def genes_operons_plot(reference_value, contigs_fpaths, files_feature_in_contigs, plot_fpath, title):
if not can_draw_plots:
return
logger.info(' Drawing ' + title + ' cumulative plot...')
plots = []
max_x = 0
for contigs_fpath in contigs_fpaths:
# calculate values for the plot
feature_in_contigs = files_feature_in_contigs[contigs_fpath]
x_vals = list(range(len(feature_in_contigs) + 1))
y_vals = [0]
total_full = 0
for feature_amount in feature_in_contigs:
total_full += feature_amount
y_vals.append(total_full)
if len(x_vals) > 0:
max_x = max(x_vals[-1], max_x)
color, ls = get_color_and_ls(contigs_fpath)
plots.append(Plot(x_vals, y_vals, color, ls))
if reference_value:
plots.append(Plot([0, max_x], [reference_value, reference_value], reference_color, reference_ls))
title = 'Cumulative # complete ' + title
legend_list = [label_from_fpath(fpath) for fpath in contigs_fpaths]
if reference_value:
legend_list += ['Reference']
create_plot(plot_fpath, title, plots, legend_list, x_label='Contig index', y_label=title)
def GC_content_plot(ref_fpath, contigs_fpaths, list_of_GC_distributions, plot_fpath):
if not can_draw_plots or qconfig.no_gc:
return
title = 'GC content'
logger.info(' Drawing ' + title + ' plot...')
plots = []
all_fpaths = contigs_fpaths
if ref_fpath:
all_fpaths = contigs_fpaths + [ref_fpath]
for i, (GC_distribution_x, GC_distribution_y) in enumerate(list_of_GC_distributions):
# for log scale
for id2, v in enumerate(GC_distribution_y):
if v == 0:
GC_distribution_y[id2] = 0.1
# add to plot
if ref_fpath and (i == len(all_fpaths) - 1):
color = reference_color
ls = reference_ls
else:
color, ls = get_color_and_ls(all_fpaths[i])
plots.append(Plot(GC_distribution_x, GC_distribution_y, color, ls))
legend_list = [label_from_fpath(fpath) for fpath in contigs_fpaths]
if ref_fpath:
legend_list += ['Reference']
create_plot(plot_fpath, title, plots, legend_list, x_label='GC (%)', y_label='# windows', x_limit=[0, 100])
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 contigs_GC_content_plot(contigs_fpath, GC_distributions, plot_fpath):
if not can_draw_plots or qconfig.no_gc:
return
title = label_from_fpath(contigs_fpath) + ' GC content'
logger.info(' Drawing ' + title + ' plot...')
plots = []
color, ls = get_color_and_ls(contigs_fpath)
x_vals, y_vals = GC_distributions
for GC_x, GC_y in zip(x_vals, y_vals):
plots.append(Bar(GC_x, GC_y, color, width=5))
legend_list = [label_from_fpath(contigs_fpath)]
create_plot(plot_fpath, title, plots, legend_list, x_label='GC (%)', y_label='# contigs', x_limit=[0, 100])
def cumulative_plot(reference, contigs_fpaths, lists_of_lengths, plot_fpath,
title):
if not can_draw_plots:
return
logger.info(' Drawing cumulative plot...')
plots = []
max_x = 0
for (contigs_fpath, lengths) in zip(contigs_fpaths, lists_of_lengths):
y_vals = [0]
for l in sorted(lengths, reverse=True):
y_vals.append(y_vals[-1] + l)
x_vals = list(range(0, len(y_vals)))
if x_vals:
max_x = max(x_vals[-1], max_x)
color, ls = get_color_and_ls(contigs_fpath)
plots.append(Plot(x_vals, y_vals, color, ls))
if reference:
y_vals = [0]
for l in sorted(
fastaparser.get_chr_lengths_from_fastafile(reference).values(),
reverse=True):
y_vals.append(y_vals[-1] + l)
x_vals = list(range(0, len(y_vals)))
# extend reference curve to the max X-axis point
reference_length = y_vals[-1]
max_x = max(max_x, x_vals[-1])
y_vals.append(reference_length)
x_vals.append(max_x)
plots.append(Plot(x_vals, y_vals, reference_color, reference_ls))
legend_list = [label_from_fpath(fpath) for fpath in contigs_fpaths]
if reference:
legend_list += ['Reference']
create_plot(plot_fpath,
title,
plots,
legend_list,
x_label='Contig index',
y_label='Cumulative length',
x_limit=[0, max_x])
def add_lengths_to_report(lengths, reporting, contigs_fpath):
if reporting:
## filling column "Assembly" with names of assemblies
report = reporting.get(contigs_fpath)
## filling columns "Number of contigs >=110 bp", ">=200 bp", ">=500 bp"
is_broken = False
if qconfig.scaffolds:
if contigs_fpath in qconfig.dict_of_broken_scaffolds or \
plotter_data.get_color_and_ls(contigs_fpath)[1] == plotter_data.secondary_line_style:
is_broken = True
min_threshold = 0 if not is_broken else qconfig.min_contig
report.add_field(reporting.Fields.CONTIGS__FOR_THRESHOLDS,
[sum(1 for l in lengths if l >= threshold) if threshold >= min_threshold else None
for threshold in qconfig.contig_thresholds])
report.add_field(reporting.Fields.TOTALLENS__FOR_THRESHOLDS,
[sum(l for l in lengths if l >= threshold) if threshold >= min_threshold else None
for threshold in qconfig.contig_thresholds])
def add_lengths_to_report(lengths, reporting, contigs_fpath):
if reporting:
## filling column "Assembly" with names of assemblies
report = reporting.get(contigs_fpath)
## filling columns "Number of contigs >=110 bp", ">=200 bp", ">=500 bp"
is_broken = False
if qconfig.scaffolds:
if contigs_fpath in qconfig.dict_of_broken_scaffolds or \
plotter_data.get_color_and_ls(contigs_fpath)[1] == plotter_data.secondary_line_style:
is_broken = True
min_threshold = 0 if not is_broken else qconfig.min_contig
report.add_field(reporting.Fields.CONTIGS__FOR_THRESHOLDS,
[sum(1 for l in lengths if l >= threshold) if threshold >= min_threshold else None
for threshold in qconfig.contig_thresholds])
report.add_field(reporting.Fields.TOTALLENS__FOR_THRESHOLDS,
[sum(l for l in lengths if l >= threshold) if threshold >= min_threshold else None
for threshold in qconfig.contig_thresholds])
def histogram(contigs_fpaths, values, plot_fpath, title='', yaxis_title='', bottom_value=None,
top_value=None):
if not can_draw_plots:
return
if len(contigs_fpaths) < 2: #
logger.info(' Skipping drawing ' + title + ' histogram... (less than 2 columns histogram makes no sense)')
return
logger.info(' Drawing ' + title + ' histogram...')
