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02_2_teste_plot.py
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02_2_teste_plot.py
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#BIBLIOTECAS
import os
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import seaborn as sns
import datetime as dt
from dateutil.relativedelta import relativedelta
gbl = globals()
#DEFINICAO PERIODO ANALISE
data_inicial = dt.datetime(2020, 1, 1, 0, 0) #YYYY, M, D, H, Min
data_final = dt.datetime(2020, 12, 31, 23, 59)
# dir_consistencia = "/discolocal/bruno/Observado/Pre_Consistencia"
# os.chdir(dir_consistencia)
dir_dados = '../dados'
os.chdir(dir_dados)
posto_nome = 'Porto_Amazonas'
posto_codigo = '25334953'
serie_completa = pd.read_csv(posto_nome+'FC.csv', sep =';', index_col = 0)
serie_completa.index = pd.to_datetime(serie_completa.index)
serie_interpolada = serie_completa.interpolate()
data_ini = data_inicial
data_fim = data_ini + relativedelta(days=+10)
while data_ini <= data_final:
serie_observada = serie_completa.loc[str(data_ini) : str(data_fim)]
serie_inter = serie_interpolada.loc[str(data_ini) : str(data_fim)]
plt.figure()
plt.plot(serie_inter['h_m'], label = "Falhas", linewidth = 0.6, color = 'red')
plt.plot(serie_observada['h_m'], label = "Observado", linewidth = 0.6, color = 'blue')
plt.title('Serie ' + posto_nome, loc = 'left')
plt.xlabel('Data')
plt.ylabel('Cota [m]')
# Format the date into months & days
plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
# Change the tick interval
plt.gca().xaxis.set_major_locator(mdates.DayLocator(interval=1))
# Puts x-axis labels on an angle
plt.gca().xaxis.set_tick_params(rotation = 30)
# Changes x-axis range
plt.gca().set_xbound(data_ini, data_fim)
data_texto = ('Data inicial: ' + str(data_ini.strftime("%Y-%m-%d")) + '\n' +
'Data final: ' + str(data_fim.strftime("%Y-%m-%d")))
plt.annotate(data_texto, xy=(1,1), xytext=(-4,26), fontsize=10,
xycoords='axes fraction', textcoords='offset points',
bbox=dict(facecolor='white', alpha=0.8),
horizontalalignment='right', verticalalignment='top')
plt.show()
data_ini = data_fim
data_fim = data_ini + relativedelta(days=+10)