def plot_l1_pos_l2_zero_bayes_marginals(summary_file_name, y_max=0.3):
summary_data = SummaryData()
summary_data.read_from_file(summary_file_name)
bayes_analysis = run_bayesian_analysis(
summary_data.auc, summary_data.bc_slope, summary_data.bc_intercept,
summary_data.bc_r_sqr, summary_data.num_trials,
summary_data.p_b_e_range, summary_data.p_e_e_range,
summary_data.p_e_i_range, summary_data.p_i_e_range,
summary_data.p_i_i_range, summary_data.p_x_e_range)
fig = plt.figure()
param_step = summary_data.p_e_e_range[1] - summary_data.p_e_e_range[0]
bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_e_e[
bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_e_e == 0] = 1e-7
plt.bar(
np.array(summary_data.p_e_e_range) - .5 * param_step,
bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_e_e, param_step)
plt.xlabel('p_e_e')
plt.ylabel('p(p_e_e|A,M)')
plt.ylim(0.0, y_max)
fig = plt.figure()
param_step = summary_data.p_e_i_range[1] - summary_data.p_e_i_range[0]
bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_e_i[
bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_e_i == 0] = 1e-7
plt.bar(
np.array(summary_data.p_e_i_range) - .5 * param_step,
bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_e_i, param_step)
plt.xlabel('p_e_i')
plt.ylabel('p(p_e_i|A,M)')
plt.ylim(0.0, y_max)
fig = plt.figure()
param_step = summary_data.p_i_i_range[1] - summary_data.p_i_i_range[0]
bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_i_i[
bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_i_i == 0] = 1e-7
plt.bar(
np.array(summary_data.p_i_i_range) - .5 * param_step,
bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_i_i, param_step)
plt.xlabel('p_i_i')
plt.ylabel('p(p_i_i|A,M)')
plt.ylim(0.0, y_max)
fig = plt.figure()
param_step = summary_data.p_i_e_range[1] - summary_data.p_i_e_range[0]
bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_i_e[
bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_i_e == 0] = 1e-7
plt.bar(
np.array(summary_data.p_i_e_range) - .5 * param_step,
bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_i_e, param_step)
plt.xlabel('p_i_e')
plt.ylabel('p(p_i_e|A,M)')
plt.ylim(0.0, y_max)
plt.show()
def regenerate_bayesian_figures(summary_filename, reports_dir):
summary_data=SummaryData()
summary_data.read_from_file(summary_filename)
bayes_analysis=run_bayesian_analysis(summary_data.auc, summary_data.bc_slope, summary_data.bc_intercept,
summary_data.bc_r_sqr, summary_data.num_trials, summary_data.p_b_e_range, summary_data.p_e_e_range,
summary_data.p_e_i_range, summary_data.p_i_e_range, summary_data.p_i_i_range, summary_data.p_x_e_range)
p_b_e_range=summary_data.p_b_e_range
p_x_e_range=summary_data.p_x_e_range
p_e_e_range=summary_data.p_e_e_range
p_e_i_range=summary_data.p_e_i_range
p_i_i_range=summary_data.p_i_i_range
p_i_e_range=summary_data.p_i_e_range
marginal_list=[bayes_analysis.l1_pos_marginals, bayes_analysis.l1_neg_marginals,
bayes_analysis.l1_pos_l2_neg_marginals, bayes_analysis.l1_neg_l2_neg_marginals,
bayes_analysis.l1_pos_l2_pos_marginals, bayes_analysis.l1_neg_l2_pos_marginals,
bayes_analysis.l1_pos_l2_zero_marginals, bayes_analysis.l1_neg_l2_zero_marginals]
file_prefix_list=['l1_pos','l1_neg','l1_pos_l2_neg','l1_neg_l2_neg','l1_pos_l2_pos','l1_neg_l2_pos','l1_pos_l2_zero',
'l1_neg_l2_zero']
for(marginals,file_prefix) in zip(marginal_list,file_prefix_list):
render_joint_marginal_report('p_b_e', 'p_x_e', p_b_e_range, p_x_e_range, marginals.posterior_p_b_e_p_x_e, file_prefix,
reports_dir)
render_joint_marginal_report('p_e_e', 'p_e_i', p_e_e_range, p_e_i_range, marginals.posterior_p_e_e_p_e_i, file_prefix,
