def plot_spike_trains_by_trial(axis_gen, data):
"ignores angle, assumes data is sorted by width"
# we will use a different axis for each speed_width & repetition
axes = {}
for d in data:
stimulus = d["stimulus"]
spike_train = d['spikes']
speed_width = (stimulus["speed"], stimulus["width"])
try:
ax, trial = axes[speed_width]
axes[speed_width] = (ax, trial + 1)
except:
ax = next(axis_gen)
if speed_width not in axes:
axes[speed_width] = None
trial = 0
axes[speed_width] = (ax, trial)
if spike_train.size > 0:
glia.draw_spikes(ax, spike_train, ymin=trial + 0.3, ymax=trial + 1)
for speed_width, tup in axes.items():
ax, trial = tup
ax.set_title("Speed: {}, Width: {}".format(speed_width[0],
speed_width[1]))
ax.set_xlabel("Time (s)")
ax.set_xlim([0, stimulus['lifespan']])
# trial is now the count
ax.set_ylim([0, trial])
ax.set_ylabel("Trial #")
def plot_spike_trains(axis_gen,data,prepend_start_time=1,append_lifespan=1):
ax = next(axis_gen)
trial = 0
for v in data:
# print(type(v))
stimulus, spike_train = (v["stimulus"], v["spikes"])
lifespan = stimulus['lifespan'] / 120
if lifespan > 10:
print("skipping stimulus longer than 10 seconds")
continue
if spike_train.size>0:
glia.draw_spikes(ax, spike_train, ymin=trial+0.3,ymax=trial+1)
stimulus_end = prepend_start_time + lifespan
duration = stimulus_end + append_lifespan
ax.fill([0,prepend_start_time,prepend_start_time,0],
[trial,trial,trial+1,trial+1],
facecolor="gray", edgecolor="none", alpha=0.1)
ax.fill([stimulus_end,duration,duration,stimulus_end],
[trial,trial,trial+1,trial+1],
facecolor="gray", edgecolor="none", alpha=0.1)
trial += 1
ax.set_title("Unit spike train per SOLID")
ax.set_xlabel("time (s)")
ax.set_ylabel("trials")
def plot_spike_trains_by_trial(axis_gen,data):
"ignores angle, assumes data is sorted by width"
# we will use a different axis for each speed_width & repetition
axes = {}
for d in data:
stimulus = d["stimulus"]
spike_train = d['spikes']
speed_width = (stimulus["speed"], stimulus["width"])
try:
ax,trial = axes[speed_width]
axes[speed_width] = (ax, trial+1)
except:
ax = next(axis_gen)
if speed_width not in axes:
axes[speed_width] = None
trial = 0
axes[speed_width] = (ax,trial)
if spike_train.size>0:
glia.draw_spikes(ax, spike_train, ymin=trial+0.3,ymax=trial+1)
for speed_width, tup in axes.items():
ax, trial = tup
ax.set_title("Speed: {}, Width: {}".format(
speed_width[0],speed_width[1]))
ax.set_xlabel("Time (s)")
ax.set_xlim([0,stimulus['lifespan']/120])
# trial is now the count
ax.set_ylim([0,trial])
ax.set_ylabel("Trial #")
def plot_spike_trains_vFail(fig, axis_gen, data):
# remove this function asap
ax = next(axis_gen)
trial = 0
# forgot to change group id, so iterate triplets
for i in range(0, len(data)-1, 3):
# x offset for row
offset = 0
for v in data[i:i+3]:
stimulus, spike_train = (v["stimulus"], v["spikes"])
lifespan = stimulus['lifespan']
end_time = lifespan + offset
if lifespan > 20:
logger.warning("skipping stimulus longer than 20 seconds")
continue
if spike_train.size>0:
glia.draw_spikes(ax, spike_train+offset, ymin=trial+0.3,
ymax=trial+1)
ax.fill([offset,end_time,end_time,offset],
[trial,trial,trial+1,trial+1],
facecolor=stimulus["backgroundColor"], edgecolor="none", alpha=0.1)
offset = end_time
trial += 1
ax.set_title("Unit spike train per SOLID group")
ax.set_xlabel("time (s)")
ax.set_ylabel("trials")
def plot_spike_train_triplet(fig, axis_gen, data):
#
ax = next(axis_gen)
trial = 0
# hardcoded 2 must correspond to pivot
longest_group = max(map(lambda x: get_lifespan(x[1]),
