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| def | lalinference.bayespputils.get_end (siminspiral) |
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| def | lalinference.bayespputils.replace_column (table, old, new) |
| | Workaround for missing astropy.table.Table.replace_column method, which was added in Astropy 1.1. More...
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| def | lalinference.bayespputils.as_array (table) |
| | Workaround for missing astropy.table.Table.as_array method, which was added in Astropy 1.0. More...
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| def | lalinference.bayespputils.det_end_time (ifo_prefix, inj) |
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| def | lalinference.bayespputils.get_prior (name) |
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| def | lalinference.bayespputils.plot_label (param) |
| | A lookup table for plot labels. More...
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| def | lalinference.bayespputils.skyArea (bounds) |
| | functions used in 2stage kdtree More...
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| def | lalinference.bayespputils.random_split (items, fraction) |
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| def | lalinference.bayespputils.addSample (tree, coordinates) |
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| def | lalinference.bayespputils.kdtree_bin_sky_volume (posterior, confidence_levels) |
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| def | lalinference.bayespputils.kdtree_bin_sky_area (posterior, confidence_levels, samples_per_bin=10) |
| | takes samples and applies a KDTree to them to return confidence levels returns confidence_intervals - dictionary of user_provided_CL:calculated_area b - ordered list of KD leaves injInfo - if injection values provided then returns [Bounds_of_inj_kd_leaf ,number_samples_in_box, weight_of_box,injection_CL ,injection_CL_area] Not quite sure that the repeated samples case is fixed, posibility of infinite loop. More...
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| def | lalinference.bayespputils.kdtree_bin (posterior, coord_names, confidence_levels, initial_boundingbox=None, samples_per_bin=10) |
| | takes samples and applies a KDTree to them to return confidence levels returns confidence_intervals - dictionary of user_provided_CL:calculated_volume b - ordered list of KD leaves initial_boundingbox - list of lists [upperleft_coords,lowerright_coords] injInfo - if injection values provided then returns [Bounds_of_inj_kd_leaf ,number_samples_in_box, weight_of_box,injection_CL ,injection_CL_volume] Not quite sure that the repeated samples case is fixed, posibility of infinite loop. More...
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| def | lalinference.bayespputils.kdtree_bin2Step (posterior, coord_names, confidence_levels, initial_boundingbox=None, samples_per_bin=10, injCoords=None, alternate=False, fraction=0.5, skyCoords=False) |
| | input: posterior class instance, list of confidence levels, optional choice of inital parameter space, samples per box in kdtree note initial_boundingbox is [[lowerbound of each param][upper bound of each param]], if not specified will just take limits of samples fraction is proportion of samples used for making the tree structure. More...
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| def | lalinference.bayespputils.greedy_bin_two_param (posterior, greedy2Params, confidence_levels) |
| | Determine the 2-parameter Bayesian Confidence Intervals using a greedy binning algorithm. More...
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| def | lalinference.bayespputils.pol2cart (long, lat) |
| | Utility function to convert longitude,latitude on a unit sphere to cartesian co-ordinates. More...
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| def | lalinference.bayespputils.sph2cart (r, theta, phi) |
| | Utiltiy function to convert r,theta,phi to cartesian co-ordinates. More...
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| def | lalinference.bayespputils.cart2sph (x, y, z) |
| | Utility function to convert cartesian coords to r,theta,phi. More...
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| def | lalinference.bayespputils.plot_sky_map (hpmap, outdir, inj=None, nest=True) |
| | Plots a sky map from a healpix map, optionally including an injected position. More...
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| def | lalinference.bayespputils.skymap_confidence_areas (hpmap, cls) |
| | Returns the area (in square degrees) for each confidence level with a greedy binning algorithm for the given healpix map. More...
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| def | lalinference.bayespputils.skymap_inj_pvalue (hpmap, inj, nest=True) |
| | Returns the greedy p-value estimate for the given injection. More...
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| def | lalinference.bayespputils.mc2ms (mc, eta) |
| | Utility function for converting mchirp,eta to component masses. More...
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| def | lalinference.bayespputils.q2ms (mc, q) |
| | Utility function for converting mchirp,q to component masses. More...
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| def | lalinference.bayespputils.q2eta (q) |
| | Utility function for converting q to eta. More...
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| def | lalinference.bayespputils.mc2q (mc, eta) |
| | Utility function for converting mchirp,eta to new mass ratio q (m2/m1). More...
