columns=['phi_0', 'ssn', 'log_ssn_fix', alpha_type],
index=df_pam_ssn.loc['2006-08-01':'2014-01-01', :].index)
df_ams = pd.DataFrame(np.vstack((ams_phi, ams_ssn, ams_log_ssn, ams_alpha)).T,
columns=['phi_0', 'ssn', 'log_ssn_fix', alpha_type],
index=df_ams_ssn.loc['2011-06-01':'2017-03-01', :].index)
print(df_pam)
"""
A
"""
# print(list(df_pam.index))
pam_x = (Time(list(df_pam.index), format='iso').jd1 -
Time('2012-06-01', format='iso').jd1) / 30
ams_x = (Time(list(df_ams.index), format='iso').jd1 -
Time('2012-06-01', format='iso').jd1) / 30
pam_A = np.array(
[format(-FUNC.sigmoid(pam_x)[i], '.3f') for i in range(len(pam_x))],
dtype='float')
ams_A = np.array(
[format(-FUNC.sigmoid(ams_x)[i], '.3f') for i in range(len(ams_x))],
dtype='float')
df_pam['A'] = pam_A
df_ams['A'] = ams_A
# df_pam.to_csv(r'./test.csv')
# df_ams.plot(y='A')
# plt.show()
print(df_pam)
print(df_ams)
# df_pam[alpha_type] = pam_alpha
# df_ams[alpha_type] = ams_alpha
#
# df_pam.to_csv(r'./output/pam_info.csv')