data)) + 2
for group in data:
# x offset for row
offset = 0
for i,v in enumerate(group):
stimulus, spike_train = (v["stimulus"], v["spikes"])
lifespan = stimulus['lifespan']
if i==0:
# only show last second before middle stimuli
pivot = lifespan-1
if pivot<0:
logger.error("first stimuli is too short--must be >1s")
pivot = 0
spike_train = spike_train[spike_train>pivot] - pivot
end_time = 1
elif i==1:
end_time = lifespan + offset
elif i==2:
# only show last second before middle stimuli
spike_train = spike_train[spike_train<1]
end_time = 1 + offset
if lifespan > 20:
logger.warning("skipping stimulus longer than 20 seconds")
continue
if spike_train.size>0:
glia.draw_spikes(ax, spike_train+offset, ymin=trial+0.3,
ymax=trial+1)
ax.fill([offset,end_time,end_time,offset],
[trial,trial,trial+1,trial+1],
facecolor=stimulus["backgroundColor"],
edgecolor="none", alpha=0.1)
offset = end_time
if offset<longest_group:
ax.fill([offset,longest_group,longest_group,offset],
[trial,trial,trial+1,trial+1],
facecolor="black",
edgecolor="none", alpha=1)
trial += 1
ax.set_title("Unit spike train per SOLID group")
ax.set_xlabel("time (s)")
ax.set_ylabel("trials")
ax.set_xlim((0,longest_group))
ax.set_ylim((0,trial))
def plot_spike_trains_by_angle(axis_gen, data):
"assumes data is sorted by angle"
# we will use a different axis for each speed_width & repetition
axes = {}
y = 0
trial = 0
current_angle = None
for d in data:
stimulus = d["stimulus"]
spike_train = d['spikes']
speed_width = (stimulus["speed"], stimulus["width"])
angle = stimulus["angle"]
if angle != current_angle:
trial = 0
y += 1
current_angle = angle
else:
# same angle, next trial
trial += 1
try:
ax = axes[speed_width][trial][0]
except:
ax = next(axis_gen)
if speed_width not in axes:
axes[speed_width] = {}
axes[speed_width][trial] = (ax, stimulus["lifespan"])
if spike_train.size > 0:
glia.draw_spikes(ax, spike_train, ymin=y + 0.3, ymax=y + 1)
for speed_width, trial in axes.items():
for trial, v in trial.items():
ax, duration = v
ax.set_title("Trial: {}, Speed: {}, Width: {}".format(
trial + 1, speed_width[0], speed_width[1]))
ax.set_xlabel("Time (s)")
ax.set_xlim([0, duration])
ax.set_ylabel("Bar Angle")
ax.set_yticks(np.linspace(0, y + 1, 9))
ax.set_yticklabels([
0, "45°", "90°", "135°", "180°", "225°", "270°", "315°", "360°"
])
def plot_spike_trains_by_angle(axis_gen,data):
"assumes data is sorted by angle"
# we will use a different axis for each speed_width & repetition
axes = {}
y = 0
trial = 0
current_angle = None
for d in data:
stimulus = d["stimulus"]
spike_train = d['spikes']
speed_width = (stimulus["speed"], stimulus["width"])
angle = stimulus["angle"]
if angle!=current_angle:
trial = 0
y += 1
current_angle = angle
else:
# same angle, next trial
trial+=1
try:
ax = axes[speed_width][trial][0]
except:
ax = next(axis_gen)
if speed_width not in axes:
axes[speed_width] = {}
axes[speed_width][trial] = (ax,stimulus["lifespan"]/120)
if spike_train.size>0:
glia.draw_spikes(ax, spike_train, ymin=y+0.3,ymax=y+1)
for speed_width, trial in axes.items():
for trial, v in trial.items():
ax, duration = v
ax.set_title("Trial: {}, Speed: {}, Width: {}".format(
trial+1,speed_width[0], speed_width[1]))
ax.set_xlabel("Time (s)")
ax.set_xlim([0,duration])
ax.set_ylabel("Bar Angle")
ax.set_yticks(np.linspace(0,y+1,9))
ax.set_yticklabels([0,"45°","90°","135°","180°","225°","270°","315°","360°"])
def plot_spike_trains(axis_gen, data):
for d in data:
ax = next(axis_gen)
