def plot_snr_scatter(cv, foreground, background, lodm, hidm, marker_dms,
fallback):
'''
Add SNR versus DM scatter plot pulsetrain diagnostic plot.
Note: for internal use, call the diagnostic.plot() function in stead.
'''
pc2 = PlotContainer(740, 150, 300, 600, data_padding=PADDING)
pc2.right.hide_label()
pc2.right.hide_tickmarklabels()
pc2.left.hide_label()
pc2.left.hide_tickmarklabels()
pc2.bottom.hide_label()
pc2.top.set_label('SNR')
scp2 = ScatterPlotter([x[1] for x in foreground],
[x[0] for x in foreground], color='red')
scp3 = ScatterPlotter([x[1] for x in background],
[x[0] for x in background], color='black')
pc2.add(scp3, fallback)
pc2.add(scp2, fallback)
pc2.set_minimum_y_range(lodm, hidm)
for m_dm in marker_dms:
if lodm <= m_dm <= hidm:
pc2.add(YLimitPlotter(m_dm, color='orange'))
cv.add(pc2)
def plot_count_histogram(cv, dms, foreground, background, lodm, hidm,
marker_dms):
'''
Add candidates per DM histogram to pulse train diagnostic.
Note: for internal use, call the diagnostic.plot() function in stead.
'''
# Determine the brp style histogram bins:
fg_bins, bg_bins, total_bins = \
bin_candidates(dms, foreground, background, lodm, hidm)
# Plot histogram of number of detections per DM trial
pc3 = PlotContainer(950, 150, 300, 600, data_padding=PADDING)
pc3.left.hide_label()
pc3.left.hide_tickmarklabels()
pc3.bottom.hide_label()
pc3.top.set_label('N')
pc3.add(HistogramPlotter(bg_bins, orientation='vertical', color='black'))
pc3.add(HistogramPlotter(total_bins, orientation='vertical', color='gray'))
pc3.add(HistogramPlotter(fg_bins, orientation='vertical', color='red'))
pc3.right.set_label('DM')
pc3.set_minimum_y_range(lodm, hidm)
for m_dm in marker_dms:
if lodm <= m_dm <= hidm:
pc3.add(YLimitPlotter(m_dm, color='orange'))
cv.add(pc3)
def plot_main_panel(cv, foreground, background, lodm, hidm, marker_dms,
fallback):
'''
Add main panel to pulsetrain diagnostic plot.
Note: for internal use, call the diagnostic.plot() function in stead.
'''
# Main panel, detections on the time-DM plane
pc1 = PlotContainer(0, 150, 830, 600, data_padding=PADDING)
pc1.right.hide_label()
pc1.right.hide_tickmarklabels()
pc1.bottom.hide_label()
pc1.left.set_label('DM')
pc1.top.set_label('Time (s)')
pc1.add(DetectionPlotterTuples(background, color='black'), fallback)
pc1.add(DetectionPlotterTuples(foreground, color='red'), fallback)
pc1.set_minimum_y_range(lodm, hidm)
for m_dm in marker_dms:
if lodm <= m_dm <= hidm:
pc1.add(YLimitPlotter(m_dm, color='orange'))
cv.add(pc1)
