add option to select metrics for spider plots of absolute performance

opal.py

@@ -175,7 +175,7 @@ def evaluate(gs_samples_list, profiles_list_to_samples_list, labels, filter_tail
                 gs_rank_to_taxid_to_percentage = gs_id_to_rank_to_taxid_to_percentage[sample_id]
                 gs_pf_profile = gs_id_to_pf_profile[sample_id]
             else:
-                sys.stderr.write("Skipping assessment of {} for sample {}. Make sure the SampleID of the gold standard and the profile are identical.\n".format(label, sample_id))
+                logging.getLogger('opal').warning("Skipping assessment of {} for sample {}. Make sure the SampleID of the gold standard and the profile are identical.\n".format(label, sample_id))
                 continue
 
             rank_to_taxid_to_percentage = load_data.get_rank_to_taxid_to_percentage(profile)
@@ -303,7 +303,8 @@ def main():
     group2.add_argument('-m', '--memory', help='Comma-separated memory usages in gigabytes', required=False)
     group2.add_argument('-d', '--desc', help='Description for HTML page', required=False)
     group2.add_argument('-r', '--ranks', help='Highest and lowest taxonomic ranks to consider in performance rankings, comma-separated. Valid ranks: superkingdom, phylum, class, order, family, genus, species, strain (default:superkingdom,species)', required=False)
-    group2.add_argument('--metrics_plot', help='Metrics for spider plot of relative performances, first character, comma-separated. Valid metrics: w:weighted Unifrac, l:L1 norm, c:completeness, p:purity, f:false positives, t:true positives (default: w,l,c,p,f)', required=False)
+    group2.add_argument('--metrics_plot_rel', help='Metrics for spider plot of relative performances, first character, comma-separated. Valid metrics: w:weighted Unifrac, l:L1 norm, c:completeness, p:purity, f:false positives, t:true positives (default: w,l,c,p,f)', required=False)
+    group2.add_argument('--metrics_plot_abs', help='Metrics for spider plot of absolute performances, first character, comma-separated. Valid metrics: c:completeness, p:purity, b:Bray-Curtis (default: c,p)', required=False)
     group2.add_argument('--silent', help='Silent mode', action='store_true')
     group2.add_argument('-v', '--version', action='version', version='%(prog)s ' + __version__)
     group2.add_argument('-h', '--help', action='help', help='Show this help message and exit')
@@ -354,7 +355,7 @@ def main():
     logger.info('done')
 
     logger.info('Creating more plots...')
-    plots_list += pl.plot_all(pd_metrics, labels, output_dir, args.metrics_plot)
+    plots_list += pl.plot_all(pd_metrics, labels, output_dir, args.metrics_plot_rel, args.metrics_plot_abs)
     logger.info('done')
 
     logger.info('Computing rankings...')

src/html_opal.py

@@ -114,7 +114,7 @@ def get_rank_to_sample_pd(pd_metrics):
     return rank_to_sample_pd
 
 
-def get_formatted_pd_rankings(pd_rankings):
+def get_formatted_pd_rankings(pd_rankings, labels):
     df_list = []
     df_list_unsorted_pos = []
     metrics_list = []
@@ -126,7 +126,8 @@ def get_formatted_pd_rankings(pd_rankings):
         df_list_unsorted_pos.append(pd.DataFrame({metric: df2['tool'].tolist(), 'score' + metric: df2['position'].tolist()}))
 
     df_sum = pd_rankings.groupby(['tool'])['position'].sum().reset_index().sort_values('position')
-    df_sum_unsorted_pos = pd_rankings.groupby(['tool'])['position'].sum().reset_index()
+    df_sum_unsorted_pos = pd_rankings.groupby(['tool'])['position'].sum().loc[labels].reset_index()
+
     df_list.append(
         pd.DataFrame({SUM_OF_SCORES: df_sum['tool'].tolist(), 'score' + SUM_OF_SCORES: df_sum['position'].tolist()}))
     df_list_unsorted_pos.append(
@@ -137,8 +138,8 @@ def get_formatted_pd_rankings(pd_rankings):
     return pd_show, pd_show_unsorted_pos
 
