def _plot_residuals(self, model, oplot=None, color='black'):
import hippoplotter as plot
resid = (self.col('nobs') - model) / model
resid_err = self.col('nobs_err') / model
energies = self.col('energy')
nt = plot.newNTuple((energies, resid, resid_err),
('energy', 'residuals', 'resid_err'))
if oplot and self.resids is not None:
plot.canvas.selectDisplay(self.resids)
rep = plot.XYPlot(nt,
'energy',
'residuals',
yerr='resid_err',
xlog=1,
oplot=1,
color=color)
rep.setSymbol('filled_square', 2)
else:
self.resids = plot.XYPlot(nt,
'energy',
'residuals',
yerr='resid_err',
xlog=1,
color=color,
yrange=(-1, 1))
self.resids.getDataRep().setSymbol('filled_square', 2)
plot.hline(0)
def plotResults(self, energy, inclination, ntrials=20, nsamp=100,
plot_residuals=False):
self._setPsf(energy, inclination)
self._setRoi(roiRadius=20)
nobs = []
nobserr = []
npreds = []
colnames = ('separation', 'Npred', 'Nobs', 'Nobserr', 'Nobs - Npred')
nt = plot.newNTuple( [[]]*len(colnames), colnames)
display = plot.Scatter(nt, 'separation', 'Npred', pointRep='Line')
display.setRange('y', 0, 1.1)
plot.XYPlot(nt, 'separation', 'Nobs', yerr='Nobserr',
color='red', oplot=1)
display.setRange('x', min(seps), max(seps))
display.setTitle("%s: %i MeV, %.1f deg" %
(self.irfs, self.energy, self.inc))
if plot_residuals:
resid_display = plot.XYPlot(nt, 'separation', 'Nobs - Npred',
yerr='Nobserr')
resid_display.setRange('x', min(seps), max(seps))
resid_display.setTitle("%s: %i MeV, %.1f deg" %
(self.irfs, self.energy, self.inc))
plot.hline(0)
resid_display.setAutoRanging('y', True)
for sep in self.seps:
nobs, nerr = self._SampleDist(sep)
npred = self._Npred(sep)
nt.addRow( (sep, npred, nobs, nerr, nobs-npred) )
return nt, display
return 1
indx = bisect.bisect(x, xval) - 1
yval = ((xval - x[indx]) / (x[indx + 1] - x[indx]) *
(y[indx + 1] - y[indx]) + y[indx])
return yval
if __name__ == '__main__':
seps = num.concatenate(
(num.arange(12, 19), num.arange(19, 21, 0.3), num.arange(21, 25)))
energies = (30, 100, 1000, 1e4)
# energies = (1e3, 3e3, 1e4, 3e4)
incs = (0, 10, 30)
nt = plot.newNTuple(([], [], []), ('energy', 'inc', 'ks prob'))
plot.Scatter(nt, 'energy', 'ks prob')
plot.Scatter(nt, 'inc', 'ks prob')
def createPlots(irfs, seps, energies, inclinations):
my_tests = PsfTests(irfs, seps)
for energy in energies:
for inclination in inclinations:
my_tests.plotResults(energy, inclination, plot_residuals=True)
nt.addRow(my_tests.plot_rspgenIntegral(energy, inclination))
# irfs = ('testIrfs::Front',) # 'testIrfs::Back')
## 'Glast25::Front', 'Glast25::Back',
## 'DC1::Front', 'DC1::Back')
# irfs = ('DC1A::Front', 'DC1A::Back')
time += dt
arrTimes.append(time)
energies.append(src.energy(time))
try:
l, b = src.dir(energies[-1])
except AttributeError:
l, b = 0, 0
glons.append(l)
glats.append(b)
return (num.array(arrTimes), num.array(energies), num.array(glons),
num.array(glats))
import hippoplotter as plot
nt = plot.newNTuple(generateData(my_src, 1e4),
('time', 'energy', 'glon', 'glat'))
plot.Histogram(nt, 'time', xrange=(0, 1e4))
spectrum = plot.Histogram(nt, 'energy', xlog=1, ylog=1)
plot.XYHist(nt, 'glon', 'glat')
@FunctionBaseDecorator
def f(e, e1=300, a=1, b=2, k=1):
return k * (e / e1)**(-(a + b * num.log(e / e1)))
spectrum.addFunction(f)
#nt2 = plot.newNTuple(generateData(grb_src, 3600),
# ('time', 'energy', 'glon', 'glat'))
#
import sys
sys.path.reverse()
sys.path.append('../python')
sys.path.append('../python')
sys.path.reverse()
from setPath import *
import hippoplotter as plot
from random import gauss, uniform
#
# Create new NTuple with columns (x, y, x^2 + y^2, uniform deviate, index)
#
nt = plot.newNTuple( ([], [], [], [], []), ("x", "y", "z", "unif", "i") )
hist = plot.Histogram( nt, "x" )
xyhist = plot.XYHist( nt, "x", "y" )
profile = plot.Profile( nt, "x", "z" )
mean = 0.
sigma = 1.
npts = 25000
nt.setIntervalCount ( 1000 )
nt.setIntervalEnabled ( 1 )
for i in range(npts):
x, y = gauss(mean, sigma), gauss(mean, sigma)
z = x*x + y*y
nt.addRow( (x, y, z, uniform(0,1), i) )