mne.io.read_raw_hitachi#
- mne.io.read_raw_hitachi(fname, preload=False, verbose=None)[source]#
Reader for a Hitachi fNIRS recording.
- Parameters
- fname
str
Path to the Hitachi CSV file.
- preloadbool or
str
(defaultFalse
) Preload data into memory for data manipulation and faster indexing. If True, the data will be preloaded into memory (fast, requires large amount of memory). If preload is a string, preload is the file name of a memory-mapped file which is used to store the data on the hard drive (slower, requires less memory).
- verbosebool |
str
|int
|None
Control verbosity of the logging output. If
None
, use the default verbosity level. See the logging documentation andmne.verbose()
for details. Should only be passed as a keyword argument.
- fname
- Returns
- rawinstance of RawHitachi
A Raw object containing Hitachi data.
See also
mne.io.Raw
Documentation of attribute and methods.
Notes
Hitachi does not encode their channel positions, so you will need to create a suitable mapping using
mne.channels.make_standard_montage()
ormne.channels.make_dig_montage()
like (for a 3x5/ETG-7000 example):>>> mon = mne.channels.make_standard_montage('standard_1020') >>> need = 'S1 D1 S2 D2 S3 D3 S4 D4 S5 D5 S6 D6 S7 D7 S8'.split() >>> have = 'F3 FC3 C3 CP3 P3 F5 FC5 C5 CP5 P5 F7 FT7 T7 TP7 P7'.split() >>> mon.rename_channels(dict(zip(have, need))) >>> raw.set_montage(mon)
The 3x3 (ETG-100) is laid out as two separate layouts:
S1--D1--S2 S6--D6--S7 | | | | | | D2--S3--D3 D7--S8--D8 | | | | | | S4--D4--S5 S9--D9--S10
The 3x5 (ETG-7000) is laid out as:
S1--D1--S2--D2--S3 | | | | | D3--S4--D4--S5--D5 | | | | | S6--D6--S7--D7--S8
The 4x4 (ETG-7000) is laid out as:
S1--D1--S2--D2 | | | | D3--S3--D4--S4 | | | | S5--D5--S6--D6 | | | | D7--S7--D8--S8
The 3x11 (ETG-4000) is laid out as:
S1--D1--S2--D2--S3--D3--S4--D4--S5--D5--S6 | | | | | | | | | | | D6--S7--D7--S8--D8--S9--D9--S10-D10-S11-D11 | | | | | | | | | | | S12-D12-S13-D13-S14-D14-S16-D16-S17-D17-S18
For each layout, the channels come from the (left-to-right) neighboring source-detector pairs in the first row, then between the first and second row, then the second row, etc.
New in version 0.24.
Examples using mne.io.read_raw_hitachi
#
Importing data from fNIRS devices