def figure1n2(info,path):
if not os.path.exists(path):
os.makedirs(path)
sessions = info.groupby(level=['subject','session'])
for (subject,session),sinfo in sessions:
fig = plt.figure()
subjectpath = os.path.join(activitymovies.datafolder,subject)
sact = activitytables.read_subjects(subjectpath,days=[session])
scr = activitytables.read_subjects(subjectpath,days=[session],
selector = activitytables.crossings)
slipframes = activitytables.slipframes(sact,scr,sinfo,3,3)
side = int(np.ceil(np.sqrt(len(slipframes))))
tile = imgproc.tile(slipframes,side,side)
plt.imshow(tile[0], cmap = plt.cm.Greys_r)
plt.title(str.format('{0} (session {1})',subject,session))
fname = str.format("{0}_session_{1}_slip_posture.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.axis("off")
plt.savefig(fpath)
plt.close(fig)
def figure1k1(info,path):
if not os.path.exists(path):
os.makedirs(path)
sessions = info.groupby(level=['subject','session'])
for (subject,session),sinfo in sessions:
subjectpath = os.path.join(activitymovies.datafolder,subject)
sact = activitytables.read_subjects(subjectpath,days=[session])
scr = activitytables.read_subjects(subjectpath,days=[session],
selector = activitytables.crossings)
features = activitytables.stepfeature(sact,scr,4,3)
leftwards = features.side == 'leftwards'
features.xhead[leftwards] = max_width_cm - features.xhead[leftwards]
median = np.sort(features.xhead)[len(features)/2+1]
median = features[features.xhead == median].iloc[-1,:]
vidpaths = activitymovies.getmoviepath(sinfo)
timepaths = activitymovies.gettimepath(info)
movie = [video.video(mpath,mtimepath)
for mpath,mtimepath in zip(vidpaths,timepaths)][0]
medianframe = movie.frame(sact.index.get_loc(median.name))
flip = median.side == 'rightwards'
stepindex = 3 if flip else 4
medianframe = activitytables.cropstep(medianframe,stepindex,flip=flip)
fname = str.format("{0}_session_{1}_median_step_posture.png",
subject, session)
fpath = os.path.join(path,subject)
if not os.path.exists(fpath):
os.makedirs(fpath)
fpath = os.path.join(fpath,fname)
cv2.imwrite(fpath,medianframe)
def figure1n2(info, path):
if not os.path.exists(path):
os.makedirs(path)
sessions = info.groupby(level=['subject', 'session'])
for (subject, session), sinfo in sessions:
fig = plt.figure()
subjectpath = os.path.join(activitymovies.datafolder, subject)
sact = activitytables.read_subjects(subjectpath, days=[session])
scr = activitytables.read_subjects(subjectpath,
days=[session],
selector=activitytables.crossings)
slipframes = activitytables.slipframes(sact, scr, sinfo, 3, 3)
side = int(np.ceil(np.sqrt(len(slipframes))))
tile = imgproc.tile(slipframes, side, side)
plt.imshow(tile[0], cmap=plt.cm.Greys_r)
plt.title(str.format('{0} (session {1})', subject, session))
fname = str.format("{0}_session_{1}_slip_posture.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.axis("off")
