import math
import matplotlib.pyplot as plt
import pandas as pd
from AFQ.viz.utils import display_string, gen_color_dict
__all__ = ["visualize_tract_profiles"]
def _plot_tract(ax, df, tract_name, metric, color, label=None):
sub = df[df["tractID"] == tract_name].sort_values("nodeID")
if sub.empty:
return
ax.plot(
sub["nodeID"],
sub[metric],
color=color,
linewidth=1.8,
label=label or tract_name,
)
def _split_hemisphere(tract_id):
if tract_id.endswith(("_L_R", "_R_L")):
return None, None
for prefix, hemi in (("Left ", "Left"), ("Right ", "Right")):
if tract_id.startswith(prefix):
return tract_id[len(prefix) :], hemi
for suffix, hemi in (("_L", "Left"), ("_R", "Right")):
if tract_id.endswith(suffix):
return tract_id[: -len(suffix)], hemi
return None, None
[docs]
def visualize_tract_profiles(
tract_profiles,
scalar="dti_fa",
file_name=None,
fontsize=14,
):
"""
Visualize all tract profiles for a scalar in one plot
Parameters
----------
tract_profiles : string
Path to CSV containing tract_profiles.
scalar : string, optional
Scalar to use in plots. Default: "dti_fa".
file_name : string, optional
File name to save figure to if not None. Default: None
fontsize : int, optional
Font size for figure. Default: 14
Returns
-------
Matplotlib figure and axes.
"""
df = pd.read_csv(tract_profiles)
color_dict = gen_color_dict(df["tractID"].unique())
bilateral = {}
callosal = []
for tt in df["tractID"].unique():
base, hemi = _split_hemisphere(tt)
if base is None:
callosal.append(tt)
else:
bilateral.setdefault(base, {})[hemi] = tt
bilateral_bases = sorted(bilateral)
callosal = sorted(callosal)
n_bilateral = len(bilateral_bases)
n_panels = n_bilateral + len(callosal)
n_cols = math.ceil(math.sqrt(n_panels))
n_rows = math.ceil(n_panels / n_cols)
fig1, axes1 = plt.subplots(
n_rows,
n_cols,
figsize=(n_cols * 4, n_rows * 4),
sharex=False,
sharey=False,
squeeze=False,
)
flat_axes = axes1.ravel()
def _style_axis(ax, ylabel):
ax.set_ylabel(ylabel, fontsize=fontsize - 2, labelpad=4)
ax.set_xlabel("Node", fontsize=fontsize)
ax.tick_params(labelsize=fontsize - 4)
ax.spines[["top", "right"]].set_visible(False)
ax.legend(fontsize=fontsize, loc="best", frameon=False)
for idx, base in enumerate(bilateral_bases):
ax = flat_axes[idx]
for hemi in ("Left", "Right"):
full_name = bilateral[base].get(hemi)
if full_name is None:
continue
_plot_tract(
ax,
df,
full_name,
scalar,
color_dict[full_name],
hemi,
)
_style_axis(ax, base + " " + display_string(scalar))
for ii, tract in enumerate(callosal):
ax = flat_axes[n_bilateral + ii]
sub = df[df["tractID"] == tract].sort_values("nodeID")
ax.plot(
sub["nodeID"],
sub[scalar],
color=color_dict[tract],
linewidth=1.8,
label=tract.replace("Callosum ", ""),
)
_style_axis(ax, tract + " " + display_string(scalar))
for ax in flat_axes[n_panels:]:
ax.set_visible(False)
fig1.suptitle(display_string(scalar), fontsize=fontsize + 2, fontweight="bold")
fig1.tight_layout(rect=[0, 0, 1, 0.97])
if file_name is not None:
fig1.savefig(file_name, dpi=300, bbox_inches="tight")
return fig1, axes1
