def poly_only(epos):
f, ax = plt.subplots()
ax.set_title('Planet Classes')
helpers.set_axes(ax, epos, Trim=True)
# coordinates are from model routine
occpoly= epos.occurrence['model']['poly']
for k, (xc, yc, coords, label) in enumerate(
zip(occpoly['xc'],occpoly['yc'],occpoly['coords'],
epos.occurrence['poly']['labels'])
):
# box
ax.add_patch(matplotlib.patches.Polygon(coords,
fill=False, zorder=2, ls='-', color='k') )
size=16 if not 'textsize' in epos.plotpars else epos.plotpars['textsize']
# 12 fit in box, 16 default
ax.text(xc,yc,label, ha='center', va='center',
size=size)
helpers.save(plt, epos.plotdir+'occurrence/poly_only')
def integrated(epos, MCMC=False, Planets=False):
f, (ax, axb) = plt.subplots(1,2, gridspec_kw = {'width_ratios':[20, 1]})
f.subplots_adjust(wspace=0)
sy= 'M' if (epos.MassRadius or epos.RV) else 'R'
ax.set_title('Occurrence'+ (' (dln'+sy+' dlnP)' if MCMC else ' (Initial Guess)'))
helpers.set_axes(ax, epos, Trim=True, In=epos.MassRadius)
''' color scale? '''
cmap='jet' # cool, spring
vmin, vmax= -5, 0
ticks=np.linspace(vmin, vmax, (vmax-vmin)+1)
levels=np.linspace(vmin, vmax, 256)
''' 2D pdf '''
pps, pdf, _, _= periodradius(epos, Init=not MCMC)
pdflog= np.log10(pdf) # in %
cs= ax.contourf(epos.X_in, epos.Y_in, pdflog, cmap=cmap, levels=levels)
cbar= f.colorbar(cs, cax=axb, ticks=ticks)
axb.set_yticklabels(100*10.**ticks)
axb.tick_params(axis='y', direction='out')
axb.set_title('%')
''' integrated occurrence per bin'''
occbin= epos.occurrence['bin']
key = 'eta' if MCMC else 'eta0'
for k, (xbin, ybin, n, inbin, occ) in enumerate(
zip(occbin['x'],occbin['y in'],occbin['n'],occbin['i'], occbin[key])
):
clr= clrs[k%4]
# colored dots
#ax.plot(epos.obs_xvar[inbin], epos.obs_yvar[inbin],
# ls='', marker='.', mew=0, ms=5.0, color=clr, zorder=1)
# box
ax.add_patch(patches.Rectangle( (xbin[0],ybin[0]),
xbin[1]-xbin[0], ybin[1]-ybin[0],
fill=False, zorder=2, ls='-', color='k') )
xnudge=1.01
ynudge=1.02
size=16 if not 'textsize' in epos.plotpars else epos.plotpars['textsize']
# 12 fit in box, 16 default
ax.text(xbin[0]*xnudge,ybin[1]/ynudge,'{:.1%}'.format(occ), va='top',size=size)
if MCMC:
ax.text(xbin[0]*xnudge,ybin[1]/ynudge,'\n +{:.1%}\n -{:.1%}'.format(
occbin['eta+'][k],occbin['eta-'][k]
), va='top',size=size)
''' overplot planets '''
if Planets:
ax.plot(epos.obs_xvar, epos.obs_yvar,
ls='', marker='.', mew=0, ms=5, alpha=1, color='k')
fname= 'posterior' if MCMC else 'integrated'
if Planets: fname+= '.planets'
helpers.save(plt, epos.plotdir+'occurrence/'+fname)
def twoD(epos, PlotZoom=False, MCMC=False):
# where does this go -> run.py
assert epos.Parametric
if not epos.Range: epos.set_ranges()
# pdf
pps, pdf, _, _ = periodradius(epos, Init=not MCMC)
pdflog = np.log10(pdf) # in %
f, (ax, axb) = plt.subplots(1, 2, gridspec_kw={'width_ratios': [20, 1]})
f.subplots_adjust(wspace=0)
ax.set_title('Occurrence [%] / d ln p d ln ' +
('M' if epos.MassRadius else 'R'))
helpers.set_axes(ax, epos, Trim=True, In=epos.MassRadius)
''' color scale? '''
cmap = 'jet'
vmin, vmax = -5, 0
ticks = np.linspace(vmin, vmax, (vmax - vmin) + 1)
levels = np.linspace(vmin, vmax)
ax.contourf(epos.X_in, epos.Y_in, pdflog, cmap=cmap, levels=levels)
# colorbar?
norm = Normalize(vmin=vmin, vmax=vmax)
cb1 = clrbar.ColorbarBase(axb,
cmap=cmap,
norm=norm,
ticks=ticks,
orientation='vertical') # horizontal
axb.set_yticklabels(100 * 10.**ticks)
axb.tick_params(axis='y', direction='out')
fname = 'mcmc/posterior' if MCMC else 'input/parametric_initial'
helpers.save(plt, epos.plotdir + fname)
def vetting(epos, PlotBox=False):
assert hasattr(epos, 'vetting')
f, (ax, axb) = plt.subplots(1, 2, gridspec_kw={'width_ratios': [20, 1]})
f.subplots_adjust(wspace=0)
#f.set_size_inches(7, 5)
ax.set_title('Vetting Efficiency')
helpers.set_axes(ax, epos, Trim=False, Eff=True)
''' color map and ticks'''
cmap = 'plasma'
levels = np.linspace(0, 1, 256)
ticks = np.array([0.0, 0.25, 0.5, 0.75, 1.0])
ticks_percent = ['0', '25', '50', '75', '100']
cs = ax.contourf(epos.eff_xvar,
epos.eff_yvar,
epos.vetting.T,
cmap=cmap,
levels=levels)
cbar = f.colorbar(cs, cax=axb, ticks=ticks)
axb.set_yticklabels(ticks_percent)
axb.tick_params(axis='y', direction='out')
axb.set_title('%')
''' Plot the zoom box or a few black contours'''
if PlotBox:
fname = '.box'
assert epos.Range
ax.add_patch(
patches.Rectangle((epos.xtrim[0], epos.ytrim[0]),
epos.xtrim[1] - epos.xtrim[0],
epos.ytrim[1] - epos.ytrim[0],
fill=False,
zorder=1,
ls='--'))
if epos.Zoom:
ax.add_patch(
patches.Rectangle((epos.xzoom[0], epos.yzoom[0]),
epos.xzoom[1] - epos.xzoom[0],
epos.yzoom[1] - epos.yzoom[0],
fill=False,
zorder=1))
else:
cs = ax.contour(epos.eff_xvar,
epos.eff_yvar,
epos.vetting.T,
colors='k',
levels=ticks)
fmt_percent = lambda x: '{:g} %'.format(100. * x)
plt.clabel(cs, cs.levels, inline=True, fmt=fmt_percent)
fname = ''
if hasattr(epos, 'xtrim'):
ax.set_xlim(*epos.xtrim)
ax.set_ylim(*epos.ytrim)
helpers.save(plt, epos.plotdir + 'survey/vetting' + fname)
def periodradius(epos, SNR=True, Parametric=False):
f, (ax, axR, axP)= helpers.make_panels(plt)
sim=epos.synthetic_survey
title='Simulated Detections'
fsuffix='detect'
if SNR:
transit=epos.transit
title= 'Simulated Transiting Planets'
fsuffix='transit'
''' plot R(P), main panel'''
ax.set_title(title)
helpers.set_axes(ax, epos, Trim=True)
if SNR: ax.plot(transit['P'], transit['Y'], ls='', marker='.', color='C6')
ax.plot(sim['P'], sim['Y'], ls='', marker='.', color='C0')
''' Period side panel '''
#helpers.set_axis_distance(axP, epos, Trim=True)
axP.set_xlabel(ax.get_xlabel())
#axP.set_yscale('log')
#axP.set_ylim([2e-3,5])
#axP.set_yticks([0.01,0.1,1])
