XX','XX'), 1000*u.km
-        raise NotImplemented('observation.longest_baseline')
+        uv = self.get_uv()
+        longest_bl = {'bl': '', 'value': None}
+        for a_bl in uv:
+            bl_length = np.sqrt(np.max((uv[a_bl]**2).sum(axis=1)))
+            if (longest_bl['value'] is None) or (bl_length > longest_bl['value']):
+                longest_bl['bl'] = a_bl
+                longest_bl['value'] = bl_length
+
+        return longest_bl['bl'], longest_bl['value']*self.wavelength
+
+    def shortest_baseline(self):
+        """Returns the shortest baseline in the observation.
+        It retuns the tuple ((ant1,ant2), length)
+        where `ant1,ant2` are the antennas in such baseline, and `length` its length.
+        """
+        uv = self.get_uv()
+        shortest_bl = {'bl': '', 'value': None}
+        for a_bl in uv:
+            bl_length = np.sqrt(np.max((uv[a_bl]**2).sum(axis=1)))
+            if (shortest_bl['value'] is None) or (bl_length < shortest_bl['value']):
+            # if (bl_length < shortest_bl['value']) or (shortest_bl['value'] is None):
+                shortest_bl['bl'] = a_bl
+                shortest_bl['value'] = bl_length
+
+        return shortest_bl['bl'], shortest_bl['value']*self.wavelength
 
     def bandwidth_smearing(self):
         """Returns the bandwidth smearing expected for the given observation.
@@ -343,6 +373,48 @@ class Observation(object):
 
         return bl_uv_up
 
+
+    def synthesized_beam(self):
+        """Estimates the resulting synthesized beam of the observations based on
+        the expected uv coverage.
+        This is just an estimation made by a ellipse fitting to the uv coverage,
+        from which we obtain the resolution on the two axes following
+        https://science.nrao.edu/facilities/vlba/docs/manuals/oss/ang-res
+            theta_HPBW (mas)  \sim 2063 x lambda(cm)/b_max^km
+
+        returns a dict with the following keys: bmaj, bmin, pa.
+        """
+        resolution = lambda bl : ((2.063e8*u.mas)/bl).to(u.mas)
+        uvdata = self.get_uv()
+        # Generates a N 2-D array with all uv data.
+        tot_length = 0
+        for bl_name in uvdata:
+            tot_length += uvdata[bl_name].shape[0]
+
+        uvvis = np.empty((tot_length, 2))
+        i = 0
+        for bl_name in uvdata:
+            uvvis[i:i+uvdata[bl_name].shape[0],:] = uvdata[bl_name]
+            i += uvdata[bl_name].shape[0]
+
+        del uvdata
+        # Transform the uv points into r,theta (polar) points
+        uvvis_polar = np.empty_like(uvvis)
+        uvvis_polar[:,0] = np.sqrt((uvvis**2).sum(axis=1)) # radius
+        uvvis_polar[:,1] = np.arctan2(uvvis[:,1], uvvis[:,0]) # theta
+        # Defines the BMAJ and PA
+        bl_bmaj = np.max(uvvis_polar[:,0])
+        bl_bmaj_theta = uvvis_polar[:,1][np.where(uvvis_polar[:,0] == bl_bmaj)][0]
+        # Estimates the BMIN
+        cond = np.where((uvvis_polar[:,1] > (bl_bmaj_theta+np.pi/3) % (2*np.pi)) & (uvvis_polar[:,1] < (bl_bmaj_theta+2*np.pi/3) % (2*np.pi) ))
+        if len(cond[0]) == 0:
+            cond = np.where((uvvis_polar[:,1] > (bl_bmaj_theta+4*np.pi/3) % (2*np.pi)) & (uvvis_polar[:,1] < (bl_bmaj_theta+5*np.pi/3) % (2*np.pi) ))
+
+        bl_bmin = np.max( uvvis_polar[:,0][cond] )
+
+        return {'bmaj': resolution(bl_bmin), 'bmin': resolution(bl_bmaj), 'pa': (bl_bmaj_theta*u.rad).to(u.deg)}
+
+
     # def get_dirtymap(self):
     #     uvdata = self._get_uv()
     #     # Generates a N 2-D array with all uv data.

test/test.py

@@ -24,7 +24,7 @@ from src import observation
 target = observation.Source('10h10m10s +0d30m20s', name='Target')
 
 obs = observation.Observation(target=target)
-obs.times = Time('2020-04-01 10:00') + np.arange(0, 600, 10)*u.min
+obs.times = Time('2020-04-01 10:00', scale='utc') + np.arange(0, 600, 10)*u.min
 obs.band = '6cm'
 obs.datarate = 1024
 obs.subbands = 8