comp_yrs[key1], comp_yrs[key2] = lowest_highest(enso, nyrs)
atm.print_odict(comp_yrs)


# ======================================================================
# PLOTS
# ======================================================================

# ----------------------------------------------------------------------
if plot_all_years:
    # --- Daily timeseries plots together (day of year)
    style = {onset_nm : 'k', onset_nm + '_clim' : 'k--', 'MFC' : 'b'}
    onset_style = {onset_nm : 'k'}
    d_onset = {onset_nm : onset.values}
    keys = [onset_nm, onset_nm + '_clim', 'MFC']
    indices.plot_tseries_together(tseries[keys], onset=d_onset, data_style=style,
                                  onset_style=onset_style, show_days=True)

    # --- Daily timeseries composites relative to onset day - clim +/- 1 stdev
    keys = [onset_nm, 'MFC']
    npre, npost = 30, 90
    ts_rel = xray.Dataset()
    for key in keys:
        ts_rel[key] = daily_rel2onset(tseries[key], onset, npre, npost,
                                           yearnm='year', daynm='day')
    dayrel = ts_rel['dayrel'].values

    offset, factor = {}, {}
    for key in keys:
        offset[key] = -np.nanmean(tseries[key].values.ravel())
        factor[key] = np.nanstd(tseries[key].values.ravel())
# The north region should go up to 35 N but there is some weirdness
# with the topography so I'm setting it to 30 N for now
north=(5, 30, 40, 100)
south=(-15, 5, 40, 100)
suptitle = varname + ' N=%s S=%s' % (str(north), str(south))
tt = onset_TT(T, north=north, south=south)

# Some weirdness going on in 1991, for now just set to NaN
# Troubleshoot later
for nm in ['ttn', 'tts', 'tseries']:
    vals = tt[nm].values
    vals = np.ma.masked_array(vals, abs(vals) > 1e30).filled(np.nan)
    tt[nm].values = vals

# Plot TTN and TTS
plot_tseries_together(tt[['ttn', 'tts']], tt['onset'].values,
                      suptitle=suptitle, standardize=False)

# Summary plot and timeseries in individual years
summarize_indices(years, tt['onset'])
plt.suptitle(suptitle)
plot_index_years(tt, suptitle=suptitle, yearnm='year', daynm='day')

if save:
    atm.savefigs(varname + '_', 'png')

# Plot contour map of pressure-level data
p_plot = 400
T_plot = T_p[p_plot]
y, d = 0, 80
lat = atm.get_coord(T_plot, 'lat')
lon = atm.get_coord(T_plot, 'lon')