def Nx_plot(results_dir, reduce_points, contigs_fpaths, lists_of_lengths, plot_fpath, title='Nx', reference_lengths=None):
if can_draw_plots:
logger.info(' Drawing ' + title + ' plot...')
plots = []
json_vals_x = [] # coordinates for Nx-like plots in HTML-report
json_vals_y = []
for id, (contigs_fpath, lengths) in enumerate(zip(contigs_fpaths, lists_of_lengths)):
if not lengths:
json_vals_x.append([])
json_vals_y.append([])
continue
lengths.sort(reverse=True)
vals_x = [0.0]
vals_y = [lengths[0]]
# calculate values for the plot
vals_Nx = [0.0]
vals_l = [lengths[0]]
lcur = 0
# if Nx-plot then we just use sum of contigs lengths, else use reference_length
lsum = sum(lengths)
if reference_lengths:
lsum = reference_lengths[id]
min_difference = 0
if reduce_points:
min_difference = qconfig.min_difference
for l in lengths:
lcur += l
x = lcur * 100.0 / lsum
if can_draw_plots:
vals_Nx.append(vals_Nx[-1] + 1e-10) # eps
vals_l.append(l)
vals_Nx.append(x)
vals_l.append(l)
if vals_y[-1] - l > min_difference or len(vals_x) == 1:
vals_x.append(vals_x[-1] + 1e-10) # eps
vals_y.append(l)
vals_x.append(x)
vals_y.append(l)
# add to plot
json_vals_x.append(vals_x)
json_vals_y.append(vals_y)
if can_draw_plots:
vals_Nx.append(vals_Nx[-1] + 1e-10) # eps
vals_l.append(0.0)
vals_x.append(vals_x[-1] + 1e-10) # eps
vals_y.append(0.0)
color, ls = get_color_and_ls(contigs_fpath)
plots.append(Plot(vals_Nx, vals_l, color, ls))
if qconfig.html_report:
from quast_libs.html_saver import html_saver
html_saver.save_coord(results_dir, json_vals_x, json_vals_y, 'coord' + title, contigs_fpaths)
if not can_draw_plots:
return
legend_list = [label_from_fpath(fpath) for fpath in contigs_fpaths]
create_plot(plot_fpath, title, plots, legend_list, x_label='x', y_label='Contig length', x_limit=[0, 100])
def frc_plot(results_dir, ref_fpath, contigs_fpaths, contigs_aligned_lengths,
features_in_contigs_by_file, plot_fpath, title):
if can_draw_plots:
logger.info(' Drawing ' + title + ' FRCurve plot...')
plots = []
max_y = 0
max_x = 0
ref_length = sum(
fastaparser.get_chr_lengths_from_fastafile(ref_fpath).values())
json_vals_x = [] # coordinates for Nx-like plots in HTML-report
json_vals_y = []
max_features = max(
sum(feature_in_contigs)
for feature_in_contigs in features_in_contigs_by_file.values()) + 1
#create TSV file for metaquast features
outf = open(results_dir + os.sep + "metaquast_frc.tsv", 'w')
outf.write(
"Assembly\tContig_ID\tContig_Length\tFeature_Count\tFeature_Type\n")
aligned_contigs_fpaths = []
idx = 0
legend_list = [label_from_fpath(fpath) for fpath in contigs_fpaths]
max_len = 0
max_features = 0
for contigs_fpath in contigs_fpaths:
x_vals = [0]
y_vals = [0]
cumulative_len = 0
cumulative_features = 0
aligned_lengths = contigs_aligned_lengths[contigs_fpath]
feature_in_contigs = features_in_contigs_by_file[contigs_fpath]
contigs_lens = fastaparser.get_chr_lengths_from_fastafile(
contigs_fpath)
if not aligned_lengths or not feature_in_contigs:
continue
aligned_contigs_fpaths.append(contigs_fpath)
len_with_zero_features = 0
lengths = []
non_zero_feature_in_contigs = []
ctg_idx = 1
#create unsorted TSV
for l, feature in zip(aligned_lengths, feature_in_contigs):
if l > 0:
outf.write("%s\t%s\t%d\t%d\t%s\n" %
(legend_list[idx], ctg_idx, l, feature, title))
ctg_idx += 1
if feature == 0:
len_with_zero_features += l
if l > 0:
lengths.append(l)
non_zero_feature_in_contigs.append(feature)
optimal_sorted_tuples = sorted(
zip(lengths, non_zero_feature_in_contigs),
reverse=True) # sort by len/features ratio
sorted_lengths = [tuple[0] for tuple in optimal_sorted_tuples]
