Merge branch '101-add-interpolation-filter' into 'release'

Resolve "Filtres: ajout du module interpolation_filter.py"

See merge request 3d/PandoraBox/pandora2d!100

pandora2d/interpolation_filter/__init__.py

@@ -0,0 +1,24 @@
+#
+# Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES).
+#
+# This file is part of PANDORA2D
+#
+#     https://github.com/CNES/Pandora2D
+#
+# 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.
+#
+"""
+Init file for interpolation filter module
+"""
+
+from .interpolation_filter import AbstractFilter

pandora2d/interpolation_filter/interpolation_filter.py

@@ -0,0 +1,117 @@
+# Copyright (c) 2021 Centre National d'Etudes Spatiales (CNES).
+#
+# This file is part of PANDORA2D
+#
+#     https://github.com/CNES/Pandora2D
+#
+# 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.
+#
+"""
+This module contains functions associated to the interpolation filters.
+"""
+from __future__ import annotations
+import logging
+from typing import Dict
+from abc import abstractmethod, ABC
+
+import numpy as np
+
+from pandora.margins.descriptors import NullMargins
+
+
+class AbstractFilter(ABC):
+    """
+    Abstract Filter class
+    """
+
+    interpolation_filter_methods_avail: Dict = {}
+    _interpolation_filter_method = None
+    cfg = None
+    margins = NullMargins()
+
+    def __new__(cls, filter_method: str | None = None):
+        """
+        Return the plugin associated with the interpolation filter given in the configuration
+
+        :param filter_method: filter_method
+        :type cfg: str | None
+        """
+
+        if cls is AbstractFilter:
+            if isinstance(filter_method, str):
+                try:
+                    return super(AbstractFilter, cls).__new__(cls.interpolation_filter_methods_avail[filter_method])
+                except KeyError:
+                    logging.error("No subpixel method named %s supported", filter_method)
+                    raise KeyError
+        return super(AbstractFilter, cls).__new__(cls)
+
+    def desc(self) -> None:
+        """
+        Describes the interpolation filter
+        :return: None
+        """
+        print(f"{self. _interpolation_filter_method} interpolation filter")
+
+    @classmethod
+    def register_subclass(cls, short_name: str):
+        """
+        Allows to register the subclass with its short name
+
+        :param short_name: the subclass to be registered
+        :type short_name: string
+        """
+
+        def decorator(subclass):
+            """
+            Registers the subclass in the available methods
+
+            :param subclass: the subclass to be registered
+            :type subclass: object
+            """
+            cls.interpolation_filter_methods_avail[short_name] = subclass
+            return subclass
+
+        return decorator
+
+    @abstractmethod
+    def get_coeffs(self, fractionnal_shift: float) -> np.ndarray:
+        """
+        Returns the interpolator coefficients to be applied to the resampling area.
+
+        The size of the returned array depends on the filter margins:
+            - For a row shift, returned array size = up_margin + down_margin + 1
+            - For a column shift, returned array size = left_margin + right_margin + 1
+
+        :param fractionnal_shift: positive fractional shift of the subpixel position to be interpolated
+        :type fractionnal_shift: float
+        :return: a array of interpolator coefficients whose size depends on the filter margins
+        :rtype: np.ndarray
+        """
+
+    @staticmethod
+    def apply(resampling_area: np.ndarray, row_coeff: np.ndarray, col_coeff: np.ndarray) -> float:
+        """
+        Returns the value of the interpolated position
+
+        :param resampling_area: area on which interpolator coefficients will be applied
+        :type resampling_area: np.ndarray
+        :param row_coeff: interpolator coefficients in rows
+        :type row_coeff: np.ndarray
+        :param col_coeff: interpolator coefficients in columns
+        :type col_coeff: np.ndarray
+        :return: the interpolated value of the position corresponding to col_coeff and row_coeff
+        :rtype: float
+        """
+
+        return (row_coeff.dot(resampling_area)).dot(col_coeff)

