def render(self, context):
qs = context[self.var_name]
tmp = StringIO.StringIO()
P = [c.p_bary for c in qs.all() if c.p_bary > 0]
cv = SVGCanvas(940, 550, background_color='white')
if P:
binned = bin_data_log(P, 200)
pc = PlotContainer(0, -20, 950, 550, color='black', x_log=True)
pc.bottom.set_label('Period (ms)')
pc.top.hide_label()
pc.left.set_label('Count')
pc.right.hide_label()
hp = HistogramPlotter(binned, color='black')
pc.add_plotter(hp)
cv.add_plot_container(pc)
# write number of candidates shown:
tf = TextFragment(50,
520,
'(Showing %d candidates.)' % len(P),
color='black',
font_size=15)
cv.add_plot_container(tf)
else:
tf = TextFragment(200,
200,
'No Candidates found.',
color='red',
font_size=50)
cv.add_plot_container(tf)
tmp = StringIO.StringIO()
cv.draw(tmp)
return tmp.getvalue()
def render(self, context):
qs = context[self.var_name]
tmp = StringIO.StringIO()
P = [c.p_bary for c in qs.all() if c.p_bary > 0]
cv = SVGCanvas(940, 550, background_color='white')
if P:
binned = bin_data_log(P, 200)
pc = PlotContainer(0, -20, 950, 550, color='black', x_log=True)
pc.bottom.set_label('Period (ms)')
pc.top.hide_label()
pc.left.set_label('Count')
pc.right.hide_label()
hp = HistogramPlotter(binned, color='black')
pc.add_plotter(hp)
cv.add_plot_container(pc)
# write number of candidates shown:
tf = TextFragment(50, 520, '(Showing %d candidates.)' %
len(P), color='black', font_size=15)
cv.add_plot_container(tf)
else:
tf = TextFragment(200, 200, 'No Candidates found.', color='red',
font_size=50)
cv.add_plot_container(tf)
tmp = StringIO.StringIO()
cv.draw(tmp)
return tmp.getvalue()
def plot(filename, spr, options, pulse_trains, pt_idx, rejected_pulses,
nlink, plink, marker_dms):
'''
Create a pulsetrain diagnostic plot.
Note: Call this function to create the plot, not others in this module.
'''
# Find DM range for this plot:
lodm, hidm = find_dm_range(spr.dms, pulse_trains[pt_idx])
# Flatten pulses into list of candidates (foreground, background):
foreground = flatten_pulses(pulse_trains[pt_idx], lodm, hidm)
background = flatten_pulses(rejected_pulses, lodm, hidm)
for i in range(len(pulse_trains)):
if i != pt_idx:
background.extend(flatten_pulses(pulse_trains[i], lodm, hidm))
# Determine whether it is wise to switch to rasterized plotting (called
# fallback).
n_candidates = len(foreground) + len(background)
if n_candidates > MAX_N_CANDIDATES:
fallback = True
else:
fallback = False
# Set up the overall canvas to wich all panels are plot:
cv = SVGCanvas(1250, 750)
# Add the three panels to the plot:
plot_main_panel(cv, foreground, background, lodm, hidm, marker_dms,
fallback)
plot_snr_scatter(cv, foreground, background, lodm, hidm, marker_dms,
fallback)
plot_count_histogram(cv, spr.dms, foreground, background, lodm, hidm,
marker_dms)
# Add the text identifying the data set etc. to the diagnostic plot:
add_text(cv, spr.md_map[spr.dms[0]], nlink, plink, n_candidates, fallback)
add_settings_text(cv, options)
add_trigger_text(cv, pulse_trains, pt_idx)
# Finally write everything out to an SVG (xml) file.
with open(filename, 'w') as f:
cv.draw(f)
p = get_commandline_parser()
options, args = p.parse_args()
if len(args) == 0:
p.print_usage()
p.print_help()
# Some custom checks:
delays_file = check_delays_option(options, args, p)
check_type_option(options, args, p)
output_files = check_directories(options, args, p)
for plot_i, searchoutdir, fn in output_files:
print plot_i, searchoutdir, fn
# Do some setting up and calculations:
cv = SVGCanvas(1250, 760)
try:
print 'Scanning for .singlepulse and .inf files ...'
