InversionResult#

class evodcinv.InversionResult[source]#
mean(dz, zmax=None)[source]#

Calculate mean velocity model.

Parameters:

  • dz (scalar) – Maximum layer thickness (in km).

  • zmax (scalar or None, optional, default None) – Depth of last data point.

property misfit#

Return best fit model misfit.

property model#

Return best fit model.

property n_runs#

Return number of runs.

plot_curve(period, mode, wave, type, show='best', stride=1, n_jobs=-1, dc=0.001, dt=0.01, plot_args=None, ax=None)[source]#

Plot calculated data curves.

Parameters:

  • period (array_like) – Periods (in s).

  • mode (int, optional, default 0) – Mode number (0 if fundamental).

  • wave (str {'love', 'rayleigh'}, optional, default 'rayleigh') – Wave type.

  • type (str {'phase', 'group', 'ellipticity'}, optional, default 'phase') – Data type.

  • show (str {'best', 'all'}, optional, default 'best') – Model to use to calculate data curves.

  • stride (int, optional, default 1) – Number of models to skip.

  • n_jobs (int, optional, default -1) – Number of CPU cores to calculate data curves in parallel. Supply -1 to use all available CPU cores. Only used if show = "all".

  • dc (scalar, optional, default 0.001) – Phase velocity increment for root finding.

  • dt (scalar, optional, default 0.01) – Frequency increment (%) for calculating group velocity.

  • plot_args (dict or None, optional, default None) – A dictionary of options to pass to plotting function.

  • ax (matplotlib.pyplot.Axes or None, optional, default None) – Matplotlib axes. If None, use current axes.

plot_misfit(run='all', plot_args=None, ax=None)[source]#

Plot misfit as a function of iteration number.

Parameters:

  • run (int or str {'all'}, optional, default 'all') – Run for which misfit to be plot.

  • plot_args (dict or None, optional, default None) – A dictionary of options to pass to plotting function.

  • ax (matplotlib.pyplot.Axes or None, optional, default None) – Matplotlib axes. If None, use current axes.

plot_model(parameter, zmax=None, show='best', stride=1, dz=None, plot_args=None, ax=None)[source]#

Plot model parameter as a function of depth.

Parameters:

  • parameter (str) –

    Parameter to plot. Should be one of:

    • ’velocity_p’ or ‘vp’

    • ’velocity_s’ or ‘vs’

    • ’density’ or ‘rho’

  • zmax (scalar or None, optional, default None) – Depth of last data point.

  • show (str {'best', 'all'}, optional, default 'best') – Model to plot.

  • stride (int, optional, default 1) – Number of models to skip.

  • dz (scalar or None, optional, default None) – Maximum layer thickness (in km).

  • plot_args (dict or None, optional, default None) – A dictionary of options to pass to plotting function.

  • ax (matplotlib.pyplot.Axes or None, optional, default None) – Matplotlib axes. If None, use current axes.

threshold(value=None)[source]#

Apply a threshold filter.

Remove models that do not satisfy the threshold criterion.

Parameters:

value (scalar or None, optional, default None) – Single value to be used for the data threshold. If None, remove invalid models (i.e., with misfit equal to Inf).

Returns:

Inversion results with models that satisfy the threshold criterion.

Return type:

evodcinv.InversionResult

write(filename, file_format=None, **kwargs)[source]#

Write inversion results to a file.

Parameters:

  • filename (str) – Output file name.

  • file_format (str {'h5', 'json'} or None, optional, default None) – Output file format.

property x#

Return best fit model parameters.