nroll = 7
tseries = utils.get_mfc_box(mfcfiles, precipfiles, None, years, nroll, lat1, lat2,
lon1, lon2)
# Monsoon onset day and index timeseries
if onset_nm.startswith('CHP'):
# Use precip/MFC already loaded
data = tseries[onset_nm.split('_')[1] + '_ACC']
else:
data = None
index = utils.get_onset_indices(onset_nm, indfiles[onset_nm], years, data)
onset, retreat, length = index['onset'], index['retreat'], index['length']
tseries[onset_nm] = index['tseries']
# ENSO
enso = utils.get_enso_indices(years)
enso = xray.DataArray(enso[enso_nm]).rename({'Year' : 'year'})
# ----------------------------------------------------------------------
# Climatology
index_clim = index.mean(dim='year')
tseries_clim = tseries.mean(dim='year')
enso_clim = enso.mean(dim='year').values
# Tile the climatology to each year for plot_tseries_together
vals = atm.biggify(tseries_clim[onset_nm], index['tseries'].values, tile=True)
_, _, coords, dims = atm.meta(index['tseries'])
ts_clim = xray.DataArray(vals, name=tseries_clim[onset_nm].name, coords=coords,
dims=dims)
tseries[onset_nm + '_clim'] = ts_clim
nroll, lat1, lat2, lon1, lon2)
# Monsoon onset/retreat indices
if onset_nm.startswith('CHP'):
# --- Use precip/MFC already loaded
data = tseries[onset_nm.split('_')[1] + '_ACC']
files = None
else:
data = None
files = datafiles[onset_nm]
index = utils.get_onset_indices(onset_nm, files, years, data)
index = index[['onset', 'retreat']].to_dataframe()
index['length'] = index['retreat'] - index['onset']
# ENSO
enso = utils.get_enso_indices(years, enso_keys)
# Monsoon strength
mfc = tseries['MFC_UNSM']
precip = tseries['PCP_UNSM']
ssn = utils.get_strength_indices(years, tseries['MFC_UNSM'],
tseries['PCP_UNSM'], index['onset'],
index['retreat'])
# ----------------------------------------------------------------------
# Helper functions
def detrend(df):
df_detrend = df.copy()
x = df.index.values
for col in df.columns:
