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Get the itemsize of the masked array in Numpy
To get the itemsize of the Masked Array, use the ma.MaskedArray.itemsize attribute in Numpy. A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether the value is valid or not.
Steps
At first, import the required library −
import numpy as np import numpy.ma as ma
Create a numpy array using the numpy.array() method −
arr = np.array([[35, 85], [67, 33]])
print("Array...
", arr)
print("
Array type...
", arr.dtype)
print("
Array itemsize...
", arr.itemsize)Get the dimensions of the Array −
print("Array Dimensions...
",arr.ndim)
Create a masked array and mask some of them as invalid −
maskArr = ma.masked_array(arr, mask =[[0, 0], [ 0, 1]])
print("
Our Masked Array
", maskArr)
print("
Our Masked Array type...
", maskArr.dtype)Get the dimensions of the Masked Array −
print("
Our Masked Array Dimensions...
",maskArr.ndim)
To get the itemsize of the Masked Array, use the ma.MaskedArray.itemsize attribute in Numpy −
print("
Our Masked Array itemsize...
", maskArr.itemsize)Example
import numpy as np
import numpy.ma as ma
# Create a numpy array using the numpy.array() method
arr = np.array([[35, 85], [67, 33]])
print("Array...
", arr)
print("
Array type...
", arr.dtype)
print("
Array itemsize...
", arr.itemsize)
# Get the dimensions of the Array
print("Array Dimensions...
",arr.ndim)
# Create a masked array and mask some of them as invalid
maskArr = ma.masked_array(arr, mask =[[0, 0], [ 0, 1]])
print("
Our Masked Array
", maskArr)
print("
Our Masked Array type...
", maskArr.dtype)
# Get the dimensions of the Masked Array
print("
Our Masked Array Dimensions...
",maskArr.ndim)
# To get the itemsize of the Masked Array, use the ma.MaskedArray.itemsize attribute in Numpy
print("
Our Masked Array itemsize...
", maskArr.itemsize)Output
Array... [[35 85] [67 33]] Array type... int64 Array itemsize... 8 Array Dimensions... 2 Our Masked Array [[35 85] [67 --]] Our Masked Array type... int64 Our Masked Array Dimensions... 2 Our Masked Array itemsize... 8
Updated on: 21-Feb-2022
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