#axP.set_yticklabels(['1%','10%','100%'])
axP.yaxis.tick_right()
axP.yaxis.set_ticks_position('both')
#axP.tick_params(axis='y', which='minor',left='off',right='off')
if SNR: axP.hist(transit['P'], bins=epos.MC_xvar, color='C6')
axP.hist(sim['P'], bins=epos.MC_xvar)
''' Radius side panel'''
#helpers.set_axis_size(axR, epos, Trim=True, In= epos.MassRadius)
axR.set_ylabel(ax.get_ylabel())
#axR.set_xscale('log')
#axR.set_xlim([2e-3,5])
#axR.set_xticks([1,10,100,1000])
#axR.set_xticklabels(['1','10','100','1000'], rotation=70)
for tick in axR.get_xticklabels():
tick.set_rotation(70)
#axR.tick_params(axis='x', which='minor',top='off',bottom='off')
#axP.tick_params(axis='y', which='minor',left='off',right='off')
if SNR: axR.hist(transit['Y'],orientation='horizontal', bins=epos.MC_yvar, color='C6')
axR.hist(sim['Y'],orientation='horizontal', bins=epos.MC_yvar)
# labels
if SNR:
xpos= epos.MC_xvar[-1]
ypos= axP.get_ylim()[-1]/1.05
axP.text(xpos, ypos, 'Detected ', color='C0', ha='right', va='top')
axP.text(xpos, ypos/1.3, 'Undetected ', color='C6', ha='right', va='top')
#ax.legend(loc='lower left', shadow=False, prop={'size':14}, numpoints=1)
helpers.save(plt, '{}output/periodradius.{}'.format(epos.plotdir,fsuffix))
def model(epos):
f, ax = plt.subplots()
name = 'Model Occurrence Rate, $\eta={:.2g}$'.format(
epos.occurrence['model']['eta'])
ax.set_title(name)
helpers.set_axes(ax, epos, Trim=True)
ax.plot(epos.pfm['P'],
epos.pfm['R'],
ls='',
marker='o',
mew=0,
ms=4,
color='C0',
zorder=0)
''' bins'''
occbin = epos.occurrence['model']['bin']
for k, (xbin, ybin, n, inbin, occ) in enumerate(
zip(occbin['x'], occbin['y'], occbin['n'], occbin['i'],
occbin['occ'])):
# box
ax.add_patch(
patches.Rectangle((xbin[0], ybin[0]),
xbin[1] - xbin[0],
ybin[1] - ybin[0],
fill=False,
zorder=2,
ls='-',
color='k'))
xnudge = 1.01
ynudge = 1.02
size = 16 if not 'textsize' in epos.plotpars else epos.plotpars[
'textsize']
# 12 fit in box, 16 default
ax.text(xbin[0] * xnudge,
ybin[1] / ynudge,
'{:.1%}'.format(occ),
va='top',
size=size)
ax.text(xbin[0] * xnudge,
ybin[1] / ynudge,
'\n$\pm${:.1f}'.format(occbin['err'][k] * 100),
va='top',
size=size)
ax.text(xbin[1] / xnudge,
ybin[0] * ynudge,
'n={}'.format(n),
ha='right',
size=size)
helpers.save(plt, epos.plotdir + 'occurrence/model')
def panels(epos, PlotZoom=False, MCMC=False):
''' Initial distribution, panel layout'''
f, (ax, axb, axR, axP) = helpers.make_panels_clrbar(plt)
# pdf
pps, pdf, pdf_X, pdf_Y = periodradius(epos, Init=not MCMC)
pdflog = np.log10(pdf) # in %
ax.set_title('Planet Occurrence / dlnP dln' +
('M' if epos.MassRadius else 'R'))
helpers.set_axes(ax, epos, Trim=True, In=epos.MassRadius)
# Side panels
axP.plot(epos.MC_xvar, pdf_X, marker='', ls='-', color='k')
axR.plot(pdf_Y, epos.in_yvar, marker='', ls='-', color='k')
#helpers.set_axis_distance(axP, epos, Trim=True)
#helpers.set_axis_size(axR, epos, Trim=True, In= epos.MassRadius)
axP.set_xlabel(ax.get_xlabel())
axR.set_ylabel(ax.get_ylabel())
axP.set_yscale('log')
axP.set_ylim([2e-3, 5])
axP.set_yticks([0.01, 0.1, 1])
axP.set_yticklabels(['1%', '10%', '100%'])
axP.yaxis.tick_right()
axP.yaxis.set_ticks_position('both')
axP.tick_params(axis='y', which='minor', left=False, right=False)
axR.set_xscale('log')
axR.set_xlim([2e-3, 5])
axR.set_xticks([0.01, 0.1, 1])
axR.set_xticklabels(['1%', '10%', '100%'], rotation=70)
axR.tick_params(axis='x', which='minor', top=False, bottom=False)
axP.tick_params(axis='y', which='minor', left=False, right=False)
axP.tick_params(axis='y', which='major', left=False, right=True)
''' color scale? '''
cmap = 'jet'
vmin, vmax = -5, 0
ticks = np.linspace(vmin, vmax, (vmax - vmin) + 1)
levels = np.linspace(vmin, vmax)
ax.contourf(epos.X_in, epos.Y_in, pdflog, cmap=cmap, levels=levels)
# colorbar?
norm = Normalize(vmin=vmin, vmax=vmax)
cb1 = clrbar.ColorbarBase(axb,
cmap=cmap,
norm=norm,
ticks=ticks,
orientation='vertical') # horizontal
axb.set_yticklabels(100 * 10.**ticks)
axb.tick_params(axis='y', direction='out')
axb.set_title('%')
helpers.save(plt, epos.plotdir + 'input/panels')
def observed(epos, PlotBox=True):
assert epos.Observation
f, ax = plt.subplots()
ax.set_title('Observed Population')
helpers.set_axes(ax, epos, Trim=epos.Range)
ax.plot(epos.obs_xvar,
epos.obs_yvar,
ls='',
marker='.',
mew=0,
ms=5.0,
color='k')
# add multis?
if PlotBox:
fname = '.box'
assert epos.Range
ax.add_patch(
patches.Rectangle((epos.xtrim[0], epos.ytrim[0]),
epos.xtrim[1] - epos.xtrim[0],
epos.ytrim[1] - epos.ytrim[0],
fill=False,
zorder=1,
ls='--'))
if epos.Zoom:
ax.add_patch(
patches.Rectangle((epos.xzoom[0], epos.yzoom[0]),
epos.xzoom[1] - epos.xzoom[0],
epos.yzoom[1] - epos.yzoom[0],
fill=False,
zorder=1))
else:
fname = ''
helpers.save(plt, epos.plotdir + 'survey/planets' + fname)
def observed(epos, PlotBox=True, PlotScore=False):
assert epos.Observation
if PlotScore:
f, (ax, axb) = plt.subplots(1,
2,
gridspec_kw={'width_ratios': [20, 1]})
f.subplots_adjust(wspace=0)
else:
f, ax = plt.subplots()
ax.set_title('Observed Population')
helpers.set_axes(ax, epos, Trim=epos.Range)
if PlotScore:
''' color scale? '''
cmap = 'plasma' # viridis, plasma, inferno, magma, spring, cool
vmin, vmax = 0, 1
#ticks=np.linspace(vmin, vmax, (vmax-vmin)+1)
clrs, norm = helpers.color_array(epos.obs_score,
vmin=vmin,
vmax=vmax,
cmap=cmap)
ax.scatter(epos.obs_xvar, epos.obs_yvar, color=clrs, s=3)
# colorbar?
cb1 = clrbar.ColorbarBase(axb,
cmap=cmap,
norm=norm,
orientation='vertical') # horizontal
axb.tick_params(axis='y', direction='out')
fname = '.score'
else:
ax.plot(epos.obs_xvar,
epos.obs_yvar,
ls='',
marker='.',
mew=0,
ms=5.0,
color='k')
fname = ''
