eolearn.core.constants

This module implements feature types used in EOPatch objects

class eolearn.core.constants.FeatureType(value)

Bases: enum.Enum

The Enum class of all possible feature types that can be included in EOPatch.

List of feature types:

• DATA with shape t x n x m x d: time- and position-dependent remote sensing data (e.g. bands) of type float

• MASK with shape t x n x m x d: time- and position-dependent mask (e.g. ground truth, cloud/shadow mask, super pixel identifier) of type int

• SCALAR with shape t x s: time-dependent and position-independent remote sensing data (e.g. weather data,) of type float

• LABEL with shape t x s: time-dependent and position-independent label (e.g. ground truth) of type int

• VECTOR: a list of time-dependent vector shapes in shapely.geometry classes

• DATA_TIMELESS with shape n x m x d: time-independent and position-dependent remote sensing data (e.g. elevation model) of type float

• MASK_TIMELESS with shape n x m x d: time-independent and position-dependent mask (e.g. ground truth, region of interest mask) of type int

• SCALAR_TIMELESS with shape s: time-independent and position-independent remote sensing data of type float

• LABEL_TIMELESS with shape s: time-independent and position-independent label of type int

• VECTOR_TIMELESS: time-independent vector shapes in shapely.geometry classes

• META_INFO: dictionary of additional info (e.g. resolution, time difference)

• BBOX: bounding box of the patch which is an instance of sentinelhub.BBox

• TIMESTAMP: list of dates which are instances of datetime.datetime

DATA = 'data'

MASK = 'mask'

SCALAR = 'scalar'

LABEL = 'label'

VECTOR = 'vector'

DATA_TIMELESS = 'data_timeless'

MASK_TIMELESS = 'mask_timeless'

SCALAR_TIMELESS = 'scalar_timeless'

LABEL_TIMELESS = 'label_timeless'

VECTOR_TIMELESS = 'vector_timeless'

META_INFO = 'meta_info'

BBOX = 'bbox'

TIMESTAMP = 'timestamp'

classmethod has_value(value)

True if value is in FeatureType values. False otherwise.

is_spatial()

True if FeatureType has a spatial component. False otherwise.

is_time_dependent()

True if FeatureType has a time component. False otherwise.

is_timeless()

True if FeatureType doesn’t have a time component and is not a meta feature. False otherwise.

is_discrete()

True if FeatureType should have discrete (integer) values. False otherwise.

is_meta()

True if FeatureType is for storing metadata info and False otherwise.

is_vector()

True if FeatureType is vector feature type. False otherwise.

has_dict()

True if FeatureType stores a dictionary. False otherwise.

is_raster()

True if FeatureType stores a dictionary with raster data. False otherwise.

contains_ndarrays()

True if FeatureType stores a dictionary of numpy.ndarrays. False otherwise.

ndim()

If given FeatureType stores a dictionary of numpy.ndarrays it returns dimensions of such arrays.

type()

Returns type of the data for the given FeatureType.

class eolearn.core.constants.FeatureTypeSet

Bases: object

A collection of immutable sets of feature types, grouped together by certain properties.

SPATIAL_TYPES = frozenset({<FeatureType.MASK: 'mask'>, <FeatureType.VECTOR: 'vector'>, <FeatureType.DATA_TIMELESS: 'data_timeless'>, <FeatureType.DATA: 'data'>, <FeatureType.MASK_TIMELESS: 'mask_timeless'>, <FeatureType.VECTOR_TIMELESS: 'vector_timeless'>})

TIME_DEPENDENT_TYPES = frozenset({<FeatureType.MASK: 'mask'>, <FeatureType.VECTOR: 'vector'>, <FeatureType.LABEL: 'label'>, <FeatureType.DATA: 'data'>, <FeatureType.SCALAR: 'scalar'>, <FeatureType.TIMESTAMP: 'timestamp'>})

