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Create a boolean mask from an array in Numpy
To create a boolean mask from an array, use the ma.make_mask() method in Python Numpy. The function can accept any sequence that is convertible to integers, or nomask. Does not require that contents must be 0s and 1s, values of 0 are interpreted as False, everything else as True.
The dtype is the data-type of the output mask. By default, the output mask has a dtype of MaskType (bool). If the dtype is flexible, each field has a boolean dtype. This is ignored when m is nomask, in which case nomask is always returned.
Steps
At first, import the required library −
import numpy as np import numpy.ma as ma
Create an array with zeros using the numpy.zeros() method in Python Numpy −
arr = np.zeros(7)
print("Array...
", arr)To Create a boolean mask from an array, use the ma.make_mask() method in Python Numpy −
print("
Masked Array...
", ma.make_mask(arr))
Type of Array −
print("
Array type...
", arr.dtype)Get the dimensions of the Array −
print("
Array Dimensions...
",arr.ndim)
Get the shape of the Array −
print("
Our Array Shape...
",arr.shape)Get the number of elements of the Array −
print("
Elements in the Array...
",arr.size)
Example
import numpy as np
import numpy.ma as ma
# Create an array with zeros using the numpy.zeros() method in Python Numpy
arr = np.zeros(7)
print("Array...
", arr)
# To Create a boolean mask from an array, use the ma.mask_mask() method in Python Numpy
print("
Masked Array...
", ma.make_mask(arr))
# Type of Array
print("
Array type...
", arr.dtype)
# Get the dimensions of the Array
print("
Array Dimensions...
",arr.ndim)
# Get the shape of the Array
print("
Our Array Shape...
",arr.shape)
# Get the number of elements of the Array
print("
Elements in the Array...
",arr.size)Output
Array... [0. 0. 0. 0. 0. 0. 0.] Masked Array... False Array type... float64 Array Dimensions... 1 Our Array Shape... (7,) Elements in the Array... 7
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