def mirror(parameters):
parser = parsers.mirror_parser()
args = parser.parse_args(parameters)
if args.colormap_lower is None:
colormap_lower = config.colormap_hic if not args.oe_lower else 'bwr'
else:
colormap_lower = args.colormap_lower
if args.colormap_upper is None:
colormap_upper = config.colormap_hic if not args.oe_upper else 'bwr'
else:
colormap_upper = args.colormap_upper
matrix_upper = fanc.load(os.path.expanduser(args.hic_upper), mode='r')
matrix_lower = fanc.load(os.path.expanduser(args.hic_lower), mode='r')
from fanc.tools.general import str_to_int
norm_upper = "lin" if not args.log_upper else "log"
upper_plot = kplt.HicPlot(matrix_upper,
colormap=colormap_upper,
max_dist=str_to_int(args.max_dist),
norm=norm_upper,
vmin=args.vmin_upper,
vmax=args.vmax_upper,
oe=args.oe_upper,
log=args.oe_upper,
colorbar_symmetry=0 if args.oe_upper
and args.colorbar_symmetry_upper is None else
args.colorbar_symmetry_upper,
show_colorbar=args.show_colorbar,
adjust_range=False)
norm_lower = "lin" if not args.log_lower else "log"
lower_plot = kplt.HicPlot(matrix_lower,
colormap=colormap_lower,
max_dist=str_to_int(args.max_dist),
norm=norm_lower,
vmin=args.vmin_lower,
vmax=args.vmax_lower,
oe=args.oe_lower,
log=args.oe_lower,
colorbar_symmetry=0 if args.oe_lower
and args.colorbar_symmetry_lower is None else
args.colorbar_symmetry_lower,
show_colorbar=args.show_colorbar,
adjust_range=False)
vsp = kplt.VerticalSplitPlot(upper_plot, lower_plot)
return vsp, args
def triangular(parameters):
parser = parsers.triangular_parser()
args = parser.parse_args(parameters)
if args.colormap is None:
colormap = config.colormap_hic if not args.oe else 'bwr'
else:
colormap = args.colormap
matrix = fanc.load(os.path.expanduser(args.hic), mode='r')
from fanc.tools.general import str_to_int
norm = "lin" if not args.log else "log"
return kplt.HicPlot(
matrix,
colormap=colormap,
max_dist=str_to_int(args.max_dist)
if args.max_dist is not None else None,
norm=norm,
vmin=args.vmin,
vmax=args.vmax,
show_colorbar=args.show_colorbar,
adjust_range=args.adjust_range,
oe=args.oe,
log=args.oe,
colorbar_symmetry=0 if args.oe and args.colorbar_symmetry is None else
args.colorbar_symmetry,
ylabel=args.ylabel,
weight_field=args.weight_field,
default_value=args.default_value,
matrix_norm=args.norm), args
def test_tick_removal(self, width, cax_width, ticks_last, draw_labels,
draw_ticks, draw_x_axis):
splot = kplot.HicSlicePlot(self.hic_matrix, "chr11:77800000-77850000")
hplot = kplot.HicPlot2D(hic_data=self.hic_matrix,
draw_ticks=draw_ticks,
draw_tick_labels=draw_labels,
draw_x_axis=draw_x_axis)
hplot2 = kplot.HicPlot(hic_data=self.hic_matrix)
gfig = kplot.GenomicFigure([splot, hplot, hplot2],
width=width,
ticks_last=ticks_last,
cax_width=cax_width)
selector = "chr11:{}-{}".format(77400000, 78600000)
fig, axes = gfig.plot(selector)
