ee.Image.arrayMask
संग्रह की मदद से व्यवस्थित रहें
अपनी प्राथमिकताओं के आधार पर, कॉन्टेंट को सेव करें और कैटगरी में बांटें.
यह फ़ंक्शन, ऐरे इमेज बनाता है. इसमें ऐरे वैल्यू वाले हर पिक्सल को ऐरे वैल्यू वाले दूसरे पिक्सल से मास्क किया जाता है. इसमें सिर्फ़ वे एलिमेंट शामिल होते हैं जहां मास्क की वैल्यू शून्य नहीं होती. अगर मास्क इमेज में एक बैंड है, तो इसे 'input' के सभी बैंड पर लागू किया जाएगा. अगर ऐसा नहीं है, तो उनमें बैंड की संख्या एक जैसी होनी चाहिए.
इस्तेमाल | रिटर्न |
---|
Image.arrayMask(mask) | इमेज |
आर्ग्यूमेंट | टाइप | विवरण |
---|
यह: input | इमेज | मास्क करने के लिए इमेज का कलेक्शन. |
mask | इमेज | मास्क करने के लिए ऐरे इमेज. |
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');
}
// Create a 1D array image with length 6.
var arrayImg1D = ee.Image([0, 1, 2, 4, 0, 5]).toArray();
print('1D array image (pixel)', sampArrImg(arrayImg1D));
// [0, 1, 2, 4, 0, 5]
// Create a mask using a relational operator to mask values greater than 2.
var mask1D = arrayImg1D.lte(2);
print('1D mask for greater than value 2 (pixel)', sampArrImg(mask1D));
// [1, 1, 1, 0, 1, 0]
var arrayImg1DMask = arrayImg1D.arrayMask(mask1D);
print('1D array image mask (pixel)', sampArrImg(arrayImg1DMask));
// [0, 1, 2, 0]
// Self mask the 1D array image. Value zero will be masked out.
var arrayImg1DselfMask = arrayImg1D.arrayMask(arrayImg1D);
print('1D array image self mask (pixel)', sampArrImg(arrayImg1DselfMask));
// [1, 2, 4, 5]
// Create a 2D array image.
var arrayImg2D = arrayImg1D.arrayReshape(ee.Image([2, 3]).toArray(), 2);
print('2D 2x3 array image (pixel)', sampArrImg(arrayImg2D));
// [[0, 1, 2],
// [4, 0, 5]]
// Slice out a row to use as a column mask.
var rowAsMaskForCols = arrayImg2D.arraySlice(0, 1, 2);
print('2D mask for cols (pixel)', sampArrImg(rowAsMaskForCols));
// [[4, 0, 5]]
var arrayImg2DMaskCols = arrayImg2D.arrayMask(rowAsMaskForCols);
print('2D array image cols masked (pixel)', sampArrImg(arrayImg2DMaskCols));
// [[0, 2],
// [4, 5]]
// Slice out a column to use as a row mask.
var colAsMaskForRows = arrayImg2D.arraySlice(1, 1, 2);
print('2D mask for rows (pixel)', sampArrImg(colAsMaskForRows));
// [[1],
// [0]]
var arrayImg2DMaskRows = arrayImg2D.arrayMask(colAsMaskForRows);
print('2D array image rows masked (pixel)', sampArrImg(arrayImg2DMaskRows));
// [[0, 1, 2]]
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')
# Create a 1D array image with length 6.
array_img_1d = ee.Image([0, 1, 2, 4, 0, 5]).toArray()
print('1D array image (pixel):', samp_arr_img(array_img_1d).getInfo())
# [0, 1, 2, 4, 0, 5]
# Create a mask using a relational operator to mask values greater than 2.
mask_1d = array_img_1d.lte(2)
print(
'1D mask for greater than value 2 (pixel):',
samp_arr_img(mask_1d).getInfo()
)
# [1, 1, 1, 0, 1, 0]
array_img1d_mask = array_img_1d.arrayMask(mask_1d)
print('1D array image mask (pixel):', samp_arr_img(array_img1d_mask).getInfo())
