# -*- coding: utf-8 -*-
# Copyright 2023, SERTIT-ICube - France, https://sertit.unistra.fr/
# This file is part of eoreader project
# https://github.com/sertit/eoreader
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
""" Product, superclass of all EOReader satellites products """
# pylint: disable=W0107
from __future__ import annotations
import datetime as dt
import functools
import gc
import logging
import os
import platform
import shutil
import tempfile
from abc import abstractmethod
from enum import unique
from io import BytesIO
from pathlib import Path
from typing import Callable, Tuple, Union
from zipfile import ZipFile
import geopandas as gpd
import numpy as np
import rasterio
import validators
import xarray as xr
from affine import Affine
from cloudpathlib import AnyPath, CloudPath
from lxml import etree, html
from rasterio import transform, warp
from rasterio.crs import CRS
from rasterio.enums import Resampling
from sertit import files, rasters, strings, xml
from sertit.misc import ListEnum
from sertit.snap import MAX_CORES
from eoreader import cache, utils
from eoreader.bands import (
DEM,
HILLSHADE,
SLOPE,
BandNames,
indices,
is_clouds,
is_dem,
is_index,
is_sat_band,
to_band,
to_str,
)
from eoreader.env_vars import CI_EOREADER_BAND_FOLDER, DEM_PATH
from eoreader.exceptions import InvalidProductError, InvalidTypeError
from eoreader.keywords import DEM_KW, HILLSHADE_KW, SLOPE_KW
from eoreader.reader import Constellation, Reader
from eoreader.stac import StacItem
from eoreader.utils import EOREADER_NAME, simplify
LOGGER = logging.getLogger(EOREADER_NAME)
PRODUCT_FACTORY = Reader()
[docs]@unique
class SensorType(ListEnum):
"""
Sensor type of the products, optical or SAR
"""
OPTICAL = "Optical"
"""For optical data"""
SAR = "SAR"
"""For SAR data"""
[docs]@unique
class OrbitDirection(ListEnum):
"""
Orbit Direction
"""
ASCENDING = "ASCENDING"
"""Ascending sensing orbit direction"""
DESCENDING = "DESCENDING"
"""Descending sensing orbit direction"""
[docs]class Product:
"""Super class of EOReader Products"""
[docs] def __init__(
self,
product_path: Union[str, CloudPath, Path],
archive_path: Union[str, CloudPath, Path] = None,
output_path: Union[str, CloudPath, Path] = None,
remove_tmp: bool = False,
**kwargs,
) -> None:
self.needs_extraction = True
"""Does this product needs to be extracted to be processed ? (:code:`True` by default)."""
self.path = AnyPath(product_path)
"""Usable path to the product, either extracted or archived path, according to the satellite."""
self.filename = files.get_filename(self.path)
"""Product filename"""
self._use_filename = False
self.name = None
"""Product true name (as specified in the metadata)"""
self.split_name = None
"""
Split name, to retrieve every information from its true name (dates, tile, product type...).
"""
self.archive_path = AnyPath(archive_path) if archive_path else self.path
"""Archive path, same as the product path if not specified.
Useful when you want to know where both the extracted and archived version of your product are stored."""
self.is_archived = self.path.is_file()
""" Is the archived product is processed
(a products is considered as archived if its products path is a directory)."""
# The output will be given later
self._tmp_output = None
self._output = None
self._remove_tmp_process = remove_tmp
# Get the products date and datetime
self.date = None
"""Acquisition date."""
self.datetime = None
"""Acquisition datetime."""
self.tile_name = None
"""Tile if possible (for data that can be piled, for example S2 and Landsats)."""
self.sensor_type = None
"""Sensor type, SAR or optical."""
self.product_type = None
"""Product type, satellite-related field, such as L1C or L2A for Sentinel-2 data."""
self.instrument = None
"""Product instrument, such as MSI for Sentinel-2 data."""
self.bands = None
"""
Band mapping between band wrapping names such as
:code:`GREEN` and band real number such as :code:`03` for Sentinel-2.
"""
self.is_reference = False
"""If the product is a reference, used for algorithms that need pre and post data, such as fire detection."""
self.corresponding_ref = []
"""The corresponding reference products to the current one
(if the product is not a reference but has a reference data corresponding to it).
A list because of multiple ref in case of non-stackable products (S3, S1...)"""
self.nodata = -9999
""" Product nodata, set to -9999 by default """
# Mask values
self._mask_true = 1
self._mask_false = 0
self._mask_nodata = 255
self.constellation = kwargs.get("constellation")
"""Product constellation, such as Sentinel-2"""
# Set the resolution, needs to be done when knowing the product type
self.resolution = None
"""
Default resolution in meters of the current product.
For SAR product, we use Ground Range resolution as we will automatically orthorectify the tiles.
"""
self.condensed_name = None
"""
Condensed name, the filename with only useful data to keep the name unique
(ie. :code:`20191215T110441_S2_30TXP_L2A_122756`).
Used to shorten names and paths.
"""
self.constellation_id = None
"""Constellation ID, i.e. :code:`S2` for :code:`Sentinel-2`"""
self.is_ortho = True
"""True if the images are orthorectified and the footprint is retrieved easily."""
self._stac = None
# Manage output
if output_path:
self._tmp_output = None
self._output = AnyPath(output_path)
else:
self._tmp_output = tempfile.TemporaryDirectory()
self._output = AnyPath(self._tmp_output.name)
# Pre initialization
self._pre_init(**kwargs)
# Only compute data if OK (for now OK is extracted if needed)
if self.is_archived and self.needs_extraction:
LOGGER.warning(f"{self.filename} needs to be extracted to be used !")
