Source code for pygimli.physics.ert.ertIPManager

"""ERT manager (derived) with FD or TD IP inversion."""
import pygimli as pg
from .ertManager import ERTManager
from .ipModelling import DCIPMModelling


[docs] class ERTIPManager(ERTManager): """Method manager for ERT including induced polarization (IP). This class should be use for any single IP data, which can be a single-frequency frequency-domain (FD) amplitude and phase, or a time-domain (TD) IP chargeability (one gate or an integral value). """
[docs] def __init__(self, *args, **kwargs): """Initialize DC part of it (parent class). Parameters ---------- fd : bool Frequency-domain, otherwise time-domain """ self.isfd = kwargs.pop("fd", False) super().__init__(*args, **kwargs)
[docs] def invertTDIP(self, ipdata='ip', **kwargs): """IP inversion in time domain.""" if isinstance(ipdata, str): ipdata = self.data[ipdata] if max(ipdata) > 1: # mV/V ipdata /= 1000 mesh0 = pg.Mesh(self.paraDomain) mesh0.setCellMarkers(mesh0.cellCount()) fopIP = DCIPMModelling(self.fop, mesh0, self.model, response=self.inv.response) fopIP.createRefinedForwardMesh(True) invIP = pg.Inversion(fop=fopIP, verbose=True) invIP.modelTrans = pg.trans.TransLogLU(0.0, 1.0) relErr = kwargs.pop("relativeError", 0.03) absErr = kwargs.pop("absoluteError", 0.001) errorIP = pg.Vector(self.data.size(), relErr) + absErr / pg.abs(ipdata) kwargs.setdefault("lam", 100) kwargs.setdefault("startModel", pg.median(ipdata)) kwargs.setdefault("verbose", True) self.modelIP = invIP.run(ipdata, errorIP, **kwargs)
[docs] def invertFDIP(self, **kwargs): """IP inversion in frequency domain.""" self.modelIP = None # naive IP inversion
[docs] def showIPModel(self, **kwargs): """"Show IP model.""" kwargs.setdefault("logSpace", False) if self.isfd: kwargs.setdefault("label", r"$\phi$ (mrad)") kwargs.setdefault("cMap", "viridis") else: kwargs.setdefault("label", r"$m$ (mV/V)") kwargs.setdefault("cMap", "magma_r") return self.showModel(self.modelIP*1000, **kwargs)
[docs] def showResults(self, reskw={}, ipkw={}, **kwargs): """Show DC and IP results. Parameters ---------- reskw : dict keyword arguments for showing resistivity image ipkw : dict keyword arguments for showing IP image **kwargs : dict keyword arguments for showing resistivity image """ _, ax = pg.plt.subplots(nrows=2, sharex=True) kwargs.setdefault("orientation", "vertical") kwargs.setdefault("xlabel", "x (m)") kwargs.setdefault("ylabel", "z (m)") reskw.setdefault("ax", ax[0]) super().showResult(**reskw, **kwargs) ipkw.setdefault("ax", ax[1]) ipkw.setdefault("logScale", False) ipkw.setdefault("cMin", 0) self.showIPModel(**ipkw, **kwargs) return ax
[docs] def invert(self, *args, **kwargs): """Carry out DC and IP inversion.""" super().invert(*args, **kwargs) # DC first (not needed for FD) if self.isfd: self.invertFDIP() else: self.invertTDIP()
[docs] def invertDC(self, *args, **kwargs): # Needed if we want to do ERT first without the IP and do IP later super().invert(*args, **kwargs)
[docs] def simulate(self, mesh, res, m, scheme=None, **kwargs): """.""" from pygimli.physics.ert import ERTModelling data = scheme or pg.DataContainerERT(self.data) if hasattr(res[0], '__iter__'): # ndim == 2 if len(res[0]) == 2: # res seems to be a res map resVec = pg.solver.parseArgToArray(res, mesh.cellCount(), mesh) elif len(res) == mesh.cellCount(): resVec = res else: resVec = res[mesh.cellMarkers()] if hasattr(m[0], '__iter__'): # ndim == 2 if len(m[0]) == 2: # res seems to be a res map mVec = pg.solver.parseArgToArray(m, mesh.cellCount(), mesh) elif len(m) == mesh.cellCount(): mVec = m else: mVec = m[mesh.cellMarkers()] print(mesh, len(resVec), len(mVec)) mesh0 = pg.Mesh(mesh) mesh0.setCellMarkers(mesh0.cellCount()) fopDC = ERTModelling() fopDC.setData(scheme) fopDC.setMesh(mesh0) data["rhoa"] = fopDC.response(resVec) fopDC.createJacobian(resVec) fopIP = DCIPMModelling(fopDC, mesh, resVec) data["ma"] = fopIP.response(mVec) # SI data["ip"] = data["ma"] * 1000 # mV/V return data
[docs] def saveResult(self, folder=None, *args, **kwargs): """Save all results in given or date-based folder.""" super().saveResult(folder=folder, **kwargs, ip=self.modelIP*1000)