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法律研究在 NumPy 中計算連續元素之間的差值並新增和追加數字陣列
要計算掩碼陣列中連續元素之間的差異，請在 Python NumPy 中使用 **MaskedArray.ediff1d()** 方法。
“**to_begin**”引數設定要新增到返回的差異開頭處的數字陣列。“**to_end**”引數設定要新增到返回的差異末尾處的數字陣列。
掩碼陣列是標準 numpy.ndarray 和掩碼的組合。掩碼要麼是 nomask，表示關聯陣列的任何值均無效，要麼是布林值陣列，用於確定關聯陣列的每個元素的值是否有效。
步驟
首先，匯入所需的庫 -
import numpy as np import numpy.ma as ma
使用 numpy.array() 方法建立具有整數元素的陣列 -
arr = np.array([[65, 68, 81], [93, 33, 76], [73, 88, 51], [62, 45, 67]])
print("Array...
", arr)建立掩碼陣列並掩蓋其中一些為無效 -
maskArr = ma.masked_array(arr, mask =[[1, 0, 0], [ 0, 0, 0], [0, 1, 0], [0, 0, 0]])
print("
Our Masked Array...
", maskArr)獲取掩碼陣列的型別 -
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("
Number of elements in the Masked Array...
",maskArr.size)要計算掩碼陣列中連續元素之間的差異，請使用 MaskedArray.ediff1d() -
prepArr = np.array([-4, -3, -2, -1])
appeArr = np.array([997, 998, 999])
print("
Result..
.", np.ediff1d(maskArr, to_begin = prepArr, to_end=appeArr))示例
# Python ma.MaskedArray - Compute the differences between consecutive elements
# and prepend & append array of numbers
import numpy as np
import numpy.ma as ma
# Create an array with int elements using the numpy.array() method
arr = np.array([[65, 68, 81], [93, 33, 76], [73, 88, 51], [62, 45, 67]])
print("Array...
", arr)
# Create a masked array and mask some of them as invalid
maskArr = ma.masked_array(arr, mask =[[1, 0, 0], [ 0, 0, 0], [0, 1, 0], [0, 0, 0]])
print("
Our Masked Array...
", maskArr)
# Get the type of the masked array
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("
Number of elements in the Masked Array...
",maskArr.size)
# To compute the differences between consecutive elements of a masked array, use the MaskedArray.ediff1d() method in Python Numpy
# The "to_begin" parameter sets the array of number(s) to prepend at the start of the returned differences.
# The "to_end" parameter sets the array of number(s) to append at theend of the returned differences.
prepArr = np.array([-4, -3, -2, -1])
appeArr = np.array([997, 998, 999])
print("
Result..
.", np.ediff1d(maskArr, to_begin = prepArr, to_end=appeArr))輸出
Array... [[65 68 81] [93 33 76] [73 88 51] [62 45 67]] Our Masked Array... [[-- 68 81] [93 33 76] [73 -- 51] [62 45 67]] Our Masked Array type... int64 Our Masked Array Dimensions... 2 Our Masked Array Shape... (4, 3) Number of elements in the Masked Array... 12 Result.. [ -4 -3 -2 -1 3 13 12 -60 43 -3 15 -37 11 -17 22 997 998 999]
更新於: 2022年2月3日
89 次瀏覽
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