import numpy as np
from piel.visual.plot.position import create_axes_per_figure
from piel.visual.plot.core import save
from piel.types import Unit
from typing import Any
import logging
logger = logging.getLogger(__name__)
[docs]
def plot_basic_scalar_metric_collection_component(
scalar_metric_collection,
metric_component: str,
fig: Any = None,
axs: Any = None,
subplots_kwargs: dict = None,
xlabel: str | Unit = None,
ylabel: str | Unit = None,
title: str | Unit = None,
label: str | Unit = "",
**kwargs,
):
"""
Plots the specified component (e.g., 'mean', 'min', 'max') of a ScalarMetricCollection.
Args:
scalar_metric_collection (ScalarMetricCollection): The collection of scalar metrics to plot.
metric_component (str): The component of the ScalarMetric to plot (e.g., 'mean', 'min', 'max', 'value', 'standard_deviation', 'count').
fig (matplotlib.figure.Figure, optional): Existing figure to plot on. If None, a new figure is created.
axs (list[matplotlib.axes.Axes], optional): Existing list of axes to plot on. If None, new axes are created. Plots on [0] by default.
subplots_kwargs (dict, optional): Keyword arguments to pass to create_axes_per_figure.
xlabel (str | Unit, optional): Label for the x-axis.
ylabel (str | Unit, optional): Label for the y-axis.
title (str | Unit, optional): Title for the plot.
**kwargs: Additional keyword arguments to pass to the save function.
Returns:
tuple: A tuple containing the figure and axes objects.
"""
# Extract the desired component from each metric in the collection
component_values = []
for metric in scalar_metric_collection.metrics:
# Get the specified component (mean, min, max, etc.)
component_value = getattr(metric, metric_component, None)
if component_value is not None:
component_values.append(component_value)
else:
component_values.append(float("nan")) # Handle missing values
# Handle empty or missing component values
if len(component_values) == 0:
raise ValueError(f"No valid {metric_component} values found in the collection.")
# If no labels provided, set default values
if xlabel is None:
xlabel = "Metric Index"
if ylabel is None:
ylabel = scalar_metric_collection.metrics[0].unit.label
y_correction = scalar_metric_collection.metrics[0].unit.base
elif isinstance(ylabel, str):
pass
elif isinstance(ylabel, Unit):
y_correction = ylabel.base
logger.warning(
f"Data correction of 1/{y_correction} from unit definition {ylabel} will be applied on y-axis."
)
ylabel = ylabel.label
if subplots_kwargs is None:
subplots_kwargs = {}
if (fig is None) or (axs is None):
fig, axs = create_axes_per_figure(rows=1, columns=1, **subplots_kwargs)
elif fig is None or axs is None:
raise ValueError("Both fig and ax should be provided together or left as None.")
if title is None:
pass
else:
fig.suptitle(title)
ax = axs[0]
# Plot the component values
ax.plot(
np.arange(len(component_values)),
component_values,
marker="o",
linestyle="-",
label=label,
)
# Set labels, title, and legend
ax.set_xlabel(xlabel)
ax.set_ylabel(ylabel)
ax.set_title(title)
# Optional saving functionality
save(fig, **kwargs)
return fig, ax
