From 6d64ce71153889766a3d5ac7fcc9d2b76eb51181 Mon Sep 17 00:00:00 2001 From: Heberto Mayorquin Date: Thu, 28 Sep 2023 08:43:04 +0200 Subject: [PATCH] minor corrections to matlab documentation --- doc/how_to/load_matlab_data.rst | 15 ++++++++------- 1 file changed, 8 insertions(+), 7 deletions(-) diff --git a/doc/how_to/load_matlab_data.rst b/doc/how_to/load_matlab_data.rst index aaca718096..e12d83810a 100644 --- a/doc/how_to/load_matlab_data.rst +++ b/doc/how_to/load_matlab_data.rst @@ -30,7 +30,7 @@ Here, we present a MATLAB code that creates a random dataset and writes it to a Loading Data in SpikeInterface ------------------------------ -After executing the above MATLAB code, a binary file named `your_data_as_a_binary.bin` will be created in your MATLAB directory. To load this file in Python, you'll need its full path. +After executing the above MATLAB code, a binary file named :code:`your_data_as_a_binary.bin` will be created in your MATLAB directory. To load this file in Python, you'll need its full path. Use the following Python script to load the binary data into SpikeInterface: @@ -55,7 +55,7 @@ Use the following Python script to load the binary data into SpikeInterface: # Load data using SpikeInterface recording = si.read_binary(file_path, sampling_frequency=sampling_frequency, - num_channels=num_channels, dtype=dtype) + num_channels=num_channels, dtype=dtype) # Confirm that the data was loaded correctly by comparing the data shapes and see they match the MATLAB data print(recording.get_num_frames(), recording.get_num_channels()) @@ -65,18 +65,18 @@ Follow the steps above to seamlessly import your MATLAB data into SpikeInterface Common Pitfalls & Tips ---------------------- -1. **Data Shape**: Make sure your MATLAB data matrix's first dimension is samples/time and the second is channels. If your time is in the second dimension, use `time_axis=1` in `si.read_binary()`. +1. **Data Shape**: Make sure your MATLAB data matrix's first dimension is samples/time and the second is channels. If your time is in the second dimension, use :code:`time_axis=1` in :code:`si.read_binary()`. 2. **File Path**: Always double-check the Python file path. 3. **Data Type Consistency**: Ensure data types between MATLAB and Python are consistent. MATLAB's `double` is equivalent to Numpy's `float64`. 4. **Sampling Frequency**: Set the appropriate sampling frequency in Hz for SpikeInterface. -5. **Transition to Python**: Moving from MATLAB to Python can be challenging. For newcomers to Python, consider reviewing numpy's [Numpy for MATLAB Users](https://numpy.org/doc/stable/user/numpy-for-matlab-users.html) guide. +5. **Transition to Python**: Moving from MATLAB to Python can be challenging. For newcomers to Python, consider reviewing numpy's `Numpy for MATLAB Users `_ guide. Using gains and offsets for integer data ---------------------------------------- Raw data formats often store data as integer values for memory efficiency. To give these integers meaningful physical units, you can apply a gain and an offset. -In SpikeInterface, you can use the `gain_to_uV` and `offset_to_uV` parameters, since traces are handled in microvolts (uV). Both parameters can be integrated into the `read_binary` function. -If your data in MATLAB is stored as `int16`, and you know the gain and offset, you can use the following code to load the data: +In SpikeInterface, you can use the :code:`gain_to_uV` and :code:`offset_to_uV` parameters, since traces are handled in microvolts (uV). Both parameters can be integrated into the :code:`read_binary` function. +If your data in MATLAB is stored as :code:`int16`, and you know the gain and offset, you can use the following code to load the data: .. code-block:: python @@ -90,7 +90,8 @@ If your data in MATLAB is stored as `int16`, and you know the gain and offset, y num_channels=num_channels, dtype=dtype_int, gain_to_uV=gain_to_uV, offset_to_uV=offset_to_uV) - recording.get_traces(return_scaled=True) # Return traces in micro volts (uV) + recording.get_traces() # Return traces in original units [type: int] + recording.get_traces(return_scaled=True) # Return traces in micro volts (uV) [type: float] This will equip your recording object with capabilities to convert the data to float values in uV using the :code:`get_traces()` method with the :code:`return_scaled` parameter set to :code:`True`.