plt.savefig(fpath)
plt.close(fig)
def figure1k3(info, path):
if not os.path.exists(path):
os.makedirs(path)
sessions = info.groupby(level=['subject'])
for subject, sinfo in sessions:
fig = plt.figure()
subjectpath = os.path.join(activitymovies.datafolder, subject)
stepframes = []
stinfo = sinfo[sinfo.protocol == 'stable']
for key, group in stinfo.groupby(level=['session']):
stact = activitytables.read_subjects(subjectpath, days=[key])
stcr = activitytables.read_subjects(
subjectpath, days=[key], selector=activitytables.crossings)
stepframes += activitytables.stepframes(stact,
stcr,
group,
4,
3,
subtractBackground=True)
stepframes = [
cv2.threshold(f, 5, 255, cv2.cv.CV_THRESH_BINARY)[1]
for f in stepframes
]
stavg = imgproc.average(stepframes, 1)
stepframes = []
uinfo = sinfo[sinfo.protocol != 'stable']
for key, group in uinfo.groupby(level=['session']):
uact = activitytables.read_subjects(subjectpath, days=[key])
ucr = activitytables.read_subjects(
subjectpath, days=[key], selector=activitytables.crossings)
stepframes += activitytables.stepframes(uact,
ucr,
group,
4,
3,
subtractBackground=True)
stepframes = [
cv2.threshold(f, 5, 255, cv2.cv.CV_THRESH_BINARY)[1]
for f in stepframes
]
uavg = imgproc.average(stepframes, 1)
avg = cv2.merge((uavg, stavg, np.zeros(stavg.shape,
dtype=stavg.dtype)))
avg = avg.astype(np.uint8)
avg = cv2.convertScaleAbs(avg, alpha=1.4, beta=0.0)
plt.imshow(avg)
plt.title(str.format('{0}', subject))
fname = str.format("{0}_posture_stable_unstable.png", subject)
fpath = os.path.join(path, fname)
plt.axis("off")
plt.savefig(fpath)
plt.close(fig)
def figure1j(info, path):
if not os.path.exists(path):
os.makedirs(path)
fig = plt.figure()
sessions = info.groupby(level=['subject'])
xticks = []
xticklabels = []
barplotwidth = 4
for i, (subject, sinfo) in enumerate(sessions):
subjectpath = os.path.join(activitymovies.datafolder, subject)
days = sinfo.index.levels[1][sinfo.index.labels[1]]
act = activitytables.read_subjects(subjectpath, days=days)
cr = activitytables.read_subjects(subjectpath,
days=days,
selector=activitytables.crossings)
offset = i * barplotwidth
stact = act[act.stepstate3]
stcr = cr[cr.stepstate3]
stfeatures = activitytables.stepfeature(stact, stcr, 4, 3)
stskipfrequency = 1 - float(len(stfeatures)) / len(stcr)
uact = act[~act.stepstate3]
ucr = cr[~cr.stepstate3]
ufeatures = activitytables.stepfeature(uact, ucr, 4, 3)
uskipfrequency = 1 - float(len(ufeatures)) / len(ucr)
plt.bar((-1 + offset, offset), (stskipfrequency, uskipfrequency),
color=['b', 'r'],
width=1,
hold=True)
xticks.append(offset)
xticklabels.append(subject.replace('JPAK_', ''))
p1 = plt.Rectangle((0, 0), 1, 1, fc="b")
p2 = plt.Rectangle((0, 0), 1, 1, fc="r")
plt.legend([p1, p2], ['stable', 'unstable'],
bbox_to_anchor=(0., 1.02, 1., .102),
loc=3,
ncol=2,
mode="expand",
borderaxespad=0.)
