I2MC Fixation-classification algorithm

Updating release workflow (no relevant change for user from v2.2.3)

I2MC Fixation-classification algorithm

Fixed limits of yaxis for plots of the vertical eye signal in I2MC.plot.plot()

I2MC Fixation-classification algorithm

added support for numpy 1.24 and above

I2MC Fixation-classification algorithm

v2.2.1:
I2MC.plot now works with data for only a single eye

I2MC Fixation-classification algorithm

v2.2:

• endT and dur fields of fixation output are now consistent
• plot submodule no longer needs to be imported separately
• some enhancements to plot function:
  • can now set a different unit for the axis label
  • doesn't assume time starts at 0
  • can now set x and y signals min and max instead of only max

I2MC Fixation-classification algorithm

v2.1.4: fix crash in plotting function

I2MC Fixation-classification algorithm

v2.1.3: filtfilt uses a different padding length in python/scipy than matlab, adjusted padlen to match matlab

I2MC Fixation-classification algorithm

two_cluster_weighting: placement of switch weights was inconsistent with locations where downsampled data were taken from, which causes a slight misalignment for some downsample levels, and also a crash due to wrong indexing for some valid input parameters (e.g. downsample 5 for 60 Hz data and a .2 s window)

I2MC Fixation-classification algorithm

v2.1.1: fix that v2.1.0 was not pip installable

I2MC Fixation-classification algorithm

v2.1.0: now accepts pandas data frames as data input. Previous dict of arrays remains working.