Try to get speedups with mpl by using blitting, linecollection, single line, etc.

mplline.py

import time
import mne
import numpy as np
import matplotlib.pyplot as plt

raw = mne.io.read_raw_fif(
    mne.datasets.sample.data_path() + '/MEG/sample/sample_audvis_raw.fif')
data, times = raw[:, :]
n_points = 1000
norms = np.std(data, axis=-1, keepdims=True)
data -= np.mean(data, axis=1, keepdims=True)
norms[norms == 0] = 1
data /= norms
data += np.arange(len(data))[:, np.newaxis]

fig, ax = plt.subplots(figsize=(8, 6), dpi=100)
x = times[:n_points]
ys = data[:, :n_points]

# Collection (same speed)
# from matplotlib.collections import LineCollection
# line_segments = LineCollection([np.column_stack([x, y]) for y in ys])
# line_segments.set_array(x)
# ax.add_collection(line_segments)
# Plot

def _nan_ravel(x, ys):
    x = np.tile(np.pad(
        x, (0, 1), 'constant', constant_values=np.nan), ys.shape[0])
    ys = np.pad(
        ys, ((0, 0), (0, 1)), 'constant', constant_values=np.nan).ravel()
    return x, ys


x, ys = _nan_ravel(x, ys)
h = ax.plot(x, ys.T, color='k', lw=0.5, alpha=0.5, antialiased=True)[0]
ax.set(xlim=times[[0, n_points - 1]], ylim=[-0.5, len(data) + 0.5])


class Updater():
    def __init__(self):
        self.offset = 0

    def __call__(self):
        sl = slice(self.offset, self.offset + n_points)
        t = times[sl]
        x, ys = _nan_ravel(times[sl], data[:, sl])
        h.set_xdata(x)
        h.set_ydata(ys.T)
        self.offset += 10
        if self.offset > len(times) - n_points:
            self.offset = 0
        ax.set(xlim=t[[0, -2]])
        fig.canvas.draw_idle()
        t0 = time.time()
        fig.canvas.flush_events()
        print(time.time() - t0)


up = Updater()
timer = fig.canvas.new_timer(interval=int(round(1000 / 60)))
fig.canvas.mpl_connect('close_event', lambda ev: timer.stop())
timer.add_callback(up)
timer.start()