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Transform a masked array into a flexibletype array with torecords() in Numpy
To transform a masked array into a flexible-type array, use the ma.MaskedArray.torecords(). The flexible type array that is returned will have two fields
The _data field stores the _data part of the array.
The _mask field stores the _mask part of the array.method in Numpy.
Returns a new flexible-type ndarray with two fields − the first element containing a value, the second element containing the corresponding mask boolean. The returned record shape matches self.shape.
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
", maskArr)
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)
Transform a masked array into a flexible-type array, use the ma.MaskedArray.torecords() method in Numpy. The flexible type array that is returned will have two fields: the _data field stores the _data part of the array −
print("
Result of the transformation...
",maskArr.torecords())Example
# Python - Transform a masked array into a flexible-type array with MaskedArray.torecords()
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
", maskArr)
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 transform a masked array into a flexible-type array, use the ma.MaskedArray.torecords() method in Numpy
# The flexible type array that is returned will have two fields: the _data field stores the _data part of the array.
#, the _mask field stores the _mask part of the array.
print("
Result of the transformation...
",maskArr.torecords())Output
Array... [[49 85 45] [67 33 59]] Array type... int64 Array Dimensions... 2 Our Masked Array [[49 85 --] [67 -- 59]] Our Masked Array type... int64 Our Masked Array Dimensions... 2 Our Masked Array Shape... (2, 3) Elements in the Masked Array... 6 Result of the transformation... [[(49, False) (85, False) (45, True)] [(67, False) (33, True) (59, False)]]
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