lalinference_compute_roq_weights.py File Reference

Prototypes
def	lalinference_compute_roq_weights.blockwise_dot (A, B, deltaF, max_elements=int(2 **27), out=None)
	Computes the dot product of two matrices in a block-wise fashion. More...
def	lalinference_compute_roq_weights.ehat (j, length)
	Return a unit vector whose j-th component is 1. More...
def	lalinference_compute_roq_weights.DEIM (basis)
	Calculate interpolation nodes following the Algorithm 5 in J Sci Comput (2013) 57:604-637. More...
def	lalinference_compute_roq_weights.construct_nodes (selected_params, flow, fhigh, deltaF, approximant, quadratic)
	Construct frequency nodes and weights from parameter values selected by greedy algorithm. More...
def	lalinference_compute_roq_weights.BuildWeights (data, B, deltaF)
	for a data array and reduced basis compute roq weights More...

Go to the source code of this file.

Namespaces
namespace	lalinference_compute_roq_weights

Variables
string	lalinference_compute_roq_weights.data_dir = './'
	lalinference_compute_roq_weights.parser
	lalinference_compute_roq_weights.type
	lalinference_compute_roq_weights.action
	lalinference_compute_roq_weights.dest
	lalinference_compute_roq_weights.help
	lalinference_compute_roq_weights.default
	lalinference_compute_roq_weights.options
	lalinference_compute_roq_weights.args
	lalinference_compute_roq_weights.basis_params = np.loadtxt(os.path.join(options.b_matrix_directory, "params.dat")).T
	lalinference_compute_roq_weights.flow_in_params
	lalinference_compute_roq_weights.fhigh_in_params
	lalinference_compute_roq_weights.deltaF_in_params
	lalinference_compute_roq_weights.B_linear_path = os.path.join(options.b_matrix_directory, "B_linear.npy")
	lalinference_compute_roq_weights.B_quadratic_path = os.path.join(options.b_matrix_directory, "B_quadratic.npy")
	lalinference_compute_roq_weights.fnodes_linear_path = os.path.join(options.b_matrix_directory, "fnodes_linear.npy")
	lalinference_compute_roq_weights.fnodes_quadratic_path = os.path.join(options.b_matrix_directory, "fnodes_quadratic.npy")
	lalinference_compute_roq_weights.params_linear_path = os.path.join(options.b_matrix_directory, "selected_params_linear.npy")
	lalinference_compute_roq_weights.params_quadratic_path = os.path.join(options.b_matrix_directory, "selected_params_quadratic.npy")
	lalinference_compute_roq_weights.B_linear = np.load(B_linear_path)
	lalinference_compute_roq_weights.B_quadratic = np.load(B_quadratic_path)
	lalinference_compute_roq_weights.fnodes_linear = np.load(fnodes_linear_path)
	lalinference_compute_roq_weights.fnodes_quadratic = np.load(fnodes_quadratic_path)
	lalinference_compute_roq_weights.selected_params_linear = np.load(params_linear_path)
	lalinference_compute_roq_weights.selected_params_quadratic = np.load(params_quadratic_path)
int	lalinference_compute_roq_weights.relative_tc_shift = options.seglen - 2.
int	lalinference_compute_roq_weights.i = 0
int	lalinference_compute_roq_weights.scale_factor = 0
	lalinference_compute_roq_weights.dat_file = np.column_stack( np.loadtxt(options.data_file[i]) )
int	lalinference_compute_roq_weights.data = dat_file[1] + 1j*dat_file[2]
	lalinference_compute_roq_weights.fseries = dat_file[0]
int	lalinference_compute_roq_weights.deltaF = 1./options.seglen
	lalinference_compute_roq_weights.fHigh = options.fHigh
	lalinference_compute_roq_weights.fHigh_index = int(fHigh / deltaF)
	lalinference_compute_roq_weights.fLow = options.fLow
	lalinference_compute_roq_weights.fLow_index = int(fLow / deltaF)
	lalinference_compute_roq_weights.psdfile = np.column_stack( np.loadtxt(options.psd_file[i]) )
	lalinference_compute_roq_weights.psd = psdfile[1]
	lalinference_compute_roq_weights.tcs = np.linspace(relative_tc_shift - options.dt - 0.045, relative_tc_shift + options.dt + 0.045, ceil(2.*(options.dt+0.045) / options.delta_tc) )
	lalinference_compute_roq_weights.tc_shifted_data = np.zeros([len(tcs), len(fseries)], dtype=complex)
	lalinference_compute_roq_weights.tc = tcs[j]
	lalinference_compute_roq_weights.weights_path_linear = os.path.join(options.outpath,"weights_linear_%s.dat"%ifo)
	lalinference_compute_roq_weights.weights_file_linear = open(weights_path_linear, "wb")
int	lalinference_compute_roq_weights.max_block_gigabytes = 4
	lalinference_compute_roq_weights.max_elements = int((max_block_gigabytes * 2 ** 30) / 8)
def	lalinference_compute_roq_weights.weights_linear = blockwise_dot(tc_shifted_data, B_linear.conjugate(), deltaF, max_elements).T
	lalinference_compute_roq_weights.weights_path_quadratic = os.path.join(options.outpath,"weights_quadratic_%s.dat"%ifo)
	lalinference_compute_roq_weights.weights_file_quadratic = open(weights_path_quadratic, "wb")
tuple	lalinference_compute_roq_weights.weights_quadratic = (BuildWeights(1./psd, B_quadratic, deltaF).T).real
	lalinference_compute_roq_weights.size_file_path = os.path.join(options.outpath,"roq_sizes.dat")
	lalinference_compute_roq_weights.fmt
	lalinference_compute_roq_weights.fnodes_linear_file = open(fnodes_linear_path, "wb")
	lalinference_compute_roq_weights.fnodes_quadratic_file = open(fnodes_quadratic_path, "wb")
	lalinference_compute_roq_weights.tcs_file_path = os.path.join(options.outpath,"tcs.dat")
	lalinference_compute_roq_weights.tcs_file = open(tcs_file_path, "wb")