TreecorrConfig

class lsst.analysis.tools.actions.vector.TreecorrConfig(*args, **kwargs)

Bases: TreecorrConfig

Deprecated since version v28.0: TreecorrConfig is no longer a part of analysis_tools (DM-45899). Please use lsst.meas.algorithms.treecorrUtils.TreecorrConfig instead.

Attributes Summary

bin_size	The width of the bins in log(separation).
bin_slop	How much slop to allow in the placement of pairs in the bins.
bin_type	What type of binning should be used? (str, default 'Log')
max_sep	The maximum separation in units of sep_units, if relevant.
metric	Which metric to use for distance measurements.
min_sep	The minimum separation in units of sep_units, if relevant.
nbins	How many bins to use.
npatch	How many patches to split the catalog into for the purpose of jackknife variance or other options that involve running via patches (boostrap, marked_boostrap etc.) (int, default 1)
num_bootstrap	How many bootstrap samples to use for the 'bootstrap' and 'marked_bootstrap' var methods.
precision	The precision to use for the output values.
rng_seed	Value to seed the treecorr random number generator with.
sep_units	The units to use for the separation values, given as a string.
var_method	Which method to use for estimating the variance (str, default 'shot')

Attributes Documentation

bin_size

The width of the bins in log(separation). Exactly three of nbins, bin_size, min_sep, max_sep are required. If bin_size is not given, it will be calculated from the values of the other three. (float, default None)

bin_slop

How much slop to allow in the placement of pairs in the bins. If bin_slop = 1, then the bin into which a particular pair is placed may be incorrect by at most 1.0 bin widths. If None, use a bin_slop that gives a maximum error of 10% on any bin, which has been found to yield good results for most applications. (float, default None)

bin_type

What type of binning should be used? (str, default 'Log')

Allowed values:

'Log'

Logarithmic binning in the distance. The bin steps will be uniform in log(r) from log(min_sep) .. log(max_sep).

'Linear'

Linear binning in the distance. The bin steps will be uniform in r from min_sep .. max_sep.

'TwoD'

2-dimensional binning from x = (-max_sep .. max_sep) and y = (-max_sep .. max_sep). The bin steps will be uniform in both x and y. (i.e. linear in x,y)

'None'

Field is optional

max_sep

The maximum separation in units of sep_units, if relevant. Exactly three of nbins, bin_size, min_sep, max_sep are required. If max_sep is not given, it will be calculated from the values of the other three. (float, default None)

metric

Which metric to use for distance measurements. For details, see https://rmjarvis.github.io/TreeCorr/_build/html/metric.html (str, default 'Euclidean')

Allowed values:

'Euclidean'

straight-line Euclidean distance between two points

'FisherRperp'

the perpendicular component of the distance, following the definitions in Fisher et al, 1994 (MNRAS, 267, 927)

'OldRperp'

the perpendicular component of the distance using the definition of Rperp from TreeCorr v3.x.

'Rlens'

Distance from the first object (taken to be a lens) to the line connecting Earth and the second object (taken to be a lensed source).

'Arc'

the true great circle distance for spherical coordinates.

'Periodic'

Like Euclidean, but with periodic boundaries.

'None'

Field is optional

min_sep

The minimum separation in units of sep_units, if relevant. Exactly three of nbins, bin_size, min_sep, max_sep are required. If min_sep is not given, it will be calculated from the values of the other three. (float, default None)

nbins

How many bins to use. (Exactly three of nbins, bin_size, min_sep, max_sep are required. If nbins is not given, it will be calculated from the values of the other three, rounding up to the next highest integer. In this case, bin_size will be readjusted to account for this rounding up. (int, default None)

npatch

How many patches to split the catalog into for the purpose of jackknife variance or other options that involve running via patches (boostrap, marked_boostrap etc.) (int, default 1)

num_bootstrap

How many bootstrap samples to use for the ‘bootstrap’ and ‘marked_bootstrap’ var methods. (int, default 500)

precision

The precision to use for the output values. This specifies how many digits to write. (int, default 4)

rng_seed

Value to seed the treecorr random number generator with. Used to generate patches. (int, default 13579)

sep_units

The units to use for the separation values, given as a string. This includes both min_sep and max_sep above, as well as the units of the output distance values. (str, default None)

Allowed values:

'arcsec'

arcsec

'arcmin'

arcmin

'degree'

degree

'hour'

hour

'radian'

radian

'None'

Field is optional

var_method

Which method to use for estimating the variance (str, default 'shot')

Allowed values:

'shot'

shot

'jackknife'

jackknife

'sample'

sample

'bootstrap'

bootstrap

'marked_bootstrap'

marked_bootstrap

'None'

Field is optional