Dachshund

Tomographic reconstruction of Lyman-alpha forest flux using a Wiener filter.

Building

Dachshund is written in C++. You will need a C++ compiler, preferably with OpenMP support. On NERSC, make sure to use the gcc compiler rather than the default intel compiler (see http://www.nersc.gov/users/software/compilers/gnu/).

The make system is straightforward. Create the 'platform.make' file by copying the relevant file from the 'platforms' directory. The 'platform.make' file controls some system-specific settings, and there are examples in the 'platforms' directory.

The default make target builds the dachshund library, the dachshund application, and runs the test suite.

Usage

The dachshund application requires an input config file specifying the run-time parameters and an input data file containing the pixel data. The config file format might change during development, so please check against app/dachshund.cc (the main application source) to make sure it is up to date. Then run the dachshund application with:

$ ./dachshund.ex input.cfg

The pixel data file should contain the spatial coordinate $(x, y, z)$, delta_F value $(d)$, and delta_F noise estimate $(n)$ for each pixel in double precision. If the data vector for each pixel is $p_i = (x_i, y_i, z_i, n_i, d_i)$, the data file should be a binary blob of $p_0, p_1, \ldots, p_{n_{\rm pixel} - 1}$.

Dependencies

Dachshund uses Eigen for some linear algebra routines and Catch for organizing tests. Both are included in the repository, so there is no need to get them separately.