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| def | lalinference.bayespputils.ang_dist (long1, lat1, long2, lat2) |
| | Find the angular separation of (long1,lat1) and (long2,lat2), which are specified in radians. More...
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| def | lalinference.bayespputils.array_dot (vec1, vec2) |
| | Calculate dot products between vectors in rows of numpy arrays. More...
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| def | lalinference.bayespputils.array_ang_sep (vec1, vec2) |
| | Find angles between vectors in rows of numpy arrays. More...
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| def | lalinference.bayespputils.array_polar_ang (vec) |
| | Find polar angles of vectors in rows of a numpy array. More...
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| def | lalinference.bayespputils.rotation_matrix (angle, direction) |
| | Compute general rotation matrices for a given angles and direction vectors. More...
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| def | lalinference.bayespputils.ROTATEZ (angle, vx, vy, vz) |
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| def | lalinference.bayespputils.ROTATEY (angle, vx, vy, vz) |
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| def | lalinference.bayespputils.orbital_momentum (fref, m1, m2, inclination) |
| | Calculate orbital angular momentum vector. More...
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| def | lalinference.bayespputils.orbital_momentum_mag (fref, m1, m2, eta) |
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| def | lalinference.bayespputils.component_momentum (m, a, theta, phi) |
| | Calculate BH angular momentum vector. More...
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| def | lalinference.bayespputils.symm_tidal_params (lambda1, lambda2, q) |
| | Calculate best tidal parameters [Eqs. More...
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| def | lalinference.bayespputils.spin_angles (fref, mc, eta, incl, a1, theta1, phi1, a2=None, theta2=None, phi2=None) |
| | Calculate physical spin angles. More...
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| def | lalinference.bayespputils.chi_precessing (m1, a1, tilt1, m2, a2, tilt2) |
| | Calculate the magnitude of the effective precessing spin following convention from Phys. More...
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| def | lalinference.bayespputils.calculate_redshift (distance, h=0.6790, om=0.3065, ol=0.6935, w0=-1.0) |
| | Calculate the redshift from the luminosity distance measurement using the Cosmology Calculator provided in LAL. More...
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| def | lalinference.bayespputils.source_mass (mass, redshift) |
| | Calculate source mass parameter for mass m as: m_source = m / (1.0 + z) For a parameter m. More...
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| def | lalinference.bayespputils.integrand_distance (redshift, nonGR_alpha) |
| | Following functions added for testing Lorentz violations. More...
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| def | lalinference.bayespputils.DistanceMeasure (redshift, nonGR_alpha) |
| | D_alpha = ((1+z)^(1-alpha))/H_0 * D_alpha # from eq.15 of arxiv 1110.2720 D_alpha calculated from integrand in above function. More...
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| def | lalinference.bayespputils.lambda_a (redshift, nonGR_alpha, lambda_eff, distance) |
| | Converting from the effective wavelength-like parameter to lambda_A: lambda_A = lambda_{eff}*(D_alpha/D_L)^(1/(2-alpha))*(1/(1+z)^((1-alpha)/(2-alpha))) More...
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| def | lalinference.bayespputils.amplitudeMeasure (redshift, nonGR_alpha, lambda_eff, distance) |
| | Converting to Lorentz violating parameter "A" in dispersion relation from lambda_A: A = (lambda_A/h)^(alpha-2) # eqn. More...
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| def | lalinference.bayespputils.physical2radiationFrame (theta_jn, phi_jl, tilt1, tilt2, phi12, a1, a2, m1, m2, fref, phiref) |
| | changes for testing Lorentz violations made till here More...
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| def | lalinference.bayespputils.plot_one_param_pdf_kde (fig, onedpos) |
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| def | lalinference.bayespputils.plot_one_param_pdf (posterior, plot1DParams, analyticPDF=None, analyticCDF=None, plotkde=False) |
| | Plots a 1D histogram and (gaussian) kernel density estimate of the distribution of posterior samples for a given parameter. More...
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| def | lalinference.bayespputils.getRAString (radians, accuracy='auto') |
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| def | lalinference.bayespputils.getDecString (radians, accuracy='auto') |
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| def | lalinference.bayespputils.plot_corner (posterior, levels, parnames=None) |
| | Make a corner plot using the triangle module (See http://github.com/dfm/corner.py) More...
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| def | lalinference.bayespputils.plot_two_param_kde_greedy_levels (posteriors_by_name, plot2DkdeParams, levels, colors_by_name, line_styles=__default_line_styles, figsize=(4, 3), dpi=250, figposition=[0.2, 0.2, 0.48, 0.75], legend='right', hatches_by_name=None, Npixels=50) |
| | Plots a 2D kernel density estimate of the 2-parameter marginal posterior. More...