else:
# Get the product real name
self.name = self._get_name()
self.split_name = self._get_split_name()
# Get the products date and datetime
self.datetime = self.get_datetime(as_datetime=True)
self.date = self.get_date(as_date=True)
# Constellation and satellite ID
if not self.constellation:
self.constellation = self._get_constellation()
self.constellation_id = (
self.constellation
if isinstance(self.constellation, str)
else self.constellation.name
)
self._set_instrument()
# Post initialization
self._post_init(**kwargs)
# Set product type, needs to be done after the post-initialization
self._set_product_type()
# Set the resolution, needs to be done when knowing the product type
self.resolution = self._get_resolution()
self._map_bands()
# Condensed name
self.condensed_name = self._get_condensed_name()
# Temporary file path (private)
self._tmp_process = self._output.joinpath(f"tmp_{self.condensed_name}")
os.makedirs(self._tmp_process, exist_ok=True)
def __del__(self):
"""Cleaning up _tmp directory"""
self.clear()
# -- Remove temp folders
if self._tmp_output:
self._tmp_output.cleanup()
elif self._remove_tmp_process:
files.remove(self._tmp_process)
@abstractmethod
def _pre_init(self, **kwargs) -> None:
"""
Function used to pre_init the products
(setting needs_extraction and so on)
"""
raise NotImplementedError
@abstractmethod
def _post_init(self, **kwargs) -> None:
"""
Function used to post_init the products
(setting sensor type, band names and so on)
"""
raise NotImplementedError
[docs] @cache
@abstractmethod
def extent(self) -> gpd.GeoDataFrame:
"""
Get UTM extent of the tile
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.utm_extent()
geometry
0 POLYGON ((309780.000 4390200.000, 309780.000 4...
Returns:
gpd.GeoDataFrame: Extent in UTM
"""
raise NotImplementedError
[docs] @cache
@abstractmethod
def crs(self) -> CRS:
"""
Get UTM projection of the tile
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.utm_crs()
CRS.from_epsg(32630)
Returns:
crs.CRS: CRS object
"""
raise NotImplementedError
@abstractmethod
def _map_bands(self):
"""
Map bands
"""
raise NotImplementedError
def _get_band_folder(self, writable: bool = False) -> Union[CloudPath, Path]:
"""
Manage the case of CI SNAP Bands
Returns:
Union[CloudPath, Path]: Band folder
"""
band_folder = self._tmp_process
# Manage CI bands (when we do not write anything, read only)
if not writable:
ci_band_folder = os.environ.get(CI_EOREADER_BAND_FOLDER)
if ci_band_folder:
ci_band_folder = AnyPath(ci_band_folder)
if ci_band_folder.is_dir():
# If we need a writable directory, check it
band_folder = ci_band_folder
return band_folder
@abstractmethod
def _get_resolution(self) -> float:
"""
Get product default resolution (in meters)
"""
raise NotImplementedError
@abstractmethod
def _set_product_type(self) -> None:
"""
Set product type
"""
raise NotImplementedError
@abstractmethod
def _set_instrument(self) -> None:
"""
Set product type
"""
raise NotImplementedError
@classmethod
def _get_constellation(cls) -> Constellation:
class_module = cls.__module__.split(".")[-1]
constellation_id = class_module.replace("_product", "").upper()
return getattr(Constellation, constellation_id)
def _get_name(self) -> str:
"""
Set product real name from metadata
Returns:
str: True name of the product (from metadata)
"""
if (
self._use_filename
and self.constellation
and Reader().valid_name(self.path, self.constellation)
):
name = self.filename
else:
name = self._get_name_constellation_specific()
return name
@abstractmethod
def _get_name_constellation_specific(self) -> str:
"""
Set product real name from metadata
Returns:
str: True name of the product (from metadata)
"""
raise NotImplementedError
@abstractmethod
def _get_condensed_name(self) -> str:
"""
Set product condensed name.
Returns:
str: Condensed name
"""
raise NotImplementedError
def _get_split_name(self) -> list:
"""
Get split name (erasing empty strings in it by precaution, especially for S1 and S3 data)
Returns:
list: Split products name
"""
return utils.get_split_name(self.name)
[docs] @abstractmethod
def get_datetime(self, as_datetime: bool = False) -> Union[str, dt.datetime]:
"""
Get the product's acquisition datetime, with format :code:`YYYYMMDDTHHMMSS` <-> :code:`%Y%m%dT%H%M%S`
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_datetime(as_datetime=True)
datetime.datetime(2020, 8, 24, 11, 6, 31)
>>> prod.get_datetime(as_datetime=False)
'20200824T110631'
Args:
as_datetime (bool): Return the date as a datetime.datetime. If false, returns a string.
Returns:
Union[str, datetime.datetime]: Its acquisition datetime
"""
raise NotImplementedError
[docs] def get_date(self, as_date: bool = False) -> Union[str, dt.date]:
"""
Get the product's acquisition date.
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_date(as_date=True)
datetime.datetime(2020, 8, 24, 0, 0)
>>> prod.get_date(as_date=False)
'20200824'
Args:
as_date (bool): Return the date as a datetime.date. If false, returns a string.
Returns:
str: Its acquisition date
"""
date = self.get_datetime().split("T")[0]
if as_date:
date = strings.str_to_date(date, date_format="%Y%m%d")
return date
[docs] @abstractmethod
def get_default_band_path(self, **kwargs) -> Union[CloudPath, Path]:
"""
Get default band path (among the existing ones).
Usually :code:`GREEN` band for optical data and the first existing one between :code:`VV` and :code:`HH` for SAR data.
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_default_band_path()
'zip+file://S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip!/S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE/GRANULE/L1C_T30TTK_A027018_20200824T111345/IMG_DATA/T30TTK_20200824T110631_B03.jp2'
Args:
kwargs: Additional arguments
Returns:
Union[CloudPath, Path]: Default band path
"""
raise NotImplementedError
[docs] @abstractmethod
def get_default_band(self) -> BandNames:
"""
Get default band:
Usually :code:`GREEN` band for optical data and the first existing one between :code:`VV` and :code:`HH` for SAR data.