# [0, 1, 2, 0]
# Self mask the 1D array image. Value zero will be masked out.
array_img_1d_self_mask = array_img_1d.arrayMask(array_img_1d)
print(
'1D array image self mask (pixel):',
samp_arr_img(array_img_1d_self_mask).getInfo()
)
# [1, 2, 4, 5]
# Create a 2D array image.
array_img_2d = array_img_1d.arrayReshape(ee.Image([2, 3]).toArray(), 2)
print('2D 2x3 array image (pixel):', samp_arr_img(array_img_2d).getInfo())
# [[0, 1, 2],
# [4, 0, 5]]
# Slice out a row to use as a column mask.
row_as_mask_for_cols = array_img_2d.arraySlice(0, 1, 2)
print('2D mask for cols (pixel):', samp_arr_img(row_as_mask_for_cols).getInfo())
# [[4, 0, 5]]
array_img_2d_mask_cols = array_img_2d.arrayMask(row_as_mask_for_cols);
print(
'2D array image cols masked (pixel):',
samp_arr_img(array_img_2d_mask_cols).getInfo()
)
# [[0, 2],
# [4, 5]]
# Slice out a column to use as a row mask.
col_as_mask_for_rows = array_img_2d.arraySlice(1, 1, 2)
print('2D mask for rows (pixel):', samp_arr_img(col_as_mask_for_rows).getInfo())
# [[1],
# [0]]
array_img_2d_mask_rows = array_img_2d.arrayMask(col_as_mask_for_rows)
print(
'2D array image rows masked (pixel):',
samp_arr_img(array_img_2d_mask_rows).getInfo()
)
# [[0, 1, 2]]
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\u003earrayMask\u003c/code\u003e creates a masked array image by retaining elements where the mask image is non-zero.\u003c/p\u003e\n"],["\u003cp\u003eIt can be applied to 1D or 2D array images, using either single-band or multi-band masks.\u003c/p\u003e\n"],["\u003cp\u003eIf the mask has one band, it's applied to all bands of the input array image; otherwise, they must have the same number of bands.\u003c/p\u003e\n"],["\u003cp\u003eThe masking operation effectively filters out array elements corresponding to zero values in the mask.\u003c/p\u003e\n"],["\u003cp\u003eThis function is useful for selectively manipulating or analyzing specific elements within array images.\u003c/p\u003e\n"]]],[],null,["# ee.Image.arrayMask\n\nCreates an array image where each array-valued pixel is masked with another array-valued pixel, retaining only the elements where the mask is non-zero. If the mask image has one band it will be applied to all the bands of 'input', otherwise they must have the same number of bands.\n\n\u003cbr /\u003e\n\n| Usage | Returns |\n|-------------------------|---------|\n| Image.arrayMask`(mask)` | Image |\n\n| Argument | Type | Details |\n|---------------|-------|---------------------------|\n| this: `input` | Image | Array image to mask. |\n| `mask` | Image | Array image to mask with. |\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// Create a 1D array image with length 6.\nvar arrayImg1D = ee.Image([0, 1, 2, 4, 0, 5]).toArray();\nprint('1D array image (pixel)', sampArrImg(arrayImg1D));\n// [0, 1, 2, 4, 0, 5]\n\n// Create a mask using a relational operator to mask values greater than 2.\nvar mask1D = arrayImg1D.lte(2);\nprint('1D mask for greater than value 2 (pixel)', sampArrImg(mask1D));\n// [1, 1, 1, 0, 1, 0]\n\nvar arrayImg1DMask = arrayImg1D.arrayMask(mask1D);\nprint('1D array image mask (pixel)', sampArrImg(arrayImg1DMask));\n// [0, 1, 2, 0]\n\n// Self mask the 1D array image. Value zero will be masked out.