Functions
def	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	ehat (j, length)
	Return a unit vector whose j-th component is 1. More...

def	DEIM (basis)
	Calculate interpolation nodes following the Algorithm 5 in J Sci Comput (2013) 57:604-637. More...

def	construct_nodes (selected_params, flow, fhigh, deltaF, approximant, quadratic)
	Construct frequency nodes and weights from parameter values selected by greedy algorithm. More...

def	BuildWeights (data, B, deltaF)
	for a data array and reduced basis compute roq weights More...

Variables
string	data_dir = './'

	parser

	type

	action

	dest

	help

	default

	options

	args

	basis_params = np.loadtxt(os.path.join(options.b_matrix_directory, "params.dat")).T

	flow_in_params

	fhigh_in_params

	deltaF_in_params

	B_linear_path = os.path.join(options.b_matrix_directory, "B_linear.npy")

	B_quadratic_path = os.path.join(options.b_matrix_directory, "B_quadratic.npy")

	fnodes_linear_path = os.path.join(options.b_matrix_directory, "fnodes_linear.npy")

	fnodes_quadratic_path = os.path.join(options.b_matrix_directory, "fnodes_quadratic.npy")

	params_linear_path = os.path.join(options.b_matrix_directory, "selected_params_linear.npy")

	params_quadratic_path = os.path.join(options.b_matrix_directory, "selected_params_quadratic.npy")

	B_linear = np.load(B_linear_path)

	B_quadratic = np.load(B_quadratic_path)

	fnodes_linear = np.load(fnodes_linear_path)

	fnodes_quadratic = np.load(fnodes_quadratic_path)

	selected_params_linear = np.load(params_linear_path)

	selected_params_quadratic = np.load(params_quadratic_path)

int	relative_tc_shift = options.seglen - 2.

int	i = 0

int	scale_factor = 0

	dat_file = np.column_stack( np.loadtxt(options.data_file[i]) )

int	data = dat_file[1] + 1j*dat_file[2]

	fseries = dat_file[0]

int	deltaF = 1./options.seglen

	fHigh = options.fHigh

	fHigh_index = int(fHigh / deltaF)

	fLow = options.fLow

	fLow_index = int(fLow / deltaF)

	psdfile = np.column_stack( np.loadtxt(options.psd_file[i]) )

	psd = psdfile[1]

	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) )

	tc_shifted_data = np.zeros([len(tcs), len(fseries)], dtype=complex)

	tc = tcs[j]

	weights_path_linear = os.path.join(options.outpath,"weights_linear_%s.dat"%ifo)

	weights_file_linear = open(weights_path_linear, "wb")

int	max_block_gigabytes = 4

	max_elements = int((max_block_gigabytes * 2 ** 30) / 8)

def	weights_linear = blockwise_dot(tc_shifted_data, B_linear.conjugate(), deltaF, max_elements).T

	weights_path_quadratic = os.path.join(options.outpath,"weights_quadratic_%s.dat"%ifo)

	weights_file_quadratic = open(weights_path_quadratic, "wb")

tuple	weights_quadratic = (BuildWeights(1./psd, B_quadratic, deltaF).T).real

	size_file_path = os.path.join(options.outpath,"roq_sizes.dat")

	fmt

	fnodes_linear_file = open(fnodes_linear_path, "wb")

	fnodes_quadratic_file = open(fnodes_quadratic_path, "wb")

	tcs_file_path = os.path.join(options.outpath,"tcs.dat")

	tcs_file = open(tcs_file_path, "wb")

Function Documentation

◆ blockwise_dot()

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.

Only blocks of A with a maximum size of max_elements will be processed simultaneously.

Definition at line 27 of file lalinference_compute_roq_weights.py.

◆ ehat()

def lalinference_compute_roq_weights.ehat	(	j,
		length
	)

Return a unit vector whose j-th component is 1.

Definition at line 60 of file lalinference_compute_roq_weights.py.

