NLLGrid

Python class for reading and writing NonLinLoc grid files.

(c) 2015-2025 Claudio Satriano, Natalia Poiata, Robert Pickle

Installation

Using Anaconda

If you use Anaconda, the latest release of nllgrid is available via conda-forge.

To install, simply run:

conda install -c conda-forge nllgrid

Using pip and PyPI

The latest release of nllgrid is available on the Python Package Index.

You can install it easily through pip:

pip install nllgrid

From nllgrid GitHub releases

Download the latest release from the releases page, in zip or tar.gz format, then:

pip install nllgrid-X.Y.zip

or

pip install nllgrid-X.Y.tar.gz

Where, X.Y is the version number (e.g., 1.3). You don't need to uncompress the release files yourself.

Installing a development snapshot

If you need a recent feature that is not in the latest release (see the unreleased section in CHANGELOG), you want to use the more recent development snapshot from the nllgrid GitHub repository.

Using pip

The easiest way to install the most recent development snapshot is to download and install it through pip, using its builtin git client:

pip install git+https://github.com/claudiodsf/nllgrid.git

Run this command again, from times to times, to keep NLLGrid updated with the development version.

Cloning the NLLGrid GitHub repository

If you want to take a look at the source code (and possibly modify it 😉), clone the project using git:

git clone https://github.com/claudiodsf/nllgrid.git

or, using SSH:

git clone [email protected]:claudiodsf/nllgrid.git

(avoid using the "Download ZIP" option from the green "Code" button, since version number is lost).

Then, go into the nllgrid main directory and install the code in "editable mode" by running:

pip install -e .

You can keep your local NLLGrid repository updated by running git pull from times to times. Thanks to pip's "editable mode", you don't need to reinstall NLLGrid after each update.

Getting Started

Reading a NLL grid

A NLL grid is composed of two files (.hdr and .buf).

To read a NLL grid, do:

>>> from nllgrid import NLLGrid
>>> grd = NLLGrid('somegrid.hdr')

or, using the .buf filename:

>>> grd = NLLGrid('somegrid.buf')

or even without any extension:

>>> grd = NLLGrid('somegrid')

A grid description can be obtained by:

>>> print(grd)

The grid data array is accessed by grd.array. The grid can be plotted doing:

>>> grd.plot()

Use Python introspection (e.g. dir(grd)) to see all the available methods and attributes.

Creating a NLL grid

Suppose that you have a 3D data array stored into a NumPy array called mydata.

First, create an empty NLL grid object:

>>> from nllgrid import NLLGrid
>>> grd = NLLGrid()

then, add the data array and information on grid sampling and grid origin, e.g.:

>>> grd.array = mydata
>>> grd.dx = 0.5  #km
>>> grd.dy = 0.5  #km
>>> grd.dz = 0.5  #km
>>> grd.x_orig = -10  #km
>>> grd.y_orig = -20. #km
>>> grd.z_orig = -1.  #km

Optionally, add a grid type and/or a geographic transformation:

>>> grd.type = 'VELOCITY'
>>> grd.orig_lat = 40.63
>>> grd.orig_lon = 15.80
>>> grd.proj_name = 'LAMBERT'
>>> grd.first_std_paral = 38.
>>> grd.second_std_paral = 42.
>>> grd.proj_ellipsoid = 'WGS-84'

Finally, give a basename and write to disk:

>>> grd.basename = 'mygrid'
>>> grd.write_hdr_file()
>>> grd.write_buf_file()

This will create the two files mygrid.hdr and mygrid.buf.

If you want to save your grid in double precision (required for instance by NLDiffLoc), change grd.float_type to 'DOUBLE' before saving the grid (default is 'FLOAT'):

>>> grd.float_type = 'DOUBLE'

Note that if you want to use your grid as input for NonLinLoc Grid2Time code, the grid type has to be SLOW_LEN and your grid array has to be transformed into slowness (in s/km) and multiplied by the grid step (in km).