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appraise: plot: Many improvements.
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@wwood
wwood committed Feb 21, 2018
1 parent b6014b8 commit 0b793de
Showing 1 changed file with 46 additions and 24 deletions.
70 changes: 46 additions & 24 deletions singlem/appraisal_result.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,7 @@
matplotlib.use('Agg') # Must be run the first time matplotlib is imported.
import matplotlib.cm
import matplotlib.pyplot as plt
plt.rcParams['svg.fonttype'] = 'none' # Export text as text, not paths
import matplotlib.gridspec as gridspec
import numpy

Expand Down Expand Up @@ -71,7 +72,10 @@ def plot(self, **kwargs):
else:
genes_to_plot = genes

logging.info("Generating plots for markers: %s" % genes_to_plot)
if len(genes_to_plot) == 1:
logging.info("Generating plot for marker: %s" % genes_to_plot[0])
else:
logging.info("Generating plots for markers: %s" % genes_to_plot)
for gene in genes_to_plot:
self._plot_gene(
"%s%s.svg" % (output_svg_base, gene) if single_output_svg is None \
Expand Down Expand Up @@ -177,14 +181,21 @@ def _plot_gene(self, output_svg, cluster_identity, gene, doing_assembly, doing_b
if num_samples == 0:
raise Exception("Cannot plot an appraisal when there are no samples to appraise")

fig = plt.figure(figsize=(4.0/5*9 + num_samples*1.0/5*9,5))
# margins of figure:
# 4 + num_samples is the number of x panels
# 2 or 3 is the number of y panels
# y needs an extra size for title
panel_side_length = 1.9
num_y_panels = 1
if doing_assembly: num_y_panels += 1
if doing_binning: num_y_panels += 1
fig = plt.figure(figsize=(
(4 + num_samples)*panel_side_length,
num_y_panels*panel_side_length + 0.5))
fig.suptitle("SingleM appraisal plot (%s)" % gene)
num_panels = 1
if doing_assembly: num_panels += 1
if doing_binning: num_panels += 1
gs = gridspec.GridSpec(num_panels, 4+num_samples)
gs = gridspec.GridSpec(num_y_panels, 4+num_samples)

legend_axis = fig.add_subplot(gs[:-1,num_samples:])
legend_axis = fig.add_subplot(gs[-2,-4])
self._plot_legend(legend_axis, plot_info, appraisal_colours)

max_count = plot_info.max_count
Expand Down Expand Up @@ -257,6 +268,7 @@ def _plot_gene(self, output_svg, cluster_identity, gene, doing_assembly, doing_b
axis = fig.add_subplot(gs[-1,num_samples])
self._plot_scale(axis, max_total_count)

logging.info("Writing output plot to %s" % output_svg)
fig.savefig(output_svg, format='svg')


Expand All @@ -273,7 +285,7 @@ def _plot_otu(self, axis, sizes, colors, max_count, name):
dx = [rect['dx'] for rect in rects]
dy = [rect['dy'] for rect in rects]

axis.bar(x, dy, width=dx, bottom=y, color=colors, align='edge', edgecolor='black', linewidth=0.5)
axis.bar(x, dy, width=dx, bottom=y, color=colors, align='edge', edgecolor='black', linewidth=0.2)

axis.set_aspect('equal')
axis.set_ylim(-0.3,10.3) # Add 0.1 so the edges are not truncated.
Expand All @@ -283,7 +295,7 @@ def _plot_otu(self, axis, sizes, colors, max_count, name):
axis.set_axis_off()

if name is not None:
fp = matplotlib.font_manager.FontProperties(size=9,weight='bold')
fp = matplotlib.font_manager.FontProperties(size=9)
axis.text(-1, 5,
name,
font_properties=fp,
Expand All @@ -292,33 +304,35 @@ def _plot_otu(self, axis, sizes, colors, max_count, name):
verticalalignment='center')

def _plot_legend(self, axis, plot_info, appraise_colours):
axis.set_aspect('equal')
# Setup global legend properties
axis.set_xlim([0,10])
axis.set_ylim([0,14])
xlim=[-0.3,10.3]
ylim=xlim
axis.set_xlim(xlim)
axis.set_ylim(ylim)
axis.set_axis_off()
fp = matplotlib.font_manager.FontProperties(size=9,weight='bold')
axis.text(0.2, 13, 'Taxonomy', font_properties=fp)
fp = matplotlib.font_manager.FontProperties(size=9)
axis.text(0.2, 10.6, 'Cluster taxonomy', font_properties=fp)
fp = matplotlib.font_manager.FontProperties(size=6)

# Plot each legend member
# Plot the 5 clusters with the highest counts
next_y_offset = 0
num_to_print = 5
top=12.6
top=10.1
last_index=len(appraise_colours)
box_height = 0.6
space=0.2
box_height = 0.8
space=(top - next_y_offset-len(appraise_colours)*box_height)/(last_index-1)
for i, sequence in enumerate(plot_info.ordered_sequences()):
if i >= last_index: break
bottom = top-next_y_offset-box_height
axis.bar(0.1, bottom=bottom, height=box_height, width=0.5,
color=appraise_colours.colour(i), align='edge', edgecolor='black', linewidth=0.5)
axis.bar(0.1, bottom=bottom, height=box_height, width=box_height,
color=appraise_colours.colour(i), align='edge', edgecolor='black', linewidth=0.2)
if i==last_index-1:
t = 'Other'
else:
t = plot_info.cluster(sequence).representative_otu.taxonomy.replace('Root; ','')
t = re.sub(r'.__','',t)
axis.text(0.75, top-next_y_offset-box_height*0.6, t, font_properties=fp)
axis.text(box_height+0.1+0.2+0.1, top-next_y_offset-box_height*0.6-0.2, t, font_properties=fp)
next_y_offset += box_height + space

def _plot_scale(self, axis, max_total_count):
Expand All @@ -337,18 +351,26 @@ def _plot_scale(self, axis, max_total_count):
sides = list([math.sqrt(normalised[i]) for i, value in enumerate(scale_values)])
overlap = (ylim[1]-ylim[0]-sum(sides))/(len(sides)-1)
next_bottom = ylim[0]
xoffset = ylim[1]-ylim[0]-sides[0]
fp = matplotlib.font_manager.FontProperties(size=6)
for i, value in enumerate(scale_values):
side = sides[i]
axis.bar(5,
axis.bar(10-side/2-0.1-xoffset,
bottom=next_bottom,
height=side,width=side,
color='0.7',edgecolor='black',linewidth=0.5)
color='0.7',edgecolor='black',linewidth=0.2)

# Add text
axis.text(10, next_bottom+side/2, value, verticalalignment='center')
if value == 1:
text = "1 read"
else:
text = "%i reads" % value
axis.text(10.2-xoffset, next_bottom+side/2, text,
verticalalignment='center', font_properties=fp)
# Setup for next loop iter
next_bottom += overlap + side
axis.set_title('OTU count')
fp = matplotlib.font_manager.FontProperties(size=9)
axis.text(0.2, 10.6, 'OTU count', font_properties=fp)


class AppraisalResult:
Expand Down

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