c语言产生随机的高斯分布

参考http://www.cnblogs.com/tsingke/p/6194737.html

采用box-muller方法:

​

#include

#include ​

double gaussrand2(double mu,double sigma){​

  static double u,v;

  static int phase=0;

  double z;

  if(phase==0){

    u=rand()/(RAND_MAX+1.0);

    v=rand()/(RAND_MAX+1.0);

    z=sqrt(-2.0*log(u))*sin(2.0*pi*v);

  }

  else{

    z=sqrt(-2.0*log(u))*cos(2.0*pi*v);

  }

  phase=1-phase;

  return(mu+z*sigma);

}

obspy绘制beach ball

import numpy as np

​import matplotlib.pyplot as plt 

 from mpl_toolkits.basemap import Basemap 

 from obspy import read_events 

from obspy.imaging.beachball import beach 

 event = read_events( 'https://earthquake.usgs.gov/archive/product/moment-tensor/' 'us_20005ysu_mww/us/1470868224040/quakeml.xml', format='QUAKEML')[0] 

origin = event.preferred_origin() or event.origins[0] 

ocmec = event.preferred_focal_mechanism() or event.focal_mechanisms[0] 

tensor = focmec.moment_tensor.tensor 

pandas日期及添加列

已经有了pandas数据框格式的地震目录,需要获取日期的datetime数值,并存储到新的一列dt中,可以这么操作
cata['dt']=cata.apply(lambda x: datetime(x['yr'],x['mn'],x['dy']),axis=1)
这个是按行操作的,很慢。
或者用pandas的to_datetime方法:
pd.to_datetime(df['year'].astype(str) + '-'+ df['month'].astype(str)+ '-1')

而批量操作不行,比如
datetime(x['yr'],x['mn'],x['dy'])
因为datetime不支持pandas的批量操作。