diff options
Diffstat (limited to 'fg21sim/extragalactic')
| -rw-r--r-- | fg21sim/extragalactic/clusters/emission.py | 44 |
1 files changed, 22 insertions, 22 deletions
diff --git a/fg21sim/extragalactic/clusters/emission.py b/fg21sim/extragalactic/clusters/emission.py index 2454644..b54d113 100644 --- a/fg21sim/extragalactic/clusters/emission.py +++ b/fg21sim/extragalactic/clusters/emission.py @@ -103,16 +103,17 @@ class SynchrotronEmission: nu_c = 1.5 * gamma**2 * np.sin(theta) * self.frequency_larmor return nu_c - @staticmethod - def F(x): + def F(self, x): """ Synchrotron kernel function. NOTE ---- - Use interpolation to optimize the speed, also avoid instabilities - near the lower end (e.g., x < 1e-5). - Interpolation also helps vectorize this function for easier calling. + * Use interpolation to optimize the speed, also avoid instabilities + near the lower end (e.g., x < 1e-5). + * Interpolation also helps vectorize this function for easier calling. + * Cache the interpolation results, since this function will be called + multiple times for each frequency. Parameters ---------- @@ -125,27 +126,26 @@ class SynchrotronEmission: y : `~numpy.ndarray` Calculated kernel function values. """ - # The lower and upper cuts - xmin = 1e-5 - xmax = 20.0 - # Number of samples within [xmin, xmax] - # NOTE: this kernel function is quiet smooth and slow-varying. - nsamples = 128 - # Make an interpolation - x_interp = np.logspace(np.log10(xmin), np.log10(xmax), - num=nsamples) - F_interp = [ - xp * integrate.quad(lambda t: scipy.special.kv(5/3, t), - a=xp, b=np.inf)[0] - for xp in x_interp - ] - func_interp = interpolate.interp1d(x_interp, F_interp, - kind="quadratic") + if not hasattr(self, "_F_interp"): + # Interpolate the kernel function and cache the results + # + # The lower and upper cuts + xmin = 1e-5 + xmax = 20.0 + # Number of samples within [xmin, xmax] + # NOTE: this kernel function is quiet smooth and slow-varying. + nsamples = 128 + # Make an interpolation + xx = np.logspace(np.log10(xmin), np.log10(xmax), num=nsamples) + Fxx = [xp * integrate.quad(lambda t: scipy.special.kv(5/3, t), + a=xp, b=np.inf)[0] + for xp in xx] + self._F_interp = interpolate.interp1d(xx, Fxx, kind="quadratic") x = np.array(x) # Make a copy! x[x < xmin] = xmin x[x > xmax] = xmax - y = func_interp(x) + y = self._F_interp(x) return y def emissivity(self, nu): |