在 NumPy 中计算连续元素之间的差值并添加和追加数字数组

要计算掩码数组中连续元素之间的差异，请在 Python NumPy 中使用 **MaskedArray.ediff1d()** 方法。

“**to_begin**”参数设置要添加到返回的差异开头处的数字数组。“**to_end**”参数设置要添加到返回的差异末尾处的数字数组。

掩码数组是标准 numpy.ndarray 和掩码的组合。掩码要么是 nomask，表示关联数组的任何值均无效，要么是布尔值数组，用于确定关联数组的每个元素的值是否有效。

步骤

首先，导入所需的库 -

import numpy as np
import numpy.ma as ma

使用 numpy.array() 方法创建具有整数元素的数组 -

arr = np.array([[65, 68, 81], [93, 33, 76], [73, 88, 51], [62, 45, 67]])
print("Array...
", arr)

创建掩码数组并掩盖其中一些为无效 -

maskArr = ma.masked_array(arr, mask =[[1, 0, 0], [ 0, 0, 0], [0, 1, 0], [0, 0, 0]])
print("
Our Masked Array...
", maskArr)

获取掩码数组的类型 -

print("
Our Masked Array type...
", maskArr.dtype)

获取掩码数组的维度 -

print("
Our Masked Array Dimensions...
",maskArr.ndim)

获取掩码数组的形状 -

print("
Our Masked Array Shape...
",maskArr.shape)

获取掩码数组的元素数量 -

print("
Number of elements in the Masked Array...
",maskArr.size)

要计算掩码数组中连续元素之间的差异，请使用 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))

输出

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]

更新于: 2022年2月3日

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