src.toolbox.steps.custom.profile_direction#

Step for determining glider profile direction.

Classes#

ProfileDirection

Determine whether water profiles are ascending or descending.

Module Contents#

class src.toolbox.steps.custom.profile_direction.ProfileDirection[source]#

Bases: toolbox.steps.base_step.BaseStep, toolbox.utils.qc_handling.QCHandlingMixin

Determine whether water profiles are ascending or descending.

This step calculates the direction of movement through the water column by analysing the rate of change of pressure with respect to time. The median direction is computed for each profile and stored in a new PROFILE_DIRECTION variable.

step_name[source]#

The name of this processing step: “Find Profile Direction”.

Type:

str

data#

The dataset being processed, updated with PROFILE_DIRECTION and PROFILE_DIRECTION_QC variables.

Type:

xarray.Dataset

context#

Processing context containing metadata and previous step outputs.

Type:

dict

Notes

The profile direction is determined by computing the sign of the pressure gradient (dPRES/dTIME). Negative gradients indicate ascending profiles (pressure decreasing), while positive gradients indicate descending profiles (pressure increasing).

The direction is calculated as:

direction = -1 * sign(dPRES/dTIME)

  • direction = 1: Ascending profile (pressure decreasing)

  • direction = -1: Descending profile (pressure increasing)

Examples

In a processing configuration file, use this step as follows:

steps:
  - name: "Find Profile Direction"
    parameters:
    diagnostics: false
step_name = 'Find Profile Direction'[source]#
required_variables = ['PROFILE_NUMBER', 'PRES', 'TIME'][source]#
provided_variables = ['PROFILE_DIRECTION'][source]#
run()[source]#

Execute the profile direction detection algorithm.

Processes the input data to determine whether each measurement point belongs to an ascending or descending profile, then propagates the direction classification to all measurements in each profile.

Returns:

The updated context dictionary with the processed data containing new PROFILE_DIRECTION and PROFILE_DIRECTION_QC variables.

Return type:

dict

Raises:

ValueError – If required variables (PROFILE_NUMBER, PRES, TIME) are missing from the input dataset.

Notes

This method:

  1. Optionally filters QC flags from the data

  2. Subsets data to remove NaN values in key variables

  3. Computes pressure gradient with respect to time

  4. Calculates median direction per profile

  5. Propagates direction to all measurements

  6. Updates QC flags

  7. Generates diagnostics if enabled

generate_diagnostics()[source]#

Create diagnostic plots of ascending and descending profiles.

Generates a scatter plot showing all measurements coloured by profile direction. Ascending profiles are shown in blue, descending profiles in red. Pressure is plotted against time.

Notes

This method uses Tkinter as the matplotlib backend and requires a display environment. It blocks continued pipeline execution until the plot window is closed.