diff --git a/sen2chain/__init__.py b/sen2chain/__init__.py
index 08a6b0b7c6ce5d489b692818b5a2685764001df2..b3148746f37b0ee2e42725ddf5e0890674c0b5b4 100644
--- a/sen2chain/__init__.py
+++ b/sen2chain/__init__.py
@@ -31,6 +31,7 @@ from .automatization import Automatization
from .utils import format_word, grouper, datetime_to_str, str_to_datetime
from .geo_utils import serialise_tiles_index, get_processed_indices_vect
from .multi_processing import l2a_multiprocessing, cldidx_multiprocessing, cld_multiprocessing, idx_multiprocessing
+#~ from .monthly_summary import MonthlySummary
__version__ = "0.1.0"
__author__ = "Jérémy Commins <jebins@openmailbox.org>"
diff --git a/sen2chain/config.py b/sen2chain/config.py
index 9af69f01d9c42e06609dde4a5c57dbfec89ea942..53a639b940626d25c40617a92f19a6438b2d6c7a 100644
--- a/sen2chain/config.py
+++ b/sen2chain/config.py
@@ -45,7 +45,8 @@ class Config:
"l1c_archive_path": "/ARCHIVE_SENTINEL-PROD/S2_L1C_ARCHIVE",
"l2a_path": "",
"indices_path": "",
- "time_series_path": ""}
+ "time_series_path": "",
+ "monthly_summaries_path": ""}
self._config_params["SEN2COR PATH"] = {"sen2cor_bashrc_path": ""}
self._config_params["HUBS LOGINS"] = {"scihub_id": "",
"scihub_pwd": "",
diff --git a/sen2chain/monthly_summary.py b/sen2chain/monthly_summary.py
new file mode 100644
index 0000000000000000000000000000000000000000..06bfa65d8cddff8e438054e703e9f75c339a4f46
--- /dev/null
+++ b/sen2chain/monthly_summary.py
@@ -0,0 +1,110 @@
+#!/usr/bin/python3
+# -*- coding: utf-8 -*-
+
+"""
+Module to compute monthly summaries for indices
+"""
+
+import logging
+import datetime
+import pandas as pd
+from pathlib import Path
+import rasterio
+import numpy as np
+
+from .tiles import Tile
+from .config import Config
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+
+class MonthlySummary:
+ """Class for managing monthly summaries.
+
+ :param tile: tile number "40KCB"
+ :param indice: "NDVI"
+ :start_date: "2020-01-15"
+ :end_date: "2020-01-19"
+
+ Usage:
+ >>> MonthlySummary("40KCB", "ndvi", "2019-01-01", "2019-10-31")
+ """
+
+ def __init__(self,
+ tile: str = None,
+ indice: str = None,
+ start_date: str = "2015-01-01",
+ stop_date: str = "2100-01-31",
+ ):
+ try:
+ self.tile = Tile(tile)
+ self.indice = indice.lower()
+ self.datetime_start = max(datetime.datetime.strptime("2015-01-01", '%Y-%m-%d'), datetime.datetime.strptime(start_date, '%Y-%m-%d'))
+ self.datetime_stop = min(datetime.datetime.strptime(stop_date, '%Y-%m-%d'), datetime.datetime.now())
+ except:
+ logger.info("Mauvaise initialisation")
+ logger.info("Usage: MonthlySummary('40KCB', 'ndvi', '2019-01-01', '2019-05-20')")
+ return
+
+ _monthly_summary_path = Path(Config().get("monthly_summaries_path"))
+ logger.info(_monthly_summary_path)
+
+ self.start_list = sorted(set([self.datetime_start.strftime("%Y-%m-%d")] + pd.date_range(self.datetime_start, self.datetime_stop, freq='MS').strftime("%Y-%m-%d").to_list()))
+ self.stop_list = sorted(set(pd.date_range(self.datetime_start, self.datetime_stop, freq='M').strftime("%Y-%m-%d").to_list() + [self.datetime_stop.strftime("%Y-%m-%d")]))
+ #~ logger.info(self.start_list)
+ #~ logger.info(self.stop_list)
+
+ for index, (start, stop) in enumerate(zip(self.start_list, self.stop_list)):
+
+ process_list = getattr(self.tile, self.indice).masks.filter_dates(start, stop)
+ logger.info("Compiling {} ({} products)".format(start[:-3], len(process_list)))
+
+ count=0
+ summary_count = None
+ coef_count = None
+
+ for product, ccover in ([p.identifier, p.cloud_cover] for p in process_list):
+ count += 1
+ logger.info("{} - {} - {}".format(product, ccover, (1-ccover/100)))
+ #~ logger.info(ccover)
+ product_path = self.tile._paths['indices'][self.indice] / product[:(-12-len(self.indice))] / product
+ #~ logger.info(product_path)
+
+ with rasterio.open(product_path) as prod_src:
+ prod_profile = prod_src.profile
+ prod = prod_src.read(1).astype(np.int16)
+ try:
+
+ summary_count += np.where(prod != 16383, prod * (1-ccover/100), 0).astype(np.int32)
+ #~ summary_count += prod * (1-ccover/100)
+ #~ coef_count += (1-ccover/100)
+ coef_count += np.where(prod != 16383, (1-ccover/100), 0).astype(np.float)
+ except:
+ summary_count = np.where(prod != 16383, prod * (1-ccover/100), 0).astype(np.int32)
+ coef_count = np.where(prod != 16383, (1-ccover/100), 0).astype(np.float)
+ #~ logger.info(summary_count)
+ #~ logger.info(coef_count)
+
+ if count:
+ logger.info("Compiled {} images".format(count))
+ prod_summary = np.where(coef_count != 0, (summary_count / coef_count).astype(np.int16), 32767)
+ prod_profile.update(driver="Gtiff",
+ compress="NONE",
+ tiled=False,
+ dtype=np.int16,
+ nodata=32767,
+ transform=prod_src.transform,
+ count=1)
+ prod_profile.pop('tiled', None)
+ #~ prod_profile.pop('nodata', None)
+
+ outpath_tif = _monthly_summary_path / \
+ self.indice.upper() / \
+ self.tile.name / \
+ (self.tile.name + "_" + self.indice.upper() + "_" + start[:-3] + '.tif')
+ outpath_tif.parent.mkdir(parents = True, exist_ok = True)
+
+ with rasterio.Env(GDAL_CACHEMAX=512) as env:
+ with rasterio.open(str(outpath_tif), "w", **prod_profile) as dst:
+ dst.write(prod_summary, 1)