def plot_cm(ecs, output_file=None):
"""
Simple wrapper for contact map plotting
"""
with misc.plot_context("Arial"):
fig = plt.figure(figsize=(8, 8))
if kwargs["scale_sizes"]:
ecs = ecs.copy()
ecs.loc[:, "size"] = ecs.cn.values / ecs.cn.max()
pairs.plot_contact_map(
ecs,
d_intra,
d_multimer,
distance_cutoff=kwargs["distance_cutoff"],
show_secstruct=kwargs["draw_secondary_structure"],
margin=5,
boundaries=kwargs["boundaries"])
plt.suptitle("{} evolutionary couplings".format(len(ecs)),
fontsize=14)
if output_file is not None:
plt.savefig(output_file, bbox_inches="tight")
plt.close(fig)
def plot_cm(ecs, output_file=None):
"""
Simple wrapper for contact map plotting
"""
with misc.plot_context("Arial"):
fig = plt.figure(figsize=(10, 10))
if kwargs["scale_sizes"]:
ecs = ecs.copy()
ecs.loc[:, "size"] = ecs.score.values / ecs.score.max()
# avoid negative sizes
ecs.loc[ecs["size"] < 0, "size"] = 0
# draw PDB structure and alignment/EC coverage information on contact map if selected
# (for now, not a required parameter, default to True)
if kwargs.get("draw_coverage", True):
additional_plot_kwargs = {
"show_structure_coverage": True,
"margin": 0,
"ec_coverage": ec_table,
}
else:
additional_plot_kwargs = {
"show_structure_coverage": False,
"margin": 5,
"ec_coverage": None,
}
pairs.plot_contact_map(
ecs,
d_intra,
d_multimer,
distance_cutoff=kwargs["distance_cutoff"],
show_secstruct=kwargs["draw_secondary_structure"],
boundaries=kwargs["boundaries"],
**additional_plot_kwargs)
# print PDB information if selected as parameter
# (for now, not a required parameter, default to True)
if kwargs.get("print_pdb_information",
True) and sifts_map is not None and len(
sifts_map.hits) > 0:
print_pdb_structure_info(
sifts_map,
ax=plt.gca(),
header_text="PDB structures:",
)
plt.suptitle("{} evolutionary couplings".format(len(ecs)),
fontsize=14)
if output_file is not None:
plt.savefig(output_file, bbox_inches="tight")
plt.close(fig)
def plot_complex_cm(ecs_i,
ecs_j,
ecs_inter,
first_segment_name,
second_segment_name,
output_file=None):
"""
Simple wrapper for contact map plotting
"""
with misc.plot_context("Arial"):
if kwargs["scale_sizes"]:
# to scale sizes, combine all ecs to rescale together
ecs = pd.concat([ecs_i, ecs_j, ecs_inter])
ecs.loc[:, "size"] = ecs.cn.values / ecs.cn.max()
# split back into three separate DataFrames
ecs_i = ecs.query(
"segment_i == segment_j == @first_segment_name")
ecs_j = ecs.query(
"segment_i == segment_j == @second_segment_name")
ecs_inter = ecs.query("segment_i != segment_j")
# if any of these groups are entry, replace with None
if len(ecs_i) == 0:
ecs_i = None
if len(ecs_j) == 0:
ecs_j = None
if len(ecs_inter) == 0:
ecs_inter = None
# Currently, we require at least one of the monomer
# to have either ECs or distances in order to make a plot
if ((ecs_i is None or ecs_i.empty) and d_intra_i is None and d_multimer_i is None) \
or ((ecs_j is None or ecs_j.empty) and d_intra_j is None and d_multimer_i is None):
return False
fig = plt.figure(figsize=(8, 8))
# create the contact map
pairs.complex_contact_map(ecs_i,
ecs_j,
ecs_inter,
d_intra_i,
d_multimer_i,
d_intra_j,
d_multimer_j,
d_inter,
margin=5,
boundaries=kwargs["boundaries"],
scale_sizes=kwargs["scale_sizes"])
# Add title to the plot
if ecs_inter is None:
ec_len = '0'
else:
ec_len = len(ecs_inter)
plt.suptitle(
"{} inter-molecule evolutionary couplings".format(ec_len),
fontsize=14)
# save to output
if output_file is not None:
plt.savefig(output_file, bbox_inches="tight")
plt.close(fig)
return True