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"""Helper function to plot a set of bandpasses in sphinx docs."""
import numpy as np
from matplotlib import rc
from matplotlib import pyplot as plt
import sncosmo
cmap = plt.get_cmap('viridis')
def plot_bandpass_set(setname, label_prefix=''):
"""Plot the given set of bandpasses."""
rc("font", family="serif")
bandpass_meta = sncosmo.bandpasses._BANDPASSES.get_loaders_metadata()
fig = plt.figure(figsize=(9, 3))
ax = plt.axes()
nbands = 0
for m in bandpass_meta:
if (
m['filterset'] != setname or
# special case of ZTF position-dependent bandpasses
'ztf::' in m['name']
):
continue
b = sncosmo.get_bandpass(m['name'])
# add zeros on either side of bandpass transmission
wave = np.zeros(len(b.wave) + 2)
wave[0] = b.wave[0]
wave[1:-1] = b.wave
wave[-1] = b.wave[-1]
trans = np.zeros(len(b.trans) + 2)
trans[1:-1] = b.trans
ax.plot(wave, trans, label=label_prefix + m['name'])
nbands += 1
ax.set_xlabel("Wavelength ($\\AA$)")
ax.set_ylabel("Transmission")
ncol = 1 + (nbands-1) // 9 # 9 labels per column
ax.legend(loc='upper right', frameon=False, fontsize='small',
ncol=ncol)
# Looks like each legend column takes up about 0.125 of the figure.
# Make room for the legend.
xmin, xmax = ax.get_xlim()
xmax += ncol * 0.125 * (xmax - xmin)
ax.set_xlim(xmin, xmax)
plt.tight_layout()
plt.show()
def plot_bandpass_interpolators(names):
# we'll figure out min and max wave as we go.
minwave = float('inf')
maxwave = 0.
fig, axes = plt.subplots(nrows=len(names), ncols=1,
figsize=(9., 2.5*len(names)), squeeze=True,
sharex=True)
for i in range(len(names)):
bi = sncosmo.bandpasses._BANDPASS_INTERPOLATORS.retrieve(names[i])
radii = np.linspace(bi.minpos(), bi.maxpos()-0.000001, 8)
for r in radii:
band = bi.at(r)
# update min,max wave
minwave = min(minwave, band.minwave())
maxwave = max(maxwave, band.maxwave())
wave = np.linspace(band.minwave(), band.maxwave(), 1000)
trans = band(wave)
label = ("radius = {:4.1f}cm".format(r)
if (r == radii[0] or r == radii[-1])
else None)
axes[i].plot(wave, trans, color=cmap((r - bi.minpos())/
(bi.maxpos() - bi.minpos())),
label=label)
axes[i].legend(loc='upper right')
axes[i].set_ylabel("Transmission")
axes[i].text(0.03, 0.92, names[i], transform=axes[i].transAxes,
va='top', ha='left')
axes[-1].set_xlabel("Wavelength ($\\AA$)")
plt.tight_layout()
plt.show()
def plot_general_bandpass_interpolators(name):
if name == 'hsc':
return plot_bandpass_set(name, label_prefix='averaged ')
names = [
m['name'] for m in sncosmo.bandpasses._BANDPASS_INTERPOLATORS.get_loaders_metadata()
if m['filterset'] == name]
# we'll figure out min and max wave as we go.
minwave = float('inf')
maxwave = 0.
fig, axes = plt.subplots(nrows=len(names), ncols=1,
figsize=(9., 2.5*len(names)), squeeze=True,
sharex=True)
for i in range(len(names)):
bi = sncosmo.bandpasses._BANDPASS_INTERPOLATORS.retrieve(names[i])
b = sncosmo.bandpasses._BANDPASSES.retrieve(names[i])
# add zeros on either side of bandpass transmission
wave = np.zeros(len(b.wave) + 2)
wave[0] = b.wave[0]
wave[1:-1] = b.wave
wave[-1] = b.wave[-1]
trans = np.zeros(len(b.trans) + 2)
trans[1:-1] = b.trans
axes[i].plot(wave, trans, label='average')
x = 1000
y = 1000
nsensors = len(bi.transforms._to_focalplane)
for n, sid in enumerate(np.linspace(1, nsensors-1, 4, dtype=int)):
band = bi.at(x=x, y=y, sensor_id=sid)
# update min,max wave
minwave = min(minwave, band.minwave())
maxwave = max(maxwave, band.maxwave())
wave = np.linspace(band.minwave(), band.maxwave(), 1000)
trans = band(wave)
label = 'x={}, y={}, sensor_id={}'.format(x, y, sid)
axes[i].plot(wave, trans, label=label, color=cmap(n / 4), linestyle='dotted')
axes[i].legend(loc='upper right')
axes[i].set_ylabel("Transmission")
axes[i].text(0.03, 0.92, names[i], transform=axes[i].transAxes,
va='top', ha='left')
axes[-1].set_xlabel("Wavelength ($\\AA$)")
plt.tight_layout()
plt.show()
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