reports_dir)
render_joint_marginal_report('p_e_e', 'p_i_i', p_e_e_range, p_i_i_range, marginals.posterior_p_e_e_p_i_i, file_prefix,
reports_dir)
render_joint_marginal_report('p_e_e', 'p_i_e', p_e_e_range, p_i_e_range, marginals.posterior_p_e_e_p_i_e, file_prefix,
reports_dir)
render_joint_marginal_report('p_e_i', 'p_i_i', p_e_i_range, p_i_i_range, marginals.posterior_p_e_i_p_i_i, file_prefix,
reports_dir)
render_joint_marginal_report('p_e_i', 'p_i_e', p_e_i_range, p_i_e_range, marginals.posterior_p_e_i_p_i_e, file_prefix,
reports_dir)
render_joint_marginal_report('p_i_i', 'p_i_e', p_i_i_range, p_i_e_range, marginals.posterior_p_i_i_p_i_e, file_prefix,
reports_dir)
def plot_l1_pos_l2_zero_bayes_marginals(summary_file_name, y_max=0.3):
summary_data=SummaryData()
summary_data.read_from_file(summary_file_name)
bayes_analysis=run_bayesian_analysis(summary_data.auc, summary_data.bc_slope, summary_data.bc_intercept,
summary_data.bc_r_sqr, summary_data.num_trials, summary_data.p_b_e_range, summary_data.p_e_e_range,
summary_data.p_e_i_range, summary_data.p_i_e_range, summary_data.p_i_i_range, summary_data.p_x_e_range)
fig = plt.figure()
param_step=summary_data.p_e_e_range[1]-summary_data.p_e_e_range[0]
bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_e_e[bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_e_e==0]=1e-7
plt.bar(np.array(summary_data.p_e_e_range) - .5*param_step, bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_e_e, param_step)
plt.xlabel('p_e_e')
plt.ylabel('p(p_e_e|A,M)')
plt.ylim(0.0,y_max)
fig = plt.figure()
param_step=summary_data.p_e_i_range[1]-summary_data.p_e_i_range[0]
bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_e_i[bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_e_i==0]=1e-7
plt.bar(np.array(summary_data.p_e_i_range) - .5*param_step, bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_e_i, param_step)
plt.xlabel('p_e_i')
plt.ylabel('p(p_e_i|A,M)')
plt.ylim(0.0,y_max)
fig = plt.figure()
param_step=summary_data.p_i_i_range[1]-summary_data.p_i_i_range[0]
bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_i_i[bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_i_i==0]=1e-7
plt.bar(np.array(summary_data.p_i_i_range) - .5*param_step, bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_i_i, param_step)
plt.xlabel('p_i_i')
plt.ylabel('p(p_i_i|A,M)')
plt.ylim(0.0,y_max)
fig = plt.figure()
param_step=summary_data.p_i_e_range[1]-summary_data.p_i_e_range[0]
bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_i_e[bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_i_e==0]=1e-7
plt.bar(np.array(summary_data.p_i_e_range) - .5*param_step, bayes_analysis.l1_pos_l2_zero_marginals.posterior_p_i_e, param_step)
plt.xlabel('p_i_e')
plt.ylabel('p(p_i_e|A,M)')
plt.ylim(0.0,y_max)
plt.show()
def create_all_reports(data_dir,
num_groups,
trial_duration,
p_b_e_range,
p_x_e_range,
p_e_e_range,
p_e_i_range,
p_i_i_range,
p_i_e_range,
contrast_range,
num_trials,
e_desc,
base_report_dir,
regenerate_network_plots=True,
regenerate_trial_plots=True,
smooth_missing_params=False,
summary_filename='wta_network_summary.h5'):
make_report_dirs(base_report_dir)
summary_data = SummaryData(num_groups=num_groups,
num_trials=num_trials,
trial_duration=trial_duration,
p_b_e_range=p_b_e_range,
p_x_e_range=p_x_e_range,
p_e_e_range=p_e_e_range,
p_e_i_range=p_e_i_range,
p_i_i_range=p_i_i_range,
p_i_e_range=p_i_e_range)
bc_slope_dict = {}
bc_intercept_dict = {}
bc_r_sqr_dict = {}
auc_dict = {}
bfr_slope_dict = {}
bfr_intercept_dict = {}
