###################################################尝试显著性检验
## 把2月份和3月份
# 从整体上来看,先看边界层高度的情况
# 整理气象数据
# 读数据
import netCDF4 as nc
import pandas as pd
import numpy as np
file1 = r'C:\Users\LHW\Desktop\Hubei task120210918\meteology\adaptor.mars.internal-1631981155.7723448-28568-14-37c609d7-a545-4a66-b4e3-3f73bf08819b.nc'
file2 =r'C:\Users\LHW\Desktop\Hubei task120210918\meteology\adaptor.mars.internal-1631983289.050715-24266-17-3c804cfb-3277-455a-a01d-1f362109c96d.nc'
file3 = r'C:\Users\LHW\Desktop\Hubei task120210918\meteology\adaptor.mars.internal-1631983382.3185003-7481-11-e104bfc6-9c58-451c-ab8d-edbf4ae0a58d.nc'
file4 = r'C:\Users\LHW\Desktop\Hubei task120210918\meteology\adaptor.mars.internal-1631983578.5396793-21124-12-b3d63215-5cbc-4b95-8397-e15f3b7df515.nc'
dataset1 = nc.Dataset(file1)
lon1=dataset1.variables['longitude'][:]
lat1=dataset1.variables['latitude'][:]
BLH=dataset1.variables['blh'][:]
BLH20190203=BLH[736:2152,:,:]
BLH20200203=BLH[3616:5056,:,:]
# 新建一个显著性检验的表格
BLH_p=np.zeros(BLH20190203.shape[1:])
row=BLH20190203.shape[1]
col=BLH20190203.shape[2]
for i in range(row):
for j in range(col):
BLH_p[i,j]=get_p_value(BLH20190203[:,i,j],BLH20200203[:,i,j])
Python 计算两个序列之间差异的显著性水平检验
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转载自blog.csdn.net/weixin_45577825/article/details/120469594
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