#!/usr/bin/env python
# coding: utf8
#
# Copyright (c) 2022 Centre National d'Etudes Spatiales (CNES).
#
# This file is part of Shareloc
# (see https://github.com/CNES/shareloc).
#
# 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 the rectification_grids class to handle CARS rectification grids.
"""
# pylint: disable=no-member
# Third party imports
import numpy as np
import rasterio as rio
from scipy import interpolate
[docs]
class RectificationGrid:
"""
Rectification grid
"""
def __init__(self, grid_filename):
"""
Constructor
:param grid_filename: grid filename
:type filename: string
"""
self.grid_filename = grid_filename
dataset = rio.open(grid_filename)
transform = dataset.transform
step_col = transform[0]
step_row = transform[4]
# 0 or 0.5
[ori_col, ori_row] = transform * (0.5, 0.5) # center pixel position
# print("ori {} {} step {} {}".format(ori_col,ori_y,step_x,step_y))
last_col = ori_col + step_col * dataset.width
last_row = ori_row + step_row * dataset.height
# transform dep to positions
self.row_dep = dataset.read(2).transpose()
self.col_dep = dataset.read(1).transpose()
cols = np.arange(ori_col, last_col, step_col)
rows = np.arange(ori_row, last_row, step_row)
self.grid_row, self.grid_col = np.mgrid[ori_col:last_col:step_col, ori_row:last_row:step_row]
self.points = (cols, rows)
self.row_positions = self.row_dep + self.grid_col
self.col_positions = self.col_dep + self.grid_row
[docs]
def get_positions(self):
"""
return grid positions
:return grid positions
:rtype numpy array, numpy array
"""
return self.row_positions, self.col_positions
[docs]
def interpolate(self, positions):
"""
interpolate position
:param positions : positions to interpolate : array Nx2 [col,row]
:type positions: np.array
:return interpolated positions : array Nx2 [col,row]
:rtype np.array
"""
interp_row = interpolate.interpn(
self.points, self.row_positions, positions, method="linear", bounds_error=False, fill_value=None
)
interp_col = interpolate.interpn(
self.points, self.col_positions, positions, method="linear", bounds_error=False, fill_value=None
)
interp_pos = np.stack((interp_col, interp_row)).transpose()
return interp_pos