def _print_figure(axes, figure, plot_fhand, plot_legend=True, fmt='png'):
if figure is None:
return
if plot_legend:
axes.legend()
canvas = FigureCanvas(figure)
canvas.print_figure(plot_fhand, format=fmt)
plot_fhand.flush()
def _print_figure(axes, figure, plot_fhand, plot_legend=True, fmt='png'):
if figure is None:
return
if plot_legend:
axes.legend()
canvas = FigureCanvas(figure)
canvas.print_figure(plot_fhand, format=fmt)
plot_fhand.flush()
def plot_haplotypes(vcf_fhand, plot_fhand, genotype_mode=REFERENCE,
filter_alleles_gt=FILTER_ALLELES_GT):
reader = VCFReader(vcf_fhand)
# collect data
genotypes = None
samples = []
for snv in reader.parse_snvs():
if genotypes is None:
genotypes = {}
for call in snv.calls:
sample = call.sample
genotypes[sample] = []
samples.append(sample)
for call in snv.calls:
alleles = _get_alleles(call, filter_alleles_gt=filter_alleles_gt)
genotypes[call.sample].append(alleles)
# draw
n_samples = len(samples)
xsize = len(genotypes[sample]) / 100
if xsize >= 100:
xsize = 100
if xsize <= 8:
xsize = 8
ysize = n_samples * 2
if ysize >= 100:
ysize = 100
# print xsize, ysize
figure_size = (xsize, ysize)
fig = Figure(figsize=figure_size)
for index, sample in enumerate(samples):
axes = fig.add_subplot(n_samples, 1, index)
axes.set_title(sample)
y_data = genotypes[sample]
x_data = [i + 1 for i in range(len(y_data))]
x_data, y_data = _flatten_data(x_data, y_data)
axes.plot(x_data, y_data, marker='o',
linestyle='None', markersize=3.0, markeredgewidth=0,
markerfacecolor='red')
ylim = axes.get_ylim()
ylim = ylim[0] - 0.1, ylim[1] + 0.1
axes.set_ylim(ylim)
axes.tick_params(axis='x', bottom='off', top='off', which='both',
labelbottom='off')
axes.tick_params(axis='y', left='on', right='off', labelleft='off')
axes.set_ylabel(sample)
canvas = FigureCanvas(fig)
canvas.print_figure(plot_fhand, dpi=300)
plot_fhand.flush()
def _plot_segregation_debug(plot_info, fhand):
greens = ['#2d6e12', '#76b75b', '#164900']
reds = ['#8f0007', '#fb1f2a', '#b90009']
grays = ['0.5', '0.25', '0.75']
fig = Figure(figsize=(10, 4))
axes1 = fig.add_subplot(211)
axes2 = fig.add_subplot(212)
plot_info.sort(key=itemgetter('pos'))
is_close_snp = [geno_info['close_snp'] for geno_info in plot_info]
tested_snp_idx = is_close_snp.index(False)
passed = [geno_info['result'] for geno_info in plot_info]
total_cnts = [
geno_info['AA'] + geno_info['Aa'] + geno_info['aa']
for geno_info in plot_info
]
num_snvs = len(passed)
bottoms = [0] * num_snvs
freq_bottoms = [0] * num_snvs
lefts = range(num_snvs)
for idx, geno in enumerate(('AA', 'Aa', 'aa')):
cnts = [geno_info[geno] for geno_info in plot_info]
backcolors = [greens[idx] if pss else reds[idx] for pss in passed]
edgecolors = [grays[idx] for pss in passed]
backcolors[tested_snp_idx], edgecolors[tested_snp_idx] = \
edgecolors[tested_snp_idx], backcolors[tested_snp_idx]
heights = cnts
axes1.bar(lefts,
heights,
bottom=bottoms,
color=backcolors,
edgecolor=edgecolors)
freq_heights = [
height / total_cnt
for height, total_cnt in zip(heights, total_cnts)
]
axes2.bar(lefts,
freq_heights,
bottom=freq_bottoms,
color=backcolors,
edgecolor=edgecolors)
bottoms = [bot + heig for bot, heig in zip(bottoms, heights)]
freq_bottoms = [
bot + heig for bot, heig in zip(freq_bottoms, freq_heights)
]
axes1.tick_params(axis='y', which='both', left='off', right='off')
axes2.tick_params(axis='y', which='both', left='off', right='off')
canvas = FigureCanvas(fig)
canvas.print_figure(fhand)
fhand.flush()
def _plot_segregation_debug(plot_info, fhand):
greens = ['#2d6e12', '#76b75b', '#164900']
reds = ['#8f0007', '#fb1f2a', '#b90009']
grays = ['0.5', '0.25', '0.75']
fig = Figure(figsize=(10, 4))
