123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155 |
-
- import os, sys
- import numpy as np
- from ruamel import yaml
-
- import pyLemma.LemmaCore as lc
- import pyLemma.Merlin as mrln
- import pyLemma.FDEM1D as em1d
-
- import numpy as np
-
- import matplotlib.pyplot as plt
- import seaborn as sns
- sns.set(style="ticks")
-
- from ruamel import yaml
-
- #import cmocean
- #from SEGPlot import *
- #from matplotlib.ticker import FormatStrFormatter
- #import matplotlib.ticker as plticker
-
-
- # Converts Lemma/Merlin/Akvo serialized Eigen arrays into numpy ones for use by Python
- class VectorXr(yaml.YAMLObject):
- """
- Converts Lemma/Merlin/Akvo serialized Eigen arrays into numpy ones for use by Python
- """
- yaml_tag = u'VectorXr'
- def __init__(self, array):
- self.size = np.shape(array)[0]
- self.data = array.tolist()
- def __repr__(self):
- # Converts to numpy array on import
- return "np.array(%r)" % (self.data)
-
- class AkvoData(yaml.YAMLObject):
- """
- Reads an Akvo serialized dataset into a standard python dictionary
- """
- yaml_tag = u'AkvoData'
- def __init__(self, array):
- pass
- #self.size = np.shape(array)[0]
- #self.Imp = array.tolist()
- def __repr__(self):
- # Converts to a dictionary with Eigen vectors represented as Numpy arrays
- return self
-
- def loadAkvoData(fnamein):
- """ Loads data from an Akvo YAML file. The 0.02 is hard coded as the pulse length. This needs to be
- corrected in future kernel calculations. The current was reported but not the pulse length.
- """
- fname = (os.path.splitext(fnamein)[0])
- with open(fnamein, 'r') as stream:
- try:
- AKVO = (yaml.load(stream, Loader=yaml.Loader))
- except yaml.YAMLError as exc:
- print(exc)
- return AKVO
-
-
- def main():
-
- if len(sys.argv) < 3:
- print ("usage python calcAkvoKernel.py AkvoDataset.yaml Coil1.yaml kparams.yaml SaveString.yaml " )
- exit()
-
- AKVO = loadAkvoData(sys.argv[1])
-
- B_inc = AKVO.META["B_0"]["inc"]
- B_dec = AKVO.META["B_0"]["dec"]
- B0 = AKVO.META["B_0"]["intensity"]
-
- fT = AKVO.transFreq
- #gamma = 2.67518e8
- #B0 = (fL*2.*np.pi) /gamma * 1e9
-
- Coil1 = em1d.PolygonalWireAntenna.DeSerialize( sys.argv[2] )
- Coil1.SetNumberOfFrequencies(1)
- Coil1.SetFrequency(0, fT)
- Coil1.SetCurrent(1.)
-
- # read in kernel params
- kparams = loadAkvoData( sys.argv[3] )
-
- ## TODO
- # pass this in...
- lmod = em1d.LayeredEarthEM()
-
- nlay = len(kparams["sigs"])
- sigs = np.array(kparams["sigs"])
- tops = np.array(kparams["tops"])
- bots = np.array(kparams["bots"])
-
- if ( (len(tops)-1) != len(bots)):
- print("Layer mismatch")
- exit()
-
- thicks = bots - tops[0:-1]
-
- lmod.SetNumberOfLayers(nlay + 1)
- lmod.SetLayerThickness(thicks)
- lmod.SetLayerConductivity( np.concatenate( ( [0.0], sigs ) ))
-
- #lmod.SetNumberOfLayers(4)
- #lmod.SetLayerThickness([15.49, 28.18])
- #lmod.SetLayerConductivity([0.0, 1./16.91, 1./24.06, 1./33.23])
-
-
- lmod.SetMagneticFieldIncDecMag( B_inc, B_dec, B0, lc.NANOTESLA )
-
- Kern = mrln.KernelV0()
- Kern.PushCoil( "Coil 1", Coil1 )
- Kern.SetLayeredEarthEM( lmod );
- Kern.SetIntegrationSize( (kparams["size_n"], kparams["size_e"], kparams["size_d"]) )
- Kern.SetIntegrationOrigin( (kparams["origin_n"], kparams["origin_e"], kparams["origin_d"]) )
- Kern.SetTolerance( 1e-9*kparams["branchTol"] )
- Kern.SetMinLevel( kparams["minLevel"] )
- Kern.SetMaxLevel( kparams["maxLevel"] )
- Kern.SetHankelTransformType( lc.FHTKEY201 )
- Kern.AlignWithAkvoDataset( sys.argv[1] )
-
- if str(kparams["Lspacing"]).strip() == "Geometric":
- thick = np.geomspace(kparams["thick1"], kparams["thickN"], num=kparams["nLay"])
- elif str(kparams["Lspacing"]) == "Log":
- thick = np.logspace(kparams["thick1"], kparams["thickN"], num=kparams["nLay"])
- elif str(kparams["Lspacing"]) == "Linear":
- thick = np.linspace(kparams["thick1"], kparams["thickN"], num=kparams["nLay"])
- else:
- print("DOOOM!, in calcAkvoKernel layer spacing was not <Geometric>, <Log>, or <Linear>")
- print( str(kparams["Lspacing"]) )
- exit()
-
- iface = np.cumsum(thick)
- Kern.SetDepthLayerInterfaces(iface)
- #Kern.SetDepthLayerInterfaces(np.geomspace(1, 110, num=40))
- #Kern.SetDepthLayerInterfaces(np.linspace(1, 110, num=50))
- #Kern.SetDepthLayerInterfaces(np.geomspace(1, 110, num=40))
-
- # autAkvoDataNode = YAML::LoadFile(argv[4]);
- # Kern->AlignWithAkvoDataset( AkvoDataNode );
-
- Kern.CalculateK0( ["Coil 1"], ["Coil 1"], False )
-
- #yml = open( 'test' + str(Kern.GetTolerance()) + '.yaml', 'w')
- yml = open( sys.argv[4], 'w' )
- print(Kern, file=yml)
-
- K0 = Kern.GetKernel()
- plt.matshow(np.abs(K0))
- plt.show()
-
- if __name__ == "__main__":
- main()
|