def main_cli():
bin_dir = os.path.abspath(os.path.dirname(__file__))
project_dir = os.path.abspath(os.path.dirname(bin_dir))
result_dir = os.path.abspath(os.path.join(project_dir, 'results'))
info_path = os.path.join(result_dir, 'sort', 'pymsbayes-results',
'pymsbayes-info.txt')
plot_dir = os.path.join(result_dir, 'sort', 'pymsbayes-results',
'plots')
plotting.plot_validation_results(info_path,
omega_symbol = r'D_T',
psi_symbol = r'|\mathbf{\tau}|',
mean_time_symbol = r'\bar{T}',
math_font = None)
vr = plotting.plot_validation_results(info_path,
omega_symbol = r'D_T',
psi_symbol = r'|\mathbf{\tau}|',
mean_time_symbol = r'\bar{T}',
label_schema = None,
prob_plot_height = 3.4,
prob_plot_margin_left = 0.005,
prob_plot_margin_bottom = 0.005,
prob_plot_margin_right = 1,
prob_plot_margin_top = 1,
plot_accuracy = False,
prob_plot_glm = False,
write_plots = False,
math_font = None)
vr['prior']['prior'].prob_plot.subplots[0].set_xlabel(
xlabel = 'Estimated probability of one divergence')
vr['prior']['prior'].save_prob_plot(os.path.join(plot_dir,
'mc-unadjusted.pdf'))
def main_cli():
info_path = os.path.join(project_util.RESULT_DIR, 'old',
'pymsbayes-results', 'pymsbayes-info.txt')
plotting.plot_validation_results(info_path,
omega_symbol = r'D_T',
psi_symbol = r'|\mathbf{\tau}|',
mean_time_symbol = r'\bar{T}',
math_font = None)
def main_cli():
bin_dir = os.path.abspath(os.path.dirname(__file__))
project_dir = os.path.abspath(os.path.dirname(bin_dir))
result_dir = os.path.abspath(os.path.join(project_dir, 'results'))
info_path = os.path.join(result_dir, 'multi-locus-no-sort', 'pymsbayes-results',
'pymsbayes-info.txt')
plotting.plot_validation_results(info_path,
omega_symbol = r'D_T',
psi_symbol = r'|\mathbf{\tau}|',
mean_time_symbol = r'\bar{T}',
math_font = None)
def main_cli():
if not os.path.exists(project_util.IMAGE_DIR):
os.mkdir(project_util.IMAGE_DIR)
results = {}
for d in ['dpp', 'old', 'uniform', 'u-shaped']:
info_path = os.path.join(project_util.RESULT_DIR, d,
'pymsbayes-results', 'pymsbayes-info.txt')
r = plotting.plot_validation_results(info_path,
plot_dir = project_util.IMAGE_DIR,
omega_symbol = r'D_T',
psi_symbol = r'|\mathbf{\tau}|',
mean_time_symbol = r'\bar{T}',
plot_accuracy = True,
prob_plot_glm = True,
prob_plot_height = 3.5,
prob_plot_margin_left = 0,
prob_plot_margin_bottom = 0,
prob_plot_margin_right = 1,
prob_plot_margin_top = 0.975,
prob_plot_padding_between_horizontal = 0.5,
prob_plot_padding_between_vertical = 1.0,
math_font = None,
write_plots = False)
for obs_name, p_dict in r.iteritems():
for prior_name, validation_result in p_dict.iteritems():
if not results.has_key(obs_name):
results[obs_name] = {}
if not results[obs_name].has_key(prior_name):
results[obs_name][prior_name] = validation_result
else:
raise Exception('Unexpected duplicate validation result')
sub_plot_map = {
0: ('psi',
r'True number of divergence events, $|\mathbf{\tau}|$',
r'Estimated number of divergence events, $\hat{|\mathbf{\tau}|}$ (mode)'),
1: ('omega',
r'True variance of divergence times, $D_T$',
r'Estimated variance of divergence times, $\hat{D_T}$ (median)'),
2: ('time',
r'True mean of divergence times, $\bar{T}$',
r'Estimated mean of divergence times, $\hat{\bar{T}}$ (median)'),
3: ('psi-glm',
r'True number of divergence events, $|\mathbf{\tau}|$',
r'GLM-adjusted number of divergence events, $\hat{|\mathbf{\tau}|}$ (mode)'),
4: ('omega-glm',
r'True variance of divergence times, $D_T$',
r'GLM-adjusted variance of divergence times, $\hat{D_T}$ (median)'),
5: ('time-glm',
r'True mean of divergence times, $\bar{T}$',
r'GLM-adjusted mean of divergence times, $\hat{\bar{T}}$ (median)'),
}
for idx, (variable, x_label, y_label) in sub_plot_map.iteritems():
sub_plots = {}
for i in ['old', 'dpp', 'uniform', 'u-shaped']:
if not sub_plots.has_key(i):
sub_plots[i] = {}
for j in ['old', 'dpp', 'uniform', 'u-shaped']:
sub_plots[i][j] = results['prior-' + i]['prior-' + j].accuracy_plot.subplots[idx]
sub_plots[i][j].set_xlabel('')
sub_plots[i][j].set_ylabel('')
sub_plot_list = [
sub_plots['old']['old'],
sub_plots['u-shaped']['old'],
sub_plots['uniform']['old'],
sub_plots['dpp']['old'],
sub_plots['old']['u-shaped'],
sub_plots['u-shaped']['u-shaped'],
sub_plots['uniform']['u-shaped'],
sub_plots['dpp']['u-shaped'],
sub_plots['old']['uniform'],
sub_plots['u-shaped']['uniform'],
sub_plots['uniform']['uniform'],
sub_plots['dpp']['uniform'],
sub_plots['old']['dpp'],
sub_plots['u-shaped']['dpp'],
sub_plots['uniform']['dpp'],
sub_plots['dpp']['dpp'],
]
for p in sub_plot_list:
p.set_extra_y_label('')
for scatter_data in p.scatter_data_list:
scatter_data.markersize = 5.0
pg = plotting.PlotGrid(subplots = sub_plot_list,
num_columns = 4,
share_x = True,
share_y = True,
title = x_label,
title_size = 14.0,
title_top = False,
y_title = y_label,
y_title_position = 0.015,
y_title_size = 14.0,
height = 9.0,
width = 11.0,
auto_height = False,
row_labels = [r'$M_{msBayes}$', r'$M_{Ushaped}$', r'$M_{Uniform}$', r'$M_{DPP}$'],
column_labels = [r'$M_{msBayes}$', r'$M_{Ushaped}$', r'$M_{Uniform}$', r'$M_{DPP}$'],
column_label_size = 20.0,
row_label_size = 20.0,
column_label_offset = 0.1,
row_label_offset = 0.05,
super_title = r'\textbf{Data model}',
super_y_title = r'\textbf{Inference model}',
super_title_size = 20.0,
super_y_title_size = 20.0,
super_y_title_right = True)
# pg.label_schema = None
pg.auto_adjust_margins = False
pg.margin_bottom = 0.04
pg.margin_left = 0.04
pg.margin_top = 0.92
pg.margin_right = 0.94
pg.plot_label_size = 12.0
pg.padding_between_vertical = 1.2
pg.reset_figure()
pg.set_shared_x_limits()
pg.set_shared_y_limits()
pg.reset_figure()
pg.savefig(os.path.join(project_util.IMAGE_DIR,
'validation-accuracy-' + variable + '.pdf'))
def main_cli():
results = {}
for d in ['dpp', 'old', 'uniform', 'u-shaped']:
info_path = os.path.join(project_util.VALIDATION_RESULT_DIR, d,
'pymsbayes-results', 'pymsbayes-info.txt')
r = plotting.plot_validation_results(info_path,
plot_dir = project_util.IMAGE_DIR,
omega_symbol = r'D_T',
psi_symbol = r'|\mathbf{\tau}|',
mean_time_symbol = r'\bar{T}',
plot_accuracy = False,
prob_plot_glm = False,
prob_plot_height = 3.5,
prob_plot_margin_left = 0,
prob_plot_margin_bottom = 0,
prob_plot_margin_right = 1,
prob_plot_margin_top = 0.975,
prob_plot_padding_between_horizontal = 0.5,
prob_plot_padding_between_vertical = 1.0,
math_font = None,
write_plots = False)
for obs_name, p_dict in r.iteritems():
for prior_name, validation_result in p_dict.iteritems():
if not results.has_key(obs_name):
results[obs_name] = {}
if not results[obs_name].has_key(prior_name):
results[obs_name][prior_name] = validation_result
else:
raise Exception('Unexpected duplicate validation result')
sub_plots = {}
for i in ['old', 'dpp', 'uniform', 'u-shaped']:
if not sub_plots.has_key(i):
sub_plots[i] = {}
for j in ['old', 'dpp', 'uniform', 'u-shaped']:
sub_plots[i][j] = results['prior-' + i]['prior-' + j].prob_plot.subplots[0]
sub_plots[i][j].set_xlabel('')
sub_plots[i][j].set_ylabel('')
sub_plot_list = [
sub_plots['old']['old'],
sub_plots['dpp']['old'],
sub_plots['old']['dpp'],
sub_plots['dpp']['dpp'],
]
pg = plotting.PlotGrid(subplots = sub_plot_list[:1],
num_columns = 1,
share_x = True,
share_y = True,
title = 'Posterior probability of one divergence',
title_size = 14.0,
title_top = False,
y_title = 'True probability of one divergence',
y_title_position = 0.001,
y_title_size = 14.0,
column_labels = [r'msBayes'],
column_label_size = 22.0,
column_label_offset = 0.04,
width = 4.6,
height = 3.7,
auto_height = False)
pg.label_schema = None
pg.auto_adjust_margins = False
pg.margin_bottom = 0.06
pg.margin_left = 0.05
pg.margin_top = 0.91
pg.margin_right = 0.94
pg.reset_figure()
pg.savefig('../images/validation-model-choice-old.pdf')
pg = plotting.PlotGrid(subplots = sub_plot_list[-1:],
num_columns = 1,
share_x = True,
share_y = True,
title = 'Posterior probability of one divergence',
title_size = 14.0,
title_top = False,
y_title = 'True probability of one divergence',
y_title_position = 0.001,
y_title_size = 14.0,
column_labels = [r'dpp-msbayes'],
column_label_size = 22.0,
column_label_offset = 0.04,
width = 4.6,
height = 3.7,
auto_height = False)
pg.label_schema = None
pg.auto_adjust_margins = False
pg.margin_bottom = 0.06
pg.margin_left = 0.05
pg.margin_top = 0.91
pg.margin_right = 0.94
pg.reset_figure()
pg.savefig('../images/validation-model-choice-dpp.pdf')
pg = plotting.PlotGrid(subplots = sub_plot_list,
num_columns = 2,
share_x = True,
share_y = True,
title = 'Posterior probability of one divergence',
title_size = 16.0,
title_top = False,
y_title = 'True probability of one divergence',
y_title_position = 0.03,
y_title_size = 16.0,
height = 6.0,
auto_height = False,
column_labels = [r'$M_{msBayes}$', r'$M_{DPP}$'],
row_labels = [r'$M_{msBayes}$', r'$M_{DPP}$'],
column_label_size = 22.0,
row_label_size = 22.0,
column_label_offset = 0.05,
row_label_offset = 0.05,
super_title = r'\textbf{Data model}',
super_y_title = r'\textbf{Analysis model}',
super_title_size = 20.0,
super_y_title_size = 20.0,
super_y_title_right = True)
pg.label_schema = None
pg.auto_adjust_margins = False
pg.margin_bottom = 0.05
pg.margin_left = 0.07
pg.margin_top = 0.90
pg.margin_right = 0.92
pg.reset_figure()
pg.savefig('../images/validation-model-choice-old-dpp.pdf')
for p in sub_plot_list:
p.set_extra_y_label('')
p.set_title_text('')
pg = plotting.PlotGrid(subplots = sub_plot_list[-1:],
num_columns = 1,
share_x = True,
share_y = True,
title = 'Posterior probability of one divergence',
title_size = 14.0,
title_top = False,
y_title = 'True probability of one divergence',
y_title_position = 0.001,
y_title_size = 14.0,
# column_labels = [r'dpp-msbayes'],
column_label_size = 22.0,
column_label_offset = 0.04,
width = 4.8,
height = 3.6,
auto_height = False)
pg.label_schema = None
pg.auto_adjust_margins = False
pg.margin_bottom = 0.06
pg.margin_left = 0.06
pg.margin_top = 0.99
pg.margin_right = 0.94
pg.reset_figure()
pg.savefig('../images/validation-model-choice-dpp-no-label.pdf')
sub_plot_list = [
sub_plots['old']['old'],
sub_plots['dpp']['old'],
sub_plots['uniform']['old'],
sub_plots['u-shaped']['old'],
sub_plots['old']['dpp'],
sub_plots['dpp']['dpp'],
sub_plots['uniform']['dpp'],
sub_plots['u-shaped']['dpp'],
]
for p in sub_plot_list:
p.set_extra_y_label('')
pg = plotting.PlotGrid(subplots = sub_plot_list,
num_columns = 4,
share_x = True,
share_y = True,
title = 'Posterior probability of one divergence',
title_size = 16.0,
title_top = False,
y_title = 'True probability of one divergence',
y_title_position = 0.015,
y_title_size = 16.0,
height = 4.8,
width = 11.0,
auto_height = False,
row_labels = [r'$M_{msBayes}$', r'$M_{DPP}$'],
column_labels = [r'$M_{msBayes}$', r'$M_{DPP}$', r'$M_{Uniform}$', r'$M_{Ushaped}$'],
column_label_size = 22.0,
row_label_size = 22.0,
column_label_offset = 0.05,
row_label_offset = 0.05,
super_title = r'\textbf{Data model}',
super_y_title = r'\textbf{Analysis model}',
