import zeep.cache
import zeep.transports
-__version__ = '3.2.4'
+__version__ = '3.3.1'
LOG = logging.getLogger(__name__)
LOG.setLevel(logging.NOTSET)
LOG.critical("%s is not a valid timezone", tz)
sys.exit(1)
+ # By default, fetch three hours of data
+ #
+ # If user wants hn24 or wind averaging, then
+ # we need more.
+ station['num_hrs_to_fetch'] = 3
+
# HN24
if 'hn24' in config['station']:
if config['station']['hn24'] not in ['true', 'false']:
if config['station']['hn24'] == "true":
station['hn24'] = True
+ station['num_hrs_to_fetch'] = 24
else:
station['hn24'] = False
else:
raise ValueError("wind_mode must be either 'normal' or 'average'")
station['wind_mode'] = config['station']['wind_mode']
+
+ if station['wind_mode'] == "average":
+ station['num_hrs_to_fetch'] = 24
else:
# default to False
station['wind_mode'] = "normal"
# Avoid transforming None values
if element_cd in ['wind_speed', 'WSPD', 'wind_direction',
'RHUM', 'relative_humidity', 'WDIR',
- 'wind_gust', 'SNWD', 'snow_depth']:
+ 'wind_gust', 'SNWD', 'snow_depth',
+ 'hn24']:
infoex['wx_data'][element_cd] = round(infoex['wx_data'][element_cd])
elif element_cd in ['TOBS', 'air_temp', 'PRES', 'pressure']:
infoex['wx_data'][element_cd] = round(infoex['wx_data'][element_cd], 1)
iemap['WDIR'] = 'windDirectionNum'
# unsupported by NRCS:
# windGustSpeedNum
+
+ # NOTE: this doesn't exist in NRCS SNOTEL, we create it in this
+ # program, so add it to the map here
+ iemap['hn24'] = 'hn24Auto'
elif provider == 'mesowest':
iemap['precip_accum'] = 'precipitationGauge'
iemap['air_temp'] = 'tempPres'
iemap['wind_speed'] = 'windSpeedNum'
iemap['wind_direction'] = 'windDirectionNum'
iemap['wind_gust'] = 'windGustSpeedNum'
+
+ # NOTE: this doesn't exist in MesoWest, we create it in this
+ # program, so add it to the map here
+ iemap['hn24'] = 'hn24Auto'
elif provider == 'python':
# we expect Python programs to use the InfoEx data type names
iemap['precipitationGauge'] = 'precipitationGauge'
else:
remote_data[element_cd] = None
+
+ # calc hn24, if applicable
+ hn24 = None
+
+ if station['hn24']:
+ hn24_values = []
+
+ if element_cd == "SNWD":
+ for idx, _ in enumerate(values):
+ val = values[idx]
+ if val is None:
+ continue
+ hn24_values.append(val['value'])
+
+ if len(hn24_values) > 0:
+ # instead of taking MAX - MIN, we want the first
+ # value (most distant) - the last value (most
+ # recent)
+ #
+ # if the result is positive, then we have
+ # settlement; if it's not, then we have HN24
+ hn24 = hn24_values[0] - hn24_values[len(hn24_values)-1]
+
+ if hn24 < 0.0:
+ hn24 = abs(hn24)
+ else:
+ # this case represents HS settlement
+ hn24 = 0.0
+
+ # finally, if user wants hn24 and it's set to None at this
+ # point, then force it to 0.0
+ if hn24 is None:
+ hn24 = 0.0
+
+ if hn24 is not None:
+ remote_data['hn24'] = hn24
+
return remote_data
def get_mesowest_data(begin, end, station):
LOG.error("Bad JSON in MesoWest response: '%s'", exc)
sys.exit(1)
+ # pos represents the last item in the array, aka the most recent
pos = len(observations['date_time']) - 1
+ # while these values only apply in certain cases, init them here
+ wind_speed_values = []
+ wind_gust_speed_values = []
+ wind_direction_values = []
+ hn24_values = []
+
+ # results
+ wind_speed_avg = None
+ wind_gust_speed_avg = None
+ wind_direction_avg = None
+ hn24 = None
+
for element_cd in station['desired_data'].split(','):
# sort and isolate the most recent, see note above in NRCS for how and
# why this is done
key_name = element_cd + '_set_1'
if key_name in observations:
- if observations[key_name][pos]:
- remote_data[element_cd] = observations[key_name][pos]
+ # val is what will make it into the dataset, after
+ # conversions... it gets defined here because in certain
+ # cases we need to look at all of the data to calculate HN24
+ # or wind averages, but for the rest of the data, we only
+ # take the most recent
+ val = None
+
+ # loop through all observations for this key_name
+ # record relevant values for wind averaging or hn24, but
+ # otherwise only persist the data if it's the last datum in
+ # the set
+ for idx, _ in enumerate(observations[key_name]):
+ val = observations[key_name][idx]
+
+ # skip bunk vals
+ if val is None:
+ continue
# mesowest by default provides wind_speed in m/s, but
# we specify 'english' units in the request; either way,
# we want mph
if element_cd in ('wind_speed', 'wind_gust'):
- remote_data[element_cd] = kn_to_mph(remote_data[element_cd])
+ val = kn_to_mph(val)
# mesowest provides HS in mm, not cm; we want cm
if element_cd == 'snow_depth' and station['units'] == 'metric':
- remote_data[element_cd] = mm_to_cm(remote_data[element_cd])
- else:
+ val = mm_to_cm(val)
+
+ # HN24 / wind_mode transformations, once the data has
+ # completed unit conversions
+ if station['wind_mode'] == "average":
+ if element_cd == 'wind_speed' and val is not None:
+ wind_speed_values.append(val)
+ elif element_cd == 'wind_gust' and val is not None:
+ wind_gust_speed_values.append(val)
+ elif element_cd == 'wind_direction' and val is not None:
+ wind_direction_values.append(val)
+
+ if element_cd == 'snow_depth':
+ hn24_values.append(val)
+
+ # again, only persist this datum to the final data if
+ # it's from the most recent date
+ if idx == pos:
+ remote_data[element_cd] = val
+
+ # ensure that the data is filled out
+ if not observations[key_name][pos]:
remote_data[element_cd] = None
else:
remote_data[element_cd] = None
+ if len(hn24_values) > 0:
+ # instead of taking MAX - MIN, we want the first value (most
+ # distant) - the last value (most recent)
+ #
+ # if the result is positive, then we have settlement; if it's not,
+ # then we have HN24
+ hn24 = hn24_values[0] - hn24_values[len(hn24_values)-1]
+
+ if hn24 < 0.0:
+ hn24 = abs(hn24)
+ else:
+ # this case represents HS settlement
+ hn24 = 0.0
+
+
+ # finally, if user wants hn24 and it's set to None at this
+ # point, then force it to 0.0
+ if station['hn24'] and hn24 is None:
+ hn24 = 0.0
+
+ if len(wind_speed_values) > 0:
+ wind_speed_avg = sum(wind_speed_values) / len(wind_speed_values)
+
+ if len(wind_gust_speed_values) > 0:
+ wind_gust_speed_avg = sum(wind_gust_speed_values) / len(wind_gust_speed_values)
+
+ if len(wind_direction_values) > 0:
+ wind_direction_avg = sum(wind_direction_values) / len(wind_direction_values)
+
+ if hn24 is not None:
+ remote_data['hn24'] = hn24
+
+ # overwrite the following with the respective averages, if
+ # applicable
+ if wind_speed_avg is not None:
+ remote_data['wind_speed'] = wind_speed_avg
+
+ if wind_gust_speed_avg is not None:
+ remote_data['wind_gust'] = wind_gust_speed_avg
+
+ if wind_direction_avg is not None:
+ remote_data['wind_direction'] = wind_direction_avg
+
return remote_data
def switch_units_to_metric(data_map, mapping):
end_date = date_time - datetime.timedelta(minutes=date_time.minute % 60,
seconds=date_time.second,
microseconds=date_time.microsecond)
- begin_date = end_date - datetime.timedelta(hours=3)
+ begin_date = end_date - datetime.timedelta(hours=station['num_hrs_to_fetch'])
return (begin_date, end_date)
def f_to_c(f):
wylark / infoex-autowx.git / blobdiff