\nvar arrayImg1DselfMask = arrayImg1D.arrayMask(arrayImg1D);\nprint('1D array image self mask (pixel)', sampArrImg(arrayImg1DselfMask));\n// [1, 2, 4, 5]\n\n// Create a 2D array image.\nvar arrayImg2D = arrayImg1D.arrayReshape(ee.Image([2, 3]).toArray(), 2);\nprint('2D 2x3 array image (pixel)', sampArrImg(arrayImg2D));\n// [[0, 1, 2],\n// [4, 0, 5]]\n\n// Slice out a row to use as a column mask.\nvar rowAsMaskForCols = arrayImg2D.arraySlice(0, 1, 2);\nprint('2D mask for cols (pixel)', sampArrImg(rowAsMaskForCols));\n// [[4, 0, 5]]\n\nvar arrayImg2DMaskCols = arrayImg2D.arrayMask(rowAsMaskForCols);\nprint('2D array image cols masked (pixel)', sampArrImg(arrayImg2DMaskCols));\n// [[0, 2],\n// [4, 5]]\n\n// Slice out a column to use as a row mask.\nvar colAsMaskForRows = arrayImg2D.arraySlice(1, 1, 2);\nprint('2D mask for rows (pixel)', sampArrImg(colAsMaskForRows));\n// [[1],\n// [0]]\n\nvar arrayImg2DMaskRows = arrayImg2D.arrayMask(colAsMaskForRows);\nprint('2D array image rows masked (pixel)', sampArrImg(arrayImg2DMaskRows));\n// [[0, 1, 2]]\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# Create a 1D array image with length 6.\narray_img_1d = ee.Image([0, 1, 2, 4, 0, 5]).toArray()\nprint('1D array image (pixel):', samp_arr_img(array_img_1d).getInfo())\n# [0, 1, 2, 4, 0, 5]\n\n# Create a mask using a relational operator to mask values greater than 2.\nmask_1d = array_img_1d.lte(2)\nprint(\n '1D mask for greater than value 2 (pixel):',\n samp_arr_img(mask_1d).getInfo()\n)\n# [1, 1, 1, 0, 1, 0]\n\narray_img1d_mask = array_img_1d.arrayMask(mask_1d)\nprint('1D array image mask (pixel):', samp_arr_img(array_img1d_mask).getInfo())\n# [0, 1, 2, 0]\n\n# Self mask the 1D array image. Value zero will be masked out.\narray_img_1d_self_mask = array_img_1d.arrayMask(array_img_1d)\nprint(\n '1D array image self mask (pixel):',\n samp_arr_img(array_img_1d_self_mask).getInfo()\n)\n# [1, 2, 4, 5]\n\n# Create a 2D array image.\narray_img_2d = array_img_1d.arrayReshape(ee.Image([2, 3]).toArray(), 2)\nprint('2D 2x3 array image (pixel):', samp_arr_img(array_img_2d).getInfo())\n# [[0, 1, 2],\n# [4, 0, 5]]\n\n# Slice out a row to use as a column mask.\nrow_as_mask_for_cols = array_img_2d.arraySlice(0, 1, 2)\nprint('2D mask for cols (pixel):', samp_arr_img(row_as_mask_for_cols).getInfo())\n# [[4, 0, 5]]\n\narray_img_2d_mask_cols = array_img_2d.arrayMask(row_as_mask_for_cols);\nprint(\n '2D array image cols masked (pixel):',\n samp_arr_img(array_img_2d_mask_cols).getInfo()\n)\n# [[0, 2],\n# [4, 5]]\n\n# Slice out a column to use as a row mask.\ncol_as_mask_for_rows = array_img_2d.arraySlice(1, 1, 2)\nprint('2D mask for rows (pixel):', samp_arr_img(col_as_mask_for_rows).getInfo())\n# [[1],\n# [0]]\n\narray_img_2d_mask_rows = array_img_2d.arrayMask(col_as_mask_for_rows)\nprint(\n '2D array image rows masked (pixel):',\n samp_arr_img(array_img_2d_mask_rows).getInfo()\n)\n# [[0, 1, 2]]\n```"]]