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_default_band()
<SpectralBandNames.GREEN: 'GREEN'>
Returns:
str: Default band
"""
raise NotImplementedError
[docs] @abstractmethod
def get_existing_bands(self) -> list:
"""
Return the existing bands.
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_existing_bands()
[<SpectralBandNames.CA: 'COASTAL_AEROSOL'>,
<SpectralBandNames.BLUE: 'BLUE'>,
<SpectralBandNames.GREEN: 'GREEN'>,
<SpectralBandNames.RED: 'RED'>,
<SpectralBandNames.VRE_1: 'VEGETATION_RED_EDGE_1'>,
<SpectralBandNames.VRE_2: 'VEGETATION_RED_EDGE_2'>,
<SpectralBandNames.VRE_3: 'VEGETATION_RED_EDGE_3'>,
<SpectralBandNames.NIR: 'NIR'>,
<SpectralBandNames.NNIR: 'NARROW_NIR'>,
<SpectralBandNames.WV: 'WATER_VAPOUR'>,
<SpectralBandNames.CIRRUS: 'CIRRUS'>,
<SpectralBandNames.SWIR_1: 'SWIR_1'>,
<SpectralBandNames.SWIR_2: 'SWIR_2'>]
Returns:
list: List of existing bands in the products
"""
raise NotImplementedError
[docs] @abstractmethod
def get_existing_band_paths(self) -> dict:
"""
Return the existing band paths (orthorectified if needed).
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_existing_band_paths()
{
<SpectralBandNames.CA: 'COASTAL_AEROSOL'>: 'zip+file://S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip!/S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE/GRANULE/L1C_T30TTK_A027018_20200824T111345/IMG_DATA/T30TTK_20200824T110631_B01.jp2',
...,
<SpectralBandNames.SWIR_2: 'SWIR_2'>: 'zip+file://S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip!/S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE/GRANULE/L1C_T30TTK_A027018_20200824T111345/IMG_DATA/T30TTK_20200824T110631_B12.jp2'
}
Returns:
dict: Dictionary containing the path of each queried band
"""
raise NotImplementedError
[docs] def get_raw_band_paths(self, **kwargs) -> dict:
"""
Return the raw band paths.
Args:
kwargs: Additional arguments
Returns:
dict: Dictionary containing the path of each queried band
"""
return self.get_existing_band_paths()
[docs] @abstractmethod
def get_band_paths(
self, band_list: list, resolution: float = None, **kwargs
) -> dict:
"""
Return the paths of required bands.
.. code-block:: python
>>> from eoreader.reader import Reader
>>> from eoreader.bands import *
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_band_paths([GREEN, RED])
{
<SpectralBandNames.GREEN: 'GREEN'>: 'zip+file://S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip!/S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE/GRANULE/L1C_T30TTK_A027018_20200824T111345/IMG_DATA/T30TTK_20200824T110631_B03.jp2',
<SpectralBandNames.RED: 'RED'>: 'zip+file://S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip!/S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE/GRANULE/L1C_T30TTK_A027018_20200824T111345/IMG_DATA/T30TTK_20200824T110631_B04.jp2'
}
Args:
band_list (list): List of the wanted bands
resolution (float): Band resolution
kwargs: Other arguments used to load bands
Returns:
dict: Dictionary containing the path of each queried band
"""
raise NotImplementedError
@abstractmethod
def _read_mtd(self) -> (etree._Element, dict):
"""
Read metadata and outputs the metadata XML root and its namespaces as a dict
Returns:
(etree._Element, dict): Metadata XML root and its namespace
"""
raise NotImplementedError
def _read_mtd_xml(
self, mtd_from_path: str, mtd_archived: str = None
) -> (etree._Element, dict):
"""
Read metadata and outputs the metadata XML root and its namespaces as a dicts as a dict
Args:
mtd_from_path (str): Metadata regex (glob style) to find from extracted product
mtd_archived (str): Metadata regex (re style) to find from archived product
Returns:
(etree._Element, dict): Metadata XML root and its namespaces
"""
try:
if self.is_archived:
root = xml.read_archive(self.path, f".*{mtd_archived}")
else:
try:
try:
mtd_file = next(self.path.glob(f"**/*{mtd_from_path}"))
except ValueError:
mtd_file = next(self.path.glob(f"*{mtd_from_path}"))
try:
root = xml.read(mtd_file)
except ValueError as ex:
raise InvalidProductError from ex
except StopIteration as ex:
raise InvalidProductError(
f"Metadata file ({mtd_from_path}) not found in {self.path}"
) from ex
except etree.XMLSyntaxError:
raise InvalidProductError(f"Invalid metadata XML for {self.path}!")
# Get namespaces map (only useful ones)
nsmap = {key: f"{{{ns}}}" for key, ns in root.nsmap.items()}
pop_list = ["xsi", "xs", "xlink"]
for ns in pop_list:
if ns in nsmap.keys():
nsmap.pop(ns)
return root, nsmap
def _read_mtd_html(
self, mtd_from_path: str, mtd_archived: str = None
) -> html.HtmlElement:
"""
Read metadata and outputs the metadata HTML root
Args:
mtd_from_path (str): Metadata regex (glob style) to find from extracted product
mtd_archived (str): Metadata regex (re style) to find from archived product
Returns:
(html.HtmlElement, dict): Metadata HTML root and its namespaces
"""
if self.is_archived:
root = files.read_archived_html(self.path, f".*{mtd_archived}")
else:
try:
mtd_file = next(self.path.glob(f"**/*{mtd_from_path}"))
if isinstance(mtd_file, CloudPath):
try:
# Try using read_text (faster)
root = html.fromstring(mtd_file.read_text())
except ValueError:
# Try using read_bytes
# Slower but works with:
# {ValueError}Unicode strings with encoding declaration are not supported.
# Please use bytes input or XML fragments without declaration.
root = html.fromstring(mtd_file.read_bytes())
else:
# pylint: disable=I1101:
# Module 'lxml.etree' has no 'parse' member, but source is unavailable.
html_tree = html.parse(str(mtd_file))
root = html_tree.getroot()
except StopIteration as ex:
raise InvalidProductError(
f"Metadata file ({mtd_from_path}) not found in {self.path}"
) from ex
return root
[docs] def read_mtd(self) -> (etree._Element, dict):
"""
Read metadata and outputs the metadata XML root and its namespaces as a dict.
