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Commit 734b0d4e authored by Jeremy Commins's avatar Jeremy Commins
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Removed dev folder.

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# -*- coding: utf-8 -*-
import pandas as pd
from sen2chain import Automatization
from sen2chain.automatization import TimeSeriesAutomatization
#tsauto = TimeSeriesAutomatization()
#tsauto.run()
auto = Automatization()
print(auto.data)
auto.run()
# -*- coding: utf-8 -*-
"""
Module for downloading and processing Sentinel-2 images in parallel.
"""
import logging
import asyncio
import random
import time
import functools
import subprocess
import shutil
from pathlib import Path
from datetime import datetime
from concurrent.futures import ThreadPoolExecutor, ProcessPoolExecutor, as_completed
from collections import OrderedDict, defaultdict
from sentinelsat import SentinelAPI
from sentinelhub import AwsProductRequest
from pprint import pprint
# type annotations
from typing import List, Set, Dict, Tuple, Optional
from sen2chain import Config, DataRequest
from sen2chain.config import SHARED_DATA
from sen2chain.library import TempContainer
from sen2chain.products import L1cProduct, L2aProduct
peps_download_script = SHARED_DATA.get("peps_download")
peps_download_config = Path(Config().get("peps_config_path"))
logger = logging.getLogger(__name__)
logging.basicConfig(level=logging.DEBUG)
def download_aws(identifier: str, tile: str, hub: str) -> Tuple[str, bool]:
"""Downloads L1C safe from AWS using sentinelhub package.
:param identifier:
:param tile:
:param hub:
"""
logger.debug("download_aws {}".format(identifier))
temp_container = TempContainer(identifier, tile)
temp_container.create_temp_folder()
downloaded = True
if not temp_container.l1c.path.exists() and not temp_container.l1c.in_library:
product_request = AwsProductRequest(product_id=identifier,
tile_list=["T"+tile],
data_folder=str(temp_container.temp_path),
safe_format=True)
product_request.save_data()
archive_l1c(identifier, tile, hub)
if not temp_container.l1c.path.exists():
downloaded = False
return (identifier, hub)
def download_peps(identifier: str, tile: str, hub: str) -> Tuple[str, str, str, bool]:
"""Downloads L1C safe zip file from PEPS using peps_downloader.py.
:param identifier:
:param tile:
:param hub:
"""
logger.debug("download_peps {}".format(identifier))
temp_container = TempContainer(identifier, tile)
temp_container.create_temp_folder()
downloaded = True
if not temp_container.l1c.path.exists() and not temp_container.l1c.in_library:
try:
command = "python3 {peps_download_script} -a {peps_download_config} -c S2ST -i {identifier}".format(
peps_download_script=peps_download_script,
peps_download_config=str(peps_download_config),
identifier=identifier)
process = subprocess.run(command.split(), cwd=str(temp_container.temp_path), check=True, stderr=subprocess.PIPE)
except subprocess.CalledProcessError as e:
logger.error("download_peps - peps_download FAILED: {}".format(e))
logger.warning("File does not exist on PEPS yet: {}".format(identifier))
try:
temp_container.unzip_l1c()
#archive_l1c(identifier, tile, hub)
except:
pass
if not temp_container.l1c.path.exists():
downloaded = False
logger.info("Failed download: {}".format(identifier))
return (identifier, tile, hub, downloaded)
def download_scihub(identifier: str, tile: str, hub: str) -> Tuple[str, str, str, bool]:
"""Downloads L1C safe zip file from Scihub using sentinelsat package.
:param identifier:
:param tile:
:param hub:
"""
logger.debug("download_scihub {}".format(identifier))
temp_container = TempContainer(identifier, tile)
temp_container.create_temp_folder()
downloaded = True
if not temp_container.l1c.path.exists() and not temp_container.l1c.in_library:
api = SentinelAPI(Config().get("scihub_id"), Config().get("scihub_pwd"))
product_request = api.query(identifier='*{}*'.format(identifier))
api.download_all(product_request, directory_path=str(temp_container.temp_path))
try:
temp_container.unzip_l1c()
#archive_l1c(identifier, tile, hub)
except:
#temp_container.delete_temp_folder()
downloaded = False
logger.info("Failed download: {}".format(identifier))
return (identifier, tile, hub, downloaded)
def processing(identifier: str, tile: str, hub: str, indices_list: List[str],
nodata_clouds: bool, quicklook: bool) -> Tuple[str, str, str]:
"""Process each L1C downloaded.
