LSST Applications  21.0.0-147-g0e635eb1+1acddb5be5,22.0.0+052faf71bd,22.0.0+1ea9a8b2b2,22.0.0+6312710a6c,22.0.0+729191ecac,22.0.0+7589c3a021,22.0.0+9f079a9461,22.0.1-1-g7d6de66+b8044ec9de,22.0.1-1-g87000a6+536b1ee016,22.0.1-1-g8e32f31+6312710a6c,22.0.1-10-gd060f87+016f7cdc03,22.0.1-12-g9c3108e+df145f6f68,22.0.1-16-g314fa6d+c825727ab8,22.0.1-19-g93a5c75+d23f2fb6d8,22.0.1-19-gb93eaa13+aab3ef7709,22.0.1-2-g8ef0a89+b8044ec9de,22.0.1-2-g92698f7+9f079a9461,22.0.1-2-ga9b0f51+052faf71bd,22.0.1-2-gac51dbf+052faf71bd,22.0.1-2-gb66926d+6312710a6c,22.0.1-2-gcb770ba+09e3807989,22.0.1-20-g32debb5+b8044ec9de,22.0.1-23-gc2439a9a+fb0756638e,22.0.1-3-g496fd5d+09117f784f,22.0.1-3-g59f966b+1e6ba2c031,22.0.1-3-g849a1b8+f8b568069f,22.0.1-3-gaaec9c0+c5c846a8b1,22.0.1-32-g5ddfab5d3+60ce4897b0,22.0.1-4-g037fbe1+64e601228d,22.0.1-4-g8623105+b8044ec9de,22.0.1-5-g096abc9+d18c45d440,22.0.1-5-g15c806e+57f5c03693,22.0.1-7-gba73697+57f5c03693,master-g6e05de7fdc+c1283a92b8,master-g72cdda8301+729191ecac,w.2021.39
LSST Data Management Base Package
Classes | Functions
lsst.meas.algorithms.objectSizeStarSelector Namespace Reference

Classes

class  ObjectSizeStarSelectorConfig
 
class  EventHandler
 
class  ObjectSizeStarSelectorTask
 

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 269 of file objectSizeStarSelector.py.

270  magType="model", clear=True):
271 
272  log = Log.getLogger("objectSizeStarSelector.plot")
273  try:
274  import matplotlib.pyplot as plt
275  except ImportError as e:
276  log.warning("Unable to import matplotlib: %s", e)
277  return
278 
279  try:
280  fig
281  except NameError:
282  fig = plt.figure()
283  else:
284  if clear:
285  fig.clf()
286 
287  axes = fig.add_axes((0.1, 0.1, 0.85, 0.80))
288 
289  xmin = sorted(mag)[int(0.05*len(mag))]
290  xmax = sorted(mag)[int(0.95*len(mag))]
291 
292  axes.set_xlim(-17.5, -13)
293  axes.set_xlim(xmin - 0.1*(xmax - xmin), xmax + 0.1*(xmax - xmin))
294  axes.set_ylim(0, 10)
295 
296  colors = ["r", "g", "b", "c", "m", "k", ]
297  for k, mean in enumerate(centers):
298  if k == 0:
299  axes.plot(axes.get_xlim(), (mean, mean,), "k%s" % ltype)
300 
301  li = (clusterId == k)
302  axes.plot(mag[li], width[li], marker, markersize=markersize, markeredgewidth=markeredgewidth,
303  color=colors[k % len(colors)])
304 
305  li = (clusterId == -1)
306  axes.plot(mag[li], width[li], marker, markersize=markersize, markeredgewidth=markeredgewidth,
307  color='k')
308 
309  if clear:
310  axes.set_xlabel("Instrumental %s mag" % magType)
311  axes.set_ylabel(r"$\sqrt{(I_{xx} + I_{yy})/2}$")
312 
313  return fig
314 
315 
316 @pexConfig.registerConfigurable("objectSize", sourceSelectorRegistry)