spr = SinglePulseReaderCondensed(searchoutdir, options.s, options.e,
delays_file, options.lo, options.hi)
print '... done'
except:
raise
datapath = os.path.abspath(searchoutdir)
msg = 'Problem with data in %s, nothing present?' % datapath
cv.add_plot_container(TextFragment(100, 100, msg, font_size=15))
else:
print 'Number of DM-trials: %d' % len(spr.dms)
tf = TextFragment(870, 600, spr.sp_map[spr.dms[0]][:-12])
cv.add_plot_container(tf)
min_dmi, max_dmi = get_dmi_range(spr, options.dmspercell)
from brp.svg.plotters.symbol import RADECSymbol
from brp.svg.plotters.symbol import RasterDebugSymbol
from brp.svg.plotters.line import LinePlotter
from brp.svg.plotters.scatter import ScatterPlotter
from brp.svg.plotters.gradient import RGBGradient, GradientPlotter
from brp.svg.plotters.crosshair import CrossHairPlotter
from brp.svg.plotters.limit import XLimitPlotter, YLimitPlotter
from brp.svg.plotters.legend import LegendPlotter, UNDER_PLOT, BOTTOMLEFT
from brp.core.interval import stretch_interval
from brp.svg.plotters.histogram import HistogramPlotter, bin_data
from brp.svg.plotters.error import ErrorPlotter
from brp.svg.plotters.linkbox import LinkBox
if __name__ == '__main__':
# Draw a simple scatter + line plot to SVG (dumped to standard out).
cv = SVGCanvas(1000, 2500)
c = PlotContainer(100,
100,
600,
400,
background_color="white",
x_log=True,
y_log=True)
TMP = [10 * x + 10 for x in range(99)]
TMP2 = [10 * x + 10 for x in range(99)]
TMP2.reverse()
gr = RGBGradient((200, 800), (1, 0, 0), (0, 0, 1))
c.add_plotter(
LinePlotter(TMP,
TMP,
def render(self, context):
qs = context[self.var_name]
P = [c.p_bary for c in qs.all() if c.best_dm > 0]
DM = [c.best_dm for c in qs.all() if c.best_dm > 0]
REDCHISQ = [c.reduced_chi_sq for c in qs.all() if c.best_dm > 0]
LINKS = [reverse('bestprof_detail', args=[c.pk])
for c in qs.all() if c.best_dm > 0]
RA = [c.ra_deg for c in qs.all() if c.best_dm > 0]
DEC = [c.dec_deg for c in qs.all() if c.best_dm > 0]
cv = SVGCanvas(940, 550, background_color='white')
if P:
lo_dm = min(DM)
max_dm = max(DM)
pc = PlotContainer(0, -20, 880, 550, color='black', x_log=True,
y_log=True, data_background_color='gray')
gr = RGBGradient((lo_dm, max_dm), (0, 0, 1), (1, 0, 0))
scp = ScatterPlotter(P, REDCHISQ, RA, DEC, DM, gradient=gr,
gradient_i=4, links=LINKS,
symbol=RADECSymbol)
pc.add_plotter(scp)
# pc.top.hide_tickmarklabels()
pc.top.hide_label()
