processing.modules.seabird_functions module

class processing.modules.seabird_functions.AlignCTD

Bases: ArrayModule

Align the given parameter columns.

Given a measurement parameter in parameters, the column will be shifted by either, a float amount that is given as value, or, by a calculated amount, using cross-correlation between the high-frequency components of the temperature and the target parameters. The returned numpy array will thus feature the complete CnvFile data, with the columns shifted to their correct positions.

transformation()

Performs the base logic of distinguishing whether to use given values or compute a delay.

Return type:

A numpy array, representing the cnv data after the alignment.

estimate_sensor_delay(delayed_parameter, margin=240, shift_seconds=10)

Estimate delay between a delayed parameter and temperature signals via cross-correlation of high-frequency components.

Parameters:

• delayed_parameter (Parameter :) – The parameter whose delay shall be computed.

• margin (int :) –

  A number of data points that are cutoff from both ends.

  (Default value = 240)

• shift_seconds (int :) – Maximum time window to search for lag (default: 10 seconds).

Return type:

A float value, representing the parameter delay in seconds.

check_correlation_result(value, correlation_value)

Performs several checks on the delay outputed by self.estimate_sensor_delay and returns True, if the result is considered feasible.

Return type:

bool

find_corresponding_temperature(parameter)

Find the temperature values of the sensor that shared the same water mass as the input parameter.

Parameters:

parameter (Parameter :) – The parameter of interest.

Return type:

The temperature parameter object.

get_correlation(parameter)

Gives a number indicating the cross correlation type regarding the input parameter and the temperature.

Basically distinguishes between positive correlation, 1, and anti- correlation, -1. This value is then used to alter the temperature values accordingly.

Parameters:

parameter (Parameter :) – The parameter to cross correlate with temperature.

Return type:

A float value representing positive or negative correlation.

handle_parameter_input(input_dict)

Return type:

dict