国际域名注册商,百度seo优化招聘,举报网站建设情况总结,新网网站建设资料Python开发之二维数组空缺值的填充 1 实现一#xff0c;任意位置填充2 实现二#xff0c;填充内部3 实现三#xff0c;只填充边缘#xff0c;不包括四个角 前言#xff1a;主要实现二维数据里面某一个数据的缺失#xff0c;用缺失的近邻数据进行均值填充#xff0c;可以… Python开发之二维数组空缺值的填充 1 实现一任意位置填充2 实现二填充内部3 实现三只填充边缘不包括四个角 前言主要实现二维数据里面某一个数据的缺失用缺失的近邻数据进行均值填充可以应用在遥感图像中空缺值的填充等。 1 实现一任意位置填充
对二维数据任意位置的空缺值进行近邻填充。 代码实现其中指定空缺值指定近邻的数量
import numpy as np# 定义一个函数来填充-23750为空值
def fill_empty_with_mean(arr, empty_value,min_neighbors):# 获取数组的行数和列数rows, cols arr.shape# 遍历数组for i in range(rows):for j in range(cols):if arr[i, j] empty_value:# 获取周围非空元素的均值neighbors []for x in [-1, 0, 1]:for y in [-1, 0, 1]:if 0 i x rows and 0 j y cols and arr[i x, j y] ! empty_value:neighbors.append(arr[i x, j y])# 计算均值并填充if len(neighbors) min_neighbors:# print(neighbors)# print(np.mean(neighbors))arr[i, j] np.mean(neighbors)if __name__ __main__:# 创建一个包含-23750为空值的示例二维数组array np.array([[1, -23750, 1, 1, 1],[1, -23750, 1, 1, -23750],[-23750, 2, 9, -1, 1.0],[-1, -1, -23750, 5, -23750]])# 使用函数填充-23750为空值empty_value -23750min_neighbors 3fill_empty_with_mean(array, empty_value,min_neighbors)# 输出填充后的数组print(array) 2 实现二填充内部
对二维数据任意位置的空缺值进行近邻填充去掉边缘。 代码实现其中指定空缺值指定近邻的数量
import numpy as npdef fill_empty_with_mean(arr, empty_value, min_neighbors5):# 获取数组的行数和列数rows, cols arr.shape# 遍历数组for i in range(1, rows - 1): # 从第2行到倒数第2行for j in range(1, cols - 1): # 从第2列到倒数第2列if arr[i, j] empty_value:# 获取周围非空元素的个数neighbors [arr[i x, j y] for x in [-1, 0, 1] for y in [-1, 0, 1] ifarr[i x, j y] ! empty_value]# 如果周围非空元素的个数大于等于min_neighbors计算均值并填充if len(neighbors) min_neighbors:arr[i, j] np.mean(neighbors)return arrif __name__ __main__:# 创建一个包含-23750为空值的示例二维数组array np.array([[1, -23750, 1, 1, 1],[1, -23750, 1, 1, -23750],[-23750, 1, 7, -1, 1],[-1, -1, -23750, 5, 6]])# 输出填充后的数组# print(array)# 使用函数填充-23750为空值只有周围至少有5个非空值时才填充empty_value -23750min_neighbors 5arr fill_empty_with_mean(array, empty_value, min_neighbors)# 输出填充后的数组print(arr)3 实现三只填充边缘不包括四个角
代码实现
import numpy as npdef fill_edge_empty_with_mean(arr, empty_value, min_neighbors5):# 获取数组的行数和列数rows, cols arr.shape# 遍历第一行for j in range(1, cols - 1):if arr[0, j] empty_value:# 获取周围非空元素的个数neighbors [arr[0 x, j y] for x in [0, 1] for y in [-1, 0, 1] if arr[0 x, j y] ! empty_value]print(neighbors)# 如果周围非空元素的个数大于等于min_neighbors计算均值并填充if len(neighbors) min_neighbors:arr[0, j] np.mean(neighbors)print(float(np.mean(neighbors)))## 遍历最后一行for j in range(1, cols - 1):if arr[rows - 1, j] empty_value:# 获取周围非空元素的个数neighbors [arr[rows - 1 x, j y] for x in [-1, 0] for y in [-1, 0, 1] if arr[rows - 1 x, j y] ! empty_value]print(neighbors)# 如果周围非空元素的个数大于等于min_neighbors计算均值并填充if len(neighbors) min_neighbors:arr[rows - 1, j] np.mean(neighbors)print(float(np.mean(neighbors)))## 遍历第一列for i in range(1, rows - 1):if arr[i, 0] empty_value :neighbors [arr[i x, 0 y] for x in [-1, 0, 1] for y in [0, 1] if arr[i x, 0 y] ! empty_value]print(neighbors)# 如果周围非空元素的个数大于等于min_neighbors计算均值并填充if len(neighbors) min_neighbors:arr[i, 0] np.mean(neighbors)print(float(np.mean(neighbors)))# 遍历最后一列for i in range(1, rows - 1):if arr[i, cols - 1] empty_value:# 获取周围非空元素的个数neighbors [arr[i x, cols-1 y] for x in [-1, 0, 1] for y in [-1, 0] if arr[i x, cols-1 y] ! empty_value]print(neighbors)# 如果周围非空元素的个数大于等于min_neighbors计算均值并填充if len(neighbors) min_neighbors:arr[i, cols - 1] np.mean(neighbors)print(float(np.mean(neighbors)))return arrif __name__ __main__:# 创建一个包含-23750为空值的示例二维数组array np.array([[1, -23750, 1, 1, 1],[1, -1, 1, 1, -23750],[-23750, 1, 7, -1, 1],[-1, -1, -23750, 5, 6.0]])# 输出填充后的数组# print(array)# 使用函数填充-23750为空值只有周围至少有5个非空值时才填充empty_value -23750min_neighbors 3arr fill_edge_empty_with_mean(array, empty_value, min_neighbors)# 输出填充后的数组print(arr)
