# -*- coding: utf-8 -*-

'''

Programa principal

Compara os dados reprocessados em python com o arquivo Summary (calculado

pela boia) e os do argos (baixados do site)

Henrique P. P. Pereira

LIOc/COPPE/UFRJ

-- Descricao --

Verificar se mesmo com a data baguncada do arquivo Summary

conseguimos coincidir as data utilizando o plot_date, ou

tentando ler os dados e fazer um 'sort'.

Ultima modificacao: 21/01/2015

'''

import numpy as np

from matplotlib import pylab as pl

from datetime import datetime

import os

pl.close('all')

# ============================================================================== #

#Carrega os dados

estado = 'pe'

local1 = 'recife'

local = 'Recife'

id_argos = '69154'

pathname = os.environ['HOME'] + '/Dropbox/pnboia/rot/saida/' + local1 + '/'

#Saida do Python

# 0 1 2 3 4 5 6 7 8

#parametros de onda = [Data,Hs,H10,Hmax,Tmed,THmax,Hm0,Tp,Dp]

py = np.loadtxt(pathname + 'paramwp_8-' + local1 + '.out',delimiter=',',skiprows = 0)

#Saida da Axys

# 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

#YearJulian Date/Zero Crossings/Ave. Ht./Ave. Per./Max Ht./Sig. Wave/Sig. Per./Peak Per.(Tp)/Peak Per.(READ)/HM0/Mean Theta/Sigma Theta/ H1/10 / T.H1/10 /Mean Per.(Tz)

ax = np.loadtxt(pathname + 'Summary_todos.txt',skiprows = 1, usecols = (range(2,18)))

ax_data = np.loadtxt(pathname + 'Summary_todos.txt',dtype = str, skiprows = 1, usecols = (0,1))

#Saida site (baixado em 08/09/2013)

# 0 1 2 3 4 5 6 7 8

# ano mes dia hora minuto Hs Hmax Tp Dirm

site = np.loadtxt(pathname + 'pnboia.B' + id_argos + '_argos.dat',delimiter=',', skiprows = 1, usecols = (2,3,4,5,6,45,46,47,48))

# ============================================================================== #

#cria variaveis de datas

#python

datam_py = []

for i in range(len(py)):

datam_py.append(datetime(int(str(py[i,0])[0:4]),int(str(py[i,0])[4:6]),int(str(py[i,0])[6:8]),int(str(py[i,0])[8:10])))

#deixa datas com numeros inteiros

ano_ax = [int(ax_data[i,0][0:4]) for i in range(len(ax_data))]

mes_ax = [int(ax_data[i,0][5:7]) for i in range(len(ax_data))]

dia_ax = [int(ax_data[i,0][8:10]) for i in range(len(ax_data))]

hora_ax = [int(ax_data[i,1][:2]) for i in range(len(ax_data))]

min_ax = [int(ax_data[i,1][3:]) for i in range(len(ax_data))]

datam_ax = []

for i in range(len(ax_data)):

datam_ax.append(datetime(ano_ax[i],mes_ax[i],dia_ax[i],hora_ax[i],min_ax[i]))

#site

#deixa os valores com -99999 (erro) com nan

for i in range(site.shape[1]):

site[np.where(site[:,i] == -99999),i] = np.nan

ano_st = site[:,0]

mes_st = site[:,1]

dia_st = site[:,2]

hora_st = site[:,3]

min_st = np.zeros(len(site))

datam_st = []

for i in range(len(site)):

datam_st.append(datetime(int(ano_st[i]),int(mes_st[i]),int(dia_st[i]),int(hora_st[i]),int(min_st[i])))

# ============================================================================== #

#Definicao de parametros de onda

#python

hs_py = py[:,1]

h10_py = py[:,2]

hmax_py = py[:,3]

tmed_py = py[:,4]

thmax_py = py[:,5]

hm0_py = py[:,6]

tp_py = py[:,7]

dirtp_py = py[:,8]

#axys

hm0_ax = ax[:,10]

tp_ax = ax[:,8] #qual periodo usar?

tmed_ax = ax[:,15]

th10_ax = ax[:,14]

dirtp_ax = ax[:,11]

hmax_ax = ax[:,5]

hs_ax = ax[:,6]

h10_ax = ax[:,13]

#site

hs_st = site[:,5]

hmax_st = site[:,6]

tp_st = site[:,7]

dirm_st = site[:,8]

