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author | Aaron LI <aaronly.me@outlook.com> | 2016-06-25 16:10:13 +0800 |
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committer | Aaron LI <aaronly.me@outlook.com> | 2016-06-25 16:10:13 +0800 |
commit | df786c667ebb052155aa9b99b22d556ff42e5d50 (patch) | |
tree | 2195afd142d29b0d3eeeff517433e5bd80b6934e | |
parent | bff0094b7adde0459d4996b312c6b2b33f51124d (diff) | |
download | cexcess-df786c667ebb052155aa9b99b22d556ff42e5d50.tar.bz2 |
deproject_sbp.py: Use InterpolatedUnivariateSpline
-rwxr-xr-x | deproject_sbp.py | 28 |
1 files changed, 13 insertions, 15 deletions
diff --git a/deproject_sbp.py b/deproject_sbp.py index ce6ad8d..313e586 100755 --- a/deproject_sbp.py +++ b/deproject_sbp.py @@ -2,9 +2,11 @@ # # Weitian LI # Created: 2016-06-10 -# Updated: 2016-06-24 +# Updated: 2016-06-25 # # Change logs: +# 2016-06-25: +# * Use 'InterpolatedUnivariateSpline' instead of 'interp1d' # 2016-06-24: # * Move class 'ChandraPixel' to module 'astro_params.py' # * Split class 'Projection' to a separate module 'projection.py' @@ -151,8 +153,8 @@ from collections import OrderedDict import astropy.units as au import numpy as np import pandas as pd -import scipy.optimize -import scipy.interpolate +import scipy.optimize as optimize +import scipy.interpolate as interpolate import lmfit import matplotlib.pyplot as plt from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas @@ -449,10 +451,10 @@ class DeprojectSBP: em0 = self.projector.deproject(self.s) # scale the EM data to reduce the dynamical range em0_scaled = self.scale_data(em0, update_params=True) - res = scipy.optimize.minimize(fun=fobj, x0=em0_scaled, - method=opt_method, - callback=callback, - options={"disp": True}) + res = optimize.minimize(fun=fobj, x0=em0_scaled, + method=opt_method, + callback=callback, + options={"disp": True}) self.deproject_res = res self.em = self.unscale_data(res.x) return self.em @@ -881,15 +883,11 @@ class BrightnessProfile: projector = Projection(rout=self.r+self.r_err) s_deproj = projector.deproject(self.s) # allow extrapolation - # XXX: cubic spline / smooth spline better ?? - cf_interp = scipy.interpolate.interp1d(x=self.cf_radius, - y=self.cf_value, - kind="linear", - bounds_error=False, - fill_value=self.cf_value[-1], - assume_sorted=True) + # XXX: smooth spline better ?? + cf_spline = interpolate.InterpolatedUnivariateSpline( + x=self.cf_radius, y=self.cf_value, ext="const") # emission measure per unit volume - em_v = s_deproj / cf_interp(self.r) + em_v = s_deproj / cf_spline(self.r) ne = np.sqrt(em_v * AstroParams.ratio_ne_np) self.ne = ne # save results to output if specified |