# add multis?
if PlotBox:
fname = '.box'
assert epos.Range
ax.add_patch(
patches.Rectangle((epos.xtrim[0], epos.ytrim[0]),
epos.xtrim[1] - epos.xtrim[0],
epos.ytrim[1] - epos.ytrim[0],
fill=False,
zorder=1,
ls='--'))
if epos.Zoom:
ax.add_patch(
patches.Rectangle((epos.xzoom[0], epos.yzoom[0]),
epos.xzoom[1] - epos.xzoom[0],
epos.yzoom[1] - epos.yzoom[0],
fill=False,
zorder=1))
helpers.save(plt, epos.plotdir + 'survey/planets' + fname)
def completeness(epos, PlotBox=False, Transit=False, Vetting=True):
assert epos.DetectionEfficiency
f, (ax, axb) = plt.subplots(1, 2, gridspec_kw={'width_ratios': [20, 1]})
f.subplots_adjust(wspace=0)
#f.set_size_inches(7, 5)
ax.set_title('Detection Efficiency' if Transit else 'Survey Completeness')
helpers.set_axes(ax, epos, Trim=False, Eff=True)
if Transit:
toplot = epos.eff_2D
if Vetting and hasattr(epos, 'vetting'): toplot *= epos.vetting
else:
toplot = epos.completeness if Vetting else epos.completeness_novet
with np.errstate(divide='ignore'):
log_completeness = np.log10(toplot)
''' color map and ticks'''
cmap = 'YlOrBr' if Transit else 'PuRd'
#cmap = 'rainbow' if Transit else 'PuRd'
vmin, vmax = -4, 0
if Transit: vmin = -3
ticks = np.linspace(vmin, vmax, (vmax - vmin) + 1)
levels = np.linspace(vmin, vmax, 256)
cs = ax.contourf(epos.eff_xvar,
epos.eff_yvar,
log_completeness.T,
cmap=cmap,
levels=levels,
vmin=vmin,
vmax=vmax)
cbar = f.colorbar(cs, cax=axb, ticks=ticks)
axb.set_yticklabels(100 * 10.**ticks)
axb.tick_params(axis='y', direction='out')
axb.set_title('%')
''' Plot the zoom box or a few black contours'''
if PlotBox:
fname = '.box'
assert epos.Range
ax.add_patch(
patches.Rectangle((epos.xtrim[0], epos.ytrim[0]),
epos.xtrim[1] - epos.xtrim[0],
epos.ytrim[1] - epos.ytrim[0],
fill=False,
zorder=1,
ls='--'))
if epos.Zoom:
ax.add_patch(
patches.Rectangle((epos.xzoom[0], epos.yzoom[0]),
epos.xzoom[1] - epos.xzoom[0],
epos.yzoom[1] - epos.yzoom[0],
fill=False,
zorder=1))
else:
if hasattr(epos, 'xtrim'):
ax.set_xlim(*epos.xtrim)
ax.set_ylim(*epos.ytrim)
if epos.RV:
levels = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
labels = ['10', '20', '30', '40', '50', '60', '70', '80', '90']
cs= ax.contour(epos.eff_xvar, epos.eff_yvar, toplot.T,\
levels= levels, colors = 'k', linewidths=2.)
else:
levels = [1e-3, 0.01, 0.1, 0.5, 0.9] if Transit else 10.**ticks
cs = ax.contour(epos.eff_xvar,
epos.eff_yvar,
toplot.T,
colors='k',
levels=levels)
fmt_percent = lambda x: '{:g} %'.format(100. * x)
plt.clabel(cs, cs.levels, inline=True, fmt=fmt_percent)
fname = ''
if not Vetting: fname += '.novet'
helpers.save(plt, epos.plotdir+'survey/'+('efficiency' if Transit else 'completeness')+ \
fname)
def panels(epos, MCMC=False):
f, (ax, axR, axP)= helpers.make_panels(plt)
sim=epos.synthetic_survey
clr_bf= 'g'
''' plot R(P), main panel'''
ax.set_title('Simulated Detections')
helpers.set_axes(ax, epos, Trim=True)
if epos.MonteCarlo:
ax.plot(sim['P'], sim['Y'], ls='', marker='.', color=clr_bf if MCMC else 'C0')
else:
levels= np.linspace(0,np.max(sim['pdf']))
ax.contourf(epos.MC_xvar, epos.MC_yvar, sim['pdf'].T, cmap='Blues', levels=levels)
''' Period side panel '''
helpers.set_axis_distance(axP, epos, Trim=True)
#axP.set_yscale('log')
#axP.set_ylim([2e-3,5])
#axP.set_yticks([0.01,0.1,1])
#axP.set_yticklabels(['1%','10%','100%'])
axP.yaxis.tick_right()
axP.yaxis.set_ticks_position('both')
#axP.tick_params(axis='y', which='minor',left='off',right='off')
''' Radius side panel'''
helpers.set_axis_size(axR, epos, Trim=True) #, In= epos.MassRadius)
#axR.set_xscale('log')
#axR.set_xlim([2e-3,5])
#axR.set_xticks([1,10,100,1000])
#axR.set_xticklabels(['1','10','100','1000'], rotation=70)
for tick in axR.get_xticklabels():
tick.set_rotation(70)
#axR.tick_params(axis='x', which='minor',top='off',bottom='off')
#axP.tick_params(axis='y', which='minor',left='off',right='off')
''' Histograms / posterior samples '''
try:
xbins= np.geomspace(*epos.xzoom, num=20)
ybins= np.geomspace(*epos.yzoom, num=10)
except:
xbins= np.logspace(*np.log10(epos.xzoom), num=20)
ybins= np.logspace(*np.log10(epos.yzoom), num=10)
xscale= np.log(xbins[1]/xbins[0])
yscale= np.log(ybins[1]/ybins[0])
if MCMC:
histkeys= {'color':'b', 'alpha':0.1}
for ss in epos.ss_sample:
if epos.MonteCarlo:
axP.hist(ss['P zoom'], bins=xbins, histtype='step', **histkeys)
axR.hist(ss['Y zoom'], bins=ybins, orientation='horizontal', \
histtype='step', **histkeys)
else:
axP.plot(ss['P zoom'], ss['P zoom pdf']*xscale,
marker='', ls='-', **histkeys)
axR.plot(ss['Y zoom pdf']*yscale, ss['Y zoom'],
marker='', ls='-', **histkeys)
histdict= {'histtype':'step', 'color':clr_bf}
else:
histdict={}
if epos.MonteCarlo:
axP.hist(sim['P zoom'], bins=xbins, **histdict)
axR.hist(sim['Y zoom'], bins=ybins, orientation='horizontal', **histdict)
else:
axP.plot(sim['P zoom'], sim['P zoom pdf']*xscale, marker='', ls='-')
axR.plot(sim['Y zoom pdf']*yscale, sim['Y zoom'], marker='', ls='-')
''' Observations'''
axP.hist(epos.obs_zoom['x'], bins=xbins,histtype='step', color='C1')
axR.hist(epos.obs_zoom['y'], bins=ybins, orientation='horizontal',histtype='step', color='C1')
''' Box/ lines'''
if epos.Zoom:
for zoom in epos.xzoom: axP.axvline(zoom, ls='--', color='k')
for zoom in epos.yzoom: axR.axhline(zoom, ls='--', color='k')
ax.add_patch(patches.Rectangle( (epos.xzoom[0],epos.yzoom[0]),
epos.xzoom[1]-epos.xzoom[0], epos.yzoom[1]-epos.yzoom[0],fill=False, zorder=1) )
#ax.legend(loc='lower left', shadow=False, prop={'size':14}, numpoints=1)
fdir= 'mcmc' if MCMC else 'output'
helpers.save(plt, '{}{}/pdf.zoom'.format(epos.plotdir, fdir))
def cdf(epos):
f, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)
f.set_size_inches(9, 7) # default 7, 5
'''
top left: synthetic obsservation
'''
sim= epos.synthetic_survey
helpers.set_axes(ax1, epos, Trim=True)
ax1.set_title('Synthetic ({})'.format(sim['nobs']))
if epos.MonteCarlo:
ax1.plot(sim['P'], sim['Y'], ls='', marker='.', mew=0, ms=5.0, color='r', alpha=0.5)
else:
levels= np.linspace(0,np.max(sim['pdf']))
ax1.contourf(epos.MC_xvar, epos.MC_yvar, sim['pdf'].T, cmap='Reds', levels=levels)
if epos.Zoom:
ax1.add_patch(patches.Rectangle( (epos.xzoom[0],epos.yzoom[0]),
epos.xzoom[1]-epos.xzoom[0], epos.yzoom[1]-epos.yzoom[0],fill=False, zorder=1) )
'''
Top right: observed population
'''
ax2.set_title('Observed ({})'.format(epos.obs_zoom['x'].size))
helpers.set_axes(ax2, epos, Trim=True)
ax2.plot(epos.obs_xvar, epos.obs_yvar, ls='', marker='.', mew=0, ms=5.0, color='b')
if epos.Zoom:
ax2.add_patch(patches.Rectangle( (epos.xzoom[0],epos.yzoom[0]),
epos.xzoom[1]-epos.xzoom[0], epos.yzoom[1]-epos.yzoom[0],fill=False, zorder=1) )
'''
cdf orbital period
'''
if 'xvar' in epos.prob:
ax3.set_title('Period, p={:.3g}'.format(epos.prob['xvar']))
else:
ax3.set_title('Orbital Period')
ax3.set_xlabel('Orbital Period [days]')
ax3.set_ylabel('CDF')
ax3.set_xscale('log')
ax3.set_ylim([-0.05,1.05])
ax3.set_xlim(*epos.xzoom)
if epos.MonteCarlo:
#model histogram x
P= sim['P zoom']
ax3.plot(np.sort(P), np.arange(P.size, dtype=float)/P.size, ls='-', marker='', color='r')
else:
ax3.plot(sim['P zoom'], sim['P zoom cdf'], ls='-', marker='', color='r')
#obs histogram x
P= epos.obs_zoom['x']
ax3.plot(np.sort(P), np.arange(P.size, dtype=float)/P.size, ls='-', marker='', color='b')
'''
CDF planet radius
'''
if 'yvar' in epos.prob:
ax4.set_title('{}, p={:.3g}'.format('M sin i' if epos.RV else 'Radius', epos.prob['yvar']))
else:
ax4.set_title('{}'.format('M sin i' if epos.RV else 'Radius'))
if epos.RV: ax4.set_xlabel(r'Planet M sin i [M$_\bigoplus$]')
else: ax4.set_xlabel(r'Planet Radius [R$_\bigoplus$]')
ax4.set_ylabel('CDF')
ax4.set_xscale('log')
ax4.set_ylim([-0.05,1.05])
ax4.set_xlim(*epos.yzoom)
ax4.set_xticks(epos.yticks)
ax4.get_xaxis().set_major_formatter(tck.ScalarFormatter())
if epos.MonteCarlo:
#model histogram x
R= sim['Y zoom']
ax4.plot(np.sort(R), np.arange(R.size, dtype=float)/R.size, ls='-', marker='', color='r')
else:
ax4.plot(sim['Y zoom'], sim['Y zoom cdf'], ls='-', marker='', color='r')
#obs histogram x
R= epos.obs_zoom['y']
ax4.plot(np.sort(R), np.arange(R.size, dtype=float)/R.size, ls='-', marker='', color='b')
f.tight_layout()
helpers.save(plt, epos.plotdir+'output/cdf.diag')
def periodradius(epos, color='C4', alpha=1):
gs = gridspec.GridSpec(nrows=9, ncols=3)
f = plt.figure()
f.set_size_inches(13, 7) # default 7, 5
f.subplots_adjust(wspace=0.5, hspace=0.0)
ax1 = f.add_subplot(gs[3:6, 0])
ax2 = f.add_subplot(gs[0:3, 1], sharex=ax1, sharey=ax1)
ax3 = f.add_subplot(gs[6:9, 1], sharex=ax1, sharey=ax1)
ax4 = f.add_subplot(gs[3:6, 2], sharex=ax1, sharey=ax1)
if True:
#f.suptitle(epos.name)
f.suptitle(
"Compare Planet Formation Models to Observed Exoplanets with epos",
bbox=dict(boxstyle='round', fc='w', ec='k'))
else:
words = [
'Compare', 'Planet Formation Models', 'to', 'Observed Exoplanets',
'with', 'epos'
]
colors = ['C0', color, '0.5', 'C3', '0.5', 'C2']
helpers.rainbow_text(0.1, 0.95, words, colors, size=20, f=f, fudge=1.5)
#helpers.rainbow_text(0.05, 1.1, words, colors, size=18, ax=axes[0,0])
''' Left: model '''
ax = ax1
helpers.set_axes(ax, epos, Trim=True)
ax.set_xlabel('')
ax.set_title('Formation Model: {}'.format(epos.name))
pfm = epos.pfm
ax.plot(pfm['P'],
pfm['R'],
ls='',
marker='.',
ms=5.0,
color=color,
alpha=alpha)
''' Top middle: synthetic obs'''
ax = ax2
ax.set_title('Simulated Observations')
if epos.MonteCarlo:
sim = epos.synthetic_survey
ax.plot(sim['P'],
sim['Y'],
ls='',
marker='.',
mew=0,
ms=5.0,
color='C2',
alpha=0.5)
else:
levels = np.linspace(0, np.max(sim['pdf']))
ax.contourf(epos.MC_xvar,
epos.MC_yvar,
sim['pdf'].T,
cmap='Greens',
levels=levels)
''' Bottom middle: occurrnce rates'''
ax = ax3
ax.set_title('Occurrence Rates')
ax.set_xlabel('Orbital Period [days]')
occbin = epos.occurrence['bin']
maxocc = np.max(occbin['occ'])
for k, (xbin, ybin, n, inbin, occ) in enumerate(
zip(occbin['x'], occbin['y'], occbin['n'], occbin['i'],
occbin['occ'])):
# box
ax.add_patch(
patches.Rectangle((xbin[0], ybin[0]),
xbin[1] - xbin[0],
ybin[1] - ybin[0],
fill=True,
ls='-',
fc=cm.Greens(occ / maxocc)))
#xnudge=1.01
#ynudge=1.02
#ax.text(xbin[0]*xnudge,ybin[1]/ynudge,'{:.1%}'.format(occ), va='top',
# size=8)
# colored dots
#ax.plot(epos.obs_xvar, epos.obs_yvar,
# ls='', marker='.', mew=0, ms=2.0, color='k')
''' right: observations '''
ax = ax4
ax.set_title('Observed Planets')
ax.plot(epos.obs_xvar,
epos.obs_yvar,
ls='',
marker='.',
mew=0,
ms=5.0,
color='C3')
'''
Draw horizontal bars
'''
xl = 0.07
xw, dy = 0.85, 0.08
yb, yt = 0.22, 0.75
props = dict(transform=f.transFigure, alpha=0.3, zorder=-10)
bar_fw = patches.Rectangle((xl, yt - dy), xw, 2 * dy, color='C1', **props)
bar_occ = patches.Rectangle((xl, yb - dy), xw, 2 * dy, color='C6', **props)
bbox = dict(boxstyle='round', fc='w', ec='k')
props = dict(rotation=0,
ha='left',
va='center',
transform=f.transFigure,
bbox=bbox)
f.patches.extend([bar_fw, bar_occ])
f.text(xl - 0.03, yt, 'Forward Model', color='k', **props)
f.text(xl - 0.03, yb, 'Inverse Model', color='k', **props)
''' Draw arrows between plots'''
props = dict(transform=f.transFigure,
arrowstyle='simple',
connectionstyle='arc3,rad=-0.3',
alpha=0.3,
fc='g',
mutation_scale=50.)
