lsst.meas.astrom.display Namespace Reference

Functions
def	displayAstrometry (refCat=None, sourceCat=None, distortedCentroidKey=None, bbox=None, exposure=None, matches=None, frame=1, title="", pause=True)
def	plotAstrometry (matches, refCat=None, sourceCat=None, refMarker="x", refColor="r", sourceMarker="+", sourceColor="g", matchColor="y")

Function Documentation

displayAstrometry()

def lsst.meas.astrom.display.displayAstrometry	(		refCat = None,
			sourceCat = None,
			distortedCentroidKey = None,
			bbox = None,
			exposure = None,
			matches = None,
			frame = 1,
			title = "",
			pause = True
	)

Show an astrometry debug image.

Parameters
----------
refCat : `lsst.afw.table.SimpleCatalog`
    reference object catalog; must have fields "centroid_x" an
    "centroid_y"
sourceCat : `lsst.afw.table.SourceCatalg`
    source catalog; must have field "slot_Centroid_x" and "slot_Centroid_y"
distortedCentroidKey : `lsst.afw.table.Key`
    key for sourceCat with field to use for distorted positions
exposure : `lsst.afw.image.Exposure`
    exposure to display
bbox : `lsst.geom.Box2I`
    bounding box of exposure; Used if the exposure is `None`
matches : `list` of `lsst.afw.table.ReferenceMatch`
    List of matched objects
frame : `int`
    frame number for display
title : `str`
    title for display
pause : `bool`
    pause for inspection of display? This is done by dropping into pdb.

Notes
-----

- reference objects in refCat are shown as red X
- sources in sourceCat are shown as green +
- distorted sources in sourceCat (position given by distortedCentroidKey)
  are shown as green o
- matches are shown as a yellow circle around the source and a yellow line
  connecting the reference object and source
- if both exposure and bbox are `None`, no image is displayed

Definition at line 33 of file display.py.

                      matches=None, frame=1, title="", pause=True):
    """Show an astrometry debug image.
 
    Parameters
    ----------
    refCat : `lsst.afw.table.SimpleCatalog`
        reference object catalog; must have fields "centroid_x" an
        "centroid_y"
    sourceCat : `lsst.afw.table.SourceCatalg`
        source catalog; must have field "slot_Centroid_x" and "slot_Centroid_y"
    distortedCentroidKey : `lsst.afw.table.Key`
        key for sourceCat with field to use for distorted positions
    exposure : `lsst.afw.image.Exposure`
        exposure to display
    bbox : `lsst.geom.Box2I`
        bounding box of exposure; Used if the exposure is `None`
    matches : `list` of `lsst.afw.table.ReferenceMatch`
        List of matched objects
    frame : `int`
        frame number for display
    title : `str`
        title for display
    pause : `bool`
        pause for inspection of display? This is done by dropping into pdb.
 
    Notes
    -----
 
    - reference objects in refCat are shown as red X
    - sources in sourceCat are shown as green +
    - distorted sources in sourceCat (position given by distortedCentroidKey)
      are shown as green o
    - matches are shown as a yellow circle around the source and a yellow line
      connecting the reference object and source
    - if both exposure and bbox are `None`, no image is displayed
 
    """
    disp = afwDisplay.getDisplay(frame=frame)
 
    if exposure is not None:
        disp.mtv(exposure, title=title)
    elif bbox is not None:
        disp.mtv(exposure=ExposureF(bbox), title=title)
 
    with disp.Buffering():
        if refCat is not None:
            refCentroidKey = Point2DKey(refCat.schema["centroid"])
            for refObj in refCat:
                rx, ry = refObj.get(refCentroidKey)
                disp.dot("x", rx, ry, size=10, ctype=afwDisplay.RED)
 
        if sourceCat is not None:
            sourceCentroidKey = Point2DKey(sourceCat.schema["slot_Centroid"])
            for source in sourceCat:
                sx, sy = source.get(sourceCentroidKey)
                disp.dot("+", sx, sy, size=10, ctype=afwDisplay.GREEN)
                if distortedCentroidKey is not None:
                    dx, dy = source.get(distortedCentroidKey)
                    disp.dot("o", dx, dy, size=10, ctype=afwDisplay.GREEN)
                    disp.line([(sx, sy), (dx, dy)], ctype=afwDisplay.GREEN)
 
        if matches is not None:
            refCentroidKey = Point2DKey(matches[0].first.schema["centroid"])
            sourceCentroidKey = Point2DKey(matches[0].second.schema["slot_Centroid"])
            radArr = np.ndarray(len(matches))
 
            for i, m in enumerate(matches):
                refCentroid = m.first.get(refCentroidKey)
                sourceCentroid = m.second.get(sourceCentroidKey)
                radArr[i] = math.hypot(*(refCentroid - sourceCentroid))
                sx, sy = sourceCentroid
                disp.dot("o", sx, sy, size=10, ctype=afwDisplay.YELLOW)
                disp.line([refCentroid, sourceCentroid], ctype=afwDisplay.YELLOW)
 
            print("<match radius> = %.4g +- %.4g [%d matches]" %
                  (radArr.mean(), radArr.std(), len(matches)))
 
    if pause:
        print("Dropping into debugger to allow inspection of display. Type 'continue' when done.")
        import pdb
        pdb.set_trace()
 
