"""Plot glacier-area weighted Alps temperature anomalies (vs 1961-1990).

Reads ``series/tas_<season>_anom_1961-1990.csv`` (run regional.py first).
Thin lines: annual values; thick lines: centered running mean, drawn only
where at least min_window years are available (default: the full window, so
the line stops window // 2 years before the ends of each series).

Usage: python plot_tas_anomaly.py [annual|jjas] [start_year] [window]
                                  [min_window]
       (defaults: annual 1700 11 11)
"""
import os
import sys

import matplotlib.pyplot as plt
import pandas as pd

HERE = os.path.dirname(os.path.abspath(__file__))

LABELS = {'lmr_v2.1': 'LMR v2.1', 'lmr_seas': 'LMR Seasonal',
          'berkeley-earth': 'Berkeley Earth',
          'histalp': 'HISTALP', 'gswp3-w5e5': 'GSWP3-W5E5',
          'cru': 'CRU TS 4.04'}
COLORS = {'lmr_v2.1': '#2a78d6', 'lmr_seas': '#4a3aa7',
          'berkeley-earth': '#eb6834',
          'histalp': '#1baf7a', 'gswp3-w5e5': '#eda100', 'cru': '#e87ba4'}

season = sys.argv[1] if len(sys.argv) > 1 else 'annual'
start = int(sys.argv[2]) if len(sys.argv) > 2 else 1700
window = int(sys.argv[3]) if len(sys.argv) > 3 else 11
min_window = int(sys.argv[4]) if len(sys.argv) > 4 else window

df = pd.read_csv(os.path.join(HERE, 'series',
                              f'tas_{season}_anom_1961-1990.csv'),
                 index_col=0)

fig, ax = plt.subplots(figsize=(11, 6.5))
ax.axhline(0, color='#52514e', lw=0.8)
ax.axvspan(1961, 1990, color='#d0cfc8', alpha=0.35, lw=0)
ax.axvline(1850, color='k', lw=1)
for name in df.columns:
    s = df[name].dropna()
    # reindex so that missing years (e.g. BE 1752) break the line
    s = s.reindex(range(s.index[0], s.index[-1] + 1))
    c = COLORS[name]
    # LMR Seasonal has no September: its summer is JJA
    jja = ', JJA' if (name == 'lmr_seas' and season == 'jjas') else ''
    # single missing years (BE 1752) are interpolated for the running mean
    # only, and it is computed before cutting at the start year
    sm = s.interpolate(limit=1, limit_area='inside').rolling(
        window, center=True, min_periods=min_window).mean().loc[start:]
    s = s.loc[start:]
    ax.plot(s.index, s, color=c, lw=0.6, alpha=0.4)
    ax.plot(sm.index, sm, color=c, lw=2,
            label=f'{LABELS[name]}{jja} ({s.dropna().index[0]}–'
                  f'{s.dropna().index[-1]})')

ax.set_xlim(start, df.index[-1] + 2)
ax.set_ylabel('Temperature anomaly vs 1961–1990 (K)')
what = 'Annual' if season == 'annual' else season.upper()
ax.set_title(f'{what} temperature, glacier-area weighted over the Alps '
             f'(RGI6.2 11-01). Thin: yearly, thick: {window}-yr running mean',
             loc='left', fontsize=11)
ax.grid(axis='y', color='#e6e5e0', lw=0.6)
for sp in ['top', 'right']:
    ax.spines[sp].set_visible(False)
ax.legend(frameon=False, loc='upper left', fontsize=9)
fig.tight_layout()
os.makedirs(os.path.join(HERE, 'figs'), exist_ok=True)
f = os.path.join(HERE, 'figs', f'tas_{season}_anom_{start}.png')
fig.savefig(f, dpi=150)
print(f)