galileoQC.transforms.spheretest

Create a synthetic data set for testing.

Author: Mark Helm Dransfield

Created: Oct 2025

License: CC BY-SA

Module Contents

Functions

sphereSurvey	Creates an airborne survey over 3 point mass sources, calculates all gravity acceleration vector and curvature tensor outputs.
sphere	Calculates the vertical gravity, gD, and all gravity gradient components (in NED coordinates), on sample points simulating an airborne survey above a massive sphere at the centre of the survey area.
_make_xr	Puts the data in 1D numpy arrays (n, e, data) into a fiducial- dimensioned 1D xarray DataSet. The n and e channels are assumed to have units ‘m’.

API

galileoQC.transforms.spheretest.sphereSurvey(numstns=20)

Creates an airborne survey over 3 point mass sources, calculates all gravity acceleration vector and curvature tensor outputs.

All information is referenced to an NED coordinates frame. Accelerations are in um/s/s and curvatures are in eotvos.

One-off function for testing Craig transform code on synthetic data.

Parameters

numstns : int, optional

The number of stations (samples) in the grid's x and y directions.
Default 20.

Returns

n, e, d, Ann, Ane, And, Aee, Aed, Add, Auv, AD :

a list of numpy 1D arrays

galileoQC.transforms.spheretest.sphere(xm, xs, rs, ps)

Calculates the vertical gravity, gD, and all gravity gradient components (in NED coordinates), on sample points simulating an airborne survey above a massive sphere at the centre of the survey area.

One-off function for testing Craig transform code on synthetic data.

Parameters

xm : numpy 2D array

The NED coordinates of the synthetic survey measurement
points in metres. Array size is [n,3] for `n` measurements.

xs : numpy 1D array

The NED coordinates of the centre of the sphere in metres.

rs : str

The radius of the sphere in metres.

ps : float

The density of the sphere in gm/cc (== tonnes per cubic metre).

Returns

Gnn, Gne, Gnd, Gee, Ged, Gdd, Guv, gD : a list of numpy 1D arrays

gravity gradients and vertical acceleration.

galileoQC.transforms.spheretest._make_xr(data, name, units, n, e, n_chan='northing', e_chan='easting')

Puts the data in 1D numpy arrays (n, e, data) into a fiducial- dimensioned 1D xarray DataSet. The n and e channels are assumed to have units ‘m’.

One-off function for testing Craig transform code on synthetic data.

Parameters

data : numpy 1D array

Airborne survey line-based data.

name : str

Name of the `data`.

units : str

Name of the units of the `data`.

n : numpy 1D array

The northings (or 'y' coordinates) for the `data`. Must be in metres.

e : numpy 1D array

The eastings (or 'x' coordinates) for the `data`. Must be in metres.

n_chan : str, optional

The name to be given to the `n` data, usually 'northing' or 'y'.
Default 'northing'.

e_chan : str, optional

The name to be given to the `e` data, usually 'easting' or 'x'.
Default 'easting'.

Returns

ds : xarray 1D DataSet

DataSet containing the provided data, dimensioned by fiducial.