ee.Image.arrayFlatten
संग्रह की मदद से व्यवस्थित रहें
अपनी प्राथमिकताओं के आधार पर, कॉन्टेंट को सेव करें और कैटगरी में बांटें.
यह फ़ंक्शन, एक ही शेप वाले मल्टीडाइमेंशनल पिक्सल की सिंगल-बैंड इमेज को स्केलर पिक्सल की इमेज में बदलता है. इसमें ऐरे के हर एलिमेंट के लिए एक बैंड होता है.
| इस्तेमाल | रिटर्न |
|---|
Image.arrayFlatten(coordinateLabels, separator) | इमेज |
| आर्ग्यूमेंट | टाइप | विवरण |
|---|
यह: image | इमेज | फ़्लैट करने के लिए, मल्टीडाइमेंशनल पिक्सल की इमेज. |
coordinateLabels | सूची | हर ऐक्सिस के साथ हर पोज़िशन का नाम. उदाहरण के लिए, 'दिन' और 'रंग' के हिसाब से बनाए गए 2x2 ऐरे में, [['सोमवार', 'मंगलवार'], ['लाल', 'हरा']] जैसे लेबल हो सकते हैं. इससे बैंड के नाम'monday_red', 'monday_green', 'tuesday_red', और 'tuesday_green' बन सकते हैं. |
separator | स्ट्रिंग, डिफ़ॉल्ट: "_" | हर बैंड के नाम में मौजूद कलेक्शन के लेबल के बीच सेपरेटर. |
उदाहरण
कोड एडिटर (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);
Python सेटअप करना
Python API और इंटरैक्टिव डेवलपमेंट के लिए geemap का इस्तेमाल करने के बारे में जानकारी पाने के लिए,
Python एनवायरमेंट पेज देखें.
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()
print('1D array image (pixel):', samp_arr_img(array_img_1d).getInfo())
# [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)
print('Image from 1D array:', img_from_1d_array.getInfo())
# Make a 2D array image by repeating the 1D array on 2-axis.
array_img_2d = array_img_1d.arrayRepeat(1, 2)
print('2D array image (pixel):', samp_arr_img(array_img_2d).getInfo())
# [[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)
print('Image from 2D array:', img_from_2d_array.getInfo())
जब तक कुछ अलग से न बताया जाए, तब तक इस पेज की सामग्री को Creative Commons Attribution 4.0 License के तहत और कोड के नमूनों को Apache 2.0 License के तहत लाइसेंस मिला है. ज़्यादा जानकारी के लिए, Google Developers साइट नीतियां देखें. Oracle और/या इससे जुड़ी हुई कंपनियों का, Java एक रजिस्टर किया हुआ ट्रेडमार्क है.
आखिरी बार 2025-07-26 (UTC) को अपडेट किया गया.
[null,null,["आखिरी बार 2025-07-26 (UTC) को अपडेट किया गया."],[[["\u003cp\u003e\u003ccode\u003eImage.arrayFlatten\u003c/code\u003e transforms an image containing multidimensional pixel arrays into a multi-band image with scalar pixel values.\u003c/p\u003e\n"],["\u003cp\u003eEach element of the input array becomes a separate band in the output image.\u003c/p\u003e\n"],["\u003cp\u003eUsers can specify custom names for the output bands using the \u003ccode\u003ecoordinateLabels\u003c/code\u003e parameter.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003eseparator\u003c/code\u003e parameter allows for customization of the delimiter used in band names derived from array indices.\u003c/p\u003e\n"],["\u003cp\u003eThis function is useful for working with data structured as arrays within an image, such as time series or multi-spectral data organized in matrices.\u003c/p\u003e\n"]]],[],null,["# ee.Image.arrayFlatten\n\nConverts a single-band image of equal-shape multidimensional pixels to an image of scalar pixels, with one band for each element of the array.\n\n\u003cbr /\u003e\n\n| Usage | Returns |\n|-------------------------------------------------------|---------|\n| Image.arrayFlatten`(coordinateLabels, `*separator*`)` | Image |\n\n| Argument | Type | Details |\n|--------------------|----------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| this: `image` | Image | Image of multidimensional pixels to flatten. |\n| `coordinateLabels` | List | Name of each position along each axis. For example, 2x2 arrays with axes meaning 'day' and 'color' could have labels like \\[\\['monday', 'tuesday'\\], \\['red', 'green'\\]\\], resulting in band names'monday_red', 'monday_green', 'tuesday_red', and 'tuesday_green'. |\n| `separator` | String, default: \"_\" | Separator between array labels in each band name. |\n\nExamples\n--------\n\n### Code Editor (JavaScript)\n\n```javascript\n// A function to print arrays for a selected pixel in the following examples.