(doc:quickfit)= # Quickstart `CONAN` can be run interactively in python shell/Jupyter notebook (see Tutorials section), but can also be quickly launched from [configuration files](doc:configfiles) (.dat or .yaml). ## Lightcurve fit Let's fit transit light curves of WASP-127b taken with the **EulerCam** at the Swiss telescope in La Silla. To do this, we need **input files** for each light curve. These are saved as `lc4bjd.dat`, `lc6bjd.dat`, and `lc7bjd.dat` which are text files with up to 9 columns representing the measurements at each timestamp. ``` time flux error xshift yshift airmass fwhm sky ... 7833.540364 1.000585 0.000941 -0.04 0.21 1.43 14.51 38.45 ... 7833.540988 1.000088 0.000941 -1.43 0.26 1.43 14.44 38.21 ... 7833.541569 1.000092 0.000997 -1.32 -0.04 1.42 13.84 33.30 ... 7833.542130 1.000181 0.000997 -1.53 0.04 1.42 13.94 33.28 ... ``` `CONAN` does not take note of the headers of these columns but refers to them only as column numbers [col0, col1,...,col8]. However the first 3 columns need to be - `col0` - time in BJD (or modified) - `col1` - normalized flux - `col2` - flux uncertainty Next, we need a **config file** that instructs `CONAN` on how to ingest the input files and the parameters and priors of the fit. The new configuration file in `CONAN` is in [.yaml](https://yaml.org/) format allowing users to configuration to only the relevant parameters for a specific fit. To fit the 3 light curves from **EulerCam**. We use the minimal configuration below. ```{code-block} yaml :lineno-start: 1 # ========================================== CONAN YAML Configuration ========================================== # This is a YAML configuration file for CONAN v3.3.12 # PRIORS: Fix-'F(val)', Norm-'N(mu,std)', Uni-'U(min,start,max)', TruncNorm–'TN(min,max,mu,std)', LogUni-'LU(min,start,max)' general: n_planet : 1 # number of planets in system photometry: light_curves: filepath : Notebooks/WASP-127/data/ # Light curve data directory names : [lc4bjd.dat, lc6bjd.dat, lc7bjd.dat] # List of LC filenames (must be in lc_filepath directory) filters : R # List of Filter names for each LC (for wavelength-dependent analysis) wavelength_um: 0.6 # Central wavelengths in microns for each filter clip_outliers: c1:W11C4n1 # Outlier clipping for each LC (format: 'c[columns]:W[width]C[sigma]n[iterations]',) scale_columns: med_sub # rescale data (med_sub=subtract median, rs0to1=rescale 0-1, rs-1to1=rescale -1 to 1, None=no rescaling) baseline : None # Baseline model configuration - polynomial orders for each data column of each LC limb_darkening: # Limb darkening coefficients (using Kipping parameterization) filters: [R] # list of unique filter names q1 : ['N(0.4223,0.0240)'] # list of linear LD coefficients prior for each filter q2 : ['N(0.3961,0.0157)'] # list of quadratic LD coefficients prior for each LC auto_decorr: # Automatic decorrelation settings - finds best baseline model using statistical comparison (BIC) get_decorr : True # Set to True to automatically find best decorrelation parameters delta_bic : -5 # BIC improvement threshold for parameter selection (more negative = more conservative) planet_parameters: rho_star : 'N(0.565,0.035)' # Stellar density prior (g/cm³) - alternative to duration parameterization Duration : None # Transit duration (alternative to rho_star) - set to None if using rho_star RpRs : ['U(0.05,0.108,0.17)'] # prior Planet-to-star radius ratio. make into list for multiplanet Impact_para : ['U(0,0.29,1)'] # pripr on impact parameter, list for multiplanet T_0 : ['N(6776.621239999775,0.001)'] # Mid-transit time (BJD) Period : ['F(4.17806203)'] # Orbital period (days) Eccentricity: ['F(0)'] # prior on eccentricity. list for multiplanet omega : ['F(90)'] # prior on argument of periastron (degrees: 0-360) K : ['F(0)'] # prior on RV semi amplitude. in same unit as rv data stellar_parameters: # optional. Only used post-fit to convert radius and mass to actual units radius_rsun : 'N(1.33, 0.03)' # stellar radius in Rsun mass_msun : 'N(0.95, 0.02)' # stellar mass in Msun fit_setup: sampler : dynesty # Sampling algorithm: 'dynesty' (nested sampling) or 'emcee' (MCMC) number_of_processes : 10 # Number of CPU cores for parallel processing dynesty_nlive : 300 # Number of live points # ============ END OF FILE ============================================ ``` Note that several possible setups are omitted in this **.yaml** config since they are not needed. A [full yaml config](doc:yamlconf) file can be downloaded [here](https://github.com/titans-ge/CONAN/blob/main/sample_config.yaml). An [equivalent .dat config](docs:datconf) file is also available [here](https://github.com/titans-ge/CONAN/blob/main/sample_config.dat). See from the congiration file that we do not specify any setup to model