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import itertools
from typing import Union
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from matplotlib.colors import to_rgb
from .core import arrops
DEFAULT_FACECOLOR = "skyblue"
DEFAULT_EDGECOLOR = "dimgray"
__all__ = ["plot_intervals", "to_ucsc_colorstring"]
def to_ucsc_colorstring(color: Union[str, tuple]) -> str:
"""
Convert any matplotlib color identifier into a UCSC itemRgb color string.
Parameters
----------
color : str or tuple
Any valid matplotlib color representation (e.g. 'red', 'tomato',
'#ff0000', '#ff00', "#ff000055", (1, 0, 0), (1, 0, 0, 0.5))
Returns
-------
str
A UCSC itemRgb colorstring of the form "r,g,b" where r, g, and b are
integers between 0 and 255, inclusive.
Notes
-----
The alpha (opacity) channel is ignored if represented in the input.
Null values are converted to "0", which is shorthand for "0,0,0" (black).
Note that BED9+ files with uninformative itemRgb values should use "0" as
the itemRgb value on every data line.
Examples
--------
>>> to_ucsc_colorstring("red")
'255,0,0'
>>> to_ucsc_colorstring("tomato")
'255,99,71'
>>> df["itemRgb"] = df["color"].apply(to_ucsc_colorstring)
>>> df
chrom start end color itemRgb
chr1 0 10 red 255,0,0
chr1 10 20 blue 0,0,255
chr2 0 10 green 0,128,0
chr2 10 20 None 0
"""
if pd.isnull(color) or color == "none":
return "0"
else:
return ",".join(str(int(x * 255)) for x in to_rgb(color))
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(
mpl.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 (start, end, level, color, label) in 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", observed=True)
chrom_gb = df.reset_index(drop=True).groupby("chrom", observed=True)
for chrom, chrom_df in chrom_gb:
chrom_indices = chrom_gb.groups[chrom].to_numpy()
if isinstance(levels, (list, pd.Series, np.ndarray)):
chrom_levels = np.asarray(levels)[chrom_indices]
elif levels is None:
chrom_levels = None
else:
raise ValueError(f"Unknown type of levels: {type(levels)}")
if isinstance(labels, (list, pd.Series, np.ndarray)):
chrom_labels = np.asarray(labels)[chrom_indices]
elif labels is None:
chrom_labels = None
else:
raise ValueError(f"Unknown type of labels: {type(levels)}")
if isinstance(colors, (list, pd.Series, np.ndarray)):
chrom_colors = np.asarray(colors)[chrom_indices]
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)
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