TreecorrConfig

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

Bases: Config

A Config class that holds some of the parameters supported by treecorr.

The fields in this class correspond to the parameters that can be passed to any calls to treecorr methods, including catalog creation and two-point correlation function calculations. The default values set for the fields are identical to the default values set in v4.2 of treecorr.

A separate config class is used instead of constructing a DictField so that mixed types can be supported and the config can be validated at the beginning of the execution.

Notes

This is intended to be used in CalcRhoStatistics class. It only supports some of the fields that are relevant for rho-statistics calculations.

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')

history

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')

Methods Summary

compare(other[, shortcut, rtol, atol, output])

Compare this configuration to another Config for equality.

formatHistory(name, **kwargs)

Format a configuration field's history to a human-readable format.

freeze()

Make this config, and all subconfigs, read-only.

items()

Get configurations as (field name, field value) pairs.

keys()

Get field names.

load(filename[, root])

Modify this config in place by executing the Python code in a configuration file.

loadFromStream(stream[, root, filename, ...])

Modify this Config in place by executing the Python code in the provided stream.

loadFromString(code[, root, filename, ...])

Modify this Config in place by executing the Python code in the provided string.

names()

Get all the field names in the config, recursively.

save(filename[, root])

Save a Python script to the named file, which, when loaded, reproduces this config.

saveToStream(outfile[, root, skipImports])

Save a configuration file to a stream, which, when loaded, reproduces this config.

saveToString([skipImports])

Return the Python script form of this configuration as an executable string.

setDefaults()

Subclass hook for computing defaults.

toDict()

Make a dictionary of field names and their values.

update(**kw)

Update values of fields specified by the keyword arguments.

validate()

Validate the Config, raising an exception if invalid.

values()

Get field values.

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

history

Read-only history.

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 'radian')

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

Methods Documentation

compare(other, shortcut=True, rtol=1e-08, atol=1e-08, output=None)

Compare this configuration to another Config for equality.

Parameters:
otherlsst.pex.config.Config

Other Config object to compare against this config.

shortcutbool, optional

If True, return as soon as an inequality is found. Default is True.

rtolfloat, optional

Relative tolerance for floating point comparisons.

atolfloat, optional

Absolute tolerance for floating point comparisons.

outputcallable, optional

A callable that takes a string, used (possibly repeatedly) to report inequalities.

Returns:
isEqualbool

True when the two lsst.pex.config.Config instances are equal. False if there is an inequality.

Notes

Unselected targets of RegistryField fields and unselected choices of ConfigChoiceField fields are not considered by this method.

Floating point comparisons are performed by numpy.allclose.

formatHistory(name, **kwargs)

Format a configuration field’s history to a human-readable format.

Parameters:
namestr

Name of a Field in this config.

**kwargs

Keyword arguments passed to lsst.pex.config.history.format.

Returns:
historystr

A string containing the formatted history.

freeze()

Make this config, and all subconfigs, read-only.

items()

Get configurations as (field name, field value) pairs.

Returns:
itemsItemsView

Iterator of tuples for each configuration. Tuple items are:

  1. Field name.

  2. Field value.

keys()

Get field names.

Returns:
namesKeysView

List of lsst.pex.config.Field names.

load(filename, root='config')

Modify this config in place by executing the Python code in a configuration file.

Parameters:
filenamestr

Name of the configuration file. A configuration file is Python module.

rootstr, optional

Name of the variable in file that refers to the config being overridden.

For example, the value of root is "config" and the file contains:

config.myField = 5

Then this config’s field myField is set to 5.

loadFromStream(stream, root='config', filename=None, extraLocals=None)

Modify this Config in place by executing the Python code in the provided stream.

Parameters:
streamfile-like object, str, bytes, or CodeType

Stream containing configuration override code. If this is a code object, it should be compiled with mode="exec".

rootstr, optional

Name of the variable in file that refers to the config being overridden.

For example, the value of root is "config" and the file contains:

config.myField = 5

Then this config’s field myField is set to 5.

filenamestr, optional

Name of the configuration file, or None if unknown or contained in the stream. Used for error reporting.

extraLocalsdict of str to object, optional

Any extra variables to include in local scope when loading.