plt.xlabel('subject (JPAK)')
plt.ylabel('p(skipping)')
plt.xticks(xticks, xticklabels)
plt.xlim(-2, len(sessions) * barplotwidth - 1)
#plt.title(str.format('4th step contact frequency',subject))
fname = str.format("all_animals_4thstep_frequency.png", subject)
fpath = os.path.join(path, fname)
plt.savefig(fpath)
plt.close(fig)
def figure1l(info,path):
if not os.path.exists(path):
os.makedirs(path)
sessions = info.groupby(level=['subject'])
for subject,sinfo in sessions:
fig = plt.figure()
subjectpath = os.path.join(activitymovies.datafolder,subject)
days = sinfo.index.levels[1][sinfo.index.labels[1]]
act = activitytables.read_subjects(subjectpath,days=days)
cr = activitytables.read_subjects(subjectpath,days=days,
selector=activitytables.crossings)
axScatter = plt.subplot2grid((3,3),(1,0),rowspan=2,colspan=2)
axHistx = plt.subplot2grid((3,3),(0,0),colspan=2)
axHisty = plt.subplot2grid((3,3),(1,2),rowspan=2)
axes = (axScatter,axHistx,axHisty)
stepoffset = stepcenter_cm[3][1]
bins = 50
xlim = (20-stepoffset,30-stepoffset)
ylim = (-1,9)
alpha = 0.75
stact = act[act.stepstate3]
stcr = cr[cr.stepstate3]
stfeatures = activitytables.stepfeature(stact,stcr,4,3)
leftwards = stfeatures.side == 'leftwards'
stfeatures.xhead[leftwards] = max_width_cm - stfeatures.xhead[leftwards]
stfeatures.xhead -= stepoffset
activityplots.scatterhist(stfeatures.xhead,stfeatures.yhead,color='b',
bins=bins,axes=axes,xlim=xlim,ylim=ylim,
histalpha=alpha)
uact = act[~act.stepstate3]
ucr = cr[~cr.stepstate3]
ufeatures = activitytables.stepfeature(uact,ucr,4,3)
leftwards = ufeatures.side == 'leftwards'
ufeatures.xhead[leftwards] = max_width_cm - ufeatures.xhead[leftwards]
ufeatures.xhead -= stepoffset
activityplots.scatterhist(ufeatures.xhead,ufeatures.yhead,color='r',
bins=bins,axes=axes,xlim=xlim,ylim=ylim,
histalpha=alpha)
axScatter.set_xlabel('x (cm)')
axScatter.set_ylabel('y (cm)')
axScatter.legend(['stable', 'unstable'],loc=2)
axHistx.set_title(str.format('{0} nose position on contact',subject))
fname = str.format("{0}_nose_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)
def figure1j(info,path):
if not os.path.exists(path):
os.makedirs(path)
fig = plt.figure()
sessions = info.groupby(level=['subject'])
xticks = []
xticklabels = []
barplotwidth = 4
for i,(subject,sinfo) in enumerate(sessions):
subjectpath = os.path.join(activitymovies.datafolder,subject)
days = sinfo.index.levels[1][sinfo.index.labels[1]]
act = activitytables.read_subjects(subjectpath,days=days)
cr = activitytables.read_subjects(subjectpath,days=days,
selector=activitytables.crossings)
offset = i * barplotwidth
stact = act[act.stepstate3]
stcr = cr[cr.stepstate3]
stfeatures = activitytables.stepfeature(stact,stcr,4,3)
stskipfrequency = 1 - float(len(stfeatures)) / len(stcr)
uact = act[~act.stepstate3]
ucr = cr[~cr.stepstate3]
ufeatures = activitytables.stepfeature(uact,ucr,4,3)
uskipfrequency = 1 - float(len(ufeatures)) / len(ucr)
plt.bar((-1 + offset,offset),(stskipfrequency,uskipfrequency),
color=['b','r'],width=1,hold=True)
xticks.append(offset)
xticklabels.append(subject.replace('JPAK_',''))
p1 = plt.Rectangle((0, 0), 1, 1, fc="b")
p2 = plt.Rectangle((0, 0), 1, 1, fc="r")
plt.legend([p1,p2],['stable', 'unstable'],
bbox_to_anchor=(0., 1.02, 1., .102), loc=3,
ncol=2, mode="expand", borderaxespad=0.)