TIMELESS_TYPES = frozenset({<FeatureType.SCALAR_TIMELESS: 'scalar_timeless'>, <FeatureType.DATA_TIMELESS: 'data_timeless'>, <FeatureType.MASK_TIMELESS: 'mask_timeless'>, <FeatureType.LABEL_TIMELESS: 'label_timeless'>, <FeatureType.VECTOR_TIMELESS: 'vector_timeless'>})

DISCRETE_TYPES = frozenset({<FeatureType.LABEL: 'label'>, <FeatureType.LABEL_TIMELESS: 'label_timeless'>, <FeatureType.MASK_TIMELESS: 'mask_timeless'>, <FeatureType.MASK: 'mask'>})

META_TYPES = frozenset({<FeatureType.META_INFO: 'meta_info'>, <FeatureType.TIMESTAMP: 'timestamp'>, <FeatureType.BBOX: 'bbox'>})

VECTOR_TYPES = frozenset({<FeatureType.VECTOR: 'vector'>, <FeatureType.VECTOR_TIMELESS: 'vector_timeless'>})

RASTER_TYPES = frozenset({<FeatureType.MASK: 'mask'>, <FeatureType.LABEL: 'label'>, <FeatureType.SCALAR_TIMELESS: 'scalar_timeless'>, <FeatureType.DATA_TIMELESS: 'data_timeless'>, <FeatureType.DATA: 'data'>, <FeatureType.MASK_TIMELESS: 'mask_timeless'>, <FeatureType.SCALAR: 'scalar'>, <FeatureType.LABEL_TIMELESS: 'label_timeless'>})

DICT_TYPES = frozenset({<FeatureType.MASK: 'mask'>, <FeatureType.VECTOR: 'vector'>, <FeatureType.LABEL: 'label'>, <FeatureType.META_INFO: 'meta_info'>, <FeatureType.SCALAR_TIMELESS: 'scalar_timeless'>, <FeatureType.DATA_TIMELESS: 'data_timeless'>, <FeatureType.DATA: 'data'>, <FeatureType.MASK_TIMELESS: 'mask_timeless'>, <FeatureType.SCALAR: 'scalar'>, <FeatureType.LABEL_TIMELESS: 'label_timeless'>, <FeatureType.VECTOR_TIMELESS: 'vector_timeless'>})

RASTER_TYPES_4D = frozenset({<FeatureType.DATA: 'data'>, <FeatureType.MASK: 'mask'>})

RASTER_TYPES_3D = frozenset({<FeatureType.MASK_TIMELESS: 'mask_timeless'>, <FeatureType.DATA_TIMELESS: 'data_timeless'>})

RASTER_TYPES_2D = frozenset({<FeatureType.LABEL: 'label'>, <FeatureType.SCALAR: 'scalar'>})

RASTER_TYPES_1D = frozenset({<FeatureType.SCALAR_TIMELESS: 'scalar_timeless'>, <FeatureType.LABEL_TIMELESS: 'label_timeless'>})

class eolearn.core.constants.FileFormat(value)

Bases: enum.Enum

Enum class for file formats used for saving and loading EOPatches

PICKLE = 'pkl'

NPY = 'npy'

GZIP = 'gz'

extension()

Returns file extension of file format

static split_by_extensions(filename)

Splits the filename string by the extension of the file

classmethod is_file_format(value)

Tests whether value represents one of the supported file formats

Parameters

value (str) – The string representation of the enum constant

Returns

True if string is file format and False otherwise

Return type

bool

class eolearn.core.constants.OverwritePermission(value)

Bases: enum.Enum

Enum class which specifies which content of saved EOPatch can be overwritten when saving new content.

Permissions are in the following hierarchy: - ADD_ONLY - Only new features can be added, anything that is already saved cannot be changed. - OVERWRITE_FEATURES - Overwrite only data for features which have to be saved. The remaining content of saved

EOPatch will stay unchanged.

• OVERWRITE_PATCH - Overwrite entire content of saved EOPatch and replace it with the new content.

ADD_ONLY = 0

OVERWRITE_FEATURES = 1

OVERWRITE_PATCH = 2