# hplot2 should always have labels and lines
assert all(l.get_visible() for l in axes[2].get_xticklabels()) and all(
l.get_visible() for l in axes[2].xaxis.get_majorticklines())
# hplot labels are affected by the three draw parameters
should_have_labels = draw_x_axis and draw_labels and (not ticks_last)
assert should_have_labels == all(l.get_visible()
for l in axes[1].get_xticklabels())
# But it should have tick lines even when ticks_last=True
should_have_ticks = draw_x_axis and draw_ticks
assert should_have_ticks == all(
l.get_visible() for l in axes[1].xaxis.get_majorticklines())
assert should_have_ticks == all(
l.get_visible() for l in axes[1].xaxis.get_minorticklines())
# splot should always have ticks and lines
assert all(l.get_visible() for l in axes[0].xaxis.get_majorticklines())
assert all(l.get_visible() for l in axes[0].xaxis.get_minorticklines())
# splot only labels if ticks_last=False
assert ticks_last != all(l.get_visible()
for l in axes[0].get_xticklabels())
bbox = axes[0].get_position()
figsize = fig.get_size_inches()
assert bbox.width * figsize[0] == pytest.approx(width)
bbox = hplot.cax.get_position()
assert bbox.width * figsize[0] == pytest.approx(cax_width)
plt.close(fig)
# draw_minor_ticks=False, title="Tollrm910")
# Toll10B_nc14_hic = fanc.load(os.path.join("data", "hic", "merged",
# "Toll10B-nc14", "hic",
# "Toll10B-nc14_1kb.hic"), mode="r")
# Toll10B_nc14_hic_plot = fancplot.HicPlot(Toll10B_nc14_hic, vmin=1e-03,
# vmax=1e-01, norm="log",
# draw_minor_ticks=False,
# title="Toll10B")
gd7_microc = fanc.load(os.path.join("data", "micro-c", "merged",
"gd7", "hic",
"gd7_" + res + ".hic"), mode="r")
gd7_microc_plot = fancplot.HicPlot(gd7_microc, vmin=1e-03,
vmax=1e-01, norm="log",
draw_minor_ticks=False, title="gd7")
control_microc = fanc.load(os.path.join("data", "micro-c", "merged",
"control", "hic",
"control_" + res + ".hic"),
mode="r")
control_microc_plot = fancplot.HicPlot(control_microc, vmin=1e-03,
vmax=1e-01, norm="log",
draw_minor_ticks=False, title="control")
genes = "external_data/flybase/dmel-all-r6.30.gtf.gz"
genes_plot = fancplot.GenePlot(genes, squash=True, group_by="gene_symbol",
aspect=0.15, label_field="gene_symbol",
show_labels=False, draw_minor_ticks=False)
def plot_regions(regions):
h = fanc.load(os.path.join("data", "hic", "merged", "3-4h", "hic",
"3-4h_2kb.hic"),
mode="r")
h_plot = fancplot.HicPlot(h,
vmin=1e-03,
vmax=1e-01,
norm="log",
draw_minor_ticks=False)
genes = "external_data/flybase/dmel-all-r6.30.gtf.gz"
genes_plot = fancplot.GenePlot(genes,
squash=True,
group_by="gene_symbol",
aspect=0.15,
label_field="gene_symbol",
show_labels=False,
draw_minor_ticks=False)
rnaseq_dict = {
name:
os.path.join("external_data", "koenecke_2016_2017", "rnaseq_aligned",
name + "_sorted_filtered_merged_canonical_chrs_rnaseq.bw")
for name in ["gd7", "tlrm910", "tl10b"]
}
h3k27ac_dict = {
name: os.path.join(
"external_data", "koenecke_2016_2017", "chipseq_aligned",
