def generate_fake_l8_old_data(root_directory: str,
tile_name: str,
dates: List[str],
res: Optional[float] = 30.0):
"""
Parameters
----------
root_directory : string
path to generate Sentinel-2 dates
tile_name : string
THEIA tile name (ex:T31TCJ)
dates : list
list of strings reprensentig dates format : YYYYMMDD
"""
tile_dir = os.path.join(root_directory, tile_name)
ensure_dir(tile_dir)
band_of_interest = ["B1", "B2", "B3", "B4", "B5", "B6", "B7"]
masks_of_interest = ["DIV", "BINARY_MASK", "NUA", "SAT"]
origin_x = 566377
origin_y = 6284029
array_name = "iota2_binary"
for date in dates:
date_dir = os.path.join(
tile_dir, (f"LANDSAT8_OLITIRS_XS_{date}_N2A_{tile_name}"))
mask_date_dir = os.path.join(date_dir, "MASK")
ensure_dir(date_dir)
ensure_dir(mask_date_dir)
all_bands = []
for cpt, mask in enumerate(masks_of_interest):
new_mask = os.path.join(mask_date_dir,
(f"LANDSAT8_OLITIRS_XS_{date}_N2A"
f"_{tile_name}_{mask}.TIF"))
array_to_raster(fun_array(array_name) * cpt % 2,
new_mask,
pixel_size=res,
origin_x=origin_x,
origin_y=origin_y)
for band in band_of_interest:
new_band = os.path.join(date_dir,
(f"LANDSAT8_OLITIRS_XS_{date}_N2A"
f"_{tile_name}_{band}.TIF"))
all_bands.append(new_band)
array = fun_array(array_name)
random_array = []
for val in array:
val_tmp = []
for pix_val in val:
val_tmp.append(pix_val * random.random() * 1000)
random_array.append(val_tmp)
array_to_raster(np.array(random_array),
new_band,
pixel_size=res,
origin_x=origin_x,
origin_y=origin_y)
stack_date = os.path.join(date_dir, (f"LANDSAT8_OLITIRS_XS_{date}_"
"N2A_ORTHO_SURF_CORR"
f"_PENTE_{tile_name}.TIF"))
stack_app = CreateConcatenateImagesApplication({
"il": all_bands,
"out": stack_date
})
stack_app.ExecuteAndWriteOutput()
def get_time_series_gapFilling(self, ram=128):
"""
Due to the SAR data, time series must be split by polarisation
and orbit (ascending / descending)
"""
import configparser
from iota2.Common.FileUtils import getNbDateInTile
from iota2.Common.OtbAppBank import getSARstack
from iota2.Common.OtbAppBank import CreateConcatenateImagesApplication
from iota2.Common.OtbAppBank import CreateImageTimeSeriesGapFillingApplication
from iota2.Common.OtbAppBank import getInputParameterOutput
(all_filtered, all_masks, interp_date_files,
input_date_files) = getSARstack(self.s1_cfg,
self.tile_name,
self.all_tiles.split(" "),
os.path.join(self.i2_output_path,
"features"),
workingDirectory=None)
# to be clearer
s1_data = OrderedDict()
s1_labels = OrderedDict()
config = configparser.ConfigParser()
config.read(self.s1_cfg)
interpolation_method = "linear"
if config.has_option("Processing", "gapFilling_interpolation"):
interpolation_method = config.get("Processing",
"gapFilling_interpolation")
dependancies = []
for filtered, masks, interp_dates, in_dates in zip(
all_filtered, all_masks, interp_date_files, input_date_files):
sar_mode = os.path.basename(
filtered.GetParameterValue("outputstack"))
sar_mode = "_".join(os.path.splitext(sar_mode)[0].split("_")[0:-1])
polarisation = sar_mode.split("_")[1]
orbit = sar_mode.split("_")[2]
gapfilling_orbit_pol_name_masks = f"{self.gapfilling_orbit_pol_name_mask}_{orbit}_{polarisation}.tif"
gapfilling_raster_mask = os.path.join(
self.features_dir, "tmp", gapfilling_orbit_pol_name_masks)
