Synthetic total-field magnetic anomaly data and code to perform Euler deconvolution on it

Synthetic data, source code, and supplementary text for the article "Euler deconvolution of potential field data" by Leonardo Uieda, Vanderlei C. Oliveira Jr., and Valéria C. F. Barbosa. This is part of a tutorial submitted to The Leading Edge (http://library.seg.org/journal/tle). Results were generated using the open-source Python package Fatiando a Terra version 0.2 (http://www.fatiando.org). This material along with the manuscript can also be found at https://github.com/pinga-lab/paper-tle-euler-tutorial Synthetic data and model Examples in the tutorial use synthetic data generated with the IPython notebook create_synthetic_data.ipynb. 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). 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 a Terra. The serialization was done using the cPickle Python module. Reproducing the results in the tutorial The notebook euler-deconvolution-examples.ipynb runs the Euler deconvolution on the synthetic data and generates the figures for the manuscript. It also presents a more detailed explanation of the method and more tests than went into the finished manuscript.