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Set storage-indexed locations to corresponding values and clip out-of-bounds indices to range in Numpy
To set storage-indexed locations to corresponding values, use the ma.MaskedArray.put() method in Numpy. The "mode" parameter specifies how out-of-bounds indices will behave. Sets self._data.flat[n] = values[n] for each n in indices. If values is shorter than indices then it will repeat. If values has some masked values, the initial mask is updated in consequence, else the corresponding values are unmasked.
The indices are the target indices, interpreted as integers. The mode specifies how out-of-bounds indices will behave. ‘raise’ : raise an error. ‘wrap’ : wrap around. ‘clip’ : clip to the range.
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([[55, 85, 59, 77], [67, 33, 39, 57], [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]])
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 set storage-indexed locations to corresponding values, use the ma.MaskedArray.put() method in Numpy. The "mode" parameter is specify how out-of-bounds indices will behave. The value ‘raise’ : raise an error. ‘wrap’ : wrap around. ‘clip’: clip to the range. We have set an out-of-bounds indice here i.e. 32. The "clip" parameter will clip to range −
maskArr.put([1, 5, 25, 27, 8],[99, 88, 33, 55, 66], mode = 'clip')
print("
Result...
",maskArr)Example
# Python ma.MaskedArray - Set storage-indexed locations to corresponding values and clip out-of-bounds indices to range
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, 59, 77], [67, 33, 39, 57], [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]])
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 set storage-indexed locations to corresponding values, use the ma.MaskedArray.put() method in Numpy
# The "mode" parameter specifies how out-of-bounds indices will behave.
# The value ‘raise’ : raise an error. ‘wrap’ : wrap around. ‘clip’ : clip to the range.
# We have set an out-of-bounds indice here i.e. 32
# The "clip" parameter will clip to range maskArr.put([1, 5, 25, 27, 8],[99, 88, 33, 55, 66], mode = 'clip')
print("
Result...
",maskArr)Output
Array... [[55 85 59 77] [67 33 39 57] [29 88 51 37] [56 45 99 85]] Array type... int64 Array Dimensions... 2 Our Masked Array [[-- -- 59 77] [67 33 -- 57] [29 88 51 --] [56 -- 99 85]] Our Masked Array type... int64 Our Masked Array Dimensions... 2 Our Masked Array Shape... (4, 4) Elements in the Masked Array... 16 Result... [[-- 99 59 77] [67 88 -- 57] [66 88 51 --] [56 -- 99 55]]
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