def muscimol_plot_sound_type(animal,
muscimolSessions,
salineSessions,
soundType,
fontsize=12):
muscimolData = behavioranalysis.load_many_sessions(animal,
muscimolSessions)
trialsSoundTypeMus = muscimolData['soundType'] == muscimolData.labels[
'soundType'][soundType]
rightTrialsMus = (muscimolData['choice'] == muscimolData.labels['choice']
['right'])[trialsSoundTypeMus]
freqEachTrialMus = muscimolData['targetFrequency'][trialsSoundTypeMus]
validMus = muscimolData['valid'][trialsSoundTypeMus]
(possibleValues,fractionHitsEachValue,ciHitsEachValue,nTrialsEachValue,nHitsEachValue)=\
calculate_psychometric(rightTrialsMus,freqEachTrialMus,validMus)
(plineM, pcapsM, pbarsM,
pdotsM) = extraplots.plot_psychometric(1e-3 * possibleValues,
fractionHitsEachValue,
ciHitsEachValue,
xTickPeriod=1)
plt.xlabel('Frequency (kHz)', fontsize=fontsize)
plt.ylabel('Rightward trials (%)', fontsize=fontsize)
extraplots.set_ticks_fontsize(plt.gca(), fontsize)
setp(plineM, color='r')
setp(pcapsM, color='r')
setp(pbarsM, color='r')
setp(pdotsM, markerfacecolor='r')
salineData = behavioranalysis.load_many_sessions(animal, salineSessions)
trialsSoundTypeSal = salineData['soundType'] == salineData.labels[
'soundType'][soundType]
rightTrialsSal = (salineData['choice'] == salineData.labels['choice']
['right'])[trialsSoundTypeSal]
freqEachTrialSal = salineData['targetFrequency'][trialsSoundTypeSal]
validSal = salineData['valid'][trialsSoundTypeSal]
(possibleValues,fractionHitsEachValue,ciHitsEachValue,nTrialsEachValue,nHitsEachValue)=\
calculate_psychometric(rightTrialsSal,freqEachTrialSal,validSal)
(plineS, pcapsS, pbarsS,
pdotsS) = extraplots.plot_psychometric(1e-3 * possibleValues,
fractionHitsEachValue,
ciHitsEachValue,
xTickPeriod=1)
title("{}, {}".format(animal, soundType))
def muscimol_plot(animal, muscimolSessions, salineSessions):
muscimolData = behavioranalysis.load_many_sessions(animal,
muscimolSessions)
plineM, pcapsM, pbarsM, pdotsM = behavioranalysis.plot_frequency_psycurve(
muscimolData)
setp(plineM, color='r')
setp(pcapsM, color='r')
setp(pbarsM, color='r')
setp(pdotsM, markerfacecolor='r')
salineData = behavioranalysis.load_many_sessions(animal, salineSessions)
plineS, pcapsS, pbarsS, pdotsS = behavioranalysis.plot_frequency_psycurve(
salineData)
# setp(plineS, color='r')
# setp(pcapsS, color='r')
# setp(pbarsS, color='r')
# setp(pdotsS, markerfacecolor='r')
title(animal)
animal = 'adap027'
nAnimals = len(animals)
muscimolSessions = ['20160601a', '20160603a', '20160607a']
salineSessions = ['20160531a', '20160602a', '20160606a']
salChordEsts = np.zeros([len(salineSessions), 4])
musChordEsts = np.zeros([len(muscimolSessions), 4])
plt.figure()
for indSession, session in enumerate(salineSessions):
ax = subplot2grid((2, len(muscimolSessions)), (0, indSession))
sdata = behavioranalysis.load_many_sessions(animal, [session])
salChordEsts[indSession,:] = plot_psycurve_fit_and_data(sdata, 'k')
behavioranalysis.nice_psycurve_settings(ax, fontsize=9, lineweight=2)
plt.ylim(-0.03, 1.03)
for indSession, session in enumerate(muscimolSessions):
ax = subplot2grid((2, len(muscimolSessions)), (1, indSession))
mdata = behavioranalysis.load_many_sessions(animal, [session])
musChordEsts[indSession,:] = plot_psycurve_fit_and_data(mdata, 'r')
