watex.utils.plot_confidence_in#

watex.utils.plot_confidence_in(z_or_edis_obj_list, /, tensor='res', view='1d', drop_outliers=True, distance=None, c_line=False, view_ci=True, figsize=(6, 2), fontsize=4.0, dpi=300.0, top_label='Stations', rotate_xlabel=90.0, fbtw=True, savefig=None, **plot_kws)[source]#

Plot data confidency from tensor errors.

The default tensor for evaluating the data confidence is the resistivity at TE mode (‘xy’).

Check confidence in the data before starting the concrete processing seems meaningful. In the area with complex terrain, with high topography addition to interference noises, signals are weals or missing especially when using AMT survey. The most common technique to do this is to eliminate the bad frequency and interpolate the remains one. However, the tricks for eliminating frequency differ from one author to another. Here, the tip using the data confidence seems meaningful to indicate which frequencies to eliminate (at which stations/sites) and which ones are still recoverable using the tensor recovering strategy.

The plot implements three levels of confidence:

  • High confidence: \(conf. \geq 0.95\) values greater than 95%

  • Soft confidence: \(0.5 \leq conf. < 0.95\). The data in this confidence range can be beneficial for tensor recovery to restore the weak and missing signals.

  • bad confidence: \(conf. <0.5\). Data in this interval must be deleted.

Parameters:

  • z_or_edis_obj_list (list of watex.edi.Edi or watex.externals.z.Z) – A collection of EDI- or Impedances tensors objects.

  • tensor (str, default='res') – Tensor name. Can be [ resistivity|phase|z|frequency]

  • view (str, default='1d') – Type of plot. Can be [‘1D’|’2D’]

  • drop_outliers (bool, default=True) – Suppress the ouliers in the data if True.

  • distance (float, optional) – Distance between stations/sites

  • fontsize (float, default=3.) – label font size.

  • figsize (Tuple, default=(6, 2)) – Figure size.

  • c_line (bool, default=True,) – Display the confidence line in two dimensinal view.

  • dpi (int, default=300) – Image resolution in dot-per-inch

  • rotate_xlabel (float, default=90.) – Angle to rotate the stations/sites labels

  • top_labels (str,default='Stations') – Labels the sites either using the survey name.

  • view_ci (bool,default=True,) – Show the marker of confidence interval.

  • fbtw (bool, default=True,) – Fill between confidence interval.

  • plot_kws (dict,) – Additional keywords pass to the plot()

See also

watex.methods.Processing.zrestore

For more details about the function for tensor recovering technique.

Examples

>>> from watex.utils.exmath import plot_confidence_in
>>> from watex.datasets import fetch_data
>>> emobj  = fetch_data ( 'huayuan', samples = 25, clear_cache =True,
                         key='raw').emo
>>> plot_confidence_in (emobj.ediObjs_ ,
                        distance =20 ,
                        view ='2d',
                        figsize =(6, 2)
                        )
>>> plot_confidence_in (emobj.ediObjs_ , distance =20 ,
                        view ='1d', figsize =(6, 3), fontsize =5,
                        )