Picking.rst

Interpretation

Interpretation in this context primarily means picking layers (either isochrones or the bed). In the future, this functionality may be expanded to make picking other things, e.g. some discontinuity, easier.

Functions used for picking

.. automodule:: impdar.lib.picklib
    :members:

Classes used by interpreter

These classes are broken down to match the structure of StODeep, so we store information about how the picks get made, and the picks themselves, using different objects.

If you have done some interpretation, you will likely want to subsequently interact with the Picks object. Often, this can be done without accessing the API by converting the picks/geospatial data to another form, e.g. with impdar convert shp fn_picked.mat. You can also make plots with the picks on top of the radar data, or with the return power in geospatial coordinates, using impplot rg fn_picked.mat or impplot power fn_picked.mat layer_num. For further operations, you will probably want to access the Picks object described next. For example, using the picks object you could do something like

import numy as np
import matplotlib.pyplot as plt
from impdar.lib import RadarData
rd = RadarData('[PICKED_DATA_FN.mat]')

# make a basic plot of the radargram
fig, ax = plt.subplots()
im, _, _, _, _ = plot.plot_radargram(rd, fig=fig, ax=ax, xdat='dist', ydat='depth', return_plotinfo=True)

# calculate the return power
c = 10. * np.log10(rd.picks.power[0, :])
c -= np.nanmax(c)

# plot the return power on the layer, being careful of NaNs
mask = ~np.isnan(rd.picks.samp1[0, :])
cm = ax.scatter(rd.dist[mask.flatten()],
                rd.nmo_depth[rd.picks.samp1[0, :].astype(int)[mask]],
                c=c.flatten()[mask.flatten()],
                s=1)

.. automodule:: impdar.lib.Picks
    :members:

.. automodule:: impdar.lib.PickParameters
    :members: