spkit.mea.mea_feature_map

spkit.mea.mea_feature_map(features, ch_labels, bad_channels=[], fmt='.1f', vmin=None, vmax=None, cmap='jet', label='unit', title='', figsize=None, show=False)

Displaying Feature values of MEA channels in a MEA Grid

Displaying Feature values of MEA channels in a MEA Grid

MEA 8x8 GRID

        | 21 | 31 | 41 | 51 | 61  | 71 |
    |12 | 22 | 32 | 42 | 52 | 62  | 72 | 82 |
    |13 | 23 | 33 | 43 | 53 | 63  | 73 | 83 |
    |14 | 24 | 34 | 44 | 54 | 64  | 74 | 84 |
    |15 | 25 | 35 | 45 | 55 | 65  | 75 | 85 |
    |16 | 26 | 36 | 46 | 56 | 66  | 76 | 86 |
    |17 | 27 | 37 | 47 | 57 | 67  | 77 | 87 |
        | 28 | 38 | 48 | 58 | 68  | 78 |
Parameters:
features: list/array

  • array of a feature for all the channels

  • e.g len(features) = 60

ch_labels: list

  • list of channel labels corresponding to features

  • same length as number of features

bad_channels: list

  • list of Bad channels, values should be inclusive of ch_labels

  • if passed, two matrix plots are showm, one without excluding bad channels

  • one by excluding bad channels

fmt: str,

  • precision format to show value, default = ‘.1f’, at one decimal point

(vmin, vmax): default (None, None)

  • colormap range, default set to (None, None)

cmap: default=’jet’

  • colormap,

label: str

  • label for colorbar default=’unit’

title: str,

  • title of figure default=’’,

figsize: figure size
show: bool, deafult=False

  • if true, plt.show() is executed, with show=False, properties of figure can be changed.

Returns:
FxMEA 8x8 Grid

  • Feature Matrix of feature of each channel arranged in MEA grid form

Fx_bad: MEA 8x8 Grid

  • Matrix of ones and NaN each channel arranged in MEA grid form

  • 1 if channel is good

  • np.nan if channels in BAD, from given list of bad_channels

  • Fx_bad can be used as by simply multiplying to Fx,

  • Fxb = Fx*Fx_bad

See also

plot_mea_grid, mat_list_show, mat_1_show, arrange_mea_grid

Examples

#sp.mea.plot_mea_grid
import numpy as np
import matplotlib.pyplot as plt
import spkit as sp

ch_labels = np.array([47, 48, 46, 45, 38, 37, 28, 36, 27, 17, 26, 16, 35, 25, 15, 14, 24,
    34, 13, 23, 12, 22, 33, 21, 32, 31, 44, 43, 41, 42, 52, 51, 53, 54,
    61, 62, 71, 63, 72, 82, 73, 83, 64, 74, 84, 85, 75, 65, 86, 76, 87,
    77, 66, 78, 67, 68, 55, 56, 58, 57])

bad_channels_list = [15,23, 25, 27, 28, 31, 34, 36]

features = sp.create_signal_1d(n=60,seed=1)*20

Fx, Fx_bad = sp.mea.mea_feature_map(features,ch_labels=ch_labels,bad_channels=bad_channels_list,
                                figsize=(12,4),title='features')
../../_images/spkit-mea-mea_feature_map-1.png

Examples using spkit.mea.mea_feature_map

MEA: Step-wise Analysis: Example

MEA: Step-wise Analysis: Example