def __spatialaverages__(cr,path,selector=lambda x:x.yhead,
ylabel='y (cm)',xlim=None,ylim=None):
if not os.path.exists(path):
os.makedirs(path)
cut = getballistictrials(cr)
sessions = cut[cut.trial > 0].groupby(level=['subject','session'])
for (subject,session),group in sessions:
fig = plt.figure()
subjectpath = os.path.join(activitymovies.datafolder,subject)
sact = activitytables.read_subjects(subjectpath,days=[session])
x,y,yerr = activitytables.spatialaverage(sact,group,selector)
activityplots.trajectoryplot(sact,group,alpha=0.2,flip=True,
selector=selector)
plt.fill_between(x,y-yerr,y+yerr)
if xlim is not None:
plt.xlim(xlim)
if ylim is not None:
plt.ylim(ylim)
plt.xlabel('x (cm)')
plt.ylabel(ylabel)
plt.title(str.format('{0} (session {1})',subject,session))
fname = str.format("{0}_session_{1}_trajectories.png",
subject, session)
fpath = os.path.join(path,subject)
if not os.path.exists(fpath):
os.makedirs(fpath)
fpath = os.path.join(fpath,fname)
plt.savefig(fpath)
plt.close(fig)
def __spatialaveragecomparison__(cr,
path,
selector=lambda x: x.yhead,
ylabel='y (cm)',
xlim=None,
ylim=None):
if not os.path.exists(path):
os.makedirs(path)
cut = getballistictrials(cr)
conditions = cut[cut.trial > 0].groupby(level=['subject'])
for subject, group in conditions:
fig = plt.figure()
days = group.index.levels[1][group.index.labels[1]]
subjectpath = os.path.join(activitymovies.datafolder, subject)
act = activitytables.read_subjects(subjectpath, days=days)
stact = act[act.stepstate3]
stcr = group[group.stepstate3]
x, y, yerr = activitytables.spatialaverage(stact, stcr, selector)
plt.fill_between(x, y - yerr, y + yerr, color='b')
uact = act[~act.stepstate3]
ucr = group[~group.stepstate3]
x, y, yerr = activitytables.spatialaverage(uact, ucr, selector)
plt.fill_between(x, y - yerr, y + yerr, color='r')
p1 = plt.Rectangle((0, 0), 1, 1, fc='b')
p2 = plt.Rectangle((0, 0), 1, 1, fc='r')
plt.legend([p1, p2], ['stable', 'unstable'])
if xlim is not None:
plt.xlim(xlim)
if ylim is not None:
plt.ylim(ylim)
plt.xlabel('x (cm)')
plt.ylabel(ylabel)
plt.title(str.format('{0} trajectories', subject))
fname = str.format("{0}_trajectories_stable_unstable.png", subject)
fpath = os.path.join(path, fname)
plt.savefig(fpath)
plt.close(fig)
def averagetimeseries(cract,column=None,baseline=None,
color='b',ax=None,**kwargs):
if ax is None:
fig = plt.figure()
ax = fig.gca()
xpoints = createspaceaxis()
ymean,yerr = activitytables.spatialaverage(xpoints,cract,column,baseline)
activityplots.boundedcurve(xpoints,ymean,yerr,color=color,ax=ax,**kwargs)
ax.set_xlabel('x (cm)')
ax.set_xlim(-15,25)
def __spatialaveragecomparison__(cr,path,selector=lambda x:x.yhead,
ylabel='y (cm)',xlim=None,ylim=None):
if not os.path.exists(path):
os.makedirs(path)
cut = getballistictrials(cr)
conditions = cut[cut.trial > 0].groupby(level=['subject'])
for subject,group in conditions:
fig = plt.figure()
days = group.index.levels[1][group.index.labels[1]]
subjectpath = os.path.join(activitymovies.datafolder,subject)
act = activitytables.read_subjects(subjectpath,days=days)
stact = act[act.stepstate3]
stcr = group[group.stepstate3]
x,y,yerr = activitytables.spatialaverage(stact,stcr,selector)
plt.fill_between(x,y-yerr,y+yerr,color='b')
uact = act[~act.stepstate3]
ucr = group[~group.stepstate3]
x,y,yerr = activitytables.spatialaverage(uact,ucr,selector)
plt.fill_between(x,y-yerr,y+yerr,color='r')
p1 = plt.Rectangle((0, 0), 1, 1, fc='b')
p2 = plt.Rectangle((0, 0), 1, 1, fc='r')
plt.legend([p1, p2], ['stable', 'unstable'])
if xlim is not None:
plt.xlim(xlim)
if ylim is not None:
plt.ylim(ylim)
plt.xlabel('x (cm)')
plt.ylabel(ylabel)
plt.title(str.format('{0} trajectories',subject))
fname = str.format("{0}_trajectories_stable_unstable.png",subject)
fpath = os.path.join(path,fname)
plt.savefig(fpath)
plt.close(fig)
def __spatialaverages__(cr,
path,
selector=lambda x: x.yhead,
ylabel='y (cm)',
xlim=None,
ylim=None):
if not os.path.exists(path):
os.makedirs(path)
cut = getballistictrials(cr)
sessions = cut[cut.trial > 0].groupby(level=['subject', 'session'])
for (subject, session), group in sessions:
fig = plt.figure()
subjectpath = os.path.join(activitymovies.datafolder, subject)
sact = activitytables.read_subjects(subjectpath, days=[session])
x, y, yerr = activitytables.spatialaverage(sact, group, selector)
activityplots.trajectoryplot(sact,
group,
alpha=0.2,
flip=True,
selector=selector)
plt.fill_between(x, y - yerr, y + yerr)
if xlim is not None:
plt.xlim(xlim)
if ylim is not None:
plt.ylim(ylim)
plt.xlabel('x (cm)')
plt.ylabel(ylabel)
plt.title(str.format('{0} (session {1})', subject, session))
fname = str.format("{0}_session_{1}_trajectories.png", subject,
session)
fpath = os.path.join(path, subject)
if not os.path.exists(fpath):
os.makedirs(fpath)
fpath = os.path.join(fpath, fname)
plt.savefig(fpath)
plt.close(fig)
uts = []
for selected in group:
names = [selected]
selection = str.format("subject in {0}", names)
sb_S = sb_SA.query(selection)
sb_U = sb_UA.query(selection)
ub_S = ub_SA.query(selection)
ub_U = ub_UA.query(selection)
# Plot data
alpha = 0.25
baseline = slice(0, 28)
xpoints = createspaceaxis()
fig, (ax1, ax2) = plt.subplots(1, 2)
st, sterr = spatialaverage(xpoints,
pd.concat([sb_S, ub_S]),
'xhead_speed',
baseline=baseline)
ut, uterr = spatialaverage(xpoints,
pd.concat([sb_U, ub_U]),
'xhead_speed',
baseline=baseline)
boundedcurve(xpoints, st, sterr, color='b', ax=ax1, alpha=alpha)
boundedcurve(xpoints, ut, uterr, color='r', ax=ax1, alpha=alpha)
proxylegend(['b', 'r'], ['stable', 'unstable'], ax=ax1, loc='upper left')
ax1.set_title('average speed across space')
ax1.set_xlabel('x (cm)')
ax1.set_ylabel('speed (cm/s)')
ax1.set_xlim(-15, 25)
ax1.set_ylim(-20, 30)
sts.append(st)
uts.append(ut)