ee.Image.arrayFlatten

Convertit une image à bande unique de pixels multidimensionnels de forme égale en une image de pixels scalaires, avec une bande pour chaque élément du tableau.

Utilisation	Renvoie
Image.arrayFlatten(coordinateLabels, separator)	Image

Argument	Type	Détails
this: image	Image	Image de pixels multidimensionnels à aplatir.
coordinateLabels	Liste	Nom de chaque position le long de chaque axe. Par exemple, les tableaux 2x2 avec des axes signifiant "jour" et "couleur" peuvent avoir des libellés tels que [["lundi", "mardi"], ["rouge", "vert"]], ce qui donne les noms de bande "lundi_rouge", "lundi_vert", "mardi_rouge" et "mardi_vert".
separator	Chaîne, par défaut : "_"	Séparateur entre les libellés de tableau dans chaque nom de bande.

Exemples

Éditeur de code (JavaScript)

// A function to print arrays for a selected pixel in the following examples.
function sampArrImg(arrImg) {
  var point = ee.Geometry.Point([-121, 42]);
  return arrImg.sample(point, 500).first().get('array');
}

// A 1D array image.
var arrayImg1D = ee.Image([0, 1, 2]).toArray();
print('1D array image (pixel)', sampArrImg(arrayImg1D));
// [0, 1, 2]

// Define image band names for a 1D array image with 3 rows. You are labeling
// all rows and columns using a list of lists; the 1st sub list defines labels
// for array rows and the 2nd (if applicable) defines labels for array columns.
var bandNames1D = [['row0', 'row1', 'row2']];

// Flatten the 1D array image into an image with n bands equal to all
// combinations of rows and columns. Here, we have 3 rows and 0 columns,
// so the result will be a 3-band image.
var imgFrom1Darray = arrayImg1D.arrayFlatten(bandNames1D);
print('Image from 1D array', imgFrom1Darray);

// Make a 2D array image by repeating the 1D array on 2-axis.
var arrayImg2D = arrayImg1D.arrayRepeat(1, 2);
print('2D array image (pixel)', sampArrImg(arrayImg2D));
// [[0, 0],
//  [1, 1],
//  [2, 2]]

// Define image band names for a 2D array image with 3 rows and 2 columns.
// Recall that you are labeling all rows and columns using a list of lists;
// The 1st sub list defines labels for array rows and the 2nd (if applicable)
// defines labels for array columns.
var bandNames2D = [['row0', 'row1', 'row2'], ['col0', 'col1']];

// Flatten the 2D array image into an image with n bands equal to all
// combinations of rows and columns. Here, we have 3 rows and 2 columns,
// so the result will be a 6-band image.
var imgFrom2Darray = arrayImg2D.arrayFlatten(bandNames2D);
print('Image from 2D array', imgFrom2Darray);

Configuration de Python

Pour en savoir plus sur l'API Python et sur l'utilisation de geemap pour le développement interactif, consultez la page Environnement Python.

import ee
import geemap.core as geemap

Colab (Python)

# A function to print arrays for a selected pixel in the following examples.
def samp_arr_img(arr_img):
  point = ee.Geometry.Point([-121, 42])
  return arr_img.sample(point, 500).first().get('array')

# A 1D array image.
array_img_1d = ee.Image([0, 1, 2]).toArray()
display('1D array image (pixel):', samp_arr_img(array_img_1d))
# [0, 1, 2]

# Define image band names for a 1D array image with 3 rows. You are labeling
# all rows and columns using a list of lists; the 1st sub list defines labels
# for array rows and the 2nd (if applicable) defines labels for array columns.
band_names_1d = [['row0', 'row1', 'row2']]

# Flatten the 1D array image into an image with n bands equal to all
# combinations of rows and columns. Here, we have 3 rows and 0 columns,
# so the result will be a 3-band image.
img_from_1d_array = array_img_1d.arrayFlatten(band_names_1d)
display('Image from 1D array:', img_from_1d_array)

# Make a 2D array image by repeating the 1D array on 2-axis.
array_img_2d = array_img_1d.arrayRepeat(1, 2)
display('2D array image (pixel):', samp_arr_img(array_img_2d))
# [[0, 0],
#  [1, 1],
#  [2, 2]]

# Define image band names for a 2D array image with 3 rows and 2 columns.
# Recall that you are labeling all rows and columns using a list of lists;
# The 1st sub list defines labels for array rows and the 2nd (if applicable)
# defines labels for array columns.
band_names_2d = [['row0', 'row1', 'row2'], ['col0', 'col1']]

# Flatten the 2D array image into an image with n bands equal to all
# combinations of rows and columns. Here, we have 3 rows and 2 columns,
# so the result will be a 6-band image.
img_from_2d_array = array_img_2d.arrayFlatten(band_names_2d)
display('Image from 2D array:', img_from_2d_array)