"H3K27ac_" + name + "_sorted_filtered_merged_canonical_chrs.bw")
for name in ["gd7", "tl10b"]
}
h3k27ac_dict["Tollrm910"] = os.path.join(
"external_data", "extra_chip-seq", "chipseq_aligned",
"H3K27ac_Tollrm910_sorted_filtered_merged_canonical_chrs.bw")
rnaseq_ylim = fancplot.helpers.LimitGroup()
h3k27ac_ylim = fancplot.helpers.LimitGroup()
polii_ylim = fancplot.helpers.LimitGroup()
# polii_chip_early = os.path.join("external_data", "blythe_2015", "aligned",
# "PolII-pSer5_NC14-early_sorted_filtered_merged_canonical_chrs.bw")
# polii_chip_mid = os.path.join("external_data", "blythe_2015", "aligned",
# "PolII-pSer5_NC14-middle_sorted_filtered_merged_canonical_chrs.bw")
polii_chip_late = os.path.join(
"external_data", "blythe_2015", "aligned",
"PolII-pSer5_NC14-late_sorted_filtered_merged_canonical_chrs.bw")
# polii_early_plot = fancplot.LinePlot(polii_chip_early, fill=True, plot_kwargs={'color': "black"},
# draw_minor_ticks=False, aspect=0.05,
# ylim=polii_ylim, n_yticks=2)
# polii_mid_plot = fancplot.LinePlot(polii_chip_mid, fill=True, plot_kwargs={'color': "black"},
# draw_minor_ticks=False, aspect=0.05,
# ylim=polii_ylim, n_yticks=2)
polii_late_plot = fancplot.LinePlot(polii_chip_late,
fill=True,
plot_kwargs={'color': "black"},
draw_minor_ticks=False,
aspect=0.05,
ylim=polii_ylim,
n_yticks=2)
rnaseq_plot_gd7 = fancplot.LinePlot(rnaseq_dict['gd7'],
fill=True,
plot_kwargs={'color': "#648fff"},
draw_minor_ticks=False,
aspect=0.05,
n_yticks=2)
h3k27ac_plot_gd7 = fancplot.LinePlot(h3k27ac_dict['gd7'],
fill=True,
plot_kwargs={'color': "#648fff"},
draw_minor_ticks=False,
aspect=0.05,
ylim=h3k27ac_ylim,
n_yticks=2)
rnaseq_plot_Tollrm910 = fancplot.LinePlot(rnaseq_dict['tlrm910'],
fill=True,
plot_kwargs={'color': "#dc267f"},
draw_minor_ticks=False,
aspect=0.05,
n_yticks=2)
h3k27ac_plot_Tollrm910 = fancplot.LinePlot(
h3k27ac_dict['Tollrm910'],
fill=True,
plot_kwargs={'color': "#dc267f"},
draw_minor_ticks=False,
aspect=0.05,
ylim=h3k27ac_ylim,
n_yticks=2)
rnaseq_plot_toll10b = fancplot.LinePlot(rnaseq_dict['tl10b'],
fill=True,
plot_kwargs={'color': "#ffb000"},
draw_minor_ticks=False,
aspect=0.05,
n_yticks=2)
h3k27ac_plot_toll10b = fancplot.LinePlot(h3k27ac_dict['tl10b'],
fill=True,
plot_kwargs={'color': "#ffb000"},
draw_minor_ticks=False,
aspect=0.05,
ylim=h3k27ac_ylim,
n_yticks=2)
gd7_enh = "data/supplementary_tables/gd7_candidate_enhancers.bed"
gd7_enh_plot = fancplot.GenomicFeaturePlot(gd7_enh,
aspect=0.02,
color="#648fff",
draw_minor_ticks=False)
Tollrm910_enh = "data/supplementary_tables/Tollrm910_candidate_enhancers.bed"
Tollrm910_enh_plot = fancplot.GenomicFeaturePlot(Tollrm910_enh,
aspect=0.02,
color="#dc267f",
draw_minor_ticks=False)
toll10b_enh = "data/supplementary_tables/Toll10B_candidate_enhancers.bed"
toll10b_enh_plot = fancplot.GenomicFeaturePlot(toll10b_enh,
aspect=0.02,
color="#ffb000",
draw_minor_ticks=False)
plots = [
