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DM-45899: Export TreecorrConfig to meas_algorithms #293

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Oct 15, 2024
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DM-45899: Export TreecorrConfig to meas_algorithms #293

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ac5f61f
export TreecorrConfig to meas_algorithms on tickets/DM-45899-transfer
PFLeget Oct 11, 2024
df5147c
add deprecation warning for TreecorrConfig
PFLeget Oct 14, 2024
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207 changes: 13 additions & 194 deletions python/lsst/analysis/tools/actions/vector/calcRhoStatistics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,9 @@

import numpy as np
import treecorr # type: ignore[import]
from lsst.pex.config import ChoiceField, Config, ConfigField, Field, FieldValidationError
from deprecated.sphinx import deprecated
from lsst.meas.algorithms.treecorrUtils import TreecorrConfig as TreecorrConfigNew
from lsst.pex.config import ChoiceField, ConfigField, Field

from ...interfaces import KeyedData, KeyedDataAction, Vector
from .calcMomentSize import CalcMomentSize
Expand All @@ -46,199 +48,16 @@
_LOG = logging.getLogger(__name__)


class TreecorrConfig(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 `~lsst.pex.config.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.
"""

nbins = Field[int](
doc=(
"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."
),
optional=True,
check=lambda x: x > 0,
)

bin_size = Field[float](
doc=(
"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."
),
optional=True,
)

min_sep = Field[float](
doc=(
"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."
),
optional=True,
)

max_sep = Field[float](
doc=(
"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."
),
optional=True,
)

sep_units = ChoiceField[str](
doc=(
"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."
),
default="radian",
optional=True,
allowed={units: units for units in ["arcsec", "arcmin", "degree", "hour", "radian"]},
)

bin_slop = Field[float](
doc=(
"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. "
r"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."
),
default=None,
optional=True,
)

precision = Field[int](
doc=("The precision to use for the output values. This specifies how many digits to write."),
default=4,
optional=True,
check=lambda x: x > 0,
)

metric = ChoiceField[str](
doc=(
"Which metric to use for distance measurements. For details, see "
"https://rmjarvis.github.io/TreeCorr/_build/html/metric.html"
),
default="Euclidean",
optional=True,
allowed={
"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.",
},
)

bin_type = ChoiceField[str](
doc="What type of binning should be used?",
default="Log",
optional=True,
allowed={
"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)"
),
},
)

var_method = ChoiceField[str](
doc="Which method to use for estimating the variance",
default="shot",
optional=True,
allowed={
method: method
for method in [
"shot",
"jackknife",
"sample",
"bootstrap",
"marked_bootstrap",
]
},
)

npatch = Field[int](
doc="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.)",
default=1,
optional=True,
)

num_bootstrap = Field[int](
doc=("How many bootstrap samples to use for the 'bootstrap' and 'marked_bootstrap' var methods."),
default=500,
optional=True,
)

rng_seed = Field[int](
doc="Value to seed the treecorr random number generator with. Used to generate patches.",
default=13579,
)

def validate(self):
# Docs inherited from base class
super().validate()
req_params = (self.nbins, self.bin_size, self.min_sep, self.max_sep)
num_req_params = sum(param is not None for param in req_params)
if num_req_params != 3:
msg = (
"You must specify exactly three of ``nbins``, ``bin_size``, ``min_sep`` and ``max_sep``"
f" in treecorr_config. {num_req_params} parameters were set instead."
)
raise FieldValidationError(self.__class__.bin_size, self, msg)

if self.min_sep is not None and self.max_sep is not None:
if self.min_sep > self.max_sep:
raise FieldValidationError(self.__class__.min_sep, self, "min_sep must be <= max_sep")
@deprecated(
reason=(
"TreecorrConfig is no longer a part of analysis_tools (DM-45899)"
"Please use lsst.meas.algorithms.treecorrUtils.TreecorrConfig instead."
),
version="v28.0",
category=FutureWarning,
)
class TreecorrConfig(TreecorrConfigNew):
pass


class CalcRhoStatistics(KeyedDataAction):
Expand Down
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