Conversions of radar data

A bunch of radar-related conversions

pygssi.lib.conversionlib.data_to_db(data, p1=None)

Convert data to decibels

Parameters:

• data (numpy.ndarray) – The data you want to convert
• p1 (float, optional) – The “zero” value for the scale. If none, use the mean of data

pygssi.lib.conversionlib.gained_decibels(gainpoints, data, p1=None, recenter=True)

Apply gain and convert to decibels

Parameters:

• gainpoints (str) – A string of comma-separated floats for the gainpoints. These get evenly distributed across depths. They are applied exponentially
• data (numpy.ndarray) – The sample data
• p1 (float, optional) – The “zero” value for the scale. If none, use the mean of data
• recenter (bool, optional) – If true (default), subtract the mean after gaining to center the data on zero

pygssi.lib.conversionlib.to_date(bin, le=True)

Convert the GSSI date format to a datetime.datetime object

Parameters:bin (bits) – The gssi binary date Returns:time – The time from the header Return type:datetime.datetime

pygssi.lib.conversionlib.tt_to_m_variable_arr(diel_array, tt_arr, conv_to_sec=1e-09)

Convert two-way travel time to distance using a variable dielectric constant

Note that this function is very much not elegant, but I think that it should not be too slow unless you dielectric array is very large

Parameters:

• diel_array (numpy.ndarray) – An nx2 array where the first column is the depth and the second column is the dielectric constant
• tt_array (numpy.ndarray) – An mxn array of two-way travel times (typically mx1)
• conv_to_sec (float, optional) – Conversion factor to get from travel-time to seconds (default is assume in nanoseconds, which should be GSSI standard)