spkit.show_compass

spkit.show_compass(Ax_theta, Ax_bad=[], arr_agg='mean', figsize=(10, 6), all_arrow_prop={'alpha': 0.2, 'edgecolor': 'C0', 'facecolor': 'C0', 'lw': 1, 'width': 0.05, 'zorder': 10}, avg_arrow_prop={'edgecolor': 'C3', 'facecolor': 'C3', 'lw': 4, 'width': 0.045, 'zorder': 100}, title='CV')

Display Compass with Arrows and aggregated Arrow

Display Compass with Arrows and aggregated Arrow

Plot two compasses:

    1. With all the arrows of angles as provided in Ax_theta, along with averaged direction

    1. Only if Ax_bad is provided;

    With arrows excluding one indicated as bad (np.nan, NaN) in Ax_bad along with averaged direction

Parameters:
Ax_theta: 2D-array,

  • e.g. MEA Feature matrix, of Angles of directions

  • 1D-array should work as well.

  • It can include NaN (np.nan) values, which will be ignored

Ax_bad2D-array,

  • Same size array as Ax_theta, with 1 and np.nan (NaNs) value

  • 1 for good channel, NaN for bad channel

  • default = [], in which case only one plot is shown

arr_agg: str {‘mean’, ‘media’}, default=’mean’

how to aggregate angles

Returns:
Ax_theta_avgAggregated Angle, including all the values
Ax_theta_avg_bd: Aggregated Angle, excluding bad channels, indicated by NaN in Ax_bad,

if Ax_bad is provided, else same as Ax_theta_avg

See also

direction_flow_map

Notes

#TODO

References

  • wikipedia -

Examples

>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> import spkit as sp
>>> np.random.seed(2)
>>> N=8
>>> Ax_theta= np.arctan2(np.random.randn(N)+1, np.random.randn(N)-1)
>>> Ax_bad   = 1*(np.random.rand(N)>0.4).astype(float)
>>> Ax_bad[Ax_bad==0]=np.nan
>>> sp.show_compass(Ax_theta, Ax_bad,arr_agg='mean',title='D')
>>> plt.show()
../../_images/spkit-show_compass-1.png