# DataFrame of EWS
df_ews = ews_dic['EWS metrics']
# DataFrame of Power spectra
df_pspec = ews_dic['Power spectrum']
print('Do bootstrapping')
#-------------------------------------
# Compute EWS using bootstrapping
#–----------------------------------
df_samples = ewstools.roll_bootstrap(series,
span=span,
roll_window=rw,
roll_offset=roll_offset,
upto=tcrit,
n_samples=n_samples,
bs_type=bs_type,
block_size=block_size)
# Execute ews_compute for each bootstrapped time-series
# List to store EWS DataFrames
list_df_ews = []
# List to store power spectra DataFrames
list_pspec = []
# Realtime values
tVals = np.array(df_samples.index.levels[0])
# Sample values
sampleVals = np.array(df_samples.index.levels[1])
#----------------------
## Compute EWS of each realisation *with bootstrapping*
#---------------------
print('\nBegin bootstrapped EWS computation\n')
# Make list of samples from each realisation
samples_list = []
for i in range(numSims):
# Compute samples for particular realisation
df_samples_temp = ewstools.roll_bootstrap(df_traj.loc[i + 1]['x'],
span=span,
roll_window=rw,
roll_offset=roll_offset,
upto=tcrit,
n_samples=n_samples,
bs_type=bs_type,
block_size=block_size)
# Add realisation number
df_samples_temp['Realisation number'] = i + 1
# Add dataframe to list
samples_list.append(df_samples_temp)
# Concatenate into a full DataFrame of sample time-series
df_samples = pd.concat(samples_list).reset_index().set_index(
['Realisation number', 'Time', 'Sample', 'Wintime'])
# Execute ews_compute for each bootstrapped time-series