Initialize the mask to homogeneous boolean array by passing in a scalar boolean value in Numpy



The mask is initialized to homogeneous boolean array with the same shape as data by passing in a scalar boolean value. True indicates a masked (i.e. invalid) data. The "mask" parameter is used to set the mask. Create a masked array using the ma.MaskedArray() method.

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 an array with int elements using the numpy.array() method −

arr = np.array([[65, 68, 81], [93, 33, 39], [73, 88, 51], [62, 45, 67]])
print("Array...\n", arr)
print("\nArray type...\n", arr.dtype)

Get the dimensions of the Array −

print("\nArray Dimensions...\n",arr.ndim)

Create a masked array. The "mask" parameter is used to set the mask. The mask is initialized to homogeneous boolean array with the same shape as data by passing in a scalar boolean value. True indicates a masked (i.e. invalid) data:

maskArr = ma.MaskedArray(arr, mask =True)
print("\nOur Masked Array\n", maskArr)
print("\nOur Masked Array type...\n", maskArr.dtype)

Get the dimensions of the Masked Array −

print("\nOur Masked Array Dimensions...\n",maskArr.ndim)

Get the shape of the Masked Array −

print("\nOur Masked Array Shape...\n",maskArr.shape)

Get the number of elements of the Masked Array −

print("\nElements in the Masked Array...\n",maskArr.size)

Example

# Python ma.MaskedArray - Initialize the mask to homogeneous boolean array by passing in a scalar boolean value

import numpy as np
import numpy.ma as ma

# Create an array with int elements using the numpy.array() method
arr = np.array([[65, 68, 81], [93, 33, 39], [73, 88, 51], [62, 45, 67]])
print("Array...\n", arr)
print("\nArray type...\n", arr.dtype)

# Get the dimensions of the Array
print("\nArray Dimensions...\n",arr.ndim)

# Create a masked array
# The mask is set using the "mask" parameter
# The mask initialized to homogeneous boolean array with the same shape as data by passing in a scalar boolean value:
# True indicates a masked (i.e. invalid) data.
maskArr = ma.MaskedArray(arr, mask =True)
print("\nOur Masked Array\n", maskArr)
print("\nOur Masked Array type...\n", maskArr.dtype)

# Get the dimensions of the Masked Array
print("\nOur Masked Array Dimensions...\n",maskArr.ndim)

# Get the shape of the Masked Array
print("\nOur Masked Array Shape...\n",maskArr.shape)

# Get the number of elements of the Masked Array
print("\nElements in the Masked Array...\n",maskArr.size)

Output

Array...
[[65 68 81]
[93 33 39]
[73 88 51]
[62 45 67]]

Array type...
int64

Array Dimensions...
2
Our Masked Array
[[-- -- --]
[-- -- --]
[-- -- --]
[-- -- --]]

Our Masked Array type...
int64

Our Masked Array Dimensions...
2

Our Masked Array Shape...
(4, 3)

Elements in the Masked Array...
12
raja
Updated on 03-Feb-2022 10:54:08

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