Installation
You can use pip
to install the package automatically:
pip install setigen
Alternately, you can clone the repository and install it directly. At the command line, execute:
git clone git@github.com:bbrzycki/setigen.git
python setup.py install
One of the dependencies for setigen
is blimpy
, which is used for working
with BL filterbank data products. Note that you can still generate synthetic
data frames even without observational data!
Because of how the bitshuffle
package was written, if you are working with
HDF5 data products (e.g. ending with “.hdf5” or “.h5”), you may also need to
do the following, especially if you’d like to save setigen
frame data as
HDF5 files:
pip install -U git+https://github.com/h5py/h5py
pip install git+https://github.com/kiyo-masui/bitshuffle
Note: this can lead to h5py
compatibility issues with older versions of
Tensorflow. Some work-arounds: if possible, work primarily with filterbank
files, or use multiple Python environments to separate data handling and
Tensorflow work.
To use GPU with setigen.voltage
setigen.voltage
’s GPU acceleration is powered by CuPy
(https://docs.cupy.dev/en/stable/install.html). Installation is not required
to use vanilla setigen
or the voltage module, but it is highly recommended
to accelerate voltage computations. While it isn’t used directly by setigen
,
you may also find it helpful to install cusignal
(https://github.com/rapidsai/cusignal) for access to CUDA-enabled versions of
scipy
functions when writing custom voltage signal source functions.