bfr_r_sqr_dict = {}
param_combos = get_tested_param_combos(data_dir, num_groups,
trial_duration, contrast_range,
num_trials, e_desc)
report_info = Struct()
report_info.edesc = e_desc
report_info.roc_auc = {}
report_info.bc_slope = {}
report_info.bc_intercept = {}
report_info.bc_r_sqr = {}
report_info.bfr_slope = {}
report_info.bfr_intercept = {}
report_info.bfr_r_sqr = {}
for (p_b_e, p_x_e, p_e_e, p_e_i, p_i_i, p_i_e) in param_combos:
if p_b_e in p_b_e_range and p_x_e in p_x_e_range and p_e_e in p_e_e_range and p_e_i in p_e_i_range and p_i_i in p_i_i_range and p_i_e in p_i_e_range:
i = p_b_e_range.index(round(p_b_e, 3))
j = p_x_e_range.index(round(p_x_e, 3))
k = p_e_e_range.index(round(p_e_e, 3))
l = p_e_i_range.index(round(p_e_i, 3))
m = p_i_i_range.index(round(p_i_i, 3))
n = p_i_e_range.index(round(p_i_e, 3))
file_desc='wta.groups.%d.duration.%0.3f.p_b_e.%0.3f.p_x_e.%0.3f.p_e_e.%0.3f.p_e_i.%0.3f.p_i_i.%0.3f.p_i_e.%0.3f.%s' %\
(num_groups, trial_duration, p_b_e, p_x_e, p_e_e, p_e_i, p_i_i, p_i_e, e_desc)
file_prefix = os.path.join(data_dir, file_desc)
reports_dir = os.path.join(base_report_dir, file_desc)
if all_trials_exist(file_prefix, contrast_range, num_trials):
print('Creating report for %s' % file_desc)
wta_report = create_wta_network_report(
file_prefix,
contrast_range,
num_trials,
reports_dir,
e_desc,
regenerate_network_plots=regenerate_network_plots,
regenerate_trial_plots=regenerate_trial_plots)
if not (i, j, k, l, m, n) in bc_slope_dict:
bc_slope_dict[(i, j, k, l, m, n)] = []
bc_slope_dict[(i, j, k, l, m,
n)].append(wta_report.bold.bold_contrast_slope)
if not (i, j, k, l, m, n) in bc_intercept_dict:
bc_intercept_dict[(i, j, k, l, m, n)] = []
bc_intercept_dict[(i, j, k, l, m, n)].append(
wta_report.bold.bold_contrast_intercept)
if not (i, j, k, l, m, n) in bc_r_sqr_dict:
bc_r_sqr_dict[(i, j, k, l, m, n)] = []
bc_r_sqr_dict[(i, j, k, l, m,
n)].append(wta_report.bold.bold_contrast_r_sqr)
if not (i, j, k, l, m, n) in auc_dict:
auc_dict[(i, j, k, l, m, n)] = []
auc_dict[(i, j, k, l, m, n)].append(wta_report.roc.auc)
if not (i, j, k, l, m, n) in bfr_slope_dict:
bfr_slope_dict[(i, j, k, l, m, n)] = []
bfr_slope_dict[(i, j, k, l, m, n)].append(
wta_report.bold.bold_firing_rate_slope)
if not (i, j, k, l, m, n) in bfr_intercept_dict:
bfr_intercept_dict[(i, j, k, l, m, n)] = []
bfr_intercept_dict[(i, j, k, l, m, n)].append(
wta_report.bold.bold_firing_rate_intercept)
if not (i, j, k, l, m, n) in bfr_r_sqr_dict:
bfr_r_sqr_dict[(i, j, k, l, m, n)] = []
bfr_r_sqr_dict[(i, j, k, l, m, n)].append(
wta_report.bold.bold_firing_rate_r_sqr)
report_info.roc_auc[(p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = wta_report.roc.auc
report_info.bc_slope[(
p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = wta_report.bold.bold_contrast_slope
report_info.bc_intercept[(
p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = wta_report.bold.bold_contrast_intercept
report_info.bc_r_sqr[(
p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = wta_report.bold.bold_contrast_r_sqr
report_info.bfr_slope[(
p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = wta_report.bold.bold_firing_rate_slope
report_info.bfr_intercept[(
p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = wta_report.bold.bold_firing_rate_intercept
report_info.bfr_r_sqr[(
p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = wta_report.bold.bold_firing_rate_r_sqr
else:
report_info.roc_auc[(p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = 0
report_info.bc_slope[(p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = 0
