Python class for reading and writing NonLinLoc grid files
Project description
NLLGrid
Python class for reading and writing NonLinLoc grid files.
(c) 2015-2024 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.
From nllgrid GitHub repository
If you need a recent feature that is not in the latest release (see the
unreleased
section in CHANGELOG), you want to use the source code from
the nllgrid GitHub repository.
For that, clone the project:
git clone https://github.com/claudiodsf/nllgrid.git
(avoid using the "Download ZIP" option from the green "Code" button, since
version number is lost), then install the code from within the nllgrid
main directory by running:
pip install .
(use pip install -e .
to install in developer mode).
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).
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