plt.xlabel('subject (JPAK)')
plt.ylabel('p(skipping)')
plt.xticks(xticks,xticklabels)
plt.xlim(-2,len(sessions) * barplotwidth - 1)
#plt.title(str.format('4th step contact frequency',subject))
fname = str.format("all_animals_4thstep_frequency.png",subject)
fpath = os.path.join(path,fname)
plt.savefig(fpath)
plt.close(fig)
def figure1k3(info,path):
if not os.path.exists(path):
os.makedirs(path)
sessions = info.groupby(level=['subject'])
for subject,sinfo in sessions:
fig = plt.figure()
subjectpath = os.path.join(activitymovies.datafolder,subject)
stepframes = []
stinfo = sinfo[sinfo.protocol == 'stable']
for key,group in stinfo.groupby(level=['session']):
stact = activitytables.read_subjects(subjectpath,days=[key])
stcr = activitytables.read_subjects(subjectpath,days=[key],
selector = activitytables.crossings)
stepframes += activitytables.stepframes(stact,stcr,group,4,3,
subtractBackground=True)
stepframes = [cv2.threshold(f, 5, 255, cv2.cv.CV_THRESH_BINARY)[1]
for f in stepframes]
stavg = imgproc.average(stepframes,1)
stepframes = []
uinfo = sinfo[sinfo.protocol != 'stable']
for key,group in uinfo.groupby(level=['session']):
uact = activitytables.read_subjects(subjectpath,days=[key])
ucr = activitytables.read_subjects(subjectpath,days=[key],
selector = activitytables.crossings)
stepframes += activitytables.stepframes(uact,ucr,group,4,3,
subtractBackground=True)
stepframes = [cv2.threshold(f, 5, 255, cv2.cv.CV_THRESH_BINARY)[1]
for f in stepframes]
uavg = imgproc.average(stepframes,1)
avg = cv2.merge((uavg,stavg,np.zeros(stavg.shape,dtype=stavg.dtype)))
avg = avg.astype(np.uint8)
avg = cv2.convertScaleAbs(avg,alpha=1.4,beta=0.0)
plt.imshow(avg)
plt.title(str.format('{0}',subject))
fname = str.format("{0}_posture_stable_unstable.png", subject)
fpath = os.path.join(path,fname)
plt.axis("off")
plt.savefig(fpath)
plt.close(fig)
def figure1k1(info, path):
if not os.path.exists(path):
os.makedirs(path)
sessions = info.groupby(level=['subject', 'session'])
for (subject, session), sinfo in sessions:
subjectpath = os.path.join(activitymovies.datafolder, subject)
sact = activitytables.read_subjects(subjectpath, days=[session])
scr = activitytables.read_subjects(subjectpath,
days=[session],
selector=activitytables.crossings)
features = activitytables.stepfeature(sact, scr, 4, 3)
leftwards = features.side == 'leftwards'
features.xhead[leftwards] = max_width_cm - features.xhead[leftwards]
median = np.sort(features.xhead)[len(features) / 2 + 1]
median = features[features.xhead == median].iloc[-1, :]
vidpaths = activitymovies.getmoviepath(sinfo)
timepaths = activitymovies.gettimepath(info)
movie = [
video.video(mpath, mtimepath)
for mpath, mtimepath in zip(vidpaths, timepaths)
][0]
medianframe = movie.frame(sact.index.get_loc(median.name))
flip = median.side == 'rightwards'
stepindex = 3 if flip else 4
medianframe = activitytables.cropstep(medianframe,
stepindex,
flip=flip)
fname = str.format("{0}_session_{1}_median_step_posture.png", subject,
session)
fpath = os.path.join(path, subject)
if not os.path.exists(fpath):
os.makedirs(fpath)
fpath = os.path.join(fpath, fname)
cv2.imwrite(fpath, medianframe)
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 figure1n(info, path):
if not os.path.exists(path):
os.makedirs(path)
sessions = info.groupby(level=['subject', 'session'])
for (subject, session), sinfo in sessions:
subjectpath = os.path.join(activitymovies.datafolder, subject)
sact = activitytables.read_subjects(subjectpath, days=[session])
activityplots.clusterslipframes(sact, sinfo, 4, 2)
plt.suptitle(str.format('{0} (session {1})', subject, session))
fname = str.format("{0}_session_{1}_slip_posture.png", subject,
session)
fpath = os.path.join(path, subject)
if not os.path.exists(fpath):
os.makedirs(fpath)
fpath = os.path.join(fpath, fname)
fig = plt.gcf()
plt.get_current_fig_manager().resize(1090, 480)
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)
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 figure1n(info,path):
