使用 NumPy 中的 torecords() 將掩碼陣列轉換為靈活型別陣列
要將掩碼陣列轉換為靈活型別陣列,請使用 **ma.MaskedArray.torecords()**。返回的靈活型別陣列將有兩個欄位
_data 欄位儲存陣列的 _data 部分。
_mask 欄位儲存陣列的 _mask 部分。
返回一個新的具有兩個欄位的靈活型別 ndarray - 第一個元素包含一個值,第二個元素包含相應的掩碼布林值。返回的記錄形狀與 self.shape 匹配。
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([[49, 85, 45], [67, 33, 59]])
print("Array...
", arr)
print("
Array type...
", arr.dtype)獲取陣列的維度 -
print("Array Dimensions...
",arr.ndim)建立一個掩碼陣列並將其中的某些元素標記為無效 -
maskArr = ma.masked_array(arr, mask =[[0, 0, 1], [ 0, 1, 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數量 -
print("
Elements in the Masked Array...
",maskArr.size)
要將掩碼陣列轉換為靈活型別陣列,請使用 NumPy 中的 ma.MaskedArray.torecords() 方法。返回的靈活型別陣列將有兩個欄位:_data 欄位儲存陣列的 _data 部分 -
print("
Result of the transformation...
",maskArr.torecords())示例
# 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())輸出
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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