masks_stack = CreateConcatenateImagesApplication({
"il": masks,
"out": gapfilling_raster_mask,
"ram": str(ram)
})
if self.write_outputs_flag is False:
filtered.Execute()
masks_stack.Execute()
else:
filtered_raster = filtered.GetParameterValue(
getInputParameterOutput(filtered))
masks_stack_raster = masks_stack.GetParameterValue(
getInputParameterOutput(masks_stack))
if not os.path.exists(masks_stack_raster):
masks_stack.ExecuteAndWriteOutput()
if not os.path.exists(filtered_raster):
filtered.ExecuteAndWriteOutput()
if os.path.exists(masks_stack_raster):
masks_stack = masks_stack_raster
if os.path.exists(filtered_raster):
filtered = filtered_raster
dependancies.append((filtered, masks_stack))
gapfilling_orbit_pol_name = f"{self.gapfilling_orbit_pol_name}_{orbit}_{polarisation}.tif"
gapfilling_raster = os.path.join(self.features_dir, "tmp",
gapfilling_orbit_pol_name)
gap_app = CreateImageTimeSeriesGapFillingApplication({
"in":
filtered,
"mask":
masks_stack,
"it":
interpolation_method,
"id":
in_dates,
"od":
interp_dates,
"comp":
str(1),
"out":
gapfilling_raster
})
s1_data[sar_mode] = gap_app
sar_dates = sorted(getNbDateInTile(interp_dates,
display=False,
raw_dates=True),
key=lambda x: int(x))
labels = [
"{}_{}_{}_{}".format(self.__class__.name, orbit, polarisation,
date).lower() for date in sar_dates
]
s1_labels[sar_mode] = labels
return (s1_data, dependancies), s1_labels
def generate_fake_s2_l3a_data(root_directory: str,
tile_name: str,
dates: List[str],
res: Optional[float] = 30.0):
"""
Parameters
----------
root_directory : string
path to generate Sentinel-2 l3a dates
tile_name : string
THEIA tile name (ex:T31TCJ)
dates : list
list of strings reprensentig dates format : YYYYMMDD
"""
tile_dir = os.path.join(root_directory, tile_name)
ensure_dir(tile_dir)
band_of_interest = [
"B2", "B3", "B4", "B5", "B6", "B7", "B8", "B8A", "B11", "B12"
]
masks_of_interest = ["BINARY_MASK", "FLG_R1"]
origin_x = 566377
origin_y = 6284029
array_name = "iota2_binary"
for date in dates:
date_dir = os.path.join(tile_dir,
("SENTINEL2X_{}-000000-"
"000_L3A_{}_D_V1-7".format(date, tile_name)))
mask_date_dir = os.path.join(date_dir, "MASKS")
ensure_dir(date_dir)
ensure_dir(mask_date_dir)
all_bands = []
for cpt, mask in enumerate(masks_of_interest):
new_mask = os.path.join(
mask_date_dir,
("SENTINEL2X_{}-000000-000_L3A"
"_{}_D_V1-7_{}.tif".format(date, tile_name, mask)))
array_to_raster(fun_array(array_name) * cpt % 2,
new_mask,
pixel_size=res,
origin_x=origin_x,
origin_y=origin_y)
for band in band_of_interest:
new_band = os.path.join(
date_dir,
("SENTINEL2X_{}-000000-000_L3A"
"_{}_D_V1-7_FRC_{}.tif".format(date, tile_name, band)))
all_bands.append(new_band)
array = fun_array(array_name)
random_array = []
for val in array:
val_tmp = []
for pix_val in val:
val_tmp.append(pix_val * random.random() * 1000)
random_array.append(val_tmp)
array_to_raster(np.array(random_array),
new_band,
pixel_size=res,
origin_x=origin_x,
origin_y=origin_y)
stack_date = os.path.join(
date_dir, ("SENTINEL2X_{}-000000-000_L3A_{}_D_V1-7"
"_FRC_STACK.tif".format(date, tile_name)))
stack_app = CreateConcatenateImagesApplication({
"il": all_bands,
"out": stack_date
})
stack_app.ExecuteAndWriteOutput()