def plot_gaussians(self, params):
plt.subplot(211)
plt.cla()
# Re-plot the original profile
plt.plot(self.phases, self.profile, c='black', lw=3, alpha=0.3)
plt.xlabel('Pulse Phase')
plt.ylabel('Pulse Amplitude')
DC = params[0]
# Plot the individual gaussians
for ii in range(self.numgaussians):
phase, FWHM, amp = params[1+ii*3:4+ii*3]
plt.plot(self.phases, DC + amp*gaussian_profile(self.proflen, phase, FWHM))
def gen_gaussians(params, N):
"""
gen_gaussians(params, N):
Return a model of a DC-component + M gaussians
params is a sequence of 1+M*3 values
the first value is the DC component. Each remaining
group of three represents the gaussians phase (0-1),
FWHM (0-1), and amplitude (>0.0).
N is the number of points in the model.
"""
numgaussians = (len(params)-1) // 3
model = Num.zeros(N, dtype='d') + params[0]
for ii in range(numgaussians):
phase, FWHM, amp = params[1+ii*3:4+ii*3]
model += amp * gaussian_profile(N, phase, FWHM)
return model
else:
fold_pfd.subfreqs = Num.asarray([0.0])
sumsubfreqs = Num.asarray([0.0])
sumsubdelays = Num.asarray([0.0])
subdelays2 = Num.asarray([0.0])
sumsubdelays_phs = Num.asarray([0.0])
# Read the template profile
if templatefilenm is not None:
template = psr_utils.read_profile(templatefilenm, normalize=1)
else:
if (gaussfitfile):
template = psr_utils.read_gaussfitfile(gaussfitfile, fold_pfd.proflen)
else:
template = psr_utils.gaussian_profile(fold_pfd.proflen, 0.0, gaussianwidth)
template = template / max(template)
#from Pgplot import *
#plotxy(template)
#closeplot()
# Determine the Telescope used
if (not fold.topo):
obs = '@' # Solarsystem Barycenter
else:
try:
if t2format:
obs = scopes2[fold_pfd.telescope.split()[0]]
else:
obs = scopes[fold_pfd.telescope.split()[0]]
except KeyError: sys.stderr.write("Unknown telescope!!! : " + fold_pfd.telescope)
print("Creating a summed profile of length %d bins using DM = %f" %
(numbins, DM))
# Read the template profile or create an appropriate Gaussian
if templatefilenm is not None:
template = psr_utils.read_profile(templatefilenm)
# Resample the template profile to have the correct number of bins (if required)
if not len(template) == numbins:
oldlen = len(template)
template = sinc_interp.periodic_interp(template, numbins)[::oldlen]
else:
if gaussfitfile is not None:
template = psr_utils.read_gaussfitfile(gaussfitfile, numbins)
else:
template = psr_utils.gaussian_profile(numbins, 0.0, gaussianwidth)
# Normalize it
template -= min(template)
template /= max(template)
# Rotate it so that it becomes a "true" template according to FFTFIT
shift, eshift, snr, esnr, b, errb, ngood = measure_phase(
template, template)
template = psr_utils.fft_rotate(template, shift)
# Determine the off-pulse bins
if bkgd_vals is not None:
Pgplot.plotxy(template, labx="Phase bins")
Pgplot.plotxy(template[bkgd_vals],
Num.arange(numbins)[bkgd_vals],
line=None,
symbol=2,
from __future__ import print_function
#>>> print fftfit.__doc__
#This module 'fftfit' is auto-generated with f2py (version:2.13.175-1250).
#Functions:
# zbrent = zbrent(x1,x2,f1,f2,tol,tmp,pha,nsum)
# dchisqr = dchisqr(tau,tmp,r,nsum)
# cprof(y,c,amp,pha,nmax=len(y),nh=(len(c)-1))
# fccf(amp,pha,shift)
# ffft(d,npts,isign,ireal)
# fftfit(prof,s,phi,nmax,shift,eshift,snr,esnr,b,errb,ngood)
import numpy as num
from presto.psr_utils import gaussian_profile, TWOPI
from presto.fftfit import cprof, fftfit
template = gaussian_profile(64, 0.5, 0.1)
c, amp, pha = cprof(template)
#pha.savespace()
pha1 = pha[0]
pha = num.fmod(pha - num.arange(1, len(pha) + 1) * pha1, TWOPI)
for phs in [0.1, 0.3, 0.7]:
prof = gaussian_profile(64, phs, 0.1) + num.random.standard_normal(64)
shift, eshift, snr, esnr, b, errb, ngood = fftfit(prof, amp, pha)
print("True phs = %f, measured phs = %f +/- %f" %
(phs, shift / len(prof), eshift / len(prof)))
