def extract_amplitudes(index, r_min=0.7):
t, rec, rec_filt = preprocess(index)
i = 0
amp = []
for rec1_, rec_filt1_, rec2_, rec_filt2_ in zip(rec[0], rec_filt[0],
rec[1], rec_filt[1]):
# using filtered signal to extract slope
ipk, _ = find_epsp_peak(t, rec_filt1_)
# slope
_, r, _, _ = epsp_slope(t, rec1_, ipk, yf=rec_filt1_, return_pos=True)
if abs(r) < r_min:
i += 1
logger.warning("discarded new frame ({}), r={:.4f}, ".format(i, r))
else:
amp.append(rec1_[ipk])
# using filtered signal to extract slope
ipk, _ = find_epsp_peak(t, rec_filt2_)
# slope
_, r, _, _ = epsp_slope(t, rec2_, ipk, yf=rec_filt2_, return_pos=True)
if abs(r) < r_min:
i += 1
logger.warning("discarded new frame ({}), r={:.4f}, ".format(i, r))
else:
amp.append(rec2_[ipk])
return amp
def ppr(index, r_min=.7):
t, rec, rec_filt = preprocess(index)
i = 0
ratio = []
for rec1_, rec_filt1_, rec2_, rec_filt2_ in zip(rec[0], rec_filt[0],
rec[1], rec_filt[1]):
# using filtered signal to extract slope
ipk, _ = find_epsp_peak(t, rec_filt1_)
# slope
_, r, _, _ = epsp_slope(t, rec1_, ipk, yf=rec_filt1_, return_pos=True)
if abs(r) < r_min:
i += 1
logger.warning("discarded new frame ({}), r={:.4f}, ".format(i, r))
continue
amp1 = rec1_[ipk]
# using filtered signal to extract slope
ipk, _ = find_epsp_peak(t, rec_filt2_)
# slope
_, r, _, _ = epsp_slope(t, rec2_, ipk, yf=rec_filt2_, return_pos=True)
if abs(r) < r_min:
i += 1
logger.warning("discarded new frame ({}), r={:.4f}, ".format(i, r))
continue
amp2 = rec2_[ipk]
ratio.append(amp2 / amp1)
return np.array(ratio)
def dual_pulse_plot(index, name="untitled"):
plt.cla()
ax.axhline(0, color="k", linestyle=":", linewidth=0.5)
t, rec1, rec2 = preprocess(index)
for rec, rec_filt, c, lbl in zip(rec1, rec2, ["r", "b"],
["1st pulse", "2nd pulse"]):
# visualize data
ax.plot(t, rec, c, label=lbl, linewidth=1)
# using filtered signal to extract slope
ipk, _ = find_epsp_peak(t, rec_filt)
ax.scatter(t[ipk],
rec[ipk],
marker="o",
edgecolors="k",
facecolor="none")
# slope
slope, r, dt, dy = epsp_slope(t,
rec,
ipk,
yf=rec_filt,
return_pos=True)
ax.plot(dt, dy, "k:", linewidth=1)
# final adjust
ax.legend()
# ax.set_xlim(coarse_crop)
plt.savefig("{}.png".format(name), dpi=300)
plt.waitforbuttonpress()
def extract_amplitude(index, r_min=.7):
t, rec, rec_filt = preprocess(index)
data = []
n_discard = 0
for i, rec_, rec_filt_ in zip(range(index[0], index[1] + 1), rec,
rec_filt):
# using filtered signal to extract slope
ipk, _ = find_epsp_peak(t, rec_filt_)
# slope
try:
slope, r, _, _ = epsp_slope(t,
rec_,
ipk,
yf=rec_filt_,
return_pos=True)
except ValueError:
n_discard += 1
logger.warning("error ({})".format(n_discard))
if abs(r) < r_min:
n_discard += 1
logger.warning("discarded new frame ({}), r={:.4f}, ".format(
n_discard, r))
data.append((i, rec_[ipk]))
x, y = tuple(zip(*data))
return np.array(x), np.array(y)
