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) < 2: print ("usage python calcAkvoKernel.py AkvoDataset.yaml Coil1.yaml kparams.yaml SaveString.yaml " ) print ("usage akvoKO AkvoDataset.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 # read in kernel params kparams = loadAkvoData( sys.argv[2] ) Kern = mrln.KernelV0() TX = [] for tx in kparams['txCoils']: Coil1 = em1d.PolygonalWireAntenna.DeSerialize( tx ) Coil1.SetNumberOfFrequencies(1) Coil1.SetFrequency(0, fT) Coil1.SetCurrent(1.) Kern.PushCoil( tx.split('.yml')[0], Coil1 ) TX.append( tx.split('.yml')[0] ) RX = [] for rx in kparams['rxCoils']: if rx not in kparams['txCoils']: print("new recv") Coil1 = em1d.PolygonalWireAntenna.DeSerialize( rx ) Coil1.SetNumberOfFrequencies(1) Coil1.SetFrequency(0, fT) Coil1.SetCurrent(1.) Kern.PushCoil( rx.split('.yml')[0], Coil1 ) else: print("reuse tx coil") RX.append( rx.split('.yml')[0] ) ## 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.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 , , or ") 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 ) Kern.CalculateK0( TX, RX, False ) #yml = open( 'test' + str(Kern.GetTolerance()) + '.yaml', 'w') yml = open( sys.argv[3], 'w' ) print(Kern, file=yml) # K0 = Kern.GetKernel() plt.matshow(np.abs(K0)) plt.show() if __name__ == "__main__": main()