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# This file is part of ip_isr. 

# 

# Developed for the LSST Data Management System. 

# This product includes software developed by the LSST Project 

# (https://www.lsst.org). 

# See the COPYRIGHT file at the top-level directory of this distribution 

# for details of code ownership. 

# 

# This program is free software: you can redistribute it and/or modify 

# it under the terms of the GNU General Public License as published by 

# the Free Software Foundation, either version 3 of the License, or 

# (at your option) any later version. 

# 

# This program is distributed in the hope that it will be useful, 

# but WITHOUT ANY WARRANTY; without even the implied warranty of 

# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 

# GNU General Public License for more details. 

# 

# You should have received a copy of the GNU General Public License 

# along with this program. If not, see <https://www.gnu.org/licenses/>. 

 

import numpy 

 

import lsst.afw.geom as afwGeom 

import lsst.afw.image as afwImage 

import lsst.afw.math as afwMath 

import lsst.afw.display as afwDisplay 

 

from lsst.pipe.base import Task, Struct, timeMethod 

from lsst.pex.config import Config, Field, ListField, ConfigField 

 

afwDisplay.setDefaultMaskTransparency(75) 

 

 

def getFrame(): 

"""Produce a new frame number each time""" 

getFrame.frame += 1 

return getFrame.frame 

 

 

getFrame.frame = 0 

 

 

class FringeStatisticsConfig(Config): 

"""Options for measuring fringes on an exposure""" 

badMaskPlanes = ListField(dtype=str, default=["SAT"], doc="Ignore pixels with these masks") 

stat = Field(dtype=int, default=int(afwMath.MEDIAN), doc="Statistic to use") 

clip = Field(dtype=float, default=3.0, doc="Sigma clip threshold") 

iterations = Field(dtype=int, default=3, doc="Number of fitting iterations") 

rngSeedOffset = Field(dtype=int, default=0, 

doc="Offset to the random number generator seed (full seed includes exposure ID)") 

 

 

class FringeConfig(Config): 

"""Fringe subtraction options""" 

filters = ListField(dtype=str, default=[], doc="Only fringe-subtract these filters") 

num = Field(dtype=int, default=30000, doc="Number of fringe measurements") 

small = Field(dtype=int, default=3, doc="Half-size of small (fringe) measurements (pixels)") 

large = Field(dtype=int, default=30, doc="Half-size of large (background) measurements (pixels)") 

iterations = Field(dtype=int, default=20, doc="Number of fitting iterations") 

clip = Field(dtype=float, default=3.0, doc="Sigma clip threshold") 

stats = ConfigField(dtype=FringeStatisticsConfig, doc="Statistics for measuring fringes") 

pedestal = Field(dtype=bool, default=False, doc="Remove fringe pedestal?") 

 

 

class FringeTask(Task): 

"""Task to remove fringes from a science exposure 

 

We measure fringe amplitudes at random positions on the science exposure 

and at the same positions on the (potentially multiple) fringe frames 

and solve for the scales simultaneously. 

""" 

ConfigClass = FringeConfig 

 

def readFringes(self, dataRef, assembler=None): 

"""Read the fringe frame(s) 

 

The current implementation assumes only a single fringe frame and 

will have to be updated to support multi-mode fringe subtraction. 

 

This implementation could be optimised by persisting the fringe 

positions and fluxes. 

 

@param dataRef Data reference for the science exposure 

@param assembler An instance of AssembleCcdTask (for assembling fringe frames) 

@return Struct(fringes: fringe exposure or list of fringe exposures; 

seed: 32-bit uint derived from ccdExposureId for random number generator 

""" 

try: 

fringe = dataRef.get("fringe", immediate=True) 

except Exception as e: 

raise RuntimeError("Unable to retrieve fringe for %s: %s" % (dataRef.dataId, e)) 

if assembler is not None: 

fringe = assembler.assembleCcd(fringe) 

 

seed = self.config.stats.rngSeedOffset + dataRef.get("ccdExposureId", immediate=True) 

# Seed for numpy.random.RandomState must be convertable to a 32 bit unsigned integer 

seed %= 2**32 

 

return Struct(fringes=fringe, 

seed=seed) 

 

@timeMethod 

def run(self, exposure, fringes, seed=None): 

"""Remove fringes from the provided science exposure. 

 

Primary method of FringeTask. Fringes are only subtracted if the 

science exposure has a filter listed in the configuration. 