def extract_peak_info(t, rec, rec_filt, r_min=0.7):
i = 0
amp, slope = [], []
for rec_, rec_filt_ in zip(rec, rec_filt):
# using filtered signal to extract slope
ipk, _ = find_epsp_peak(t, rec_filt_)
# slope
slope_, r, _, _ = epsp_slope(t,
rec_,
ipk,
yf=rec_filt_,
return_pos=True)
if abs(r) < r_min:
i += 1
logger.warning("discarded new frame ({}), r={:.4f}, ".format(i, r))
continue
# save datapoint
amp.append(rec_[ipk])
slope.append(slope_)
amp = np.array(amp)
slope = np.array(slope)
return len(amp), amp, slope
def compare_plot(indice, labels, name="untitled", **kwargs):
plt.cla()
coarse_crop = (0.1, 0.15)
ax.axhline(0, color="k", linestyle=":", linewidth=0.5)
for index, label, c in zip(indice, labels, ["r", "b", "k"]):
t, rec, rec_filt = preprocess(index, coarse_crop)
# visualize data
ax.plot(t, rec, c, label=label, linewidth=1)
try:
# using filtered signal to extract slope
ipk, _ = find_epsp_peak(t, rec_filt)
ax.scatter(t[ipk],
rec[ipk],
marker="o",
edgecolors="k",
facecolor="none")
# slope
slope, r, dt, dy = epsp_slope(t,
rec,
ipk,
yf=rec_filt,
return_pos=True)
ax.plot(dt, dy, "k:", linewidth=1)
except ValueError:
logger.error("unable to determine slope")
# labels
plt.xlabel("Time (s)")
plt.ylabel("Intensity (mV)")
ax.legend()
plt.savefig("{}.png".format(name), dpi=300)
plt.waitforbuttonpress()
def main(index, name="filter_demo_sink"):
plt.cla()
# load data
t, stim, rec = load_frame_group(path, index=index, stacked=False)
# apply filter
rec_filt = []
for rec_ in rec:
rec_ = butter_lpf(rec_, lo_cutoff, fs)
rec_filt.append(rec_)
# mean
rec = np.stack(rec, axis=0).mean(axis=0)
rec = subtract_baseline(t, rec)
# visualize raw data
crop = (0.1, 0.15)
t_, rec = t_crop(t, rec, crop)
ax.plot(t_, rec, "r", label="raw", linewidth=1)
ax.axhline(0, color="k", linestyle=":", linewidth=0.5)
# using filtered signal to extract slope
rec_filt = np.stack(rec_filt, axis=0).mean(axis=0)
rec_filt = subtract_baseline(t, rec_filt)
t_, rec_filt = t_crop(t, rec_filt, crop)
ipk, _ = find_epsp_peak(t_, rec_filt)
ax.scatter(
t_[ipk],
rec_filt[ipk],
marker="o",
edgecolors="b",
facecolor="none",
label="EPSP peak",
)
# slope
slope, r, dt, dy = epsp_slope(t_, rec, ipk, yf=rec_filt, return_pos=True)
ax.plot(dt, dy, "b:", label="EPSP slope", linewidth=1)
# labels
ax.legend()
plt.xlabel("Time (s)")
plt.ylabel("Intensity (mV)")
# create inset
axin = inset_axes(ax, width="30%", height="50%", loc=4, borderpad=3)
t_in, rec_in = t_crop(t_, rec, (0.1025, 0.1100))
axin.plot(t_in, rec_in, "r", label="raw", linewidth=1)
axin.scatter(
t_[ipk],
rec_filt[ipk],
marker="o",
edgecolors="b",
facecolor="none",
label="EPSP peak",
)
axin.plot(dt, dy, "b:", linewidth=2)
axin.set_xlim((0.1025, 0.1100))
# final adjust
ax.set_xlim(crop)
plt.savefig("{}_slope-{:.3f}_r-{:.3f}.png".format(name, slope, r), dpi=300)
plt.waitforbuttonpress()