kdcount.models module

class kdcount.models.dataset(pos, weights=None, boxsize=None, extra={})

Bases: object

A data set with a KD-tree

The class is directly used with kdcount.cluster.fof in friend-of-friend clustering.

Useful subclasses for kdcount.correlate.paircount are points, and field

Attributes

pos	(array_like (Npoints, Ndim)) position of sample points
weights	(array_like) weight of objects, default is 1.0. Not to be confused with values.
boxsize	(float) if not None, a periodic boundary is assumed, and boxsize is the size of periodic box.
extra	(dict) extra properties.

class kdcount.models.points(pos, weights=None, boxsize=None, extra={})

Bases: kdcount.models.dataset

Point-wise data set

Examples are galaxies, halos. These objects come with a position and a weight, and are discrete representation of the underlying density field.

class kdcount.models.field(pos, value, weights=None, boxsize=None, extra={})

Bases: kdcount.models.dataset

Discrte sampling data set

Examples are Lyman-alpha forest transmission fractions, over-density fields. These objects come with a position, a value, and a weight. The value is the underlying field integrated over some sampling kernel.

Attributes

pos	(array_like) sample points
wvalue	(array_like) the weighted value at pos.