tests/unit_tests/test_interpolation_filter/test_interpolation_filter.py

@@ -0,0 +1,107 @@
+# Copyright (c) 2024 Centre National d'Etudes Spatiales (CNES).
+#
+# This file is part of PANDORA2D
+#
+#     https://github.com/CNES/Pandora2D
+#
+# 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.
+"""
+Test the interpolation filter module.
+"""
+
+import numpy as np
+import pytest
+
+from pandora2d import interpolation_filter
+
+
+@pytest.mark.parametrize(
+    ["resampling_area", "row_coeff", "col_coeff", "expected_value"],
+    [
+        pytest.param(
+            np.array([[0, 1, 2, 3], [0, 1, 2, 3], [0, 1, 2, 3], [0, 1, 2, 3]]),
+            np.array([-0.0625, 0.5625, 0.5625, -0.0625]),
+            np.array([-0.0625, 0.5625, 0.5625, -0.0625]),
+            1.5,
+            id="Shift of 0.5 in columns and in rows with identical rows in resampling area",
+        ),
+        pytest.param(
+            np.array([[0, 1, 2, 3], [0, 1, 2, 3], [0, 1, 2, 3], [0, 1, 2, 3]]),
+            np.array([0.0, 1.0, 0.0, 0.0]),
+            np.array([-0.0625, 0.5625, 0.5625, -0.0625]),
+            1.5,
+            id="Shift of 0.5 in columns with identical rows in resampling area",
+        ),
+        pytest.param(
+            np.array([[0, 1, 2, 3], [0, 1, 2, 3], [0, 1, 2, 3], [0, 1, 2, 3]]),
+            np.array([-0.0625, 0.5625, 0.5625, -0.0625]),
+            np.array([0.0, 1.0, 0.0, 0.0]),
+            1.0,
+            id="Shift of 0.5 in rows with identical rows in resampling area",
+        ),
+        pytest.param(
+            np.array([[0, 1, 2, 3], [0, 1, 2, 3], [0, 1, 2, 3], [0, 1, 2, 3]]),
+            np.array([0.0, 1.0, 0.0, 0.0]),
+            np.array([-0.0703125, 0.8671875, 0.2265625, -0.0234375]),
+            1.25,
+            id="Shift of 0.25 in columns with identical rows in resampling area",
+        ),
+        pytest.param(
+            np.array([[0, 1, 2, 3], [0, 1, 2, 3], [0, 1, 2, 3], [0, 1, 2, 3]]),
+            np.array([-0.0703125, 0.8671875, 0.2265625, -0.0234375]),
+            np.array([0.0, 1.0, 0.0, 0.0]),
+            1.0,
+            id="Shift of 0.25 in rows with identical rows in resampling area",
+        ),
+        pytest.param(
+            np.array([[0, 0, 0, 0], [1, 1, 1, 1], [2, 2, 2, 2], [3, 3, 3, 3]]),
+            np.array([-0.0625, 0.5625, 0.5625, -0.0625]),
+            np.array([-0.0625, 0.5625, 0.5625, -0.0625]),
+            1.5,
+            id="Shift of 0.5 in columns and in rows with identical columns in resampling area",
+        ),
+        pytest.param(
+            np.array([[0, 0, 0, 0], [1, 1, 1, 1], [2, 2, 2, 2], [3, 3, 3, 3]]),
+            np.array([0.0, 1.0, 0.0, 0.0]),
+            np.array([-0.0625, 0.5625, 0.5625, -0.0625]),
+            1.0,
+            id="Shift of 0.5 in columns with identical columns in resampling area",
+        ),
+        pytest.param(
+            np.array([[0, 0, 0, 0], [1, 1, 1, 1], [2, 2, 2, 2], [3, 3, 3, 3]]),
+            np.array([-0.0625, 0.5625, 0.5625, -0.0625]),
+            np.array([0.0, 1.0, 0.0, 0.0]),
+            1.5,
+            id="Shift of 0.5 in rows with identical columns in resampling area",
+        ),
+        pytest.param(
+            np.array([[0, 1, 2, 3], [0, 1, 4, 3], [0, 1, 2, 3], [0, 1, 2, 3]]),
+            np.array([0.0, 1.0, 0.0, 0.0]),
+            np.array([-0.0625, 0.5625, 0.5625, -0.0625]),
+            2.625,
+            id="Shift of 0.5 in columns with 3/4 identical rows in resampling area",
+        ),
+        pytest.param(
+            np.array([[0, 1, 2, 3], [0, 1, 4, 3], [0, 1, 2, 3], [0, 1, 2, 3]]),
+            np.array([-0.0625, 0.5625, 0.5625, -0.0625]),
+            np.array([0.0, 1.0, 0.0, 0.0]),
+            1.0,
+            id="Shift of 0.5 in rows with 3/4 identical rows in resampling area",
+        ),
+    ],
+)
+def test_apply(resampling_area, row_coeff, col_coeff, expected_value):
+    """
+    Test the apply method
+    """
+    assert interpolation_filter.AbstractFilter.apply(resampling_area, row_coeff, col_coeff) == expected_value