analysis:course-w16:week4
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| Both sides previous revision Previous revision Next revision | Previous revision Next revision Both sides next revision | ||
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analysis:course-w16:week4 [2016/01/21 22:20] aacarey [Subsampling (decimating) time series data] |
analysis:course-w16:week4 [2016/02/01 11:21] course-w16 [Reconstructing a signal from sampled data (optional)] |
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| <code matlab> | <code matlab> | ||
| % sample at 12 Hz with different method | % sample at 12 Hz with different method | ||
| + | tvec1d = decimate(tvec1, dt); | ||
| signal2d = decimate(signal1,dt); | signal2d = decimate(signal1,dt); | ||
| Line 182: | Line 183: | ||
| <code matlab> | <code matlab> | ||
| xl = [1 1.04]; | xl = [1 1.04]; | ||
| - | linkaxes('x','ax1',ax2); | + | linkaxes([ax1, ax2], 'x'); |
| set(ax1,'XLim',xl); % see what I did there?) | set(ax1,'XLim',xl); % see what I did there?) | ||
| </code> | </code> | ||
| Line 208: | Line 209: | ||
| ==== Detailed examination of Neuralynx time series data ==== | ==== Detailed examination of Neuralynx time series data ==== | ||
| - | This section will look in some detail at how raw time series data is stored by the Neuralynx system. Even if you do not use this system in your own work, the lessions that can be learned from looking at what can go wrong at the raw data level already are universal! | + | This section will look in some detail at how raw time series data is stored by the Neuralynx system. Even if you do not use this system in your own work, the lessons that can be learned from looking at what can go wrong at the raw data level already are universal! |
| To get into the guts of actual Neuralynx data, we will not use the sanitized wrapper provided by ''LoadCSC()'' but instead use the loading function provided by Neuralynx. Using cell mode in a sandbox file as usual, ''cd'' into the ''R016-2012-10-08'' data folder you downloaded previously in Week 1. Then deploy the Neuralynx loader: | To get into the guts of actual Neuralynx data, we will not use the sanitized wrapper provided by ''LoadCSC()'' but instead use the loading function provided by Neuralynx. Using cell mode in a sandbox file as usual, ''cd'' into the ''R016-2012-10-08'' data folder you downloaded previously in Week 1. Then deploy the Neuralynx loader: | ||
| Line 360: | Line 361: | ||
| ★ If you implemented your own file loader(s) back in Module 2, implement checks for missing samples and possible sampling frequency misalignments. | ★ If you implemented your own file loader(s) back in Module 2, implement checks for missing samples and possible sampling frequency misalignments. | ||
| + | |||
| + | ★ Important! If you have your own idea of something you'd like to accomplish in this course, even if is isn't listed as an official challenge, ask me and we can make it count as one. What you do in this course should be as relevant as possible to your work! | ||
analysis/course-w16/week4.txt · Last modified: 2018/07/07 10:19 (external edit)
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