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DM-22299: Speed up specific diaCalculation plugins using fast pandas functionality #65

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merged 3 commits into from
Dec 3, 2019
Merged

DM-22299: Speed up specific diaCalculation plugins using fast pandas functionality #65

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df9582d
Add faster groupby functions.
morriscb Nov 26, 2019
c78ab39
Change to pandas skew.
morriscb Dec 2, 2019
4a127a2
Changed from agg function to direct panads function.
morriscb Dec 2, 2019
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43 changes: 10 additions & 33 deletions python/lsst/ap/association/diaCalculationPlugins.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,6 @@
import numpy as np
import pandas as pd
from scipy.optimize import lsq_linear
from scipy.stats import skew

import lsst.geom as geom
from lsst.meas.algorithms.indexerRegistry import IndexerRegistry
Expand Down Expand Up @@ -184,7 +183,7 @@ def calculate(self, diaObjects, diaSources, **kwargs):
diaObject : `dict`
Summary object to store values in and read ra/decl from.
"""
diaObjects.loc[:, "nDiaSources"] = diaSources.apply(len)
diaObjects.loc[:, "nDiaSources"] = diaSources.diaObjectId.count()


class SimpleSourceFlagDiaPluginConfig(DiaObjectCalculationPluginConfig):
Expand Down Expand Up @@ -216,13 +215,7 @@ def calculate(self, diaObjects, diaSources, **kwargs):
diaObject : `dict`
Summary object to store values in and read ra/decl from.
"""

def _flagDiaObject(df):
if np.any(df["flags"] > 0):
return 1
return 0

diaObjects.loc[:, "flags"] = diaSources.apply(_flagDiaObject)
diaObjects.loc[:, "flags"] = diaSources.flags.any()


class WeightedMeanDiaPsFluxConfig(DiaObjectCalculationPluginConfig):
Expand Down Expand Up @@ -404,12 +397,8 @@ def calculate(self,
"""
# Set "delta degrees of freedom (ddf)" to 1 to calculate the unbiased
# estimator of scatter (i.e. 'N - 1' instead of 'N').

def _sigma(df):
return np.nanstd(df["psFlux"], ddof=1)

diaObjects.loc[:, "{}PSFluxSigma".format(filterName)] = \
filterDiaSources.apply(_sigma)
filterDiaSources.psFlux.std()


class Chi2DiaPsFluxConfig(DiaObjectCalculationPluginConfig):
Expand Down Expand Up @@ -506,12 +495,9 @@ def calculate(self,
filterName : `str`
Simple, string name of the filter for the flux being calculated.
"""

def _mad(df):
return median_absolute_deviation(df["psFlux"], ignore_nan=True)

diaObjects.loc[:, "{}PSFluxMAD".format(filterName)] = \
filterDiaSources.apply(_mad)
filterDiaSources.psFlux.apply(median_absolute_deviation,
ignore_nan=True)


class SkewDiaPsFluxConfig(DiaObjectCalculationPluginConfig):
Expand Down Expand Up @@ -556,7 +542,7 @@ def calculate(self,
Simple, string name of the filter for the flux being calculated.
"""
diaObjects.loc[:, "{}PSFluxSkew".format(filterName)] = \
filterDiaSources.psFlux.apply(skew, nan_policy='omit')
filterDiaSources.psFlux.skew()


class MinMaxDiaPsFluxConfig(DiaObjectCalculationPluginConfig):
Expand Down Expand Up @@ -607,11 +593,8 @@ def calculate(self,
if maxName not in diaObjects.columns:
diaObjects[maxName] = np.nan

def _minMax(df):
return pd.Series({minName: df["psFlux"].min(),
maxName: df["psFlux"].max()})

diaObjects.loc[:, [minName, maxName]] = filterDiaSources.apply(_minMax)
diaObjects.loc[:, minName] = filterDiaSources.psFlux.min()
diaObjects.loc[:, maxName] = filterDiaSources.psFlux.max()


class MaxSlopeDiaPsFluxConfig(DiaObjectCalculationPluginConfig):
Expand Down Expand Up @@ -712,11 +695,8 @@ def calculate(self,
filterName : `str`
Simple, string name of the filter for the flux being calculated.
"""
def _meanErr(df):
return np.nanmean(df["psFluxErr"])

diaObjects.loc[:, "{}PSFluxErrMean".format(filterName)] = \
filterDiaSources.apply(_meanErr)
filterDiaSources.psFluxErr.mean()


class LinearFitDiaPsFluxConfig(DiaObjectCalculationPluginConfig):
Expand Down Expand Up @@ -1044,8 +1024,5 @@ def calculate(self,
"""
# Set "delta degrees of freedom (ddf)" to 1 to calculate the unbiased
# estimator of scatter (i.e. 'N - 1' instead of 'N').
def _sigma(df):
return np.nanstd(df["totFlux"], ddof=1)

diaObjects.loc[:, "{}TOTFluxSigma".format(filterName)] = \
filterDiaSources.apply(_sigma)
filterDiaSources.totFlux.std()
19 changes: 12 additions & 7 deletions tests/test_dia_calculation_plugins.py
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Original file line number Diff line number Diff line change
Expand Up @@ -543,7 +543,9 @@ def testCalculate(self):
"ap_skewFlux",
None)
run_multi_plugin(diaObjects, diaSources, "u", plug)
self.assertAlmostEqual(diaObjects.loc[objId, "uPSFluxSkew"], skew(fluxes))
self.assertAlmostEqual(
diaObjects.loc[objId, "uPSFluxSkew"],
skew(fluxes, bias=False, nan_policy="omit"))

# Test expected skew value with a nan set.
fluxes[4] = np.nan
Expand All @@ -555,8 +557,11 @@ def testCalculate(self):
"psFlux": fluxes,
"psFluxErr": np.ones(n_sources)})
run_multi_plugin(diaObjects, diaSources, "r", plug)
self.assertAlmostEqual(diaObjects.at[objId, "rPSFluxSkew"],
skew(fluxes, nan_policy="omit"))
# Skew returns a named tuple when called on an array
# with nan values.
self.assertAlmostEqual(
diaObjects.at[objId, "rPSFluxSkew"],
skew(fluxes, bias=False, nan_policy="omit").data)


class TestMinMaxDiaPsFlux(unittest.TestCase):
Expand Down Expand Up @@ -674,8 +679,8 @@ def testCalculate(self):
"ap_errMeanFlux",
None)
run_multi_plugin(diaObjects, diaSources, "u", plug)
self.assertEqual(diaObjects.at[objId, "uPSFluxErrMean"],
np.nanmean(errors))
self.assertAlmostEqual(diaObjects.at[objId, "uPSFluxErrMean"],
np.nanmean(errors))

# Test mean of the errors with input nan value.
errors[4] = np.nan
Expand All @@ -687,8 +692,8 @@ def testCalculate(self):
"psFlux": fluxes,
"psFluxErr": errors})
run_multi_plugin(diaObjects, diaSources, "r", plug)
self.assertEqual(diaObjects.at[objId, "rPSFluxErrMean"],
np.nanmean(errors))
self.assertAlmostEqual(diaObjects.at[objId, "rPSFluxErrMean"],
np.nanmean(errors))


class TestLinearFitDiaPsFlux(unittest.TestCase):
Expand Down