From b24a3c6abe4c8197779afc61f40d850c4441716a Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Thu, 15 Aug 2024 20:08:00 +0000 Subject: [PATCH] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- doc/source/reference/df.rst | 2 +- doc/source/streamdf.rst | 12 ++++++------ 2 files changed, 7 insertions(+), 7 deletions(-) diff --git a/doc/source/reference/df.rst b/doc/source/reference/df.rst index 36ad346c0..008e311a6 100644 --- a/doc/source/reference/df.rst +++ b/doc/source/reference/df.rst @@ -335,7 +335,7 @@ The distribution function of a tidal stream using a particle-spray technique ---------------------------------------------------------------------------- Model from `Chen et al. (2024) -`__ and +`__ and `Fardal et al. (2015) `__ with full details of the ``galpy`` implementation given in `Qian et al. (2022) diff --git a/doc/source/streamdf.rst b/doc/source/streamdf.rst index 150fc1815..15d761bdb 100644 --- a/doc/source/streamdf.rst +++ b/doc/source/streamdf.rst @@ -539,7 +539,7 @@ as a simple ``LogarithmicHaloPotential``): >>> o= Orbit([1.56148083,0.35081535,-1.15481504,0.88719443,-0.47713334,0.12019596]) >>> lp= LogarithmicHaloPotential(normalize=1.,q=0.9) -Then, we setup ``chen24spraydf`` and ``fardal15spraydf`` models for the leading +Then, we setup ``chen24spraydf`` and ``fardal15spraydf`` models for the leading and trailing arm of the stream: >>> from astropy import units @@ -557,15 +557,15 @@ potential. Here, we use a Plummer potential for the prognenitor: >>> orbs_c24,dt_c24= spdf_c24.sample(n=300,returndt=True,integrate=True, pot_prog=pot_prog) >>> orbts_c24,dt_c24= spdft_c24.sample(n=300,returndt=True,integrate=True, pot_prog=pot_prog) -which returns a ``galpy.orbit.Orbit`` instance with all 300 stars. Next, we +which returns a ``galpy.orbit.Orbit`` instance with all 300 stars. Next, we sample stars with ``fardal15spraydf`` without the progenitor's potential: >>> orbs_f15,dt= spdf_f15.sample(n=300,returndt=True,integrate=True) >>> orbts_f15,dt= spdft_f15.sample(n=300,returndt=True,integrate=True) -We can plot the ``galpy.orbit.Orbit`` instance in :math:`Z` versus :math:`X` -and compare to Fig. 1 in Bovy (2014). First, we also integrate the orbit of the -progenitor forward and backward in time for a brief period to show its location +We can plot the ``galpy.orbit.Orbit`` instance in :math:`Z` versus :math:`X` +and compare to Fig. 1 in Bovy (2014). First, we also integrate the orbit of the +progenitor forward and backward in time for a brief period to show its location in the area of the stream: >>> ts= numpy.linspace(0.,3.,301) @@ -590,7 +590,7 @@ which gives We can also compare to the track for this stream as predicted by ``streamdf``. For this, we first setup a similar ``streamdf`` model (they are not exactly the same, as ``streamdf`` uses a velocity dispersion to set the progenitor's -mass, while ``fardal15spraydf`` and ``chen15spraydf`` uses the mass directly); +mass, while ``fardal15spraydf`` and ``chen15spraydf`` uses the mass directly); see the ``streamdf`` documentation for a full explanation of this code: >>> from galpy.actionAngle import actionAngleIsochroneApprox