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

'''
Author: Sebastian Cajas

We recommend to use eo-learn for more complex cases where you need multiple timestamps or high-resolution data for larger areas.
https://github.com/sentinel-hub/eo-learn

!pip install epiweeks


'''

from sentinelhub import SHConfig
import os
import datetime
import numpy as np
import matplotlib.pyplot as plt
import sys
from datetime import timedelta
sys.path.insert(0,'..') 
from sentinelhub import MimeType, CRS, BBox, SentinelHubRequest, SentinelHubDownloadClient, DataCollection, bbox_to_dimensions, DownloadRequest
#from rename_linux import *
from epiweeks import Week, Year
from datetime import date
import glob, shutil

def cleaners(dataset, root_images):
    for root, dirs, files in os.walk(dataset, topdown=True):
        for name in files:
             path = os.path.join(root, name)
             if ".tiff" in path:
                    os.remove(path)
                    
    
    return print("Ready")

def get_epi_weeks(start):
    

    tdelta =  timedelta(days = 7)

    
    edges = [(start + i*tdelta) for i in range(2)]
    
    
    return [(edges[i], edges[i+1]) for i in range(len(edges)-1)]
    

def plot_image(image, factor=1.0, clip_range = None, **kwargs):
    """
    Utility function for plotting RGB images.
    """
    fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(15, 15))
    if clip_range is not None:
        ax.imshow(np.clip(image * factor, *clip_range), **kwargs)
    else:
        ax.imshow(image * factor, **kwargs)
    ax.set_xticks([])
    ax.set_yticks([])

def download_multiple_images(coordinates, start, year, CLIENT_ID, CLIENT_SECRET):

    # put here your credentials
    CLIENT_ID = CLIENT_ID
    CLIENT_SECRET = CLIENT_SECRET

    config = SHConfig()

    if CLIENT_ID and CLIENT_SECRET:
        config.sh_client_id = CLIENT_ID
        config.sh_client_secret=CLIENT_SECRET
    
    if not config.sh_client_id or not config.sh_client_secret:
        print("Warning! To use Process API, please provide the credentials (OAuth client ID and client secret).")

    resolution = 10
    bbox = BBox(bbox=coordinates, crs=CRS.WGS84)
    bbox_size = bbox_to_dimensions(bbox, resolution=resolution)

    #print(f'Image shape at {resolution} m resolution: {bbox_size} pixels')

    slots = get_epi_weeks(start)
    
    # Visualization purposes
    d_init = slots[0][0].strftime('%m/%d/%Y')
    d_end  = slots[0][1].strftime('%m/%d/%Y')
    print(f"Requested week slot: {d_init} - {d_end} ")


    script_Medellin = """

        //VERSION=3
        function setup() {
          return {
            input: [{
              bands: ["B01", "B02", "B03", "B04", "B05", "B06", "B07", "B08", "B8A", "B09", "B10", "B11", "B12"],
              units: "DN"
            }],
            output: {
              id: "default",
              bands: 12,
              sampleType: SampleType.UINT16
            }
          }
        }

        function evaluatePixel(sample) {
            return [ sample.B01, sample.B02, sample.B03, sample.B04, sample.B05, sample.B06, sample.B07, sample.B08, sample.B8A, sample.B09, sample.B10, sample.B11, sample.B12]
        }
    """
    

    '''Check if directory exists, if not, create it'''
    
    # You should change 'test' to your preferred folder.
    # If folder doesn't exist, then create it.
    
    # if windows: 
    path = os.path.abspath(os.getcwd()) + "//data"  + "//" + year
    # if linux: path = os.path.abspath(os.getcwd()) + "/data"  + "/" year
    
    if not os.path.isdir(path):
        os.makedirs(path)
        #print("created folder : ", path)
    else:
        #print(path, "Folder already exists. Rewriting*")
        pass
    
    def get_true_color_request(time_interval):
        return SentinelHubRequest(
            data_folder= 'data' + "/" + year,
            evalscript=script_Medellin,
            input_data=[
                SentinelHubRequest.input_data(
                    data_collection=DataCollection.SENTINEL2_L1C,
                    #time_interval=('2015-11-1', '2015-11-20'), #time_interval,
                    time_interval=time_interval,
                    mosaicking_order='leastCC'
                )
            ],
            responses=[
                SentinelHubRequest.output_response('default', MimeType.TIFF)
            ],
            bbox=bbox,
            size=bbox_size,
            config=config
        )

    # create a list of requests
    list_of_requests = [get_true_color_request(slot) for slot in slots]
    list_of_requests = [request.download_list[0] for request in list_of_requests]

    image = SentinelHubDownloadClient(config=config).download(list_of_requests, max_threads=5)
    print("Ended downloading")

    # Verify if images are empty, if not, correct
    img = np.array(image)
    #with open('readme.txt', 'w') as f:
    #  f.write(img.shape)
      
    print(img.shape)
    print(img.max())
    
    # Verify if images are empty, if not, correct
    if img.sum() == 0:
        print("Image empty: ", img.sum())
        # Initialize  
        end = slots[0][1]
        # Add delay by 1 day step
        while img.sum() == 0: # tune
            tdelta =  timedelta(days = 1)
            init =  slots[0][0]
            end = end + tdelta
            corrected_slot =  [(init, end)]
            #print("Slot corrected to: ", corrected_slot)
            list_of_requests = [get_true_color_request(slot) for slot in corrected_slot]
                
            list_of_requests = [request.download_list[0] for request in list_of_requests]
            image = SentinelHubDownloadClient(config=config).download(list_of_requests, max_threads=5)
            img = np.array(image)
            print("This image is being replaced..")
        print("Slot corrected to: ", corrected_slot)
        
        
    else:
        print(f"Pixel values: ", np.unique(img))
        pass

    '''
    # Remove extra dimension
    img = np.squeeze(image, axis = 0)
   
    ncols = 4
    nrows = 3

    aspect_ratio = bbox_size[0] / bbox_size[1]
    subplot_kw = {'xticks': [], 'yticks': [], 'frame_on': False}

    plot_image(img[:,:,1], factor=1.0, cmap=plt.cm.Greys_r, vmin=0, vmax=120)
    '''
    return img

def get_folder_ID(root_images, img_format):
    
    walker = "." + root_images
            
    for root, dirs, files in os.walk(walker, topdown=True):
        for name in files:
            path = os.path.join(root, name)
            if "response" in path:
                        
                folder_path = path.replace("/" + "response." + img_format, "")

    return folder_path