if not os.path.exists(path):
os.makedirs(path)
sessions = info.groupby(level=['subject','session'])
for (subject,session),sinfo in sessions:
subjectpath = os.path.join(activitymovies.datafolder,subject)
sact = activitytables.read_subjects(subjectpath,days=[session])
activityplots.clusterslipframes(sact,sinfo,4,2)
plt.suptitle(str.format('{0} (session {1})',subject,session))
fname = str.format("{0}_session_{1}_slip_posture.png",
subject, session)
fpath = os.path.join(path,subject)
if not os.path.exists(fpath):
os.makedirs(fpath)
fpath = os.path.join(fpath,fname)
fig = plt.gcf()
plt.get_current_fig_manager().resize(1090,480)
plt.savefig(fpath)
plt.close(fig)
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_27',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_28',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_29',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_36',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_37',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_38',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_39',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_48',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_49',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_50',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_51',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_52',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_53',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_54',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_55']
cr = activitytables.read_subjects(datafolders,days=days,
selector=lambda x:activitytables.crossings(x,True,False))
rr = activitytables.read_subjects(datafolders,days=days,
key=activitytables.rewards_key)
info = activitytables.read_subjects(datafolders,days=days,
key=activitytables.info_key)
# For video analysis (4,10,12,16)
days = [0]
datafolders = [r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_21']
cr = activitytables.read_subjects(datafolders,days=days)
rr = activitytables.read_subjects(datafolders,days=days,key=activitytables.rewards_key)
info = activitytables.read_subjects(datafolders,days=days,key=activitytables.info_key)
def clusterstepframes(cr,info,leftstep,rightstep):
# Compute step times
def figure1l(info, path):
if not os.path.exists(path):
os.makedirs(path)
sessions = info.groupby(level=['subject'])
for subject, sinfo in sessions:
fig = plt.figure()
subjectpath = os.path.join(activitymovies.datafolder, subject)
days = sinfo.index.levels[1][sinfo.index.labels[1]]
act = activitytables.read_subjects(subjectpath, days=days)
cr = activitytables.read_subjects(subjectpath,
days=days,
selector=activitytables.crossings)
axScatter = plt.subplot2grid((3, 3), (1, 0), rowspan=2, colspan=2)
axHistx = plt.subplot2grid((3, 3), (0, 0), colspan=2)
axHisty = plt.subplot2grid((3, 3), (1, 2), rowspan=2)
axes = (axScatter, axHistx, axHisty)
stepoffset = stepcenter_cm[3][1]
bins = 50
xlim = (20 - stepoffset, 30 - stepoffset)
ylim = (-1, 9)
alpha = 0.75
stact = act[act.stepstate3]
stcr = cr[cr.stepstate3]
stfeatures = activitytables.stepfeature(stact, stcr, 4, 3)
leftwards = stfeatures.side == 'leftwards'
stfeatures.xhead[
leftwards] = max_width_cm - stfeatures.xhead[leftwards]
stfeatures.xhead -= stepoffset
activityplots.scatterhist(stfeatures.xhead,
stfeatures.yhead,
color='b',
bins=bins,
axes=axes,
xlim=xlim,
ylim=ylim,
histalpha=alpha)
uact = act[~act.stepstate3]
ucr = cr[~cr.stepstate3]
ufeatures = activitytables.stepfeature(uact, ucr, 4, 3)
leftwards = ufeatures.side == 'leftwards'
ufeatures.xhead[leftwards] = max_width_cm - ufeatures.xhead[leftwards]
ufeatures.xhead -= stepoffset
activityplots.scatterhist(ufeatures.xhead,
ufeatures.yhead,
color='r',
bins=bins,
axes=axes,
xlim=xlim,
ylim=ylim,
histalpha=alpha)
axScatter.set_xlabel('x (cm)')
axScatter.set_ylabel('y (cm)')
axScatter.legend(['stable', 'unstable'], loc=2)
axHistx.set_title(str.format('{0} nose position on contact', subject))