h_plot,
# ins_plot,
# boundaries_plot,
genes_plot,
# hk_plot,
# polii_early_plot, polii_mid_plot,
polii_late_plot,
rnaseq_plot_gd7,
rnaseq_plot_Tollrm910,
rnaseq_plot_toll10b,
h3k27ac_plot_gd7,
h3k27ac_plot_Tollrm910,
h3k27ac_plot_toll10b,
gd7_enh_plot,
Tollrm910_enh_plot,
toll10b_enh_plot
]
with PdfPages(output_file) as pdf:
with fancplot.GenomicFigure(plots, ticks_last=True) as gfig:
for name, region, rnaseq_ylim in regions:
logging.info(region)
fig, axes = gfig.plot(region)
axes[3].set_ylim([0, rnaseq_ylim])
axes[4].set_ylim([0, rnaseq_ylim])
axes[5].set_ylim([0, rnaseq_ylim])
pdf.savefig()
import os
import pybedtools
import re
import seaborn
# import sys
matplotlib.use('agg')
logging.basicConfig(level=logging.INFO)
gd7_nc14_hic = fanc.load(os.path.join("data", "hic", "merged", "gd7-nc14",
"hic", "gd7-nc14_2kb.hic"),
mode="r")
gd7_nc14_hic_plot = fancplot.HicPlot(gd7_nc14_hic,
vmin=1e-03,
vmax=1e-01,
norm="log",
draw_minor_ticks=False,
title="gd7")
Tollrm910_nc14_hic = fanc.load(os.path.join("data", "hic", "merged",
"Tollrm910-nc14", "hic",
"Tollrm910-nc14_2kb.hic"),
mode="r")
Tollrm910_nc14_hic_plot = fancplot.HicPlot(Tollrm910_nc14_hic,
vmin=1e-03,
vmax=1e-01,
norm="log",
draw_minor_ticks=False,
title="Tollrm910")
Toll10B_nc14_hic = fanc.load(os.path.join("data", "hic", "merged",
def plot_region(name, region):
output_file = os.path.join("figures", "figure_4_panels", name + ".pdf")
logging.info("Working on %s", name)
logging.info("Will write output to %s", output_file)
gd7_nc14_hic = fanc.load(os.path.join("data", "hic", "merged", "gd7-nc14",
"hic", "gd7-nc14_5kb.hic"),
mode="r")
gd7_nc14_hic_plot = fancplot.HicPlot(gd7_nc14_hic,
norm="log",
vmin=1e-03,
vmax=1e-01,
draw_minor_ticks=False,
title="gd7",
max_dist='250kb')
gd7_nc14_diff = fanc.load(os.path.join(
"data", "hic", "merged", "gd7-nc14", "hic",
"diff_control-nc14_gd7-nc14_5kb.hic"),
mode="r")
gd7_nc14_diff_plot = fancplot.HicPlot(gd7_nc14_diff,
norm="lin",
colormap='bwr_r',
vmin=-0.01,
vmax=0.01,
draw_minor_ticks=False,
max_dist='250kb')
Tollrm910_nc14_hic = fanc.load(os.path.join("data", "hic", "merged",
"Tollrm910-nc14", "hic",
"Tollrm910-nc14_5kb.hic"),
mode="r")
Tollrm910_nc14_hic_plot = fancplot.HicPlot(Tollrm910_nc14_hic,
norm="log",
vmin=1e-03,
vmax=1e-01,
draw_minor_ticks=False,
title="Tollrm910",
max_dist='250kb')
Tollrm910_nc14_diff = fanc.load(os.path.join(
"data", "hic", "merged", "Tollrm910-nc14", "hic",
"diff_control-nc14_Tollrm910-nc14_5kb.hic"),
mode="r")
Tollrm910_nc14_diff_plot = fancplot.HicPlot(Tollrm910_nc14_diff,
norm="lin",
colormap='bwr_r',
vmin=-0.01,
vmax=0.01,
draw_minor_ticks=False,
max_dist='250kb')
Toll10B_nc14_hic = fanc.load(os.path.join("data", "hic", "merged",
"Toll10B-nc14", "hic",
"Toll10B-nc14_5kb.hic"),
mode="r")
Toll10B_nc14_hic_plot = fancplot.HicPlot(Toll10B_nc14_hic,
norm="log",
vmin=1e-03,
vmax=1e-01,
draw_minor_ticks=False,
