Get the information about the memory layout of the masked array in Numpy

NumpyServer Side ProgrammingProgramming

To get the information about the memory layout of the masked array, use the ma.MaskedArray.flags in Numpy. Masked arrays are arrays that may have missing or invalid entries. The numpy.ma module provides a nearly work-alike replacement for numpy that supports data arrays with masks.

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 a numpy array using the numpy.array() method −

arr = np.array([[35, 85], [67, 33]])
print("Array...\n", arr)
print("\nArray type...\n", arr.dtype)

Get the dimensions of the Array −

print("Array Dimensions...",arr.ndim)

Get the information about the memory layout of the array −

print("\nArray flags...\n",arr.flags)

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

maskArr = ma.masked_array(arr, mask =[[0, 0], [ 0, 1]])
print("\nOur Masked Array\n", maskArr)
print("\nOur Masked Array type...\n", maskArr.dtype)

Get the dimensions of the Masked Array −

print(" Our Masked Array Dimensions...",maskArr.ndim)

To get the information about the memory layout of the masked array, use the ma.MaskedArray.flags in Numpy −

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

Example

import numpy as np
import numpy.ma as ma

# Create a numpy array using the numpy.array() method
arr = np.array([[35, 85], [67, 33]])
print("Array...\n", arr)
print("\nArray type...\n", arr.dtype)

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

# Get the information about the memory layout of the array
print("\nArray flags...\n",arr.flags)

# Create a masked array and mask some of them as invalid
maskArr = ma.masked_array(arr, mask =[[0, 0], [ 0, 1]])
print("\nOur Masked Array\n", maskArr)
print("\nOur Masked Array type...\n", maskArr.dtype)

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

# To get the information about the memory layout of the masked array, use the ma.MaskedArray.flags in Numpy
print("\nOur Masked Array flags...\n",maskArr.flags)

Output

Array...
[[35 85]
[67 33]]

Array type...
int64
Array Dimensions... 2

Array flags...
C_CONTIGUOUS : True
F_CONTIGUOUS : False
OWNDATA : True
WRITEABLE : True
ALIGNED : True
WRITEBACKIFCOPY : False
UPDATEIFCOPY : False


Our Masked Array
[[35 85]
[67 --]]

Our Masked Array type...
int64
Our Masked Array Dimensions... 2

Our Masked Array flags...
C_CONTIGUOUS : True
F_CONTIGUOUS : False
OWNDATA : False
WRITEABLE : True
ALIGNED : True
WRITEBACKIFCOPY : False
UPDATEIFCOPY : False
raja
Updated on 21-Feb-2022 10:59:02

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