the baseline from cotrending column vector. Instead, we turned on the `get_decorr` functionality that finds the best combination of column vectors and the polynomial order to detrend the data. ### Running the fit Fitting from a config file can be launched within `python` or from the `command line` - Within `python` ``` from CONAN import fit_configfile result = fit_configfile("input_config.yaml", out_folder="output") ``` - from `command line`: ``` conanfit input_config.yam output_folder ``` to see commandline help use: ``` conanfit -h ``` ## Adding Radial velocity data Including radial velocity data in the fit requies adding a `radial_velocity` section, specifing the input files (with up to 6 columns). The first 3 columns are: - `col0` - time in BJD (or modified) - `col1` - RV measurements - `col2` - RV uncertainty while the other columns can contain e.g., `fwhm`,`BIS`,`S_HK`. We also need to include a prior for the RV semi-amplitude, `K`. For the baseline here, we chose to specify directly the polynomial order to use for each cotrending column vector which in this case are the ```{code-block} yaml :lineno-start: 1 # ========================================== CONAN YAML Configuration ========================================== # This is a YAML configuration file for CONAN v3.3.12 # PRIORS: Fix-'F(val)', Norm-'N(mu,std)', Uni-'U(min,start,max)', TruncNorm–'TN(min,max,mu,std)', LogUni-'LU(min,start,max)' general: n_planet : 1 # number of planets in system photometry: light_curves: filepath : Notebooks/WASP-127/data/ # Light curve data directory names : [lc4bjd.dat, lc6bjd.dat, lc7bjd.dat] # List of LC filenames (must be in lc_filepath directory) filters : R # List of Filter names for each LC (for wavelength-dependent analysis) wavelength_um: 0.6 # Central wavelengths in microns for each filter clip_outliers: c1:W11C4n1 # Outlier clipping for each LC (format: 'c[columns]:W[width]C[sigma]n[iterations]',) scale_columns: med_sub # rescale data (med_sub=subtract median, rs0to1=rescale 0-1, rs-1to1=rescale -1 to 1, None=no rescaling) baseline : None # Baseline model configuration - polynomial orders for each data column of each LC limb_darkening: # Limb darkening coefficients (using Kipping parameterization) filters: [R] # list of unique filter names q1 : ['N(0.4223,0.0240)'] # list of linear LD coefficients prior for each filter q2 : ['N(0.3961,0.0157)'] # list of quadratic LD coefficients prior for each LC auto_decorr: # Automatic decorrelation settings - finds best baseline model using statistical comparison (BIC) get_decorr : True # Set to True to automatically find best decorrelation parameters delta_bic : -5 # BIC improvement threshold for parameter selection (more negative = more conservative) # ==== RADIAL VELOCITY CONFIGURATION ==== radial_velocity: rv_curves: filepath : Notebooks/WASP-127/data/ # directory of rv files rv_unit : km/s # unit for radial velocity data: m/s or km/s names : [rv1.dat, rv2.dat] scale_columns: [med_sub, med_sub] # rescale data (med_sub=subtract median, rs0to1=rescale 0-1, rs-1to1=rescale -1 to 1, None=no rescaling) spline : [None, None] # c{column_no}:d{degree}K{knot_spacing} e.g. c0:d3K2 or c0:d3K2|c4:d3K2 for two dimensional apply_jitter : [y, y] # Whether to fit jitter term for each rv ('y'=yes, 'n'=no) baseline: gammas: ['N(-9.22924,0.1)', 'N(-9.2105,0.1)'] # systemic velocity priors col0 : [2, 0] # Time trend (0=none, 1=linear, 2=quadratic) col3 : [1, 0] # Column 3 decorrelation order col4 : [1, 0] # Column 4 decorrelation order col5 : [0, 0] # Column 5 decorrelation order planet_parameters: rho_star : 'N(0.565,0.035)' # Stellar density prior (g/cm³) - alternative to duration parameterization Duration : None # Transit duration (alternative to rho_star) - set to None if using rho_star RpRs : ['U(0.05,0.108,0.17)'] # prior Planet-to-star radius ratio. make into list for multiplanet Impact_para : ['U(0,0.29,1)'] # pripr on impact parameter, list for multiplanet T_0 : ['N(6776.621239999775,0.001)'] # Mid-transit time (BJD) Period : ['F(4.17806203)'] # Orbital period (days) Eccentricity: ['F(0)'] # prior on eccentricity. list for multiplanet omega : ['F(90)'] # prior on argument of periastron (degrees: 0-360) K : ['U(0,0.01,0.05)'] #prior on RV semi amplitude. in same unit as rv data stellar_parameters: # optional. Only used post-fit to convert radius and mass to actual units radius_rsun : 'N(1.33, 0.03)' # stellar radius in Rsun mass_msun : 'N(0.95, 0.02)' # stellar mass in Msun fit_setup: sampler : dynesty # Sampling algorithm: 'dynesty' (nested sampling) or 'emcee' (MCMC) number_of_processes : 10 # Number of CPU cores for parallel processing dynesty_nlive : 300 # Number of live points # ============ END OF FILE ============================================ ```