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_actions.py
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1from __future__ import annotations
2
3__all__ = ("SingleColumnAction", "MultiColumnAction", "CoordColumn", "MagColumnDN", "SumColumns", "AddColumn",
4 "DivideColumns", "SubtractColumns", "MultiplyColumns", "FractionalDifferenceColumns",
5 "MagColumnNanoJansky", "DiffOfDividedColumns", "PercentDiffOfDividedColumns",)
6
7from typing import Iterable
8
9import warnings
10import numpy as np
11import pandas as pd
12from astropy import units
13
14from lsst.pex.config.configurableActions import ConfigurableActionStructField, ConfigurableActionField
15from ._baseDataFrameActions import DataFrameAction
16from ._evalColumnExpression import makeColumnExpressionAction
17
18from lsst.pex.config import Field
19
20
22 column = Field(doc="Column to load for this action", dtype=str, optional=False)
23
24 @property
25 def columns(self) -> Iterable[str]:
26 return (self.column, )
27
28 def __call__(self, df, **kwargs):
29 return df[self.column]
30
31
33 actions = ConfigurableActionStructField(doc="Configurable actions to use in a joint action")
34
35 @property
36 def columns(self) -> Iterable[str]:
37 yield from (column for action in self.actions for column in action.columns)
38
39
41 inRadians = Field(doc="Return the column in radians if true", default=True, dtype=bool)
42
43 def __call__(self, df):
44 col = super().__call__(df)
45 return col * 180 / np.pi if self.inRadians else col
46
47
49 coadd_zeropoint = Field(doc="Magnitude zero point", dtype=float, default=27)
50
51 def __call__(self, df: pd.DataFrame, **kwargs):
52 if not (fluxMag0 := kwargs.get('fluxMag0')):
53 fluxMag0 = 1/np.power(10, -0.4*self.coadd_zeropoint)
54
55 with warnings.catch_warnings():
56 warnings.filterwarnings('ignore', r'invalid value encountered')
57 warnings.filterwarnings('ignore', r'divide by zero')
58 return -2.5 * np.log10(df[self.column] / fluxMag0)
59
60
62
63 def __call__(self, df: pd.DataFrame, **kwargs):
64
65 with warnings.catch_warnings():
66 warnings.filterwarnings('ignore', r'invalid value encountered')
67 warnings.filterwarnings('ignore', r'divide by zero')
68 return -2.5 * np.log10((df[self.column] * 1e-9) / 3631.0)
69
70
72 ab_flux_scale = Field(doc="Scaling of ab flux", dtype=float, default=(0*units.ABmag).to_value(units.nJy))
73 coadd_zeropoint = Field(doc="Magnitude zero point", dtype=float, default=27)
74
75 def __call__(self, df, **kwargs):
76 dataNumber = super().__call__(df, **kwargs)
77 if not (fluxMag0 := kwargs.get('fluxMag0')):
78 fluxMag0 = 1/np.power(10, -0.4*self.coadd_zeropoint)
79 return self.ab_flux_scale * dataNumber / fluxMag0
80
81 def setDefaults(self):
82 super().setDefaults()
83 self.cache = True # cache this action for future calls
84
85
87 flux_mag_err = Field(doc="Error in the magnitude zeropoint", dtype=float, default=0)
88 flux_action = ConfigurableActionField(doc="Action to use if flux is not provided to the call method",
89 default=NanoJansky, dtype=DataFrameAction)
90
91 @property
92 def columns(self):
93 yield from zip((self.column,), self.flux_action.columns)
94
95 def __call__(self, df, flux_column=None, flux_mag_err=None, **kwargs):
96 if flux_column is None:
97 flux_column = self.flux_action(df, **kwargs)
98 if flux_mag_err is None:
99 flux_mag_err = self.flux_mag_err
100
101
102_docs = """This is a `DataFrameAction` that is designed to add two columns
103together and return the result.
104"""
105SumColumns = makeColumnExpressionAction("SumColumns", "colA+colB",
106 exprDefaults={"colA": SingleColumnAction,
107 "colB": SingleColumnAction},
108 docstring=_docs)
109
110_docs = """This is a `MultiColumnAction` that is designed to subtract two columns
111together and return the result.
112"""
113SubtractColumns = makeColumnExpressionAction("SubtractColumns", "colA-colB",
114 exprDefaults={"colA": SingleColumnAction,
115 "colB": SingleColumnAction},
116 docstring=_docs)
117
118_docs = """This is a `MultiColumnAction` that is designed to multiply two columns
119together and return the result.
120"""
121MultiplyColumns = makeColumnExpressionAction("MultiplyColumns", "colA*colB",
122 exprDefaults={"colA": SingleColumnAction,
123 "colB": SingleColumnAction},
124 docstring=_docs)
125
126_docs = """This is a `MultiColumnAction` that is designed to divide two columns
127together and return the result.
128"""
129DivideColumns = makeColumnExpressionAction("DivideColumns", "colA/colB",
130 exprDefaults={"colA": SingleColumnAction,
131 "colB": SingleColumnAction},
132 docstring=_docs)
133
134_docs = """This is a `MultiColumnAction` that is designed to divide two columns
135together, subtract one and return the result.
136"""
137FractionalDifferenceColumns = makeColumnExpressionAction("FractionalDifferenceColumns", "(colA-colB)/colB",
138 exprDefaults={"colA": SingleColumnAction,
139 "colB": SingleColumnAction},
140 docstring=_docs)
141
142_docs = """This is a `MultiColumnAction` that is designed to subtract the division of two columns
143from the division of two other columns and return the result (i.e. colA1/colB1 - colA2/colB2).
144"""
145DiffOfDividedColumns = makeColumnExpressionAction("DiffOfDividedColumns", "(colA1/colB1)-(colA2/colB2)",
146 exprDefaults={"colA1": SingleColumnAction,
147 "colB1": SingleColumnAction,
148 "colA2": SingleColumnAction,
149 "colB2": SingleColumnAction},
150 docstring=_docs)
151_docs = """This is a `MultiColumnAction` that is designed to compute the percent difference
152between the division of two columns and the division of two other columns and return the result
153(i.e. 100*((colA1/colB1 - colA2/colB2)/(colA1/colB1))).
154"""
155PercentDiffOfDividedColumns = makeColumnExpressionAction("PercentDiffOfDividedColumns",
156 "100*(((colA1/colB1)-(colA2/colB2))/(colA1/colB1))",
157 exprDefaults={"colA1": SingleColumnAction,
158 "colB1": SingleColumnAction,
159 "colA2": SingleColumnAction,
160 "colB2": SingleColumnAction},
161 docstring=_docs)
162
163
165 aggregator = ConfigurableActionField(doc="This is an instance of a Dataframe action that will be used "
166 "to create a new column", dtype=DataFrameAction)
167 newColumn = Field(doc="Name of the new column to add", dtype=str)
168
169 @property
170 def columns(self) -> Iterable[str]:
171 yield from self.aggregator.columns
172
173 def __call__(self, df, **kwargs) -> pd.DataFrame:
174 # do your calculation and and
175 df[self.newColumn] = self.aggregator(df, kwargs)
176 return df
Type[DataFrameAction] makeColumnExpressionAction(str className, str expr, Optional[Mapping[str, Union[DataFrameAction, Type[DataFrameAction]]]] exprDefaults=None, str docstring=None)