def plot_greyscale_boxplot(graph_image, description, sample_type, sample_df, colors, y_limit, min_length, max_length, plot_mean):
pyplot.rc('font',**{'family':'sans-serif','sans-serif':[JOURNAL_FONT]})
for dpi in JOURNAL_GRAPH_DPIS:
figure = Figure(dpi=dpi)
figure.patch.set_facecolor('white')
ax = figure.add_subplot(1, 1, 1)
for (condition, df) in sample_df.groupby(CONDITION):
numeric_columns = df.columns - GROUP_BY_COLUMNS
numeric_df = df[numeric_columns]
# Remove 0 length from boxplot - it will use axis 1... for elements 0...
boxplot_df = numeric_df[numeric_df.columns[1:]]
data_lists = []
for column in boxplot_df:
data_lists.append(boxplot_df[column])
if plot_mean:
lines = ax.plot(numeric_df.mean(axis=0), linestyle='dashed', zorder=-1)
pyplot.setp(lines, color=colors[condition])
r = ax.boxplot(data_lists, patch_artist=True)
pyplot.setp(r.values(), color=colors[condition], lw=1)
pyplot.setp(r['boxes'], facecolor='white')
patches = []
labels = []
for name in ["WT", "pin/pin"]:
color = colors[name]
labels.append(name)
patches.append(Rectangle((0, 0), 1, 1, fc=color))
ax.legend(patches, labels, loc=2)
# Only show range we're interested in
# Use .5 to get a bit of spacing, & don't show numbers either side
ax.set_xlim(min_length - .5, max_length + .5)
ax.set_ylim(0, y_limit)
ax.set_xlabel("Read length", weight='bold', size=14)
ax.set_ylabel("Percentage of %s" % description, weight='bold', size=14)
ax.set_title(sample_type, weight='bold', size=18)
canvas = FigureCanvasAgg(figure)
canvas.print_tif(graph_image + '_%s_dpi.tiff' % dpi)
canvas.print_png(graph_image + '_%d_dpi.png' % dpi)