 
-def create_rankings_html(pd_rankings, ranks_scored):
-    pd_show, pd_show_unsorted_pos = get_formatted_pd_rankings(pd_rankings)
+def create_rankings_html(pd_rankings, ranks_scored, labels):
+    pd_show, pd_show_unsorted_pos = get_formatted_pd_rankings(pd_rankings, labels)
 
     table_source = ColumnDataSource(pd_show)
 
@@ -196,7 +197,7 @@ def create_rankings_html(pd_rankings, ranks_scored):
     weight_unifrac = Slider(start=0, end=10, value=1, step=.1, title=c.UNIFRAC + " weight", callback=callback)
     callback.args["weight_unifrac"] = weight_unifrac
 
-    p = figure(x_range=pd_show_unsorted_pos[SUM_OF_SCORES].tolist(), plot_width=1000, plot_height=400, title=SUM_OF_SCORES + " - lower is better")
+    p = figure(x_range=pd_show_unsorted_pos[SUM_OF_SCORES].tolist(), plot_width=800, plot_height=400, title=SUM_OF_SCORES + " - lower is better")
     p.vbar(x='x', top='top', source=source, width=0.5, bottom=0, color="firebrick")
 
     col_rankings = column([Div(text="<font color='navy'><u>Hint 1:</u> click on the columns of scores for sorting.</font>", style={"width": "600px", "margin-bottom": "0px"}),
@@ -309,8 +310,8 @@ def create_metrics_table(pd_metrics, labels, sample_ids_list):
     alpha_diversity_metics = 'Alpha diversity'
     all_metrics_labels = [presence_metrics_label, estimates_metrics_label, alpha_diversity_metics]
 
-    styles = [{'selector': 'td', 'props': [('width', '100pt')]},
-              {'selector': 'th', 'props': [('width', '100pt'), ('text-align', 'left')]},
+    styles = [{'selector': 'td', 'props': [('width', '115pt')]},
+              {'selector': 'th', 'props': [('width', '115pt'), ('text-align', 'left')]},
               {'selector': 'th:nth-child(1)', 'props': [('width', '120pt'), ('font-weight', 'normal')]},
               {'selector': '', 'props': [('width', 'max-content'), ('width', '-moz-max-content'), ('border-top', '1px solid lightgray'), ('border-spacing', '0px')]},
               {'selector': 'expand-toggle:checked ~ * .data', 'props': [('background-color', 'white !important')]}]
@@ -418,10 +419,10 @@ def create_alpha_diversity_tab():
 def create_plots_html(plots_list):
     message_no_spdplot = 'Spider plots of performance require at least 3 profiles.'
 
-    text = '<img src="spider_plot.png" />' if 'spider_plot' in plots_list else message_no_spdplot
+    text = '<img src="spider_plot_relative.png" />' if 'spider_plot_relative' in plots_list else message_no_spdplot
     plot1 = Panel(child=Div(text=text), title='Relative performance', width=780)
 
-    text = '<img src="spider_plot_recall_precision.png" />' if 'spider_plot_recall_precision' in plots_list else message_no_spdplot
+    text = '<img src="spider_plot_absolute.png" />' if 'spider_plot_absolute' in plots_list else message_no_spdplot
     plot2 = Panel(child=Div(text=text), title='Absolute performance')
 
     tabs_plots = Tabs(tabs=[plot1, plot2], width=780, css_classes=['bk-tabs-margin'])
@@ -501,7 +502,7 @@ def create_computing_efficiency_tab(pd_metrics, plots_list, tabs_list):
 