:tile:
:hub:
:indices_list:
:nodata_clouds:
:quicklook:
"""
logger.debug("processing {}".format(identifier))
l1c_product = L1cProduct(identifier, tile)
l1c_product.process_l2a()
l2a_identifier = identifier.replace("L1C_","L2A_").replace("_USER_", "_OPER_")
l2a_product = L2aProduct(l2a_identifier, tile)
l2a_product.process_cloud_mask()
l2a_product.process_indices(indices_list, nodata_clouds, quicklook)
return (identifier, tile, hub)
def archive_l1c(identifier, tile, hub):
"""
"""
temp = TempContainer(identifier)
l1c_prod = L1cProduct(identifier, tile, path=temp.temp_path)
l1c_prod.archive()
temp.delete_temp_folder()
return (identifier, tile, hub)
class DownloadAndProcess:
"""Class for downloading and processing products from :class:`data_request.DataRequest`.
:param identifiers: a dictionnary containing products identifiers as keys.
:param hubs_limit: hub name as key, max of downloading threads as value.
:param aws_limit: max of downloading threads.
:param process_products: process products after download.
:param max_processes: number of parallel processes.
:param indices_list: list of valid indices names that will be processed.
:param nodata_clouds: mask indices output rasters with a cloud-mask.
:param quicklook: creates a quicklook for each indice processed.
"""
def __init__(self, identifiers: str,
hubs_limit: dict = None, aws_limit: int = None,
process_products: bool = False, max_processes: int = 2, indices_list: list = [],
nodata_clouds: bool = False, quicklook: bool = False) -> None:
if not isinstance(identifiers, dict):
raise ValueError("identifiers needs to be a dict")
else:
self.identifiers = identifiers
if hubs_limit is None:
self.hubs_limit={"peps":3, "scihub":2}
logger.debug("hubs_limit set to: {}".format(self.hubs_limit))
else:
self.hubs_limit = hubs_limit
if aws_limit is None:
self.aws_limit = 3
logger.debug("aws_limit set to: {}".format(self.aws_limit))
else:
if aws_limit > 3:
self.aws_limit = 3
logger.warning("aws limit too high, using default: {}".format(self.aws_limit))
if not isinstance(process_products, bool):
raise ValueError("process_product must be either True or False")
else:
self.process_products = process_products
if max_processes >= 1:
self.max_processes = max_processes + 1 # + 1 pour process principal
if max_processes > 2:
logger.warning("max_processes set to: {}, don't run out of memory!".format(max_processes))
else:
raise ValueError("max_processes must be an unsigned number > 0.")
if indices_list is None:
self.indices_list = []
else:
if not isinstance(indices_list, list):
raise ValueError("indices_list must be a list of indices names")
self.indices_list = indices_list
if not isinstance(nodata_clouds, bool):
raise ValueError("nodata_clouds must be either True or False")
else:
self.nodata_clouds = nodata_clouds
if not isinstance(quicklook, bool):
raise ValueError("quicklook must be either True or False")
else:
self.quicklook = quicklook
self.loop = asyncio.get_event_loop()
self.queue = asyncio.Queue()
# executors
self.threads_executor = ThreadPoolExecutor(
max_workers=sum(self.hubs_limit.values())
)
self.processes_executor = ProcessPoolExecutor(
max_workers=self.max_processes
) if self.process_products else None
# failed downloads
self._products_attempts = defaultdict(lambda: 0)
self.failed_products = set()
# run main coroutine
self.run_loop()
async def proxy_pool(self, hub: str, limit: int) -> None:
"""
gestionnaire de "proxies" : permet de switcher entre peps et scihub
de façon à ce que les éléments de la queue soient traités le plus
rapidement possible
:param hub:
:param limit:
"""
logger.debug("proxy_pool")
tasks = []
while self.queue.qsize() > 0:
logger.debug("while True")
while len(tasks) < limit and self.queue.qsize() > 0:
logger.debug("tasks < limit")
item = await self.queue.get()
tile = self.identifiers["hubs"][item]["tile"]
task = asyncio.ensure_future(self.downloader_hubs(item, tile, hub))
tasks.append(task)
done, pending = await asyncio.wait(tasks,
return_when=asyncio.FIRST_COMPLETED)
for each in done:
tasks.remove(each)
if self.queue.empty():
logger.debug("queue empty")
if tasks:
await asyncio.gather(*tasks)
return
async def downloader_hubs(self,
identifier: str, tile: str, hub: str) -> Tuple[str, str, str]:
"""Coroutine for starting
coroutine de téléchargement sur peps et scihub : appelle la fonction qui va télécharger
"""
if hub == "scihub":
logger.info("--> downloading {} from {}".format(identifier, hub))
