GODDAMMIT

f1_noise = np.load("noise-lo-1269.6_04-29-2014_132304.npz")
f1 = np.load("lo-1269.6_04-29-2014_132518.npz")
f2_noise = np.load("noise-lo-1273.6_04-29-2014_132217.npz")
f2 = np.load("lo-1273.6_04-29-2014_132151.npz")
f1["spec"]
plot(f1["spec"])
plot(f1_noise["spec"])
plot(f2_noise["spec"])
plot(f2["spec"])
np.mean(f2_noise["spec"])/np.mean(f2["spec])
np.mean(f2_noise["spec"])/np.mean(f2["spec"])
1/(np.mean(f2_noise["spec"])/np.mean(f2["spec"])-1)*100
100*np.mean(f2_noise["spec"])/np.mean(f2["spec"])-100
1/(np.mean(f2_noise["spec"])/np.mean(f2["spec"])-1)*100
np.mean(f2["spec"])/np.mean(f1["spec"])
np.mean(f2["spec"])/np.mean(f1["spec"])
(f2_noise["spec"] - f2["spec"]) / (f1_noise["spec"] - f1["spec"])
g2g1 = _
figure()
plot(f2["spec"])
plot(g2g1 * f1["spec"])
plot(np.mean(g2g1) * f1["spec"])
plot(f1["spec"]/np.mean(g2g1))
%history