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We recommend installing pyaneti in a dedicated Python virtual environment to isolate dependencies and avoid conflicts. You can create a virtual environment using Python's built-in venv, virtualenvwrapper, conda, or your favourite environment manager.
You can create an environment using Python venv as
# Create and activate a virtual environment
python3 -m venv pyaneti-env
source pyaneti-env/bin/activate
# Upgrade pip and install build tools
python -m pip install --upgrade pip wheel meson meson-python ninja
Or using virtualenvwrapper (if you have it installed, check documentation)
# Create and activate a virtual environment
mkvirtualenv pyaneti-env
workon pyaneti-dev
# Upgrade pip and install build tools
python -m pip install --upgrade pip wheel meson meson-python ninja
Or using conda as
conda create -n pyaneti-env -c conda-forge python gfortran openblas lapack meson meson-python ninja numpy
conda activate pyaneti-env
You can now install pyaneti using pip.
Just clone the pyaneti repository
git clone https://github.com/oscaribv/pyaneti
The advantage of cloning the repository is the possibility to follow the changes to this package easily with git pull (learn more about git at https://git-scm.com/).
The next step is to enter the pyaneti directory
cd pyaneti
Now install the code as
pip install .
This will start pyaneti installation, and all its dependencies.
You should see something like this if the code is installed successfully
Successfully installed pyaneti-2.1.0
This setup has been tested on Linux (Fedora, Ubuntu) and macOS. If you experience issues, ensure your system Fortran compiler supports OpenMP and that the Meson build system is installed correctly.
Now you are ready to run the code for the first time. Just type
python run_pyaneti.py test
The program will start. You will see something like:
==============================
------------------------------
INITIAL CONFIGURATION
------------------------------
Star = test
No. planets = 1
------------------------------
iter max = 100000000
thin factor = 1
nconv = 500
nwalkers = 100
------------------------------
fit RV = [True]
fit Transit = [True]
------------------------------
LC data = free
cadence time = 30.000 min
n rebinning = 1
Stellar priors = [True]
------------------------------
PLANET testb
------------------------------
PRIOR RANGES
------------------------------
T0 = u[ 2448285.0500 , 2448285.1500 ]
P = u[ 365.2060 , 365.3060 ]
ew1= f[ 0.0000 , 1.0000 ]
ew2= f[ 0.0000 , 1.0000 ]
b = f[ 0.0000 , 1.0000 ]
a = g[ 200.0000 , 250.0000 ]
rp = u[ 0.0000 , 0.1000 ]
K = u[ 0.0000 , 0.0010 ]
------------------------------
Other parameter priors
------------------------------
q1 = g[ 0.3464 , 0.0500 ]
q2 = g[ 0.2839 , 0.0500 ]
Super_telescope = u[ 21.0719 , 23.0721 ]
==============================
CREATING RANDOM SEED
CREATING CHAINS
STARTING MCMC CALCULATION
RV datapoints = 36
TR datapoints = 112
No. parameters = 8
dof = 140
==================================
Chain statistics
==================================
chain | reduced chi^2
best : 64667.93
worst : **********
mean : **********
==================================
STARTING INFINITE LOOP!
==================================
Chain statistics
==================================
chain | reduced chi^2
best : 0.95
worst : 1.05
mean : 0.99
==================================
==================================
PERFOMING GELMAN-RUBIN
TEST FOR CONVERGENCE
==================================
==================================
CHAINS HAVE NOT CONVERGED YET!
