def load_AWS():
'''Load AWS observations from case study.'''
print('\nimporting AWS observations...')
# Load AWS data
AWS_srs = np.genfromtxt(
'/data/clivarm/wip/ellgil82/AWS/iWS18_SEB_hourly_untilnov17.txt',
names=True)
AWS_srs = pd.DataFrame(
AWS_srs
) # Convert to pandas DataFrame this way because it loads in incorrectly using pd.from_csv
# Calculate date, given list of years and day of year
date_list = compose_date(AWS_srs['year'], days=AWS_srs['day'])
AWS_srs['Date'] = date_list
# Set date as index
AWS_srs.index = AWS_srs['Date']
# Calculate actual time from decimal DOY (seriously, what even IS that format?)
AWS_srs['time'] = 24 * (AWS_srs['Time'] - AWS_srs['day'])
# Trim to case study
print('\nsubsetting for Case Study...')
case = AWS_srs.loc[case_start:case_end]
print('\nconverting times...')
# Convert times so that they can be plotted
time_list = []
for i in case['time']:
hrs = int(i) # will now be 1 (hour)
mins = int((i - hrs) * 60) # will now be 4 minutes
secs = int(0 - hrs * 60 * 60 + mins * 60) # will now be 30
j = datetime.time(hour=hrs, minute=mins)
time_list.append(j)
case['Time'] = time_list
case['datetime'] = case.apply(
lambda r: pd.datetime.combine(r['Date'], r['Time']), 1)
case['E'] = case['LWnet_corr'] + case['SWnet_corr'] + case['Hlat'] + case[
'Hsen'] - case['Gs']
return case
def load_AWS(station):
## --------------------------------------------- SET UP VARIABLES ------------------------------------------------##
## Load data from AWS 14 and AWS 15 for January 2011
print('\nDayum grrrl, you got a sweet AWS...')
if host == 'jasmin':
os.chdir(filepath)
for file in os.listdir(filepath):
if fnmatch.fnmatch(file, '%(station)s*' % locals()):
AWS_srs = pd.read_csv(str(file), na_values=-9999, header=0)
elif host == 'bsl':
os.chdir('/data/clivarm/wip/ellgil82/AWS/')
for file in os.listdir('/data/clivarm/wip/ellgil82/AWS/'):
if fnmatch.fnmatch(file, '%(station)s*' % locals()):
AWS_srs = pd.read_csv(str(file), na_values = -9999, header = 0)
# Calculate date, given list of years and day of year
date_list = compose_date(AWS_srs['year'], days=AWS_srs['day'])
AWS_srs['Date'] = date_list
# Set date as index
AWS_srs.index = AWS_srs['Date']
# Calculate actual time from decimal DOY (seriously, what even IS that format?)
try:
AWS_srs['time'] = 24.*(AWS_srs['Time'] - AWS_srs['day'])
time_list = []
for i in AWS_srs['time']:
hrs = int(i) # will now be 1 (hour)
mins = int((i-hrs)*60) # will now be 4 minutes
secs = int(0 - hrs*60*60 + mins*60) # will now be 30
j = datetime.time(hour = hrs, minute=mins)
time_list.append(j)
AWS_srs['Time'] = time_list
except TypeError:
print('Got time already m9')
AWS_srs['Time'] = pd.to_datetime(AWS_srs['Time'], format='%H:%M:%S').dt.time
print '\nconverting times...'
# Convert times so that they can be plotted
AWS_srs['datetime'] = AWS_srs.apply(lambda r : pd.datetime.combine(r['Date'],r['Time']),1)
try:
AWS_srs['E'] = AWS_srs['LWnet_corr'].values + AWS_srs['SWnet_corr'].values + AWS_srs['Hlat'].values + AWS_srs['Hsen'].values - AWS_srs['Gs'].values
except:
print('No full SEB \'ere pal...')
