def draw_meta_summary_plot(html_fpath, output_dirpath, labels, ref_names, all_rows, results, plot_fpath, title='', reverse=False, yaxis_title=''):
import math
if can_draw_plots:
meta_logger.info(' Drawing ' + title + ' metaQUAST summary plot...')
import matplotlib.pyplot
import matplotlib.ticker
fig = matplotlib.pyplot.figure()
ax = fig.add_subplot(111)
matplotlib.pyplot.title(title)
box = ax.get_position()
ax.set_position([box.x0, box.y0, box.width * 0.9, box.height * 1.0])
ax.yaxis.grid(with_grid)
ref_num = len(ref_names)
contigs_num = len(labels)
arr_x = []
arr_y = []
values = []
arr_y_by_refs = []
for j in range(contigs_num):
to_plot_x = []
to_plot_y = []
arr = range(1, ref_num + 1)
for i in range(ref_num):
arr[i] += 0.07 * (j - (contigs_num - 1) * 0.5)
to_plot_x.append(arr[i])
if results[i][j] and results[i][j] != '-':
to_plot_y.append(parseStrToNum(results[i][j]))
else:
to_plot_y.append(None)
arr_x.append(to_plot_x)
arr_y.append(to_plot_y)
refs = []
for i in range(ref_num):
points_y = [arr_y[j][i] for j in range(contigs_num) if i < len(arr_y[j])]
significant_points_y = [points_y[k] for k in range(len(points_y)) if points_y[k] is not None]
if significant_points_y:
arr_y_by_refs.append(points_y)
values.append(sum(filter(None, points_y))/len(points_y))
refs.append(ref_names[i])
sorted_values = sorted(itertools.izip(values, refs, arr_y_by_refs), reverse=reverse, key=lambda x: x[0])
values, refs, arr_y_by_refs = [[x[i] for x in sorted_values] for i in range(3)]
if can_draw_plots:
matplotlib.pyplot.xticks(range(1, len(refs) + 1), refs, size='small', rotation='vertical')
json_points_x = []
json_points_y = []
for j in range(contigs_num):
points_x = [arr_x[j][i] for i in range(len(arr_y_by_refs))]
points_y = [arr_y_by_refs[i][j] for i in range(len(arr_y_by_refs))]
if can_draw_plots:
color, ls = get_color_and_ls(None, labels[j])
ax.plot(points_x, points_y, 'o:', color=color, ls=ls)
json_points_x.append(points_x)
json_points_y.append(points_y)
if qconfig.html_report:
from quast_libs.html_saver import html_saver
html_saver.save_meta_summary(html_fpath, output_dirpath, json_points_x, json_points_y,
title.replace(' ', '_'), labels, refs)
if can_draw_plots:
matplotlib.pyplot.xlim([0, ref_num + 1])
ymax = 0
for i in range(ref_num):
for j in range(contigs_num):
if all_rows[j + 1]['values'][i] is not None and all_rows[j + 1]['values'][i] != '-':
ymax = max(ymax, parseStrToNum(all_rows[j + 1]['values'][i]))
if ymax < 5:
matplotlib.pyplot.ylim([0, 5])
else:
matplotlib.pyplot.ylim([0, math.ceil(ymax * 1.05)])
if yaxis_title:
ylabel = yaxis_title
ylabel, mkfunc = y_formatter(ylabel, ymax)
matplotlib.pyplot.ylabel(ylabel, fontsize=axes_fontsize)
mkformatter = matplotlib.ticker.FuncFormatter(mkfunc)
ax.yaxis.set_major_formatter(mkformatter)
if ymax == 0:
matplotlib.pyplot.ylim([0, 5])
legend = []
for j in range(contigs_num):
legend.append(labels[j])
try:
ax.legend(legend, loc='center left', bbox_to_anchor=(1.0, 0.5), numpoints=1)
except Exception:
pass
matplotlib.pyplot.tight_layout()
matplotlib.pyplot.savefig(plot_fpath, bbox_inches='tight')
meta_logger.info(' saved to ' + plot_fpath)
matplotlib.pyplot.close()
def draw_meta_summary_plot(html_fpath,
output_dirpath,
labels,
ref_names,
results,
plot_fpath,
title='',
reverse=False,
yaxis_title='',
print_all_refs=False,
logger=logger):
if can_draw_plots:
logger.info(' Drawing ' + title + ' metaQUAST summary plot...')
