lsst.cp.pipe
21.0.0-4-g42917e2+78c1d8e8b8
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Public Member Functions | |
def | __init__ (self, *args, **kwargs) |
def | runDataRef (self, dataRef) |
def | run (self, filenameFull, datasetPtc, linearizer=None, log=None) |
def | covAstierMakeAllPlots (self, dataset, pdfPages, log=None) |
def | plotNormalizedCovariances (self, i, j, inputMu, covs, covsModel, covsWeights, covsNoB, covsModelNoB, covsWeightsNoB, expIdMask, pdfPages, offset=0.004, numberOfBins=10, plotData=True, topPlot=False, log=None) |
Static Public Member Functions | |
def | plotCovariances (mu, covs, covsModel, covsWeights, covsNoB, covsModelNoB, covsWeightsNoB, gainDict, noiseDict, aDict, bDict, expIdMask, pdfPages) |
def | plot_a_b (aDict, bDict, pdfPages, bRange=3) |
def | ab_vs_dist (aDict, bDict, pdfPages, bRange=4) |
def | plotAcoeffsSum (aDict, bDict, pdfPages) |
def | plotRelativeBiasACoeffs (aDict, aDictNoB, fullCovsModel, fullCovsModelNoB, signalElectrons, gainDict, pdfPages, maxr=None) |
def | findGroups (x, maxDiff) |
def | indexForBins (x, nBins) |
def | binData (x, y, binIndex, wy=None) |
Static Public Attributes | |
ConfigClass = PlotPhotonTransferCurveTaskConfig | |
A class to plot the dataset from MeasurePhotonTransferCurveTask. Parameters ---------- *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 77 of file plotPtc.py.
def lsst.cp.pipe.plotPtc.PlotPhotonTransferCurveTask.__init__ | ( | self, | |
* | args, | ||
** | kwargs | ||
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Definition at line 95 of file plotPtc.py.
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Fig. 13 of Astier+19. Values of a and b arrays fits, averaged over amplifiers, as a function of distance. Parameters ---------- aDict : `dict`, [`numpy.array`] Dictionary keyed by amp names containing the fitted 'a' coefficients from the model in Eq. 20 of Astier+19 (if `ptcFitType` is `FULLCOVARIANCE`). bDict : `dict`, [`numpy.array`] Dictionary keyed by amp names containing the fitted 'b' coefficients from the model in Eq. 20 of Astier+19 (if `ptcFitType` is `FULLCOVARIANCE`). pdfPages: `matplotlib.backends.backend_pdf.PdfPages` PDF file where the plots will be saved. bRange : `int` Maximum lag for b arrays.
Definition at line 655 of file plotPtc.py.
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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 1156 of file plotPtc.py.
def lsst.cp.pipe.plotPtc.PlotPhotonTransferCurveTask.covAstierMakeAllPlots | ( | self, | |
dataset, | |||
pdfPages, | |||
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 ---------- dataset : `lsst.ip.isr.ptcDataset.PhotonTransferCurveDataset` The dataset containing the necessary information to produce the plots. 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 155 of file plotPtc.py.
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Group data into bins, with at most maxDiff distance between bins. Parameters ---------- x: `list` Data to bin. maxDiff: `int` Maximum distance between bins. Returns ------- index: `list` Bin indices.
Definition at line 1098 of file plotPtc.py.
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Builds an index with regular binning. The result can be fed into binData. Parameters ---------- x: `numpy.array` Data to bin. nBins: `int` Number of bin. Returns ------- np.digitize(x, bins): `numpy.array` Bin indices.
Definition at line 1136 of file plotPtc.py.
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Fig. 12 of Astier+19 Color display of a and b arrays fits, averaged over channels. Parameters ---------- aDict : `dict`, [`numpy.array`] Dictionary keyed by amp names containing the fitted 'a' coefficients from the model in Eq. 20 of Astier+19 (if `ptcFitType` is `FULLCOVARIANCE`). bDict : `dict`, [`numpy.array`] Dictionary keyed by amp names containing the fitted 'b' coefficients from the model in Eq. 20 of Astier+19 (if `ptcFitType` is `FULLCOVARIANCE`). pdfPages: `matplotlib.backends.backend_pdf.PdfPages` PDF file where the plots will be saved. bRange : `int` Maximum lag for b arrays.
Definition at line 602 of file plotPtc.py.
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Fig. 14. of Astier+19 Cumulative sum of a_ij as a function of maximum separation. This plot displays the average over channels. Parameters ---------- aDict : `dict`, [`numpy.array`] Dictionary keyed by amp names containing the fitted 'a' coefficients from the model in Eq. 20 of Astier+19 (if `ptcFitType` is `FULLCOVARIANCE`). bDict : `dict`, [`numpy.array`] Dictionary keyed by amp names containing the fitted 'b' coefficients from the model in Eq. 20 of Astier+19 (if `ptcFitType` is `FULLCOVARIANCE`). pdfPages: `matplotlib.backends.backend_pdf.PdfPages` PDF file where the plots will be saved.
Definition at line 738 of file plotPtc.py.
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Plot covariances and models: Cov00, Cov10, Cov01. Figs. 6 and 7 of Astier+19 Parameters ---------- mu : `dict`, [`str`, `list`] Dictionary keyed by amp name with mean signal values. covs : `dict`, [`str`, `list`] Dictionary keyed by amp names containing a list of measued covariances per mean flux. covsModel : `dict`, [`str`, `list`] Dictionary keyed by amp names containinging covariances model (Eq. 20 of Astier+19) per mean flux. covsWeights : `dict`, [`str`, `list`] Dictionary keyed by amp names containinging sqrt. of covariances weights. covsNoB : `dict`, [`str`, `list`] Dictionary keyed by amp names containing a list of measued covariances per mean flux ('b'=0 in Astier+19). covsModelNoB : `dict`, [`str`, `list`] Dictionary keyed by amp names containing covariances model (with 'b'=0 in Eq. 20 of Astier+19) per mean flux. covsWeightsNoB : `dict`, [`str`, `list`] Dictionary keyed by amp names containing sqrt. of covariances weights ('b' = 0 in Eq. 20 of Astier+19). gainDict : `dict`, [`str`, `float`] Dictionary keyed by amp names containing the gains in e-/ADU. noiseDict : `dict`, [`str`, `float`] Dictionary keyed by amp names containing the rms redout noise in e-. aDict : `dict`, [`str`, `numpy.array`] Dictionary keyed by amp names containing 'a' coefficients (Eq. 20 of Astier+19). bDict : `dict`, [`str`, `numpy.array`] Dictionary keyed by amp names containing 'b' coefficients (Eq. 20 of Astier+19). expIdMask : `dict`, [`str`, `list`] Dictionary keyed by amp names containing the masked exposure pairs. pdfPages: `matplotlib.backends.backend_pdf.PdfPages` PDF file where the plots will be saved.
Definition at line 212 of file plotPtc.py.
def lsst.cp.pipe.plotPtc.PlotPhotonTransferCurveTask.plotNormalizedCovariances | ( | self, | |
i, | |||
j, | |||
inputMu, | |||
covs, | |||
covsModel, | |||
covsWeights, | |||
covsNoB, | |||
covsModelNoB, | |||
covsWeightsNoB, | |||
expIdMask, | |||
pdfPages, | |||
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 ---------- i : `int` Covariane lag j : `int` Covariance lag inputMu : `dict`, [`str`, `list`] Dictionary keyed by amp name with mean signal values. covs : `dict`, [`str`, `list`] Dictionary keyed by amp names containing a list of measued covariances per mean flux. covsModel : `dict`, [`str`, `list`] Dictionary keyed by amp names containinging covariances model (Eq. 20 of Astier+19) per mean flux. covsWeights : `dict`, [`str`, `list`] Dictionary keyed by amp names containinging sqrt. of covariances weights. covsNoB : `dict`, [`str`, `list`] Dictionary keyed by amp names containing a list of measued covariances per mean flux ('b'=0 in Astier+19). covsModelNoB : `dict`, [`str`, `list`] Dictionary keyed by amp names containing covariances model (with 'b'=0 in Eq. 20 of Astier+19) per mean flux. covsWeightsNoB : `dict`, [`str`, `list`] Dictionary keyed by amp names containing sqrt. of covariances weights ('b' = 0 in Eq. 20 of Astier+19). expIdMask : `dict`, [`str`, `list`] Dictionary keyed by amp names containing the masked exposure pairs. 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 446 of file plotPtc.py.
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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 ---------- aDict: `dict` Dictionary of 'a' matrices (Eq. 20, Astier+19), with amp names as keys. aDictNoB: `dict` Dictionary of 'a' matrices ('b'= 0 in Eq. 20, Astier+19), with amp names as keys. fullCovsModel : `dict`, [`str`, `list`] Dictionary keyed by amp names containing covariances model per mean flux. fullCovsModelNoB : `dict`, [`str`, `list`] Dictionary keyed by amp names containing covariances model (with 'b'=0 in Eq. 20 of Astier+19) per mean flux. 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. gainDict : `dict`, [`str`, `float`] Dicgionary keyed by amp names with the gains in e-/ADU. maxr : `int`, optional Maximum lag.
Definition at line 788 of file plotPtc.py.
def lsst.cp.pipe.plotPtc.PlotPhotonTransferCurveTask.run | ( | self, | |
filenameFull, | |||
datasetPtc, | |||
linearizer = None , |
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log = None |
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Make the plots for the PTC task
Definition at line 139 of file plotPtc.py.
def lsst.cp.pipe.plotPtc.PlotPhotonTransferCurveTask.runDataRef | ( | self, | |
dataRef | |||
) |
Run the Photon Transfer Curve (PTC) plotting measurement task. Parameters ---------- dataRef : list of lsst.daf.persistence.ButlerDataRef dataRef for the detector for the expIds to be fit.
Definition at line 111 of file plotPtc.py.
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Definition at line 92 of file plotPtc.py.