# Extracting EEG segments from an MNE Raw objects such that the time frames are preserved **URL:** \ **Category:** Support & Discussions\ **Tags:** preprocessing, eeg, epochs\ **Created:** [October 21, 2022, 7:00pm UTC](https://mne.discourse.group/t/extracting-eeg-segments-from-an-mne-raw-objects-such-that-the-time-frames-are-preserved/5782 "2022-10-21T19:00:40Z")\ **Posts on this page:** 6\ **Page:** 1
**Author:** ![SC\_1234](https://avatars.discourse-cdn.com/v4/letter/s/b5e925/32.png) [@SC\_1234](https://mne.discourse.group/u/SC_1234)\ **Post date:** [October 21, 2022, 7:00pm UTC](https://mne.discourse.group/t/extracting-eeg-segments-from-an-mne-raw-objects-such-that-the-time-frames-are-preserved/5782/1 "2022-10-21T19:00:40Z")
I have an MNE raw EEG object from which I would like to extract segments given by start time and end time points that are in a csv file that looks like this: rem\_df: ```python Sleep Stage start end SLEEP-REM 4770.0 5280.0 SLEEP-REM 5310.0 5760.0 SLEEP-REM 10620.0 12270.0 SLEEP-REM 16440.0 17010.0 SLEEP-REM 17040.0 17670.0 SLEEP-REM 21390.0 21630.0 ``` I just want the REM segments such that the times are preserved exactly as they are. I tried the following: ```python rem_raw = raw.copy().crop(tmin=rem_df.iloc[0,1], tmax=rem_df.iloc[0,2]) #first rem epoch for i in range(1,len(rem_df)): t_start = rem_df.iloc[i,1] #iterating over start t_end = rem_df.iloc[i,2] #iterating over end rem_raw.append(raw.copy().crop(tmin=t_start, tmax=t_end)) ``` This does extract the REM stages for me, but the problem in appending this way is that it completely restarts the timepoints from t = 0 and has a continuous data structure, while I want a discontinuous structure. Is there a way to store all of this in discontinuous epochs? - MNE version: Version 1.2.1 - operating system: macOS ---
**Author:** ![drammock](https://yyz2.discourse-cdn.com/free1/user_avatar/mne.discourse.group/drammock/32/4_2.png) [@drammock](https://mne.discourse.group/u/drammock)\ **Post date:** [October 21, 2022, 8:14pm UTC](https://mne.discourse.group/t/extracting-eeg-segments-from-an-mne-raw-objects-such-that-the-time-frames-are-preserved/5782/2 "2022-10-21T20:14:36Z")
cropping a raw will always reset the times to start at 0. However, the offset from the original raw’s start time will be preserved in the attribute `raw.first_time`, so the info is still recoverable _as long as you don’t concatenate the segments into one Raw object_. ```python import os import mne sample_data_folder = mne.datasets.sample.data_path() sample_data_raw_file = os.path.join(sample_data_folder, 'MEG', 'sample', 'sample_audvis_raw.fif') raw = mne.io.read_raw_fif(sample_data_raw_file, verbose=False, preload=True) raws = list() for tmin, tmax in rem_df[['start', 'end']].itertuples(index=False, name=None): this_raw = raw.copy().crop(tmin, tmax) raws.append(this_raw) assert tmin == this_raw.first_time - raw.first_time ``` ---
**Author:** ![SC\_1234](https://avatars.discourse-cdn.com/v4/letter/s/b5e925/32.png) [@SC\_1234](https://mne.discourse.group/u/SC_1234)\ **Post date:** [October 22, 2022, 5:00pm UTC](https://mne.discourse.group/t/extracting-eeg-segments-from-an-mne-raw-objects-such-that-the-time-frames-are-preserved/5782/3 "2022-10-22T17:00:44Z")
This does give me a list of raw objects, but isn’t there a way to preserve the original time points? This code preserves epochs, but not their start and end time points. Plotting raws[1] for example, still plots from time t=0. ---
**Author:** ![drammock](https://yyz2.discourse-cdn.com/free1/user_avatar/mne.discourse.group/drammock/32/4_2.png) [@drammock](https://mne.discourse.group/u/drammock)\ **Post date:** [October 22, 2022, 8:23pm UTC](https://mne.discourse.group/t/extracting-eeg-segments-from-an-mne-raw-objects-such-that-the-time-frames-are-preserved/5782/4 "2022-10-22T20:23:09Z")
> [@SC\_1234](#): > > isn’t there a way to preserve the original time points? As I said above: > [@drammock](#): > > cropping a raw will always reset the times to start at 0. This is not something we will change; a lot of module code implicitly assumes that raw times always start at zero. Is plotting your ultimate goal here? Can you say more about exactly what kind of plot you want / what you want to accomplish? What other advice we offer depends on what you want to do. ---
**Author:** ![SC\_1234](https://avatars.discourse-cdn.com/v4/letter/s/b5e925/32.png) [@SC\_1234](https://mne.discourse.group/u/SC_1234)\ **Post date:** [October 22, 2022, 10:38pm UTC](https://mne.discourse.group/t/extracting-eeg-segments-from-an-mne-raw-objects-such-that-the-time-frames-are-preserved/5782/5 "2022-10-22T22:38:16Z")
Plotting isn’t the only goal. I wanted to have a way to revert back to the original time points. For example, if I find an anomaly on the third segment/epoch, I want to be able to specify at what time point it occurs in the original dataset. ---
**Author:** ![drammock](https://yyz2.discourse-cdn.com/free1/user_avatar/mne.discourse.group/drammock/32/4_2.png) [@drammock](https://mne.discourse.group/u/drammock)\ **Post date:** [October 22, 2022, 11:54pm UTC](https://mne.discourse.group/t/extracting-eeg-segments-from-an-mne-raw-objects-such-that-the-time-frames-are-preserved/5782/6 "2022-10-22T23:54:07Z")
You can do that by adding the value `raws[2].first_time - raw.first_time` to the apparent time of the anomaly.