 
 def create_html(pd_rankings, ranks_scored, pd_metrics, labels, sample_ids_list, plots_list, output_dir, desc_text):
-    col_rankings = create_rankings_html(pd_rankings, ranks_scored)
+    col_rankings = create_rankings_html(pd_rankings, ranks_scored, labels)
 
     create_heatmap_bar(output_dir)
 

src/plots.py

@@ -356,7 +356,7 @@ def spider_plot(metrics, labels, rank_to_metric_to_toolvalues, output_dir, file_
         return []
     theta = spl.radar_factory(N, frame='polygon')
     fig, axes = plt.subplots(figsize=(9, 9), nrows=2, ncols=3, subplot_kw=dict(projection='radar'))
-    fig.subplots_adjust(wspace=1.0, hspace=0.0, top=0.87, bottom=0.45)
+    fig.subplots_adjust(wspace=.5, hspace=0.3, top=0.87, bottom=0.45)
 
     for ax, rank in zip(axes.flat, c.PHYLUM_SPECIES):
         if grid_points:
@@ -366,12 +366,8 @@ def spider_plot(metrics, labels, rank_to_metric_to_toolvalues, output_dir, file_
         ax.set_title(rank, weight='bold', size=9, position=(0.5, 1.1),
                      horizontalalignment='center', verticalalignment='center')
 
-        if absolute:
-            metric_suffix = 'absolute'
-        else:
-            metric_suffix = ''
         # select only metrics in metrics list
-        metrics_subdict = OrderedDict((metric, rank_to_metric_to_toolvalues[rank][metric + metric_suffix]) for metric in metrics)
+        metrics_subdict = OrderedDict((metric, rank_to_metric_to_toolvalues[rank][metric]) for metric in metrics)
         it = 1
         metric_to_toolindex = []
         for d, color in zip(metrics_subdict.values(), colors):
@@ -408,6 +404,9 @@ def spider_plot(metrics, labels, rank_to_metric_to_toolvalues, output_dir, file_
             xticklabel.set_position((0,.20))
             xticklabel.set_fontsize('x-small')
 
+    if absolute:
+        metrics = [metric[:-8] for metric in metrics]
+
     ax = axes[0, 0]
     ax.legend(metrics, loc=(2.0 - 0.353 * len(metrics), 1.25), labelspacing=0.1, fontsize='small', ncol=len(metrics), frameon=False)
     fig.savefig(os.path.join(output_dir, file_name + '.pdf'), dpi=100, format='pdf', bbox_inches='tight')
@@ -452,14 +451,25 @@ def plot_braycurtis_l1norm(braycurtis_list, l1norm_list, labels, output_dir):
     plt.close(fig)
 
 
-def get_metrics_for_spider_plot(metrics_plot):
-    initial_to_metric = {'w':c.UNIFRAC, 'l':c.L1NORM, 'c':c.RECALL, 'p':c.PRECISION, 'f':c.FP, 't':c.TP}
+def get_metrics_for_spider_plot(metrics_plot, absolute):
     metrics_initial = [x.strip() for x in metrics_plot.split(',')]
     metrics_list = []
+
+    if not absolute:
+        initial_to_metric = {'w':c.UNIFRAC, 'l':c.L1NORM, 'c':c.RECALL, 'p':c.PRECISION, 'f':c.FP, 't':c.TP}
+        for initial in metrics_initial:
+            if initial not in initial_to_metric:
+                logging.getLogger('opal').warning('Invalid metric initial {} provided with option --metrics_plot_rel. Defaults will be used.'.format(initial))
+                return [c.UNIFRAC, c.L1NORM, c.RECALL, c.PRECISION, c.FP]
+            else:
+                metrics_list.append(initial_to_metric[initial])
+        return metrics_list
+
+    initial_to_metric = {'c':c.RECALL+'absolute', 'p':c.PRECISION+'absolute', 'b':c.BRAY_CURTIS+'absolute'}
     for initial in metrics_initial:
         if initial not in initial_to_metric:
-            logging.getLogger('opal').warning('Invalid metric initial {} provided with option --metrics_plot. Defaults will be used.'.format(initial))
-            return [c.UNIFRAC, c.L1NORM, c.RECALL, c.PRECISION, c.FP]
+            logging.getLogger('opal').warning('Invalid metric initial {} provided with option --metrics_plot_abs. Defaults will be used.'.format(initial))
+            return [c.RECALL+'absolute', c.PRECISION+'absolute']
         else:
             metrics_list.append(initial_to_metric[initial])
     return metrics_list
@@ -576,8 +586,7 @@ def spider_plot_preprocess_metrics(pd_mean, labels):
     return tool_to_rank_to_metric_to_value
 