report_info.bc_intercept[(p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = 0
report_info.bc_r_sqr[(p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = 0
report_info.bfr_slope[(p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = 0
report_info.bfr_intercept[(p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = 0
report_info.brf_r_sqr[(p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = 0
report_info.num_groups = num_groups
report_info.trial_duration = trial_duration
report_info.num_trials = num_trials
report_info.p_b_e_range = p_b_e_range
report_info.p_x_e_range = p_x_e_range
report_info.p_e_e_range = p_e_e_range
report_info.p_e_i_range = p_e_i_range
report_info.p_i_i_range = p_i_i_range
report_info.p_i_e_range = p_i_e_range
summary_data.fill(auc_dict,
bc_slope_dict,
bc_intercept_dict,
bc_r_sqr_dict,
bfr_slope_dict,
bfr_intercept_dict,
bfr_r_sqr_dict,
smooth_missing_params=smooth_missing_params)
summary_data.write_to_file(os.path.join(base_report_dir, summary_filename))
bc_bayes_analysis = run_bayesian_analysis(
summary_data.auc, summary_data.bc_slope, summary_data.bc_intercept,
summary_data.bc_r_sqr, num_trials, p_b_e_range, p_e_e_range,
p_e_i_range, p_i_e_range, p_i_i_range, p_x_e_range)
bfr_bayes_analysis = run_bayesian_analysis(
summary_data.auc, summary_data.bfr_slope, summary_data.bfr_intercept,
summary_data.bfr_r_sqr, num_trials, p_b_e_range, p_e_e_range,
p_e_i_range, p_i_e_range, p_i_i_range, p_x_e_range)
bc_base_dir = os.path.join(base_report_dir, 'bold-contrast')
make_report_dirs(bc_base_dir)
render_summary_report(bc_base_dir, bc_bayes_analysis, p_b_e_range,
p_e_e_range, p_e_i_range, p_i_e_range, p_i_i_range,
p_x_e_range, report_info)
bfr_base_dir = os.path.join(base_report_dir, 'bold-firing_rate')
make_report_dirs(bfr_base_dir)
render_summary_report(bfr_base_dir, bfr_bayes_analysis, p_b_e_range,
p_e_e_range, p_e_i_range, p_i_e_range, p_i_i_range,
p_x_e_range, report_info)
def create_summary_report(summary_file_name, base_report_dir, e_desc):
make_report_dirs(base_report_dir)
summary_data=SummaryData()
summary_data.read_from_file(summary_file_name)
report_info=Struct()
report_info.edesc=e_desc
report_info.roc_auc={}
report_info.io_slope={}
report_info.io_intercept={}
report_info.io_r_sqr={}
report_info.bc_slope={}
report_info.bc_intercept={}
report_info.bc_r_sqr={}
report_info.bfr_slope={}
report_info.bfr_intercept={}
report_info.bfr_r_sqr={}
for i,p_b_e in enumerate(summary_data.p_b_e_range):
for j,p_x_e in enumerate(summary_data.p_x_e_range):
for k,p_e_e in enumerate(summary_data.p_e_e_range):
for l,p_e_i in enumerate(summary_data.p_e_i_range):
for m,p_i_i in enumerate(summary_data.p_i_i_range):
for n,p_i_e in enumerate(summary_data.p_i_e_range):
if summary_data.auc[i,j,k,l,m,n]>0:
report_info.roc_auc[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=summary_data.auc[i,j,k,l,m,n]
report_info.bc_slope[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=summary_data.bc_slope[i,j,k,l,m,n]
report_info.bc_intercept[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=summary_data.bc_intercept[i,j,k,l,m,n]
report_info.bc_r_sqr[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=summary_data.bc_r_sqr[i,j,k,l,m,n]
report_info.bfr_slope[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=summary_data.bfr_slope[i,j,k,l,m,n]
report_info.bfr_intercept[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=summary_data.bfr_intercept[i,j,k,l,m,n]
report_info.bfr_r_sqr[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=summary_data.bfr_r_sqr[i,j,k,l,m,n]
else:
report_info.roc_auc[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=0
report_info.bc_slope[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=0
report_info.bc_intercept[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=0
report_info.bc_r_sqr[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=0
report_info.bfr_slope[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=0
report_info.bfr_intercept[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=0
report_info.bfr_r_sqr[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=0
report_info.num_groups=summary_data.num_groups
report_info.trial_duration=summary_data.trial_duration
report_info.num_trials=summary_data.num_trials
report_info.p_b_e_range=summary_data.p_b_e_range
report_info.p_x_e_range=summary_data.p_x_e_range
report_info.p_e_e_range=summary_data.p_e_e_range[:-1]
report_info.p_e_i_range=summary_data.p_e_i_range
report_info.p_i_i_range=summary_data.p_i_i_range
report_info.p_i_e_range=summary_data.p_i_e_range
bc_bayes_analysis=run_bayesian_analysis(summary_data.auc, summary_data.bc_slope, summary_data.bc_intercept,
summary_data.bc_r_sqr, summary_data.num_trials, summary_data.p_b_e_range, summary_data.p_e_e_range,
summary_data.p_e_i_range, summary_data.p_i_e_range, summary_data.p_i_i_range, summary_data.p_x_e_range)
bfr_bayes_analysis=run_bayesian_analysis(summary_data.auc, summary_data.bfr_slope, summary_data.bfr_intercept,
summary_data.bfr_r_sqr, summary_data.num_trials, summary_data.p_b_e_range, summary_data.p_e_e_range,
summary_data.p_e_i_range, summary_data.p_i_e_range, summary_data.p_i_i_range, summary_data.p_x_e_range)
bc_base_dir=os.path.join(base_report_dir, 'bold-contrast')
make_report_dirs(bc_base_dir)
render_summary_report(bc_base_dir, bc_bayes_analysis, summary_data.p_b_e_range, summary_data.p_e_e_range,
summary_data.p_e_i_range, summary_data.p_i_e_range, summary_data.p_i_i_range, summary_data.p_x_e_range,
report_info)
bfr_base_dir=os.path.join(base_report_dir, 'bold-firing_rate')
make_report_dirs(bfr_base_dir)
render_summary_report(bfr_base_dir, bfr_bayes_analysis, summary_data.p_b_e_range, summary_data.p_e_e_range,
summary_data.p_e_i_range, summary_data.p_i_e_range, summary_data.p_i_i_range, summary_data.p_x_e_range,
report_info)
def create_all_reports(data_dir, num_groups, trial_duration, p_b_e_range, p_x_e_range, p_e_e_range, p_e_i_range,
p_i_i_range, p_i_e_range, contrast_range, num_trials, e_desc, base_report_dir, regenerate_network_plots=True,
regenerate_trial_plots=True, smooth_missing_params=False,
summary_filename='wta_network_summary.h5'):
make_report_dirs(base_report_dir)
summary_data=SummaryData(num_groups=num_groups, num_trials=num_trials, trial_duration=trial_duration,
p_b_e_range=p_b_e_range, p_x_e_range=p_x_e_range, p_e_e_range=p_e_e_range, p_e_i_range=p_e_i_range,
p_i_i_range=p_i_i_range, p_i_e_range=p_i_e_range)
bc_slope_dict={}
bc_intercept_dict={}
bc_r_sqr_dict={}
auc_dict={}
bfr_slope_dict={}
bfr_intercept_dict={}
bfr_r_sqr_dict={}
param_combos=get_tested_param_combos(data_dir, num_groups, trial_duration, contrast_range, num_trials, e_desc)
report_info=Struct()
report_info.edesc=e_desc
report_info.roc_auc={}
report_info.bc_slope={}
report_info.bc_intercept={}
report_info.bc_r_sqr={}
report_info.bfr_slope={}
report_info.bfr_intercept={}
report_info.bfr_r_sqr={}
for (p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e) in param_combos:
if p_b_e in p_b_e_range and p_x_e in p_x_e_range and p_e_e in p_e_e_range and p_e_i in p_e_i_range and p_i_i in p_i_i_range and p_i_e in p_i_e_range:
i=p_b_e_range.index(round(p_b_e,3))