# pc.right.hide_tickmarklabels()
pc.right.hide_label()
pc.left.set_label('Reduced Chi Square')
pc.bottom.set_label('Period (ms)')
cv.add_plot_container(pc)
# Gradient:
pc = PlotContainer(820, -20, 120, 550, color='black', data_padding=0)
pc.top.hide_label()
pc.top.hide_tickmarks()
pc.left.hide_tickmarks()
pc.bottom.hide_label()
pc.bottom.hide_tickmarks()
pc.left.hide_label()
pc.right.set_label('Dispersion Measure cm^-3 pc')
pc.add_plotter(GradientPlotter(gr))
cv.add_plot_container(pc)
# write number of candidates shown:
tf = TextFragment(50, 520,
'(Showing %d candidates.)' % len(P),
color='black', font_size=15)
cv.add_plot_container(tf)
else:
tf = TextFragment(200, 200, 'No Candidates found.', color='red',
font_size=50)
cv.add_plot_container(tf)
tmp = StringIO.StringIO()
cv.draw(tmp)
return tmp.getvalue()
from brp.svg.plotters.symbol import RADECSymbol
from brp.svg.plotters.symbol import RasterDebugSymbol
from brp.svg.plotters.line import LinePlotter
from brp.svg.plotters.scatter import ScatterPlotter
from brp.svg.plotters.gradient import RGBGradient, GradientPlotter
from brp.svg.plotters.crosshair import CrossHairPlotter
from brp.svg.plotters.limit import XLimitPlotter, YLimitPlotter
from brp.svg.plotters.legend import LegendPlotter, UNDER_PLOT, BOTTOMLEFT
from brp.core.interval import stretch_interval
from brp.svg.plotters.histogram import HistogramPlotter, bin_data
from brp.svg.plotters.error import ErrorPlotter
from brp.svg.plotters.linkbox import LinkBox
if __name__ == "__main__":
# Draw a simple scatter + line plot to SVG (dumped to standard out).
cv = SVGCanvas(1000, 2500)
c = PlotContainer(100, 100, 600, 400, background_color="white", x_log=True, y_log=True)
TMP = [10 * x + 10 for x in range(99)]
TMP2 = [10 * x + 10 for x in range(99)]
TMP2.reverse()
gr = RGBGradient((200, 800), (1, 0, 0), (0, 0, 1))
c.add_plotter(LinePlotter(TMP, TMP, gradient=gr, gradient_i=1, symbol=BaseSymbol, linepattern="2 2 8 2"))
c.add_plotter(ScatterPlotter(TMP, TMP2, symbol=BaseSymbol, gradient=gr, gradient_i=0))
c.add_plotter(CrossHairPlotter(500, 500))
c.add_plotter(CrossHairPlotter(200, 700, color="red"))
c.add_plotter(XLimitPlotter(300))
c.add_plotter(YLimitPlotter(300))
c.add_plotter(CrossHairPlotter(1e6, 1e6))
c.add_plotter(ScatterPlotter([1000], [1000], symbol=CrossHairSymbol, color="lime"))
c.add_plotter(LinkBox((100, 100, 10000, 10000), "http://www.slashdot.org"))
'''
Some tests of the rasterized fallback mode.
