def plotFishpathandTraces(dataArr, colorArr):
fig = pyplot.figure(1, figsize=(11, 7))
for i in range(2):
if i == 0:
for k in range(3):
ax = pyplot.subplot(4, 3, k + 1)
aba.plotFishPath(dataArr[k], color=colorArr[k], smoothWinLen=5)
# pyplot.title('Fish Path in Tank')
pyplot.xlabel("46 mm")
pyplot.ylabel("22 mm")
ax.set_xticks([20, 40])
ax.set_yticks([10, 20])
ax2 = pyplot.subplot(4, 3, k + 4)
aba.plotFishXPosition(dataArr[k], fmt=colorArr[k], smooth=5)
ax2.set_yticks([20, 40])
pyplot.ylabel("x position")
if k == 1:
patch5 = mpl.patches.Rectangle((900, 0), 1844, 50, color=[1, 0.5, 0.5], fill=True)
pyplot.gca().add_patch(patch5)
if i == 1:
for k in range(3):
ax = pyplot.subplot(4, 3, i + k + 6)
aba.plotFishPath(dataArr[k + i + 2], color=colorArr[k + i + 2], smoothWinLen=5)
# pyplot.title('Fish Path in Tank')
pyplot.xlabel("46 mm")
pyplot.ylabel("22 mm")
ax.set_xticks([20, 40])
ax.set_yticks([10, 20])
ax2 = pyplot.subplot(4, 3, i + k + 9)
aba.plotFishXPosition(dataArr[k + i + 2], fmt=colorArr[k + i + 2], smooth=5)
pyplot.ylabel("x position")
ax2.set_yticks([20, 40])
if k == 1:
patch5 = mpl.patches.Rectangle((900, 0), 1844, 50, color=[1, 0.5, 0.5], fill=True)
pyplot.gca().add_patch(patch5)
e_fish_oldR = aba.loadMultipleDataFiles(e_fish_oldR)
# assumes shock is on red
(e_frac_yNR, e_dist_yNR) = aba.getSidePreference_Multi(e_fish_youngNR, cond=[8, 8], refState="Red")
(e_frac_yR, e_dist_yR) = aba.getSidePreference_Multi(e_fish_youngR, cond=[8, 8], refState="Red")
(e_frac_oNR, e_dist_oNR) = aba.getSidePreference_Multi(e_fish_oldNR, cond=[8, 8], refState="Red")
(e_frac_oR, e_dist_oR) = aba.getSidePreference_Multi(e_fish_oldR, cond=[8, 8], refState="Red")
e_young_frac = np.append(e_frac_yNR, e_frac_yR, axis=0)
e_old_frac = np.append(e_frac_oNR, e_frac_oR, axis=0)
e_young_dist = np.append(e_dist_yNR, e_dist_yR, axis=0)
e_old_dist = np.append(e_dist_oNR, e_dist_oR, axis=0)
import scipy
[tv, e_yfrac] = scipy.stats.ttest_1samp(np.mean(e_young_frac, axis=1), 0.5)
[tv, e_ofrac] = scipy.stats.ttest_1samp(np.mean(e_old_frac, axis=1), 0.5)
[tv, e_ydist] = scipy.stats.ttest_1samp(np.mean(e_young_dist, axis=1), 24)
[tv, e_odist] = scipy.stats.ttest_1samp(np.mean(e_old_dist, axis=1), 24)
print "experimental young frac, old frac, young dist, old dist: ", e_yfrac, e_ofrac, e_ydist, e_odist
import pylab
total = e_fish_youngNR + e_fish_youngR + e_fish_oldNR + e_fish_oldR
for n in range(len(total)):
pylab.figure(1)
ax = pylab.subplot(2, 4, n)
aba.plotFishXPosition(total[n])
pylab.show()
[tv, c_frac_stat] = scipy.stats.ttest_1samp(np.mean(c_frac, axis = 1), 0.5)
[tv, c_dist_stat] = scipy.stats.ttest_1samp(np.mean(c_dist, axis = 1), 24)
[t, time_diff_five] = scipy.stats.ttest_ind(np.mean(ef_frac,1), np.mean(c_frac,1))
