#%% multi-channel synthetic data
''' multi-channel synthetic data (clean) '''
s0 = np.array(pd.read_csv("data/syn_data.csv", header=None))
#fig, ax = plt.subplots(figsize=(10,8))
#ax.imshow(s1,interpolation='quadric', aspect='auto',vmax=0.2,vmin=-0.2)
s0 = s0[350:350+360, :][:, 40:101]
min_max_scaler = preprocessing.MaxAbsScaler()
s0 = min_max_scaler.fit_transform(s0)
#fig, ax = plt.subplots(figsize=(10,8))
#ax.imshow(s1,interpolation='quadric', aspect='auto')
s0fb = f.fb_pick_gather_wholetrace(s0,fb_tr_step=1,method='kmeans',w=21, c=2)
fig, ax = f.seisplot_wig(s0)
#ax.scatter(s0fb[:,0],s0fb[:,1], s=50,facecolors='none',edgecolors='b',lw=1)
#fig.savefig('fig/s1.pdf', dpi=200)
#%
''' multi-channel synthetic data (noisy) '''
np.random.seed(20180320) #20180320
s0n = s0 + np.random.randn(s0.shape[0],s0.shape[1])*0.2
f.fb_pick_wholetrace(s0n[:,14], method='kmeans', plot=True,
c=2, w=21, nlta=20, nsta=10, a=0)
#%
t = np.arange(400) * dt * 1000
cwtmatr, freqs = tf.spectrum_cwt(t,
s1[:, 13],
wavelet='morl',
widths=200,
cmap='RdBu',
colorscale=1,
contour_dvision=41,
freqmax=100,
figsize=(12, 3),
plot=True,
ymin=5,
ymax=80)
s1fb = f.fb_pick_gather_wholetrace(s1, fb_tr_step=1, method='kmeans', w=5, c=2)
fig, ax = f.seisplot_wig(s1, lw=0.8)
ax.scatter(s1fb[:, 0],
s1fb[:, 1],
s=50,
facecolors='none',
edgecolors='r',
lw=2)
ax.set_yticks(np.arange(0, nt + 1, 50))
ax.set_yticklabels(np.arange(0, nt + 1, 50) * dt)
#fig.savefig('fig/micro_fb', dpi=200)
#%% parameter defination and label generate
dt = 0.002 # time interval
freq_index = [4, 5, 6, 7, 8, 9, 11, 13, 15, 19, 26, 39, 80] #124
testsize = 0.2
seed = 20180319
channel = 1
tinc = 2 # time increment of samples, inside time window
length = int(tw / tinc)
classes = 2
cbar_binary = ListedColormap(["darkgray", "yellow"])
tr_num = 260 # trace number
#%%
Obsfb = f.fb_pick_gather_wholetrace(Obs,
fb_tr_step=10,
method='kmeans',
w=21,
c=2)
fig, ax = f.seisplot_wig(
Obs,
inc=10,
scale=30,
lw=0.2,
)
#ax.scatter(Obsfb[:,0],Obsfb[:,1], s=30,facecolors='none',edgecolors='r',lw=1)
ax.set_yticks(np.arange(0, nt + 1, 400))
ax.set_yticklabels(np.arange(0, nt + 1, 400) * dt)
ax.set_xticks(np.arange(0, 967, 100))
ax.set_xticklabels(np.arange(0, 967, 100) / 10)
#fig.savefig('fig/obs', dpi=200)