import rasterio
import numpy
from xml.dom import minidom

from socket import *
from oct2py import octave
from io import BytesIO
import base64
from google.cloud import storage
from oauth2client.service_account import ServiceAccountCredentials
import os
import firebase_admin
from firebase_admin import credentials
from firebase_admin import db
from PIL import Image, ImageFilter
from send_notification import send_notification
from sendemail import sendemail
from sen_start_noti import sen_start_noti
from send_sar_email import send_sar_email
import json
import scipy
import random
import time
import datetime
from merge_sar import merge_sar
from find_sar import find_sar
from merge_dem import merge_dem
from find_dem import find_dem
from scipy import ndimage
from make_bigquery import make_bigquery
from send_moni_noti import send_moni_noti
from send_error_noti import send_error_noti
from gmap_image import gmap_image
from gmap_image_large import gmap_image_large
from datetime import date
from find_img import find_img
from find_img_large import find_img_large
from merge_img import merge_img
from all_proc import all_proc
from contour_images import contour_images
from send_expiring_noti import send_expiring_noti
from send_expired_noti import send_expired_noti
from make_trial_bigquery import make_trial_bigquery
from gen_geotiff import gen_geotiff
from sendgeotifs import sendgeotifs
from gen_report import gen_report
from get_weather_data import get_weather_data
from sendonlyreport import sendonlyreport
from gen_failed_report import gen_failed_report
from sendfailedreport import sendfailedreport
#from search_sentinel import search_sentinel
from map_coords import map_coords
from search_new_sentinel import search_new_sentinel
from convert_to_pdf import convert_to_pdf
from latlon_jp2_to_pixel import latlon_jp2_to_pixel
from gen_geotiff2 import gen_geotiff2
from search_sentinel_again import search_sentinel_again
from get_prev_date import get_prev_date
from make_bigquery_again import make_bigquery_again
import requests
import pdftotree
from convert_to_html import convert_to_html
from map_planet_coords import map_planet_coords
from latlon_tif_to_pixel import latlon_tif_to_pixel
import cv2
from merge_planet_img import merge_planet_img
import csv
import math
today = date.today()
d1 = today.strftime('%Y%m%d')
new_field = 0
print(d1)
aqw2 = 1
cred = credentials.Certificate('servicekey.json')

image_file = "main.tif"

with rasterio.open(image_file) as src:
	band_blue = src.read(1)

with rasterio.open(image_file) as src:
	band_green = src.read(2)
# Load red and NIR bands - note all PlanetScope 4-band images have band order BGRN
with rasterio.open(image_file) as src:
	band_red = src.read(3)

with rasterio.open(image_file) as src:
	band_nir = src.read(4)

with rasterio.open(image_file) as src:
	band_redge = src.read(5)

# Allow division by zero
numpy.seterr(divide='ignore', invalid='ignore')


# Calculate NDVI
ndvi = (band_nir.astype(float) - band_red.astype(float)) / (band_nir + band_red)
ndre = (band_nir.astype(float) - band_redge.astype(float)) / (band_nir + band_redge)
vari = (band_green.astype(float)-band_red.astype(float)/(band_green.astype(float) + band_red.astype(float) - band_blue.astype(float)))
# Set spatial characteristics of the output object to mirror the input
kwargs = src.meta
kwargs.update(
    dtype=rasterio.float32,
    count = 1)


with rasterio.open('band_nir.png', 'w', **kwargs) as dst:
        dst.write(band_nir.astype(rasterio.float32),1)
# Create the file
with rasterio.open('ndvi.tif', 'w', **kwargs) as dst:
        dst.write_band(1, ndvi.astype(rasterio.float32))

with rasterio.open('ndre.tif', 'w', **kwargs) as dst:
        dst.write_band(1, ndre.astype(rasterio.float32))

with rasterio.open('vari.tif', 'w', **kwargs) as dst:
        dst.write_band(1, vari.astype(rasterio.float32))


result_status = octave.drone_index('ndvi')