sorted_features = [tuple[1] for tuple in optimal_sorted_tuples]
for tuple in optimal_sorted_tuples:
cumulative_len += tuple[0]
cumulative_features += tuple[1]
y_vals.append(cumulative_features)
x_vals.append(cumulative_len)
#y_vals.append(cumulative_features)
#x_vals.append(cumulative_len )
json_vals_x.append(y_vals)
json_vals_y.append(x_vals)
max_y = max(max_y, max(y_vals))
max_x = max(max_x, max(x_vals))
idx += 1
color, ls = get_color_and_ls(contigs_fpath)
plots.append(Plot(x_vals, y_vals, color, ls))
if qconfig.html_report:
from quast_libs.html_saver import html_saver
html_saver.save_coord(results_dir, json_vals_x, json_vals_y,
'coord' + title, aligned_contigs_fpaths)
if can_draw_plots:
title = 'FRCurve (' + title + ')'
legend_list = [
label_from_fpath(fpath) for fpath in aligned_contigs_fpaths
]
create_plot(plot_fpath,
title,
plots,
legend_list,
x_label='Cumulative length',
y_label='Cumulative features',
y_limit=[0, max_y],
x_limit=[0, max_x])
def frc_plot(results_dir, ref_fpath, contigs_fpaths, contigs_aligned_lengths,
features_in_contigs_by_file, plot_fpath, title):
if can_draw_plots:
logger.info(' Drawing ' + title + ' FRCurve plot...')
plots = []
max_y = 0
ref_length = sum(
fastaparser.get_chr_lengths_from_fastafile(ref_fpath).values())
json_vals_x = [] # coordinates for Nx-like plots in HTML-report
json_vals_y = []
max_features = max(
sum(feature_in_contigs)
for feature_in_contigs in features_in_contigs_by_file.values()) + 1
aligned_contigs_fpaths = []
for contigs_fpath in contigs_fpaths:
aligned_lengths = contigs_aligned_lengths[contigs_fpath]
feature_in_contigs = features_in_contigs_by_file[contigs_fpath]
if not aligned_lengths or not feature_in_contigs:
continue
aligned_contigs_fpaths.append(contigs_fpath)
len_with_zero_features = 0
lengths = []
non_zero_feature_in_contigs = []
for l, feature in zip(aligned_lengths, feature_in_contigs):
if feature == 0:
len_with_zero_features += l
else:
lengths.append(l)
non_zero_feature_in_contigs.append(feature)
optimal_sorted_tuples = sorted(
zip(lengths, non_zero_feature_in_contigs),
key=lambda tuple: tuple[0] * 1.0 / tuple[1],
reverse=True) # sort by len/features ratio
sorted_lengths = [tuple[0] for tuple in optimal_sorted_tuples]
sorted_features = [tuple[1] for tuple in optimal_sorted_tuples]
x_vals = []
y_vals = []
for features_n in range(max_features):
features_cnt = 0
cumulative_len = len_with_zero_features
for l, feature in zip(sorted_lengths, sorted_features):
if features_cnt + feature <= features_n:
features_cnt += feature
cumulative_len += l
if features_cnt == features_n:
break
x_vals.append(features_n)
y_vals.append(cumulative_len * 100.0 / ref_length)
x_vals.append(features_n + 1)
y_vals.append(cumulative_len * 100.0 / ref_length)
json_vals_x.append(x_vals)
json_vals_y.append(y_vals)
max_y = max(max_y, max(y_vals))
color, ls = get_color_and_ls(contigs_fpath)
plots.append(Plot(x_vals, y_vals, color, ls))
if qconfig.html_report:
from quast_libs.html_saver import html_saver
html_saver.save_coord(results_dir, json_vals_x, json_vals_y,
'coord' + title, aligned_contigs_fpaths)
if can_draw_plots:
title = 'FRCurve (' + title + ')'
legend_list = [
label_from_fpath(fpath) for fpath in aligned_contigs_fpaths
]
create_plot(plot_fpath,
title,
plots,
legend_list,
x_label='Feature space',
y_label='Genome coverage (%)',
x_limit=[0, max_features],
y_limit=[0, max(100, max_y)])
def EAxmax_plot(results_dir, reduce_points, contigs_fpaths, plot_fpath, title,
ea_x_max):
if can_draw_plots:
logger.info(' Drawing ' + title + ' plot...')
ea_x_max = eval(ea_x_max)
plots = []
json_vals_x = [] # coordinates for Nx-like plots in HTML-report
json_vals_y = []
vals_x = [0.0]
vals_y = [float(ea_x_max[0])]
# calculate values for the plot
vals_px = [0.0]
vals_py = [float(ea_x_max[0])]
min_difference = 0
if reduce_points:
min_difference = qconfig.min_difference
for x, eax in enumerate(ea_x_max):
eax = float(eax)
if can_draw_plots:
vals_px.append(vals_px[-1] + 1e-2) # eps
vals_py.append(eax)
vals_px.append(x)
vals_py.append(eax)
if vals_y[-1] - eax > min_difference or len(vals_x) == 1:
vals_x.append(vals_x[-1] + 1e-2) # eps
vals_y.append(eax)
vals_x.append(x)
vals_y.append(eax)
# add to plot
json_vals_x.append(vals_x)
json_vals_y.append(vals_y)
if can_draw_plots:
vals_px.append(vals_px[-1] + 1e-2) # eps
vals_py.append(0.0)
vals_x.append(vals_x[-1] + 1e-2) # eps
vals_y.append(0.0)
from quast_libs import plotter_data
color = plotter_data.colors[0]
ls = plotter_data.primary_line_style
plots.append(Plot(vals_px, vals_py, color, ls))
if qconfig.html_report:
from quast_libs.html_saver import html_saver
html_saver.save_coord(results_dir, json_vals_x, json_vals_y,
'coord' + title, contigs_fpaths)
# Save raw coordinates
with open(plot_fpath + ".csv", 'w') as file:
for x, y in zip(vals_px, vals_py):
file.write(str(x) + ", " + str(y) + "\n")
if not can_draw_plots:
return
legend_list = [label_from_fpath(fpath) for fpath in contigs_fpaths]
create_plot(plot_fpath,
title,
plots,
legend_list,
x_label='x',
y_label='EAxmax',
x_limit=[0, 100])
def Nx_plot(results_dir, reduce_points, contigs_fpaths, lists_of_lengths, plot_fpath, title='Nx', reference_lengths=None, json_output_dir=None):
if can_draw_plots:
logger.info(' Drawing ' + title + ' plot...')
