Move utils to spm.utils

Author: johmedr

utils/mne2spm2mne.py examples/mne2spm2mne.pyutils/mne2spm2mne.py renamed to examples/mne2spm2mne.py

@@ -1,12 +1,13 @@
-import matplotlib.pyplot as plt 
+# MNE2MATLAB2MNE - reads in and preprocesses data using MNE, then moves to SPM to do specific preprocessing, then moves back to MNE for the rest of the analysis
+
+
+import matplotlib.pyplot as plt
 import numpy as np
 import mne
-import sys
-plt.ion()
-sys.path.insert(1, r'C:\Users\ybezsudnova\Documents\Git\spm-python\utils\spm_mne_converter.py')
+from spm import Struct, spm_opm_amm
+from spm.utils import spm_2_mne_raw, mne_raw_2_spm
 
-from spm_mne_converter import spm_2_mne_raw, mne_raw_2_spm
-from spm import *
+plt.ion()
 
 # 1. read in the data using mne
 subject = "sub-002"
@@ -17,7 +18,7 @@
 subjects_dir = data_path / "derivatives" / "freesurfer" / "subjects"
 
 raw = mne.io.read_raw_fil(opm_file, verbose="error")
-raw.crop(120, 210).load_data() 
+raw.crop(120, 210).load_data()
 
 # 2. Plot raw data using mne
 picks = mne.pick_types(raw.info, meg=True)
@@ -34,27 +35,31 @@
 set_kwargs = dict(
     ylim=(-500, 500), xlim=time_ds[[0, -1]], xlabel="Time (s)", ylabel="Amplitude (pT)"
 )
-ax.set(title="No preprocessing",**set_kwargs)
+ax.set(title="No preprocessing", **set_kwargs)
 plt.show()
 
-psd_kwargs = dict(fmax=100, n_fft=int(round(raw.info["sfreq"])*2*2))
+psd_kwargs = dict(fmax=100, n_fft=int(round(raw.info["sfreq"]) * 2 * 2))
 raw.compute_psd(**psd_kwargs).plot(dB=True, amplitude=True)
 
 # 2. Some preproceesing using mne
 raw.notch_filter(np.arange(50, 251, 50), notch_widths=4)
 raw.filter(1, 70, picks="meg")
 
-ref_mag_name = [ch['ch_name'] for ch in raw.info['chs'] if ch['kind'] == mne.io.constants.FIFF.FIFFV_REF_MEG_CH]
-raw.info['bads'] = ref_mag_name
-#raw.info['bads'].extend(['G2-A4-RAD','G2-17-TAN'])
+ref_mag_name = [
+    ch["ch_name"]
+    for ch in raw.info["chs"]
+    if ch["kind"] == mne.io.constants.FIFF.FIFFV_REF_MEG_CH
+]
+raw.info["bads"] = ref_mag_name
+# raw.info['bads'].extend(['G2-A4-RAD','G2-17-TAN'])
 
 
 # 3. MNE 2 SPM
-data = mne_raw_2_spm(raw,'D:/opm-tutorial')
+data = mne_raw_2_spm(raw, "D:/opm-tutorial")
 data
 
 # 4. SPM prossesing
-S = Struct() 
+S = Struct()
 S.D = data
 mD = spm_opm_amm(S)
 
@@ -65,7 +70,7 @@
 
 
 # 6. MNE plotting
-psd_kwargs = dict(fmax=100, n_fft=int(round(cleaned_data.info["sfreq"])*2*2))
+psd_kwargs = dict(fmax=100, n_fft=int(round(cleaned_data.info["sfreq"]) * 2 * 2))
 cleaned_data.compute_psd(**psd_kwargs).plot(dB=True, amplitude=True)
 
 
@@ -83,38 +88,41 @@
 set_kwargs = dict(
     ylim=(-500, 500), xlim=time_ds[[0, -1]], xlabel="Time (s)", ylabel="Amplitude (pT)"
 )
-ax.set(title="No preprocessing",**set_kwargs)
+ax.set(title="No preprocessing", **set_kwargs)
 plt.show()
 
 
-
 # 7. MNE epoching
-events=[]
-events = mne.find_events(cleaned_data, stim_channel ='NI-TRIG',min_duration=0.001)
-events_dict = {'trigger':3}
+events = []
+events = mne.find_events(cleaned_data, stim_channel="NI-TRIG", min_duration=0.001)
+events_dict = {"trigger": 3}
 
 cleaned_data.filter(2, 40, picks="meg")
-epochs = mne.Epochs(cleaned_data, 
-                    events, 
-                    tmin=-0.1, tmax=0.4, 
-                    event_id=events_dict,
-                    detrend = 1,
-                    baseline=[-0.05,0],
-                    preload=True)
+epochs = mne.Epochs(
+    cleaned_data,
+    events,
+    tmin=-0.1,
+    tmax=0.4,
+    event_id=events_dict,
+    detrend=1,
+    baseline=[-0.05, 0],
+    preload=True,
+)
 
 
-evoked = epochs['trigger'].average()
+evoked = epochs["trigger"].average()
 evoked.plot()
 
 
-radial_channels = [ch for ch in evoked.ch_names if ch.endswith('RAD')] # take on radial sensors
+radial_channels = [
+    ch for ch in evoked.ch_names if ch.endswith("RAD")
+]  # take on radial sensors
 evoked_radial = evoked.pick_channels(radial_channels)
 fig = evoked_radial.plot_joint()
 
 
-
-tang_channels = [ch for ch in evoked.ch_names if ch.endswith('TAN')] # take on tangatial sensors
+tang_channels = [
+    ch for ch in evoked.ch_names if ch.endswith("TAN")
+]  # take on tangatial sensors
 evoked_tang = evoked.pick_channels(tang_channels)
 evoked_tang.plot_joint()
-
-

spm/utils/__init__.py

@@ -0,0 +1,4 @@
+from .spm_mne_converter import mne_raw_2_spm, spm_2_mne_raw
+
+
+__all__ = ["mne_raw_2_spm", "spm_2_mne_raw"]