[python #JEP-515405]: FW: 20171221: script that inserts CSPP-GEO created GOES-16 products into an LDM queue (cont.)
- Subject: [python #JEP-515405]: FW: 20171221: script that inserts CSPP-GEO created GOES-16 products into an LDM queue (cont.)
- Date: Tue, 02 Jan 2018 13:17:32 -0700
CSPP-GEO comes from SSEC at Wisconsin, and handles all of the dealings with
combining metadata and individual image sections--so if you're wondering how
that's calculating corners, you probably need to ask them. :)
As far as nc.variables is concerned, in the example I sent you, nc is a
netCDF4.Dataset object for a file from the GOES-16 GRB feed, *after* CSPP-GEO
has assembled the complete file.
> And yes, I am using the "basemap" collection.
> On Friday, December 29, 2017 3:39pm, "Unidata Python Support"
> <address@hidden> said:
> > Ray,
> > So your original question was: "How are you getting the other corner
> > values?"
> > My answer is: I don't think we are. :)
> > You mention matplotlib and the "map" command, but I'm not aware of any such
> > command. Are you using Basemap? If so, I'm not sure I can help much. We've
> > moved
> > away from it, since it's in maintenance-only mode.
> > I've plotted the GRB data using CartoPy, and I have been able to get away
> > with
> > only using the coordinate information contained within the data. Here's the
> > plotting code I've used:
> > import matplotlib.pyplot as plt
> > import cartopy.crs as ccrs
> > import cartopy.feature as cfeature
> > data = nc.variables['Rad'][:]
> > state_boundaries = cfeature.NaturalEarthFeature(category='cultural',
> > name='admin_1_states_provinces_lakes',
> > scale='50m',
> > facecolor='none')
> > fig = plt.figure(figsize=(10,10))
> > proj_var = nc.variables['goes_imager_projection']
> > globe = ccrs.Globe(semimajor_axis=proj_var.semi_major_axis,
> > semiminor_axis=proj_var.semi_minor_axis)
> > proj =
> > ccrs.Geostationary(central_longitude=proj_var.longitude_of_projection_origin,
> > satellite_height=proj_var.perspective_point_height,
> > globe=globe)
> > ax = fig.add_subplot(1, 1, 1, projection=proj)
> > x = nc.variables['x'][:] * proj_var.perspective_point_height
> > y = nc.variables['y'][:] * proj_var.perspective_point_height
> > ax.imshow(data, extent=(x.min(), x.max(), y.min(), y.max()), cmap='Greys_r',
> > origin='upper')
> > ax.coastlines('10m', color='tab:blue')
> > ax.add_feature(state_boundaries, edgecolor='tab:red')
> > Ryan
> >> And yes, NOAAPORT uses a totally different projection, lambert conformal,
> >> and the
> >> proper values are in that data. So its being calculated by CSPP-GEO or
> >> however
> >> they are driving NOAAPORT from GRB.
> >> Ray
> > Ticket Details
> > ===================
> > Ticket ID: JEP-515405
> > Department: Support Python
> > Priority: Low
> > Status: Closed
> > ===================
> > NOTE: All email exchanges with Unidata User Support are recorded in the
> > Unidata
> > inquiry tracking system and then made publicly available through the web.
> > If you
> > do not want to have your interactions made available in this way, you must
> > let us
> > know in each email you send to us.
Ticket ID: JEP-515405
Department: Support Python
NOTE: All email exchanges with Unidata User Support are recorded in the Unidata
inquiry tracking system and then made publicly available through the web. If
you do not want to have your interactions made available in this way, you must
let us know in each email you send to us.