plots = []
ref_num = len(ref_names)
contigs_num = len(labels)
max_y = 0
arr_x = []
arr_y = []
mean_values = []
arr_y_by_refs = []
for j in range(contigs_num):
to_plot_x = []
to_plot_y = []
arr = list(range(1, ref_num + 1))
for i in range(ref_num):
arr[i] += 0.07 * (j - (contigs_num - 1) * 0.5)
to_plot_x.append(arr[i])
if results[i][j] and results[i][j] != '-':
to_plot_y.append(parse_str_to_num(results[i][j]))
elif print_all_refs:
to_plot_y.append(0)
else:
to_plot_y.append(None)
arr_x.append(to_plot_x)
arr_y.append(to_plot_y)
selected_refs = []
for i in range(ref_num):
points_y = [
arr_y[j][i] for j in range(contigs_num) if i < len(arr_y[j])
]
significant_points_y = [
points_y[k] for k in range(len(points_y))
if points_y[k] is not None
]
if significant_points_y or print_all_refs:
arr_y_by_refs.append(points_y)
mean_values.append(
sum(list(filter(None, points_y))) * 1.0 / len(points_y))
selected_refs.append(ref_names[i])
json_points_x = []
json_points_y = []
if not qconfig.use_input_ref_order:
sorted_values = sorted(zip(mean_values, selected_refs, arr_y_by_refs),
reverse=reverse,
key=lambda x: x[0])
mean_values, selected_refs, arr_y_by_refs = [
[x[i] for x in sorted_values] for i in range(3)
]
for j in range(contigs_num):
points_x = [arr_x[j][i] for i in range(len(arr_y_by_refs))]
points_y = [arr_y_by_refs[i][j] for i in range(len(arr_y_by_refs))]
max_y = max(max_y, max(points_y))
color, ls = get_color_and_ls(None, labels[j])
plots.append(
Plot(points_x,
points_y,
color=color,
ls='dotted',
marker='o',
markersize=7))
if not qconfig.use_input_ref_order:
json_points_x.append(points_x)
json_points_y.append(points_y)
refs_for_html = [
r for r in selected_refs
] # for summary html, we need to sort values by average value anyway
if qconfig.use_input_ref_order:
sorted_values = sorted(zip(mean_values, selected_refs, arr_y_by_refs),
reverse=reverse,
key=lambda x: x[0])
mean_values, refs_for_html, arr_y_by_refs = [
[x[i] for x in sorted_values] for i in range(3)
]
for j in range(contigs_num):
points_x = [arr_x[j][i] for i in range(len(arr_y_by_refs))]
points_y = [arr_y_by_refs[i][j] for i in range(len(arr_y_by_refs))]
json_points_x.append(points_x)
json_points_y.append(points_y)
if qconfig.html_report and html_fpath:
from quast_libs.html_saver import html_saver
html_saver.save_meta_summary(html_fpath, output_dirpath,
json_points_x, json_points_y,
title.replace(' ',
'_'), labels, refs_for_html)
if can_draw_plots:
legend_list = labels
create_plot(plot_fpath,
title,
plots,
legend_list,
y_label=yaxis_title,
vertical_legend=True,
x_ticks=[''] + selected_refs,
vertical_ticks=True,
x_limit=[0, len(selected_refs) + 1],
add_to_report=False,
logger=logger)
def draw_meta_summary_plot(html_fpath, output_dirpath, labels, ref_names, all_rows, results, plot_fpath, title='', reverse=False,
yaxis_title='', print_all_refs=False):
import math
if can_draw_plots:
meta_logger.info(' Drawing ' + title + ' metaQUAST summary plot...')