title="Toll10B",
max_dist='250kb')
Toll10B_nc14_diff = fanc.load(os.path.join(
"data", "hic", "merged", "Toll10B-nc14", "hic",
"diff_control-nc14_Toll10B-nc14_5kb.hic"),
mode="r")
Toll10B_nc14_diff_plot = fancplot.HicPlot(Toll10B_nc14_diff,
norm="lin",
colormap='bwr_r',
vmin=-0.01,
vmax=0.01,
draw_minor_ticks=False,
max_dist='250kb')
genes = "external_data/flybase/dmel-all-r6.30.gtf.gz"
genes_plot = fancplot.GenePlot(genes,
squash=True,
group_by="gene_symbol",
aspect=0.15,
label_field="gene_symbol",
show_labels=False,
draw_minor_ticks=False)
rnaseq_dict = {
name:
os.path.join("external_data", "koenecke_2016_2017", "rnaseq_aligned",
name + "_sorted_filtered_merged_canonical_chrs_rnaseq.bw")
for name in ["gd7", "tlrm910", "tl10b"]
}
h3k27ac_dict = {
name: os.path.join(
"external_data", "koenecke_2016_2017", "chipseq_aligned",
"H3K27ac_" + name + "_sorted_filtered_merged_canonical_chrs.bw")
for name in ["gd7", "tl10b"]
}
h3k27ac_dict["Tollrm910"] = os.path.join(
"external_data", "extra_chip-seq", "chipseq_aligned",
"H3K27ac_Tollrm910_sorted_filtered_merged_canonical_chrs.bw")
h3k27me3_dict = {
name: os.path.join(
"external_data", "koenecke_2016_2017", "chipseq_aligned",
"H3K27me3_" + name + "_sorted_filtered_merged_canonical_chrs.bw")
for name in ["gd7", "tl10b"]
}
h3k27me3_dict["Tollrm910"] = os.path.join(
"external_data", "extra_chip-seq", "chipseq_aligned",
"H3K27me3_Tollrm910_sorted_filtered_merged_canonical_chrs.bw")
# ins_dict = {name: os.path.join("data", "boundaries", name + "_2kb_8.bw")
# for name in ["gd7-nc14", "Tollrm910-nc14", "Toll10B-nc14", "3-4h"]}
rnaseq_ylim = fancplot.helpers.LimitGroup()
rnaseq_ylim = [0, 10]
h3k27ac_ylim = fancplot.helpers.LimitGroup()
h3k27me3_ylim = fancplot.helpers.LimitGroup()
rnaseq_plot_gd7 = fancplot.LinePlot(rnaseq_dict['gd7'],
fill=False,
plot_kwargs={'color': "#648fff"},
draw_minor_ticks=False,
aspect=0.05,
ylim=rnaseq_ylim,
n_yticks=2)
h3k27ac_plot_gd7 = fancplot.LinePlot(h3k27ac_dict['gd7'],
fill=False,
plot_kwargs={'color': "#648fff"},
draw_minor_ticks=False,
aspect=0.05,
ylim=h3k27ac_ylim,
n_yticks=2)
h3k27me3_plot_gd7 = fancplot.LinePlot(h3k27me3_dict['gd7'],
fill=False,
plot_kwargs={'color': "#648fff"},
draw_minor_ticks=False,
aspect=0.05,
ylim=h3k27me3_ylim,
n_yticks=2)
rnaseq_plot_Tollrm910 = fancplot.LinePlot(rnaseq_dict['tlrm910'],
fill=False,
plot_kwargs={'color': "#dc267f"},
draw_minor_ticks=False,
aspect=0.05,
ylim=rnaseq_ylim,
n_yticks=2)
h3k27ac_plot_Tollrm910 = fancplot.LinePlot(
h3k27ac_dict['Tollrm910'],
fill=False,
plot_kwargs={'color': "#dc267f"},
draw_minor_ticks=False,
aspect=0.05,
ylim=h3k27ac_ylim,
n_yticks=2)
h3k27me3_plot_Tollrm910 = fancplot.LinePlot(
h3k27me3_dict['Tollrm910'],
fill=False,
plot_kwargs={'color': "#dc267f"},
draw_minor_ticks=False,
aspect=0.05,
ylim=h3k27me3_ylim,
n_yticks=2)
rnaseq_plot_toll10b = fancplot.LinePlot(rnaseq_dict['tl10b'],
fill=False,
