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from awips.dataaccess import DataAccessLayer
import cartopy.crs as ccrs
import cartopy.feature as cfeat
import matplotlib.pyplot as plt
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
import numpy as np
import datetime

# Create an EDEX data request
DataAccessLayer.changeEDEXHost("edex-cloud.unidata.ucar.edu")
request = DataAccessLayer.newDataRequest()
request.setDatatype("satellite")

# get optional identifiers for satellite datatype
identifiers = set(DataAccessLayer.getOptionalIdentifiers(request))

print("Available Identifiers:")
for id in identifiers:
    if id.lower() == 'datauri':
        continue
    print(" - " + id.decode('UTF-8'))


    

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# Show available sources
identifier = "source"
sources = DataAccessLayer.getIdentifierValues(request, identifier)
print(identifier + ":")
print(list(sources))


    

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# Show available creatingEntities
identifier = "creatingEntity"
creatingEntities = DataAccessLayer.getIdentifierValues(request, identifier)
print(identifier + ":")
print(list(creatingEntities))


    

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# Show available sectorIDs
identifier = "sectorID"
sectorIDs = DataAccessLayer.getIdentifierValues(request, identifier)
print(identifier + ":")
print(list(sectorIDs))


    

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# Contrust a full satellite product tree
for entity in creatingEntities:
    print(entity.decode('UTF-8'))
    request = DataAccessLayer.newDataRequest("satellite")
    request.addIdentifier("creatingEntity", entity)
    availableSectors = DataAccessLayer.getAvailableLocationNames(request)
    availableSectors.sort()
    for sector in availableSectors:
        print(" - " + sector.decode('UTF-8'))
        request.setLocationNames(sector.decode('UTF-8'))
        availableProducts = DataAccessLayer.getAvailableParameters(request)
        availableProducts.sort()
        for product in availableProducts:
            print("    - " + product.decode('UTF-8'))


    

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%matplotlib inline

def make_map(bbox, projection=ccrs.PlateCarree()):
    fig, ax = plt.subplots(figsize=(10,12),
            subplot_kw=dict(projection=projection))
    if bbox[0] is not np.nan:
        ax.set_extent(bbox)
    ax.coastlines(resolution='50m')
    gl = ax.gridlines(draw_labels=True)
    gl.xlabels_top = gl.ylabels_right = False
    gl.xformatter = LONGITUDE_FORMATTER
    gl.yformatter = LATITUDE_FORMATTER
    return fig, ax

sectors = ["EMESO-1","EMESO-2"]
fig = plt.figure(figsize=(16,7*len(sectors)))

for i, sector in enumerate(sectors):

    request = DataAccessLayer.newDataRequest()
    request.setDatatype("satellite")
    request.setLocationNames(sector)
    request.setParameters("CH-13-10.35um")

    utc = datetime.datetime.utcnow()
    times = DataAccessLayer.getAvailableTimes(request)
    hourdiff = utc - datetime.datetime.strptime(str(times[-1]),'%Y-%m-%d %H:%M:%S')
    hours,days = hourdiff.seconds/3600,hourdiff.days
    minute = str((hourdiff.seconds - (3600 * hours)) / 60)
    offsetStr = ''
    if hours > 0:
        offsetStr += str(hours) + "hr "
    offsetStr += str(minute) + "m ago"
    if days > 1:
        offsetStr = str(days) + " days ago"

    response = DataAccessLayer.getGridData(request, [times[-1]])
    grid = response[0]
    data = grid.getRawData()
    lons,lats = grid.getLatLonCoords()
    bbox = [lons.min(), lons.max(), lats.min(), lats.max()]

    print("Latest image available: "+str(times[-1]) + " ("+offsetStr+")")
    print("Image grid size: " + str(data.shape))
    print("Image grid extent: " + str(list(bbox)))

    fig, ax = make_map(bbox=bbox)
    states = cfeat.NaturalEarthFeature(category='cultural',
                                        name='admin_1_states_provinces_lines',
                                        scale='50m', facecolor='none')
    ax.add_feature(states, linestyle=':')
    cs = ax.pcolormesh(lons, lats, data, cmap='coolwarm')
    cbar = fig.colorbar(cs, shrink=0.6, orientation='horizontal')
    cbar.set_label(sector + " " \
    + grid.getParameter().decode('UTF-8') + " " \
    + str(grid.getDataTime().getRefTime()))