print("##################### NOISELVL %i %% #####################\n" %
int(noiselevellist[i] * 100.))
for filein in rickerlist:
print(
"##################### CURRENT FILE %s #####################\n" %
filein)
PICPATH = filein[:filein.rfind("/"):] + "/" + noisefolder + "/"
FNAME = filein[filein.rfind("/"):].split('/')[1].split('.')[0]
plotname = FPATH + FNAME + 'pocs_' + 'nlvl' + str(
noiselevellist[i]) + '_linear' '.png'
plotname2 = FPATH + FNAME + 'pocs_' + 'nlvl' + str(
noiselevellist[i]) + '_mask' '.png'
if not os.path.isdir(PICPATH):
os.mkdir(PICPATH)
PATH = filein
stream = read_st(PATH)
d0 = stream2array(stream.copy(), normalize=True)
data = stream2array(stream.copy(),
normalize=True) + noiselevellist[i] * noise
srs = array2stream(data)
Qlinall = []
Qbwmaskall = []
Qtapermaskall = []
if 'original' in PICPATH:
DOMETHOD = 'denoise'
else:
DOMETHOD = 'recon'
for alpha in alphalist:
noise = np.fromfile('../data/test_datasets/randnumbers/noisearr.txt')
noise = noise.reshape(20, 300)
with open("../data/test_datasets/ricker/rickerlist.dat", 'r') as fh:
rickerlist = np.array(fh.read().split()).astype('str')
noisefoldlist = [
"no_noise"
] #,"10pct_noise", "20pct_noise", "50pct_noise", "60pct_noise", "80pct_noise"]
noiselevellist = np.array([0.]) #, 0.1, 0.2, 0.5, 0.6, 0.8])
alphalist = np.linspace(0.01, 0.9, 10)
maxiterlist = np.arange(11)[1:]
bwlist = [1, 2, 4]
taperlist = [2, 4, 5, 8, 200]
stream_org = read_st(
'/home/s_schn42/dev/FK-Toolbox/data/test_datasets/ricker/original/SR.QHD')
d0 = stream2array(stream_org.copy(), normalize=True)
peaks = np.array([[-13.95, 6.06, 20.07], [8.46648822, 8.42680793, 8.23354933]])
errors = []
FPATH = '/home/s_schn42/dev/FK-Toolbox/data/test_datasets/ricker/'
for i, noisefolder in enumerate(noisefoldlist):
print("##################### NOISELVL %i %% #####################\n" %
int(noiselevellist[i] * 100.))
for filein in rickerlist:
print(
"##################### CURRENT FILE %s #####################\n" %
filein)
PICPATH = filein[:filein.rfind("/"):] + "/" + noisefolder + "/"
FNAME = filein[filein.rfind("/"):].split('/')[1].split('.')[0]
plotname = FPATH + FNAME + 'pocs_' + 'nlvl' + str(
noiselevellist[i]) + '_linear' '.png'
