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215 | def plot_cluster(
name,
fits_path,
units="mJy",
bound=None,
radius=2.0,
plot_r=True,
figsize=(5, 5),
ncontours=0,
hdu=0,
downsample=1,
smooth=9.0,
convention="calabretta",
):
"""
Function for doing core plotting. TODO: This function could probably use an args/kwargs, but there are an enourmous number of keyword args within so that might be difficult.
Parameters:
-----------
Name : str
Name of the cluster
fits_path : str
Path to the fits file to be plotted.
units : str, default: mJy
String to be used as units. If snr, then it will autoformat to sigma
bound : None | float, default: None
Bounds for the colormap. If none, reasonable bounds will be computed.
radius : float, default: 2.0
Radius, in arcmin, of figure
plot_r : bool | str, default: True
If true, plot r500. If a str, plot a related critical radius
figsize : tuple[float, float], default: (5,5)
Width and height of plot in inches.
ncontours : int, default = 0
Number of countours to be plotted
hdu : int, default: 0
Fits hdu corresponding to the image to be plotted
downsample : int, default: 1
Factor by which to downsample the image.
smooth : float, default: 9.0
Scale, in arcminutes, at which to smooth the image.
convention : str, default: calabretta
Determines interpretation of abigious fits headers. See aplpy.FITSFigure documentation
Returns:
--------
img: aplpy.FITSFigure
FITSFigure plot of the cluster
"""
fits_path = os.path.abspath(fits_path)
root = os.path.split(os.path.split(fits_path)[0])[0]
res_path = (
root
+ "/"
+ str(sorted([file for file in os.listdir(root) if ".dill" in file])[-1])
)
with open(res_path, "rb") as f:
results = pk.load(f)
pix_size = results.pix_size * rad_to_arcsec
cfg_path = root + "/" + "config.yaml"
cfg = load_config({}, cfg_path)
smooth = max(
1, int(smooth / pix_size)
) # FITSfigure smoothing is in pixels, so convert arcsec to pixels
kernel = Gaussian2DKernel(x_stddev=smooth * 5)
fig = plt.figure(figsize=figsize)
img = aplpy.FITSFigure(
fits_path,
hdu=hdu,
figure=fig,
downsample=downsample,
smooth=False,
convention=convention,
) # Smooth here does something whack
img.set_theme("publication")
## make and register a divergent blue-orange colormap:
cmap = "mymap"
try:
cm.get_cmap(
cmap
) # Stops these anoying messages if you've already registered mymap
except:
bottom = cm.get_cmap("Oranges", 128)
top = cm.get_cmap("Blues_r", 128)
newcolors = np.vstack(
(top(np.linspace(0, 1, 128)), bottom(np.linspace(0, 1, 128)))
)
cm.register_cmap(cmap, cmap=ListedColormap(newcolors))
if bound is None:
nx, ny = img._data.shape
lims = int(radius * 60 / pix_size)
xmin = int(nx / 2 - lims)
xmax = int(nx / 2 + lims)
ymin = int(ny / 2 - lims)
ymax = int(ny / 2 + lims)
bound = np.amax(np.abs(img._data[xmin:xmax, ymin:ymax]))
order = int(np.floor(np.log10(bound)))
bound = np.round(bound, -1 * order) / 2
img.show_colorscale(cmap=cmap, stretch="linear", vmin=-bound, vmax=bound, smooth=3)
ra = eval(cfg["coords"]["x0"])
dec = eval(cfg["coords"]["y0"])
ra, dec = np.rad2deg(
[ra, dec]
) # TODO: Currently center on config center, which is fine but should probably be fit center
img.recenter(ra, dec, radius=radius / 60.0)
img.ax.tick_params(axis="both", which="both", direction="in")
matplotlib.rcParams["lines.linewidth"] = 3.0
img.add_scalebar(
0.5 / 60.0, '30"', color="black"
) # Adds a 30 arcsec scalebar to the image
matplotlib.rcParams["lines.linewidth"] = 2.0
img.add_beam(
major=9.0 / 3600.0, minor=9.0 / 3600.0, angle=0
) # TODO: For now hard-coded to M2 beam but may want some flexibility later
img.beam.set_color("white")
img.beam.set_edgecolor("green")
img.beam.set_facecolor("white")
img.beam.set_corner("bottom left")
img.show_markers(
ra,
dec,
facecolor="black",
edgecolor=None,
marker="+",
s=50,
linewidths=2,
alpha=0.5,
)
img.add_colorbar("right")
img.colorbar.set_width(0.12)
if units == "snr":
cbar_label = r"$\sigma$"
else:
cbar_label = str(units)
img.colorbar.set_axis_label_text(cbar_label)
if ncontours:
matplotlib.rcParams["lines.linewidth"] = 0.5
clevels = np.linspace(-bound, bound, ncontours)
img.show_contour(
fits_path,
colors="gray",
levels=clevels,
returnlevels=True,
convention="calabretta",
smooth=3,
)
if plot_r: # TODO: Allow passing of r500 values, make this a subfunction
if "a10" in cfg["model"]["structures"].keys():
mod_type = "a10"
elif "ea10" in cfg["model"]["structures"].keys():
mod_type = "ea10"
else:
raise ModelError("For R500, must have structure type A10 or EA10")
for i in range(len(results.structures)):
if str(results.structures[i].name) == mod_type:
break
for parameter in results.structures[i].parameters:
if str(parameter.name.lower()) == "m500":
m500 = parameter.val
break
z = float(cfg["constants"]["z"])
nz = get_nz(z)
r500 = (m500 / (4.00 * np.pi / 3.00) / 5.00e02 / nz) ** (1.00 / 3.00)
da = get_da(z)
r500 /= da
if plot_r == "rs":
r500 /= float(
cfg["model"]["structures"][mod_type]["parameters"]["c500"]["value"]
) # Convert to rs
img.show_circles(
ra, dec, radius=r500 / 3600, coords_frame="world", color="green"
)
return img
|