plot_kwargs={'color': "#ffb000"},
draw_minor_ticks=False,
aspect=0.05,
ylim=rnaseq_ylim,
n_yticks=2)
h3k27ac_plot_toll10b = fancplot.LinePlot(h3k27ac_dict['tl10b'],
fill=False,
plot_kwargs={'color': "#ffb000"},
draw_minor_ticks=False,
aspect=0.05,
ylim=h3k27ac_ylim,
n_yticks=2)
h3k27me3_plot_toll10b = fancplot.LinePlot(h3k27me3_dict['tl10b'],
fill=False,
plot_kwargs={'color': "#ffb000"},
draw_minor_ticks=False,
aspect=0.05,
ylim=h3k27me3_ylim,
n_yticks=2)
gd7_enh = "data/supplementary_tables/gd7_candidate_enhancers.bed"
gd7_enh_plot = fancplot.GenomicFeaturePlot(gd7_enh,
aspect=0.02,
color="#648fff",
draw_minor_ticks=False)
Tollrm910_enh = "data/supplementary_tables/Tollrm910_candidate_enhancers.bed"
Tollrm910_enh_plot = fancplot.GenomicFeaturePlot(Tollrm910_enh,
aspect=0.02,
color="#dc267f",
draw_minor_ticks=False)
toll10b_enh = "data/supplementary_tables/Toll10B_candidate_enhancers.bed"
toll10b_enh_plot = fancplot.GenomicFeaturePlot(toll10b_enh,
aspect=0.02,
color="#ffb000",
draw_minor_ticks=False)
plots = [
gd7_nc14_hic_plot, gd7_nc14_diff_plot, rnaseq_plot_gd7,
h3k27ac_plot_gd7, gd7_enh_plot, h3k27me3_plot_gd7,
Tollrm910_nc14_hic_plot, Tollrm910_nc14_diff_plot,
rnaseq_plot_Tollrm910, h3k27ac_plot_Tollrm910, Tollrm910_enh_plot,
h3k27me3_plot_Tollrm910, Toll10B_nc14_hic_plot, Toll10B_nc14_diff_plot,
rnaseq_plot_toll10b, h3k27ac_plot_toll10b, toll10b_enh_plot,
h3k27me3_plot_toll10b, genes_plot
]
with fancplot.GenomicFigure(plots, ticks_last=True) as gfig:
fig, axes = gfig.plot(region)
fig.savefig(output_file)
import matplotlib
import os
import pybedtools
import re
import seaborn
# import sys
matplotlib.use('agg')
logging.basicConfig(level=logging.INFO)
control_stg10_hic = fanc.load(os.path.join("data", "hic", "merged",
"control-stg10", "hic",
"control-stg10_2kb.hic"), mode="r")
control_stg10_hic_plot = fancplot.HicPlot(control_stg10_hic, vmin=1e-03,
vmax=1e-01, norm="log",
draw_minor_ticks=False, title="control")
gd7_stg10_hic = fanc.load(os.path.join("data", "hic", "merged",
"gd7-stg10", "hic",
"gd7-stg10_2kb.hic"), mode="r")
gd7_stg10_hic_plot = fancplot.HicPlot(gd7_stg10_hic, vmin=1e-03,
vmax=1e-01, norm="log",
draw_minor_ticks=False, title="gd7")
Tollrm910_stg10_hic = fanc.load(os.path.join("data", "hic", "merged",
"Tollrm910-stg10", "hic",
"Tollrm910-stg10_2kb.hic"),
mode="r")
Tollrm910_stg10_hic_plot = fancplot.HicPlot(Tollrm910_stg10_hic, vmin=1e-03,
vmax=1e-01, norm="log",
# 7. Loop aggregate plot
loops = fanc.load(loops_file)
if not os.path.exists(loop_am_output_file):
loop_am = fanc.AggregateMatrix.from_center_pairs(hic_10kb, loops, log=True, oe=True,
file_name=loop_am_output_file, cache=False)
else:
loop_am = fanc.AggregateMatrix(loop_am_output_file)
fanc_stats_plot.aggregate_plot(loop_am, labels=('loop anchor',), vmin=-1, vmax=1,
oe=False, log=False, colormap='bwr', ax=ax_aggregate_loops,
