from tempfile import tempdir
from unittest.mock import sentinel
import firebase_admin
from firebase_admin import credentials
from firebase_admin import db
from find_s1_image2 import find_img_value
import pandas as pd
import statsmodels.api as sm
import seaborn as sns
sns.set()
import time
import json
import numpy as np
from sklearn.cluster import KMeans
from find_study_area_values import find_study_area_values
from make_area_estimate_image import make_area_estimate_image
import json
from sentinelhub import WebFeatureService, BBox, CRS, DataSource, MimeType, CRS, BBox, WmsRequest,DataCollection
cred = credentials.Certificate('servicekey.json')
x = 0.0003
y = 0.0003
fromdate = '20220701'
todate = '20220715'

s1_images = ['IW-VH-DB']

s1_images = ['B01']
s2_images = []
# s1_images = ["B02", "B03", "B04", "B05"]
#s2_images = ["RVI-NEW"]
try:
    firebase_admin.initialize_app(cred, {'databaseURL': 'https://farmbase-b2f7e-31c0c.firebaseio.com/'})
except:
    print('fire running')

study_uid = "vPM6EKWHfHRxmRfc0YJ7PZ8J9tR2"
gt_uid = ['u5ZgAskSltX7dQdNFUlHsgVhAlf2', 'b2j92LjidjeGt2b60QHhSj4GeS63', 'hSoBF0u61YfFeBFzcjhUFU3dh0e2','0AC0f8JWjUdg9fCm7f8QbXZTOp23']
different_gt_uid = 'hxA3VYEFpaOluurIbHxdzd4gPlw1'
study_field_id = '1662365839021'
gt_fields = {}
for temp_id in gt_uid:
    temp_gt_fields = db.reference('PaidMonitoredFields').child('PMF').child(temp_id).get()
    for(p,q) in temp_gt_fields.items():
        gt_fields[p] = q
#gt_fields = db.reference('PaidMonitoredFields').child('PMF').child(gt_uid).get()
different_gt_fields = db.reference('PaidMonitoredFields').child('PMF').child(different_gt_uid).get()

study_fields = db.reference('PaidMonitoredFields').child('PMF').child(study_uid).get()
for (p,q) in study_fields.items():
  study_field = q

x = 0.0003
y = 0.0003


sentinelSettings = db.reference('SentinelSettings').get()
clientID = sentinelSettings["ClientID"]
clientSecret = sentinelSettings["ClientSecret"]
wmsID = sentinelSettings["WMSID"]
rviID = sentinelSettings["RVIID"]
demID = sentinelSettings["DEMID"]
modisID = sentinelSettings["MODISID"]
field_num = 0
from_date = '2022-06-25T00:00:00'
to_date = '2022-09-17T23:59:59'
max_num = 7

def append_img_vals(temp_arr, img_values):
    if temp_arr is not None:
        for k in temp_arr:
            img_values.append(k)
    return img_values


all_fields_img_values = []
gt_fields_img_values = []
i = 0

i = 0
labels = []
for (fieldid, fieldobj) in gt_fields.items():
    if i < 150:
        img_values = []
        midlat = (float(fieldobj["FieldMinLat"]) + float(fieldobj["FieldMaxLat"]))/2
        midlng = (float(fieldobj["FieldMinLong"]) + float(fieldobj["FieldMaxLong"]))/2
        bounds = [(midlng-y),(midlat-x),(midlng+y),(midlat+x)]
        print(bounds)
        image_num = 0
        for image in s2_images:
            temp_arr = find_img_value(fieldid,DataCollection.SENTINEL2_L1C,image, bounds, from_date, to_date, clientID, clientSecret, wmsID, max_num)
            img_values = append_img_vals(temp_arr, img_values)
        for image in s1_images:
            temp_arr = find_img_value(fieldid,DataCollection.MODIS, image, bounds, from_date, to_date, clientID, clientSecret, modisID, max_num)
            img_values = append_img_vals(temp_arr, img_values)
        if len(img_values) > 0:
            print(i)
            all_fields_img_values.append(img_values)
            gt_fields_img_values.append(img_values)
            labels.append(10)
        i = i+1
    else:
        break

i = 0
for (fieldid, fieldobj) in different_gt_fields.items():
    if i < 40:
        img_values = []
        midlat = (float(fieldobj["FieldMinLat"]) + float(fieldobj["FieldMaxLat"]))/2
        midlng = (float(fieldobj["FieldMinLong"]) + float(fieldobj["FieldMaxLong"]))/2
        bounds = [(midlng-y),(midlat-x),(midlng+y),(midlat+x)]
        print(bounds)
        image_num = 0
        for image in s2_images:
            temp_arr = find_img_value(fieldid,DataCollection.SENTINEL2_L1C,image, bounds, from_date, to_date, clientID, clientSecret, wmsID, max_num)
            img_values = append_img_vals(temp_arr, img_values)
        for image in s1_images:
            temp_arr = find_img_value(fieldid, DataCollection.MODIS, image, bounds, from_date, to_date, clientID, clientSecret, modisID, max_num)
            img_values = append_img_vals(temp_arr, img_values)
        if len(img_values) > 0:
            print(i)
            all_fields_img_values.append(img_values)
            labels.append(-1)
        i = i+1
    else:
        break


print(all_fields_img_values)
print(gt_fields_img_values)
np.savetxt("modis_paddy_all_field_img_values.csv", all_fields_img_values, delimiter = ",")
np.savetxt("modis_paddy_gt_field_img_values.csv", gt_fields_img_values, delimiter = ",")

np.savetxt("modis_paddy_all_field_labels.csv", labels, delimiter = ",")