j=p_x_e_range.index(round(p_x_e,3))
k=p_e_e_range.index(round(p_e_e,3))
l=p_e_i_range.index(round(p_e_i,3))
m=p_i_i_range.index(round(p_i_i,3))
n=p_i_e_range.index(round(p_i_e,3))
file_desc='wta.groups.%d.duration.%0.3f.p_b_e.%0.3f.p_x_e.%0.3f.p_e_e.%0.3f.p_e_i.%0.3f.p_i_i.%0.3f.p_i_e.%0.3f.%s' %\
(num_groups, trial_duration, p_b_e, p_x_e, p_e_e, p_e_i, p_i_i, p_i_e, e_desc)
file_prefix=os.path.join(data_dir,file_desc)
reports_dir=os.path.join(base_report_dir,file_desc)
if all_trials_exist(file_prefix, contrast_range, num_trials):
print('Creating report for %s' % file_desc)
wta_report=create_wta_network_report(file_prefix, contrast_range, num_trials, reports_dir,
e_desc, regenerate_network_plots=regenerate_network_plots, regenerate_trial_plots=regenerate_trial_plots)
if not (i,j,k,l,m,n) in bc_slope_dict:
bc_slope_dict[(i,j,k,l,m,n)]=[]
bc_slope_dict[(i,j,k,l,m,n)].append(wta_report.bold.bold_contrast_slope)
if not (i,j,k,l,m,n) in bc_intercept_dict:
bc_intercept_dict[(i,j,k,l,m,n)]=[]
bc_intercept_dict[(i,j,k,l,m,n)].append(wta_report.bold.bold_contrast_intercept)
if not (i,j,k,l,m,n) in bc_r_sqr_dict:
bc_r_sqr_dict[(i,j,k,l,m,n)]=[]
bc_r_sqr_dict[(i,j,k,l,m,n)].append(wta_report.bold.bold_contrast_r_sqr)
if not (i,j,k,l,m,n) in auc_dict:
auc_dict[(i,j,k,l,m,n)]=[]
auc_dict[(i,j,k,l,m,n)].append(wta_report.roc.auc)
if not (i,j,k,l,m,n) in bfr_slope_dict:
bfr_slope_dict[(i,j,k,l,m,n)]=[]
bfr_slope_dict[(i,j,k,l,m,n)].append(wta_report.bold.bold_firing_rate_slope)
if not (i,j,k,l,m,n) in bfr_intercept_dict:
bfr_intercept_dict[(i,j,k,l,m,n)]=[]
bfr_intercept_dict[(i,j,k,l,m,n)].append(wta_report.bold.bold_firing_rate_intercept)
if not (i,j,k,l,m,n) in bfr_r_sqr_dict:
bfr_r_sqr_dict[(i,j,k,l,m,n)]=[]
bfr_r_sqr_dict[(i,j,k,l,m,n)].append(wta_report.bold.bold_firing_rate_r_sqr)
report_info.roc_auc[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=wta_report.roc.auc
report_info.bc_slope[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=wta_report.bold.bold_contrast_slope
report_info.bc_intercept[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=wta_report.bold.bold_contrast_intercept
report_info.bc_r_sqr[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=wta_report.bold.bold_contrast_r_sqr
report_info.bfr_slope[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=wta_report.bold.bold_firing_rate_slope
report_info.bfr_intercept[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=wta_report.bold.bold_firing_rate_intercept
report_info.bfr_r_sqr[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=wta_report.bold.bold_firing_rate_r_sqr
else:
report_info.roc_auc[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=0
report_info.bc_slope[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=0
report_info.bc_intercept[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=0
report_info.bc_r_sqr[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=0
report_info.bfr_slope[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=0
report_info.bfr_intercept[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=0
report_info.brf_r_sqr[(p_b_e,p_x_e,p_e_e,p_e_i,p_i_i,p_i_e)]=0
report_info.num_groups=num_groups
report_info.trial_duration=trial_duration
report_info.num_trials=num_trials
report_info.p_b_e_range=p_b_e_range
report_info.p_x_e_range=p_x_e_range
report_info.p_e_e_range=p_e_e_range
report_info.p_e_i_range=p_e_i_range
report_info.p_i_i_range=p_i_i_range
report_info.p_i_e_range=p_i_e_range
summary_data.fill(auc_dict, bc_slope_dict, bc_intercept_dict, bc_r_sqr_dict, bfr_slope_dict, bfr_intercept_dict,
