lsst.meas.algorithms.objectSizeStarSelector Namespace Reference

Classes
class	EventHandler
class	ObjectSizeStarSelectorConfig
class	ObjectSizeStarSelectorTask
	A star selector that looks for a cluster of small objects in a size-magnitude plot. More...

Functions
def	plot (mag, width, centers, clusterId, marker="o", markersize=2, markeredgewidth=0, ltype='-', magType="model", clear=True)

Function Documentation

plot()

def lsst.meas.algorithms.objectSizeStarSelector.plot	(		mag,
			width,
			centers,
			clusterId,
			marker = "o",
			markersize = 2,
			markeredgewidth = 0,
			ltype = '-',
			magType = "model",
			clear = True
	)

Definition at line 265 of file objectSizeStarSelector.py.

         magType="model", clear=True):

    log = Log.getLogger("objectSizeStarSelector.plot")
    try:
        import matplotlib.pyplot as plt
    except ImportError as e:
        log.warn("Unable to import matplotlib: %s", e)
        return

    try:
        fig
    except NameError:
        fig = plt.figure()
    else:
        if clear:
            fig.clf()

    axes = fig.add_axes((0.1, 0.1, 0.85, 0.80))

    xmin = sorted(mag)[int(0.05*len(mag))]
    xmax = sorted(mag)[int(0.95*len(mag))]

    axes.set_xlim(-17.5, -13)
    axes.set_xlim(xmin - 0.1*(xmax - xmin), xmax + 0.1*(xmax - xmin))
    axes.set_ylim(0, 10)

    colors = ["r", "g", "b", "c", "m", "k", ]
    for k, mean in enumerate(centers):
        if k == 0:
            axes.plot(axes.get_xlim(), (mean, mean,), "k%s" % ltype)

        li = (clusterId == k)
        axes.plot(mag[li], width[li], marker, markersize=markersize, markeredgewidth=markeredgewidth,
                  color=colors[k % len(colors)])

    li = (clusterId == -1)
    axes.plot(mag[li], width[li], marker, markersize=markersize, markeredgewidth=markeredgewidth,
              color='k')

    if clear:
        axes.set_xlabel("Instrumental %s mag" % magType)
        axes.set_ylabel(r"$\sqrt{(I_{xx} + I_{yy})/2}$")

    return fig