def criteria(self, hit=False, fa=False):
data = self.data
amnesic_fa = data.iloc[0][::-1]
control_fa = data.iloc[3][::-1]
amnesic_fa = amnesic_fa[:-1]
control_fa = control_fa[:-1]
amnesic_hit = data.iloc[1][::-1]
control_hit = data.iloc[4][::-1]
amnesic_hit = amnesic_hit[:-1]
control_hit = control_hit[:-1]
if fa:
fig, ax = plt.subplots(1, 1)
ax.plot(np.arange(1, 7, 1), np.cumsum(amnesic_fa), 'ro-')
ax.plot(np.arange(1, 7, 1), np.cumsum(control_fa), 'go-')
ax.plot()
ax.set_title(self.name, fontsize=16)
ax.set_ylabel('False alarms', fontsize=16)
ax.set_xlabel('Threshold', fontsize=16)
set_aspect(ax)
if hit:
fig, ax = plt.subplots(1, 1)
ax.plot(np.arange(1, 7, 1), np.cumsum(amnesic_hit), 'ro-')
ax.plot(np.arange(1, 7, 1), np.cumsum(control_hit), 'go-')
ax.set_title(self.name, fontsize=16)
ax.set_ylabel('Hits', fontsize=16)
ax.set_xlabel('Threshold', fontsize=16)
set_aspect(ax)
def F_and_R(self):
data = self.data
F_time = normalize_F(data.iloc[:5][:]['F'])
R_time = data.iloc[:5][:]['R']
cond = data.iloc[:5][:]['Condition']
fig, ax = plt.subplots(1, 1)
ax.plot(F_time, 'go-', label='F')
ax.plot(R_time, 'bo-', label='R')
plt.xticks(range(len(cond)), cond, fontsize=14)
ax.legend(prop={'size': 15})
ax.set_title(self.name, fontsize=15)
set_aspect(ax)
def plot_results(self, experiment):
fig, axes = plt.subplots(1, 3, figsize=(10, 10))
hits = self.data[experiment]['hits']
fa = self.data[experiment]['fa']
markers = ['go--', 'ro--', 'go-', 'ro-']
for ind, item in enumerate(self.keys):
axes[0].plot(hits[item], markers[ind], label=item)
axes[1].plot(fa[item], markers[ind], label=item)
axes[2].plot(fa[item], hits[item], markers[ind], label=item)
# axis_default(axes[0],'Criterion','Hit rate',legend=True,limit=[[0,len(hits[item])],[0,1]])
# axis_default(axes[1],'Criterion','False alarm rate',limit=[[0,len(fa[item])],[0,1]],legend=False)
# axis_default(axes[2],'False alarm rate','Hit rate',limit=[[0,1],[0,1]],legend=False)
[set_aspect(ax) for ax in axes]
fig.tight_layout()
fig.suptitle('Ratcliff et al. 1992 ' + experiment, fontsize=15, y=.75)
def plot_experiment(self, experiment):
experiment -= 1
exp = self.experiments[experiment]
fig, axes = plt.subplots(1, 2, figsize=(8, 8))
hit = self.data.loc[experiment, self.hit_keys]
fa = self.data.loc[experiment, self.fa_keys]
hit.plot.bar(ax=axes[0],
x='lab',
y='val',
rot=0,
colors=['g', 'g', 'crimson', 'crimson'])
fa.plot.bar(ax=axes[1],
x='lab',
y='val',
rot=0,
colors=['g', 'g', 'crimson', 'crimson'])
# axis_default(axes[0],' ','Hit rate',legend=False,limit=[[None,None],[0,1]],ticks=False)
# axis_default(axes[1],' ','False alarm rate',legend=False,limit=[[None,None],[0,1]],ticks=False)
[set_aspect(ax) for ax in axes]
fig.tight_layout()
fig.suptitle(self.name + ': experiment ' + str(exp) + '*',
fontsize=15,
y=.75)
plt.gcf().text(0.1, .2, '*' + self.notes[experiment], fontsize=14)
#fits=['Rn:0','Rn:0','Rn:0','Rn:0']
fits = ['Full', 'Rn:0', 'Full', 'Full']
fig, ax = plt.subplots(1, 1)
m = -1
o = 0
nn = 0
for index, simID in enumerate(IDs):
params = pickle.load(open(path1 + '/Log/metadata_' + simID + '.pkl', "rb"))
params.data_dir = update_path(path1, params.data_dir)
params.data_dir = "/".join(params.data_dir.split(os.sep)[:9]) + '/'
params.path = update_path(path1, params.path)
mat = matlab(params)
data, conds = mat.load_dpsd(fit=fits[index])
ax.plot(data[o][m]['fa'][0][nn],
