Convert inputs to arrays with at least two dimensions in Numpy

NumpyServer Side ProgrammingProgramming

To convert inputs to arrays with at least two dimensions, use the ma.atleast_2d() method in Python Numpy. The parameters are One or more array-like sequences. Non-array inputs are converted to arrays. Arrays that already have two or more dimensions are preserved.

The method returns an array, or list of arrays, each with a.ndim >= 2. Copies are avoided where possible, and views with two or more dimensions are returned.

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, 39], [73, 88, 51], [62, 45, 67]])
print("Array...\n", arr)
print("\nArray type...\n", arr.dtype)

Get the dimensions of the Array −

print("\nArray Dimensions...\n",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("\nOur Masked Array\n", maskArr)
print("\nOur Masked Array type...\n", maskArr.dtype)

Get the dimensions of the Masked Array −

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

Get the shape of the Masked Array −

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

Get the number of elements of the Masked Array −

print("\nElements in the Masked Array...\n",maskArr.size)

To convert inputs to arrays with at least two dimensions, use the ma.atleast_2d() method in Python Numpy −

print("\nResult...\n",np.atleast_2d(1, maskArr))

Example

# Python ma.MaskedArray - Convert inputs to arrays with at least two dimensions

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, 39], [73, 88, 51], [62, 45, 67]])
print("Array...\n", arr)
print("\nArray type...\n", arr.dtype)

# Get the dimensions of the Array
print("\nArray Dimensions...\n",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("\nOur Masked Array\n", maskArr)
print("\nOur Masked Array type...\n", maskArr.dtype)

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

# Get the shape of the Masked Array
print("\nOur Masked Array Shape...\n",maskArr.shape)

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

# To convert inputs to arrays with at least two dimensions, use the ma.atleast_2d() method in Python Numpy
print("\nResult...\n",np.atleast_2d(1, maskArr))

Output

Array...
[[65 68 81]
[93 33 39]
[73 88 51]
[62 45 67]]

Array type...
int64

Array Dimensions...
2
Our Masked Array
[[-- -- 81]
[-- 33 39]
[73 -- 51]
[62 -- 67]]

Our Masked Array type...
int64

Our Masked Array Dimensions...
2

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

Elements in the Masked Array...
12

Result...
[array([[1]]), masked_array(
data=[[--, --, 81],
   [--, 33, 39],
   [73, --, 51],
   [62, --, 67]],
mask=[[ True, True, False],
   [ True, False, False],
   [False, True, False],
   [False, True, False]],
fill_value=999999)]
raja
Updated on 03-Feb-2022 12:05:32

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