Notes

For backwards compatibility reasons, this method accepts strings, bytes and code objects as well as file-like objects. New code should use loadFromString instead for most of these types.

loadFromString(code, root='config', filename=None, extraLocals=None)

Modify this Config in place by executing the Python code in the provided string.

Parameters:
codestr, bytes, or CodeType

Stream containing configuration override code.

rootstr, optional

Name of the variable in file that refers to the config being overridden.

For example, the value of root is "config" and the file contains:

config.myField = 5

Then this config’s field myField is set to 5.

filenamestr, optional

Name of the configuration file, or None if unknown or contained in the stream. Used for error reporting.

extraLocalsdict of str to object, optional

Any extra variables to include in local scope when loading.

Raises:
ValueError

Raised if a key in extraLocals is the same value as the value of the root argument.

names()

Get all the field names in the config, recursively.

Returns:
nameslist of str

Field names.

save(filename, root='config')

Save a Python script to the named file, which, when loaded, reproduces this config.

Parameters:
filenamestr

Desination filename of this configuration.

rootstr, optional

Name to use for the root config variable. The same value must be used when loading (see lsst.pex.config.Config.load).

saveToStream(outfile, root='config', skipImports=False)

Save a configuration file to a stream, which, when loaded, reproduces this config.

Parameters:
outfilefile-like object

Destination file object write the config into. Accepts strings not bytes.

rootstr, optional

Name to use for the root config variable. The same value must be used when loading (see lsst.pex.config.Config.load).

skipImportsbool, optional

If True then do not include import statements in output, this is to support human-oriented output from pipetask where additional clutter is not useful.

saveToString(skipImports=False)

Return the Python script form of this configuration as an executable string.

Parameters:
skipImportsbool, optional

If True then do not include import statements in output, this is to support human-oriented output from pipetask where additional clutter is not useful.

Returns:
codestr

A code string readable by loadFromString.

setDefaults()

Subclass hook for computing defaults.

Notes

Derived Config classes that must compute defaults rather than using the Field instances’s defaults should do so here. To correctly use inherited defaults, implementations of setDefaults must call their base class’s setDefaults.

toDict()

Make a dictionary of field names and their values.

Returns:
dict_dict

Dictionary with keys that are Field names. Values are Field values.

Notes

This method uses the toDict method of individual fields. Subclasses of Field may need to implement a toDict method for this method to work.

update(**kw)

Update values of fields specified by the keyword arguments.

Parameters:
**kw

Keywords are configuration field names. Values are configuration field values.

Notes

The __at and __label keyword arguments are special internal keywords. They are used to strip out any internal steps from the history tracebacks of the config. Do not modify these keywords to subvert a Config instance’s history.

Examples

This is a config with three fields:

>>> from lsst.pex.config import Config, Field
>>> class DemoConfig(Config):
...     fieldA = Field(doc='Field A', dtype=int, default=42)
...     fieldB = Field(doc='Field B', dtype=bool, default=True)
...     fieldC = Field(doc='Field C', dtype=str, default='Hello world')
...
>>> config = DemoConfig()

These are the default values of each field:

>>> for name, value in config.iteritems():
...     print(f"{name}: {value}")
...
fieldA: 42
fieldB: True
fieldC: 'Hello world'

Using this method to update fieldA and fieldC:

>>> config.update(fieldA=13, fieldC='Updated!')

Now the values of each field are:

>>> for name, value in config.iteritems():
...     print(f"{name}: {value}")
...
fieldA: 13
fieldB: True
fieldC: 'Updated!'
validate()

Validate the Config, raising an exception if invalid.

Raises:
lsst.pex.config.FieldValidationError

Raised if verification fails.

Notes

The base class implementation performs type checks on all fields by calling their validate methods.

Complex single-field validation can be defined by deriving new Field types. For convenience, some derived lsst.pex.config.Field-types (ConfigField and ConfigChoiceField) are defined in lsst.pex.config that handle recursing into subconfigs.

Inter-field relationships should only be checked in derived Config classes after calling this method, and base validation is complete.

values()

Get field values.

Returns:
valuesValuesView

Iterator of field values.