![]() ![]() On the other hand, it makes available options for importing different other file formats and go through the data. Limited functionalityĪs the name suggests, LabChart Reader is a viewing utility, so it does not integrate the functionality available in the LabChart application it is not equipped with the possibility to record new data or save it. The tool is not complicated and the installation process is a simple one, all the user has to do is follow the instructions on the screen and a few clicks later the software is available on the system. ![]() It makes working with this sort of files easier by providing access to this sort of files in order to analyze it. However, I couldn’t find the file.LabChart Reader is a utility that can help users view LabChart data files without the need of the full-blown application. adicht file using SDKį = adi.read_file(r'C:\Users\Mehmet\Desktop\scz_56e.adicht')ĮcogData = np.array()Īnd output: runfile('C:/Users/Mehmet/.spyder-p圓/untitled0.py', wdir='C:/Users/Mehmet/.spyder-p圓')Ĭreating RawArray with float64 data, n_channels=3, n_times=584785 # Converting the ecog data to NumPy array from. Hi, I rearranged the codes as follows: import mne # Specifying the onset times and duration of each trial, and labelling them with strings and classification codes (left, right) (1, -1)Įvent_on = np.array()ĭuration=,Įvent_desc=ĭesc_codes= # Creating an array of (number_of_channels, number_of_samples) which looks like (2, 286749) # Scaling the values appropriately to be interpreted by the CSP (SDK always returns incorrect units) adicht file using SDKį = adi.read_file(r'C:\Users\jkill\Desktop\session3_16.adicht') # Converting the EEG data to NumPy array from. Info = mne.create_info(ch_names, ch_types=ch_types, sfreq=sampling_freq) Ive already spent 2 months learning everything I need to know about BCI, EEG, signal processing and classification, Im confident about it all, but if this doesnt work out, ill be at a dead end, with too little time till my submission to start a new project from scratch.Īny help would be greatly appreicated, and im happy to provide any further details So im not sure where to go from here, I need to find a way to convert these two Arrays to a single one, or find another way to get the. When i try to concatenate these arrays into one, i get the following error : However my EEG data is in two seperate arrays. Simulated_raw = mne.io.RawArray(data, info) When matplot’ing the data, it looks like this :Īs the data is already in array format, I figured i could just assign it straight to the data variable in So although the data I have is already an array, I attempted this In the turorial, they build the array using np.array : Printing the Array looks like this, the NumPy shape is (14850,) I am a new user, cannot embed more than 3 images or share more than 5 links, so apologies for the broken imgur links, Id advise tpying the imgur part, and copying the rest Here are as much details as I can think to give, hopefully somebody can spot a fault or suggest a possible solution, any help would be greatly appreciated I hope that I am just doing something wrong, although I fear that the format of the numpy array from the SDK just wont be interpretable by MNE. adicht file so i could figure out interfacing it with MNE, dont worry about how wrong they look, the matplot representation is ‘correct’, as in it was how they appeared on the Labchart software. These signals were taken very quickly as I just needed to get an. When using matplotlib on the array straight from the SDK it looks like this : Converting that array to simulated raw data 542×571 3.22 KB ![]()
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