# Check which element in a masked array is less than or equal to a given value in Numpy

To check which element in a masked array is less than or equal to a given value, use the ma.MaskedArray.__le__() method. Returns with boolean type i.e. True and False. 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.

NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. It supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries.

## 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([[55, 85, 68, 84], [67, 33, 39, 53], [29, 88, 51, 37], [56, 45, 99, 85]])
print("Array...", arr)
print("Array type...", arr.dtype)

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 =[[1, 1, 0, 0], [ 0, 0, 1, 0], [0, 0, 0, 1], [0, 1, 0, 0]])
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)

Get the shape of the Masked Array −

print("Our Masked Array Shape...",maskArr.shape)

Get the number of elements of the Masked Array −

print("Elements in the Masked Array...",maskArr.size)


The value to be compared −

val = 61
print("The given value to be compared with the masked array elements...",val)

To check which element in a masked array is less than or equal to a given value, use the ma.MaskedArray.__le__() method. Returns with boolean type i.e. True and False. True is returned for every array element less than or equal to a given value val −

print("Display True for each element less than or equal to a given value val...", maskArr.__le__(val))

## Example

import numpy as np
import numpy.ma as ma

# Create an array with int elements using the numpy.array() method
arr = np.array([[55, 85, 68, 84], [67, 33, 39, 53], [29, 88, 51, 37], [56, 45, 99, 85]])
print("Array...", arr)
print("Array type...", arr.dtype)

# 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 =[[1, 1, 0, 0], [ 0, 0, 1, 0], [0, 0, 0, 1], [0, 1, 0, 0]])
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)

# Get the shape of the Masked Array
print("Our Masked Array Shape...",maskArr.shape)

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

# The value to be compared
val = 61
print("The given value to be compared with the masked array elements...",val)

# To check which element in a masked array is less than or equal to a given value, use the ma.MaskedArray.__le__() method
# Returns with boolean type i.e. True and False.
# True is returned for every array element less than or equal to a given value val
print("Display True for each element less than or equal to a given value val...", maskArr.__le__(val))

## Output

Array...
[[55 85 68 84]
[67 33 39 53]
[29 88 51 37]
[56 45 99 85]]

Array type...
int64

Array Dimensions...
2

Our Masked Array
[[-- -- 68 84]
[67 33 -- 53]
[29 88 51 --]
[56 -- 99 85]]

Our Masked Array type...
int64

Our Masked Array Dimensions...
2

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

Elements in the Masked Array...
16

The given value to be compared with the masked array elements...
61

Display True for each element less than or equal to a given value val...
[[-- -- False False]
[False True -- True]
[True False True --]
[True -- False False]]

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