prolint.plotting.timeseries

Time series plotters for temporal contact visualization.

This module provides time series plots for contact dynamics and distance evolution over trajectory frames.

Classes

TimeSeriesPlotter	Plotter for contact time series.
DistanceTimeSeriesPlotter	Plotter for distance time series.
ContactEventsPlotter	Plotter for contact event timelines.

Module Contents

class prolint.plotting.timeseries.TimeSeriesPlotter

Bases: prolint.plotting.base.BasePlotter

Plotter for contact time series.

Displays contact counts over trajectory frames for multiple residues as overlaid line plots.

See also

TimeSeriesAnalysis

Generates time series data

DistanceTimeSeriesPlotter

Distance evolution plots

name = 'timeseries'

required_analysis = 'timeseries'

description = 'Contact counts over time for multiple residues'

classmethod validate_result(result: prolint.analysis.base.AnalysisResult) → None

Validate that result contains required time series data.

classmethod plot(result: prolint.analysis.base.AnalysisResult, xlabel: str = 'Frame', ylabel: str = 'Contact Count', title: str = 'Contacts Over Time', figsize: Tuple[float, float] = (10, 4), ax: matplotlib.axes.Axes | None = None, time_units: str | None = None, dt: float = 1.0, legend: bool = True, max_series: int = 10) → Tuple[matplotlib.figure.Figure, matplotlib.axes.Axes]

Create contact count time series plot.

Parameters:

• result (AnalysisResult) – Result from timeseries analysis.

• xlabel (str, default="Frame") – X-axis label.

• ylabel (str, default="Contact Count") – Y-axis label.

• title (str, default="Contacts Over Time") – Plot title.

• figsize (tuple of (float, float), default=(10, 4)) – Figure dimensions (width, height).

• ax (Axes, optional) – Existing axes to plot on.

• time_units (str, optional) – Time unit for x-axis (e.g., “ns”, “us”).

• dt (float, default=1.0) – Time step multiplier when using time_units.

• legend (bool, default=True) – Whether to show legend.

• max_series (int, default=10) – Maximum number of residue series to plot.

Returns:

Matplotlib figure and axes objects.

Return type:

tuple of (Figure, Axes)

class prolint.plotting.timeseries.DistanceTimeSeriesPlotter

Bases: prolint.plotting.base.BasePlotter

Plotter for distance time series.

Displays distance evolution between query and database residues over trajectory frames with optional cutoff line and contact highlighting.

See also

DistanceAnalysis

Generates distance data

TimeSeriesPlotter

Contact count time series

name = 'distance_timeseries'

required_analysis = 'distances'

description = 'Distance over time between query and database residue'

classmethod validate_result(result: prolint.analysis.base.AnalysisResult) → None

Validate that result contains required distance data.

classmethod plot(result: prolint.analysis.base.AnalysisResult, cutoff: float | None = None, xlabel: str = 'Frame', ylabel: str = 'Distance (Å)', title: str = 'Distance Over Time', figsize: Tuple[float, float] = (12, 4), ax: matplotlib.axes.Axes | None = None, time_units: str | None = None, dt: float = 1.0) → Tuple[matplotlib.figure.Figure, matplotlib.axes.Axes]

Create distance time series plot.

Parameters:

• result (AnalysisResult) – Result from distances analysis.

• cutoff (float, optional) – Distance cutoff to draw as horizontal line.

• xlabel (str, default="Frame") – X-axis label.

• ylabel (str, default="Distance (Å)") – Y-axis label.

• title (str, default="Distance Over Time") – Plot title.

• figsize (tuple of (float, float), default=(12, 4)) – Figure dimensions (width, height).

• ax (Axes, optional) – Existing axes to plot on.

• time_units (str, optional) – Time unit for x-axis (e.g., “ns”, “us”).

• dt (float, default=1.0) – Time step multiplier when using time_units.

Returns:

Matplotlib figure and axes objects.

Return type:

tuple of (Figure, Axes)

class prolint.plotting.timeseries.ContactEventsPlotter

Bases: prolint.plotting.base.BasePlotter

Plotter for contact event timelines.

Displays contact events as horizontal bars on a timeline, showing when contacts occur during the trajectory.

See also

KineticsAnalysis

Generates contact event data

SurvivalCurvePlotter

Survival probability curves

name = 'contact_events'

required_analysis = 'kinetics'

description = 'Contact events timeline showing when contacts occur'

classmethod validate_result(result: prolint.analysis.base.AnalysisResult) → None

Validate that result contains contact_frames data.

classmethod plot(result: prolint.analysis.base.AnalysisResult, xlabel: str = 'Frame', title: str = 'Contact Events', figsize: Tuple[float, float] = (12, 2), ax: matplotlib.axes.Axes | None = None, time_units: str | None = None, dt: float = 1.0) → Tuple[matplotlib.figure.Figure, matplotlib.axes.Axes]

Create contact events timeline plot.

Parameters:

• result (AnalysisResult) – Result from kinetics analysis.

• xlabel (str, default="Frame") – X-axis label.

• title (str, default="Contact Events") – Plot title.

• figsize (tuple of (float, float), default=(12, 2)) – Figure dimensions (width, height).

• ax (Axes, optional) – Existing axes to plot on.

• time_units (str, optional) – Time unit for x-axis (e.g., “ns”, “us”).

• dt (float, default=1.0) – Time step multiplier when using time_units.

Returns:

Matplotlib figure and axes objects.

Return type:

tuple of (Figure, Axes)