plots = []
min_value = sorted(values)[0]
max_value = sorted(values, reverse=True)[0]
exponent = None
if max_value == min_value:
if max_value > 0:
exponent = math.pow(10, math.floor(math.log(max_value, 10)))
else:
exponent = 1
else:
exponent = math.pow(10, math.floor(math.log(max_value - min_value, 10)))
if not bottom_value:
bottom_value = (math.floor(min_value / exponent) - 5) * exponent
if not top_value:
top_value = (math.ceil(max_value / exponent) + 1) * exponent
#bars' params
width = 0.3
interval = width // 3
start_pos = interval // 2
for i, (contigs_fpath, val) in enumerate(zip(contigs_fpaths, values)):
color, ls = get_color_and_ls(contigs_fpath)
if ls == primary_line_style:
hatch = ''
else:
hatch = 'x'
plots.append(Bar(start_pos + (width + interval) * i, val, color, width=width, hatch=hatch))
legend_list = [label_from_fpath(fpath) for fpath in contigs_fpaths]
create_plot(plot_fpath, title, plots, legend_list, x_label='', y_label=yaxis_title, is_histogram=True,
x_limit=[0, start_pos + width * len(contigs_fpaths) + interval * (len(contigs_fpaths) - 1)],
y_limit=[max(bottom_value, 0), top_value])
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 coverage_histogram(contigs_fpaths,
values,
plot_fpath,
title='',
bin_size=None,
draw_bars=None,
max_cov=None,
low_threshold=None,
high_threshold=None):
if not can_draw_plots:
return
logger.info(' Drawing ' + title + '...')
plots = []
max_y = 0
max_x = max(len(v) for v in values)
x_vals = list(range(0, max_x))
bar_width = 1.0
bar_widths = [bar_width] * max_x
if high_threshold and draw_bars:
x_vals.append(max_x + 1)
bar_widths[-1] = 2.0
x_ticks_labels = [
str(x_val * bin_size + low_threshold) for x_val in x_vals
]
if low_threshold:
x_vals = [x_val + 1 for x_val in x_vals]
x_vals[0] = 0
bar_widths[0] = 2.0
for i, (contigs_fpath, y_vals) in enumerate(zip(contigs_fpaths, values)):
max_y = max(max(y_vals), max_y)
color, ls = get_color_and_ls(contigs_fpath)
if draw_bars:
for x_val, y_val, bar_width in zip(x_vals, y_vals, bar_widths):
if bar_width == 2:
plots.append(
Bar(x_val,
y_val,
color,
width=bar_width,
edgecolor='#595959',
hatch='x'))
else:
plots.append(Bar(x_val, y_val, color, width=bar_width))
plots.append(Bar(0, 0, color=color))
else:
y_vals.append(y_vals[-1])
plot_x_vals = [x_val + 0.5 for x_val in x_vals]
plot_x_vals[-1] += 1
plots.append(
Plot(plot_x_vals,
y_vals[:-1],
marker='o',
markersize=3,
color=color,
ls=ls))
x_factor = max(1, len(x_vals) // 10)
x_ticks = x_vals[::x_factor]
x_ticks_labels = x_ticks_labels[::x_factor]
if low_threshold:
x_ticks_labels.insert(0, 0)
if high_threshold:
if low_threshold:
last_tick = (high_threshold - low_threshold
) // bin_size + 4 # first and last bars have width 2
else:
last_tick = high_threshold // bin_size + 2
x_ticks = [x for x in x_ticks if x < last_tick]
x_ticks_labels = x_ticks_labels[:len(x_ticks)]
x_ticks.append(last_tick)
x_ticks_labels.append(str(max_cov))
for i in range(len(x_ticks) - 1, 0, -1):
val, prev_val = x_ticks[i], x_ticks[i - 1]
while val - 1 != prev_val:
val -= 1
x_ticks.insert(i, val)
x_ticks_labels.insert(i, '')
legend_list = [label_from_fpath(fpath) for fpath in contigs_fpaths]
xlabel = 'Coverage depth (x)'
ylabel = 'Total length'
create_plot(plot_fpath,
title,
plots,
legend_list,
x_label=xlabel,
y_label=ylabel,
is_histogram=True,
x_limit=[0, max(x_ticks)],
y_limit=[0, max_y * 1.1],
x_ticks=x_ticks_labels)
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)])