fname = str.format("{0}_nose_stable_unstable.png", subject)
fpath = os.path.join(path, fname)
plt.savefig(fpath)
plt.close(fig)
# -*- coding: utf-8 -*- """ Created on Tue Oct 07 13:17:13 2014 @author: Gonçalo """ import activitytables import activityplots subject = r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_25' stablerange = range(4,5) randomrange = range(13,17) act1 = activitytables.read_subjects(subject, days=stablerange) act2 = activitytables.read_subjects(subject, days=randomrange) cross1 = activitytables.read_subjects(subject, days=stablerange, selector=activitytables.crossings) cross2 = activitytables.read_subjects(subject, days=randomrange, selector=activitytables.crossings) validc1 = cross1[(cross1.label == 'valid') & (cross1.stepstate3)] validc2 = cross2[(cross2.label == 'valid') & (cross2.stepstate3)] traj1 = [act1[slice(s.start,s.stop)] for s in validc1.slices] traj2 = [act2[slice(s.start,s.stop)] for s in validc2.slices]
# -*- coding: utf-8 -*- """ Created on Thu Apr 30 12:30:38 2015 @author: Gonçalo """ from activitytables import read_subjects from activitytables import visiblecrossings, fullcrossings, crossings from datapath import lesionsham, decorticate from datapath import lesionshamcache, decorticatecache from datapath import visiblecrossings_key, fullcrossings_key, crossings_key # Rebuild crossing cache print "Rebuilding lesionsham visible crossings..." cr = read_subjects(lesionsham,selector=visiblecrossings) cr.to_hdf(lesionshamcache,visiblecrossings_key) print "Rebuilding lesionsham full crossings..." cr = read_subjects(lesionsham,selector=fullcrossings) cr.to_hdf(lesionshamcache,fullcrossings_key) print "Rebuilding lesionsham crossings..." cr = read_subjects(lesionsham,selector=crossings) cr.to_hdf(lesionshamcache,crossings_key) print "Rebuilding decorticate visible crossings..." cr = read_subjects(decorticate,selector=visiblecrossings) cr.to_hdf(decorticatecache,visiblecrossings_key) print "Rebuilding decorticate full crossings..."
gioias = [
r'D:/Protocols/Shuttling/Decorticate/Data/GIOIA_01',
r'D:/Protocols/Shuttling/Decorticate/Data/GIOIA_03'
]
decorticates = [
r'D:/Protocols/Shuttling/Decorticate/Data/JPAK_79',
r'D:/Protocols/Shuttling/Decorticate/Data/JPAK_81',
r'D:/Protocols/Shuttling/Decorticate/Data/JPAK_82'
]
subjects = gioias + subjects + decorticates
cr = activitytables.read_subjects(subjects[1:],
days=[3, 4, 9, 10, -1],
selector=activitytables.crossings)
info = activitytables.read_subjects(subjects[1:],
days=[3, 4, 9, 10, -1],
key=activitytables.info_key)
# Figure 1B (Across Conditions)
rr = activitytables.read_subjects(subjects,
days=range(1, 5),
key=activitytables.rewards_key)
info = activitytables.read_subjects(subjects,
days=range(1, 5),
key=activitytables.info_key)
fbase = r'C:\figs\figure1b'
figure1.figure1b(rr, info, fbase)
# -*- coding: utf-8 -*- """ Created on Sun May 03 15:08:56 2015 @author: Gonçalo """ from activitytables import read_subjects from activitytables import stepfeatures from datapath import lesionsham, decorticate from datapath import lesionshamcache, decorticatecache from datapath import stepfeatures_key # Rebuild crossing cache print "Rebuilding lesionsham step features..." cr = read_subjects(lesionsham, selector=stepfeatures) cr.to_hdf(lesionshamcache, stepfeatures_key) print "Rebuilding decorticate step features..." cr = read_subjects(decorticate, selector=stepfeatures) cr.to_hdf(decorticatecache, stepfeatures_key)
@author: Gonçalo """ from activitytables import read_subjects from activitytables import crossingactivity from datapath import lesionsham, decorticate from datapath import lesionshamcache, decorticatecache from datapath import crossingactivity_stable_key from datapath import crossingactivity_unstable_key from datapath import crossingactivity_restable_key from datapath import crossingactivity_random_key from datapath import crossingactivity_challenge_key # Rebuild crossing trajectory cache