Merge branch 'master' into twopowertri

doc/source/conf.py

@@ -38,7 +38,7 @@
 
 # General information about the project.
 project = u'galpy'
-copyright = u'2010 - 2015, Jo Bovy'
+copyright = u'2010 - 2016, Jo Bovy'
 
 # The version info for the project you're documenting, acts as replacement for
 # |version| and |release|, also used in various other places throughout the

doc/source/index.rst

@@ -108,6 +108,8 @@ The following is a list of publications using ``galpy``; please let me (bovy -at
     Introduces ``galpy.df.streamdf`` and ``galpy.actionAngle.actionAngleIsochroneApprox`` for modeling tidal streams using simple models formulated in action-angle space (see the tutorial above).
 #. *The Milky Way Tomography with SDSS. V. Mapping the Dark Matter Halo*, Sarah R. Loebman, Zeljko Ivezic Thomas R. Quinn, Jo Bovy, Charlotte R. Christensen, Mario Juric, Rok Roskar, Alyson M. Brooks, & Fabio Governato (2014), *Astrophys. J.*, **794**, 151 (`2014ApJ...794..151L <http://adsabs.harvard.edu/abs/2014ApJ...794..151L>`_):
     Uses ``galpy.potential`` functions to calculate the acceleration field of the best-fit potential in Bovy & Rix (2013) above.
+#. *The Proper Motion of the Galactic Center Pulsar Relative to Sagittarius A**, Geoffrey C. Bower, Adam Deller, Paul Demorest, et al. (2015), *Astrophys. J.*, **798**, 120 (`2015ApJ...798..120B <http://adsabs.harvard.edu/abs/2015ApJ...798..120B>`_):
+    Utilizes ``galpy.orbit`` integration in Monte Carlo simulations of the possible origin of the pulsar PSR J1745-2900 near the black hole at the center of the Milky Way.
 #. *The power spectrum of the Milky Way: Velocity fluctuations in the Galactic disk*, Jo Bovy, Jonathan C. Bird, Ana E. Garcia Perez, Steven M. Majewski, David L. Nidever, & Gail Zasowski (2015), *Astrophys. J.*, **800**, 83 (`2015ApJ...800...83B <http://adsabs.harvard.edu/abs/2015ApJ...800...83B>`_):
     Uses ``galpy.df.evolveddiskdf`` to calculate the mean non-axisymmetric velocity field due to different non-axisymmetric perturbations and compares it to APOGEE data.
 #. *The LMC geometry and outer stellar populations from early DES data*, Eduardo Balbinot, B. X. Santiago, L. Girardi, et al. (2015), *Mon. Not. Roy. Astron. Soc.*, **449**, 1129 (`2015MNRAS.449.1129B <http://adsabs.harvard.edu/abs/2015MNRAS.449.1129B>`_):
@@ -156,6 +158,8 @@ The following is a list of publications using ``galpy``; please let me (bovy -at
      Makes use of potential models, the Staeckel actionAngle modules, and the quasiisothermal DF to develop a robust dynamical modeling approach for recovering the Milky Way's gravitational potential from kinematics of disk stars.
 #. *A Dipole on the Sky: Predictions for Hypervelocity Stars from the Large Magellanic Cloud*, Douglas Boubert & N. W. Evans (2016), *Astrophys. J. Lett.*, in press (`arXiv/1606.02548 <http://arxiv.org/abs/1606.02548>`_):
      Uses ``galpy.orbit`` integration to investigate the orbits of hyper-velocity stars that could be ejected from the Large Magellanic Cloud and their distribution on the sky.
+#. *Linear perturbation theory for tidal streams and the small-scale CDM power spectrum*, Jo Bovy, Denis Erkal, & Jason L. Sanders (2016), *Mon. Not. Roy. Astron. Soc.*, submitted (`arXiv/1606.03470 <http://arxiv.org/abs/1606.03470>`_):
+     Uses and extends ``galpy.df.streamdf`` and ``galpy.df.streamgapdf`` to quickly compute the effect of impacts from dark-matter subhalos on stellar streams and investigates the structure of perturbed streams and how this structure relates to the CDM subhalo mass spectrum.
 