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"S1A_IW_GRDH_1SDV_20191215T060906_20191215T060931_030355_0378F7_3696.zip"
>>> prod = Reader().open(path)
>>> prod.read_mtd()
(<Element product at 0x1832895d788>, '')
Returns:
(etree._Element, dict): Metadata XML root and its namespace
"""
return self._read_mtd()
# pylint: disable=W0613
@abstractmethod
def _read_band(
self,
path: Union[CloudPath, Path],
band: BandNames = None,
resolution: Union[tuple, list, float] = None,
size: Union[list, tuple] = None,
**kwargs,
) -> xr.DataArray:
"""
Read band from disk.
.. WARNING::
For optical data, invalid pixels are not managed here
Args:
path (Union[CloudPath, Path]): Band path
band (BandNames): Band to read
resolution (Union[tuple, list, float]): Resolution of the wanted band, in dataset resolution unit (X, Y)
size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided.
kwargs: Other arguments used to load bands
Returns:
xr.DataArray: Band xarray
"""
raise NotImplementedError
@abstractmethod
def _load_bands(
self,
bands: list,
resolution: float = None,
size: Union[list, tuple] = None,
**kwargs,
) -> dict:
"""
Load bands as numpy arrays with the same resolution (and same metadata).
Args:
bands (list): List of the wanted bands
resolution (int): Band resolution in meters
size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided.
kwargs: Other arguments used to load bands
Returns:
dict: Dictionary {band_name, band_xarray}
"""
raise NotImplementedError
def _load_dem(
self,
band_list: list,
resolution: float = None,
size: Union[list, tuple] = None,
**kwargs,
) -> dict:
"""
Load bands as numpy arrays with the same resolution (and same metadata).
Args:
band_list (list): List of the wanted bands
resolution (int): Band resolution in meters
size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided.
kwargs: Other arguments used to load bands
Returns:
dict: Dictionary {band_name, band_xarray}
"""
dem_bands = {}
if band_list:
dem_path = os.environ.get(DEM_PATH) # We already checked if it exists
for band in band_list:
assert is_dem(band)
if band == DEM:
path = self._warp_dem(
kwargs.get(DEM_KW, dem_path),
resolution=resolution,
size=size,
**kwargs,
)
elif band == SLOPE:
path = self._compute_slope(
kwargs.get(SLOPE_KW, dem_path),
resolution=resolution,
size=size,
)
elif band == HILLSHADE:
path = self._compute_hillshade(
kwargs.get(HILLSHADE_KW, dem_path),
resolution=resolution,
size=size,
)
else:
raise InvalidTypeError(f"Unknown DEM band: {band}")
dem_bands[band] = utils.read(
path, resolution=resolution, size=size
).astype(np.float32)
return dem_bands
[docs] def load(
self,
bands: Union[list, BandNames, Callable],
resolution: float = None,
size: Union[list, tuple] = None,
**kwargs,
) -> dict:
"""
Open the bands and compute the wanted index.
- For Optical data:
The bands will be purged of nodata and invalid pixels (if specified with the CLEAN_OPTICAL keyword),
the nodata will be set to -9999 and the bands will be DataArrays in float32.
- For SAR data:
The bands will be purged of nodata (not over the sea),
the nodata will be set to 0 to respect SNAP's behavior and the bands will be DataArray in float32.
Bands that come out this function at the same time are collocated and therefore have the same shapes.
This can be broken if you load data separately. Its is best to always load DEM data with some real bands.
.. code-block:: python
>>> from eoreader.reader import Reader
>>> from eoreader.bands import *
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> bands = prod.load([GREEN, NDVI], resolution=20)
Args:
bands (Union[list, BandNames, Callable]): Band list
resolution (float): Resolution of the band, in meters
size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided.
kwargs: Other arguments used to load bands
Returns:
dict: {band_name, band xarray}
"""
# Check if all bands are valid
bands = to_band(bands)
for band in bands:
try:
band_name = band.value
except AttributeError:
band_name = band
assert self.has_band(band), f"{self.name} has not a {band_name} band."
if not resolution and not size:
resolution = self.resolution
# Load bands (only once ! and convert the bands to be loaded to correct format)
unique_bands = list(set(to_band(bands)))
band_dict = self._load(unique_bands, resolution, size, **kwargs)
# Manage the case of arrays of different size -> collocate arrays if needed
band_dict = self._collocate_bands(band_dict)
# Convert to xarray dataset when all the bands have the same size
# TODO: cannot convert as we have non-string index
# xds = xr.Dataset(band_dict)
# Sort bands to the asked order
# xds.reindex({"band": bands})
# Rename all bands and add attributes
for key, val in band_dict.items():
band_dict[key] = self._update_attrs(val, key, **kwargs)
return band_dict
@abstractmethod
def _load(
self,
bands: list,
resolution: float = None,
size: Union[list, tuple] = None,
**kwargs,
) -> dict:
"""
Core function loading data bands
Args:
bands (list): Band list
resolution (float): Resolution of the band, in meters
size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided.
kwargs: Other arguments used to load bands
Returns:
Dictionary {band_name, band_xarray}
"""
raise NotImplementedError
[docs] def has_band(self, band: Union[BandNames, Callable]) -> bool:
"""
Does this product has the specified band ?
By band, we mean:
- satellite band
- index
- DEM band
- cloud band
.. code-block:: python
>>> from eoreader.reader import Reader
>>> from eoreader.bands import *
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.has_band(GREEN)
True
>>> prod.has_band(TIR_2)
False
>>> prod.has_band(NDVI)
True
>>> prod.has_band(SHADOWS)
False
>>> prod.has_band(HILLSHADE)
True
Args:
band (Union[BandNames, Callable]): EOReader band (optical, SAR, clouds, DEM)
Returns:
bool: True if the products has the specified band
"""
band = to_band(band)[0]
if is_dem(band):
if self.sensor_type == SensorType.SAR and band == HILLSHADE:
has_band = False
else:
has_band = True
elif is_clouds(band):
has_band = self._has_cloud_band(band)
elif is_index(band):
has_band = self._has_index(band)
else:
has_band = band in self.get_existing_bands()
return has_band
[docs] def has_bands(self, bands: Union[list, BandNames, Callable]) -> bool:
"""
Does this product has the specified bands ?
By band, we mean:
- satellite band
- index
- DEM band
- cloud band
See :code:`has_bands` for a code example.
Args:
bands (Union[list, BandNames, Callable]): EOReader bands (optical, SAR, clouds, DEM)
Returns:
bool: True if the products has the specified band
"""
if not isinstance(bands, list):
bands = [bands]
return all([self.has_band(band) for band in set(bands)])
@abstractmethod
def _has_cloud_band(self, band: BandNames) -> bool:
"""
Does this product has the specified cloud band ?
.. code-block:: python
>>> from eoreader.reader import Reader
>>> from eoreader.bands import *
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.has_cloud_band(CLOUDS)
True
"""
raise NotImplementedError
def _has_index(self, idx: Callable) -> bool:
"""
Cen the specified index be computed from this product ?
.. code-block:: python
>>> from eoreader.reader import Reader
>>> from eoreader.bands import *
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.has_index(NDVI)
True
Args:
idx (Callable): Index
Returns:
bool: True if the specified index can be computed with this product's bands
"""
index_bands = to_band(indices.get_needed_bands(idx))
return all(np.isin(index_bands, self.get_existing_bands()))
def __gt__(self, other: Product) -> bool:
"""
Overload greater than for eoreader -> compare the dates:
The greater products is the one acquired the last.
Args:
other (Product): Other products to be compared with this one
Returns:
bool: True if this product has been acquired after the other
"""
return self.date > other.date
def __ge__(self, other: Product) -> bool:
"""
Overload greater than for eoreader -> compare the dates:
The greater products is the one acquired the last.
Args:
other (Product): Other products to be compared with this one
Returns:
bool: True if this product has been acquired after or in the same time as the other
"""
return self.date >= other.date
def __eq__(self, other: Product) -> bool:
"""
Overload greater than for eoreader -> compare the dates:
The greater products is the one acquired the last.
Args:
other (Product): Other products to be compared with this one
Returns:
bool: True if this product has been acquired in the same time as the other
"""
return self.date == other.date
def __ne__(self, other: Product) -> bool:
"""
Overload greater than for eoreader -> compare the dates:
The greater products is the one acquired the last.
Args:
other (Product): Other products to be compared with this one
Returns:
bool: True if this product has been acquired not in the same time as the other
"""
return self.date != other.date
def __le__(self, other: Product) -> bool:
"""
Overload greater than for eoreader -> compare the dates:
The greater products is the one acquired the last.
Args:
other (Product): Other products to be compared with this one
Returns:
bool: True if this product has been acquired before or in the same time as the other
"""
return self.date <= other.date
def __lt__(self, other: Product) -> bool:
"""
Overload greater than for eoreader -> compare the dates:
The greater products is the one acquired the last.
Args:
other (Product): Other products to be compared with this one
Returns:
bool: True if this product has been acquired before the other
"""
return self.date < other.date
def __hash__(self):
return hash(self.condensed_name)
def _get_out_path(self, filename: str) -> Tuple[Union[Path, CloudPath], bool]:
"""
Returns the output path of a file to be written, depending on if it already exists or not (manages CI folders)
Args:
filename (str): Filename
Returns:
Tuple[Union[Path, CloudPath], bool]: Output path and if the file already exists or not
"""
out = self._get_band_folder() / filename
exists = True
if not out.exists():
exists = False
out = self._get_band_folder(writable=True) / filename
return out, exists
@property
def output(self) -> Union[CloudPath, Path]:
"""Output directory of the product, to write orthorectified data for example."""
return self._output
@output.setter
def output(self, value: str):
"""Output directory of the product, to write orthorectified data for example."""
# Set the new output
self._output = AnyPath(value)
if not isinstance(self._output, CloudPath):
self._output = self._output.resolve()
# Create temporary process folder
old_tmp_process = self._tmp_process
self._tmp_process = self._output.joinpath(f"tmp_{self.condensed_name}")
os.makedirs(self._tmp_process, exist_ok=True)
# Move all files from old process folder into the new one
for file in files.listdir_abspath(old_tmp_process):
try:
shutil.move(str(file), self._tmp_process)
except shutil.Error:
# Don't overwrite file
pass
# Remove old output if existing into the new output
if self._tmp_output:
self._tmp_output.cleanup()
self._tmp_output = None
@property
def stac(self) -> StacItem:
if not self._stac:
self._stac = StacItem(self)
return self._stac
def _warp_dem(
self,
dem_path: str = "",
resolution: Union[float, tuple] = None,
size: Union[list, tuple] = None,
resampling: Resampling = Resampling.bilinear,
**kwargs,
) -> Union[Path, CloudPath]:
"""
Get this product DEM, warped to this product footprint and CRS.