xl, xr = 0.3, 0.62
yt, yb = 0.7, 0.2
xw, yw = 0.1, 0.1
arrow1 = patches.FancyArrowPatch((xl, yt), (xl + xw, yt + yw), **props)
arrow2 = patches.FancyArrowPatch((xr + xw, yb + yw), (xr, yb), **props)
f.text(xl - 0.05,
yt + 0.06,
'Apply Survey\nDetection Bias',
color='g',
ha='center',
va='center',
transform=f.transFigure)
f.text(xr + xw + 0.07,
yb,
'Account for\nSurvey Completeness',
color='g',
ha='center',
va='center',
transform=f.transFigure)
# and top-bottom
props['connectionstyle'] = 'arc3,rad=0.0'
props['mutation_scale'] = 30.
props['fc'] = 'b'
#props['shape']= 'full'
#props['arrowstyle']='darrow'
xl, xr = 0.33, 0.63
yt, yb = 0.7, 0.25
xw, yw = 0.005, 0.01
dy = 0.04
xs, ys = 0.05, 0.03
arrow3 = patches.FancyArrowPatch((xl - xw, yb + dy),
(xl - xw + xs, yb - dy), **props)
arrow4 = patches.FancyArrowPatch((xl + xw + xs, yb - dy + ys),
(xl + xw, yb + dy + ys), **props)
#for x,y in zip([xl-0.04, xr+xs+0.04],[yb-dy,yt+dy]):
# f.text(x,y,'Compare',color='b',
# ha='center', va='center', transform=f.transFigure)
f.text(xr + xs + 0.1,
yt + dy,
'Compare Distribution\nof Detections',
color='b',
ha='center',
va='center',
transform=f.transFigure)
f.text(xl - 0.07,
yb - dy,
'Compare Intrinsic\n Planet Population',
color='b',
ha='center',
va='center',
transform=f.transFigure)
arrow5 = patches.FancyArrowPatch((xr - xw, yt + dy),
(xr - xw + xs, yt - dy), **props)
arrow6 = patches.FancyArrowPatch((xr + xw + xs, yt - dy + ys),
(xr + xw, yt + dy + ys), **props)
f.patches.extend([arrow1, arrow2, arrow3, arrow4, arrow5, arrow6])
''' Draw crossed out arrow '''
props['mutation_scale'] = 50.
props['fc'] = 'w'
props['zorder'] = -1
xc, yc = 0.5, 0.5
xw = 0.15
if False:
arrow_left = patches.FancyArrowPatch((xc, yc), (xc - xw, yc), **props)
arrow_right = patches.FancyArrowPatch((xc, yc), (xc + xw, yc), **props)
else:
yw = 0.02
arrow_left = patches.FancyArrowPatch((xc + xw - 0.01, yc + yw),
(xc - xw, yc + yw), **props)
arrow_right = patches.FancyArrowPatch((xc - xw + 0.01, yc - yw),
(xc + xw, yc - yw), **props)
f.patches.extend([arrow_left, arrow_right])
dx, dy = 0.05, 0.05
redcross = plt.scatter(xc,
yc,
s=2000,
c='red',
transform=f.transFigure,
marker='x',
lw=7,
clip_on=False)
ax.add_artist(redcross)
#f.tight_layout()
helpers.save(plt, epos.plotdir + 'workflow/arrows')
def model(epos, color='C0', alpha_fac=None, Bins=False, Poly=False, Gradient=False):
f, ax = plt.subplots()
name= '{}, $\eta={:.2g}$'.format(epos.name, epos.occurrence['model']['eta'])
ax.set_title(name)
helpers.set_axes(ax, epos, Trim=True)
# set transparency / color gradient
if Gradient:
suffix= '.gradient'
weigths= epos.occurrence['model']['completeness']
cmin, cmax= 0.001, 0.1
weigths= np.maximum(np.minimum(weigths,cmax), cmin)
cmap='copper_r'
#ticks=np.linspace(vmin, vmax, (vmax-vmin)+1)
clrs, norm= helpers.color_array(np.log10(weigths),
vmin=np.log10(cmin),vmax=np.log10(cmax), cmap=cmap)
ax.scatter(epos.pfm['P'], epos.pfm['R'],
marker='o', s=13, lw=0, color=clrs,zorder=0)
# colorbar?
# cb1 = clrbar.ColorbarBase(axb, cmap=cmap, norm=norm, ticks=ticks,
# orientation='vertical') # horizontal
# axb.set_yticklabels(100*10.**ticks)
# axb.tick_params(axis='y', direction='out')
elif alpha_fac is not None:
suffix= '.alpha'
weigths= epos.occurrence['model']['completeness']*alpha_fac #*epos.nstars
alpha= np.maximum(np.minimum(weigths,1.), 0.0) # 0.2?
if True:
# color issues with to_rgba_array
clr_rgba = np.empty((len(alpha), 4), float)
for i, a in enumerate(alpha):
clr_rgba[i] = matplotlib.colors.to_rgba(color, a)
else:
clr= np.full_like(weigths,color,dtype=str)
clr_rgba= matplotlib.colors.to_rgba_array(clr) # alpha
#print clr_rgba[0,:]
clr_rgba[:,3]= alpha
ax.scatter(epos.pfm['P'], epos.pfm['R'],
marker='o', s=13, lw=0, color=clr_rgba,zorder=0)
else:
suffix=''
clr= matplotlib.colors.to_rgba(color)
ax.plot(epos.pfm['P'], epos.pfm['R'], ls='', marker='o', mew=0, ms=4,
color=clr, zorder=0)
''' bins'''
if Bins:
occbin= epos.occurrence['model']['bin']
for k, (xbin, ybin, n, inbin, occ) in enumerate(
zip(occbin['x'],occbin['y'],occbin['n'],occbin['i'], occbin['occ'])
):
# box
ax.add_patch(patches.Rectangle( (xbin[0],ybin[0]),
xbin[1]-xbin[0], ybin[1]-ybin[0],
fill=False, zorder=2, ls='-', color='k') )
xnudge=1.01
ynudge=1.02
size=16 if not 'textsize' in epos.plotpars else epos.plotpars['textsize']
# 12 fit in box, 16 default
ax.text(xbin[0]*xnudge,ybin[1]/ynudge,'{:.1%}'.format(occ), va='top',
size=size)
ax.text(xbin[0]*xnudge,ybin[1]/ynudge,'\n$\pm${:.1f}'.format(
occbin['err'][k]*100), va='top', size=size)
ax.text(xbin[1]/xnudge,ybin[0]*ynudge,'n={}'.format(n), ha='right',
size=size)
helpers.save(plt, epos.plotdir+'occurrence/model_bins'+suffix)
elif Poly:
occpoly= epos.occurrence['model']['poly']
for k, (xc, yc, coords, n, inbin, occ, err) in enumerate(
zip(occpoly['xc'],occpoly['yc'],occpoly['coords'],
occpoly['n'],occpoly['i'], occpoly['occ'], occpoly['err'])
):
# box
ax.add_patch(matplotlib.patches.Polygon(coords,
fill=False, zorder=2, ls='-', color='k') )
size=16 if not 'textsize' in epos.plotpars else epos.plotpars['textsize']
# 12 fit in box, 16 default
ax.text(xc,yc,'{:.1%}\n$\pm${:.1%}'.format(occ, err), ha='center', va='center',
size=size)
helpers.save(plt, epos.plotdir+'occurrence/model_poly'+suffix)
else:
helpers.save(plt, epos.plotdir+'occurrence/model'+suffix)
def panels_radius(epos,
Population=False,
Occurrence=False,
Observation=False,
Tag=False,
color='C0',
clr_obs='C3',
Shade=True,
Fancy=True,
Zoom=False):
f, (ax, axR, axP) = helpers.make_panels(plt, Fancy=Fancy)
pfm = epos.pfm
eta = epos.modelpars.get('eta', Init=True)
title = ''
if not 'R' in pfm:
pfm['R'], _ = epos.MR(pfm['M'])
if Tag:
# function that return a simulation subset based on the tag
subset = {
'Fe/H<=0': lambda tag: tag <= 0,
'Fe/H>0': lambda tag: tag > 0
}
''' Bins '''
dwR = 0.2 # bin width in ln space
dwP = 0.3
if Zoom:
xbins = np.exp(
np.arange(np.log(epos.xzoom[0]),
np.log(epos.xzoom[-1]) + dwP, dwP))
ybins = np.exp(
np.arange(np.log(epos.yzoom[0]),
np.log(epos.yzoom[-1]) + dwR, dwR))
else:
xbins = np.exp(
np.arange(np.log(epos.xtrim[0]),
np.log(epos.xtrim[-1]) + dwP, dwP))
ybins = np.exp(
np.arange(np.log(epos.ytrim[0]),
np.log(epos.ytrim[-1]) + dwR, dwR))
''' Plot model occurrence or observed counts'''
if Observation:
# plot model planets * completeness
weights = eta * epos.occurrence['model']['completeness'] / pfm['ns']
else:
weights = np.full(pfm['np'], eta / pfm['ns'])
if 'draw prob' in pfm and not Tag:
prob = pfm['draw prob'][pfm['ID']]
weights *= prob * pfm['ns'] # system weights sum up to 1
#nonzero= np.where(prob>0, 1., 0.)