# title('{},{}'.format(animal, 'chords'))
plt.ylim(-0.03, 1.03)
behavioranalysis.nice_psycurve_settings(ax, fontsize=9, lineweight=2)
'adap022': ['20160601a', '20160603a', '20160607a', '20160609a', '20160611a'],
'adap026': ['20160601a', '20160603a', '20160607a', '20160609a', '20160611a'],
'adap027': ['20160601a', '20160603a', '20160607a', '20160609a', '20160611a'],
'adap030': ['20160601a', '20160603a', '20160607a', '20160609a', '20160611a']
}
salChordEsts = np.zeros([nAnimals, 4])
musChordEsts = np.zeros([nAnimals, 4])
for indAnimal, animal in enumerate(animals):
# ax = subplot2grid((1, nAnimals), (0, indAnimal))
ax = subplot(2, 3, indAnimal)
mdata = behavioranalysis.load_many_sessions(animal, muscimolSessions[animal])
sdata = behavioranalysis.load_many_sessions(animal, salineSessions[animal])
musChordEsts[indAnimal,:] = behavioranalysis.plot_psycurve_fit_and_data(mdata, 'r')
salChordEsts[indAnimal,:] = behavioranalysis.plot_psycurve_fit_and_data(sdata, 'k')
plt.ylim(-0.03, 1.03)
behavioranalysis.nice_psycurve_settings(ax, fontsize=9, lineweight=2, fitlineinds=[3, 7])
title(animal)
mc = musChordEsts[:,1]
sc = salChordEsts[:,1]
figure()
return percentCorrectSoundType * 100
clf()
animal = 'amod003'
muscimolSessions = ['20160413a', '20160415a', '20160417a', '20160419a']
salineSessions = ['20160412a', '20160414a', '20160416a', '20160418a']
subplot(221)
muscimol_plot_sound_type(animal, muscimolSessions, salineSessions, 'chords')
subplot(223)
muscimol_plot_sound_type(animal, muscimolSessions, salineSessions, 'amp_mod')
#Overall muscimol and saline performance
muscimolData = behavioranalysis.load_many_sessions(animal, muscimolSessions)
muscimolChords = percent_correct_sound_type(muscimolData, 'chords')
muscimolMod = percent_correct_sound_type(muscimolData, 'amp_mod')
salineData = behavioranalysis.load_many_sessions(animal, salineSessions)
salineChords = percent_correct_sound_type(salineData, 'chords')
salineMod = percent_correct_sound_type(salineData, 'amp_mod')
#Individual session muscimol and saline performance
for indp, pair in enumerate(zip(salineSessions, muscimolSessions)):
salineFile = loadbehavior.path_to_behavior_data(
animal, settings.DEFAULT_EXPERIMENTER, '2afc', pair[0])
salineData = loadbehavior.BehaviorData(salineFile, readmode='full')
from jaratest.nick import behavioranalysis_vnick as behavioranalysis
'''
Test data analysis for adap023 - this needs work because all of my muscimol overview reports are currently written for data with different sound types
As part of this work, I need to work on my behavioranalysis fxns
'''
# behavior_summary('adap023', ['20160426a', '20160427a','20160428a','20160429a', '20160430a', '20160501a', '20160502a', '20160503a', '20160504b','20160505a','20160506a','20160507a','20160508a','20160509a', '20160510a']) #left
## -- Plotting the average saline and muscimol psycurves
#NOTE THE b in 0504 below
salineSessions = [
'20160428a', '20160430a', '20160502a', '20160504b', '20160506a',
'20160508a'
]
muscimolSessions = [
'20160429a', '20160501a', '20160503a', '20160505a', '20160507a',
'20160509a'
]
salineData = behavioranalysis.load_many_sessions('adap023', salineSessions)
muscimolData = behavioranalysis.load_many_sessions('adap023', muscimolSessions)
behavioranalysis.plot_multiple_psycurves([salineData, muscimolData],
['k', 'r'])
