import matplotlib.pyplot as plt
from ..settings import PhotometryApertures
__all__ = ["seeing_plot"]
[docs]
def seeing_plot(
raw_radius,
raw_counts,
binned_radius,
binned_counts,
HWHM,
plot_title="",
file_name="",
photometry_settings=None,
figsize=(20, 10),
):
"""
Show a seeing plot for data from an image with radius on the x axis and
counts (ADU) on the y axis.
Parameters
----------
raw_radius : array
the distance of each pixel from the object of interest
raw_counts : array
the counts of each pixel
binned_radius : array
pixels grouped by distance from object of interest
binned_counts : array
average counts of each group of pixels
HWHM : number
half width half max, 1/2 * FWHM
plot_title : optional, string
title of plot
file_name : optional, string
if entered, file will save as png with this name
photometry_settings : optional, `stellarphot.settings.PhotometryApertures`
The aperture settings used to create the plot. If not provided, the
aperture radius will be set to 4 * HWHM, the inner annulus will be set
to radius + 10, and the outer annulus will be set to radius + 25, and the
FWHM will be set to 2 * HWHM.
figsize : tuple of int, optional
Size of figure.
Returns
-------
`matplotlib.pyplot.figure`
The figure object containing the seeing plot.
"""
if photometry_settings is None:
radius = 4 * HWHM
photometry_settings = PhotometryApertures(
radius=radius,
inner_annulus=radius + 10,
outer_annulus=radius + 25,
fwhm_estimate=2 * HWHM,
variable_aperture=False,
)
radius = photometry_settings.radius_pixels(2 * HWHM)
inner_annulus = photometry_settings.inner_annulus
outer_annulus = photometry_settings.outer_annulus
fig = plt.figure(figsize=figsize)
plt.grid(True)
# plot the raw radius and raw counts
plt.plot(
raw_radius,
raw_counts,
linestyle="none",
marker="s",
markerfacecolor="none",
color="blue",
)
# plot the binned radius and binned counts
plt.plot(binned_radius, binned_counts, color="magenta", linewidth="1.0")
# draw vertical line at HWHM and label it
plt.vlines(HWHM, -0.2, 1.2, linestyle=(0, (5, 10)), color="#00cc00")
plt.annotate(
f"HWHM {HWHM:2.1f}",
(HWHM, -0.25),
color="#00cc00",
horizontalalignment="center",
)
# label axis
plt.xlabel("Radius (pixels)")
plt.ylabel("ADU")
# draw vertical line at the radius and label it
plt.vlines(radius, -0.2, binned_counts[0], color="red")
plt.annotate(
f"Radius {radius:2.1f}",
(radius, -0.25),
color="red",
horizontalalignment="center",
)
plt.hlines(binned_counts[0], binned_counts[0], radius, color="red")
# label the source
plt.annotate(
"SOURCE",
(radius, binned_counts[0] + 0.02),
color="red",
horizontalalignment="center",
)
# draw vertical lines at the background and label it
plt.vlines(inner_annulus, -0.2, binned_counts[0], color="red")
plt.vlines(outer_annulus, -0.2, binned_counts[0], color="red")
plt.hlines(binned_counts[0], inner_annulus, outer_annulus, color="red")
plt.annotate("BACKGROUND", (inner_annulus, binned_counts[0] + 0.02), color="red")
plt.annotate(
f"Back> {inner_annulus:2.1f}",
(inner_annulus, -0.25),
color="red",
horizontalalignment="center",
)
plt.annotate(
f"<Back {outer_annulus:2.1f}",
(outer_annulus, -0.25),
color="red",
horizontalalignment="center",
)
# title the plot
title_string = [f"{plot_title}", f"FWHM:{HWHM*2:.1f} pixels"]
plt.title("\n".join(title_string))
# save plot as png
if file_name:
safe_name = file_name.replace(" ", "-")
plt.savefig(f"{safe_name + '-seeing-profile'}.png")
return fig