#weights*= nonzero*(pfm['np']/nonzero.sum())
# histograms
if Tag:
for key, f in subset.iteritems():
toplot = f(pfm['tag'])
#weights= eta*epos.occurrence['model']['completeness'] \
# *np.where(toplot,1.,0.)/f(pfm['system tag']).sum()
weights = np.where(toplot, eta, 0.) / f(pfm['system tag']).sum()
axP.hist(pfm['P'],
bins=xbins,
weights=weights,
histtype='step',
label=key)
axR.hist(pfm['R'],
bins=ybins,
orientation='horizontal',
weights=weights,
histtype='step')
else:
# color have to be 1-element lists ??
axP.hist(pfm['P'], bins=xbins, weights=weights, color=[color])
axR.hist(pfm['R'],
bins=ybins,
orientation='horizontal',
weights=weights,
color=[color])
''' Overplot observations? '''
if Population:
assert hasattr(epos, 'func')
fname = '.pop' + ('.zoom' if Zoom else '')
title = epos.title
pps, pdf, pdf_X, pdf_Y = periodradius(epos, Init=True)
_, _, pdf_X, _ = periodradius(epos, Init=True, ybin=ybins)
_, _, _, pdf_Y = periodradius(epos, Init=True, xbin=xbins)
pps, _, _, _ = periodradius(epos, Init=True, xbin=xbins, ybin=ybins)
#pdf/= np.max(pdf)
#pdflog= np.log10(pdf) # in %
levels = np.linspace(0, np.max(pdf))
lines = np.array([0.1, 0.5]) * np.max(pdf)
if Shade:
ax.contourf(epos.X_in,
epos.Y_in,
pdf,
cmap='Purples',
levels=levels)
#ax.contour(epos.X_in, epos.Y_in, pdf, levels=lines)
# Side panels
#print 'pps model= {}'.format(eta)
axP.plot(epos.MC_xvar,
pdf_X * dwP,
marker='',
ls='-',
color='purple')
axR.plot(pdf_Y * dwR,
epos.in_yvar,
marker='',
ls='-',
color='purple')
else:
# renormalize
xnorm = axP.get_ylim()[1] / max(pdf_X)
ynorm = axR.get_xlim()[1] / max(pdf_Y)
axP.plot(epos.MC_xvar,
pdf_X * xnorm,
marker='',
ls='-',
color=clr_obs)
axR.plot(pdf_Y * ynorm,
epos.in_yvar,
marker='',
ls='-',
color=clr_obs)
elif Observation:
fname = '.obs' + ('.zoom' if Zoom else '')
title = epos.title + ': Counts'
ax.plot(epos.obs_xvar,
epos.obs_yvar,
ls='',
marker='.',
ms=5.0,
color='0.5')
weights = np.full(epos.obs_xvar.size, 1. / epos.nstars)
axP.hist(epos.obs_xvar,
bins=xbins,
weights=weights,
histtype='step',
color='0.5')
axR.hist(epos.obs_yvar,
bins=ybins,
weights=weights,
orientation='horizontal',
histtype='step',
color='0.5')
elif Occurrence:
fname = '.occ' + ('.zoom' if Zoom else '')
title = epos.title + r': Occurrence, $\eta={:.2g}$'.format(eta)
ax.plot(epos.obs_xvar,
epos.obs_yvar,
ls='',
marker='.',
ms=5.0,
color='0.5')
cut = epos.obs_yvar > 0.45
weights = 1. / (epos.occurrence['planet']['completeness'][cut] *
epos.nstars)
axP.hist(epos.obs_xvar[cut],
bins=xbins,
weights=weights,
histtype='step',
color='k')
axR.hist(epos.obs_yvar[cut],
bins=ybins,
weights=weights,
orientation='horizontal',
histtype='step',
color='k')
elif Tag:
fname = '.tag'
ax.set_title(epos.title + ': Tag')
axP.legend(frameon=False, fontsize='small')
# for k, tag in enumerate(subset):
# axP.text(0.98,0.95-0.05*k,tag,ha='right',va='top',color='C1',
# transform=axP.transAxes)
else:
fname = ''
if Fancy:
plt.suptitle(title, ha='center') #, x=0.05)
else:
ax.set_title(title)
''' plot main panel'''
#helpers.set_axes(ax, epos, Trim=True)
helpers.set_axes(ax, epos, Trim=True)
if Tag:
for key, f in subset.iteritems():
todraw = f(pfm['tag'])
ax.plot(pfm['P'][todraw], pfm['R'][todraw], **fmt_symbol)
elif 'draw prob' in pfm:
#fmt_symbol['alpha']= 0.6*pfm['draw prob'][pfm['ID']] # alpha can't be array
todraw = pfm['draw prob'][pfm['ID']] > 0
ax.plot(pfm['P'][todraw], pfm['R'][todraw], color=color, **fmt_symbol)
else:
ax.plot(pfm['P'], pfm['R'], color=color, **fmt_symbol)
''' Period side panel '''
#axP.yaxis.tick_right()
#axP.yaxis.set_ticks_position('both')
#axP.tick_params(axis='y', which='minor',left='off',right='off')
helpers.set_axis_distance(axP, epos, Trim=True)
''' Mass side panel'''
helpers.set_axis_size(axR, epos, Trim=True) #, In= epos.MassRadius)
helpers.save(plt, '{}model/input.radius{}'.format(epos.plotdir, fname))
def periodradius_2x2(epos):
f, axes = plt.subplots(2, 2, sharex=True, sharey=True)
((ax1, ax2), (ax3, ax4)) = axes
f.set_size_inches(9, 7) # default 7, 5
f.subplots_adjust(wspace=0.5, hspace=0.5)
if False:
#f.suptitle(epos.name)
f.suptitle(
"Compare Planet Formation Models to Observed Exoplanets with epos")
else:
words = [
'Compare', 'Planet Formation Models', 'to', 'Observed Exoplanets',
'with', 'epos'
]
colors = ['b', '0.5', 'k', 'r', 'k', 'g']
helpers.rainbow_text(0.05,
0.95,
words,
colors,
size=16,
f=f,
fudge=1.5)
#helpers.rainbow_text(0.05, 1.1, words, colors, size=18, ax=axes[0,0])
helpers.set_axes(axes[1, 0], epos, Trim=True)
''' Top left: model '''
ax = axes[0, 0]
ax.set_title('Formation Model: {}'.format(epos.name))
pfm = epos.pfm
ax.plot(pfm['P'], pfm['R'], ls='', marker='.', ms=5.0, color='0.5')
''' Top right: synthetic obs'''
ax = axes[0, 1]
ax.set_title('Simulated Observations')
if epos.MonteCarlo:
sim = epos.synthetic_survey
ax.plot(sim['P'],
sim['Y'],
ls='',
marker='.',
mew=0,
ms=5.0,
color='r',
alpha=0.5)
else:
levels = np.linspace(0, np.max(sim['pdf']))
ax.contourf(epos.MC_xvar,
epos.MC_yvar,
sim['pdf'].T,
cmap='Reds',
levels=levels)
''' Bottom left: occurrnce rates'''
ax = axes[1, 0]
ax.set_title('Occurrence Rates')
occbin = epos.occurrence['bin']
maxocc = np.max(occbin['occ'])
for k, (xbin, ybin, n, inbin, occ) in enumerate(
zip(occbin['x'], occbin['y'], occbin['n'], occbin['i'],
occbin['occ'])):
# box
ax.add_patch(
patches.Rectangle((xbin[0], ybin[0]),
xbin[1] - xbin[0],
ybin[1] - ybin[0],
fill=True,
ls='-',
fc=cm.binary(occ / maxocc)))
#xnudge=1.01
#ynudge=1.02
#ax.text(xbin[0]*xnudge,ybin[1]/ynudge,'{:.1%}'.format(occ), va='top',
# size=8)
# colored dots
#ax.plot(epos.obs_xvar, epos.obs_yvar,
# ls='', marker='.', mew=0, ms=2.0, color='k')
''' Bottom right: observations '''
ax = axes[1, 1]
ax.set_title('Observed Planets')
ax.plot(epos.obs_xvar,
epos.obs_yvar,
ls='',
marker='.',
mew=0,
ms=5.0,
color='C3')
''' Draw arrows between plots'''
props = dict(transform=f.transFigure,
arrowstyle='simple',
connectionstyle='arc3',
alpha=0.3,
fc='g',
mutation_scale=80.)
