Surface NMR processing and inversion GUI
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  1. import matplotlib.pyplot as plt
  2. import sys,os
  3. from pylab import meshgrid
  4. from matplotlib.colors import LightSource
  5. from matplotlib.ticker import ScalarFormatter
  6. from matplotlib.ticker import MaxNLocator
  7. from matplotlib.ticker import AutoMinorLocator
  8. from matplotlib.ticker import LogLocator
  9. from matplotlib.ticker import FormatStrFormatter
  10. import numpy as np
  11. import yaml
  12. from lemma_yaml import *
  13. import cmocean
  14. def catLayers(K0):
  15. K = np.zeros( (len(K0.keys()), len(K0["layer-0"].data)) , dtype=complex )
  16. for lay in range(len(K0.keys())):
  17. #print(K0["layer-"+str(lay)].data) # print (lay)
  18. K[lay] = K0["layer-"+str(lay)].data # print (lay)
  19. return K
  20. if __name__ == "__main__":
  21. with open(sys.argv[1]) as f:
  22. # use safe_load instead load
  23. K0 = yaml.load(f, Loader=yaml.Loader)
  24. K = 1e9*catLayers(K0.K0)
  25. q = np.array(K0.PulseI.data)* (float)(K0.Taup)
  26. #plt.pcolor(K0.Interfaces.data, K0.PulseI.data, np.abs(K))
  27. #plt.pcolor(q, K0.Interfaces.data, np.abs(K), cmap=cmocean.cm.gray_r)
  28. #plt.contourf(q, K0.Interfaces.data[0:-1], np.abs(K), cmap=cmocean.cm.tempo)
  29. plt.pcolor(q, K0.Interfaces.data, np.abs(K), cmap=cmocean.cm.tempo)
  30. plt.colorbar()
  31. ax1 = plt.gca()
  32. ax1.set_ylim( ax1.get_ylim()[1], ax1.get_ylim()[0] )
  33. #ax1.set_xscale('log')
  34. #ax1.set_yscale('log')
  35. #ax1.xaxis.set_major_formatter(ScalarFormatter())
  36. ax1.set_xticks([ax1.get_xlim()[0], 1, ax1.get_xlim()[1],])
  37. ax1.xaxis.set_major_formatter(FormatStrFormatter('%.1f'))
  38. #print(yaml.dump(K0.K0))
  39. #print( K0.K0["layer-0"].data )
  40. #print( type( np.array(K0.K0["layer-0"].data) ) )
  41. #plt.plot( np.real( K0.K0["layer-0"].data ) )
  42. #plt.plot( K0.K0["layer-0"].data )
  43. plt.gca().set_xlabel("q (A $\cdot$ s)")
  44. plt.gca().set_ylabel("depth (m)")
  45. plt.savefig("kernel.pdf")
  46. sound = np.sum(K, axis=0)
  47. plt.figure()
  48. plt.plot(q, np.abs(sound))
  49. plt.savefig("sound.pdf")
  50. plt.show()
  51. #print(yaml.dump(K0))