Statistics

摘要

基于已定义的焦点邻域计算影像中各像元的统计数据。

说明

有关此函数使用方法和波段顺序的详细信息，请参阅统计数据栅格函数。

栅格对象所引用的栅格数据集是临时性的。 要将其设置为永久，可以调用栅格对象的 save 方法。

语法

Statistics (raster, kernel_columns, kernel_rows, stat_type, {fill_no_data_only})

参数	说明	数据类型
raster	The input raster on which to perform focal statistics.	Raster
kernel_columns	The number of pixel columns to use in your focal neighborhood dimension. (默认值为 3)	Integer
kernel_rows	The number of pixel rows to use in your focal neighborhood dimension. (默认值为 3)	Integer
stat_type	Specify the type of statistics to calculate. max— Calculates the maximum value of the pixels within the neighborhood. mean— Calculates the average value of the pixels within the neighborhood. This is the default. min— Calculates the minimum value of the pixels within the neighborhood. standarddeviation—Calculates the standard deviation value of the pixels within the neighborhood. median—Calculates the median value of the pixels within the neighborhood. majority— Calculates the majority value, or the value that occurs most frequently, of the pixels within the neighborhood. minority— Calculates the minority value, or the value that occurs least frequently, of the pixels within the neighborhood. (默认值为 None)	String
fill_no_data_only	Specify whether NoData values are ignored in the analysis. True—Fills NoData pixels only. This is the default. False—NoData pixels will not be filled. (默认值为 False)	Boolean

返回值

数据类型	说明
Raster	输出栅格。

代码示例

统计数据示例

使用 5 x 5 邻域中的多数值填写 NoData 值，以获取分类数据。

from arcpy.ia import *
LandCover_filled = arcpy.ia.Statistics("LandCover.tif", 5, 5, "majority", True)
LandCover_filles.save("LandCover_majority_5_by_5.tif")

统计数据示例

使用平均值对 3 x 3 邻域中的高程栅格进行平滑处理。

import arcpy
from arcpy import env
from arcpy.ia import *

# Set environment settings
env.workspace = "C:/statistics_example/data"

# Set local variables
inRaster = "elevation.tif"
kernel_columns=3
kernel_rows=3
stat_type="Mean"
fill_no_data_only = False

# for each pixel, calculate the average value of pixels within its neighborhood. the neighborhood size is 5x5
output = Statistics(imagePath1, kernel_columns, kernel_rows, stat_type, fill_no_data_only)
output.save("statistics_mean_5_by_5.tif")