def _plot_genes_job(gene, region_series_fits, filename, bin_centers):
with interactive(False):
print 'Saving figure for gene {}'.format(gene)
fig = _plot_gene_inner(gene,
region_series_fits,
change_distribution_bin_centers=bin_centers)
save_figure(fig, filename, b_close=True)
def _plot_exons_job(gene, region, exons_series_fits, filename):
with interactive(False):
print 'Saving Exons figure for gene {} on region {}'.format(
gene, region)
exons_chunks = split_list(exons_series_fits, cfg.exons_per_plot)
for i, chunk in enumerate(exons_chunks):
fig = _plot_exons_inner(gene, region, chunk, i + 1,
len(exons_chunks))
curr_fig_filename = filename[:-4] + cfg.exon_separator + str(
i + 1) + filename[-4:] if i > 0 else filename
save_figure(fig, curr_fig_filename, b_close=True, b_square=False)
def _plot_series_job(series, fit, filename, use_correlations, change_distribution, figure_kw):
if figure_kw is None:
figure_kw = {}
with interactive(False):
print 'Saving figure for {}@{}'.format(series.gene_name, series.region_name)
if use_correlations:
preds = fit.with_correlations.LOO_predictions
else:
preds = fit.LOO_predictions
fig = plot_one_series(series, fit.fitter.shape, fit.theta, preds, change_distribution=change_distribution, **figure_kw)
save_figure(fig, filename, b_close=True)
def _plot_series_job(series, fit, filename, use_correlations,
change_distribution, figure_kw):
if figure_kw is None:
figure_kw = {}
with interactive(False):
print 'Saving figure for {}@{}'.format(series.gene_name,
series.region_name)
if use_correlations:
preds = fit.with_correlations.LOO_predictions
else:
preds = fit.LOO_predictions
fig = plot_one_series(series,
fit.fitter.shape,
fit.theta,
preds,
change_distribution=change_distribution,
**figure_kw)
save_figure(fig, filename, b_close=True)
def create_score_distribution_html(fits, use_correlations, dirname):
ensure_dir(dirname)
with interactive(False):
hist_filename = 'R2-hist.png'
fig = plot_score_distribution(fits,use_correlations)
save_figure(fig, join(dirname,hist_filename), b_close=True)
if use_correlations:
scatter_filename = 'comparison-scatter.png'
fig = plot_score_comparison_scatter_for_correlations(fits)
save_figure(fig, join(dirname,scatter_filename), b_close=True)
delta_hist_filename = 'R2-delta-hist.png'
fig = plot_score_improvement_histogram_for_correlations(fits)
save_figure(fig, join(dirname,delta_hist_filename), b_close=True)
image_size = "50%"
from jinja2 import Template
import shutil
html = Template("""
<html>
<head>
<link rel="stylesheet" type="text/css" href="score-distribution.css">
</head>
<body>
<center><H1>R2 Score Distribution</H1></center>
<a href="{{hist_filename}}"> <img src="{{hist_filename}}" height="{{image_size}}"></a>
{% if use_correlations %}
<a href="{{delta_hist_filename}}"> <img src="{{delta_hist_filename}}" height="{{image_size}}"></a>
<a href="{{scatter_filename}}"> <img src="{{scatter_filename}}" height="{{image_size}}"></a>
{% endif %}
</body>
</html>
""").render(**locals())
filename = join(dirname,'scores.html')
with open(filename, 'w') as f:
f.write(html)
shutil.copy(join(resources_dir(),'score-distribution.css'), dirname)
def create_score_distribution_html(fits, use_correlations, dirname):
ensure_dir(dirname)
with interactive(False):
hist_filename = 'R2-hist.png'
fig = plot_score_distribution(fits, use_correlations)
save_figure(fig, join(dirname, hist_filename), b_close=True)
if use_correlations:
scatter_filename = 'comparison-scatter.png'
fig = plot_score_comparison_scatter_for_correlations(fits)
save_figure(fig, join(dirname, scatter_filename), b_close=True)
delta_hist_filename = 'R2-delta-hist.png'
fig = plot_score_improvement_histogram_for_correlations(fits)
save_figure(fig, join(dirname, delta_hist_filename), b_close=True)
image_size = "50%"
import shutil
html = get_jinja_env().get_template('R2.jinja').render(**locals())
filename = join(dirname, 'scores.html')
with open(filename, 'w') as f:
f.write(html)
shutil.copy(join(resources_dir(), 'score-distribution.css'), dirname)
def _plot_genes_job(gene, region_series_fits, filename, bin_centers):
with interactive(False):
print 'Saving figure for gene {}'.format(gene)
fig = _plot_gene_inner(gene, region_series_fits, change_distribution_bin_centers=bin_centers)
save_figure(fig, filename, b_close=True)