 
-def plot_all(pd_metrics, labels, output_dir, metrics_plot):
-    metrics = [c.UNIFRAC, c.L1NORM, c.RECALL, c.PRECISION, c.FP]
+def plot_all(pd_metrics, labels, output_dir, metrics_plot_rel, metrics_plot_abs):
     rank_to_metric_to_toolvalues = defaultdict(lambda : defaultdict(list))
 
     pd_copy = pd_metrics.copy()
@@ -593,33 +602,37 @@ def plot_all(pd_metrics, labels, output_dir, metrics_plot):
 
     tool_to_rank_to_metric_to_value = spider_plot_preprocess_metrics(pd_mean, labels)
 
-    metrics_for_plot = get_metrics_for_spider_plot(metrics_plot) if metrics_plot else metrics
+    metrics_for_plot_rel = get_metrics_for_spider_plot(metrics_plot_rel, absolute=False) if metrics_plot_rel else [c.UNIFRAC, c.L1NORM, c.RECALL, c.PRECISION, c.FP]
+    metrics_for_plot_abs = get_metrics_for_spider_plot(metrics_plot_abs, absolute=True) if metrics_plot_abs else [c.RECALL+'absolute', c.PRECISION+'absolute']
+
     present_labels = []
     for label in labels:
         if label not in tool_to_rank_to_metric_to_value:
             continue
         else:
             present_labels.append(label)
         for rank in c.PHYLUM_SPECIES:
-            for metric in metrics_for_plot + [c.RECALL+'absolute', c.PRECISION+'absolute']:
+            for metric in metrics_for_plot_rel + metrics_for_plot_abs:
                 if metric in tool_to_rank_to_metric_to_value[label][rank]:
                     rank_to_metric_to_toolvalues[rank][metric].append(tool_to_rank_to_metric_to_value[label][rank][metric])
             rank_to_metric_to_toolvalues[rank][c.UNIFRAC].append(tool_to_rank_to_metric_to_value[label]['rank independent'][c.UNIFRAC])
 
     colors = [plt.cm.tab10(2), plt.cm.tab10(0), plt.cm.tab10(3), 'k', 'm', 'y']
-    plots_list = spider_plot(metrics_for_plot,
+    colors2 = ['r', 'k', 'olive']
+
+    plots_list = spider_plot(metrics_for_plot_rel,
                              present_labels,
                              rank_to_metric_to_toolvalues,
                              output_dir,
-                             'spider_plot',
-                             colors[:len(metrics_for_plot)])
+                             'spider_plot_relative',
+                             colors[:len(metrics_for_plot_rel)])
 
-    plots_list += spider_plot([c.RECALL, c.PRECISION],
+    plots_list += spider_plot(metrics_for_plot_abs,
                               present_labels,
                               rank_to_metric_to_toolvalues,
                               output_dir,
-                              'spider_plot_recall_precision',
-                              ['r', 'k'],
+                              'spider_plot_absolute',
+                              colors2[:len(metrics_for_plot_abs)],
                               grid_points=[0.2, 0.4, 0.6, 0.8, 1.0],
                               fill=True,
                               absolute=True)