Class
NumCosmoMathPowspecFilter
Description [src]
final class NumCosmoMath.PowspecFilter : GObject.Object
{
/* No available fields */
}Class to compute filtered power spectrum.
This class computes the filtered power spectrum, $\sigma^2(k, r)$, and its derivatives with respect to $\ln r$
(#ncm_powspec_filter_eval_dnvar_dlnrn()) using the FFTLog approach (see NcmFftlog),
\begin{equation}\label{eq:variance}
\sigma^2(r, z) = \frac{1}{2\pi^2} \int_0^\infty k^2 \ P(k, z) \vert W(k,r) \vert^2 \ \mathrm{d}k,
\end{equation}
where $P(k, z)$ is the power spectrum at mode $k$ and redshift $z$ and $W(k, r)$ is the filter (or window function).
Functions
ncm_powspec_filter_clear
If psf is different from NULL,
atomically decrements the reference count of psf by one.
If the reference count drops to 0,
all memory allocated by psf is released and psf is set to NULL.
Instance methods
ncm_powspec_filter_eval_dlnvar_dlnr
Evaluates the first derivative of the logarithm of the filtered
variance with respect to $\ln r$ at lnr and z.
ncm_powspec_filter_eval_dlnvar_dr
Evaluates the first derivative of the logarithm of the filtered
variance with respect to $r$ at lnr and z.
ncm_powspec_filter_eval_dnlnvar_dlnrn
Evaluates the derivatives of the logarithm of the filtered variance at lnr and z, namely:
- $n = 0 \rightarrow \ln \left[ \sigma(r, z)^2 \right]$,
- $n = 1 \rightarrow \frac{\mathrm{d}\ln \left( \sigma^2 \right)}{\mathrm{d} \ln r}$,
- $n = 2 \rightarrow \frac{\mathrm{d}^2 \ln \left( \sigma^2 \right)}{\mathrm{d}(\ln r)^2}$,
- $n = 3 \rightarrow \frac{\mathrm{d}^3 \ln \left( \sigma^2 \right)}{\mathrm{d}(\ln r)^3}$.
ncm_powspec_filter_eval_dnvar_dlnrn
Evaluates the derivatives of the filtered variance at lnr and z, namely:
- $n = 0 \rightarrow \sigma(r, z)^2$,
- $n = 1 \rightarrow \frac{\mathrm{d}\sigma^2}{\mathrm{d} \ln r}$,
- $n = 2 \rightarrow \frac{\mathrm{d}^2\sigma^2}{\mathrm{d}(\ln r)^2}$,
- $n = 3 \rightarrow \frac{\mathrm{d}^3\sigma^2}{\mathrm{d}(\ln r)^3}$.
ncm_powspec_filter_eval_dvar_dlnr
Evaluates the first derivative of the filtered
variance with respect to $\ln r$ at lnr and z.
ncm_powspec_filter_eval_lnvar_lnr
Evaluates the logarithm base e of the filtered power spectrum at lnr and z.
ncm_powspec_filter_eval_sigma_lnr
Evaluate the square root of the filtered power spectrum at lnr and z.
ncm_powspec_filter_free
Atomically decrements the reference count of psf by one.
If the reference count drops to 0, all memory allocated by psf is released.
ncm_powspec_filter_get_reltol
Gets the relative tolerance for calibration in the distance direction.
ncm_powspec_filter_get_reltol_z
Gets the relative tolerance for calibration in the redshift direction.
ncm_powspec_filter_peek_powspec
Gets the NcmPowspec object used to compute the filtered variance $\sigma^{2}(r,z)$.
ncm_powspec_filter_prepare_if_needed
Prepares (if necessary) the object applying the filter to the power spectrum.
ncm_powspec_filter_set_best_lnr0
Sets the value of $\ln(r_0)$ which gives the best results for the transformation based on the current value of $\ln(k_0)$.
ncm_powspec_filter_set_lnr0
Sets the center of the transform output $\ln(r_0)$ (see ncm_fftlog_set_lnr0()).
ncm_powspec_filter_set_reltol
Sets the relative tolerance for calibration in the distance direction.
ncm_powspec_filter_set_reltol_z
Sets the relative tolerance for calibration in the redshift direction.
Properties
NumCosmoMath.PowspecFilter:powerspectrum
The NcmPowspec object to be used to compute the variance $\sigma^{2}(r,z)$.
NumCosmoMath.PowspecFilter:reltol-z
The relative tolerance for calibration in the redshift direction.
Signals
Signals inherited from GObject (1)
GObject::notify
The notify signal is emitted on an object when one of its properties has its value set through g_object_set_property(), g_object_set(), et al.