mlubej

# Define the workflow
eo_workflow = eolearn.core.LinearWorkflow(
    add_sentinel2_data, # Sentinel-2 data task
    add_cloud_mask, # cloud mask task
    append_ndvi, # calculate ndvi
    append_ndwi, # calculate ndwi
    append_norm, # calculate norm
    add_valid_mask, # add new feature: valid mask
    add_count_valid, # add new feature: valid counts
    *reference_task_array, # add an array of tasks for adding each reference label

mlubej

import numpy as np
p, t, w, h, d = features_array.shape

# move t axis from position 1 to position 3
features_array = np.moveaxis(features_array, 1, 3)

# reshape array
features_array = features_array.reshape(p*w*h, t*d)

mlubej

mlubej

# load EOPatch
EOPatch.load('path_to_eopatches/eopatch-0x6/')

mlubej

EOPatch(
  data: {
    BANDS: numpy.ndarray(shape=(80, 1010, 999, 6), dtype=float32)
  }
  mask: {
    CLM: numpy.ndarray(shape=(80, 1010, 999, 1), dtype=uint8)
    IS_DATA: numpy.ndarray(shape=(80, 1010, 999, 1), dtype=uint8)
    IS_VALID: numpy.ndarray(shape=(80, 1010, 999, 1), dtype=bool)
  }
  mask_timeless: {

mlubej

eopatch.timestamp
eopatch.mask['LULC']
eopatch.data['CLM'][0]
eopatch.data['BANDS'][5][..., [3, 2, 1]]

mlubej

function setup() {
  return {
    input: ["sunZenithAngles", "sunAzimuthAngles"],
    mosaicking: Mosaicking.ORBIT,
    output: { id:"default", bands: 0}
  }
}

function updateOutputMetadata(scenes, inputMetadata, outputMetadata) {

mlubej

def get_unique_orientations(poly):
    """
    Out of all possible rotations and flips, take into account the polygon symmetry and
    obtain the unique polygon orientations.
    :param poly: input polygon
    :return: array of unique settings of (rotation, flip)
    """
    cx, cy = poly.centroid.x, poly.centroid.y
    pts = np.array(poly.checkers)[:, :-1]
    checkers = np.array(poly.checkers)[:, -1]

mlubej

for idx, c in enumerate(chromosome):
    if np.random.rand() < mutation_probability:
        has_mutated = True
        rand_idx = np.random.choice(range(len(chromosome)))
        chromosome[idx], chromosome[rand_idx] = chromosome[rand_idx], chromosome[idx]

mlubej

def mate(self, partner):
    """
    Create offspring with a order-crossover method
    :param partner: a second p1 which will participate in the mating
    :return: two new offspring individuals
    """
    c1, c2 = np.zeros((2, self.n_pieces), dtype=int)
    start, end = np.sort(np.random.choice(range(self.n_pieces), 2, replace=False))

    p1 = self.chromosome