Return the maximum value that can be represented by the dtype of an object in Numpy



To return the maximum value that can be represented by the dtype of an object, use the ma.minimum_fill_value() method in Python Numpy. This function is useful for calculating a fill value suitable for taking the minimum of an array with a given dtype. It returns the maximum representable value.

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, 76], [73, 88, 51], [62, 45, 67]])
print("Array...
", arr)

Create a masked array and mask some of them as invalid −

maskArr = ma.masked_array(arr, mask =[[1, 1, 0], [ 0, 0, 0], [0, 1, 0], [0, 1, 0]])
print("
Our Masked Array...
", maskArr)

Get the type of the masked array −

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("
Number of elements in the Masked Array...
",maskArr.size)

To return the maximum value that can be represented by the dtype of an object, use the ma.minimum_fill_value() method in Python Numpy. This function is useful for calculating a fill value suitable for taking the minimum of an array with a given dtype:

print("
Result..
",np.ma.minimum_fill_value(maskArr))

Example

# Python ma.MaskedArray - Return the maximum value that can be represented by the dtype of an object

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, 76], [73, 88, 51], [62, 45, 67]])
print("Array...
", arr) # Create a masked array and mask some of them as invalid maskArr = ma.masked_array(arr, mask =[[1, 1, 0], [ 0, 0, 0], [0, 1, 0], [0, 1, 0]]) print("
Our Masked Array...
", maskArr) # Get the type of the masked array 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("
Number of elements in the Masked Array...
",maskArr.size) # To return the maximum value that can be represented by the dtype of an object, use the ma.minimum_fill_value() method in Python Numpy # This function is useful for calculating a fill value suitable for taking the minimum of an array with a given dtype # It returns the maximum representable value. print("
Result..
",np.ma.minimum_fill_value(maskArr))

Output

Array...
[[65 68 81]
[93 33 76]
[73 88 51]
[62 45 67]]

Our Masked Array...
[[-- -- 81]
[93 33 76]
[73 -- 51]
[62 -- 67]]

Our Masked Array type...
int64

Our Masked Array Dimensions...
2

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

Number of elements in the Masked Array...
12
Result..
9223372036854775807

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