Module vectors

Vectors, handles, and inner products.

We recommend using these functions and classes when possible. Otherwise, you can write your own vector class and/or vector handle, see documentation Interfacing with your data.

class vectors.InnerProductTrapz(*grids)

Inner product of n-dim arrays on grid using the trapezoidal rule.

Args:

grids: 1D arrays of grid points, in the order of the dims.

x_grid: 1D array of grid points in x-dimension; y_grid: 1D array of grid points in y-dimension; ...

Usage:

nx = 10
ny = 11
x_grid = 1 - N.cos(N.linspace(0, N.pi, nx))
y_grid = N.linspace(0, 1.0, ny)**2
my_trapz = InnerProductTrapz(x_grid, y_grid)

v1 = N.random.random((nx,ny))
v2 = N.random.random((nx,ny))
IP_v1_v2 = my_trapz(v1, v2)

inner_product(vec1, vec2)

Takes the inner product.

class vectors.VecHandle(base_vec_handle=None, scale=None)

Recommended base class for vector handles (not required).

get()

Get a vector, using the private _get function. If available, the base vector will be subtracted from the specified vector. Then, if a scale factor is specified, the base-subtracted vector will be scaled. The scaled, base-subtracted vector is then returned.

put(vec)

Put a vector to file or memory using the _put function.

class vectors.VecHandleArrayText(vec_path, base_vec_handle=None, scale=None)

Gets and puts array vector objects to text files.

class vectors.VecHandleInMemory(vec=None, base_vec_handle=None, scale=None)

Gets and puts vectors in memory.

class vectors.VecHandlePickle(vec_path, base_vec_handle=None, scale=None)

Gets and puts any vector object to pickle files.

class vectors.Vector

Recommended base class for vector objects (not required).

vectors.inner_product_array_uniform(vec1, vec2)

Takes inner product of numpy arrays without weighting.