import json
import matplotlib.pyplot as plt
import numpy, pandas
import requests
import sys

sst_urls = {
        "world": "https://climatereanalyzer.org/clim/sst_daily/json/oisst2.1_world2_sst_day.json",
        "natlan": "https://climatereanalyzer.org/clim/sst_daily/json/oisst2.1_natlan1_sst_day.json"
        }

print(sys.argv[1])
start_range = 29 
start_year = 1982
res = requests.get(sst_urls[list(sst_urls)[int(sys.argv[1])]])
data = json.loads(res.text)
data = data[1:-3]

temps = numpy.array([i['data'] for i in data], numpy.float32).T 
cols = [i['name'] for i in data] 

df = pandas.DataFrame(temps, columns = cols)
for col in cols:
    if int(col) % 4 != 0:
        df[col].iloc[60:] = df[col].iloc[60:].shift(1)
mean = df[df.columns[:start_range + 1]].mean(axis=1) 
sd = df[df.columns[:start_range + 1]].std(axis=1) 
diffs = pandas.DataFrame(columns = cols, dtype=numpy.float32) 
for col in cols[start_range:]: 
    diffs[col] = (df[col] - mean) / sd 
series = diffs.melt().drop('variable', axis=1).rename(columns={'value': f'sd ({start_year}-{start_year + start_range})'})
series.plot(figsize=(20,5))
plt.xticks(numpy.arange(0,len(series),366)[start_range+1:], (numpy.arange(0, len(series), 366)[start_range+1:] / 366 + start_year).astype(int)) # fix labels
plt.show()