data[o][m]['hits'][0][nn],
'o',
color=colors[index],
alpha=0.6)
# ax.plot(data[o][0]['fa'][nn][0],data[o][0]['hits'][nn][0],'ro')
ax.plot(data[o][m]['roc_fa'][m][:, nn],
data[o][m]['roc_hit'][0][:, nn],
'b',
color=colors[index],
linestyle=markers[index],
label='Set ' + labels[index])
# ax.plot(data[o][0]['roc_fa'][0][:,nn],data[o][0]['roc_hit'][0][:,nn],'r',linestyle=markers[index])
ax.plot([0, 1], [0, 1], 'k--')
set_aspect(ax)
axis_default(ax, 'False alarm rate', 'Hit rate', legend=True)
fig.savefig('related_unrelated.eps')
lures=[]
for ind, folder in enumerate(folders):
directory=input_dir+folder+'/'
filenames=sorted([item for item in os.listdir(directory) if item[-3:]=='pkl'])
data=[pd.read_pickle(directory+file) for file in filenames]
targ=get_data(data[m],'target',o,nn)
lure=get_data(data[m],'lure',o,nn)
targs.append(targ)
lures.append(lure)
hit=calc_rates(targ,params.N_t)
fa=calc_rates(lure,params.N_t)
ax.plot(fa,hit,'o-',label=folder)
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.legend()
set_aspect(ax)
targs_average=np.mean(targs[:10],axis=0)
lure_average=np.mean(lures[:10],axis=0)
hit_average=calc_rates(targs_average,params.N_t)
fa_average=calc_rates(lure_average,params.N_t)
axis.plot(fa_average,hit_average,'o-')
axis.plot([0,1],[0,1],'k--')
axis.set_xlim(0,1)
axis.set_ylim(0,1)
set_aspect(axis)
sys.exit()
#figure,axis=plt.subplots(1,1)
#for noise_ind in range(len(params.noise)):
strong_hits = [.38, .60, .64, .70, .82]
strong_sp = [.14, .30, .36, .43, .64]
strong_ur = [.02, .06, .09, .19, .41]
fig, axes = plt.subplots(1, 3)
axes[0].plot(weak_hits, 'ro-')
axes[0].plot(strong_hits, 'go-')
axes[1].plot(weak_sp, 'ro-')
axes[1].plot(strong_sp, 'go-')
axes[2].plot(weak_ur, 'ro-')
axes[2].plot(strong_ur, 'go-')
axes[0].set_title('Hit rates')
axes[1].set_title('SP false alarms')
axes[2].set_title('UL false alarms')
[set_aspect(ax) for ax in axes]
fig.tight_layout()
fig1, axes1 = plt.subplots(1, 3)
axes1[0].plot(weak_ur, weak_hits, 'ro-')
axes1[0].plot(strong_ur, strong_hits, 'go-')
axes1[1].plot(weak_sp, weak_hits, 'ro-')
axes1[1].plot(strong_sp, strong_hits, 'go-')
axes1[2].plot(weak_ur, weak_sp, 'ro-')
axes1[2].plot(strong_ur, strong_sp, 'go-')
axes1[0].set_title('ROC for UL')
axes1[1].set_title('ROC for SP**')
axes1[2].set_title('ROC UL vs SP**')
[set_aspect(ax) for ax in axes1]
fig1.tight_layout()
calc_rates(data_strong_hip['lure'], params.N_t)
]
labels = ['weak', 'mixed', 'strong']
titles = ['cort_hit_rate', 'cort_false_rate', 'hip_hit_rate', 'hip_false_rate']
data_all = [cort_hit_rate, cort_false_rate, hip_hit_rate, hip_false_rate]
fig1, axes = plt.subplots(2, 2)
axes = axes.flatten()
for i, data in enumerate(data_all):
ax = axes[i]
[
ax.plot(threshold[:-1], item[:-1], 'o-', label=labels[ind])
and ax.legend() and ax.set_ylabel(titles[i])
and ax.set_xlabel('threshold') and ax.set_ybound(0, 1.1)
and set_aspect(ax) for ind, item in enumerate(data)
]
# ax.set_aspect('equal')
fig1.tight_layout()
#fig2,axes=plt.subplots(2,2)
#axes=axes.flatten()
#for i, data in enumerate(data_all):
# ax=axes[i]
# ax.plot([1,2,3],[data[0][0],data[1][0],data[2][0]], 'o-', label='threshold 1')
# ax.plot([1,2,3],[data[0][1],data[1][1],data[2][1]], 'o-', label='threshold 2')
# ax.set_ylabel(titles[i])
# ax.set_ybound(0,0.9)
# ax.legend()
# ax.set_xticks([1,2,3])
# ax.set_xticklabels(labels)