Plotting

Functions:

plot_intervals(df[, levels, labels, colors, ...])

Plot a collection of intervals, one plot per chromosome.

to_ucsc_colorstring(color)

Convert any matplotlib color identifier into a UCSC itemRgb color string.
plot_intervals(df, levels=None, labels=None, colors=None, xlim=None, show_coords=False, figsize=(10, 2))[source]

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.

to_ucsc_colorstring(color: str | tuple) → str[source]

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:

A UCSC itemRgb colorstring of the form “r,g,b” where r, g, and b are integers between 0 and 255, inclusive.

Return type:

str

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