def update_all(filename, ext_electrodes, save_folder, intr_electrode = 1, data_part = 'all'):
""" should be done each time the data is to be run from the beginning to the end again"""
# read all the data
data_all, fs = ispw.update_datafile(filename, ext_electrodes, save_folder, data_file = 'data', data_part = data_part)
data_dspl, fs_dspl = ispw.update_downsample(data_all, fs, save_folder, data_file = 'data_dspl')
data_bas, fs_bas = ispw.update_databas(data_dspl, fs_dspl, save_folder, data_file = 'data_bas') # move to baseline
# update filtered data
SPW_freq = [1.5, 500.0]
ripple_freq = [100.0, 300.0]
fast_freq = [750.0, -1]
data_spw, freq, fs_data = ispw.update_filtered(data_bas, fs_bas, save_folder, SPW_freq, 'spw_data')
data_ripple, freq, fs_ripple = ispw.update_filtered(data_bas, fs_bas, save_folder, ripple_freq, "ripple_data")
data_fast, freq, fs_fast = ispw.update_filtered(data_bas, fs_bas, save_folder, fast_freq, "fast_data")
#uspl = 1
#data_uspl_extra, fs_new_up = update_upsample(data_all, fs, save_folder, uspl = uspl, data_file = 'data_uspl_extra')
spike_idxs, spikes_ampl, fs_espikes = ispw.update_extraspikes(data_all, fs, save_folder, save_file = "ex_spikes")
spike_idxs, all_valley_to_peak, all_half_valley_width, all_half_peak_width, fs_new = ispw.update_expikes_params(data_all, fs_espikes, save_folder, spike_idxs, save_file = "ex_sparamas")
spw_idxs, spw_maxs, starts_spw, ends_spw, lengths_spw, fs_spws = ispw.update_spws(data_bas, data_fast, data_spw, fs_bas, save_folder, save_file = 'SPWs')
rip_idxs, fs_ripple = ispw.update_ripples(data_ripple, fs_ripple, save_folder, data_file = 'ripples')
ris_all, iris_no_all = ispw.update_spw_ripple(starts_spw, ends_spw, spw_idxs, save_folder, data_file = 'spw_ripple')
if fs_spws != fs_espikes:
fs_div = fs_espikes/ fs_spws # if the sampling rate is different
print np.shape(spw_idxs[0])
for i in range(len(spw_idxs)):
for g in range(len(spw_idxs[i])):
spw_idxs[i][g] = spw_idxs[i][g] * fs_div
starts_spw[i][g] = starts_spw[i][g] * fs_div
ends_spw[i][g] = ends_spw[i][g] * fs_div
spw_idxs = ispw.round_spike_idxs(spw_idxs)
starts_spw = ispw.round_spike_idxs(starts_spw)
ends_spw = ispw.round_spike_idxs(ends_spw)
fs_spws = fs_spws * fs_div
distances, min_distances, fs, max_dist = ispw.update_dist_fromSpike(starts_spw, spike_idxs, fs_spws, save_folder, data_file = 'dist_fromSPW')
if intr_electrode != -1:
data_intra, fs = ispw.update_datafile(filename, [intr_electrode], save_folder, data_file = 'intra', data_part = data_part)
data_dspl_intra, fs_new_down = ispw.update_downsample(data_intra, fs, save_folder, dspl = 2, data_file = 'data_dspl_intra')
sp_idx_first, sp_idx_all, fs = ispw.update_intraSpikes(data_intra[0], fs, save_folder, save_file = "intra_spikes", pulse_len = 500)
# compare extra and intra data
distances, min_distances, fs, max_dist = ispw.update_dist_fromSpike(sp_idx_all, spike_idxs, fs, save_folder, data_file = 'dist_fromSpike', max_dist = 3)
distances, min_distances, fs, max_dist = ispw.update_dist_fromSpike(sp_idx_first, starts_spw, fs, save_folder, data_file = 'dist_SpwfromSpike', max_dist = 10)
def update_fs(fs_1, fs_2, values = []):
# all the values will be updated to the fs_2
if fs_1 != fs_2:
fs_div = fs_2/ fs_1 # if the sampling rate is different
# the sampling rates in the two data sets are different
for val in range(len(values)):
#print np.size(spw_idxs)
for electr in range(len(values[val])):
for trace in range(len(values[val][electr])):
for individual in range(len(values[val][electr][trace])):
values[val][electr][trace][individual] = values[val][electr][trace][individual] * fs_div
values[val] = ispw.round_spike_idxs(values[val])
fs = fs_1 * fs_div
else:
fs = fs_2
return values, fs