'''
import sys
import random
from brp.svg.base import SVGCanvas
from brp.svg.base import PlotContainer
from brp.svg.plotters.scatter import ScatterPlotter
from brp.svg.plotters.error import ErrorPlotter
from brp.svg.plotters.symbol import RADECSymbol, SquareSymbol
from brp.svg.plotters.line import LinePlotter
if __name__ == '__main__':
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)
def render(self, context):
qs = context[self.var_name]
tmp = StringIO.StringIO()
cv = SVGCanvas(940, 550, background_color='white')
P = [c.p_bary for c in qs.all() if c.best_dm > 0]
DM = [c.best_dm for c in qs.all() if c.best_dm > 0]
REDCHISQ = [c.reduced_chi_sq for c in qs.all() if c.best_dm > 0]
LINKS = [
reverse('bestprof_detail', args=[c.pk]) for c in qs.all()
if c.best_dm > 0
]
RA = [c.ra_deg for c in qs.all() if c.best_dm > 0]
DEC = [c.dec_deg for c in qs.all() if c.best_dm > 0]
if P:
max_redchisq = max(REDCHISQ)
min_redchisq = min(REDCHISQ)
# Main panel showing candidate period-DM scatter plot:
pc = PlotContainer(0,
-20,
880,
550,
color='black',
x_log=True,
y_log=True,
data_background_color='gray')
pc.bottom.set_label('Period (ms)')
pc.top.hide_label()
pc.left.set_label('Dispersion Measure (cm^-3 pc)')
pc.right.hide_label()
gr = RGBGradient((min_redchisq, max_redchisq), (0, 0, 1),
(1, 0, 0))
scp = ScatterPlotter(P,
DM,
RA,
DEC,
REDCHISQ,
gradient=gr,
gradient_i=4,
links=LINKS,
symbol=RADECSymbol)
pc.add_plotter(scp)
cv.add_plot_container(pc)
# Gradient:
pc = PlotContainer(820,
-20,
120,
550,
color='black',
data_padding=0)
pc.top.hide_label()
pc.top.hide_tickmarks()
pc.left.hide_tickmarks()
pc.bottom.hide_label()
pc.bottom.hide_tickmarks()
pc.left.hide_label()
pc.right.set_label('Candidate Reduced Chi-Square')
pc.add_plotter(GradientPlotter(copy.deepcopy(scp.gradient)))
cv.add_plot_container(pc)
# write number of candidates shown:
tf = TextFragment(50,
520,
'(Showing %d candidates.)' % len(P),
color='black',
font_size=15)
cv.add_plot_container(tf)
else:
tf = TextFragment(200,
200,
'No Candidates found.',
color='red',
font_size=50)
cv.add_plot_container(tf)
cv.draw(tmp)
return tmp.getvalue()
'''
from __future__ import division
import sys
from random import random as r
from brp.svg.base import SVGCanvas, PlotContainer
from brp.svg.plotters import newhist2d
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))
'%.2f ms' % bpf.header.p_bary[0], alignment='start',
font_size=TEXTSIZE))
cv.add_plot_container(TextFragment(x + width,
y + height + 2 * TEXTSIZE, '%.3f pc cm^-3' % bpf.header.best_dm,
alignment='end', font_size=TEXTSIZE))
files = os.listdir(sys.argv[1])
tmp = []
for f in files:
if f.endswith('.bestprof'):
try:
bpf = BestprofFile(os.path.join(sys.argv[1], f))
except:
print 'There was a problem reading %s' % os.path.join(sys.argv[1], f)
else:
tmp.append(bpf)
tmp.sort(key=lambda x: x.header.reduced_chi_sq)
tmp.reverse()
cv = SVGCanvas(1140, 1240)
N_HORIZONTAL = 5
N_VERTICAL = 10
for ix in range(N_HORIZONTAL):
for iy in range(N_VERTICAL):
try:
plot_profile(cv, 220 * ix + 20, 140 * iy + 20, 200, 100, tmp[ix + N_HORIZONTAL * iy], psr_name='B0000+0000')
except IndexError, e:
pass
cv.draw('test234.xml')
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)
files = os.listdir(sys.argv[1])
tmp = []
for f in files:
if f.endswith('.bestprof'):
try:
bpf = BestprofFile(os.path.join(sys.argv[1], f))
except:
print 'There was a problem reading %s' % os.path.join(
sys.argv[1], f)
else:
tmp.append(bpf)
tmp.sort(key=lambda x: x.header.reduced_chi_sq)
tmp.reverse()
cv = SVGCanvas(1140, 1240)
N_HORIZONTAL = 5
N_VERTICAL = 10
for ix in range(N_HORIZONTAL):
for iy in range(N_VERTICAL):
try:
plot_profile(cv,
220 * ix + 20,
140 * iy + 20,
200,
100,
tmp[ix + N_HORIZONTAL * iy],
psr_name='B0000+0000')
except IndexError, e:
pass
cv.draw('test234.xml')