# True Divide each element of a masked Array by a scalar value in-place in Numpy

To true divide each element of a masked Array by a scalar value in-place, use the ma.MaskedArray.__itruediv__() method in Python 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.

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 float elements using the numpy.array() method −

arr = np.array([[65.5, 68.3, 81.2], [93.7, 33.8, 39.5], [73.4, 88.3, 51.9], [62.2, 45.5, 67.9]])
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], [ 1, 0, 0], [0, 1, 0], [0, 1, 0]])
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 scalar −

val = 7
print("The given value...",val)

To true divide each element of a masked Array by a scalar value in-place, use the ma.MaskedArray.__itruediv__() method −

print("Resultant Masked Array...",maskArr.__itruediv__(val))


## Example

import numpy as np
import numpy.ma as ma

# Create an array with float elements using the numpy.array() method
arr = np.array([[65.5, 68.3, 81.2], [93.7, 33.8, 39.5], [73.4,88.3, 51.9], [62.2, 45.5, 67.9]])
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], [ 1, 0, 0], [0, 1, 0], [0, 1, 0]])

# Get the dimensions of the Masked Array

# Get the shape of the Masked Array

# Get the number of elements of the Masked Array
# The scalar
val = 7
print("The given value...",val)

# To true divide each element of a masked Array by a scalar value in-place, use the ma.MaskedArray.__itruediv__() method
print("Resultant Masked Array...",maskArr.__itruediv__(val))

## Output

Array...
[[65.5 68.3 81.2]
[93.7 33.8 39.5]
[73.4 88.3 51.9]
[62.2 45.5 67.9]]

Array type...
float64

Array Dimensions...
2

[[-- -- 81.2]
[-- 33.8 39.5]
[73.4 -- 51.9]
[62.2 -- 67.9]]

float64

2

(4, 3)

[8.885714285714286 -- 9.700000000000001]]