def get_layout(o_dir, layout_name):
"""
**Layout functions in mne depreciated.**
Read or generate layout. Layout generated by clicking on input image.
Parameters
----------
o_dir : dir
dir in which layout is to be read or saved into
layout_name : str, default None
basename of image used as layout template. if None, "topo.lout" is used.
Returns
-------
lt : mne layout object
"""
# Layout function depreciated. Load tetrode layout
layout_path = o_dir
if layout_name is None:
layout_name = "SA5_topo.lout"
try:
lt = mne.channels.read_layout(layout_name,
path=layout_path,
scale=False)
except:
# Generate layout of tetrodes
# This code opens the image so you can click on it to designate tetrode positions
from mne.viz import ClickableImage # noqa
from mne.viz import (plot_alignment, snapshot_brain_montage,
set_3d_view)
# The click coordinates are stored as a list of tuples
template_loc = r'F:\!Imaging\LKC\SA5\SA5_Histology-07.tif' # template location
im = plt.imread(template_loc)
click = ClickableImage(im)
click.plot_clicks()
# Generate a layout from our clicks and normalize by the image
print('Generating and saving layout...')
lt = click.to_layout()
# To save if we want
lt.save(os.path.join(layout_path, layout_name))
print('Saved layout to', os.path.join(layout_path, layout_name))
# Load and display layout
lt = mne.channels.read_layout(layout_name, path=layout_path, scale=False)
x = lt.pos[:, 0] * float(im.shape[1])
y = (1 - lt.pos[:, 1]) * float(im.shape[0]) # Flip the y-position
fig, ax = plt.subplots()
ax.imshow(im)
ax.scatter(x, y, s=120, color='r')
plt.autoscale(tight=True)
ax.set_axis_off()
plt.show()
return lt
def test_clickable_image():
"""Test the ClickableImage class."""
# Gen data and create clickable image
im = np.random.randn(100, 100)
clk = ClickableImage(im)
clicks = [(12, 8), (46, 48), (10, 24)]
# Generate clicks
for click in clicks:
_fake_click(clk.fig, clk.ax, click, xform='data')
assert_allclose(np.array(clicks), np.array(clk.coords))
assert_true(len(clicks) == len(clk.coords))
# Exporting to layout
lt = clk.to_layout()
assert_true(lt.pos.shape[0] == len(clicks))
assert_allclose(lt.pos[1, 0] / lt.pos[2, 0],
clicks[1][0] / float(clicks[2][0]))
def test_clickable_image():
"""Test the ClickableImage class."""
# Gen data and create clickable image
im = np.random.RandomState(0).randn(100, 100)
clk = ClickableImage(im)
clicks = [(12, 8), (46, 48), (10, 24)]
# Generate clicks
for click in clicks:
_fake_click(clk.fig, clk.ax, click, xform='data')
assert_allclose(np.array(clicks), np.array(clk.coords))
assert (len(clicks) == len(clk.coords))
# Exporting to layout
lt = clk.to_layout()
assert (lt.pos.shape[0] == len(clicks))
assert_allclose(lt.pos[1, 0] / lt.pos[2, 0],
clicks[1][0] / float(clicks[2][0]))
clk.plot_clicks()
plt.close('all')