fut = self.loop.run_in_executor(self.threads_executor,
functools.partial(download_scihub,
identifier,
tile,
hub))
elif hub == "peps":
logger.info("--> downloading {} from {}".format(identifier, hub))
fut = self.loop.run_in_executor(self.threads_executor,
functools.partial(download_peps,
identifier,
tile,
hub))
await fut
# if download was successful, process the file
if fut.result()[3]:
logger.info("--> --> {} downloaded from {}".format(identifier, hub))
arch = asyncio.ensure_future(self.archive_l1c(identifier, tile, hub))
await arch
if self.process_products:
fut = asyncio.ensure_future(self.process(identifier, tile, hub))
await fut
# if download failed, try again on another hub if first retry
elif not fut.result()[3] and self._products_attempts[identifier] < 3:
self._products_attempts[identifier] += 1
logger.info("{} download failed, will try again".format(identifier))
# increase the number of seconds to wait with the number of attempts
# will retry in 2, 4 then 6 minutes before giving up
seconds_to_wait = self._products_attempts[identifier] * 120
await asyncio.sleep(seconds_to_wait)
await self.queue.put(identifier)
# if the download failed again, return without processing
else:
self.failed_products.add(identifier)
logger.error("Download failed: {}".format(identifier))
return (identifier, tile, hub)
async def downloader_aws(self,
identifier: str, tile: str, hub: str) -> Tuple[str, str, str]:
"""coroutine appelant la coroutine de téléchargement sur aws
"""
logger.debug("downloader_aws {}".format(identifier))
async with asyncio.Semaphore(self.aws_limit):
fut = self.loop.run_in_executor(self.threads_executor,
functools.partial(download_aws,
identifier,
tile,
hub))
await fut
logger.info("--> --> {} downloaded from {}".format(identifier, hub))
return (identifier, tile, hub)
async def archive_l1c(self,
identifier: str, tile: str, hub: str) -> Tuple[str, str, str]:
"""
"""
#fut = self.loop.run_in_executor(self.processes_executor,
fut = self.loop.run_in_executor(None,
functools.partial(archive_l1c,
identifier,
tile,
hub))
if fut.cancelled:
return fut
await fut
logger.info("--> --> --> --> {} archived".format(identifier, hub))
return (identifier, tile, hub)
async def process(self,
identifier: str, tile: str, hub: str) -> Tuple[str, str, str]:
"""
coroutine qui va appeler la fonction permettant de traiter le fichier pour scihub et peps
:param identifier:
:param tile:
:param hub:
"""
logger.debug("process {}".format(identifier))
#async with asyncio.Semaphore(self.max_processes):
logger.info("--> --> --> processing {}".format(identifier))
fut = self.loop.run_in_executor(self.processes_executor,
functools.partial(processing,
identifier,
tile,
hub,
self.indices_list,
self.nodata_clouds,
self.quicklook))
if fut.cancelled:
return fut
await fut
logger.info("--> --> --> --> {} processed".format(identifier, hub))
return (identifier, tile, hub)
async def download_process_aws(self, identifier: str) -> Tuple[str, str, str]:
"""
Coroutine for downloading and processing products from AWS.
:param identifier:
"""
logger.info("download_process_aws")
tile = self.identifiers["aws"][identifier]["tile"]
downloads = await asyncio.ensure_future(self.downloader_aws(identifier, tile, "aws"))
if self.process_products:
fut = self.process(*downloads)
#if fut.cancelled():
#return fut
await fut
return downloads
async def main(self) -> None:
"""
Main coroutine.
"""
logger.debug("main")
identifiers_aws = self.identifiers["aws"]
identifiers_hubs = self.identifiers["hubs"]
print("Tiled: ",len(identifiers_hubs))
print("Non tiled: ", len(identifiers_aws))
tasks = []
# on lance les proxies
for hub, limit in self.hubs_limit.items():
if limit > 0:
tasks.append(asyncio.ensure_future(self.proxy_pool(hub, limit)))
# on remplit la queue
if identifiers_hubs:
for identifier, data in identifiers_hubs.items():
if TempContainer(identifier).l1c.in_library :
continue
await self.queue.put(identifier)
# on attend que tout se termine
await asyncio.gather(*tasks)
# on lance les DL aws sur la bonne liste
if identifiers_aws:
aws = [asyncio.ensure_future(self.download_process_aws(identifier))
for (identifier, data) in identifiers_aws.items()]
await asyncio.gather(*aws)
# shutting down executors
try:
self.threads_executor.shutdown(wait=True)
logger.debug("Shutting down threads_executor")
except:
pass
try:
self.processes_executor.shutdown(wait=True)
logger.debug("Shutting down processes_executor")
except:
pass