# ========================================================================== #

#Correcao dos dados (para facilitar na visualizacao dos graficos

#*pois tem valores de hs de 1200 no site)

hs_st[(np.where(hs_st>30))] = np.nan

# ========================================================================== #

#Graficos

# #hm0

# pl.figure()

# pl.plot_date(datam_py,hm0_py,'bo')

# pl.plot_date(datam_ax,hm0_ax,'go',alpha=0.5)

# pl.title('Hm0 - Rio_Grande_do_Sul')

# pl.ylabel('metros')

# pl.legend(('python','axys'))

# #hs

# pl.figure()

# pl.plot_date(datam_py,hs_py,'bo')

# pl.plot_date(datam_ax,hs_ax,'go',alpha=0.6)

# pl.plot_date(datam_st,hs_st,'ro',alpha=0.5)

# pl.title('Hs - Rio_Grande_do_Sul')

# pl.ylabel('meters')

# pl.legend(('python','axys','site'))

# #h 1/10

# pl.figure()

# pl.plot_date(datam_py,h10_py,'bo')

# pl.plot_date(datam_ax,h10_ax,'go',alpha=0.5)

# pl.title('H 1/10 - Rio_Grande_do_Sul')

# pl.ylabel('metros')

# pl.legend(('python','axys'))

# #hmax

# pl.figure()

# pl.plot_date(datam_py,hmax_py,'bo')

# pl.plot_date(datam_ax,hmax_ax,'go',alpha=0.6)

# pl.plot_date(datam_st,hmax_st,'ro',alpha=0.5)

# pl.ylabel('metros')

# pl.title('Hmax - Rio_Grande_do_Sul')

# pl.legend(('python','axys','site'))

# #tp

# pl.figure()

# pl.plot_date(datam_py,tp_py,'bo')

# pl.plot_date(datam_ax,tp_ax,'go',alpha=0.6)

# pl.plot_date(datam_st,tp_st,'ro',alpha=0.5)

# pl.ylabel('segundos')

# pl.title('Tp - Rio_Grande_do_Sul')

# pl.legend(('python','axys','site'))

# #tmed

# pl.figure()

# pl.plot_date(datam_py,tmed_py,'bo')

# pl.plot_date(datam_ax,tmed_ax,'go',alpha=0.5)

# pl.title('tmed')

# pl.legend(('python','axys'))

# #t hmax

# pl.figure()

# pl.plot_date(datam_py,thmax_py,'bo')

# pl.plot_date(datam_ax,th10_ax,'go',alpha=0.6)

# pl.title('t hmax')

# pl.legend(('python','axys'))

# #dirtp

# pl.figure()

# pl.plot_date(datam_py,dirtp_py,'bo')

# pl.plot_date(datam_ax,dirtp_ax,'go',alpha=0.6)

# pl.plot_date(datam_st,dirm_st,'ro',alpha=0.5)

# pl.title('Dirtp - Rio_Grande_do_Sul')

# pl.ylabel('graus')

# pl.legend(('python','axys','site'))

#subplot do periodo de dez 09

pl.figure()

pl.subplot(3,1,1)

pl.plot_date(datam_py,hs_py,'bo')

pl.plot_date(datam_ax,hs_ax,'go',alpha=0.6)

pl.plot_date(datam_st,hs_st,'ro',alpha=0.5)

pl.axis([datam_py[0],datam_py[-1],0,10])

pl.title(local)

pl.ylabel('Hs - metros')

pl.legend(('lioc','axys','site'))

pl.xticks(rotation=70)

pl.subplot(3,1,2)

pl.plot_date(datam_py,tp_py,'bo')

pl.plot_date(datam_ax,tp_ax,'go',alpha=0.6)

pl.plot_date(datam_st,tp_st,'ro',alpha=0.5)

pl.axis([datam_py[0],datam_py[-1],0,20])

pl.ylabel('Tp - segundos')

# pl.legend(('lioc','axys','site'))

pl.subplot(3,1,3)

pl.plot_date(datam_py,dirtp_py,'bo')

pl.plot_date(datam_ax,dirtp_ax,'go',alpha=0.6)

pl.plot_date(datam_st,dirm_st,'ro',alpha=0.5)

pl.axis([datam_py[0],datam_py[-1],0,360])

pl.ylabel('Dp - graus')

# pl.legend(('lioc','axys','site'))

pl.show()