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import itertools
import numpy as np
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
from .core import arrops
DEFAULT_FACECOLOR = "skyblue"
DEFAULT_EDGECOLOR = "dimgray"
__all__ = ["plot_intervals"]
def _plot_interval(
start, end, level, facecolor=None, edgecolor=None, height=0.6, ax=None
):
facecolor = DEFAULT_FACECOLOR if facecolor is None else facecolor
edgecolor = DEFAULT_EDGECOLOR if edgecolor is None else edgecolor
ax = plt.gca() if ax is None else ax
ax.add_patch(
matplotlib.patches.Rectangle(
(start, level - height / 2),
end - start,
height,
facecolor=facecolor,
edgecolor=edgecolor,
)
)
def plot_intervals_arr(
starts,
ends,
levels=None,
labels=None,
colors=None,
xlim=None,
show_coords=False,
figsize=(10, 2),
):
"""
Plot a collection of intervals.
Parameters
----------
starts, ends : np.ndarray
A collection of intervals.
levels : iterable or None
The level of each interval, i.e. the y-coordinate at which the interval
must be plotted. If None, it will be determined automatically.
labels : str or iterable or None
The label of each interval.
colors : str or iterable or None.
The color of each interval.
xlim : (float, float) or None
The x-span of the plot.
show_coords : bool
If True, plot x-ticks.
figsize : (float, float) or None.
The size of the figure. If None, plot within the current figure.
"""
starts = np.asarray(starts)
ends = np.asarray(ends)
if figsize is not None:
plt.figure(figsize=figsize)
if levels is None:
levels = arrops.stack_intervals(starts, ends)
else:
levels = np.asarray(levels)
if isinstance(colors, str) or (colors is None):
colors = itertools.cycle([colors])
else:
colors = itertools.cycle(colors)
if isinstance(labels, str) or (labels is None):
labels = itertools.cycle([labels])
else:
labels = itertools.cycle(labels)
for i, (start, end, level, color, label) in enumerate(
zip(starts, ends, levels, colors, labels)
):
_plot_interval(start, end, level, facecolor=color)
if label is not None:
plt.text(
(start + end) / 2,
level,
label,
horizontalalignment="center",
verticalalignment="center",
)
plt.ylim(-0.5, np.max(levels) + 0.5)
if xlim is None:
plt.xlim(-0.5, np.max(ends) + 0.5)
else:
plt.xlim(xlim[0], xlim[1])
plt.gca().set_aspect(1)
plt.gca().set_frame_on(False)
plt.yticks([])
if show_coords:
pass
else:
plt.xticks([])
def plot_intervals(
df,
levels=None,
labels=None,
colors=None,
xlim=None,
show_coords=False,
figsize=(10, 2),
):
"""
Plot a collection of intervals, one plot per chromosome.
Parameters
----------
df : pandas.DataFrame
A collection of intervals.
levels : iterable or None
The level of each interval, i.e. the y-coordinate at which the interval
must be plotted. If None, it will be determined automatically.
labels : str or iterable or None
The label of each interval.
colors : str or iterable or None.
The color of each interval.
xlim : (float, float) or None
The x-span of the plot.
show_coords : bool
If True, plot x-ticks.
figsize : (float, float) or None.
The size of the figure. If None, plot within the current figure.
"""
chrom_gb = df.groupby("chrom")
for chrom, chrom_df in chrom_gb:
if isinstance(levels, (list, pd.core.series.Series, np.ndarray)):
chrom_levels = np.asarray(levels)[chrom_gb.groups[chrom].values]
elif levels is None:
chrom_levels = None
else:
raise ValueError(f"Unknown type of levels: {type(levels)}")
if isinstance(labels, (list, pd.core.series.Series, np.ndarray)):
chrom_labels = np.asarray(labels)[chrom_gb.groups[chrom].values]
elif labels is None:
chrom_labels = None
else:
raise ValueError(f"Unknown type of labels: {type(levels)}")
if isinstance(colors, (list, pd.core.series.Series, np.ndarray)):
chrom_colors = np.asarray(colors)[chrom_gb.groups[chrom].values]
elif colors is None or isinstance(colors, str):
chrom_colors = colors
else:
raise ValueError(f"Unknown type of colors: {type(colors)}")
plot_intervals_arr(
chrom_df.start,
chrom_df.end,
levels=chrom_levels,
labels=chrom_labels,
colors=chrom_colors,
xlim=xlim,
show_coords=show_coords,
figsize=figsize,
)
plt.title(chrom)
|
