"""
Visualization utilities for astronomical images.
This module provides functions for image scaling and for plotting
marks and labels on matplotlib axes.
"""
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import patches
from astropy.visualization import ZScaleInterval
[docs]
def z_scale(data, c=0.05):
"""
Compute z-scale interval for image display.
Parameters
----------
data : np.ndarray
2D image data.
c : float, optional
Contrast parameter for ZScaleInterval.
Returns
-------
tuple
(vmin, vmax) for display scaling.
"""
interval = ZScaleInterval(contrast=c)
return interval(data.copy())
[docs]
def plot_marks(
x,
y,
label=None,
position="bottom",
offset=7,
fontsize=12,
color=[0.51, 0.86, 1.0],
ms=12,
n=None,
inside=True,
alpha=1,
ax=None,
):
"""
Plot circular marks and optional labels on a matplotlib axis.
Parameters
----------
x : array-like
X coordinates.
y : array-like
Y coordinates.
label : array-like or None, optional
Labels for each mark.
position : str, optional
Position of the label ("top" or "bottom").
offset : float, optional
Offset for label position.
fontsize : int, optional
Font size for labels.
color : list or str, optional
Color for marks and labels.
ms : float, optional
Marker size.
n : int or None, optional
Number of marks to plot.
inside : bool, optional
Only plot marks inside axis limits.
alpha : float, optional
Alpha transparency.
ax : matplotlib.axes.Axes or None, optional
Axis to plot on.
Returns
-------
None
"""
y_offset = ms + offset
if position == "top":
y_offset *= -1
if not isinstance(x, (list, np.ndarray, tuple)):
x = np.array([x])
y = np.array([y])
if label is True:
label = np.array([0])
elif label is not None:
label = np.array([label])
else:
if label is True:
label = np.arange(len(x))
elif label is not None:
label = np.array(label)
if ax is None:
ax = plt.gcf().axes[0]
if inside:
ax = ax
xlim, ylim = np.array(ax.get_xlim()), np.array(ax.get_ylim())
xlim.sort()
ylim.sort()
within = np.argwhere(
np.logical_and.reduce([xlim[0] < x, x < xlim[1], ylim[0] < y, y < ylim[1]])
).flatten()
x = x[within]
y = y[within]
if label is not None:
print
label = label[within]
if n is not None:
x = x[0:n]
y = y[0:n]
if label is not None:
label = label[0:n]
if label is None:
label = [None for _ in range(len(x))]
for _x, _y, _label in zip(x, y, label):
circle = patches.Circle((_x, _y), ms, fill=None, ec=color, alpha=alpha)
ax.add_artist(circle)
f = 5
if _label is not None:
plt.annotate(
_label,
xy=[_x, _y - y_offset],
color=color,
ha="center",
fontsize=fontsize,
alpha=alpha,
va="top" if position == "bottom" else "bottom",
)