500 ITERATIONS MORE!
==================================
==================================
Chain statistics
==================================
chain | reduced chi^2
best : 0.95
worst : 1.09
mean : 0.99
==================================
==================================
PERFOMING GELMAN-RUBIN
TEST FOR CONVERGENCE
==================================
==================================
CHAINS HAVE CONVERGED
==================================
CREATING OUTPUT DATA FILES
==================================
STARTING CHAIN CLUSTERING
Initial number of chains: 100
Final number of chains: 100
--------------------------------------------------------------
Summary:
N_chains = 100
N_iter = 500
thin_factor = 1
N_rv_data = 36
N_tr_data = 112
N_data = 148
N_pars = 8
chi2_rv = 7.2765
chi2_tr = 125.9964
chi2 = 133.2729
dof = 140
chi2/dof = 0.9519
ln likelihood_rv = 377.7453
ln likelihood_tr = 1131.1755
ln likelihood = 1508.9208
BIC = -2977.8640
AIC = -3001.8417
--------------------------------------------------------------
INPUT STELLAR PARAMETERS
--------------------------------------------------------------
M_* = 1.0000000 - 0.1000000 + 0.1000000 solar masses
R_* = 1.0000000 - 0.1000000 + 0.1000000 solar radii
T_* = 5772.0000000 - 100.0000000 + 100.0000000 K
--------------------------------------------------------------
Parameters test b
-------------------------Fitted-------------------------------
T0 = 2448285.0955436 - 0.0031192 + 0.0031409 days
P = 365.2508520 - 0.0049167 + 0.0048356 days
ew 1 = 0.0000000 - 0.0000000 + 0.0000000
ew 2 = 0.0000000 - 0.0000000 + 0.0000000
b = 0.0000000 - 0.0000000 + 0.0000000
a/R* = 215.4640517 - 2.3708930 + 2.5122541
rp/R* = 0.0093235 - 0.0000712 + 0.0000775
K = 0.0881821 - 0.0024223 + 0.0023856 m/s
-------------------------Derived------------------------------
Mp = 0.9841032 - 0.0704355 + 0.0718640 M_earth
Rp = 1.0173252 - 0.1028264 + 0.1013333 R_earth
e = 0.0000000 - 0.0000000 + 0.0000000
w = 0.0000000 - 0.0000000 + 0.0000000 deg
i = 90.0000000 - 0.0000000 + 0.0000000 deg
a = 1.0019439 - 0.1014392 + 0.1005043 AU
Insolation = 0.9967687 - 0.0707513 + 0.0741733 F_Earth
rho* = 1.4183711 - 0.0463035 + 0.0502306 g/cm^3 (transit)
rho* = 1.4065628 - 0.3676615 + 0.5586840 g/cm^3 (stellar paramters)
rho_p = 5.1298925 - 1.3074050 + 1.9887038 g/cm^3
g_p = 936.8970215 - 30.5861395 + 32.3670771 cm/s^2 (K and Rp/R*)
g_p = 933.8572371 - 172.6787114 + 234.1233896 cm/s^2 (planet parameters)
Tperi = 2448193.7827742 - 0.0039813 + 0.0041039 days
Teq = 278.1026529 - 5.0720559 + 5.0352570 K (albedo=0)
T_tot = 13.0713846 - 0.1507021 + 0.1448215 hours
T_full = 12.8294707 - 0.1483685 + 0.1432300 hours
--------------------------------------------------------------
-------------------- Other parameters -----------------------
q1 = 0.3760168 - 0.0418577 + 0.0442539
q2 = 0.3157777 - 0.0460379 + 0.0468480
u1 = 0.3855446 - 0.0574350 + 0.0598140
u2 = 0.2246861 - 0.0583548 + 0.0612362
Sys. vel. Super_telescope = 22.0719865 - 0.0000015 + 0.0000016 m/s
--------------------------------------------------------------
Creating outpy/test_out/test_posterior.pdf
Creating outpy/test_out/test_correlations.pdf
Creating outpy/test_out/testb_tr.pdf
Creating outpy/test_out/test_rv_all.pdf
Creating outpy/test_out/testb_rv.pdf
If you see this output it means that pyaneti ended succesfully.
Now let us check the plots (I use evince but you can use your favourite pdf reader)
evince outpy/test_out/testb_tr.pdf outpy/test_out/testb_rv.pdf
You will see some nice plots that look like this
Let me explain you briefly what this test fit was about:
If you were an advanced alien civilization with really high technology, and "lucky" enough to see an Earth-like planet crossing in front of a Sun-like star, this is how the Earth would look like to you.
Look at those well-known parameters:
- 1 Earth Mass
- 1 Earth radii
- Period of 365 days
- 1 AU semi-major axis
- Density of ~5.5 g/cm^2,
- Gravity of ~10 m/s^2.
Of course, you would need a spectrograph with a precision of a few cm/s and also a very nice photometer, and an excellent way to remove stellar intrinsic signals in your data, but that is another story.
If you are at this point, you learned two things. First, with good data you can obtain really nice planet parameters and second, you learned how to run pyaneti.