logger.debug("exiting main")
def run_loop(self) -> None:
"""
run loop
"""
start_time = datetime.now()
try:
self.loop.run_until_complete(self.main())
end_time = datetime.now() - start_time
total_products = len(self.identifiers["aws"]) + len(self.identifiers["hubs"]) - len(self.failed_products)
logger.info("Downloaded and processed {} file(s) in {}".format(total_products, end_time))
finally:
logger.debug("closing loop")
#self.loop.close()
if self.failed_products:
print("Failed downloads:")
pprint(self.failed_products)
#tiles_list = ["10TEP", "13SDT", "13TEF", "14SQJ", "16TCS", "19MHP", "30PXU", "32UPC", "33KUA", "35KRR", "36JUT", "38KQB", "38KQV", "48PWU", "52VDN"]
prods = DataRequest("2018-09-10", "2018-09-28").from_tiles(["13TEF"])
DownloadAndProcess(prods, process_products=True, indices_list=["NDVI"], nodata_clouds=True, quicklook=True)
# -*-coding:utf-8-*-
from pathlib import Path
from collections import namedtuple
from pprint import pprint, pformat
from datetime import datetime
import re
# type annotations
from typing import List, Set, Dict, Tuple, Optional
from sen2chain import (Config,
L1cProduct, L2aProduct, Tile,
IndicesCollection,
str_to_datetime)
data = Path("data")
t = Tile("38KQV")
#print(t.l2a.last.date)
#print(t.l2a.filter_by_cloud_cover(0,50))
#l1c = L1cProduct("S2A_MSIL1C_20180904T063511_N0206_R134_T40KCB_20180904T090928.SAFE")
#print(l1c.in_library)
class Library:
"""
"""
_temp_path = Path(Config().get("temp_path"))
_l1c_path = Path(Config().get("l1c_path"))
_l2a_path = Path(Config().get("l2a_path"))
_indices_path = Path(Config().get("indices_path"))
def __init__(self) -> None:
self._l1c_tiles = [f.name for f in self._l1c_path.glob("*")]
self._l2a_tiles = [f.name for f in self._l2a_path.glob("*")]
self._indices = [f.name for f in self._indices_path.glob("*")]
@property
def l1c_tiles(self):
return self._l1c_tiles
@property
def l2a_tiles(self):
return self._l2a_tiles
@property
def indices(self):
return self._indicess
print(Library().l_tiles)
# -*- coding: utf-8 -*-
import fiona
import rasterio
import csv
from fiona import transform
from pathlib import Path
from shapely.geometry import shape
from rasterstats import zonal_stats
from collections import OrderedDict
from osgeo import ogr
# type annotations
from typing import List, Set, Dict, Tuple, Union
import pandas as pd
from pprint import pprint
from sen2chain import TimeSeries, Tile
from sen2chain.indices import IndicesCollection
from sen2chain.geo_utils import get_tiles_from_file
from sen2chain.utils import datetime_to_str
#TimeSeries("/media/seas-oi/92DAD912DAD8F387/jeremy/DATA_S2/TIME_SERIES/35LLD_kafue.geojson", indices=["NDVI"], date_min="2018-01-01", date_max="2018-09-01")
auto = TimeSeries("/home/jiji/sen2chain/data/TIME_SERIES/test.shp") #, indices=["NDVI"], date_min="2016-01-01", date_max="2016-09-01")
auto = TimeSeries()
# coding:utf-8
import sys
import os
sys.path.insert(0, os.path.abspath('..'))
import re
from pathlib import Path
from pprint import pprint
from sen2chain import xmlparser, L1cProduct
tile = "40KCB"
#mtd = Path("data/S2A_USER_MTD_SAFL2A_PDMC_20160119T023918_R134_V20160118T063524_20160118T063524.xml")
mtd = Path("data/S2A_OPER_MTD_SAFL1C_PDMC_20151201T164959_R134_V20151129T063527_20151129T063527.xml")
#parser = xmlparser.MetadataParser(mtd, tile)
p = L1cProduct("S2A_MSIL1C_20161213T063502_N0204_R134_T40KCB_20161213T063504.SAFE", path=Path()/"data")
print(p._update_metadata_parser())
#def test_xmlparser_get_granule():
#print(parser._psd_version)
#print(parser._root)
#schema_location = parser._root.attrib["{http://www.w3.org/2001/XMLSchema-instance}schemaLocation"]
#version = re.findall("https://psd-([0-9]{2}).sentinel2.eo.esa.int", schema_location)[0]
#print(parser._psd_version)
#pprint(parser.__dict__)
#pprint([g.attrib['granuleIdentifier'] for g in parser._root.findall('.//Granules') if tile in g.attrib["granuleIdentifier"]][0])
#print(parser._granule)
#granules = [g.attrib["granuleIdentifier"] for g in parser._root.findall('.//Granule')]
#print(parser._granule_string)
#print(parser.get_band_path("B04"))
#parser._root.findall(".//[@granuleIdentifier={}]"
#print(
#[f.text + ".jp2"
#for f in parser._root.findall(".//{}[@granuleIdentifier='{}']/{}".format(parser._granule_string, parser._granule, parser._image_string))
#if "B04" in f.text][0]
#)
#print(granules)
#for child in granules[0]:
#print(child.text)
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