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def | __init__ (self, *args, **kwargs) |
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def | runDataRef (self, dataRef) |
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def | run (self, filenameFull, datasetPtc, linearizer=None, log=None) |
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def | covAstierMakeAllPlots (self, covFits, covFitsNoB, pdfPages, log=None) |
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def | plotNormalizedCovariances (self, covFits, covFitsNoB, i, j, pdfPages, offset=0.004, numberOfBins=10, plotData=True, topPlot=False, log=None) |
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A class to plot the dataset from MeasurePhotonTransferCurveTask.
Parameters
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*args: `list`
Positional arguments passed to the Task constructor. None used at this
time.
**kwargs: `dict`
Keyword arguments passed on to the Task constructor. None used at this
time.
Definition at line 75 of file plotPtc.py.
def lsst.cp.pipe.plotPtc.PlotPhotonTransferCurveTask.binData |
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x, |
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y, |
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binIndex, |
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wy = None |
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Bin data (usually for display purposes).
Patrameters
-----------
x: `numpy.array`
Data to bin.
y: `numpy.array`
Data to bin.
binIdex: `list`
Bin number of each datum.
wy: `numpy.array`
Inverse rms of each datum to use when averaging (the actual weight is wy**2).
Returns:
-------
xbin: `numpy.array`
Binned data in x.
ybin: `numpy.array`
Binned data in y.
wybin: `numpy.array`
Binned weights in y, computed from wy's in each bin.
sybin: `numpy.array`
Uncertainty on the bin average, considering actual scatter, and ignoring weights.
Definition at line 1021 of file plotPtc.py.
def lsst.cp.pipe.plotPtc.PlotPhotonTransferCurveTask.covAstierMakeAllPlots |
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self, |
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covFits, |
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covFitsNoB, |
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pdfPages, |
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log = None |
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Make plots for MeasurePhotonTransferCurve task when doCovariancesAstier=True.
This function call other functions that mostly reproduce the plots in Astier+19.
Most of the code is ported from Pierre Astier's repository https://github.com/PierreAstier/bfptc
Parameters
----------
covFits: `dict`
Dictionary of CovFit objects, with amp names as keys.
covFitsNoB: `dict`
Dictionary of CovFit objects, with amp names as keys (b=0 in Eq. 20 of Astier+19).
pdfPages: `matplotlib.backends.backend_pdf.PdfPages`
PDF file where the plots will be saved.
log : `lsst.log.Log`, optional
Logger to handle messages
Definition at line 156 of file plotPtc.py.
def lsst.cp.pipe.plotPtc.PlotPhotonTransferCurveTask.plotNormalizedCovariances |
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self, |
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covFits, |
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covFitsNoB, |
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i, |
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j, |
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pdfPages, |
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offset = 0.004 , |
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numberOfBins = 10 , |
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plotData = True , |
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topPlot = False , |
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log = None |
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Plot C_ij/mu vs mu.
Figs. 8, 10, and 11 of Astier+19
Parameters
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covFits: `dict`
Dictionary of CovFit objects, with amp names as keys.
covFitsNoB: `dict`
Dictionary of CovFit objects, with amp names as keys (b=0 in Eq. 20 of Astier+19).
i : `int`
Covariane lag
j : `int
Covariance lag
pdfPages: `matplotlib.backends.backend_pdf.PdfPages`
PDF file where the plots will be saved.
offset : `float`, optional
Constant offset factor to plot covariances in same panel (so they don't overlap).
numberOfBins : `int`, optional
Number of bins for top and bottom plot.
plotData : `bool`, optional
Plot the data points?
topPlot : `bool`, optional
Plot the top plot with the covariances, and the bottom plot with the model residuals?
log : `lsst.log.Log`, optional
Logger to handle messages.
Definition at line 379 of file plotPtc.py.
def lsst.cp.pipe.plotPtc.PlotPhotonTransferCurveTask.plotRelativeBiasACoeffs |
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covFits, |
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covFitsNoB, |
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signalElectrons, |
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pdfPages, |
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maxr = None |
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Fig. 15 in Astier+19.
Illustrates systematic bias from estimating 'a'
coefficients from the slope of correlations as opposed to the
full model in Astier+19.
Parameters
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covFits : `dict`
Dictionary of CovFit objects, with amp names as keys.
covFitsNoB : `dict`
Dictionary of CovFit objects, with amp names as keys (b=0 in Eq. 20 of Astier+19).
signalElectrons : `float`
Signal at which to evaluate the a_ij coefficients.
pdfPages: `matplotlib.backends.backend_pdf.PdfPages`
PDF file where the plots will be saved.
maxr : `int`, optional
Maximum lag.
Definition at line 671 of file plotPtc.py.