返回NumPy中掩碼陣列元素的標準差
要返回掩碼陣列元素的標準差,請在Python NumPy中使用**ma.MaskedArray.std()**。返回標準差,這是衡量分佈分散程度的指標。預設情況下,標準差是針對扁平化陣列計算的,否則是在指定的軸上計算。
axis引數是計算標準差的軸或軸集。預設情況下,計算扁平化陣列的標準差。如果這是一個整數元組,則會對多個軸執行標準差,而不是像以前那樣對單個軸或所有軸執行。
dtype是用於計算標準差的型別。對於整數型別陣列,預設值為float64;對於浮點型別陣列,它與陣列型別相同。
步驟
首先,匯入所需的庫:
import numpy as np import numpy.ma as ma
使用numpy.array()方法建立一個包含整數元素的陣列:
arr = np.array([[55, 85, 68, 84], [67, 33, 39, 53], [29, 88, 51, 37], [56, 45, 99, 85]])
print("Array...
", arr)獲取陣列的維度:
print("Array Dimensions...
",arr.ndim)
建立一個掩碼陣列,並將其中一些標記為無效:
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)獲取掩碼陣列的維度:
print("
Our Masked Array Dimensions...
",maskArr.ndim)
獲取掩碼陣列的形狀:
print("
Our Masked Array Shape...
",maskArr.shape)獲取掩碼陣列的元素個數:
print("
Elements in the Masked Array...
",maskArr.size)
要返回掩碼陣列元素的標準差,請在NumPy中使用ma.MaskedArray.std():
res = maskArr.std()
print("
Result..
.", res)示例
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, 68, 84], [67, 33, 39, 53], [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 return the standard deviation of the masked array elements, use the ma.MaskedArray.std() in Numpy
res = maskArr.std()
print("
Result..
.", res)輸出
Array... [[55 85 68 84] [67 33 39 53] [29 88 51 37] [56 45 99 85]] Array type... int64 Array Dimensions... 2 Our Masked Array [[-- -- 68 84] [67 33 -- 53] [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.. . 21.74153202688424
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