galpy.df.evolveddiskdf.meanvR

evolveddiskdf.meanvR(R, t=0.0, nsigma=None, deg=False, phi=0.0, epsrel=0.01, epsabs=1e-05, grid=None, gridpoints=101, returnGrid=False, surfacemass=None, hierarchgrid=False, nlevels=2, integrate_method='dopr54_c')[source]

NAME:

meanvR

PURPOSE:

calculate the mean vR of the velocity distribution at (R,phi)

INPUT:

R - radius at which to calculate the moment(/ro) (can be Quantity)

phi= azimuth (rad unless deg=True; can be Quantity)

t= time at which to evaluate the DF (can be a list or ndarray; if this is the case, list needs to be in descending order and equally spaced) (can be Quantity)

surfacemass= if set use this pre-calculated surfacemass

nsigma - number of sigma to integrate the velocities over (based on an estimate, so be generous)

deg= azimuth is in degree (default=False); do not set this when giving phi as a Quantity

epsrel, epsabs - scipy.integrate keywords (the integration calculates the ratio of this vmoment to that of the initial DF)

grid= if set to True, build a grid and use that to evaluate integrals; if set to a grid-objects (such as returned by this procedure), use this grid

gridpoints= number of points to use for the grid in 1D (default=101)

returnGrid= if True, return the grid object (default=False)

hierarchgrid= if True, use a hierarchical grid (default=False)

nlevels= number of hierarchical levels for the hierarchical grid

integrate_method= orbit.integrate method argument

OUTPUT:

mean vR

HISTORY:

2011-03-31 - Written - Bovy (NYU)