From be405d448c9af266fb85a0e79dee399dbe482bfb Mon Sep 17 00:00:00 2001
From: tsanona <tsanona@gmail.com>
Date: Mon, 22 Feb 2021 12:25:59 +0100
Subject: [PATCH] Add option to json_to_tiff to skip mask conversion.

---
 gts2_client/gts2_client.py | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/gts2_client/gts2_client.py b/gts2_client/gts2_client.py
index fc00a42..16c4152 100755
--- a/gts2_client/gts2_client.py
+++ b/gts2_client/gts2_client.py
@@ -398,7 +398,7 @@ def mk_rgb(basedir, outdir, rgb_comb=("B04", "B03", "B02"), rgb_gamma=(1.0, 1.0,
 
 
 def json_to_tiff(out_mode, api_result, only_tile, outpath, out_prefix, wl,
-                 level, stack_resolution, bands,  tif_opts, logger=None):
+                 level, stack_resolution, bands, tif_opts, keep_mask, logger=None):
     """
     Get data from json dict and save if as singletif files OR:
     save all requested bands plus cloudmask as one tiff file per date and tile.
@@ -464,7 +464,7 @@ def json_to_tiff(out_mode, api_result, only_tile, outpath, out_prefix, wl,
                             tif_list.append(outfile)
 
                             # create tif file for clm
-                            if level != "L1C":
+                            if level != "L1C" and keep_mask:
                                 clm = api_result['Metadata'][tile_key]['MSK_' + str(res) + 'm']['data'][ti]
                                 clm_arr = np.asarray(clm)
                                 clm_outfile = "{path}/{sensor}_{level}_{pref}_{date}_{tile}_MSK_{res}m.tif".format(
@@ -540,7 +540,7 @@ def json_to_tiff(out_mode, api_result, only_tile, outpath, out_prefix, wl,
                 geo_proj = api_result['Results'][tile_key][band_key]['mapinfo']['geo_projection']
                 geotrans = (x_min, int(stack_resolution), 0, y_max, 0, -int(stack_resolution))
                 driver = gdal.GetDriverByName("GTiff")
-                if level == "L1C":
+                if level == "L1C" or not keep_mask:
                     outfile = "{path}/{sensor}_{level}_{pref}_{date}_{tile}_{band}_{res}m.tif".format(
                         path=outpath, pref=out_prefix, date=ac_date, tile=tile_key, band=bands, level=level,
                         res=stack_resolution, sensor=sensor)
@@ -548,7 +548,7 @@ def json_to_tiff(out_mode, api_result, only_tile, outpath, out_prefix, wl,
                     outfile = "{path}/{sensor}_{level}_{pref}_{date}_{tile}_{band}_MSK_{res}m.tif".format(
                         path=outpath, pref=out_prefix, date=ac_date, tile=tile_key, band=bands, level=level,
                         res=stack_resolution, sensor=sensor)
-                img = driver.Create(outfile, cols, rows, count_bands + 1, gdal.GDT_Int32)
+                img = driver.Create(outfile, cols, rows, count_bands + keep_mask, gdal.GDT_Int32, options=tif_opts)
                 img.SetGeoTransform(geotrans)
                 img.SetProjection(geo_proj)
 
@@ -564,11 +564,11 @@ def json_to_tiff(out_mode, api_result, only_tile, outpath, out_prefix, wl,
                     slice += 1
 
                 # This is done outside of the loop because one can not set a nodata_value for each band
-                img.GetRasterBand(slice).SetNoDataValue(api_result['Results'][tile_key][band_key]["fill_value"])
+                img.GetRasterBand(slice-1).SetNoDataValue(api_result['Results'][tile_key][band_key]["fill_value"])
                 img.SetMetadata({'TIFFTAG_YRESOLUTION': '%s' % stack_resolution,
                                  'TIFFTAG_XRESOLUTION': '%s' % stack_resolution})
 
-                if level != "L1C":
+                if level != "L1C" and keep_mask:
                     clm = api_result['Metadata'][tile_key]['MSK_%sm' % stack_resolution]['data'][ti]
                     clm_arr = np.asarray(clm)
                     img.GetRasterBand(slice).WriteArray(clm_arr)
@@ -745,7 +745,7 @@ def __get_auth(logger=None):
 
 def client(outpath="", out_prefix="", out_mode="json", compress="ZSTD-2" , geo_ll=(), geo_ur=(), sensor="S2A", bands="", max_cloudy="0.5",
            level="L2A", start_date="", end_date="", version="0.15", suffix="", minimum_fill="0.8",
-           only_tile="", stack_resolution="10", quiet=False, rgb_extension="jpg", rgb_bands_selection="realistic",
+           only_tile="", stack_resolution="10", keep_mask=True, quiet=False, rgb_extension="jpg", rgb_bands_selection="realistic",
            merge_tifs=False, merge_tile=None, onlytime=False, timeout=None):
     """
     Downloads data via API and saves it in a wanted file format (.json, .tiff or .nc) or alternatively returns a python 
@@ -868,7 +868,7 @@ def client(outpath="", out_prefix="", out_mode="json", compress="ZSTD-2" , geo_l
     elif out_mode == "single" or out_mode == "stack":
         logger.info("Converting data to %s tif-files ..." % out_mode, )
         tif_list = json_to_tiff(out_mode, api_result, only_tile, outpath, out_prefix, wl, level, stack_resolution,
-                                bands, tif_opts=tif_opts, logger=logger)
+                                bands, tif_opts=tif_opts, keep_mask=keep_mask, logger=logger)
         if merge_tifs is True:
             merge_tiles(tif_list, out_mode=out_mode, target_tile=merge_tile)
 
@@ -877,7 +877,7 @@ def client(outpath="", out_prefix="", out_mode="json", compress="ZSTD-2" , geo_l
         with tempfile.TemporaryDirectory(dir=outpath) as tmp_dir:
 
             tif_list = json_to_tiff("stack", api_result, only_tile, tmp_dir, out_prefix, wl, level, stack_resolution,
-                                    bands, tif_opts=tif_opts, logger=logger)
+                                    bands, tif_opts=tif_opts, keep_mask=keep_mask, logger=logger)
 
             if merge_tifs is True:
                 merge_tiles(tif_list, out_mode="stack", target_tile=merge_tile)
-- 
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