README.md

VectorTrace

Python vector trace plot using numpy and pyplot. This is useful for plotting vectorcardiograms (VECG)

Usage: (Assuming that Imat is a 2D array of a vectorcardiogram, and the respective timings like tmax and qwave have been defined)

from lineArrowPlot import lineArrowPlot

lineArrowPlot(Imat[:,0], Imat[:,1], color='k')
  plt.xlabel('Current ((A*(mu0*4pi)*10^6', size=20)
  plt.ylabel('Current ((A*(mu0*4pi)*10^6', size=20)
  plt.title(ID, size=30)
  plt.annotate("R-peak, "+str((rpeak+1)*2)+"ms",
  xy=(Imat[rpeak,0], Imat[rpeak,1]), xycoords='data',
  xytext=(Imat[rpeak,0], Imat[rpeak,1]), textcoords='data', size=20,
  arrowprops=dict(arrowstyle="fancy",
  connectionstyle="angle3", color='0.5'),
  )
  plt.annotate("T-max, "+str((tmax+1)*2)+"ms",
  xy=(Imat[tmax,0], Imat[tmax,1]), xycoords='data',
  xytext=(Imat[tmax,0], Imat[tmax,1]), textcoords='data', size=20,
  arrowprops=dict(arrowstyle="fancy",
  connectionstyle="angle3", color='0.5'),
  )
  if pwaveexists:
  	plt.annotate("Q-wave, "+str((qwave+1)*2)+"ms",
  	xy=(Imat[qwave,0], Imat[qwave,1]), xycoords='data',
  	xytext=(Imat[qwave,0], Imat[qwave,1]), textcoords='data', size=20,
  	arrowprops=dict(arrowstyle="fancy",
  	connectionstyle="angle3", color='0.5'),
  	)
  fig = plt.gcf()
  fig.set_size_inches(15.5, 15.5, forward=True)
  ax = plt.gca()
  ax.grid()
  ax.set_aspect('equal')
plt.show()