spkit.mea.plot_mea_grid

spkit.mea.plot_mea_grid(X, ch_labels, fs=25000, bad_channels=[], act_spikes=[], rep_spikes=[], fill_apd=False, fill_color='C0', verbose=1, xlim=(None, None), limy=False, ylim=(None, None), figsize=(12, 9), title_style=1, show=True, title='')

Plot MEA Grid 8x8: Visualisation of EGM/Signal in MEA Grid Form

Plot MEA Grid 8x8: Visualisation of EGM/Signal in MEA Grid Form

Parameters:

X: np. array

• (nch,n) - nch = number of channels, n=number of samples of a SINGLE CYLCLE

• axis=0 is a channel.

fs:int

• sampling frequency,

ch_labels: list

• list of label of each channel.

• It is used to arrange signals in MEA grid

bad_channels: list

• list of bad channels, should be inclusive of ch_labels

• Bad channels are plotted with red color

• if passed empty list, all the channels are considered good and plotted in Blue

act_spikes: list

• list of activation spike location for each channel

• Same length as number of channels. If passed, it is used to display activation time as

• a verticle line with black color, if passed as empty, no line is plotted.

rep_spikes: list

• list of repolarisation spike location for each channel.

• Same length as number of channels. If passed, it is used to display repolarisation time as

• a verticle line with green color, if passed as empty, no line is plotted.

fill_apd: bool,

• if True, a region between activation time and repolarisation time is shaded with ‘fill_color’

fill_color: str,

• color to fill for APD

xlim: tuple (t0,t1), default = (None,None)

• x-axis limits in ms. To zoom in or plot specific duration

ylim: tuple (y0,y1), default = (None,None)

• y-axis limits. To zoom in or plot specific height

• only used if limy=True

limybool, default=False.

• if True, y-axis of all the channels are fixed to same limit

• If True, and ylim = (None, None), min and max of all the channels are computed as used same for all channels

figsize=(12,9): Figure size

title_style: int,

• if 1 : each channels has its title,

• if 2 : only plots at boundaries has index number

title: str, default =’’

• title of whole figure

show: bool, default = True,

• if True, plt.show() is executed, if false, not.

• useful if to edit some properties of figure

verbose: 0 Silent

• 1 a few details

• 2 all the computations

Returns:

None

• display: plots

See also

mea_feature_map, 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 os, requests
import spkit as sp

# Download Sample file if not done already

file_name= 'MEA_Sample_North_1000mV_1Hz.h5'

if not(os.path.exists(file_name)):
    path = 'https://spkit.github.io/data_samples/files/MEA_Sample_North_1000mV_1Hz.h5'
    req = requests.get(path)
    with open(file_name, 'wb') as f:
            f.write(req.content)

fs = 25000
stim_fhz=1
exclude_first_dur=2
dur_after_spike=500
exclude_last_cycle=True
at_range = [0,50]
dur_from_loc = 5
remove_drift = True
bad_channels_list = [15,23, 25, 27, 28, 31, 34, 36]

X,fs,ch_labels = sp.io.read_hdf(file_name,fs=fs,verbose=1)
stim_loc,_  = sp.mea.get_stim_loc(X,fs=fs,fhz=stim_fhz, plot=0,verbose=0)

XB = sp.mea.align_cycles(X,stim_loc,fs=fs, exclude_first_dur=exclude_first_dur,dur_after_spike=dur_after_spike,
                        exclude_last_cycle=exclude_last_cycle,pad=np.nan,verbose=True)

X1B = np.nanmean(XB,axis=2)

at_loc = sp.mea.activation_time_loc(X1B,fs=fs,at_range=at_range)

XE,ATloc = sp.mea.extract_egm(X1B,act_loc=at_loc,fs=fs,dur_from_loc=dur_from_loc,remove_drift=remove_drift)

sp.mea.plot_mea_grid(X1B,act_spikes=at_loc,ch_labels=ch_labels,bad_channels=bad_channels_list,
                    xlim=at_range,verbose=True,
                    figsize=(8,7),title_style=1, title='Time Trace + AT')

sp.mea.plot_mea_grid(XE,ch_labels=ch_labels,bad_channels=bad_channels_list,verbose=True,
                    figsize=(8,7),title_style=2, title='Electrograms: EGMs')

Examples using spkit.mea.plot_mea_grid

MEA: Step-wise Analysis: Example

MEA: Step-wise Analysis: Example