.. code-block:: python
>>> from eoreader.reader import Reader
>>> from eoreader.bands import *
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.warp_dem(resolution=20) # In meters
'/path/to/20200824T110631_S2_T30TTK_L1C_150432_DEM.tif'
Args:
dem_path (str): DEM path, using EUDEM/MERIT DEM if none
resolution (Union[float, tuple]): Resolution in meters. If not specified, use the product resolution.
resampling (Resampling): Resampling method
size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided.
kwargs: Other arguments used to load bands
Returns:
Union[Path, CloudPath]: DEM path (as a VRT)
"""
dem_name = f"{self.condensed_name}_DEM_{files.get_filename(dem_path)}.tif"
warped_dem_path, warped_dem_exists = self._get_out_path(dem_name)
if warped_dem_exists:
LOGGER.debug(
"Already existing DEM for %s. Skipping process.", self.condensed_name
)
else:
LOGGER.debug("Warping DEM for %s", self.condensed_name)
# Allow S3 HTTP Urls only on Linux because rasterio bugs on Windows
if validators.url(dem_path) and platform.system() == "Windows":
raise OSError(
f"URLs to DEM like {dem_path} are not supported on Windows! Use Docker or Linux instead"
)
# Check existence (SRTM)
if not validators.url(dem_path):
dem_path = AnyPath(dem_path)
if not dem_path.is_file():
raise FileNotFoundError(f"DEM file does not exist here: {dem_path}")
# Reproject DEM into products CRS
LOGGER.debug("Using DEM: %s", dem_path)
def_tr, def_w, def_h, def_crs = self.default_transform(**kwargs)
with rasterio.open(str(dem_path)) as dem_ds:
# Get adjusted transform and shape (with new resolution)
if size is not None and resolution is None:
try:
# Get destination transform
out_h = size[1]
out_w = size[0]
# Get destination transform
coeff_x = def_w / out_w
coeff_y = def_h / out_h
dst_tr = def_tr
dst_tr *= dst_tr.scale(coeff_x, coeff_y)
except (TypeError, KeyError):
raise ValueError(
f"Size should exist (as resolution is None)"
f" and castable to a list: {size}"
)
else:
# Refine resolution
if resolution is None:
resolution = self.resolution
bounds = transform.array_bounds(def_h, def_w, def_tr)
dst_tr, out_w, out_h = warp.calculate_default_transform(
def_crs,
self.crs(),
def_w,
def_h,
*bounds,
resolution=resolution,
)
# Get empty output
reprojected_array = np.zeros(
(dem_ds.count, out_h, out_w), dtype=np.float32
)
# Write reprojected DEM: here do not use utils.write()
out_meta = {
"driver": "GTiff",
"dtype": reprojected_array.dtype,
"nodata": self.nodata,
"width": out_w,
"height": out_h,
"count": dem_ds.count,
"crs": self.crs(),
"transform": dst_tr,
}
with rasterio.open(str(warped_dem_path), "w", **out_meta) as out_dst:
out_dst.write(reprojected_array)
# Reproject
warp.reproject(
source=rasterio.band(dem_ds, range(1, dem_ds.count + 1)),
destination=rasterio.band(out_dst, range(1, out_dst.count + 1)),
resampling=resampling,
num_threads=MAX_CORES,
dst_transform=dst_tr,
dst_crs=self.crs(),
src_crs=dem_ds.crs,
src_transform=dem_ds.transform,
)
return warped_dem_path
@abstractmethod
def _compute_hillshade(
self,
dem_path: str = "",
resolution: Union[float, tuple] = None,
size: Union[list, tuple] = None,
resampling: Resampling = Resampling.bilinear,
) -> Union[Path, CloudPath]:
"""
Compute Hillshade mask
Args:
dem_path (str): DEM path, using EUDEM/MERIT DEM if none
resolution (Union[float, tuple]): Resolution in meters. If not specified, use the product resolution.
size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided.
resampling (Resampling): Resampling method
Returns:
Union[Path, CloudPath]: Hillshade mask path
"""
raise NotImplementedError
def _compute_slope(
self,
dem_path: str = "",
resolution: Union[float, tuple] = None,
size: Union[list, tuple] = None,
resampling: Resampling = Resampling.bilinear,
) -> Union[Path, CloudPath]:
"""
Compute slope mask
Args:
dem_path (str): DEM path, using EUDEM/MERIT DEM if none
resolution (Union[float, tuple]): Resolution in meters. If not specified, use the product resolution.
size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided.
resampling (Resampling): Resampling method
Returns:
Union[Path, CloudPath]: Slope mask path
"""
# Warp DEM
warped_dem_path = self._warp_dem(dem_path, resolution, size, resampling)
# Get slope path
slope_name = f"{self.condensed_name}_SLOPE_{files.get_filename(dem_path)}.tif"
slope_path, slope_exists = self._get_out_path(slope_name)
if slope_exists:
LOGGER.debug(
"Already existing slope DEM for %s. Skipping process.",
self.condensed_name,
)
else:
LOGGER.debug("Computing slope for %s", self.condensed_name)
# Compute slope
slope = rasters.slope(warped_dem_path)
utils.write(slope, slope_path)
return slope_path
@staticmethod
def _collocate_bands(bands: dict, master_xds: xr.DataArray = None) -> dict:
"""
Collocate all bands from a dict if needed (if a raster shape is different)
Args:
bands (dict): Dict of bands to collocate if needed
master_xds (xr.DataArray): Master array
Returns:
dict: Collocated bands
"""
for band_id, band in bands.items():
if master_xds is None:
master_xds = band # Master array is the first one in this case
if band.shape != master_xds.shape:
bands[band_id] = rasters.collocate(
master_xds=master_xds, slave_xds=band
)
bands[band_id] = bands[band_id].assign_coords(
{
"x": master_xds.x,
"y": master_xds.y,
}
) # Bug for now, tiny difference in coords
return bands
# pylint: disable=R0913
# Too many arguments (6/5)
[docs] def stack(
self,
bands: list,
resolution: float = None,
size: Union[list, tuple] = None,
stack_path: Union[str, CloudPath, Path] = None,
save_as_int: bool = False,
**kwargs,
) -> xr.DataArray:
"""
Stack bands and index of a products.
