aridkpi.viz

Visualisation utilities for aridkpi.

All functions are import-guarded for matplotlib so the core package can be installed without it. Use pip install aridkpi[viz] to enable.

aridkpi.viz.plot_kpi_summary(kpi_results: dict[str, dict[str, float]], title: str = 'KPI summary across typologies', ax: Any | None = None)[source]

Bar chart comparing KPI values across typologies / cases.

Parameters:

kpi_results – Nested dict of the form {case_name: {kpi_id: value, ...}, ...}.
title – Plot title.
ax – Optional matplotlib axes.

Returns:

matplotlib.axes.Axes – The axes used.

Examples

>>> data = {
...     "adobe":          {"IOD": 45.0, "dT_dt_max": 0.6},
...     "lightweight":    {"IOD": 92.0, "dT_dt_max": 2.4},
... }
>>> # Used in the tutorial notebook to compare 4 typologies side by side.

aridkpi.viz.plot_overheating_diagnostic(T_op: Series, T_comf: float = 26.0, title: str = 'Overheating diagnostic', ax: Any | None = None)[source]

Visual diagnostic of overheating: shaded area = excess over T_comf.

Useful for explaining IOD intuitively: the shaded area under the curve above the threshold is exactly the IOD integral.

Parameters:

T_op – Operative temperature series.
T_comf – Comfort threshold.
title – Plot title.
ax – Optional matplotlib axes.

Returns:

matplotlib.axes.Axes – The axes used.

aridkpi.viz.plot_temperature_series(T_in: Series, T_ext: Series | None = None, T_comf: float = 26.0, title: str = 'Indoor / outdoor temperature', ax: Any | None = None)[source]

Plot indoor (and optional outdoor) temperature with comfort threshold.

Parameters:

T_in – Indoor temperature series.
T_ext – Optional outdoor temperature series (overlaid on the same axes).
T_comf – Comfort threshold drawn as a horizontal reference line.
title – Plot title.
ax – Optional matplotlib axes. If None, a new figure is created.

Returns:

matplotlib.axes.Axes – The axes used.