axes1 = fig.add_subplot(211)
axes2 = fig.add_subplot(212)
plot_info.sort(key=itemgetter('pos'))
is_close_snp = [geno_info['close_snp'] for geno_info in plot_info]
tested_snp_idx = is_close_snp.index(False)
passed = [geno_info['result'] for geno_info in plot_info]
total_cnts = [geno_info['AA'] + geno_info['Aa'] + geno_info['aa'] for geno_info in plot_info]
num_snvs = len(passed)
bottoms = [0] * num_snvs
freq_bottoms = [0] * num_snvs
lefts = range(num_snvs)
for idx, geno in enumerate(('AA', 'Aa', 'aa')):
cnts = [geno_info[geno] for geno_info in plot_info]
backcolors = [greens[idx] if pss else reds[idx] for pss in passed]
edgecolors = [grays[idx] for pss in passed]
backcolors[tested_snp_idx], edgecolors[tested_snp_idx] = \
edgecolors[tested_snp_idx], backcolors[tested_snp_idx]
heights = cnts
axes1.bar(lefts, heights, bottom=bottoms, color=backcolors,
edgecolor=edgecolors)
freq_heights = [height/total_cnt for height, total_cnt in zip(heights, total_cnts)]
axes2.bar(lefts, freq_heights, bottom=freq_bottoms,
color=backcolors, edgecolor=edgecolors)
bottoms = [bot + heig for bot, heig in zip(bottoms, heights)]
freq_bottoms = [bot + heig for bot, heig in zip(freq_bottoms, freq_heights)]
axes1.tick_params(axis='y', which='both', left='off', right='off')
axes2.tick_params(axis='y', which='both', left='off', right='off')
canvas = FigureCanvas(fig)
canvas.print_figure(fhand)
fhand.flush()
def get_fig_and_canvas(num_rows=1, num_cols=1, figsize=None):
if figsize is None:
height = 5.0 * num_rows
width = 7.5 * num_cols
if height > 320.0:
height = 320.0
figsize = (width, height)
try:
fig = Figure(figsize=figsize)
canvas = FigureCanvas(fig)
except NameError:
msg = 'Matplotlib module is required to draw graphical histograms'
raise OptionalRequirementError(msg)
return fig, canvas
def get_canvas_and_axes(figure_size=FIGURE_SIZE,
left=0.1,
right=0.9,
top=0.9,
bottom=0.1,
plot_type=111):
'It returns a matplotlib canvas and axes instance'
try:
fig = Figure(figsize=FIGURE_SIZE)
canvas = FigureCanvas(fig)
except NameError:
msg = 'Matplotlib module is required to draw graphical histograms'
raise OptionalRequirementError(msg)
axes = fig.add_subplot(plot_type)
fig.subplots_adjust(left=left, right=right, top=top, bottom=bottom)
return canvas, axes
def plot_haplotypes(vcf_fhand,
plot_fhand,
genotype_mode=REFERENCE,
filter_alleles_gt=FILTER_ALLELES_GT):
reader = VCFReader(vcf_fhand)
# collect data
genotypes = None
samples = []
for snv in reader.parse_snvs():
if genotypes is None:
genotypes = {}
for call in snv.calls:
sample = call.sample
genotypes[sample] = []
samples.append(sample)
for call in snv.calls:
alleles = _get_alleles(call, filter_alleles_gt=filter_alleles_gt)
genotypes[call.sample].append(alleles)
# draw
n_samples = len(samples)
xsize = len(genotypes[sample]) / 100
if xsize >= 100:
xsize = 100
if xsize <= 8:
xsize = 8
ysize = n_samples * 2
if ysize >= 100:
ysize = 100
# print xsize, ysize
figure_size = (xsize, ysize)
fig = Figure(figsize=figure_size)
for index, sample in enumerate(samples):
axes = fig.add_subplot(n_samples, 1, index)
axes.set_title(sample)
y_data = genotypes[sample]
x_data = [i + 1 for i in range(len(y_data))]
x_data, y_data = _flatten_data(x_data, y_data)
axes.plot(x_data,
y_data,
marker='o',
linestyle='None',
markersize=3.0,
markeredgewidth=0,
markerfacecolor='red')
ylim = axes.get_ylim()
ylim = ylim[0] - 0.1, ylim[1] + 0.1
axes.set_ylim(ylim)
axes.tick_params(axis='x',
bottom='off',
top='off',
which='both',
labelbottom='off')
axes.tick_params(axis='y', left='on', right='off', labelleft='off')
axes.set_ylabel(sample)
canvas = FigureCanvas(fig)
canvas.print_figure(plot_fhand, dpi=300)
plot_fhand.flush()
