"""Clip data values."""
from pydantic import validate_call
from typing import Optional, Union
from remote_sensing_processor.common.common_functions import create_path, persist
from remote_sensing_processor.common.common_raster import (
check_dtype,
load_dataset,
prepare_nodata,
restore_nodata_from_nan,
set_nodata_to_nan,
write_dataset,
)
from remote_sensing_processor.common.dataset import check_output, postprocess_dataset, read_dataset
from remote_sensing_processor.common.types import DirectoryPath, DType, FilePath, NewPath, PystacItem
[docs]
@validate_call
def clip_values(
input_path: Union[FilePath, DirectoryPath, PystacItem],
output_path: Optional[Union[FilePath, DirectoryPath, NewPath]] = None,
minimum: Optional[Union[int, float]] = None,
maximum: Optional[Union[int, float]] = None,
nodata: Optional[Union[int, float]] = None,
dtype: Optional[DType] = None,
write_stac: Optional[bool] = True,
) -> NewPath:
"""
Clip data values.
Parameters
----------
input_path : string or STAC Item
Path to input file, directory or STAC dataset or a STAC Item (e.g., from Planetary Computer).
output_path : string (optional)
Path to an output file, directory, or STAC dataset. If not set, then will overwrite the input files.
Must be set if input is a remote STAC Item.
minimum : int or float (optional)
Min value.
maximum : int or float (optional)
Max value.
nodata : int or float (default = None)
Nodata value. If not set, then is read from inputs.
dtype : dtype definition as a string (optional)
Requested output data type.
write_stac : bool (default = True)
If True, then output metadata is saved to a STAC file.
Returns
-------
output_path : pathlib.Path
Path where output raster is saved.
Examples
--------
>>> import remote_sensing_processor as rsp
>>> # Clip raster values
>>> rsp.clip_values(
... input_path="/home/rsp_test/sentinel_B1.tif",
... output_path="/home/rsp_test/sentinel_B1_clipped.tif",
... minimum=0,
... maximum=10000,
... )
'/home/rsp_test/sentinel_B1_clipped.json'
>>> # Clip only lower values
>>> rsp.clip_values(
... input_path="/home/rsp_test/sentinel_B1.tif",
... output_path="/home/rsp_test/sentinel_B1_clipped.tif",
... minimum=0,
... )
'/home/rsp_test/sentinel_B1_clipped.json'
"""
if minimum is None and maximum is None:
raise ValueError("Minimum or maximum should be set")
output_path = check_output(input_path, output_path)
dataset = read_dataset(input_path)
img = load_dataset(dataset)
img, nodata = prepare_nodata(img, nodata)
# Replacing nodata with nan
img = set_nodata_to_nan(img)
img = img.clip(min=minimum, max=maximum)
# Restoring nodata values
img = restore_nodata_from_nan(img)
# Changing dtype
if dtype:
img = img.astype(dtype)
img = persist(img)
img = check_dtype(img)
# Creating an output folder
create_path(output_path)
# Creating final STAC dataset
dataset, json_path = postprocess_dataset(dataset, img, output_path)
# Write
write_dataset(img, dataset, json_path)
if write_stac:
# Writing JSON metadata file
dataset.save_object(dest_href=json_path.as_posix())
return json_path
return output_path