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Explicit arguments in tasks instead of **kwargs #738

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Aug 31, 2023
Merged

Explicit arguments in tasks instead of **kwargs #738

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694a4c3
Inline **kwargs in sampling
zigaLuksic Aug 31, 2023
9304b2f
Inline kwargs for tiff tasks
zigaLuksic Aug 31, 2023
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45 changes: 38 additions & 7 deletions eolearn/io/raster_io.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,7 @@
import logging
import warnings
from abc import ABCMeta
from typing import Any, BinaryIO
from typing import BinaryIO

import fs
import numpy as np
Expand Down Expand Up @@ -155,7 +155,10 @@ def __init__(
crs: CRS | int | str | None = None,
fail_on_missing: bool = True,
compress: str | None = None,
**kwargs: Any,
filesystem: FS | None = None,
image_dtype: np.dtype | type | None = None,
no_data_value: float | None = None,
config: SHConfig | None = None,
):
"""
:param feature: A feature to be exported.
Expand All @@ -173,9 +176,22 @@ def __init__(
:param fail_on_missing: A flag to specify if the task should fail if a feature is missing or if it should
just show a warning.
:param compress: A type of compression that rasterio should apply to an exported image.
:param kwargs: Keyword arguments to be propagated to `BaseRasterIoTask`.
:param filesystem: A filesystem object. If not given it will be initialized according to `folder` parameter.
:param image_dtype: A data type of data in exported images or data imported from images.
:param no_data_value: When exporting this is the NoData value of pixels in exported images.
When importing this value is assigned to the pixels with NoData.
:param config: A configuration object with AWS credentials. By default, is set to None and in this case the
default configuration will be taken.
"""
super().__init__(feature, folder=folder, create=True, **kwargs)
super().__init__(
feature,
folder=folder,
create=True,
filesystem=filesystem,
image_dtype=image_dtype,
no_data_value=no_data_value,
config=config,
)

self.date_indices = date_indices
self.band_indices = band_indices
Expand Down Expand Up @@ -397,7 +413,10 @@ def __init__(
*,
use_vsi: bool = False,
timestamp_size: int | None = None,
**kwargs: Any,
filesystem: FS | None = None,
image_dtype: np.dtype | type | None = None,
no_data_value: float | None = None,
config: SHConfig | None = None,
):
"""
:param feature: EOPatch feature into which data will be imported
Expand All @@ -413,9 +432,21 @@ def __init__(
channels of given tiff image should be in order
T(1)B(1), T(1)B(2), ..., T(1)B(N), T(2)B(1), T(2)B(2), ..., T(2)B(N), ..., ..., T(M)B(N)
where T and B are the time and band indices.
:param kwargs: Keyword arguments to be propagated to `BaseRasterIoTask`.
:param filesystem: A filesystem object. If not given it will be initialized according to `folder` parameter.
:param image_dtype: A data type of data in exported images or data imported from images.
:param no_data_value: When exporting this is the NoData value of pixels in exported images.
When importing this value is assigned to the pixels with NoData.
:param config: A configuration object with AWS credentials. By default, is set to None and in this case the
default configuration will be taken.
"""
super().__init__(feature, folder=folder, **kwargs)
super().__init__(
feature,
folder=folder,
filesystem=filesystem,
image_dtype=image_dtype,
no_data_value=no_data_value,
config=config,
)

self.use_vsi = use_vsi
self.timestamp_size = timestamp_size
Expand Down
20 changes: 10 additions & 10 deletions eolearn/ml_tools/sampling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@

from abc import ABCMeta
from math import sqrt
from typing import Any, Dict, Union
from typing import Dict, Union

import numpy as np
from shapely.geometry import Point, Polygon
Expand Down Expand Up @@ -182,17 +182,17 @@ def __init__(
fraction: _FractionType,
exclude_values: list[int] | None = None,
replace: bool = False,
**kwargs: Any,
mask_of_samples: Feature | None = None,
):
"""
:param features_to_sample: Features that will be spatially sampled according to given sampling parameters.
:param sampling_feature: A timeless mask feature according to which points will be sampled.
:param fraction: Fraction of points to sample. Can be dictionary mapping values of mask to fractions.
:param exclude_values: Skips points that have these values in `sampling_mask`
:param replace: Whether to sample with replacement. False means each value can only be chosen once.
:param kwargs: Arguments for :class:`BaseSamplingTask<eolearn.geometry.sampling.BaseSamplingTask>`
:param mask_of_samples: An output mask timeless feature of counts how many times each pixel has been sampled.
"""
super().__init__(features_to_sample, **kwargs)
super().__init__(features_to_sample, mask_of_samples=mask_of_samples)

self.sampling_feature = self.parse_feature(sampling_feature, allowed_feature_types={FeatureType.MASK_TIMELESS})

Expand Down Expand Up @@ -267,17 +267,17 @@ def __init__(
amount: float,
sample_size: tuple[int, int] = (1, 1),
replace: bool = False,
**kwargs: Any,
mask_of_samples: Feature | None = None,
):
"""
:param features_to_sample: Features that will be spatially sampled according to given sampling parameters.
:param amount: The number of points to sample if integer valued and the fraction of all points if `float`
:param sample_size: A tuple describing a size of sampled blocks. The size is defined as a tuple of number of
rows and number of columns.
:param replace: Whether to sample with replacement. False means each value can only be chosen once.
:param kwargs: Arguments for :class:`BaseSamplingTask<eolearn.geometry.sampling.BaseSamplingTask>`
:param mask_of_samples: An output mask timeless feature of counts how many times each pixel has been sampled.
"""
super().__init__(features_to_sample, **kwargs)
super().__init__(features_to_sample, mask_of_samples=mask_of_samples)

self.amount = amount
self.sample_size = tuple(sample_size)
Expand Down Expand Up @@ -330,7 +330,7 @@ def __init__(
features_to_sample: FeaturesSpecification,
sample_size: tuple[int, int] = (1, 1),
stride: tuple[int, int] = (1, 1),
**kwargs: Any,
mask_of_samples: Feature | None = None,
):
"""
:param features_to_sample: Features that will be spatially sampled according to given sampling parameters.
Expand All @@ -339,9 +339,9 @@ def __init__(
:param stride: A tuple describing a distance between upper left corners of two consecutive sampled blocks.
The first number is the vertical distance and the second number the horizontal distance. If stride in
smaller than sample_size in any dimensions then sampled blocks will overlap.
:param kwargs: Arguments for :class:`BaseSamplingTask<eolearn.geometry.sampling.BaseSamplingTask>`
:param mask_of_samples: An output mask timeless feature of counts how many times each pixel has been sampled.
"""
super().__init__(features_to_sample, **kwargs)
super().__init__(features_to_sample, mask_of_samples=mask_of_samples)

self.sample_size = tuple(sample_size)
self.stride = tuple(stride)
Expand Down