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| def | lalinference.bayespputils.plot_two_param_kde (posterior, plot2DkdeParams) |
| | Plots a 2D kernel density estimate of the 2-parameter marginal posterior. More...
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| def | lalinference.bayespputils.get_inj_by_time (injections, time) |
| | Filter injections to find the injection with end time given by time +/- 0.1s. More...
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| def | lalinference.bayespputils.histogram2D (posterior, greedy2Params, confidence_levels) |
| | Returns a 2D histogram and edges for the two parameters passed in greedy2Params, plus the actual discrete confidence levels imposed by the finite number of samples. More...
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| def | lalinference.bayespputils.plot_two_param_greedy_bins_contourf (posteriors_by_name, greedy2Params, confidence_levels, colors_by_name, figsize=(7, 6), dpi=120, figposition=[0.3, 0.3, 0.5, 0.5], legend='right', hatches_by_name=None) |
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| def | lalinference.bayespputils.plot_two_param_greedy_bins_hist (posterior, greedy2Params, confidence_levels) |
| | Histograms of the ranked pixels produced by the 2-parameter greedy binning algorithm colured by their confidence level. More...
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| def | lalinference.bayespputils.greedy_bin_one_param (posterior, greedy1Param, confidence_levels) |
| | Determine the 1-parameter Bayesian Confidence Interval using a greedy binning algorithm. More...
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| def | lalinference.bayespputils.contigious_interval_one_param (posterior, contInt1Params, confidence_levels) |
| | Calculates the smallest contigious 1-parameter confidence interval for a set of given confidence levels. More...
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| def | lalinference.bayespputils.autocorrelation (series) |
| | Returns an estimate of the autocorrelation function of a given series. More...
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| def | lalinference.bayespputils.autocorrelation_length_estimate (series, acf=None, M=5, K=2) |
| | Attempts to find a self-consistent estimate of the autocorrelation length of a given series. More...
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| def | lalinference.bayespputils.effectiveSampleSize (samples, Nskip=1) |
| | Compute the effective sample size, calculating the ACL using only the second half of the samples to avoid ACL overestimation due to chains equilibrating after adaptation. More...
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| def | lalinference.bayespputils.readCoincXML (xml_file, trignum) |
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| def | lalinference.bayespputils.find_ndownsample (samples, nDownsample) |
| | Given a list of files, threshold value, and a desired number of outputs posterior samples, return the skip number to achieve the desired number of posterior samples. More...
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| def | lalinference.bayespputils.parse_converge_output_section (fo) |
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| def | lalinference.bayespputils.vo_nest2pos (nsresource, Nlive=None) |
| | Parse a VO Table RESOURCE containing nested sampling output and return a VOTable TABLE element with posterior samples in it. More...
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| def | lalinference.bayespputils.confidence_interval_uncertainty (cl, cl_bounds, posteriors) |
| | Returns a tuple (relative_change, fractional_uncertainty, percentile_uncertainty) giving the uncertainty in confidence intervals from multiple posteriors. More...
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| def | lalinference.bayespputils.plot_waveform (pos=None, siminspiral=None, event=0, path=None, ifos=['H1', 'L1', 'V1']) |
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| def | lalinference.bayespputils.plot_psd (psd_files, outpath=None, f_min=30.) |
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| def | lalinference.bayespputils.cred_interval (x, cl=.9, lower=True) |
| | Return location of lower or upper confidence levels Args: x: List of samples. More...
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| def | lalinference.bayespputils.spline_angle_xform (delta_psi) |
| | Returns the angle in degrees corresponding to the spline calibration parameters delta_psi. More...
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| def | lalinference.bayespputils.plot_spline_pos (logf, ys, nf=100, level=0.9, color='k', label=None, xform=None) |
| | Plot calibration posterior estimates for a spline model in log space. More...
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| def | lalinference.bayespputils.plot_calibration_pos (pos, level=.9, outpath=None) |
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| def | lalinference.bayespputils.plot_burst_waveform (pos=None, simburst=None, event=0, path=None, ifos=['H1', 'L1', 'V1']) |
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| def | lalinference.bayespputils.make_1d_table (html, legend, label, pos, pars, noacf, GreedyRes, onepdfdir, sampsdir, savepdfs, greedy, analyticLikelihood, nDownsample) |
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1.9.4