import matplotlib.pyplot
import matplotlib.ticker
figure = matplotlib.pyplot.figure()
matplotlib.pyplot.rc('font', **font)
max_y = 0
color_id = 0
json_vals_x = [] # coordinates for Nx-like plots in HTML-report
json_vals_y = []
for id, (contigs_fpath, lengths) in enumerate(itertools.izip(contigs_fpaths, lists_of_lengths)):
if not lengths:
json_vals_x.append([])
json_vals_y.append([])
continue
vals_x = [0.0]
vals_y = [lengths[0]]
lengths.sort(reverse=True)
# calculate values for the plot
vals_Nx = [0.0]
vals_l = [lengths[0]]
lcur = 0
# if Nx-plot then we just use sum of contigs lengths, else use reference_length
lsum = sum(lengths)
if reference_lengths:
lsum = reference_lengths[id]
min_difference = 0
if reduce_points:
min_difference = qconfig.min_difference
for l in lengths:
lcur += l
x = lcur * 100.0 / lsum
if can_draw_plots:
vals_Nx.append(vals_Nx[-1] + 1e-10) # eps
vals_l.append(l)
vals_Nx.append(x)
vals_l.append(l)
if vals_y[-1] - l > min_difference or len(vals_x) == 1:
vals_x.append(vals_x[-1] + 1e-10) # eps
vals_y.append(l)
vals_x.append(x)
vals_y.append(l)
# add to plot
json_vals_x.append(vals_x)
json_vals_y.append(vals_y)
if can_draw_plots:
vals_Nx.append(vals_Nx[-1] + 1e-10) # eps
vals_l.append(0.0)
vals_x.append(vals_x[-1] + 1e-10) # eps
vals_y.append(0.0)
max_y = max(max_y, max(vals_l))
color, ls = get_color_and_ls(contigs_fpath)
matplotlib.pyplot.plot(vals_Nx, vals_l, color=color, lw=line_width, ls=ls)
if qconfig.html_report:
from quast_libs.html_saver import html_saver
html_saver.save_coord(results_dir, json_vals_x, json_vals_y, 'coord' + title, contigs_fpaths)
if json_output_dir:
from quast_libs.html_saver import json_saver
json_saver.save_coord(json_output_dir, json_vals_x, json_vals_y, title, contigs_fpaths)
if not can_draw_plots:
return
if with_title:
matplotlib.pyplot.title(title)
matplotlib.pyplot.grid(with_grid)
ax = matplotlib.pyplot.gca()
# Shink current axis's height by 20% on the bottom
box = ax.get_position()
ax.set_position([box.x0, box.y0 + box.height * 0.2, box.width, box.height * 0.8])
legend_list = map(qutils.label_from_fpath, contigs_fpaths)
# Put a legend below current axis
try: # for matplotlib <= 2009-12-09
ax.legend(legend_list, loc='upper center', bbox_to_anchor=(0.5, -0.1), fancybox=True,
shadow=True, ncol=n_columns if n_columns<3 else 3)
except Exception:
pass
ylabel = 'Contig length '
ylabel, mkfunc = y_formatter(ylabel, max_y)
matplotlib.pyplot.xlabel('x', fontsize=axes_fontsize)
matplotlib.pyplot.ylabel(ylabel, fontsize=axes_fontsize)
mkformatter = matplotlib.ticker.FuncFormatter(mkfunc)
ax.yaxis.set_major_formatter(mkformatter)
matplotlib.pyplot.xlim([0, 100])
#ax.invert_xaxis()
#matplotlib.pyplot.ylim(matplotlib.pyplot.ylim()[::-1])
xLocator, yLocator = get_locators()
ax.yaxis.set_major_locator(yLocator)
ax.xaxis.set_major_locator(xLocator)
plot_fpath += '.' + qconfig.plot_extension
matplotlib.pyplot.savefig(plot_fpath, bbox_inches='tight')
logger.info(' saved to ' + plot_fpath)
pdf_plots_figures.append(figure)
matplotlib.pyplot.close()
def Nx_plot(results_dir, reduce_points, contigs_fpaths, lists_of_lengths, plot_fpath, title='Nx', reference_lengths=None, json_output_dir=None):
if can_draw_plots:
logger.info(' Drawing ' + title + ' plot...')
