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'