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@@ -69,14 +69,27 @@ Download the latest release as a zip file by clicking on *Releases* on the main
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## Repository structure
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-### Directory datasets
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-Contains the two data sets `i140703-001` and `l101210-001`. Original data files are provided in the Blackrock file format (.nev, .ns2, .ns5, .ns6, .ccf), e.g., `i140703-001.nev`, `i140703-001.ns6`,.... The files `i140703-001-03.nev` and `l101210-001-02.nev` contain offline spike sorted data for both datasets as opposed to the original recordings `i140703-001.nev` and `l101210-001.nev` which contain the same spikes, but unreliable sorting that should not be used. The files `i140703-001.odml` and `l101210-001.odml` contain extensive metadata describing the datasets in the odML format. The Excel files `i140703-001.xls` and `l101210-001.xls` contain the same information as in the odML for easy reading and browsing, however, they are not used by the loading routines. The odml.xsl is an XML schema that is required for viewing the odML files with a web browser.
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+### Directory datasets_blackrock
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+Contains the two original data sets `i140703-001` and `l101210-001`. Original data files are provided in the Blackrock file format (.nev, .ns2, .ns5, .ns6, .ccf), e.g., `i140703-001.nev`, `i140703-001.ns6`,.... The files `i140703-001-03.nev` and `l101210-001-02.nev` contain offline spike sorted data for both datasets as opposed to the original recordings `i140703-001.nev` and `l101210-001.nev` which contain the same spikes, but unreliable sorting that should not be used. The files `i140703-001.odml` and `l101210-001.odml` contain extensive metadata describing the datasets in the odML format. The Excel files `i140703-001.xls` and `l101210-001.xls` contain the same information as in the odML for easy reading and browsing, however, they are not used by the loading routines. The file `odml.xsl` is an XML schema that is required for viewing the odML files with a web browser. These datasets can be
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+
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+### Directory datasets_nix
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+Contains a ready to use version data sets `i140703-001` and `l101210-001` in the Nix data format using a Neo structure. Datasets can be loaded via the Neo command
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+```
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+import neo
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+with neo.NixIO(nix_filename, mode='ro') as io:
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+ block = io.read_block()
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+```
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+The resulting Neo objects are fully annotated and processed, similar to what the custom loading code in the `code` subdirectory will do.
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+
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+In addition, `l101210-001.nix` will contain a downsampled version of the raw 30Khz data (i.e., the LFP) that is comparable to the online (hardware) downsampled ns2 LFP data that is supplied with `i140703-001`. Here, a 4th order, 250 Hz low pass Butterworth filter was applied using phase preservation and SOS, following a 30-fold downsampling. The structure of both files therefore becomes nearly identical.
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+
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+The code to produce the Nix files from the source files in the dataset directory is given in `convert_to_nix.py` in the `code` subdirectory.
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### Directory datasets_matlab
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Contains the data and metadata output of the Python loading routines in the MATLAB .mat file format. These files are provided for convenience for MATLAB users, however, note that these files are not the original data files and contain a condensed, interpreted subset of the original data. Due to size restrictions of the MATLAB file format, the files `i140703-001_lfp-spikes.mat` and `l101210-001 _lfp-spikes.mat` contain only spikes and LFP data (for monkey N), while raw data is saved separately for each channel in correspondingly named files.
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### Directory code
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-Contains example code to help in loading and analyzing the data. The file `examply.py` is a Python script that acts as a tutorial for loading and plotting data. The scripts `data_overview_1.py` and `data_overview_2.py` reproduce the plots of the data found in the publication. The files `neo_utils.py` and `odml_utils.py` contain useful utility routines to work with data and metadata. Finally, the file `example.m` contains a rudimentary MATLAB script demonstrating how to use the data provided in the .mat files.
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+Contains example code to help in loading and analyzing the data based on the original data files contained in the `datasets_blackrock` folder. The file `examply.py` is a Python script that acts as a tutorial for loading and plotting data. The scripts `data_overview_1.py` and `data_overview_2.py` reproduce the plots of the data found in the publication. The files `neo_utils.py` and `odml_utils.py` contain useful utility routines to work with data and metadata. Finally, the file `example.m` contains a rudimentary MATLAB script demonstrating how to use the data provided in the .mat files.
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To run the Python example code, download the release of this repository, and install the requirements in `code/requirements.txt`. Then, run the example via
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```
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@@ -85,6 +98,8 @@ To run the Python example code, download the release of this repository, and ins
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```
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The script produces a figure saved in three different graphics file formats.
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+Also, the file `convert_to_nix.py` contains code that produces the easy-to-use Nix files (in `datasets_nix`) from the original source data.
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+
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### Directory code/reachgraspio
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Contains the file `reachgraspio.py`, which contains the loading routine specific to the Reach-to-Grasp experiments in this repository. This loading routine merges the recorded data with metadata information from the odML files into a common Neo object. It is recommended that this loading routine is used in combination with the odML and Neo libraries (see below) to work on the data.
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