Quickstart
This page gives short, tested paths for using the published Python package or
running wlcov from a source checkout.
Run Online in Google Colab
The quickest route needs no clone and no local compiler setup:
The notebook installs the system GSL dependency and the published
wlcovpy==1.0.1 package, downloads inputs from the v1.0.1 release, and
checks that the compact covariance result is finite, symmetric, and 6 x 6.
Install the Python Package Locally
On Debian or Ubuntu:
sudo apt-get update
sudo apt-get install build-essential libgsl-dev python3-dev
python3 -m pip install "wlcovpy==1.0.1"
The Python package compiles its native extension during installation; a
separate source checkout or make command is not required.
Build From a Source Checkout
The remaining commands use the small test power-spectrum file included in the repository and also build the optional standalone executable.
python3 -m pip install --user numpy Cython scipy
make clean
make PYTHON=python3 all
Run the CLI
./wlcov clsfile=tests/input/Cls_ep2.txt rootDir=Output_quick \
r=0.01 theta1=0.01 theta2=0.012 thetap1=0.011 thetap2=0.013 \
m=0 mp=0 ellmin=1 ellmax=25 ppp=4 Nr=8 rmin=0.00232711 rmax=0.02 \
verbose=0 verbose_log=0
The executable prints the intermediate integrals, the covariance integrand, the radial integral, and timing information to standard output. It also writes a parameter provenance file:
ls Output_quick
cat Output_quick/parameters_null-wlcov-usedvalues
Run With a Parameter File
For reproducible runs, store parameters in a text file:
r = 0.01
theta1 = 0.01
theta2 = 0.012
thetap1 = 0.011
thetap2 = 0.013
m = 0
mp = 0
ppp = 4
ellmin = 1
ellmax = 25
clsfile = tests/input/Cls_ep2.txt
rootDir = Output_paramfile
numberThreads = 1
verbose = 0
verbose_log = 0
options =
Then run:
./wlcov paramfile=docs/examples/minimal.params
Run the Python Wrapper
python3 docs/examples/python_wrapper.py
The wrapper runs the same C core and returns the measured MainLoop CPU time
to Python. Numerical values are currently emitted by the C layer to standard
output.
Next Steps
Inputs and Parameter Files explains the two-column
C_ellinput table.Command-Line Usage lists all runtime parameters.
Performance and Parallelization explains
ppp,ellmin,ellmax, and OpenMP.Covariance-Matrix Notebook Workflow documents the Colab and source-checkout covariance workflows in detail.
Tutorials contains the other longer workflows.