import matplotlib.pyplot
import matplotlib.ticker
figure = matplotlib.pyplot.figure()
matplotlib.pyplot.rc('font', **font)
max_y = 0
color_id = 0
json_vals_x = [] # coordinates for Nx-like plots in HTML-report
json_vals_y = []
for id, (contigs_fpath, lengths) in enumerate(zip(contigs_fpaths, lists_of_lengths)):
if not lengths:
json_vals_x.append([])
json_vals_y.append([])
continue
vals_x = [0.0]
vals_y = [lengths[0]]
lengths.sort(reverse=True)
# calculate values for the plot
vals_Nx = [0.0]
vals_l = [lengths[0]]
lcur = 0
# if Nx-plot then we just use sum of contigs lengths, else use reference_length
lsum = sum(lengths)
if reference_lengths:
lsum = reference_lengths[id]
min_difference = 0
if reduce_points:
min_difference = qconfig.min_difference
for l in lengths:
lcur += l
x = lcur * 100.0 / lsum
if can_draw_plots:
vals_Nx.append(vals_Nx[-1] + 1e-10) # eps
vals_l.append(l)
vals_Nx.append(x)
vals_l.append(l)
if vals_y[-1] - l > min_difference or len(vals_x) == 1:
vals_x.append(vals_x[-1] + 1e-10) # eps
vals_y.append(l)
vals_x.append(x)
vals_y.append(l)
# add to plot
json_vals_x.append(vals_x)
json_vals_y.append(vals_y)
if can_draw_plots:
vals_Nx.append(vals_Nx[-1] + 1e-10) # eps
vals_l.append(0.0)
vals_x.append(vals_x[-1] + 1e-10) # eps
vals_y.append(0.0)
max_y = max(max_y, max(vals_l))
color, ls = get_color_and_ls(contigs_fpath)
matplotlib.pyplot.plot(vals_Nx, vals_l, color=color, lw=line_width, ls=ls)
if qconfig.html_report:
from quast_libs.html_saver import html_saver
html_saver.save_coord(results_dir, json_vals_x, json_vals_y, 'coord' + title, contigs_fpaths)
if json_output_dir:
from quast_libs.html_saver import json_saver
json_saver.save_coord(json_output_dir, json_vals_x, json_vals_y, title, contigs_fpaths)
if not can_draw_plots:
return
if with_title:
matplotlib.pyplot.title(title)
matplotlib.pyplot.grid(with_grid)
ax = matplotlib.pyplot.gca()
# Shink current axis's height by 20% on the bottom
box = ax.get_position()
ax.set_position([box.x0, box.y0 + box.height * 0.2, box.width, box.height * 0.8])
legend_list = [qutils.label_from_fpath(fpath) for fpath in contigs_fpaths]
# Put a legend below current axis
try: # for matplotlib <= 2009-12-09
ax.legend(legend_list, loc='upper center', bbox_to_anchor=(0.5, -0.1), fancybox=True,
shadow=True, ncol=n_columns if n_columns<3 else 3)
except Exception:
pass
ylabel = 'Contig length '
ylabel, mkfunc = y_formatter(ylabel, max_y)
matplotlib.pyplot.xlabel('x', fontsize=axes_fontsize)
matplotlib.pyplot.ylabel(ylabel, fontsize=axes_fontsize)
mkformatter = matplotlib.ticker.FuncFormatter(mkfunc)
ax.yaxis.set_major_formatter(mkformatter)
matplotlib.pyplot.xlim([0, 100])
#ax.invert_xaxis()
#matplotlib.pyplot.ylim(matplotlib.pyplot.ylim()[::-1])
xLocator, yLocator = get_locators()
ax.yaxis.set_major_locator(yLocator)
ax.xaxis.set_major_locator(xLocator)
plot_fpath += '.' + qconfig.plot_extension
matplotlib.pyplot.savefig(plot_fpath, bbox_inches='tight')
logger.info(' saved to ' + plot_fpath)
pdf_plots_figures.append(figure)
matplotlib.pyplot.close()
