# PotentialBase¶

class gala.potential.potential.PotentialBase(parameters, origin=None, parameter_physical_types=None, ndim=3, units=None)[source]

Bases: gala.potential.common.CommonBase

A baseclass for defining pure-Python gravitational potentials.

Subclasses must define (at minimum) a method that evaluates the potential energy at a given position q and time t: _energy(q, t). For integration, the subclasses must also define a method to evaluate the gradient, _gradient(q,t). Optionally, they may also define methods to compute the density and hessian: _density(), _hessian().

Methods Summary

 __call__(q) Call self as a function. acceleration(q[, t]) Compute the acceleration due to the potential at the given position(s). circular_velocity(q[, t]) Estimate the circular velocity at the given position assuming the potential is spherical. density(q[, t]) Compute the density value at the given position(s). energy(q[, t]) Compute the potential energy at the given position(s). gradient(q[, t]) Compute the gradient of the potential at the given position(s). hessian(q[, t]) Compute the Hessian of the potential at the given position(s). integrate_orbit(*args, **kwargs) Warning This is now deprecated. Convenient orbit integration should mass_enclosed(q[, t]) Estimate the mass enclosed within the given position by assuming the potential is spherical. plot_contours(grid[, filled, ax, labels, …]) Plot equipotentials contours. plot_density_contours(grid[, filled, ax, …]) Plot density contours. save(f) Save the potential to a text file. total_energy(x, v) Compute the total energy (per unit mass) of a point in phase-space in this potential. value(*args, **kwargs)

Methods Documentation

__call__(q)[source]

Call self as a function.

acceleration(q, t=0.0)[source]

Compute the acceleration due to the potential at the given position(s).

Parameters: q : PhaseSpacePosition, Quantity, array_like Position to compute the acceleration at. acc : Quantity The acceleration. Will have the same shape as the input position array, q.
circular_velocity(q, t=0.0)[source]

Estimate the circular velocity at the given position assuming the potential is spherical.

Parameters: q : array_like, numeric Position(s) to estimate the circular velocity. vcirc : Quantity Circular velocity at the given position(s). If the input position has shape q.shape, the output energy will have shape q.shape[1:].
density(q, t=0.0)[source]

Compute the density value at the given position(s).

Parameters: q : PhaseSpacePosition, Quantity, array_like The position to compute the value of the potential. If the input position object has no units (i.e. is an ndarray), it is assumed to be in the same unit system as the potential. dens : Quantity The potential energy or value of the potential. If the input position has shape q.shape, the output energy will have shape q.shape[1:].
energy(q, t=0.0)[source]

Compute the potential energy at the given position(s).

Parameters: q : PhaseSpacePosition, Quantity, array_like The position to compute the value of the potential. If the input position object has no units (i.e. is an ndarray), it is assumed to be in the same unit system as the potential. E : Quantity The potential energy per unit mass or value of the potential.
gradient(q, t=0.0)[source]

Compute the gradient of the potential at the given position(s).

Parameters: q : PhaseSpacePosition, Quantity, array_like The position to compute the value of the potential. If the input position object has no units (i.e. is an ndarray), it is assumed to be in the same unit system as the potential. grad : Quantity The gradient of the potential. Will have the same shape as the input position.
hessian(q, t=0.0)[source]

Compute the Hessian of the potential at the given position(s).

Parameters: q : PhaseSpacePosition, Quantity, array_like The position to compute the value of the potential. If the input position object has no units (i.e. is an ndarray), it is assumed to be in the same unit system as the potential. hess : Quantity The Hessian matrix of second derivatives of the potential. If the input position has shape q.shape, the output energy will have shape (q.shape[0],q.shape[0]) + q.shape[1:]. That is, an n_dim by n_dim array (matrix) for each position.
integrate_orbit(*args, **kwargs)[source]

Warning

This is now deprecated. Convenient orbit integration should happen using the gala.potential.Hamiltonian class. With a static reference frame, you just need to pass your potential in to the Hamiltonian constructor.

Integrate an orbit in the current potential using the integrator class provided. Uses same time specification as Integrator.run() – see the documentation for gala.integrate for more information.

Parameters: w0 : PhaseSpacePosition, array_like Initial conditions. Integrator : Integrator (optional) Integrator class to use. Integrator_kwargs : dict (optional) Any extra keyword argumets to pass to the integrator class when initializing. Only works in non-Cython mode. cython_if_possible : bool (optional) If there is a Cython version of the integrator implemented, and the potential object has a C instance, using Cython will be much faster. **time_spec Specification of how long to integrate. See documentation for parse_time_specification. orbit : Orbit
mass_enclosed(q, t=0.0)[source]

Estimate the mass enclosed within the given position by assuming the potential is spherical.

Parameters: q : PhaseSpacePosition, Quantity, array_like Position(s) to estimate the enclossed mass. menc : Quantity Mass enclosed at the given position(s). If the input position has shape q.shape, the output energy will have shape q.shape[1:].
plot_contours(grid, filled=True, ax=None, labels=None, subplots_kw={}, **kwargs)[source]

Plot equipotentials contours. Computes the potential energy on a grid (specified by the array grid).

Warning

Right now the grid input must be arrays and must already be in the unit system of the potential. Quantity support is coming…

Parameters: grid : tuple Coordinate grids or slice value for each dimension. Should be a tuple of 1D arrays or numbers. filled : bool (optional) Use contourf() instead of contour(). Default is True. ax : matplotlib.Axes (optional) labels : iterable (optional) List of axis labels. subplots_kw : dict kwargs passed to matplotlib’s subplots() function if an axes object is not specified. kwargs : dict kwargs passed to either contourf() or plot(). fig : Figure
plot_density_contours(grid, filled=True, ax=None, labels=None, subplots_kw={}, **kwargs)[source]

Plot density contours. Computes the density on a grid (specified by the array grid).

Warning

Right now the grid input must be arrays and must already be in the unit system of the potential. Quantity support is coming…

Parameters: grid : tuple Coordinate grids or slice value for each dimension. Should be a tuple of 1D arrays or numbers. filled : bool (optional) Use contourf() instead of contour(). Default is True. ax : matplotlib.Axes (optional) labels : iterable (optional) List of axis labels. subplots_kw : dict kwargs passed to matplotlib’s subplots() function if an axes object is not specified. kwargs : dict kwargs passed to either contourf() or plot(). fig : Figure
save(f)[source]

Save the potential to a text file. See save() for more information.

Parameters: f : str, file_like A filename or file-like object to write the input potential object to.
total_energy(x, v)[source]

Compute the total energy (per unit mass) of a point in phase-space in this potential. Assumes the last axis of the input position / velocity is the dimension axis, e.g., for 100 points in 3-space, the arrays should have shape (100,3).

Parameters: x : array_like, numeric Position. v : array_like, numeric Velocity.
value(*args, **kwargs)[source]