from matplotlib import pyplot as plt
fig = plt.figure()
n = 8
n2 = int(n/2)
fig, axes = plt.subplots(n2,2, figsize=(30, 15), sharex=True)

k=0
for ch in data.keys():
　ii=n
　k = int(ii / n2)
　i = ii % n2

　axes[i, k].plot(data[ch], label=labels[ii], color="green")
　axes[i, k].legend(loc="upper right")

　#q_1p = np.quantile(data[ch], 0.01)
　#q_99p = np.quantile(data[ch], 0.99)
　q_1p, q_99p = np.percentile(data[ch], q=[1, 99])
　axes[i, k].axhline(y=q_1p, color="m", alpha=0.7, linestyle='--')
　axes[i, k].axhline(y=q_99p, color="m", alpha=0.7, linestyle='--')

axes[0, 0].set_title("time from %s" % time1)
axes[0, 1].set_title("channel = %s" % ch_out)

fig.savefig("./fig/hoge.png")

from matplotlib import pyplot as plt

fig, axes = plt.subplots(2,1, figsize=(10, 12), sharex=True)
ax1 = plt.subplot(2, 1, 1)
ax1.plot(data_freq, data_TF, color="skyblue", marker="o", linestyle="None", label="aaaaa")
ax1.set_xscale('log')
ax1.set_yscale('log')
ax1.set_ylabel('magnitude')
ax1.set_xlim(fmin, fmax)
ax1.set_title("title daup")
ax1.legend(loc="upper right")

ax2 = plt.subplot(2, 1, 2)
ax2.plot(data1, data2, label="coherence (original)")
ax2.set_xscale('log')
ax2.set_xlabel('frequency [Hz]')
ax2.set_ylabel('coherence')
ax2.set_xlim(fmin, fmax)
ax2.legend(loc="lower right")
plt.savefig(fname)
plt.show()