bfr_r_sqr_dict, smooth_missing_params=smooth_missing_params)
summary_data.write_to_file(os.path.join(base_report_dir,summary_filename))
bc_bayes_analysis=run_bayesian_analysis(summary_data.auc, summary_data.bc_slope, summary_data.bc_intercept,
summary_data.bc_r_sqr, num_trials, p_b_e_range, p_e_e_range, p_e_i_range, p_i_e_range, p_i_i_range, p_x_e_range)
bfr_bayes_analysis=run_bayesian_analysis(summary_data.auc, summary_data.bfr_slope, summary_data.bfr_intercept,
summary_data.bfr_r_sqr, num_trials, p_b_e_range, p_e_e_range, p_e_i_range, p_i_e_range, p_i_i_range, p_x_e_range)
bc_base_dir=os.path.join(base_report_dir, 'bold-contrast')
make_report_dirs(bc_base_dir)
render_summary_report(bc_base_dir, bc_bayes_analysis, p_b_e_range, p_e_e_range, p_e_i_range, p_i_e_range,
p_i_i_range, p_x_e_range, report_info)
bfr_base_dir=os.path.join(base_report_dir, 'bold-firing_rate')
make_report_dirs(bfr_base_dir)
render_summary_report(bfr_base_dir, bfr_bayes_analysis, p_b_e_range, p_e_e_range, p_e_i_range, p_i_e_range,
p_i_i_range, p_x_e_range, report_info)
def regenerate_bayesian_figures(summary_filename, reports_dir):
summary_data = SummaryData()
summary_data.read_from_file(summary_filename)
bayes_analysis = run_bayesian_analysis(
summary_data.auc, summary_data.bc_slope, summary_data.bc_intercept,
summary_data.bc_r_sqr, summary_data.num_trials,
summary_data.p_b_e_range, summary_data.p_e_e_range,
summary_data.p_e_i_range, summary_data.p_i_e_range,
summary_data.p_i_i_range, summary_data.p_x_e_range)
p_b_e_range = summary_data.p_b_e_range
p_x_e_range = summary_data.p_x_e_range
p_e_e_range = summary_data.p_e_e_range
p_e_i_range = summary_data.p_e_i_range
p_i_i_range = summary_data.p_i_i_range
p_i_e_range = summary_data.p_i_e_range
marginal_list = [
bayes_analysis.l1_pos_marginals, bayes_analysis.l1_neg_marginals,
bayes_analysis.l1_pos_l2_neg_marginals,
bayes_analysis.l1_neg_l2_neg_marginals,
bayes_analysis.l1_pos_l2_pos_marginals,
bayes_analysis.l1_neg_l2_pos_marginals,
bayes_analysis.l1_pos_l2_zero_marginals,
bayes_analysis.l1_neg_l2_zero_marginals
]
file_prefix_list = [
'l1_pos', 'l1_neg', 'l1_pos_l2_neg', 'l1_neg_l2_neg', 'l1_pos_l2_pos',
'l1_neg_l2_pos', 'l1_pos_l2_zero', 'l1_neg_l2_zero'
]
for (marginals, file_prefix) in zip(marginal_list, file_prefix_list):
render_joint_marginal_report('p_b_e', 'p_x_e', p_b_e_range,
p_x_e_range,
marginals.posterior_p_b_e_p_x_e,
file_prefix, reports_dir)
render_joint_marginal_report('p_e_e', 'p_e_i', p_e_e_range,
p_e_i_range,
marginals.posterior_p_e_e_p_e_i,
file_prefix, reports_dir)
render_joint_marginal_report('p_e_e', 'p_i_i', p_e_e_range,
p_i_i_range,
marginals.posterior_p_e_e_p_i_i,
file_prefix, reports_dir)
render_joint_marginal_report('p_e_e', 'p_i_e', p_e_e_range,
p_i_e_range,
marginals.posterior_p_e_e_p_i_e,
file_prefix, reports_dir)
render_joint_marginal_report('p_e_i', 'p_i_i', p_e_i_range,
p_i_i_range,
marginals.posterior_p_e_i_p_i_i,
file_prefix, reports_dir)
render_joint_marginal_report('p_e_i', 'p_i_e', p_e_i_range,
p_i_e_range,
marginals.posterior_p_e_i_p_i_e,
file_prefix, reports_dir)
render_joint_marginal_report('p_i_i', 'p_i_e', p_i_i_range,
p_i_e_range,
marginals.posterior_p_i_i_p_i_e,
file_prefix, reports_dir)
def create_summary_report(summary_file_name, base_report_dir, e_desc):
make_report_dirs(base_report_dir)
summary_data = SummaryData()
summary_data.read_from_file(summary_file_name)
report_info = Struct()
report_info.edesc = e_desc
report_info.roc_auc = {}
report_info.io_slope = {}
report_info.io_intercept = {}
report_info.io_r_sqr = {}
report_info.bc_slope = {}
