coverage

coverage(
    spool ,
    tolerance: float = 1.5,
    group: str | collections.abc.Sequence[str, collections.abc.Sequence[str], None] = None,
    color = None,
    ax: matplotlib.axes._axes.Axes | None[Axes, None] = None,
    figsize: tuple[tuple[float, float], None] = None,
    show: bool = False,
    **kwargs ,
)-> ‘plt.Axes’

Plot what a spool covers along a dimension, and where it does not.

One lane per group of patches which could combine, drawn as the runs the group holds and the holes between them. The holes are the ones get_gaps reports, so a gap drawn here is exactly a boundary chunk would refuse to close, and the percentage on each lane is that group’s get_coverage.

Parameters

Parameter	Description
spool	The spool to measure.
tolerance	How many samples patches may be spaced and still count as contiguous. Same meaning as chunk’s `tolerance`.
group	Attributes which separate patches into unrelated groups; a gap is never reported between two groups. Defaults to the config option `patch_kind_attrs`.
color	A mapping of “data” and “gap” to colors, overriding the default.
ax	A matplotlib Axes; one is created when None.
figsize	Size of the figure built when ax is None.
show	Whether to call plt.show.
**kwargs	The dimension to measure along, optionally with the window to draw: `time=("2020-01-01", None)`. `time=...` states the dimension and asks for all of it. Defaults to the whole of time.

Note

Coverage is measured between patches, from the envelopes the index records, so a hole inside a patch is not visible here. A lane reading 100% says “nothing chunk would refuse to merge”, not “nothing missing”.

Examples

import dascore as dc
from dascore.viz.spool import coverage

spool = dc.get_example_spool("diverse_das")
_ = coverage(spool)
_ = coverage(spool, time=("2020-01-03", "2020-01-04"))