.. code-block:: python
>>> from eoreader.reader import Reader
>>> from eoreader.bands import *
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> stack = prod.stack([NDVI, MNDWI, GREEN], resolution=20) # In meters
Args:
bands (list): Bands and index combination
resolution (float): Stack resolution. . If not specified, use the product resolution.
size (Union[tuple, list]): Size of the array (width, height). Not used if resolution is provided.
stack_path (Union[str, CloudPath, Path]): Stack path
save_as_int (bool): Convert stack to uint16 to save disk space (and therefore multiply the values by 10.000)
**kwargs: Other arguments passed to :code:`load` or :code:`rioxarray.to_raster()` (such as :code:`compress`)
Returns:
xr.DataArray: Stack as a DataArray
"""
if not isinstance(bands, list):
bands = [bands]
# Ensure the bands are not in strings (otherwise will bug in Dataset conversion)
bands = to_band(bands)
if not resolution and not size:
resolution = self.resolution
# Create the analysis stack
band_dict = self.load(bands, resolution=resolution, size=size, **kwargs)
# Convert into dataset with str as names
LOGGER.debug("Stacking")
data_vars = {}
coords = band_dict[bands[0]].coords
for key in bands:
data_vars[to_str(key)[0]] = (
band_dict[key].coords.dims,
band_dict[key].data,
)
# Set memory free (for big stacks)
band_dict[key].close()
band_dict[key] = None
# Create dataset, with dims well-ordered
stack = (
xr.Dataset(
data_vars=data_vars,
coords=coords,
)
.to_stacked_array(new_dim="z", sample_dims=("x", "y"))
.transpose("z", "y", "x")
)
# Save as integer
dtype = np.float32
if save_as_int:
default_nodata = 65535
scale = 10000
stack_min = np.min(stack)
if stack_min < -0.1:
LOGGER.warning(
"Cannot convert the stack to uint16 as it has negative values (< -0.1). Keeping it in float32."
)
else:
if stack_min < 0:
LOGGER.warning(
"Small negative values ]-0.1, 0] have been found. Clipping to 0."
)
stack = stack.copy(data=np.clip(stack.data, a_min=0, a_max=None))
# Scale to uint16, fill nan and convert to uint16
dtype = np.uint16
nodata = kwargs.get("nodata", default_nodata) # Can be 0
for b_id, band in enumerate(bands):
# SCALING
# NOT ALL bands need to be scaled, only:
# - Satellite bands
# - index
if is_sat_band(band) or is_index(band):
if np.max(stack[b_id, ...]) > default_nodata / scale:
LOGGER.debug(
"Band not in reflectance, keeping them as is (the values will be rounded)"
)
else:
stack[b_id, ...] = stack[b_id, ...] * scale
# Fill no data (done here to avoid RAM saturation)
stack[b_id, ...] = stack[b_id, ...].fillna(nodata)
if dtype == np.float32:
# Set nodata if needed (NaN values are already set)
if stack.rio.encoded_nodata != self.nodata:
stack = stack.rio.write_nodata(self.nodata, encoded=True, inplace=True)
# Update stack's attributes
stack = self._update_attrs(stack, bands, **kwargs)
# Write on disk
LOGGER.debug("Saving stack")
if stack_path:
stack_path = AnyPath(stack_path)
if not stack_path.parent.exists():
os.makedirs(str(stack_path.parent), exist_ok=True)
utils.write(stack, stack_path, dtype=dtype, **kwargs)
return stack
@abstractmethod
def _update_attrs_constellation_specific(
self, xarr: xr.DataArray, bands: list, **kwargs
) -> xr.DataArray:
"""
Update attributes of the given array (constellation specific)
Args:
xarr (xr.DataArray): Array whose attributes need an update
bands (list): Array name (as a str or a list)
"""
raise NotImplementedError
def _update_attrs(self, xarr: xr.DataArray, bands: list, **kwargs) -> xr.DataArray:
"""
Update attributes of the given array
Args:
xarr (xr.DataArray): Array whose attributes need an update
bands (list): Bands
Returns:
xr.DataArray: Updated array
"""
# Clean attributes, we don't want to pollute our attributes by default ones (not deterministic)
# Are we sure of that ?
xarr.attrs = {}
if not isinstance(bands, list):
bands = [bands]
long_name = to_str(bands)
xr_name = "_".join(long_name)
attr_name = " ".join(long_name)
xarr = xarr.rename(xr_name)
xarr.attrs["long_name"] = attr_name
xarr.attrs["constellation"] = (
self.constellation
if isinstance(self.constellation, str)
else self.constellation.value
)
xarr.attrs["constellation_id"] = self.constellation_id
xarr.attrs["product_path"] = str(self.path) # Convert to string
xarr.attrs["product_name"] = self.name
xarr.attrs["product_filename"] = self.filename
xarr.attrs["instrument"] = (
self.instrument
if isinstance(self.instrument, str)
else self.instrument.value
)
xarr.attrs["product_type"] = (
self.product_type
if isinstance(self.product_type, str)
else self.product_type.value
)
xarr.attrs["acquisition_date"] = self.get_datetime(as_datetime=False)
xarr.attrs["condensed_name"] = self.condensed_name
od = self.get_orbit_direction()
xarr.attrs["orbit_direction"] = od.value if od is not None else str(od)
# kwargs attrs
xarr = self._update_attrs_constellation_specific(xarr, bands, **kwargs)
return xarr
@staticmethod
def _check_dem_path(bands: list, **kwargs) -> None:
"""
Check if DEM is set and exists if DEM bands are asked.
Args:
bands (list): List of the wanted bands
kwargs: Other arguments used to load bands
"""
if DEM_PATH not in os.environ:
if (
(DEM in bands and DEM_KW not in kwargs)
or (SLOPE in bands and SLOPE_KW not in kwargs)
or (HILLSHADE in bands and HILLSHADE_KW not in kwargs)
):
raise ValueError(
f"DEM path not set, unable to compute DEM bands! "
f"Please set the environment variable {DEM_PATH} or a DEM keyword."
