getdist.densities
- class getdist.densities.Density1D(x, P=None, view_ranges=None)[source]
Class for 1D marginalized densities, inheriting from
GridDensity
. You can call it like a InterpolatedUnivariateSpline obect to get interpolated values, or call Prob.- Parameters:
x – array of x values
P – array of densities at x values
view_ranges – optional range for viewing density
- Prob(x, derivative=0)[source]
Calculate density at position x by interpolation in the density grid
- Parameters:
x – x value
derivative – optional order of derivative to calculate (default: no derivative)
- Returns:
P(x) density value
- getLimits(p, interpGrid=None, accuracy_factor=None)[source]
Get parameter equal-density confidence limits (a credible interval). If the density is bounded, may only have a one-tail limit.
- Parameters:
p – list of limits to calculate, e.g. [0.68, 0.95]
interpGrid – optional pre-computed cache
accuracy_factor – parameter to boost default accuracy for fine sampling
- Returns:
list of (min, max, has_min, has_top) values where has_min and has_top are True or False depending on whether lower and upper limit exists
- class getdist.densities.Density2D(x, y, P=None, view_ranges=None)[source]
Class for 2D marginalized densities, inheriting from
GridDensity
. You can call it like aRectBivariateSpline
object to get interpolated values.- Parameters:
x – array of x values
y – array of y values
P – 2D array of density values at x, y
view_ranges – optional ranges for viewing density
- Prob(x, y, grid=False)[source]
Evaluate density at x,y using interpolation
- Parameters:
x – x value or array
y – y value or array
grid – whether to make a grid, see
RectBivariateSpline
. Default False.
- class getdist.densities.DensityND(xs, P=None, view_ranges=None)[source]
Class for ND marginalized densities, inheriting from
GridDensity
andLinearNDInterpolator
.This is not well tested recently.
- Parameters:
xs – list of arrays of x values
P – ND array of density values at xs
view_ranges – optional ranges for viewing density
- class getdist.densities.GridDensity[source]
Base class for probability density grids (normalized or not)
- Variables:
P – array of density values
- getContourLevels(contours=(0.68, 0.95))[source]
Get contour levels
- Parameters:
contours – list of confidence limits to get (default [0.68, 0.95])
- Returns:
list of contour levels
- getdist.densities.getContourLevels(inbins, contours=(0.68, 0.95), missing_norm=0, half_edge=True)[source]
Get contour levels enclosing “contours” fraction of the probability, for any dimension bins array
- Parameters:
inbins – binned density.
contours – list or tuple of confidence contours to calculate, default [0.68, 0.95]
missing_norm – accounts of any points not included in inbins (e.g. points in far tails that are not in inbins)
half_edge – If True, edge bins are only half integrated over in each direction.
- Returns:
list of density levels