print "Rebuilding lesionsham stable trajectories..." cr = read_subjects(lesionsham, days=slice(0, 5), selector=crossingactivity) cr.to_hdf(lesionshamcache, crossingactivity_stable_key) print "Rebuilding lesionsham unstable trajectories..." cr = read_subjects(lesionsham, days=slice(5, 11), selector=crossingactivity) cr.to_hdf(lesionshamcache, crossingactivity_unstable_key) print "Rebuilding lesionsham restable trajectories..." cr = read_subjects(lesionsham, days=slice(11, 13), selector=crossingactivity) cr.to_hdf(lesionshamcache, crossingactivity_restable_key) print "Rebuilding lesionsham random trajectories..." cr = read_subjects(lesionsham, days=slice(13, 17), selector=crossingactivity) cr.to_hdf(lesionshamcache, crossingactivity_random_key) print "Rebuilding lesionsham challenge trajectories..."
r'D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_50',
r'D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_51',
r'D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_52',
r'D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_53',
r'D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_54',
r'D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_55'
]
decorticates = [
r'D:/Protocols/Shuttling/Decorticate/Data/JPAK_79',
r'D:/Protocols/Shuttling/Decorticate/Data/JPAK_81',
r'D:/Protocols/Shuttling/Decorticate/Data/JPAK_82'
]
# Figure 1
rr = activitytables.read_subjects(subjects, key=activitytables.rewards_key)
info = activitytables.read_subjects(subjects, key=activitytables.info_key)
cr = None
crd = None
infod = None
# Reward time over sessions
selection = 'session > 0 and session < 17'
shuttlingplots.timetoreward(rr.query(selection), info.query(selection))
ymin, ymax = plt.ylim()
plt.vlines(5 * 3 + 0.5, ymin, ymax, linestyles='solid')
plt.vlines(12 * 3 + 0.5, ymin, ymax, linestyles='solid')
plt.vlines(15 * 3 + 0.5, ymin, ymax, linestyles='solid')
plt.ylim(ymin, ymax)
# Time to cross over sessions
# -*- coding: utf-8 -*- """ Created on Sat May 02 22:09:50 2015 @author: Gonçalo """ from activitytables import read_subjects from activitytables import info_key from datapath import ecog, ecogcache from datapath import ecoganalysis, ensurefolder # Rebuild info cache ensurefolder(ecoganalysis) print "Rebuilding ecog session info..." cr = read_subjects(ecog, key=info_key) cr.to_hdf(ecogcache, info_key)
# -*- coding: utf-8 -*- """ Created on Sun May 03 15:08:56 2015 @author: Gonçalo """ from activitytables import read_subjects from activitytables import stepfeatures from datapath import ecog, ecogcache from datapath import stepfeatures_key # Rebuild crossing cache print "Rebuilding ecog step features..." cr = read_subjects(ecog,selector=stepfeatures) cr.to_hdf(ecogcache,stepfeatures_key)
r"D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_29",
r"D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_36",
r"D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_37",
r"D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_38",
r"D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_39",
r"D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_48",
r"D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_49",
r"D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_50",
r"D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_51",
r"D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_52",
r"D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_53",
r"D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_54",
r"D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_55",
]
cr = activitytables.read_subjects(subjects[1:], days=[3, 4, 9, 10, -1], selector=activitytables.crossings)
info = activitytables.read_subjects(subjects[1:], days=[3, 4, 9, 10, -1], key=activitytables.info_key)
# Figure 1C (Across Conditions)
alpha = 1
fbase = r"C:\figs\figure1c"
scr = cr.query("session != 3 and session != 9")
sinfo = info.query("session != 3 and session != 9")
scr = figure1.resetsessionindex(scr, [0, 1, 2], 2)