)
else:
dem_path = os.environ.get(DEM_PATH)
# URLs and file paths are required
if not validators.url(dem_path):
dem_path = AnyPath(dem_path)
if not dem_path.is_file():
raise FileNotFoundError(
f"{dem_path} is not a file! "
f"Please set the environment variable {DEM_PATH} to an existing file."
)
def _resolution_from_size(self, size: Union[list, tuple] = None) -> tuple:
"""
Compute the corresponding resolution to a given size (positive resolution)
Args:
size (Union[list, tuple]): Size
Returns:
tuple: Resolution as a tuple (x, y)
"""
def_tr, def_w, def_h, def_crs = self.default_transform()
bounds = transform.array_bounds(def_h, def_w, def_tr)
# Manage WGS84 case
if not def_crs.is_projected:
utm_tr, utm_w, utm_h = warp.calculate_default_transform(
def_crs,
self.crs(),
def_w,
def_h,
*bounds,
resolution=self.resolution,
)
res_x = abs(utm_tr.a * utm_w / size[0])
res_y = abs(utm_tr.e * utm_h / size[1])
# Manage UTM case
else:
res_x = abs(def_tr.a * def_w / size[0])
res_y = abs(def_tr.e * def_h / size[1])
# Round resolution to the closest meter (under 1 meter, allow centimetric resolution)
if res_x < 1.0:
res_x = np.round(res_x, 1)
else:
res_x = np.round(res_x, 0)
if res_y < 1.0:
res_y = np.round(res_y, 1)
else:
res_y = np.round(res_y, 0)
return res_x, res_y
[docs] def clean_tmp(self):
"""
Clean the temporary directory of the current product
"""
if self._tmp_process.exists():
for tmp_file in self._tmp_process.glob("*"):
files.remove(tmp_file)
[docs] def clear(self):
"""
Clear this product's cache
"""
# -- Delete all cached properties and functions
gc.collect()
# All objects collected
objects = []
for obj in gc.get_objects():
try:
if isinstance(obj, functools._lru_cache_wrapper):
objects.append(obj)
except ReferenceError:
pass
# All objects cleared
for obj in objects:
obj.cache_clear()
def _resolution_to_str(self, resolution: Union[float, tuple, list] = None):
"""
Convert a resolution to a normalized string
Args:
resolution (Union[float, tuple, list]): Resolution
Returns:
str: Resolution as a string
"""
def _res_to_str(res):
return f"{abs(res):.2f}m".replace(".", "-")
if resolution:
if isinstance(resolution, (tuple, list)):
res_x = _res_to_str(resolution[0])
res_y = _res_to_str(resolution[1])
if res_x == res_y:
res_str = res_x
else:
res_str = f"{res_x}_{res_y}"
else:
res_str = _res_to_str(resolution)
else:
res_str = _res_to_str(self.resolution)
return res_str
def _to_repr(self) -> list:
"""
Returns a representation of the product as a list
Returns:
list: Representation of the product
"""
band_repr = "\n".join(
[
f"\t\t{band.value}: {val.id}"
for band, val in self.bands.items()
if val is not None
]
)
repr_str = [
f"eoreader.{self.__class__.__name__} '{self.name}'",
"Attributes:",
f"\tcondensed_name: {self.condensed_name}",
f"\tpath: {self.path}",
f"\tconstellation: {self.constellation if isinstance(self.constellation, str) else self.constellation.value}",
f"\tsensor type: {self.sensor_type if isinstance(self.sensor_type, str) else self.sensor_type.value}",
f"\tproduct type: {self.product_type if isinstance(self.product_type, str) else self.product_type.value}",
f"\tdefault resolution: {self.resolution}",
f"\tacquisition datetime: {self.get_datetime(as_datetime=True).isoformat()}",
f"\tband mapping:\n{band_repr}",
f"\tneeds extraction: {self.needs_extraction}",
]
return repr_str + self._to_repr_constellation_specific()
@abstractmethod
def _to_repr_constellation_specific(self) -> list:
"""
Representation specific to the constellation
Returns:
list: Representation list (constellation specific)
"""
raise NotImplementedError
def __repr__(self):
return "\n".join(self._to_repr())
[docs] def get_quicklook_path(self) -> Union[None, str]:
"""
Get quicklook path if existing (no such thing for Sentinel-2)
Returns:
str: Quicklook path
"""
LOGGER.debug(f"No quicklook available for {self.constellation.value} data!")
return None
[docs] def plot(self) -> None:
"""
Plot the quicklook if existing
"""
try:
import matplotlib.pyplot as plt
from PIL import Image
except ModuleNotFoundError:
LOGGER.warning("You need to install matplotlib to plot the product.")
else:
quicklook_path = self.get_quicklook_path()
if quicklook_path is not None:
if quicklook_path[:4].lower() in [".png", ".jpg"]:
plt.figure(figsize=(6, 6))
if quicklook_path.startswith("zip::"):
str_path = quicklook_path.replace("zip::", "")
zip_path, zip_name = str_path.split("!")
with ZipFile(zip_path, "r") as zip_ds:
with BytesIO(zip_ds.read(zip_name)) as bf:
plt.imshow(Image.open(bf))
else:
qck = rasters.read(quicklook_path)
if qck.rio.count == 3:
plt.figure(figsize=(6, 6))
qck.plot.imshow(robust=True)
elif qck.rio.count == 1:
plt.figure(figsize=(7, 6))
qck.plot(cmap="GnBu_r", robust=True)
else:
pass
plt.title(f"{self.condensed_name}")
[docs] @cache
def get_orbit_direction(self) -> OrbitDirection:
"""
Get cloud cover as given in the metadata
.. code-block:: python
>>> from eoreader.reader import Reader
>>> path = r"S2A_MSIL1C_20200824T110631_N0209_R137_T30TTK_20200824T150432.SAFE.zip"
>>> prod = Reader().open(path)
>>> prod.get_orbit_direction().value
"DESCENDING"
Returns:
OrbitDirection: Orbit direction (ASCENDING/DESCENDING)
"""
raise NotImplementedError