super_title_size = 20.0,
super_y_title_size = 20.0,
super_y_title_right = True)
pg.label_schema = None
pg.auto_adjust_margins = False
pg.margin_bottom = 0.06
pg.margin_left = 0.045
pg.margin_top = 0.88
pg.margin_right = 0.94
pg.reset_figure()
pg.savefig('../images/validation-model-choice-old-dpp-full.pdf')
for p in sub_plot_list:
p.set_extra_y_label('')
p.set_title_text('')
old_violations = sub_plot_list[1:3]
dpp_violations = sub_plot_list[4:5] + sub_plot_list[6:7]
pg = plotting.PlotGrid(subplots = old_violations,
num_columns = 1,
share_x = True,
share_y = True,
title = 'Posterior probability of one divergence',
title_size = 16.0,
title_top = False,
y_title = 'True probability of one divergence',
y_title_position = 0.015,
y_title_size = 16.0,
height = 6.5,
width = 4.5,
auto_height = False,
column_labels = [r'msBayes'],
column_label_size = 22.0,
column_label_offset = 0.05,
# super_title = r'\textbf{Data model}',
# super_y_title = r'\textbf{Analysis model}',
super_title_size = 20.0,
super_y_title_size = 20.0,
super_y_title_right = True)
pg.label_schema = None
pg.auto_adjust_margins = False
pg.margin_bottom = 0.05
pg.margin_left = 0.07
pg.margin_top = 0.94
pg.margin_right = 0.95
pg.reset_figure()
pg.savefig('../images/validation-model-choice-old-violations.pdf')
pg = plotting.PlotGrid(subplots = dpp_violations,
num_columns = 1,
share_x = True,
share_y = True,
title = 'Posterior probability of one divergence',
title_size = 16.0,
title_top = False,
y_title = 'True probability of one divergence',
y_title_position = 0.015,
y_title_size = 16.0,
height = 6.5,
width = 4.5,
auto_height = False,
column_labels = [r'dpp-msbayes'],
column_label_size = 22.0,
column_label_offset = 0.05,
# super_title = r'\textbf{Data model}',
# super_y_title = r'\textbf{Analysis model}',
super_title_size = 20.0,
super_y_title_size = 20.0,
super_y_title_right = True)
pg.label_schema = None
pg.auto_adjust_margins = False
pg.margin_bottom = 0.05
pg.margin_left = 0.07
pg.margin_top = 0.94
pg.margin_right = 0.95
pg.reset_figure()
pg.savefig('../images/validation-model-choice-dpp-violations.pdf')
for p in sub_plot_list:
p.set_extra_y_label('')
p.set_title_text('')
pg = plotting.PlotGrid(subplots = dpp_violations,
num_columns = 2,
share_x = True,
share_y = True,
title = 'Posterior probability of one divergence',
title_size = 16.0,
title_top = False,
y_title = 'True probability of one divergence',
y_title_position = 0.015,
y_title_size = 16.0,
height = 4,
width = 10,
auto_height = False,
# column_labels = ['',''],
column_label_size = 22.0,
column_label_offset = 0.05,
# super_title = r'\textbf{Data model}',
# super_y_title = r'\textbf{Analysis model}',
super_title_size = 20.0,
super_y_title_size = 20.0,
super_y_title_right = True)
pg.label_schema = None
pg.auto_adjust_margins = False
pg.margin_bottom = 0.06
pg.margin_left = 0.06
pg.margin_top = 0.99
pg.margin_right = 0.95
pg.reset_figure()
pg.savefig('../images/validation-model-choice-dpp-violations-horizontal.pdf')
pg = plotting.PlotGrid(subplots = dpp_violations[-1:],
num_columns = 1,
share_x = True,
share_y = True,
title = 'Posterior probability of one divergence',
title_size = 14.0,
title_top = False,
y_title = 'True probability of one divergence',
y_title_position = 0.001,
y_title_size = 14.0,
# column_labels = [r'dpp-msbayes'],
column_label_size = 22.0,
column_label_offset = 0.04,
width = 4.8,
height = 3.6,
auto_height = False)
pg.label_schema = None
pg.auto_adjust_margins = False
pg.margin_bottom = 0.06
pg.margin_left = 0.06
pg.margin_top = 0.99
pg.margin_right = 0.94
pg.reset_figure()
pg.savefig('../images/validation-model-choice-dpp-uniform-no-label.pdf')
