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)
c.top.hide_all()
c.bottom.hide_all()
c.left.hide_label()
c.left.hide_tickmarklabels()
c.right.set_label('Significance (sigma)')
c.add_plotter(GradientPlotter(gr2))
cv.add_plot_container(c)
# ------------------------------------------------------
# -- For debugging raster fallback ---------------------
# Note: this also tests the 'new' shortcuts on SVGCanvas and PlotContainer
# The raster fallback might still have some off-by-one problems.
gr = RGBGradient((0, 25), (0, 0, 1), (1, 0, 0))
gr2 = RGBGradient((0, 25), (1, 0, 0), (0, 0, 1))
c = PlotContainer(100, 1900, 600, 400)
xdata = list(range(25))
c.add(ScatterPlotter(xdata, symbols=[RasterDebugSymbol]), True)
c.add(ScatterPlotter(xdata, symbols=[RasterDebugSymbol]))
xdata.reverse()
colors = ['yellow' for x in xdata]
c.add(ScatterPlotter(xdata, symbols=[BaseSymbol], colors=colors))
c.add(ScatterPlotter(xdata, gradient=gr, gradient_i=0), True)
cv.add(c)
#
# ------------------------------------------------------
cv.draw(sys.stdout)
c.top.hide_all()
c.bottom.hide_all()
c.left.hide_label()
c.left.hide_tickmarklabels()
c.right.set_label("Significance (sigma)")
c.add_plotter(GradientPlotter(gr2))
cv.add_plot_container(c)
# ------------------------------------------------------
# -- For debugging raster fallback ---------------------
# Note: this also tests the 'new' shortcuts on SVGCanvas and PlotContainer
# The raster fallback might still have some off-by-one problems.
gr = RGBGradient((0, 25), (0, 0, 1), (1, 0, 0))
gr2 = RGBGradient((0, 25), (1, 0, 0), (0, 0, 1))
c = PlotContainer(100, 1900, 600, 400)
xdata = list(range(25))
c.add(ScatterPlotter(xdata, symbols=[RasterDebugSymbol]), True)
c.add(ScatterPlotter(xdata, symbols=[RasterDebugSymbol]))
xdata.reverse()
colors = ["yellow" for x in xdata]
c.add(ScatterPlotter(xdata, symbols=[BaseSymbol], colors=colors))
c.add(ScatterPlotter(xdata, gradient=gr, gradient_i=0), True)
cv.add(c)
#
# ------------------------------------------------------
cv.draw(sys.stdout)
cv = SVGCanvas(1200, 1800)
# ------------------------------------------------------
# -- For debugging RADECSymbol raster fallback ---------
NPULSARS = 100
P = [random.uniform(0.001, 10) for i in range(NPULSARS)]
DM = [random.uniform(1, 100) for i in range(NPULSARS)]
RA = [random.uniform(0, 24) for i in range(NPULSARS)]
DEC = [random.uniform(-90, 90) for i in range(NPULSARS)]
SIGMA = [random.uniform(2, 15) for i in range(NPULSARS)]
# plot
pc = PlotContainer(0, 0, 600, 400)
pc.add(ScatterPlotter(P, DM, RA, DEC, SIGMA, symbol=RADECSymbol))
cv.add(pc)
pc = PlotContainer(600, 0, 600, 400)
pc.add(ScatterPlotter(P, DM, RA, DEC, SIGMA, symbols=[RADECSymbol]),
raster=True)
cv.add(pc)
# ------------------------------------------------------
# -- For debugging error bar raster fallback -----------
# LINEAR TRANSFORM CASE:
# c = PlotContainer(0, 400, 600, 400, x_log=True, y_log=True)
c = PlotContainer(600, 400, 600, 400)
data_y = [10, 10, 20, 30, 40, 50, 40, 30, 20, 10, 10]
from brp.svg.plotters.gradient import GradientPlotter
from brp.svg.plotters.line import LinePlotter
if __name__ == '__main__':
x_data = [r() for i in range(1000)]
y_data = [r() for i in range(1000)]
cv = SVGCanvas(1200, 800)
p = PlotContainer(0, 0, 600, 400)
h = newhist2d.Histogram2dPlotter(x_data, y_data, x_bins=100)
gr = h.get_gradient()
collapsed_x, yvalues = h.collapse_x()
xvalues, collapsed_y = h.collapse_y()
p.add(h)
cv.add(p)
p = PlotContainer(800, 0, 160, 400)
p.add(GradientPlotter(gr, 'vertical'))
cv.add(p)
p = PlotContainer(600, 0, 200, 400)
p.add(LinePlotter(collapsed_x, yvalues))
cv.add(p)
p = PlotContainer(0, 400, 600, 200)
p.add(LinePlotter(xvalues, collapsed_y))
cv.add(p)
cv.draw(sys.stdout)
import sys
#sys.path.append('../')
from brp.svg.base import SVGCanvas, PlotContainer, TextFragment
from brp.svg.plotters.histogram import HistogramPlotter, merge_bins
if __name__ == '__main__':
bins = [(0, 1, 10), (1, 2, 10), (2, 3, 11), (3, 4, 10), (4, 5, 10),
(5, 6, 7)]
cv = SVGCanvas(1200, 1200)
# Histogram testing:
c = PlotContainer(0, 0, 600, 400)
c.add(HistogramPlotter(bins))
cv.add(c)
cv.add(TextFragment(100, 100, 'Unmerged bins', color='red'))
merged = merge_bins(bins)
c2 = PlotContainer(600, 0, 600, 400)
c2.add(HistogramPlotter(merged))
cv.add(c2)
cv.add(TextFragment(700, 100, 'Merged bins', color='red'))
cv.draw(sys.stdout)
