plotind = [1, 3, 5, 7][i + 2 * j]
ax = plt.subplot(4, 2, plotind)
ax.plot(t, fr, 'k', linewidth=.5)
plf.spineless(ax)
if cond == 'M':
plf.drawonoff(ax, preframedur, stimdur, h=.1)
plf.subplottext(['A', 'B'][j], ax, x=-0.1)
elif cond != 'M' and j == 0:
scalebars.add_scalebar(
ax,
matchx=False,
sizex=.5,
labelx='500 ms',
matchy=False,
sizey=30,
labely='30 Hz',
# labely=fr'{dist_set} $\upmu$m',
hidey=False,
barwidth=1.2,
loc='upper right',
sep=2,
pad=0)
for pos in [2, 3, 5, 6]:
ax.axvline(pos,
color='k',
alpha=.5,
linestyle='dashed',
linewidth=1)
ax.set_ylabel(cond)
ax.set_xticks([])
ax.set_yticks([])
def FORMAT_FIG(fig=None,
ax=None,
remove_top=True,
remove_bottom=False,
remove_right=True,
remove_left=False,
adjust_left=settings.FIG_ADJUST_LEFT,
adjust_top=settings.FIG_ADJUST_TOP,
scalebar=None):
"""
:param fig:
:param ax:
:param remove_top:
:param remove_bottom:
:param remove_right:
:param remove_left:
:param adjust_left:
:param adjust_top:
:param scalebar:
:type ax: np.ndarray or plt.Axes
:type scalebar: dict or bool
"""
if type(ax) == list or type(ax) == np.ndarray:
for sub_ax in ax:
FORMAT_FIG(fig,
sub_ax,
remove_top=remove_top,
remove_bottom=remove_bottom,
remove_right=remove_right,
remove_left=remove_left,
adjust_left=adjust_left,
adjust_top=adjust_top)
else:
if scalebar is not None:
from scalebars import add_scalebar
if type(scalebar) is dict:
sb = add_scalebar(ax, **scalebar)
else:
sb = add_scalebar(ax)
elif ax is not None:
if remove_top:
ax.spines['top'].set_visible(False)
if remove_right:
ax.spines['right'].set_visible(False)
if remove_bottom:
ax.spines['bottom'].set_visible(False)
x_axis = ax.axes.get_xaxis()
x_axis.set_visible(False)
if remove_left:
ax.spines['left'].set_visible(False)
y_axis = ax.axes.get_yaxis()
y_axis.set_visible(False)
if fig is not None:
fig.tight_layout()
# tight_layout doesn't take row labels into account. We'll need
# to make some room. These numbers are manually tweaked.
# You could automatically calculate them, but it's a pain.
if adjust_left:
fig.subplots_adjust(left=adjust_left)
if adjust_top:
fig.subplots_adjust(top=adjust_top)
colors.seaborn.set_context('paper',
font_scale=3.0,
rc={"lines.linewidth": 1.5})
colors.seaborn.set_style('whitegrid', {"axes.linewidth": 1.5})
lw = 1.5
fig = pl.figure(figsize=[16, 10])
fig.set_tight_layout(True)
ax0 = fig.add_subplot(1, 1, 1)
scalebars.add_scalebar(ax0,
matchx=False,
matchy=False,
hidex=False,
hidey=False,
size=3,
label="3 Hz",
horizontal=False)
x = np.arange(0, 30, 0.001 * step_size)
collection = collections.BrokenBarHCollection.span_where(
x,
ymin=26.5,
ymax=29.5,
where=switching > 0,
facecolor=colors.colors[0],
alpha=1.0)
ax0.add_collection(collection)
collection = collections.BrokenBarHCollection.span_where(
checkercolors = ['black', 'orange']
with warnings.catch_warnings():
warnings.filterwarnings('ignore', category=UserWarning)
warnings.filterwarnings('ignore', '.*invalid value encountered*.')
ax1.contour(Y, X, Zm, [inner_b, outer_b], linewidths=.5,
cmap=plf.RFcolormap(checkercolors))
barsize_set_checker = 100 # micrometers
checker_scalebarsize = barsize_set_checker/(stx_h*px_size)
scalebars.add_scalebar(ax1,
matchx=False, sizex=checker_scalebarsize,
labelx=f'{barsize_set_checker} µm',
barwidth=1.2,
loc='lower right',
sep=3,
pad=.5)
with warnings.catch_warnings():
warnings.filterwarnings('ignore',
'.*invalid value encountered in*.',
RuntimeWarning)
center_mask = np.logical_not(Zm < inner_b)
center_mask_3d = np.broadcast_arrays(sta,
center_mask[..., None])[1]
surround_mask = np.logical_not(np.logical_and(Zm > inner_b,
Zm < outer_b))
surround_mask_3d = np.broadcast_arrays(sta,
surround_mask[..., None])[1]
for n in range(80, 120, 4):
plt.plot(np.arange(pots.shape[1]) * 0.0025,
pots[n, :].T / scale - (n - 100) * 100.,
color='black')
plt.plot(np.arange(pots.shape[1]) * 0.0025,
pots[100, :].T / scale,
color='black',
lw=lw)
plt.xlim(1.4, 1.9)
plt.axis('off')
add_scalebar(ax1,
sizex=.2,
sizey=0.02e6 / scale,
matchx=False,
matchy=False,
labelx='0.2 ms',
labely='20 $\mu$V',
loc=8,
bbox_to_anchor=(170.5, 170.5))
plt.axes([4 * axes_w, axes_h, axes_ws, axes_hs],
sharey=ax1) #plt.subplot(2,8,2*order[n_p]+1,sharey=ax1)
for n in range(180, 220, 4):
plt.plot(np.arange(pots.shape[1]) * 0.0025,
pots[n, :].T / scale - (n - 200) * 100.,
color='black')
plt.plot(np.arange(pots.shape[1]) * 0.0025,
pots[200, :].T / scale,
color='black',
lw=lw)