◆ DEIM()

def lalinference_compute_roq_weights.DEIM ( basis )

Calculate interpolation nodes following the Algorithm 5 in J Sci Comput (2013) 57:604-637.

Parameters

basis : ndarray ndarray whose i-th row is the i-th basis vector

Return

nodes : array interpolation nodes B : ndarray ndarray whose i-th row is the weight for the i-th frequency node.

Definition at line 80 of file lalinference_compute_roq_weights.py.

◆ construct_nodes()

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.

Parameters

selected_params : ndarray rray whose i-th row is the i-th parameter set selected by greedy algorithm flow : float fhigh : float deltaF : float approximant : string quadratic : bool construct nodes for products of waveforms when this is True

Return

f_nodes : ndarray interpolation frequency nodes B : ndarray ndarray whose i-th roq is the weight for the i-th frequency node.

Definition at line 140 of file lalinference_compute_roq_weights.py.

◆ BuildWeights()

def lalinference_compute_roq_weights.BuildWeights	(	data,
		B,
		deltaF
	)

for a data array and reduced basis compute roq weights

B: (reduced basis element)*invV (the inverse Vandermonde matrix) data: data set PSD: detector noise power spectral density (must be same shape as data) deltaF: integration element df

Definition at line 258 of file lalinference_compute_roq_weights.py.

Variable Documentation

◆ data_dir

string lalinference_compute_roq_weights.data_dir = './'

Definition at line 172 of file lalinference_compute_roq_weights.py.

◆ parser

lalinference_compute_roq_weights.parser

Initial value:

1 = OptionParser(usage="usage: %prog [options]",

2 version="%prog")

Definition at line 175 of file lalinference_compute_roq_weights.py.

◆ type

lalinference_compute_roq_weights.type

Definition at line 177 of file lalinference_compute_roq_weights.py.

◆ action

lalinference_compute_roq_weights.action

Definition at line 178 of file lalinference_compute_roq_weights.py.

◆ dest

lalinference_compute_roq_weights.dest

Definition at line 179 of file lalinference_compute_roq_weights.py.

◆ help

lalinference_compute_roq_weights.help

Definition at line 180 of file lalinference_compute_roq_weights.py.

◆ default

lalinference_compute_roq_weights.default

Definition at line 220 of file lalinference_compute_roq_weights.py.

◆ options

lalinference_compute_roq_weights.options

Definition at line 223 of file lalinference_compute_roq_weights.py.

◆ args

lalinference_compute_roq_weights.args

Definition at line 223 of file lalinference_compute_roq_weights.py.

◆ basis_params

lalinference_compute_roq_weights.basis_params = np.loadtxt(os.path.join(options.b_matrix_directory, "params.dat")).T

Definition at line 225 of file lalinference_compute_roq_weights.py.

◆ flow_in_params

lalinference_compute_roq_weights.flow_in_params

Definition at line 226 of file lalinference_compute_roq_weights.py.

◆ fhigh_in_params

lalinference_compute_roq_weights.fhigh_in_params

Definition at line 226 of file lalinference_compute_roq_weights.py.

◆ deltaF_in_params

lalinference_compute_roq_weights.deltaF_in_params

Definition at line 226 of file lalinference_compute_roq_weights.py.

◆ B_linear_path

lalinference_compute_roq_weights.B_linear_path = os.path.join(options.b_matrix_directory, "B_linear.npy")

Definition at line 228 of file lalinference_compute_roq_weights.py.

◆ B_quadratic_path

lalinference_compute_roq_weights.B_quadratic_path = os.path.join(options.b_matrix_directory, "B_quadratic.npy")

Definition at line 229 of file lalinference_compute_roq_weights.py.

◆ fnodes_linear_path

lalinference_compute_roq_weights.fnodes_linear_path = os.path.join(options.b_matrix_directory, "fnodes_linear.npy")

Definition at line 230 of file lalinference_compute_roq_weights.py.

◆ fnodes_quadratic_path

lalinference_compute_roq_weights.fnodes_quadratic_path = os.path.join(options.b_matrix_directory, "fnodes_quadratic.npy")

Definition at line 231 of file lalinference_compute_roq_weights.py.

◆ params_linear_path

lalinference_compute_roq_weights.params_linear_path = os.path.join(options.b_matrix_directory, "selected_params_linear.npy")

Definition at line 232 of file lalinference_compute_roq_weights.py.

◆ params_quadratic_path

lalinference_compute_roq_weights.params_quadratic_path = os.path.join(options.b_matrix_directory, "selected_params_quadratic.npy")

Definition at line 233 of file lalinference_compute_roq_weights.py.

◆ B_linear

lalinference_compute_roq_weights.B_linear = np.load(B_linear_path)

Definition at line 236 of file lalinference_compute_roq_weights.py.

◆ B_quadratic

lalinference_compute_roq_weights.B_quadratic = np.load(B_quadratic_path)

Definition at line 237 of file lalinference_compute_roq_weights.py.

◆ fnodes_linear

lalinference_compute_roq_weights.fnodes_linear = np.load(fnodes_linear_path)

Definition at line 238 of file lalinference_compute_roq_weights.py.

◆ fnodes_quadratic

lalinference_compute_roq_weights.fnodes_quadratic = np.load(fnodes_quadratic_path)

Definition at line 239 of file lalinference_compute_roq_weights.py.

◆ selected_params_linear

lalinference_compute_roq_weights.selected_params_linear = np.load(params_linear_path)

Definition at line 241 of file lalinference_compute_roq_weights.py.

◆ selected_params_quadratic

lalinference_compute_roq_weights.selected_params_quadratic = np.load(params_quadratic_path)

Definition at line 242 of file lalinference_compute_roq_weights.py.

◆ relative_tc_shift

int lalinference_compute_roq_weights.relative_tc_shift = options.seglen - 2.

Definition at line 265 of file lalinference_compute_roq_weights.py.

◆ i

int lalinference_compute_roq_weights.i = 0

Definition at line 269 of file lalinference_compute_roq_weights.py.

◆ scale_factor

lalinference_compute_roq_weights.scale_factor = 0

Definition at line 270 of file lalinference_compute_roq_weights.py.

◆ dat_file

lalinference_compute_roq_weights.dat_file = np.column_stack( np.loadtxt(options.data_file[i]) )

Definition at line 274 of file lalinference_compute_roq_weights.py.

◆ data

int lalinference_compute_roq_weights.data = dat_file[1] + 1j*dat_file[2]

Definition at line 275 of file lalinference_compute_roq_weights.py.

◆ fseries

lalinference_compute_roq_weights.fseries = dat_file[0]

Definition at line 276 of file lalinference_compute_roq_weights.py.

◆ deltaF

lalinference_compute_roq_weights.deltaF = 1./options.seglen

Definition at line 278 of file lalinference_compute_roq_weights.py.

◆ fHigh

lalinference_compute_roq_weights.fHigh = options.fHigh

Definition at line 282 of file lalinference_compute_roq_weights.py.

◆ fHigh_index

lalinference_compute_roq_weights.fHigh_index = int(fHigh / deltaF)

Definition at line 285 of file lalinference_compute_roq_weights.py.

◆ fLow

lalinference_compute_roq_weights.fLow = options.fLow

Definition at line 290 of file lalinference_compute_roq_weights.py.

◆ fLow_index

lalinference_compute_roq_weights.fLow_index = int(fLow / deltaF)

Definition at line 296 of file lalinference_compute_roq_weights.py.

◆ psdfile

lalinference_compute_roq_weights.psdfile = np.column_stack( np.loadtxt(options.psd_file[i]) )

Definition at line 303 of file lalinference_compute_roq_weights.py.

◆ psd

lalinference_compute_roq_weights.psd = psdfile[1]

Definition at line 304 of file lalinference_compute_roq_weights.py.

◆ tcs

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) )

Definition at line 327 of file lalinference_compute_roq_weights.py.