def matching_pursuit(samp):
"""
Run matching pursuit, with time shifted signals in the dictionary.
Abandoned because too slow, not fully tested.
"""
R = samp.get_target()
ret = []
maxinn = 1
while maxinn > 0:
print("iter: " + str(len(ret)))
maxinn = 0
maxres = (-1, -1, -1)
for i, s in enumerate(samp.components):
print("file: " + str(i))
for offset in range(len(R)):
f = np.pad(samp.comp_to_signal(i), (offset, 0), 'constant')
f, R = sample.pad(f, R)
a = np.inner(R, f) # np.inner uses dot product
if (np.abs(a) < maxinn):
continue
maxinn = a
maxres = (i, offset, a)
g = np.pad(samp.comp_to_signal(maxres[0]), (maxres[1], 0), 'constant')
g = g * maxres[2]
g, R = sample.pad(g, R)
R = R - g
R = np.trim_zeros(R, 'b')
ret.append(maxres)
return AlgResult(samp, ret)
def matching_pursuit_mp(samp):
"""
Run matching pursuit, with time shifted signals in the dictionary.
Abandoned because too slow, not fully tested.
"""
R = samp.get_target()
ret = []
maxinn = 1
while maxinn > 0:
print("iter: " + str(len(ret)))
maxinn = 0
maxres = (-1, -1, -1)
mp_args = [(R, samp, i) for i in range(len(samp.components))]
p = mp.Pool(config.POOL_SIZE)
processresults = p.imap(_matching_pusuit_mp_in, mp_args)
maxres = max(processresults, key=lambda x: x[2])
g = np.pad(samp.comp_to_signal(maxres[0]), (maxres[1], 0), 'constant')
g = g * maxres[2]
R, g = sample.pad(R, g)
R = R - g
R = np.trim_zeros(R, 'b')
ret.append(maxres)
return AlgResult(samp, ret)
def to_signal(self):
"""Use the components and result from to create the result signal."""
signal = np.ndarray((0))
for c in self.a_result:
s = np.pad(self.comp_to_signal(c[0]), (c[1], 0), 'constant') * c[2]
signal, s = sample.pad(
signal,
s,
)
signal += s
return signal
def MSE_L2_time(results):
"""Mean Square Error where error is the L2 norm."""
total = 0
res_string = "\n\nSingle Sample L2 Norms:\n"
for r in results:
rsignal, tsignal = sample.pad(r.to_signal(), r.get_target())
single = np.linalg.norm(tsignal - rsignal)
res_string += r.s_name + ": " + single.__str__() + "\n"
total += single**2
total /= len(results)
res_string = "total: " + total.__str__() + res_string
return EvalResult("MSE_L2_time", res_string)
def matching_pursuit2(samp):
"""
Run matching pursuit, with time shifted signals in the dictionary.
Imagine if I didn't forget about the convolution theorem
and cross correlation when it is overly relevent.
Normal test stop condition doesn't currently work
because of floating point errors;
need new one, but this is good enough to test for time
"""
if config.VERBOSE:
print("Matching Pursuit on " + samp.s_name)
if config.PLOT:
plotfile = open(
config.RESULTS_DIR + "matching_pursuit2-" + samp.s_name + ".txt",
'w')
R = samp.get_target()
ret = []
maxinn = 1
itt = 1
while np.abs(maxinn) > 0 and itt <= config.N_SIGNALS:
if config.VERBOSE:
print("\tChoosing Signal " + str(itt))
maxinn = 0
maxres = (-1, -1, -1)
for i, s in enumerate(samp.components):
f = samp.get_signal(s)
# convolving with 2nd arg reversed is cross correlation
# cross correlation essentially sliding dot product
inners = scipy.signal.fftconvolve(R, f[::-1], 'full')[f.size - 1:]
offset = np.argmax(np.abs(inners))
a = inners[offset]
if np.abs(a) < np.abs(maxinn):
continue
maxinn = a
maxres = (i, offset, a)
g = np.pad(samp.comp_to_signal(maxres[0]), (maxres[1], 0), 'constant')
g = g * maxres[2]
R, g = sample.pad(R, g)
R = R - g
R = np.trim_zeros(R, 'b')
if config.PLOT:
plotfile.write(str(1 - np.linalg.norm(R)) + "\n")
ret.append(maxres)
itt += 1
return AlgResult(samp, ret)
def _matching_pusuit_mp_in(args):
target, samp, i = args
maxinn = 0
sig = samp.comp_to_signal(i)
for offset in range(len(target)):
f = np.pad(sig, (offset, 0), 'constant')
f, R = sample.pad(f, target)
a = np.inner(R, f) # np.inner uses dot product
if (np.abs(a) < maxinn):
continue
maxinn = a
maxres = (i, offset, a)
return maxres
def matching_pursuit2_mp(samp):
"""
Run matching pursuit, with time shifted signals in the dictionary.
Convolution again, but this time multiprocess because I am impatient.
"""
if config.VERBOSE:
print("Matching Pursuit on " + samp.s_name)
if config.PLOT:
plotfile = open(
config.RESULTS_DIR + "matching_pursuit2-" + samp.s_name + ".txt",
'w')
R = samp.get_target()
ret = []
maxinn = 1
itt = 1
p = mp.Pool(config.POOL_SIZE)
while np.abs(maxinn) > 0 and itt <= config.N_SIGNALS:
if config.VERBOSE:
print("\tChoosing Signal " + str(itt))
maxinn = 0
mp_args = [(R, samp, i) for i in range(len(samp.components))]
processresults = p.starmap(_matching_pusuit2_mp_in, mp_args)
maxres = max(processresults, key=lambda x: np.abs(x[2]))
g = np.pad(samp.comp_to_signal(maxres[0]), (maxres[1], 0), 'constant')
g = g * maxres[2]
R, g = sample.pad(R, g)
R = R - g
R = np.trim_zeros(R, 'b')
if config.PLOT:
plotfile.write(str(1 - np.linalg.norm(R)) + "\n")
ret.append(maxres)
itt += 1
maxinn = maxres[2]
return AlgResult(samp, ret)