galpy.df.evolveddiskdf.meanvT

evolveddiskdf.meanvT(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]

Calculate the mean vT of the velocity distribution at (R,phi)

Parameters:

  • R (float) – radius at which to calculate the moment(/ro) (can be Quantity)

  • phi (float, optional) – azimuth (rad unless deg=True; can be Quantity) (default=0.0)

  • t (float or array, optional) – 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) (default=0.0)

  • surfacemass (float, optional) – if set use this pre-calculated surfacemass (default=None)

  • nsigma (float, optional) – number of sigma to integrate the velocities over (based on an estimate, so be generous) (default=None)

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

  • epsrel (float, optional) – scipy.integrate keywords (the integration calculates the ratio of this vmoment to that of the initial DF) (default=1.0e-02)

  • epsabs (float, optional) – scipy.integrate keywords (the integration calculates the ratio of this vmoment to that of the initial DF) (default=1.0e-05)

  • grid (bool or evolveddiskdfGrid or evolveddiskdfHierarchicalGrid, optional) – 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 (default=None)

  • gridpoints (int, optional) – number of points to use for the grid in 1D (default=101)

  • returnGrid (bool, optional) – if True, return the grid object (default=False)

  • hierarchgrid (bool, optional) – if True, use a hierarchical grid (default=False)

  • nlevels (int, optional) – number of hierarchical levels for the hierarchical grid (default=2)

  • integrate_method (str, optional) – orbit.integrate method argument (default=”dopr54_c”)

Returns:

mean vT

Return type:

float or tuple

Notes

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