 

plotAstrometry()

def lsst.meas.astrom.display.plotAstrometry	(		matches,
			refCat = None,
			sourceCat = None,
			refMarker = "x",
			refColor = "r",
			sourceMarker = "+",
			sourceColor = "g",
			matchColor = "y"
	)

Plot reference objects, sources and matches

Parameters
----------
matches : `list` of `lsst.afw.table.ReferenceMatch`
    list of matches
refCat : `lsst.afw.table.SimpleCatalog`
    reference object catalog, or None to not plot reference objects
sourceCat : `lsst.afw.table.SourceCatalog`
    source catalog, or None to not plot sources
refMarker : `str`
    pyplot marker for reference objects
refColor : `str`
    pyplot color for reference objects
sourceMarker : `str`
    pyplot marker for sources
sourceColor : `str`
    pyplot color for sources
matchColor : `str`
    color for matches; can be a constant
    or a function taking one match and returning a string

Notes
-----
By default:

- reference objects in refCat are shown as red X
- sources in sourceCat are shown as green +
- matches are shown as a yellow circle around the source and a line
  connecting the reference object to the source

Definition at line 117 of file display.py.

):
    """Plot reference objects, sources and matches
 
    Parameters
    ----------
    matches : `list` of `lsst.afw.table.ReferenceMatch`
        list of matches
    refCat : `lsst.afw.table.SimpleCatalog`
        reference object catalog, or None to not plot reference objects
    sourceCat : `lsst.afw.table.SourceCatalog`
        source catalog, or None to not plot sources
    refMarker : `str`
        pyplot marker for reference objects
    refColor : `str`
        pyplot color for reference objects
    sourceMarker : `str`
        pyplot marker for sources
    sourceColor : `str`
        pyplot color for sources
    matchColor : `str`
        color for matches; can be a constant
        or a function taking one match and returning a string
 
    Notes
    -----
    By default:
 
    - reference objects in refCat are shown as red X
    - sources in sourceCat are shown as green +
    - matches are shown as a yellow circle around the source and a line
      connecting the reference object to the source
    """
    # delay importing plt to give users a chance to set the backend before calling this function
    import matplotlib.pyplot as plt
    refSchema = matches[0][0].schema
    refCentroidKey = Point2DKey(refSchema["centroid"])
    srcSchema = matches[0][1].schema
    srcCentroidKey = Point2DKey(srcSchema["slot_Centroid"])
 
    if refCat is not None:
        refXArr, refYArr = list(zip(*[ref.get(refCentroidKey) for ref in refCat]))
        plt.plot(refXArr, refYArr, marker=refMarker, color=refColor, linestyle="")
 
    if sourceCat is not None:
        srcXArr, srcYArr = list(zip(*[src.get(srcCentroidKey) for src in sourceCat]))
        plt.plot(srcXArr, srcYArr, marker=sourceMarker, color=sourceColor, linestyle="")
 
    def makeLineSegmentData(refXYArr, srcXYArr, colorArr):
        """Make a list of line segement data
 
        This is used to draw line segements between ref and src positions in the specified color
 
        Notes
        -----
        The returned data has the format:
         [(refX0, srcX0), (refY0, srcY0), color0, (refX1, srcX1), (refY1, srcY1), color1,...]
        """
        if len(refXYArr) != len(srcXYArr):
            raise RuntimeError("len(refXYArr) = %d != %d = len(srcXYArr)" %
                               (len(refXYArr), len(srcXYArr)))
        if len(refXYArr) != len(colorArr):
            raise RuntimeError("len(refXYArr) = %d != %d = len(colorArr)" %
                               (len(refXYArr), len(colorArr)))
 
        refXArr, refYArr = list(zip(*refXYArr))
        srcXArr, srcYArr = list(zip(*srcXYArr))
        refSrcXArr = list(zip(refXArr, srcXArr))
        refSrcYArr = list(zip(refYArr, srcYArr))
        dataList = []
        for xycolor in zip(refSrcXArr, refSrcYArr, colorArr):
            for val in xycolor:
                dataList.append(val)
        return dataList
 
    refXYArr, srcXYArr = \
        list(zip(*[(match[0].get(refCentroidKey), match[1].get(srcCentroidKey)) for match in matches]))
 
    def plotSourceCircles(matches, color):
        srcXYArr = [match[1].get(srcCentroidKey) for match in matches]
        srcXArr, srcYArr = list(zip(*srcXYArr))
        plt.plot(srcXArr, srcYArr, "o", mec=color, mfc="none", ms=10,)
 
    if callable(matchColor):
        # different matches have different colors
        matchColorArr = [matchColor(match) for match in matches]
 
        # plot circles for each color separately
        matchColorSet = set(matchColorArr)
        for color in matchColorSet:
            subMatches = [match for match in matches if matchColor(match) == color]
            plotSourceCircles(subMatches, color=color)
    else:
        matchColorArr = [matchColor]*len(refXYArr)
        plotSourceCircles(matches, color=matchColor)
 
    lineSegData = makeLineSegmentData(refXYArr, srcXYArr, matchColorArr)
    plt.plot(*lineSegData)
 
    plt.show()