xl, xr = 0.44, 0.57
yt, yb = 0.75, 0.25
arrow1 = patches.FancyArrowPatch((xl, yt), (xr, yt), **props)
arrow2 = patches.FancyArrowPatch((xr, yb), (xl, yb), **props)
f.text((xl + xr) / 2,
yt,
'Bias',
color='k',
ha='center',
va='center',
transform=f.transFigure)
f.text((xl + xr) / 2,
yb,
'Debias',
color='k',
ha='center',
va='center',
transform=f.transFigure)
# and top-bottom
props['connectionstyle'] = 'arc3,rad=0.9'
props['mutation_scale'] = 30.
props['fc'] = 'b'
xl, xr = 0.27, 0.75
xw = 0.03
yt, yb = 0.55, 0.46
arrow3 = patches.FancyArrowPatch((xl - xw, yt), (xl - xw, yb), **props)
arrow4 = patches.FancyArrowPatch((xl + xw, yb), (xl + xw, yt), **props)
for xt in [xl, xr]:
f.text(xt, (yt + yb) / 2,
'Compare',
color='b',
ha='center',
va='center',
transform=f.transFigure)
arrow5 = patches.FancyArrowPatch((xr - xw, yt), (xr - xw, yb), **props)
arrow6 = patches.FancyArrowPatch((xr + xw, yb), (xr + xw, yt), **props)
f.patches.extend([arrow1, arrow2, arrow3, arrow4, arrow5, arrow6])
#f.tight_layout()
helpers.save(plt, epos.plotdir + 'workflow/arrows_2x2')
def colored(epos, Bins=False, Poly=False):
f, (ax, axb) = plt.subplots(1,2, gridspec_kw = {'width_ratios':[20, 1]})
f.subplots_adjust(wspace=0)
name= 'Survey Completeness'
if epos.name in ['dr25_F','dr25_G','dr25_K','dr25_M','dr25_GK']: name+= ' ('+epos.name[5:]+')'
ax.set_title(name)
helpers.set_axes(ax, epos, Trim=True)
#if epos.plot['']
#ax.plot(epos.obs_xvar, epos.obs_yvar, ls='', marker='.', mew=0, ms=5.0, color='k')
''' color scale? '''
cmap='magma' # viridis, plasma, inferno, magma, spring, cool
cmap='viridis'
vmin, vmax= -4, 0
ticks=np.linspace(vmin, vmax, (vmax-vmin)+1)
clrs, norm= helpers.color_array(np.log10(epos.occurrence['planet']['completeness']),
vmin=vmin,vmax=vmax, cmap=cmap)
ax.scatter(epos.obs_xvar, epos.obs_yvar, color=clrs, s=4)
# colorbar?
cb1 = clrbar.ColorbarBase(axb, cmap=cmap, norm=norm, ticks=ticks,
orientation='vertical') # horizontal
axb.set_yticklabels(100*10.**ticks)
axb.tick_params(axis='y', direction='out')
''' bins?'''
if Bins:
occbin= epos.occurrence['bin']
for k, (xbin, ybin, n, inbin, occ) in enumerate(
zip(occbin['x'],occbin['y'],occbin['n'],occbin['i'], occbin['occ'])
):
clr= clrs[k%4]
# colored dots
#ax.plot(epos.obs_xvar[inbin], epos.obs_yvar[inbin],
# ls='', marker='.', mew=0, ms=5.0, color=clr, zorder=1)
# box
ax.add_patch(patches.Rectangle( (xbin[0],ybin[0]),
xbin[1]-xbin[0], ybin[1]-ybin[0],
fill=False, zorder=2, ls='-', color='k') )
xnudge=1.01
ynudge=1.02
size=16 if not 'textsize' in epos.plotpars else epos.plotpars['textsize']
# 12 fit in box, 16 default
ax.text(xbin[0]*xnudge,ybin[1]/ynudge,'{:.1%}'.format(occ), va='top',
size=size)
ax.text(xbin[0]*xnudge,ybin[1]/ynudge,'\n$\pm${:.1f}'.format(
occbin['err'][k]*100), va='top', size=size)
ax.text(xbin[1]/xnudge,ybin[0]*ynudge,'n={}'.format(n), ha='right',
size=size)
helpers.save(plt, epos.plotdir+'occurrence/bins')
elif Poly:
occpoly= epos.occurrence['poly']
for k, (xc, yc, coords, n, inbin, occ, err) in enumerate(
zip(occpoly['xc'],occpoly['yc'],occpoly['coords'],
occpoly['n'],occpoly['i'], occpoly['occ'], occpoly['err'])
):
# box
ax.add_patch(matplotlib.patches.Polygon(coords,
fill=False, zorder=2, ls='-', color='k') )
size=16 if not 'textsize' in epos.plotpars else epos.plotpars['textsize']
# 12 fit in box, 16 default
ax.text(xc,yc,'{:.1%}\n$\pm${:.1f}'.format(occ, err*100), ha='center', va='center',
size=size)
#ax.text(xbin[1]/xnudge,ybin[0]*ynudge,'n={}'.format(n), ha='right',
# size=size)
helpers.save(plt, epos.plotdir+'occurrence/poly')
else:
helpers.save(plt, epos.plotdir+'occurrence/colored')
def periodradius(epos, Nth=False, MC=True):
f, (ax, axR, axP) = helpers.make_panels(plt)
if MC:
sim = epos.synthetic_survey
ID = sim['ID']
P = sim['P']
Y = sim['Y']
outdir = 'output'
title = 'Simulated Detections'
else:
ID = epos.obs_starID
P = epos.obs_xvar
Y = epos.obs_yvar
outdir = 'survey'
title = r'Planet Candidates (score$\geq$0.9)'
''' plot R(P), main panel'''
ax.set_title(title)
helpers.set_axes(ax, epos, Trim=True)
''' Period side panel '''
helpers.set_axis_distance(axP, epos, Trim=True)
#axP.set_yscale('log')
#axP.set_ylim([2e-3,5])
#axP.set_yticks([0.01,0.1,1])
#axP.set_yticklabels(['1%','10%','100%'])
axP.yaxis.tick_right()
axP.yaxis.set_ticks_position('both')
#axP.tick_params(axis='y', which='minor',left='off',right='off')
#axP.hist(sim['P'], bins=epos.MC_xvar, color='0.7')
''' Radius side panel'''
helpers.set_axis_size(axR, epos, Trim=True, In=epos.MassRadius)
#axR.set_xscale('log')
#axR.set_xlim([2e-3,5])
#axR.set_xticks([1,10,100,1000])
#axR.set_xticklabels(['1','10','100','1000'], rotation=70)
for tick in axR.get_xticklabels():
tick.set_rotation(70)
#axR.tick_params(axis='x', which='minor',top='off',bottom='off')
#axP.tick_params(axis='y', which='minor',left='off',right='off')
''' which multiplanets to color '''
