"""

created on May 6, 2014

@author: Nikola Jajcay

"""

from src.oscillatory_time_series import OscillatoryTimeSeries

from src.data_class import DataField

from datetime import date, timedelta

import matplotlib.pyplot as plt

import numpy as np

from surrogates.surrogates import SurrogateField

import calendar

ts = OscillatoryTimeSeries('TG_STAID000027.txt', date(1834,7,28), date(2014,1,1), False)

sg = SurrogateField()

g = DataField()

daily_var = np.zeros((365,3))

mean, var_data, trend = ts.g.get_seasonality(True)

sg.copy_field(ts.g)

#MF

sg.construct_multifractal_surrogates()

sg.add_seasonality(mean, var_data, trend)

g.data = sg.surr_data.copy()

g.time = sg.time.copy()

_, var_surr_MF, _ = g.get_seasonality(True)

#FT

sg.construct_fourier_surrogates_spatial()

sg.add_seasonality(mean, var_data, trend)

g.data = sg.surr_data.copy()

g.time = sg.time.copy()

_, var_surr_FT, _ = g.get_seasonality(True)

delta = timedelta(days = 1)

d = date(1895,1,1)

for i in range(daily_var.shape[0]):

ndx = ts.g.find_date_ndx(d)

daily_var[i,0] = var_data[ndx]

daily_var[i,1] = var_surr_MF[ndx]

daily_var[i,2] = var_surr_FT[ndx]

d += delta

p1, = plt.plot(daily_var[:, 0], linewidth = 2, color = '#AEBC76')

p2, = plt.plot(daily_var[:, 1], linewidth = 2, color = '#350E18')

p3, = plt.plot(daily_var[:, 2], linewidth = 2, color = '#8C4E5E')

plt.axis([0, 365, 2, 7])

plt.ylabel('standard deviation in temperature [$^{\circ}$C$^{2}$]')

plt.xlabel('time [months]')

plt.title('STD - data / MF surr / FT surr - %s \n %s -- %s' % (ts.g.location,

str(ts.g.get_date_from_ndx(0)), str(ts.g.get_date_from_ndx(-1))), size = 22)

plt.legend([p1, p2, p3], ('data', 'MF surr', 'FT surr'))

plt.xticks(np.arange(1,365,365/11), calendar.month_name[1:13], rotation = 30)

plt.show()