 

@param exposure Science exposure from which to remove fringes 

@param fringes Exposure or list of Exposures 

@param seed 32-bit unsigned integer for random number generator 

""" 

import lsstDebug 

display = lsstDebug.Info(__name__).display 

 

if not self.checkFilter(exposure): 

return 

 

if seed is None: 

seed = self.config.stats.rngSeedOffset 

rng = numpy.random.RandomState(seed=seed) 

 

if not hasattr(fringes, '__iter__'): 

fringes = [fringes] 

 

mask = exposure.getMaskedImage().getMask() 

for fringe in fringes: 

fringe.getMaskedImage().getMask().__ior__(mask) 

if self.config.pedestal: 

self.removePedestal(fringe) 

 

# Placeholder implementation for multiple fringe frames 

# This needs to be revisited in DM-4441 

positions = self.generatePositions(fringes[0], rng) 

fluxes = numpy.ndarray([self.config.num, len(fringes)]) 

for i, f in enumerate(fringes): 

fluxes[:, i] = self.measureExposure(f, positions, title="Fringe frame") 

 

expFringes = self.measureExposure(exposure, positions, title="Science") 

solution = self.solve(expFringes, fluxes) 

self.subtract(exposure, fringes, solution) 

if display: 

afwDisplay.Display(frame=getFrame()).mtv(exposure, title="Fringe subtracted") 

 

@timeMethod 

def runDataRef(self, exposure, dataRef, assembler=None): 

"""Remove fringes from the provided science exposure. 

 

Retrieve fringes from butler dataRef provided and remove from 

provided science exposure. 

Fringes are only subtracted if the science exposure has a filter 

listed in the configuration. 

 

@param exposure Science exposure from which to remove fringes 

@param dataRef Data reference for the science exposure 

@param assembler An instance of AssembleCcdTask (for assembling fringe frames) 

""" 

if not self.checkFilter(exposure): 

return 

fringeStruct = self.readFringes(dataRef, assembler=assembler) 

self.run(exposure, **fringeStruct.getDict()) 

 

def checkFilter(self, exposure): 

"""Check whether we should fringe-subtract the science exposure""" 

return exposure.getFilter().getName() in self.config.filters 

 

def removePedestal(self, fringe): 

"""Remove pedestal from fringe exposure""" 

stats = afwMath.StatisticsControl() 

stats.setNumSigmaClip(self.config.stats.clip) 

stats.setNumIter(self.config.stats.iterations) 

mi = fringe.getMaskedImage() 

pedestal = afwMath.makeStatistics(mi, afwMath.MEDIAN, stats).getValue() 

self.log.info("Removing fringe pedestal: %f", pedestal) 

mi -= pedestal 

 

def generatePositions(self, exposure, rng): 

"""Generate a random distribution of positions for measuring fringe amplitudes""" 

start = self.config.large 

num = self.config.num 

width = exposure.getWidth() - self.config.large 

height = exposure.getHeight() - self.config.large 

return numpy.array([rng.randint(start, width, size=num), 

rng.randint(start, height, size=num)]).swapaxes(0, 1) 

 

@timeMethod 

def measureExposure(self, exposure, positions, title="Fringe"): 

"""Measure fringe amplitudes for an exposure 

 

The fringe amplitudes are measured as the statistic within a square 

aperture. The statistic within a larger aperture are subtracted so 

as to remove the background. 

 

@param exposure Exposure to measure 

@param positions Array of (x,y) for fringe measurement 

@param title Title for display 

@return Array of fringe measurements 

""" 

stats = afwMath.StatisticsControl() 

stats.setNumSigmaClip(self.config.stats.clip) 

stats.setNumIter(self.config.stats.iterations) 

stats.setAndMask(exposure.getMaskedImage().getMask().getPlaneBitMask(self.config.stats.badMaskPlanes)) 

 

num = self.config.num 

fringes = numpy.ndarray(num) 

 

for i in range(num): 

x, y = positions[i] 

small = measure(exposure.getMaskedImage(), x, y, self.config.small, self.config.stats.stat, stats) 

large = measure(exposure.getMaskedImage(), x, y, self.config.large, self.config.stats.stat, stats) 

fringes[i] = small - large 

 

import lsstDebug 

display = lsstDebug.Info(__name__).display 

if display: 

disp = afwDisplay.Display(frame=getFrame()) 

disp.mtv(exposure, title=title) 

if False: 

with disp.Buffering(): 

for x, y in positions: 

corners = numpy.array([[-1, -1], [1, -1], [1, 1], [-1, 1], [-1, -1]]) + [[x, y]] 

disp.line(corners*self.config.small, ctype=afwDisplay.GREEN) 

disp.line(corners*self.config.large, ctype=afwDisplay.BLUE) 

 

return fringes 

 

@timeMethod 

def solve(self, science, fringes): 

"""Solve (with iterative clipping) for the scale factors 

 

@param science Array of science exposure fringe amplitudes 

@param fringes Array of arrays of fringe frame fringe amplitudes 

@return Array of scale factors for the fringe frames 

""" 

import lsstDebug 

doPlot = lsstDebug.Info(__name__).plot 

 

origNum = len(science) 

 

def emptyResult(msg=""): 

"""Generate an empty result for return to the user 

 

There are no good pixels; doesn't matter what we return. 

""" 

self.log.warn("Unable to solve for fringes: no good pixels%s", msg) 

out = [0] 

if len(fringes) > 1: 

out = out*len(fringes) 

return numpy.array(out) 

 

good = numpy.where(numpy.logical_and(numpy.isfinite(science), numpy.any(numpy.isfinite(fringes), 1))) 

science = science[good] 

fringes = fringes[good] 

oldNum = len(science) 

if oldNum == 0: 

return emptyResult() 

 

# Up-front rejection to get rid of extreme, potentially troublesome values 

# (e.g., fringe apertures that fall on objects). 

good = select(science, self.config.clip) 

for ff in range(fringes.shape[1]): 

good &= select(fringes[:, ff], self.config.clip) 

science = science[good] 

fringes = fringes[good] 

oldNum = len(science) 

if oldNum == 0: 

return emptyResult(" after initial rejection") 

 

for i in range(self.config.iterations): 

solution = self._solve(science, fringes) 

resid = science - numpy.sum(solution*fringes, 1) 

rms = stdev(resid) 

good = numpy.logical_not(abs(resid) > self.config.clip*rms) 

self.log.debug("Iteration %d: RMS=%f numGood=%d", i, rms, good.sum()) 

self.log.debug("Solution %d: %s", i, solution) 

newNum = good.sum() 

if newNum == 0: 

return emptyResult(" after %d rejection iterations" % i) 

 

if doPlot: 

import matplotlib.pyplot as plot 

for j in range(fringes.shape[1]): 

fig = plot.figure(j) 

fig.clf() 

try: 

fig.canvas._tkcanvas._root().lift() # == Tk's raise 

except Exception: 

pass 

ax = fig.add_subplot(1, 1, 1) 

adjust = science.copy() 

others = set(range(fringes.shape[1])) 

others.discard(j) 

for k in others: 

adjust -= solution[k]*fringes[:, k] 

ax.plot(fringes[:, j], adjust, 'r.') 

xmin = fringes[:, j].min() 

xmax = fringes[:, j].max() 

ymin = solution[j]*xmin 

ymax = solution[j]*xmax 

ax.plot([xmin, xmax], [ymin, ymax], 'b-') 

ax.set_title("Fringe %d: %f" % (j, solution[j])) 

ax.set_xlabel("Fringe amplitude") 

ax.set_ylabel("Science amplitude") 

ax.set_autoscale_on(False) 

ax.set_xbound(lower=xmin, upper=xmax) 

ax.set_ybound(lower=ymin, upper=ymax) 

fig.show() 

while True: 

ans = input("Enter or c to continue [chp]").lower() 

if ans in ("", "c",): 

break 

if ans in ("p",): 

import pdb 

pdb.set_trace() 

elif ans in ("h", ): 

print("h[elp] c[ontinue] p[db]") 

 

if newNum == oldNum: 

# Not gaining 

break 

oldNum = newNum 

good = numpy.where(good) 

science = science[good] 

fringes = fringes[good] 

 

# Final solution without rejection 

solution = self._solve(science, fringes) 

self.log.info("Fringe solution: %s RMS: %f Good: %d/%d", solution, rms, len(science), origNum) 

return solution 

 

def _solve(self, science, fringes): 

"""Solve for the scale factors 

 

@param science Array of science exposure fringe amplitudes 

@param fringes Array of arrays of fringe frame fringe amplitudes 

@return Array of scale factors for the fringe frames 

""" 

return afwMath.LeastSquares.fromDesignMatrix(fringes, science, 

afwMath.LeastSquares.DIRECT_SVD).getSolution() 

 

def subtract(self, science, fringes, solution): 

"""Subtract the fringes 

 

@param science Science exposure 

@param fringes List of fringe frames 

@param solution Array of scale factors for the fringe frames 

""" 

if len(solution) != len(fringes): 

raise RuntimeError("Number of fringe frames (%s) != number of scale factors (%s)" % 

(len(fringes), len(solution))) 

 

for s, f in zip(solution, fringes): 

science.getMaskedImage().scaledMinus(s, f.getMaskedImage()) 

 

 

def measure(mi, x, y, size, statistic, stats): 

"""Measure a statistic within an aperture 

 

@param mi MaskedImage to measure 

@param x, y Center for aperture 

@param size Size of aperture 

@param statistic Statistic to measure 

@param stats StatisticsControl object 

@return Value of statistic within aperture 

""" 

bbox = afwGeom.Box2I(afwGeom.Point2I(int(x) - size, int(y - size)), afwGeom.Extent2I(2*size, 2*size)) 

subImage = mi.Factory(mi, bbox, afwImage.LOCAL) 

return afwMath.makeStatistics(subImage, statistic, stats).getValue() 

 

 

def stdev(vector): 

"""Calculate a robust standard deviation of an array of values 

 

@param vector Array of values 

@return Standard deviation 

""" 

q1, q3 = numpy.percentile(vector, (25, 75)) 

return 0.74*(q3 - q1) 

 

 

def select(vector, clip): 

"""Select values within 'clip' standard deviations of the median 

 

Returns a boolean array. 

""" 

q1, q2, q3 = numpy.percentile(vector, (25, 50, 75)) 

return numpy.abs(vector - q2) < clip*0.74*(q3 - q1)