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RichardFav / spikeGUI

Electrophysiology Analysis GUI Repository
MIT License
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Creation of Correlation Parameter Comparison/Fit Parameter functions for fixed experiments. #68

Closed RichardFav closed 4 years ago

RichardFav commented 4 years ago

These functions are to mirror that which has already been created for the freely moving experiments (namely the "AHV Correlation Comparison" and "AHV Fit Parameters" functions located in the "Freely Moving Analysis" function group).

RichardFav commented 4 years ago

These functions have been created and are now available within the program, and are named "Correlation Comparison (Fixed)" and "Correlation Fit Parameters (Fixed)" available under the "Angular Head Velocity Analysis" function group.

Note that the two freely moving analysis functions named in the issue above have also been moved to the "Angular Head Velocity Analysis" function group and (for consistency purposes) are also renamed as:

These new functions are available on Git so a pull request will need to be made on Subiculum to apply these changes.

Sepidak commented 4 years ago

add an option to combine CW and CCW data points, so that they are all shown on the same plot and the stats will also be done on all together.

RichardFav commented 4 years ago

The option to combine metrics has been added to the function "Correlation Comparison (Fixed)", and is possible by using the plotting parameter "Combine Metrics Between Phases". This is now available on Subiculum.

Sepidak commented 4 years ago

Need to also implement a measure for residuals to use instead of/in addition to the Pearson's correlation. Either the standard error or the sum of squared residuals.

RichardFav commented 4 years ago

This has been implemented within the function "Correlation Comparison (Fixed)", and can be accessed via the "Metric Type" plotting parameter using the value "Fit Error".

Note that there are 3 different types of fit errors that can be calculated (accessed by setting the value of the calculation parameter "Error Calculation Type"):

  1. Covariance - Value is calculated using the "curve_fit" function. Additionally, the fit function assumes 0 intercept value (i.e, y = mx only)
  2. Sum-of-Squares - Value is calculated using the "polyfit" function (fit assumes that y = mx + c)
  3. Standard Error - Value is calculated using the "linregress" function (fit also assumes that y = mx + c)