[t, time_diff_old] = scipy.stats.ttest_ind(np.mean(et_frac,1), np.mean(c_frac,1))
[t, dist_diff_five] = scipy.stats.ttest_ind(np.mean(ef_dist,1), np.mean(c_dist,1))
[t, dist_diff_old] = scipy.stats.ttest_ind(np.mean(et_dist,1), np.mean(c_dist,1))
print 'BY ANIMAL 5 DPF Avoidance Post LH_5V (frac, distance): ', ef_frac_stat, ef_dist_stat
print 'BY ANIMAL 13 DPF Avoidance Post LH_5V (frac, distance): ', et_frac_stat, et_dist_stat
print 'BY ANIMAL Controls diff from Exper (time, dist) at 5 days: ', time_diff_five, dist_diff_five
print 'BY ANIMAL Controls diff from Exper (time, dist) at 13 days: ', time_diff_five, dist_diff_five
for n in range(len(f_fish)):
pylab.figure(n+10);
ax1 = pylab.subplot2grid((4,1),(0,0),rowspan=2);
aba.plotFishXPosition(f_fish[n])
ax = pylab.subplot2grid((4,1),(2,0),sharex=ax1);
[sh,s,d,dsh,ds,st] = aba.getSidePreference(f_fish[n], cond=[3,4], refState='On')
pylab.bar(st,np.array(s)/np.array(d),width=d)
pylab.axhline(.5,color='k')
pylab.ylabel('% time side1')
ax.set_yticks((0,.5,1))
ax = pylab.subplot2grid((4,1),(3,0),sharex=ax1);
pylab.bar(st,np.array(ds),width=d);
pylab.ylim((0,48))
pylab.axhline(24,color='k')
ax.set_yticks((0,24,48))
pylab.ylabel('Avg dist from\nside 1 (mm)')
pylab.xlabel('Time (s)')
"""
pylab.figure(5)
[tv, e_distRT2_stat] = scipy.stats.ttest_1samp(np.mean(e_distRT2, axis = 1), 24)
[tv, c_fracRT_stat] = scipy.stats.ttest_1samp(np.mean(c_fracRT, axis = 1), 0.5)
[tv, c_distRT_stat] = scipy.stats.ttest_1samp(np.mean(c_distRT, axis = 1), 24)
[t, time_diff] = scipy.stats.ttest_ind(np.mean(e_fracRT,axis = 1), np.mean(c_fracRT,1))
[t, dist_diff] = scipy.stats.ttest_ind(np.mean(e_distRT,axis = 1), np.mean(c_distRT,1))
print 'BY ANIMAL Avoidance Post LH_5V 14dpf (frac, distance): ', e_fracRT_stat, e_distRT_stat
print 'By ANIMAL Avoidance Post LH_5V 27dpf (frac, distance):', e_fracRT2_stat, e_distRT2_stat
print 'BY ANIMAL Avoidance Control: ', c_fracRT_stat, c_distRT_stat
print 'BY ANIMAL Controls diff from Exper (time, dist): ', time_diff, dist_diff
e_RTn = e_RT + e_RT2
for n in range(len(e_RTn)):
pylab.figure(n);
ax1 = pylab.subplot2grid((4,1),(0,0),rowspan=2)
aba.plotFishXPosition(e_RTn[n])
ax = pylab.subplot2grid((4,1),(2,0),sharex=ax1)
[sh,s,d,dsh,ds,st] = aba.getSidePreference(e_RTn[n], cond=[3,4], refState='On')
pylab.bar(st,np.array(s)/np.array(d),width=d)
pylab.axhline(.5,color='k')
pylab.ylabel('% time side1')
ax.set_yticks((0,.5,1))
ax = pylab.subplot2grid((4,1),(3,0),sharex=ax1);
pylab.bar(st,np.array(ds),width=d);
pylab.ylim((0,48))
pylab.axhline(24,color='k')
ax.set_yticks((0,24,48))
pylab.ylabel('Avg dist from\nside 1 (mm)')
pylab.xlabel('Time (s)')
pylab.show()
