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A collection of methods for data stacking
A collection of methods for stacking of generic time series data.
This package is under active development. The currently available modules are listed here.
utils
: This module contains frequently used utility functions.
core
: This module contains core stacking functions.
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.
cd
to the directory you want to save the package files. Then run:
$ pip install .
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.
See https://github.com/xtyangpsp/StackMaster for tutorials and more detailed descriptions.
Any bugs and ideas are welcome. Please file an issue through GitHub https://github.com/xtyangpsp/StackMaster.
FAQs
A collection of methods for data stacking
We found that stackmaster demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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