relative_label_locations=(0.5,), cax=cax_aggregate_loops)
ax_aggregate_loops.set_yticklabels([])
# 8. Hi-C plot triangular
p_hic_triangular = fancplot.HicPlot(hic_10kb, norm='lin', ax=ax_hic_triangular, cax=cax_hic_triangular,
max_dist=750000,
vmin=0, vmax=0.03, draw_tick_legend=False, draw_minor_ticks=False)
p_hic_triangular.plot(triangular_plotting_region)
ax_hic_triangular.set_xticks([triangular_plotting_region.start,
triangular_plotting_region.center,
triangular_plotting_region.end])
p_hic_triangular.colorbar.set_ticks([0, 0.03])
p_hic_triangular.colorbar.set_label("Normalised\ncontact probability")
# 9. Insulation array
insulation = fanc.load(insulation_file)
p_ins_array = fancplot.GenomicVectorArrayPlot(insulation, y_scale='log', ax=ax_ins_array,
colormap='bwr', cax=cax_ins_array,
vmin=-1, vmax=1, draw_tick_legend=False,
def test_hicplot_inputs(self, norm, max_dist, colormap, colorbar,
blend_zero, aspect, vrange, crange,
unmappable_color, proportional):
start, end = crange
vmin, vmax = vrange
hplot = kplot.HicPlot(hic_data=self.hic_matrix,
title="quark",
norm=norm,
vmin=vmin,
vmax=vmax,
max_dist=max_dist,
colormap=colormap,
show_colorbar=colorbar,
blend_zero=blend_zero,
aspect=aspect,
unmappable_color=unmappable_color,
proportional=proportional)
gfig = kplot.GenomicFigure([hplot])
selector = "chr11:{}-{}".format(start, end)
fig, axes = gfig.plot(selector)
assert axes[0].get_title() == "quark"
norm_values = {"lin": mpl.colors.Normalize, "log": mpl.colors.LogNorm}
assert isinstance(hplot.collection.norm, norm_values[norm])
assert axes[0].get_xlim() == (start, end)
if vmin is not None:
assert hplot.collection.norm.vmin == vmin
if vmax is not None:
assert hplot.collection.norm.vmax == vmax
if proportional:
if max_dist is None:
assert abs_ax_aspect(hplot.ax) == pytest.approx(.5)
else:
rl = end - start
assert abs_ax_aspect(hplot.ax) == pytest.approx(
.5 * min(max_dist, rl) / rl)
else:
assert abs_ax_aspect(hplot.ax) == aspect
colorbar_values = {True: mpl.colorbar.Colorbar, False: type(None)}
assert isinstance(hplot.colorbar, colorbar_values[colorbar])
hic_matrix = self.hic_matrix[selector, selector]
zero_mask = np.isclose(hic_matrix, 0.)
unmap_mask = np.all(zero_mask, axis=0)
unmap_mask = np.logical_or(unmap_mask, unmap_mask[:, np.newaxis])
if unmappable_color is not None:
unmap_color = mpl.colors.colorConverter.to_rgba(unmappable_color)
assert np.all(
np.isclose(
hplot.collection.get_facecolors()[unmap_mask.T.ravel(), :],
unmap_color))
# blend zero only really makes sense with log normalization, with
# linear normalization 0 values map to the first colormap value anyway
if norm == "log":
exp_zero = np.logical_and(zero_mask, np.logical_not(unmap_mask))
if np.sum(exp_zero) > 0:
zero_value = hplot.colormap(0)
zero_blended = np.all(
np.isclose(
hplot.collection.get_facecolors()[
exp_zero.T.ravel(), :], zero_value))
assert blend_zero == zero_blended
plt.close(fig)