通过python计算有效波高，平均波高，平均周期，有效周期
现有波面数据如下图所示，采用频率为20Hz，需要根据波面数据计算得到平均波高、有效波高等信息。
python代码如下所示，绘图部分仅展示了概率分布：
# -*- coding: utf-8 -*- """ Created on %(date)s @author: %(jixianpu)s Email : 211311040008@hhu.edu.cn introduction : keep learning althongh walk slowly """ import matplotlib.pyplot as plt import pandas as pd import numpy as np path=r'D:/data.xlsx' data=pd.read_excel(path) high=data['波面数据(m)'] da=np.array(high) da=da a=[] for i in range(len(da)-1): if (da[i]<0)&(da[i+1]>0): print(i) a.append(i) wh=[] tm=[] for j in range(len(a)-1): x=da[a[j]:a[j+1]] x_max=np.max(x) x_min=np.min(x) h=x_max-x_min t=a[j+1]-a[j] tr=0.05*t tm.append(tr) wh.append(h) ### mean time \mean wave high h_mean=np.mean(wh) t_mean=np.mean(tm) ### h_s=sorted(wh,reverse=True) hs_3=h_s[0:int(len(h_s)/3)+1] hs3_mean=np.mean((hs_3)) t_s=sorted(tm,reverse=True) ts_3=t_s[0:int(len(h_s)/3)+1] ts3_mean=np.mean(ts_3) ####f hist, x, y= np.histogram2d(wh,tm,bins=10) ############################################################################ fig=plt.figure(figsize=(10,10)) ax = fig.add_subplot(111) # ax.plot(da[0:1000]) # plt.axhline(y=0, color='r', linestyle='--') ax.imshow(hist) ax.set_xlabel('H(m)',fontsize=20) ax.set_ylabel('T(s)',fontsize=20) ax.set_ylim(0,10) ax.pcolor(hist) # ax.bar(x,y) plt.show()
