def get_coops(start, end, sos_name, units, bbox, verbose=False):
collector = CoopsSos()
collector.set_bbox(bbox)
collector.end_time = end
collector.start_time = start
collector.variables = [sos_name]
ofrs = collector.server.offerings
title = collector.server.identification.title
config = dict(units=units, sos_name=sos_name,)
data = collector2table(
collector=collector,
config=config,
col="{} ({})".format(sos_name, units.format(cf_units.UT_ISO_8859_1)),
)
# Clean the table.
table = dict(
station_name=[s._metadata.get("station_name") for s in data],
station_code=[s._metadata.get("station_code") for s in data],
sensor=[s._metadata.get("sensor") for s in data],
lon=[s._metadata.get("lon") for s in data],
lat=[s._metadata.get("lat") for s in data],
depth=[s._metadata.get("depth", "NA") for s in data],
)
table = pd.DataFrame(table).set_index("station_name")
if verbose:
print("Collector offerings")
print("{}: {} offerings".format(title, len(ofrs)))
return data, table
def get_coops(start, end, sos_name, units, bbox, verbose=False):
"""
function to read COOPS data
We need to retry in case of failure b/c the server cannot handle
the high traffic during hurricane season.
"""
print(' >> Get CO-OPS information')
collector = CoopsSos()
collector.set_bbox(bbox)
collector.end_time = end
collector.start_time = start
collector.variables = [sos_name]
ofrs = collector.server.offerings
title = collector.server.identification.title
config = dict(
units=units,
sos_name=sos_name,
datum='MSL', ###Saeed added
)
data = collector2table(
collector=collector,
config=config,
col='{} ({})'.format(sos_name, units.format(cf_units.UT_ISO_8859_1))
)
# Clean the table.
table = dict(
station_name = [s._metadata.get('station_name') for s in data],
station_code = [s._metadata.get('station_code') for s in data],
sensor = [s._metadata.get('sensor') for s in data],
lon = [s._metadata.get('lon') for s in data],
lat = [s._metadata.get('lat') for s in data],
depth = [s._metadata.get('depth', 'NA') for s in data],
)
table = pd.DataFrame(table).set_index('station_name')
if verbose:
print('Collector offerings')
print('{}: {} offerings'.format(title, len(ofrs)))
return data, table
config = dict(
units=units,
sos_name=sos_name,
datum='MSL', ###Saeed added
)
data = collector2table(
collector=collector,
config=config,
col='{} ({})'.format(sos_name, units.format(cf_units.UT_ISO_8859_1))
)
# Clean the table.
table = dict(
station_name = [s._metadata.get('station_name') for s in data],
station_code = [s._metadata.get('station_code') for s in data],
sensor = [s._metadata.get('sensor') for s in data],
lon = [s._metadata.get('lon') for s in data],
lat = [s._metadata.get('lat') for s in data],
depth = [s._metadata.get('depth', 'NA') for s in data],
)
table = pd.DataFrame(table).set_index('station_name')
if verbose:
collector_coops.start_time = config["date"]["start"]
collector_coops.variables = [config["sos_name"]]
ofrs = collector_coops.server.offerings
title = collector_coops.server.identification.title
print(fmt(" Collector offerings "))
print("{}: {} offerings".format(title, len(ofrs)))
To make it easier to work with the data we extract the time-series as pandas tables and interpolate them to a common 1-hour interval index.
import pandas as pd
from ioos_tools.ioos import collector2table
data = collector2table(
collector=collector_coops,
config=config,
col="water_surface_height_above_reference_datum (m)",
)
df = dict(
station_name=[s._metadata.get("station_name") for s in data],
station_code=[s._metadata.get("station_code") for s in data],
sensor=[s._metadata.get("sensor") for s in data],
lon=[s._metadata.get("lon") for s in data],
lat=[s._metadata.get("lat") for s in data],
depth=[s._metadata.get("depth") for s in data],
)
pd.DataFrame(df).set_index("station_code")
index = pd.date_range(
collector_ndbc.set_bbox(config["region"]["bbox"])
collector_ndbc.end_time = config["date"]["stop"]
collector_ndbc.start_time = config["date"]["start"]
collector_ndbc.variables = [config["sos_name"]]
ofrs = collector_ndbc.server.offerings
title = collector_ndbc.server.identification.title
print(fmt(" NDBC Collector offerings "))
print("{}: {} offerings".format(title, len(ofrs)))
import pandas as pd
from ioos_tools.ioos import collector2table
ndbc = collector2table(
collector=collector_ndbc, config=config, col="sea_water_temperature (C)"
)
if ndbc:
data = dict(
station_name=[s._metadata.get("station_name") for s in ndbc],
station_code=[s._metadata.get("station_code") for s in ndbc],
sensor=[s._metadata.get("sensor") for s in ndbc],
lon=[s._metadata.get("lon") for s in ndbc],
lat=[s._metadata.get("lat") for s in ndbc],
depth=[s._metadata.get("depth") for s in ndbc],
)
table = pd.DataFrame(data).set_index("station_code")
table
collector_ndbc.set_bbox(config["region"]["bbox"])
collector_ndbc.end_time = config["date"]["stop"]
collector_ndbc.start_time = config["date"]["start"]
collector_ndbc.variables = [config["sos_name"]]
ofrs = collector_ndbc.server.offerings
title = collector_ndbc.server.identification.title
print(fmt(" NDBC Collector offerings "))
print("{}: {} offerings".format(title, len(ofrs)))
import pandas as pd
from ioos_tools.ioos import collector2table
ndbc = collector2table(
collector=collector_ndbc,
config=config,
col="sea_surface_wave_significant_height (m)",
)
if ndbc:
data = dict(
station_name=[s._metadata.get("station_name") for s in ndbc],
station_code=[s._metadata.get("station_code") for s in ndbc],
sensor=[s._metadata.get("sensor") for s in ndbc],
lon=[s._metadata.get("lon") for s in ndbc],
lat=[s._metadata.get("lat") for s in ndbc],
depth=[s._metadata.get("depth") for s in ndbc],
)
table = pd.DataFrame(data).set_index("station_code")
table