stackmaster 1.2.0

A collection of methods for data stacking

StackMaster

A collection of methods for data stacking

Introduction

A collection of methods for stacking of generic time series data.

Available modules

This package is under active development. The currently available modules are listed here.

1. utils: This module contains frequently used utility functions.

2. core: This module contains core stacking functions.

Installation

1. Install stackmaster package functions using pip

$ pip install stackmaster

This step will install the StackMaster package. The modules would then be imported under any working directory.

2. Install with local copy:

cd to the directory you want to save the package files. Then run:

$ pip install .

Test the installation

Run the following commands to test your installation, under the root directory of StackMaster.

iimport os,pickle
import numpy as np
import matplotlib.pyplot as plt
from stackmaster.core import stack
from scipy.signal import sosfiltfilt, butter

dataroot='./data'
dfile=dataroot+"/stackmaster_testdataset.pk"
d=pickle.load(open(dfile,'rb'))

scale=60
data,dt,lag,d_id=[d["data"],d["dt"],d['lag'],d['id']]
tx=np.arange(-lag,lag+0.5*dt,dt)
extent=[-lag,lag,data.shape[0],0]
dn=data.copy()

sos=butter(4,[0.05,0.5],fs=1/dt,btype="bandpass",output='sos')

stack_method="robust"

for i in range(data.shape[0]):
    dn[i,:]=sosfiltfilt(sos,data[i,:]/np.max(np.abs(data[i,:])))

## plot
plt.figure(figsize=(10,5),facecolor="w")
plt.imshow(dn,extent=extent,cmap="seismic",aspect="auto")

dstack=stack(dn,method=stack_method)
plt.plot(tx,scale*dstack+0.5*data.shape[0],'k',lw=2,label=stack_method)
plt.vlines(0,0,data.shape[0],'k')
plt.xlim([-200,200])
plt.ylim([0,data.shape[0]])
plt.xticks(fontsize=14)
plt.yticks(fontsize=14)
plt.title(d_id)
plt.xlabel("time (s)",fontsize=14)
plt.ylabel("order",fontsize=14)
plt.legend(fontsize=12)
plt.show()

You should get a plot of the data and the stacked trace.

Tutorials on key functionalities

See https://github.com/xtyangpsp/StackMaster for tutorials and more detailed descriptions.

Contribute

Any bugs and ideas are welcome. Please file an issue through GitHub https://github.com/xtyangpsp/StackMaster.

References

• To be added.