# single, multi= EPOS.multi.indices(sim['ID'])
# for k, (label, subset) in enumerate(zip(['single','multi'],[single, multi])):
# ax.plot(sim['P'][subset], sim['Y'][subset], ls='', marker='.', mew=0, ms=5.0, \
# label=label)
if Nth:
single, multi, ksys, multis = EPOS.multi.nth_planet(ID, P)
suffix = '.nth'
label_single = 'single'
else:
single, multi, ksys, multis = EPOS.multi.indices(ID)
suffix = ''
label_single = '1'
ax.plot(P[single], Y[single], ls='', marker='.', \
color='0.7', label=label_single)
''' Multiplanets with colors'''
Stacked = True
plist = []
ylist = []
colors = []
CDF = False
#stacked histogram
for k, subset in zip(ksys, multis):
ht, = ax.plot(P[subset], Y[subset], ls='', marker='.', \
label=k)
if not CDF:
if Stacked:
plist.insert(0, P[subset])
ylist.insert(0, Y[subset])
colors.insert(0, ht.get_color())
# pdf
else:
axP.hist(P[subset],
bins=epos.MC_xvar,
color=ht.get_color(),
histtype='step')
if k == ksys[-1]:
axP.hist(P[single],
bins=epos.MC_xvar,
color='0.7',
histtype='step')
else:
# cumulative
Plist = np.sort(P[subset])
axP.step(Plist, np.arange(Plist.size, dtype=float) / Plist.size)
if Stacked:
plist.append(P[single])
ylist.append(Y[single])
colors.append('0.7')
axP.hist(plist, bins=epos.MC_xvar, color=colors, histtype='barstacked')
axR.hist(ylist,
bins=epos.MC_yvar,
orientation='horizontal',
color=colors,
histtype='barstacked')
else:
#axR.hist(Y,orientation='horizontal', bins=epos.MC_yvar, color='0.7')
axR.hist(Y,
orientation='horizontal',
bins=epos.MC_yvar,
color='k',
histtype='step')
axR.hist(Y[single],
orientation='horizontal',
bins=epos.MC_yvar,
color='0.7')
#ax.legend(loc='lower left', shadow=False, prop={'size':14}, numpoints=1)
ax.legend(bbox_to_anchor=(1.0, 1.0),
markerscale=2,
frameon=True,
borderpad=0.2,
handlelength=1,
handletextpad=0.2)
helpers.save(plt, '{}{}/PR.multi{}'.format(epos.plotdir, outdir, suffix))
def periodradius(epos, SNR=True, Model=False, color='C1'):
f, (ax, axR, axP) = helpers.make_panels(plt, Fancy=True)
sim = epos.synthetic_survey
title = 'Simulated Detections: {}'.format(epos.name)
fsuffix = 'detect'
xbins = epos.MC_xvar
ybins = epos.MC_yvar
if SNR:
transit = epos.transit
title = 'Simulated Transiting Planets'
fsuffix = 'transit'
elif Model:
pfm = epos.pfm
fsuffix = 'population'
dwR = 0.2 # bin width in ln space
dwP = 0.3
xbins = np.exp(
np.arange(np.log(epos.mod_xlim[0]),
np.log(epos.mod_xlim[-1]) + dwP, dwP))
ybins = np.exp(
np.arange(np.log(epos.ytrim[0]),
np.log(epos.ytrim[-1]) + dwR, dwR))
''' plot R(P), main panel'''
f.suptitle(title)
helpers.set_axes(ax, epos, Trim=True)
if SNR:
ax.plot(transit['P'], transit['Y'], ls='', marker='.', color='C6')
elif Model:
ax.plot(pfm['P'], pfm['R'], ls='', marker='.', ms=5.0, color='0.5')
ax.plot(sim['P'], sim['Y'], ls='', marker='.', color=color)
if Model:
xlim = ax.get_xlim()
ax.set_xlim(xlim[0], epos.mod_xlim[-1])
#ax.set_ylim(epos.mod_ylim)
''' Period side panel '''
#helpers.set_axis_distance(axP, epos, Trim=True)
axP.set_xlabel(ax.get_xlabel())
#axP.set_yscale('log')
#axP.set_ylim([2e-3,5])
#axP.set_yticks([0.01,0.1,1])
#axP.set_yticklabels(['1%','10%','100%'])
axP.yaxis.tick_right()
axP.yaxis.set_ticks_position('both')
#axP.tick_params(axis='y', which='minor',left='off',right='off')
if SNR:
axP.hist(transit['P'], bins=xbins, color='C6', density=True)
elif Model:
axP.hist(pfm['P'], bins=xbins, color='0.5', density=True, log=True)
axP.hist(pfm['P'],
bins=xbins,
color='k',
density=True,
log=True,
histtype='step',
zorder=10,
ls='-')
axP.hist(sim['P'], bins=xbins, density=Model, log=Model, color=color)
''' Radius side panel'''
#helpers.set_axis_size(axR, epos, Trim=True, In= epos.MassRadius)
axR.set_ylabel(ax.get_ylabel())
#axR.set_xscale('log')
#axR.set_xlim([2e-3,5])
#axR.set_xticks([1,10,100,1000])
#axR.set_xticklabels(['1','10','100','1000'], rotation=70)
for tick in axR.get_xticklabels():
tick.set_rotation(70)
#axR.tick_params(axis='x', which='minor',top='off',bottom='off')
#axP.tick_params(axis='y', which='minor',left='off',right='off')
if SNR:
axR.hist(transit['Y'],
orientation='horizontal',
bins=ybins,
color='C6',
density=True)
elif Model:
axR.hist(pfm['R'],
orientation='horizontal',
bins=ybins,
color='0.5',
density=True,
log=True)
axR.hist(pfm['R'],
orientation='horizontal',
bins=ybins,
color='k',
density=True,
log=True,
histtype='step',
zorder=10,
ls='-')
axR.hist(sim['Y'],
orientation='horizontal',
bins=ybins,
density=Model,
log=Model,
color=color)
# labels
if SNR:
xpos = epos.MC_xvar[-1]
ypos = axP.get_ylim()[-1] / 1.05
axP.text(xpos, ypos, 'Detected ', color=color, ha='right', va='top')
axP.text(xpos,
ypos / 1.3,
'Undetected ',
color='C6',
ha='right',
va='top')
elif Model:
xpos = ax.get_xlim()[-1]
ypos = ax.get_ylim()[-1] / 1.05
ax.text(xpos, ypos, 'Detected ', color=color, ha='right', va='top')
ax.text(xpos,
ypos / 1.3,
'Undetected ',
color='0.5',
ha='right',
va='top')
#ax.legend(loc='lower left', shadow=False, prop={'size':14}, numpoints=1)
helpers.save(plt, '{}output/periodradius.{}'.format(epos.plotdir, fsuffix))