 Indices and tables
 ==================

galpy/util/bovy_plot.py

@@ -489,6 +489,8 @@ def bovy_dens2d(X,**kwargs):
 
        conditional - normalize each column separately (for probability densities, i.e., cntrmass=True)
 
+       gcf=True does not start a new figure (does change the ranges and labels)
+
        Contours:
        
        justcontours - if True, only draw contours
@@ -527,7 +529,8 @@ def bovy_dens2d(X,**kwargs):
 
     """
     overplot= kwargs.pop('overplot',False)
-    if not overplot:
+    gcf= kwargs.pop('gcf',False)
+    if not overplot and not gcf:
         pyplot.figure()
     xlabel= kwargs.pop('xlabel',None)
     ylabel= kwargs.pop('ylabel',None)
@@ -577,7 +580,7 @@ def bovy_dens2d(X,**kwargs):
     retAxes= kwargs.pop('retAxes',False)
     retCont= kwargs.pop('retCont',False)
     if onedhists:
-        if overplot: fig= pyplot.gcf()
+        if overplot or gcf: fig= pyplot.gcf()
         else: fig= pyplot.figure()
         nullfmt   = NullFormatter()         # no labels
         # definitions for the axes
@@ -828,6 +831,8 @@ def scatterplot(x,y,*args,**kwargs):
 
        conditional - normalize each column separately (for probability densities, i.e., cntrmass=True)
 
+       gcf=True does not start a new figure (does change the ranges and labels)
+
        contours - if False, don't plot contours
 
        justcontours - if True, only draw contours, no density
@@ -902,14 +907,15 @@ def scatterplot(x,y,*args,**kwargs):
     onedhistlw= kwargs.pop('onedhistlw',None)
     onedhistsbins= kwargs.pop('onedhistsbins',round(0.3*sc.sqrt(ndata)))
     overplot= kwargs.pop('overplot',False)
+    gcf= kwargs.pop('gcf',False)
     cmap= kwargs.pop('cmap',cm.gist_yarg)
     onedhistxnormed= kwargs.pop('onedhistxnormed',True)
     onedhistynormed= kwargs.pop('onedhistynormed',True)
     onedhistxweights= kwargs.pop('onedhistxweights',weights)
     onedhistyweights= kwargs.pop('onedhistyweights',weights)
     retAxes= kwargs.pop('retAxes',False)
     if onedhists or onedhistx or onedhisty:
-        if overplot: fig= pyplot.gcf()
+        if overplot or gcf: fig= pyplot.gcf()
         else: fig= pyplot.figure()
         nullfmt   = NullFormatter()         # no labels
         # definitions for the axes
@@ -950,7 +956,7 @@ def scatterplot(x,y,*args,**kwargs):
                               conditional=conditional,
                               cntrlw=cntrlw,cntrls=cntrls,
                               justcontours=justcontours,zorder=5*justcontours,
-                              overplot=(onedhists or overplot or onedhistx or onedhisty))
+                              overplot=(gcf or onedhists or overplot or onedhistx or onedhisty))
     else:
         cumimage= bovy_dens2d(hist.T,contours=contours,
                               cntrcolors=cntrcolors,
@@ -960,7 +966,7 @@ def scatterplot(x,y,*args,**kwargs):
                               conditional=conditional,
                               retCumImage=True,aspect=aspect,
                               cntrlw=cntrlw,cntrls=cntrls,
-                              overplot=(onedhists or overplot or onedhistx or onedhisty))
+                              overplot=(gcf or onedhists or overplot or onedhistx or onedhisty))
     #Set axes and labels
     pyplot.axis(list(xrange)+list(yrange))
     if not overplot: