EmDataPoint

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class geobipy.src.classes.data.datapoint.EmDataPoint.EmDataPoint(x=0.0, y=0.0, z=0.0, elevation=None, components=None, channels_per_system=None, data=None, std=None, predictedData=None, channel_names=None, lineNumber=0.0, fiducial=0.0, **kwargs)

Abstract EmDataPoint Class

This is an abstract base class for TdemDataPoint and FdemDataPoint classes

See also

geobipy.src.classes.data.datapoint.FdemDataPoint, geobipy.src.classes.data.datapoint.TdemDataPoint

property active

Gets the indices to the observed data values that are not NaN

Returns:

out – Indices into the observed data that are not NaN

Return type:

array of ints

find_best_halfspace(minConductivity=0.0001, maxConductivity=10000.0, nSamples=100)

Computes the best value of a half space that fits the data.

Carries out a brute force search of the halfspace conductivity that best fits the data. The profile of data misfit vs halfspace conductivity is not quadratic, so a bisection will not work.

Parameters:

• minConductivity (float, optional) – The minimum conductivity to search over

• maxConductivity (float, optional) – The maximum conductivity to search over

• nSamples (int, optional) – The number of values between the min and max

Returns:

out – The best fitting log10 conductivity for the half space

Return type:

float64

plot_halfspace_responses(minConductivity=-4.0, maxConductivity=2.0, nSamples=100, **kwargs)

Plots the reponses of different half space models.

Parameters:

• minConductivity (float, optional) – The minimum log10 conductivity to search over

• maxConductivity (float, optional) – The maximum log10 conductivity to search over

• nInc (int, optional) – The number of increments between the min and max

property predictedData

The predicted data.

update_posteriors()

Update any attached posteriors