parser.add_argument("--output",nargs="?",type=str,help="output type (print/JSON) ");
parser.add_argument("--save_sum",action='store_true',help="If True, sum of potential output will be saved for all grid cells in outfile+_sum.npy. False by default. ");
parser.set_defaults(save_sum=False)
args = parser.parse_args();
server = args.server[0];
port = args.port
username = args.username;
password = args.password;
cutoutname = args.cutoutname[0];
cutoutuser = args.cutoutuser
conversion_name = args.name;
save_sum = args.save_sum
onshorecurve = reatlas_client.turbineconf_to_powercurve_object(args.onshorepowercurve[0]);
offshorecurve = reatlas_client.turbineconf_to_powercurve_object(args.offshorepowercurve[0]);
capacitylayouts = args.capacitylayout;
output = args.output
if (username == None):
username = raw_input("username: "******"password: ");
try:
if (port != None):
atlas = reatlas_client.REatlas(server,port);
else:
atlas = reatlas_client.REatlas(server);
print("56.9,7.5 degrees has index " + str((i, j)) + ".")
# Prepare for wind conversion:
# Make a capacity layout with 0 everywhere but in (i,j)
layout = numpy.zeros(Denmark["latitudes"].shape)
layout[i, j] = 1.0
# Upload it
numpy.save("layout.npy", layout)
atlas.upload_file(filename="layout.npy")
# Load the power curve
Vestas90 = reatlas_client.turbineconf_to_powercurve_object("TurbineConfig/Vestas_V90_3MW.cfg")
# Start a wind conversion on Denmark:
atlas.select_cutout(cutoutname="Denmark", username="******")
wind_job = atlas.convert_and_aggregate_wind(
result_name="myresult", onshorepowercurve=Vestas90, offshorepowercurve=Vestas90, capacitylayouts=["layout.npy"]
)
# Find the temporal index for January 13, 1992 at 05.00 UTC
idx = numpy.where(Denmark["dates"] == datetime.datetime(1992, 1, 13, 5, 0))[0][0]
print("January 13, 1992 at 05.00 UTC has index " + str(idx) + ".")