\nfunction sampArrImg(arrImg) {\n var point = ee.Geometry.Point([-121, 42]);\n return arrImg.sample(point, 500).first().get('array');\n}\n\n// A 1D array image.\nvar arrayImg1D = ee.Image([0, 1, 2]).toArray();\nprint('1D array image (pixel)', sampArrImg(arrayImg1D));\n// [0, 1, 2]\n\n// Define image band names for a 1D array image with 3 rows. You are labeling\n// all rows and columns using a list of lists; the 1st sub list defines labels\n// for array rows and the 2nd (if applicable) defines labels for array columns.\nvar bandNames1D = [['row0', 'row1', 'row2']];\n\n// Flatten the 1D array image into an image with n bands equal to all\n// combinations of rows and columns. Here, we have 3 rows and 0 columns,\n// so the result will be a 3-band image.\nvar imgFrom1Darray = arrayImg1D.arrayFlatten(bandNames1D);\nprint('Image from 1D array', imgFrom1Darray);\n\n// Make a 2D array image by repeating the 1D array on 2-axis.\nvar arrayImg2D = arrayImg1D.arrayRepeat(1, 2);\nprint('2D array image (pixel)', sampArrImg(arrayImg2D));\n// [[0, 0],\n// [1, 1],\n// [2, 2]]\n\n// Define image band names for a 2D array image with 3 rows and 2 columns.\n// Recall that you are labeling all rows and columns using a list of lists;\n// The 1st sub list defines labels for array rows and the 2nd (if applicable)\n// defines labels for array columns.\nvar bandNames2D = [['row0', 'row1', 'row2'], ['col0', 'col1']];\n\n// Flatten the 2D array image into an image with n bands equal to all\n// combinations of rows and columns. Here, we have 3 rows and 2 columns,\n// so the result will be a 6-band image.\nvar imgFrom2Darray = arrayImg2D.arrayFlatten(bandNames2D);\nprint('Image from 2D array', imgFrom2Darray);\n```\nPython setup\n\nSee the [Python Environment](/earth-engine/guides/python_install) page for information on the Python API and using\n`geemap` for interactive development. \n\n```python\nimport ee\nimport geemap.core as geemap\n```\n\n### Colab (Python)\n\n```python\n# A function to print arrays for a selected pixel in the following examples.\ndef samp_arr_img(arr_img):\n point = ee.Geometry.Point([-121, 42])\n return arr_img.sample(point, 500).first().get('array')\n\n# A 1D array image.\narray_img_1d = ee.Image([0, 1, 2]).toArray()\nprint('1D array image (pixel):', samp_arr_img(array_img_1d).getInfo())\n# [0, 1, 2]\n\n# Define image band names for a 1D array image with 3 rows. You are labeling\n# all rows and columns using a list of lists; the 1st sub list defines labels\n# for array rows and the 2nd (if applicable) defines labels for array columns.\nband_names_1d = [['row0', 'row1', 'row2']]\n\n# Flatten the 1D array image into an image with n bands equal to all\n# combinations of rows and columns. Here, we have 3 rows and 0 columns,\n# so the result will be a 3-band image.\nimg_from_1d_array = array_img_1d.arrayFlatten(band_names_1d)\nprint('Image from 1D array:', img_from_1d_array.getInfo())\n\n# Make a 2D array image by repeating the 1D array on 2-axis.\narray_img_2d = array_img_1d.arrayRepeat(1, 2)\nprint('2D array image (pixel):', samp_arr_img(array_img_2d).getInfo())\n# [[0, 0],\n# [1, 1],\n# [2, 2]]\n\n# Define image band names for a 2D array image with 3 rows and 2 columns.\n# Recall that you are labeling all rows and columns using a list of lists;\n# The 1st sub list defines labels for array rows and the 2nd (if applicable)\n# defines labels for array columns.\nband_names_2d = [['row0', 'row1', 'row2'], ['col0', 'col1']]\n\n# Flatten the 2D array image into an image with n bands equal to all\n# combinations of rows and columns. Here, we have 3 rows and 2 columns,\n# so the result will be a 6-band image.\nimg_from_2d_array = array_img_2d.arrayFlatten(band_names_2d)\nprint('Image from 2D array:', img_from_2d_array.getInfo())\n```"]]
