def plot_peaks_aft_histogram(
context, run_id, peaks,
pe_bins=np.logspace(0, 7, 120),
rt_bins=np.geomspace(2, 1e5, 120),
extra_labels=tuple(),
rate_range=(1e-4, 1),
aft_range=(0, .85),
figsize=(14, 5)):
"""Plot side-by-side (area, width) histograms of the peak rate
and mean area fraction top.
:param pe_bins: Array of bin edges for the peak area dimension [PE]
:param rt_bins: array of bin edges for the rise time dimension [ns]
:param extra_labels: List of (area, risetime, text, color) extra labels
to put on the plot
:param rate_range: Range of rates to show [peaks/(bin*s)]
:param aft_range: Range of mean S1 area fraction top / bin to show
:param figsize: Figure size to use
"""
livetime_sec = straxen.get_livetime_sec(context, run_id, peaks)
mh = Histdd(peaks,
dimensions=(
('area', pe_bins),
('range_50p_area', rt_bins),
('area_fraction_top', np.linspace(0, 1, 100))
))
f, axes = plt.subplots(1, 2, figsize=figsize)
def std_axes():
plt.gca().set_facecolor('k')
plt.yscale('log')
plt.xscale('log')
plt.xlabel("Area [PE]")
plt.ylabel("Range 50% area [ns]")
labels = [
(12, 8, "AP?", 'white'),
(3, 150, "1PE\npileup", 'gray'),
(30, 200, "1e", 'gray'),
(100, 1000, "n-e", 'w'),
(2000, 2e4, "Train", 'gray'),
(1200, 50, "S1", 'w'),
(45e3, 60, "αS1", 'w'),
(2e5, 800, "S2", 'w'),
] + list(extra_labels)
for x, w, text, color in labels:
plt.text(x, w, text, color=color,
verticalalignment='center',
horizontalalignment='center')
plt.sca(axes[0])
(mh / livetime_sec).sum(axis=2).plot(
log_scale=True,
vmin=rate_range[0], vmax=rate_range[1],
colorbar_kwargs=dict(extend='both'),
cblabel='Peaks / (bin * s)')
std_axes()
plt.sca(axes[1])
mh.average(axis=2).plot(
vmin=aft_range[0], vmax=aft_range[1],
colorbar_kwargs=dict(extend='max'),
cmap=plt.cm.jet, cblabel='Mean area fraction top')
std_axes()
plt.tight_layout()
def plot_peaks_aft_histogram(context,
run_id,
peaks,
pe_bins=np.logspace(0, 7, 120),
width_bins=np.geomspace(2, 1e5, 120),
extra_labels=tuple(),
rate_range=(1e-4, 1),
aft_range=(0, .85),
figsize=(14, 5)):
"""Plot side-by-side (area, width) histograms of the peak rate
and mean area fraction top."""
try:
md = context.run_metadata(run_id, projection=('start', 'end'))
livetime_sec = (md['end'] - md['start']).total_seconds()
except strax.RunMetadataNotAvailable:
livetime_sec = (strax.endtime(peaks)[-1] - peaks[0]['time']) / 1e9
mh = Histdd(peaks,
dimensions=(('area', pe_bins), ('range_50p_area', width_bins),
('area_fraction_top', np.linspace(0, 1, 100))))
f, axes = plt.subplots(1, 2, figsize=figsize)
def std_axes():
plt.gca().set_facecolor('k')
plt.yscale('log')
plt.xscale('log')
plt.xlabel("Area [PE]")
plt.ylabel("Range 50% area [ns]")
labels = [
(12, 8, "AP?", 'white'),
(3, 150, "1PE\npileup", 'gray'),
(30, 200, "1e", 'gray'),
(100, 1000, "n-e", 'w'),
(2000, 2e4, "Train", 'gray'),
(1200, 50, "S1", 'w'),
(45e3, 60, "αS1", 'w'),
(2e5, 800, "S2", 'w'),
] + list(extra_labels)
for x, w, text, color in labels:
plt.text(x,
w,
text,
color=color,
verticalalignment='center',
horizontalalignment='center')
plt.sca(axes[0])
(mh / livetime_sec).sum(axis=2).plot(log_scale=True,
vmin=rate_range[0],
vmax=rate_range[1],
colorbar_kwargs=dict(extend='both'),
cblabel='Peaks / (bin * hour)')
std_axes()
plt.sca(axes[1])
mh.average(axis=2).plot(vmin=aft_range[0],
vmax=aft_range[1],
colorbar_kwargs=dict(extend='max'),
cmap=plt.cm.jet,
cblabel='Mean area fraction top')
std_axes()
plt.tight_layout()