stimulus = d["stimulus"]
train_list = d["train_list"]
trial = 0
for spike_train in train_list:
if spike_train.size > 0:
glia.draw_spikes(ax,
spike_train,
ymin=trial + 0.3,
ymax=trial + 1)
trial += 1
ax.set_title(
"speed={}, width={}, wavelength={}, angle={}, barColor={}".format(
stimulus["speed"], stimulus["width"], stimulus["wavelength"],
stimulus["angle"], stimulus["barColor"]))
ax.set_xlabel("relative time (s)")
ax.set_ylabel("period # (lower is earlier)")
def plot_spike_trains(fig, axis_gen, data,prepend_start_time=1,append_lifespan=1):
colors = set()
for e in data:
color = e["stimulus"]["backgroundColor"]
colors.add(color)
sorted_colors = sorted(list(colors),reverse=True)
for color in sorted_colors:
ax = next(axis_gen)
filtered_data = list(filter(lambda x: x["stimulus"]["backgroundColor"]==color,
data))
trial = 0
for v in filtered_data:
# print(type(v))
stimulus, spike_train = (v["stimulus"], v["spikes"])
lifespan = stimulus['lifespan']
if lifespan > 20:
print("skipping stimulus longer than 20 seconds")
continue
if spike_train.size>0:
glia.draw_spikes(ax, spike_train, ymin=trial+0.3,ymax=trial+1)
stimulus_end = prepend_start_time + lifespan
duration = stimulus_end + append_lifespan
ax.fill([0,prepend_start_time,prepend_start_time,0],
[trial,trial,trial+1,trial+1],
facecolor="gray", edgecolor="none", alpha=0.1)
ax.fill([stimulus_end,duration,duration,stimulus_end],
[trial,trial,trial+1,trial+1],
facecolor="gray", edgecolor="none", alpha=0.1)
trial += 1
ax.set_title("Unit spike train per SOLID ({})".format(color))
ax.set_xlabel("time (s)")
ax.set_ylabel("trials")
def plot_acuity_v3(fig, axis_gen, data, prepend, append, speed):
logger.debug("plot solid versus bar for speed")
ax = next(axis_gen)
solids, bars_by_speed = data
bars = bars_by_speed[speed]
max_lifespan = max(
bars, key=lambda e: e["stimulus"]["lifespan"])["stimulus"]["lifespan"]
lifespans = set()
widths = set()
angles = set()
for e in bars:
width = e["stimulus"]["width"]
angle = e["stimulus"]["angle"]
widths.add(width)
angles.add(angle)
# need to calculate duration of light over a particular point
light_duration = int(np.ceil(width / speed))
lifespans.add(light_duration)
logger.debug("lifespans {}, widths {}".format(len(lifespans), len(widths)))
# WARNING
# assert len(lifespans)==len(widths)
# keep charts aligned by row
angle_width = []
for w in sorted(widths):
for a in sorted(angles):
angle_width.append((a, w))
bar_ymap = {aw: i for i, aw in enumerate(angle_width)}
# used to map stimulus to proper row
c_bar_ymap = lambda s: bar_ymap[(s["angle"], s["width"])]
nangles = len(angles)
nwidths = len(widths)
ny = nangles * nwidths
xlim = glia.axis_continuation(lambda axis: axis.set_xlim(0, max_lifespan))
ylim = glia.axis_continuation(lambda axis: axis.set_ylim(0, ny))
bar_text = glia.axis_continuation(
partial(c_plot_bar,
title="{} angles x {} widths at {} px/s".format(
nangles, nwidths, speed)))
bar_continuation = glia.compose(ylim, xlim, bar_text)
for e in bars:
spikes = e["spikes"]
lifespan = e["stimulus"]["lifespan"]
angle = e["stimulus"]["angle"]
width = e["stimulus"]["width"]
y = bar_ymap[(angle, width)]
glia.draw_spikes(ax, spikes, y + 0.2, y + 0.8)
ax.fill([0, lifespan, lifespan, 0], [y, y, y + 1, y + 1],
facecolor="gray",
edgecolor="none",
alpha=0.1)
ax.yaxis.set_ticks(np.arange(0, nwidths * nangles, nangles))
ax.yaxis.set_ticklabels(sorted(list(widths)))
ax.set_ylabel("Bar Width in pixels (angle changes each row)")
ax.set_xlabel("Time in seconds")