Tutorial about Euler deconvolution for The Leading Edge by @leouieda, @birocoles and @valcris

# pinga-lab/paper-tle-euler-tutorial

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# Euler deconvolution of potential field data

This tutorial was published on the April 2014 issue of The Leading Edge.

Results were generated using the open-source Python package Fatiando a Terra version 0.2.

The IPython notebooks and data files are also on figshare at dx.doi.org/10.6084/m9.figshare.923450

You can view the final edited version at http://dx.doi.org/10.1190/tle33040448.1

The tutorial is also openly available at the SEG wiki. If you're a SEG member, you can help improve the article by adding more information or correcting any mistakes that you find. If you're not, submit an issue to this repository to start a discussion. We can add the relevant information to the wiki after. Hurray for openness!

If you don't want to leave this repository, you can read a pre-print of the tutorial (`manuscript.pdf`) or have a quick look at the Markdown source manuscript.md. See below for instructions on how to convert the Markdown source to PDF.

## Synthetic data and model

Examples in the tutorial use synthetic data generated with the IPython notebook create_synthetic_data.ipynb. The data can be found in the `data` directory of this repository. File `synthetic_data.txt` has 4 columns: x (north), y (east), z (down) and the total field magnetic anomaly. x, y, and z are in meters. The total field anomaly is in nanoTesla (nT). File `metadata.json` contains extra information about the data, such as inclination and declination of the inducing field (in degrees), shape of the data grid (number of points in y and x, respectively), the area containing the data (W, E, S, N, in meters), and the model boundaries (W, E, S, N, top, bottom, in meters):

``````{"shape": [100, 100],
"dec": 30,
"inc": -15,
"bounds": [0, 30000, 0, 30000, 0, 5000],
"area": [5000, 25000, 5000, 25000]}
``````

File `model.pickle` is a serialized version of the model used to generate the data. It contains a list of instances of the PolygonalPrism class of Fatiando. To load this module in a Python session, run:

``````import cPickle as pickle
with open('model.pickle') as f:
``````

## Reproducing the results

The notebook euler-deconvolution-examples.ipynb runs the Euler deconvolution on the synthetic data and generates the figures for the manuscript. Also presents a more detailed explanation of the method and more tests than went into the finished manuscript.

## Compiling the manuscript

The text (`manuscript.md`) is written using Markdown and compiled to PDF and Microsoft Word (doc) formats using pandoc. To produce the PDF, run:

``````make pdf
``````

and to produce doc:

``````make doc
``````

Tutorial about Euler deconvolution for The Leading Edge by @leouieda, @birocoles and @valcris

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