welltestpy.tools

welltestpy subpackage providing miscellaneous tools.

Included functions

The following functions are provided for point triangulation

triangulate(distances, prec[, all_pos])

Triangulate points by given distances.

sym(A)

Get the symmetrized version of a lower or upper triangle-matrix A.

The following plotting routines are provided

campaign_plot(campaign[, select_test, fig, …])

Plot an overview of the tests within the campaign.

fadeline(ax, x, y[, label, color, steps])

Fading line for matplotlib.

plot_well_pos(well_const[, names, title, …])

Plot all well constellations and label the points with the names.

campaign_well_plot(campaign[, plot_tests, …])

Plot of the well constellation within the campaign.

plotfit_transient(setup, data, para, rad, …)

Plot of transient estimation fitting.

plotfit_steady(setup, data, para, rad, …)

Plot of steady estimation fitting.

plotparainteract(result, paranames[, …])

Plot of parameter interaction.

plotparatrace(result[, parameternames, …])

Plot of parameter trace.

plotsensitivity(paralabels, sensitivities[, …])

Plot of sensitivity results.

diagnostic_plot_pump_test(observation, rate)

plot the derivative with the original data.
campaign_plot(campaign, select_test=None, fig=None, style='WTP', **kwargs)[source]

Plot an overview of the tests within the campaign.

Parameters

  • campaign (Campaign) – The campaign to be plotted.

  • select_test (dict, optional) – The selected tests to be added to the plot. The default is None.

  • fig (Figure, optional) – Matplotlib figure to plot on. The default is None.

  • style (str, optional) – Plot style. The default is “WTP”.

  • **kwargs (TYPE) – Keyword arguments forwarded to the tests plotting routines.

Returns

fig – The created matplotlib figure.

Return type

Figure

campaign_well_plot(campaign, plot_tests=True, plot_well_names=True, fig=None, style='WTP')[source]

Plot of the well constellation within the campaign.

Parameters

  • campaign (Campaign) – The campaign to be plotted.

  • plot_tests (bool, optional) – DESCRIPTION. The default is True.

  • plot_well_names (TYPE, optional) – DESCRIPTION. The default is True.

  • fig (Figure, optional) – Matplotlib figure to plot on. The default is None.

  • style (str, optional) – Plot stlye. The default is “WTP”.

Returns

ax – The created matplotlib axes.

Return type

Axes

diagnostic_plot_pump_test(observation, rate, method='bourdet', linthresh_time=1.0, linthresh_head=1e-05, fig=None, ax=None, plotname=None, style='WTP')[source]

plot the derivative with the original data.

Parameters

  • observation (welltestpy.data.Observation) – The observation to calculate the derivative.

  • rate (float) – Pumping rate.

  • method (str, optional) – Method to calculate the time derivative. Default: “bourdet”

  • linthresh_time – Range of time around 0 that behaves linear. Default: 1

  • linthresh_head – Range of head values around 0 that behaves linear. Default: 1e-5

  • fig (Figure, optional) – Matplotlib figure to plot on. Default: None.

  • ax (Axes) – Matplotlib axes to plot on. Default: None.

  • plotname (str, optional) – Plot name if the result should be saved. Default: None.

  • style (str, optional) –

    Plot style.

    Default: “WTP”.

    returns

    rtype

    Diagnostic plot

fadeline(ax, x, y, label=None, color=None, steps=20, **kwargs)[source]

Fading line for matplotlib.

This is a workaround to produce a fading line.

Parameters

  • ax (axis) – Axis to plot on.

  • x (list) – start and end value of x components of the line

  • y (list) – start and end value of y components of the line

  • label (str, optional) – label for the legend. Default: None

  • color (MPL color, optional) – color of the line Default: None

  • steps (int, optional) – steps of fading Default: 20

  • **kwargs – keyword arguments that are forwarded to plt.plot

plot_well_pos(well_const, names=None, title='', filename=None, plot_well_names=True, ticks_set='auto', fig=None, style='WTP')[source]

Plot all well constellations and label the points with the names.

Parameters

  • well_const (list) – List of well constellations.

  • names (list of str, optional) – Names for the wells. The default is None.

  • title (str, optional) – Plot title. The default is “”.

  • filename (str, optional) – Filename if the result should be saved. The default is None.

  • plot_well_names (bool, optional) – Whether to plot the well-names. The default is True.

  • ticks_set (int or str, optional) – Tick spacing in the plot. The default is “auto”.

  • fig (Figure, optional) – Matplotlib figure to plot on. The default is None.

  • style (str, optional) – Plot stlye. The default is “WTP”.

Returns

fig – The created matplotlib figure.

Return type

Figure

plotfit_steady(setup, data, para, rad, radnames, extra, plotname=None, ax_ins=True, fig=None, ax=None, style='WTP')[source]

Plot of steady estimation fitting.

plotfit_transient(setup, data, para, rad, time, radnames, extra, plotname=None, fig=None, ax=None, style='WTP')[source]

Plot of transient estimation fitting.

plotparainteract(result, paranames, plotname=None, fig=None, style='WTP')[source]

Plot of parameter interaction.

plotparatrace(result, parameternames=None, parameterlabels=None, xticks=None, stdvalues=None, plotname=None, fig=None, style='WTP')[source]

Plot of parameter trace.

plotsensitivity(paralabels, sensitivities, plotname=None, fig=None, ax=None, style='WTP')[source]

Plot of sensitivity results.

sym(A)[source]

Get the symmetrized version of a lower or upper triangle-matrix A.

triangulate(distances, prec, all_pos=False)[source]

Triangulate points by given distances.

try to triangulate points by given distances within a symmetric matrix ‘distances’ with distances[i,j] = |pi-pj|

thereby p0 will be set to the origin (0,0) and p1 to (|p0-p1|,0)

Parameters

  • distances (numpy.ndarray) –

    Given distances among the point to be triangulated. It hat to be a symmetric matrix with a vanishing diagonal and

    distances[i,j] = |pi-pj|

    If a distance is unknown, you can set it to -1.

  • prec (float) – Given Precision to be used within the algorithm. This can be used to smooth away messure errors

  • all_pos (bool, optional) – If True all possible constellations will be calculated. Otherwise, the first possibility will be returned. Default: False