def __init__(self):
# number of frequency bins
frequencies=int(nts/2) + 1
# Space-frequency matrix
self.cfreq=vsip.matrix(complex, sensors, frequencies)
# Space-time matrix
self.rfreq=vsip.matrix(float, sensors, frequencies)
# K-omega output matrix initialized
self.gram=vsip.matrix(float, sensors, frequencies, 0)
# FFT object along time domain
self.rcfftm=fftm(float, fwd, sensors, nts, 1, vsip.row, 0, alg_hint.time)
# FFT object along spatial domain
self.ccfftm=fftm(complex, fwd, sensors, frequencies, 1, vsip.col, 0, alg_hint.time)
# Window taper object around time axis
self.ts_taper=window.hanning(float, nts)
# Window taper object around spatial axis
self.array_taper=window.hanning(float, sensors)
#
# This file is part of OpenVSIP. It is made available under the
# license contained in the accompanying LICENSE.BSD file.
from vsip import vector
from vsip import matrix
from vsip.selgen.generation import ramp
from vsip.math import elementwise as elm
from vsip.signal import *
from vsip.signal.fftm import *
import numpy as np
#from matplotlib.pyplot import *
v1 = ramp(float, 0, 0.1, 1024)
v1 = elm.sin(v1)
m1 = matrix(float, 16, 1024)
for r in range(16):
m1[r,:] = ramp(float, r, 0.1, 1024)
fwd_fftm = fftm(float, fwd, 16, 1024, 1., 0, 1, alg_hint.time)
inv_fftm = fftm(float, inv, 16, 1024, 1./1024, 0, 1, alg_hint.time)
m2 = matrix(complex, 16, 513)
fwd_fftm(m1, m2)
m3 = matrix(float, 16, 1024)
inv_fftm(m2, m3)
assert np.isclose(m1, m3).all()
#plot(v1)
#plot(v3)
#show()