AWS_srs['WD'][AWS_srs['WD'] < 0.] = np.nan
AWS_srs['FF_10m'][AWS_srs['FF_10m'] < 0.] = np.nan
AWS_srs['WD'] = AWS_srs['WD'].interpolate() # interpolate missing values
AWS_srs['FF_10m'] = AWS_srs['FF_10m'].interpolate()
AWS_srs['WD'][AWS_srs['WD'] == 0.] = np.nan
if station == 'AWS14_SEB_2009-2017_norp':
AWS_srs = AWS_srs.tail(1).append(AWS_srs.iloc[:-1])
# Calculate months
months = [g for n, g in AWS_srs.groupby(pd.TimeGrouper('M'))]
DJF = pd.concat((months[11], months[0], months[1]), axis=0)
MAM = pd.concat((months[2], months[3], months[4]), axis=0)
JJA = pd.concat((months[5], months[6], months[7]), axis=0)
SON = pd.concat((months[8], months[9], months[10]), axis=0)
if host == 'jasmin':
os.chdir('/gws/nopw/j04/bas_climate/users/ellgil82/hindcast/output/alloutput/')
elif host == 'bsl':
os.chdir('/data/mac/ellgil82/hindcast/output/')
return AWS_srs, DJF, MAM, JJA, SON
def load_AWS(station, year):
## --------------------------------------------- SET UP VARIABLES ------------------------------------------------##
## Load data from AWS 14 and AWS 15 for January 2011
print('\nDayum grrrl, you got a sweet AWS...')
if host == 'jasmin':
os.chdir(filepath)
for file in os.listdir(filepath):
if fnmatch.fnmatch(file, '%(station)s*' % locals()):
AWS_srs = pd.read_csv(str(file), na_values=-9999, header=0)
elif host == 'bsl':
os.chdir('/data/clivarm/wip/ellgil82/AWS/')
for file in os.listdir('/data/clivarm/wip/ellgil82/AWS/'):
if fnmatch.fnmatch(file, '%(station)s*' % locals()):
AWS_srs = pd.read_csv(str(file), na_values=-9999, header=0)
# Calculate date, given list of years and day of year
date_list = compose_date(AWS_srs['year'], days=AWS_srs['day'])
AWS_srs['Date'] = date_list
# Set date as index
AWS_srs.index = AWS_srs['Date']
# Calculate actual time from decimal DOY (seriously, what even IS that format?)
try:
AWS_srs['time'] = 24. * (AWS_srs['Time'] - AWS_srs['day'])
time_list = []
case = AWS_srs.loc[year + '-01-01':year +
'-12-31'] # '2015-01-01':'2015-12-31'
for i in case['time']:
hrs = int(i) # will now be 1 (hour)
mins = int((i - hrs) * 60) # will now be 4 minutes
secs = int(0 - hrs * 60 * 60 + mins * 60) # will now be 30
j = datetime.time(hour=hrs, minute=mins)
time_list.append(j)
case['Time'] = time_list
except TypeError:
print('Got time already m9')
AWS_srs['Time'] = pd.to_datetime(AWS_srs['Time'],
format='%H:%M:%S').dt.time
case = AWS_srs.loc[year + '-01-01':year +
'-12-31'] #'2015-01-01':'2015-12-31'
print '\nconverting times...'
# Convert times so that they can be plotted
case['datetime'] = case.apply(
lambda r: pd.datetime.combine(r['Date'], r['Time']), 1)
try:
case['E'] = case['LWnet_corr'].values + case[
'SWnet_corr'].values + case['Hlat'].values + case[
'Hsen'].values - case['Gs'].values
except:
print('No full SEB \'ere pal...')
case['WD'][case['WD'] < 0.] = np.nan
case['FF_10m'][case['FF_10m'] < 0.] = np.nan
case['WD'] = case['WD'].interpolate() # interpolate missing values
case['FF_10m'] = case['FF_10m'].interpolate()
if station == 'AWS14_SEB_2009-2017_norp':
case = case.tail(1).append(case.iloc[:-1])