report_info.bc_intercept = {}
report_info.bc_r_sqr = {}
report_info.bfr_slope = {}
report_info.bfr_intercept = {}
report_info.bfr_r_sqr = {}
for i, p_b_e in enumerate(summary_data.p_b_e_range):
for j, p_x_e in enumerate(summary_data.p_x_e_range):
for k, p_e_e in enumerate(summary_data.p_e_e_range):
for l, p_e_i in enumerate(summary_data.p_e_i_range):
for m, p_i_i in enumerate(summary_data.p_i_i_range):
for n, p_i_e in enumerate(summary_data.p_i_e_range):
if summary_data.auc[i, j, k, l, m, n] > 0:
report_info.roc_auc[(
p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = summary_data.auc[i, j, k, l, m,
n]
report_info.bc_slope[(
p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = summary_data.bc_slope[i, j, k, l,
m, n]
report_info.bc_intercept[(
p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = summary_data.bc_intercept[i, j,
k, l,
m, n]
report_info.bc_r_sqr[(
p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = summary_data.bc_r_sqr[i, j, k, l,
m, n]
report_info.bfr_slope[(
p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = summary_data.bfr_slope[i, j, k,
l, m, n]
report_info.bfr_intercept[(
p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = summary_data.bfr_intercept[i, j,
k, l,
m, n]
report_info.bfr_r_sqr[(
p_b_e, p_x_e, p_e_e, p_e_i, p_i_i,
p_i_e)] = summary_data.bfr_r_sqr[i, j, k,
l, m, n]
else:
report_info.roc_auc[(p_b_e, p_x_e, p_e_e,
p_e_i, p_i_i, p_i_e)] = 0
report_info.bc_slope[(p_b_e, p_x_e, p_e_e,
p_e_i, p_i_i, p_i_e)] = 0
report_info.bc_intercept[(p_b_e, p_x_e, p_e_e,
p_e_i, p_i_i,
p_i_e)] = 0
report_info.bc_r_sqr[(p_b_e, p_x_e, p_e_e,
p_e_i, p_i_i, p_i_e)] = 0
report_info.bfr_slope[(p_b_e, p_x_e, p_e_e,
p_e_i, p_i_i,
p_i_e)] = 0
report_info.bfr_intercept[(p_b_e, p_x_e, p_e_e,
p_e_i, p_i_i,
p_i_e)] = 0
report_info.bfr_r_sqr[(p_b_e, p_x_e, p_e_e,
p_e_i, p_i_i,
p_i_e)] = 0
report_info.num_groups = summary_data.num_groups
report_info.trial_duration = summary_data.trial_duration
report_info.num_trials = summary_data.num_trials
report_info.p_b_e_range = summary_data.p_b_e_range
report_info.p_x_e_range = summary_data.p_x_e_range
report_info.p_e_e_range = summary_data.p_e_e_range[:-1]
report_info.p_e_i_range = summary_data.p_e_i_range
report_info.p_i_i_range = summary_data.p_i_i_range
report_info.p_i_e_range = summary_data.p_i_e_range
bc_bayes_analysis = run_bayesian_analysis(
summary_data.auc, summary_data.bc_slope, summary_data.bc_intercept,
summary_data.bc_r_sqr, summary_data.num_trials,
summary_data.p_b_e_range, summary_data.p_e_e_range,
summary_data.p_e_i_range, summary_data.p_i_e_range,
summary_data.p_i_i_range, summary_data.p_x_e_range)
bfr_bayes_analysis = run_bayesian_analysis(
summary_data.auc, summary_data.bfr_slope, summary_data.bfr_intercept,
summary_data.bfr_r_sqr, summary_data.num_trials,
summary_data.p_b_e_range, summary_data.p_e_e_range,
summary_data.p_e_i_range, summary_data.p_i_e_range,
summary_data.p_i_i_range, summary_data.p_x_e_range)
bc_base_dir = os.path.join(base_report_dir, 'bold-contrast')
make_report_dirs(bc_base_dir)
render_summary_report(bc_base_dir, bc_bayes_analysis,
summary_data.p_b_e_range, summary_data.p_e_e_range,
summary_data.p_e_i_range, summary_data.p_i_e_range,
summary_data.p_i_i_range, summary_data.p_x_e_range,
report_info)
bfr_base_dir = os.path.join(base_report_dir, 'bold-firing_rate')
make_report_dirs(bfr_base_dir)
render_summary_report(bfr_base_dir, bfr_bayes_analysis,
summary_data.p_b_e_range, summary_data.p_e_e_range,
summary_data.p_e_i_range, summary_data.p_i_e_range,
summary_data.p_i_i_range, summary_data.p_x_e_range,
report_info)
