# Return range of values from the masked array for each row in Numpy

To return the range of values from a masked array, use the ma.MaskedArray.ptp() method in Numpy. Peak to peak (maximum - minimum) value along a given axis.

The ptp() method returns a new array holding the result, unless out was specified, in which case a reference to out is returned.

The axis parameter is the axis along which to find the peaks. If None (default) the flattened array is used. The out is a parameter, an alternative output array in which to place the result. It must have the same shape and buffer length as the expected output but the type will be cast if necessary.

The keepdims parameter, if set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the array.

## 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([[49, 85, 45], [67, 33, 59]])
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 =[[0, 0, 1], [ 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)


To return the range of values from a masked array, use the ma.MaskedArray.ptp() method in Numpy. Peak to peak (maximum - minimum) value along a given axis. The axis is set using the axis parameter. The value 1 gets the range of values for each row −

print("Peak to peak value (max - min) for each row...", np.ptp(maskArr, axis=1))

## Example

# Python ma.MaskedArray - Return range of values from the masked array for each row

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]])

# Get the dimensions of the Masked Array

# Get the shape of the Masked Array

# Get the number of elements of the Masked Array

# To return the range of values from a masked array, use the ma.MaskedArray.ptp() method in Numpy.
# Peak to peak (maximum - minimum) value along a given axis.
# The axis is set using the axis parameter
# The value 1 gets the range of values for each row
print("Peak to peak value (max - min) for each row...",np.ptp(maskArr, axis=1))

## Output

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

Array type...
int64

Array Dimensions...
2

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

int64

[16 34 59 43]