import matplotlib.pyplot
import matplotlib.ticker
figure = matplotlib.pyplot.figure()
ax = figure.add_subplot(111)
matplotlib.pyplot.title(title)
box = ax.get_position()
ax.set_position([box.x0, box.y0, box.width * 0.9, box.height * 1.0])
ax.yaxis.grid(with_grid)
ref_num = len(ref_names)
contigs_num = len(labels)
arr_x = []
arr_y = []
values = []
arr_y_by_refs = []
for j in range(contigs_num):
to_plot_x = []
to_plot_y = []
arr = list(range(1, ref_num + 1))
for i in range(ref_num):
arr[i] += 0.07 * (j - (contigs_num - 1) * 0.5)
to_plot_x.append(arr[i])
if results[i][j] and results[i][j] != '-':
to_plot_y.append(parseStrToNum(results[i][j]))
elif print_all_refs and results[i][j] != '-':
to_plot_y.append(0)
else:
to_plot_y.append(None)
arr_x.append(to_plot_x)
arr_y.append(to_plot_y)
refs = []
for i in range(ref_num):
points_y = [arr_y[j][i] for j in range(contigs_num) if i < len(arr_y[j])]
significant_points_y = [points_y[k] for k in range(len(points_y)) if points_y[k] is not None]
if significant_points_y or print_all_refs:
arr_y_by_refs.append(points_y)
values.append(sum(list(filter(None, points_y))) / len(points_y))
refs.append(ref_names[i])
sorted_values = sorted(zip(values, refs, arr_y_by_refs), reverse=reverse, key=lambda x: x[0])
values, refs, arr_y_by_refs = [[x[i] for x in sorted_values] for i in range(3)]
if can_draw_plots:
matplotlib.pyplot.xticks(range(1, len(refs) + 1), refs, size='small', rotation='vertical')
json_points_x = []
json_points_y = []
for j in range(contigs_num):
points_x = [arr_x[j][i] for i in range(len(arr_y_by_refs))]
points_y = [arr_y_by_refs[i][j] for i in range(len(arr_y_by_refs))]
if can_draw_plots:
color, ls = get_color_and_ls(None, labels[j])
ax.plot(points_x, points_y, 'o:', color=color, ls=ls)
json_points_x.append(points_x)
json_points_y.append(points_y)
if qconfig.html_report and html_fpath:
from quast_libs.html_saver import html_saver
html_saver.save_meta_summary(html_fpath, output_dirpath, json_points_x, json_points_y,
title.replace(' ', '_'), labels, refs)
if can_draw_plots:
matplotlib.pyplot.xlim([0, ref_num + 1])
ymax = 0
for i in range(ref_num):
for j in range(contigs_num):
if all_rows[j + 1]['values'][i] is not None and all_rows[j + 1]['values'][i] != '-':
ymax = max(ymax, parseStrToNum(all_rows[j + 1]['values'][i]))
if ymax < 5:
matplotlib.pyplot.ylim([0, 5])
else:
matplotlib.pyplot.ylim([0, math.ceil(ymax * 1.05)])
if yaxis_title:
ylabel = yaxis_title
ylabel, mkfunc = y_formatter(ylabel, ymax)
matplotlib.pyplot.ylabel(ylabel, fontsize=axes_fontsize)
mkformatter = matplotlib.ticker.FuncFormatter(mkfunc)
ax.yaxis.set_major_formatter(mkformatter)
if ymax == 0:
matplotlib.pyplot.ylim([0, 5])
legend = []
for j in range(contigs_num):
legend.append(labels[j])
try:
ax.legend(legend, loc='center left', bbox_to_anchor=(1.0, 0.5), numpoints=1)
except Exception:
pass
matplotlib.pyplot.tight_layout()
matplotlib.pyplot.savefig(plot_fpath, bbox_inches='tight')
meta_logger.info(' saved to ' + plot_fpath)
pdf_plots_figures.append(figure)
matplotlib.pyplot.close()