sinfo = figure1.resetsessionindex(sinfo, [0, 1, 2], 2)
figure1.figure1c0(scr, fbase, alpha=alpha, fname="all_subjects_duration_maxheight_all_conditions_0.png")
figure1.figure1c2(scr, fbase, alpha=alpha, fname="all_subjects_duration_maxheight_all_conditions_0a_colored.png")
figure1.figure1c3(scr, sinfo, fbase, alpha=alpha, fname="all_subjects_duration_maxheight_all_conditions_1_lesion.png")
figure1.figure1c4(
scr, sinfo, fbase, alpha=alpha, fname="all_subjects_duration_maxheight_all_conditions_2_big_lesion.png"
)
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 07 13:17:13 2014
@author: Gonçalo
"""
import activitytables
import activityplots
subject = r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_25'
stablerange = range(4, 5)
randomrange = range(13, 17)
act1 = activitytables.read_subjects(subject, days=stablerange)
act2 = activitytables.read_subjects(subject, days=randomrange)
cross1 = activitytables.read_subjects(subject,
days=stablerange,
selector=activitytables.crossings)
cross2 = activitytables.read_subjects(subject,
days=randomrange,
selector=activitytables.crossings)
validc1 = cross1[(cross1.label == 'valid') & (cross1.stepstate3)]
validc2 = cross2[(cross2.label == 'valid') & (cross2.stepstate3)]
traj1 = [act1[slice(s.start, s.stop)] for s in validc1.slices]
traj2 = [act2[slice(s.start, s.stop)] for s in validc2.slices]
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_29',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_36',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_37',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_38',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_39',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_48',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_49',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_50',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_51',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_52',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_53',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_54',
r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_55'
]
cr = activitytables.read_subjects(
datafolders,
days=days,
selector=lambda x: activitytables.crossings(x, True, False))
rr = activitytables.read_subjects(datafolders,
days=days,
key=activitytables.rewards_key)
info = activitytables.read_subjects(datafolders,
days=days,
key=activitytables.info_key)
# For video analysis (4,10,12,16)
days = [0]
datafolders = [r'E:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_21']
cr = activitytables.read_subjects(datafolders, days=days)
rr = activitytables.read_subjects(datafolders,
days=days,
key=activitytables.rewards_key)
r'D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_36',
r'D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_37',
r'D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_38',
r'D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_39',
r'D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_48',
r'D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_49',
r'D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_50',
r'D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_51',
r'D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_52',
r'D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_53',
r'D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_54',
r'D:/Protocols/Shuttling/LightDarkServoStable/Data/JPAK_55'
]
cr = activitytables.read_subjects(subjects[1:],
days=[3, 4, 9, 10, -1],
selector=activitytables.crossings)
info = activitytables.read_subjects(subjects[1:],
days=[3, 4, 9, 10, -1],
key=activitytables.info_key)
# Figure 1C (Across Conditions)
alpha = 1
fbase = r'C:\figs\figure1c'
scr = cr.query('session != 3 and session != 9')
sinfo = info.query('session != 3 and session != 9')
scr = figure1.resetsessionindex(scr, [0, 1, 2], 2)
sinfo = figure1.resetsessionindex(sinfo, [0, 1, 2], 2)
figure1.figure1c0(scr,
fbase,
alpha=alpha,