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void | ncm_data_gauss_cov_set_size () |
guint | ncm_data_gauss_cov_get_size () |
void | ncm_data_gauss_cov_use_norma () |
void | ncm_data_gauss_cov_replace_mean () |
void | ncm_data_gauss_cov_set_cov () |
NcmVector * | ncm_data_gauss_cov_peek_mean () |
NcmMatrix * | ncm_data_gauss_cov_peek_cov () |
NcmMatrix * | ncm_data_gauss_cov_compute_cov () |
NcmVector * | ncm_data_gauss_cov_compute_mean () |
gdouble | ncm_data_gauss_cov_get_log_norma () |
void | ncm_data_gauss_cov_bulk_resample () |
GObject ╰── NcmData ╰── NcmDataGaussCov ├── NcDataBaoDHrDAr ├── NcDataBaoDMrHr ├── NcDataBaoDtrDHr ├── NcDataClusterNCountsGauss ├── NcDataSNIACov ├── NcDataXcor ╰── NcmDataGaussCovMVND
void ncm_data_gauss_cov_set_size (NcmDataGaussCov *gauss
,guint np
);
Sets the data size to np
.
[virtual set_size]
guint
ncm_data_gauss_cov_get_size (NcmDataGaussCov *gauss
);
Gets the data size.
[virtual get_size]
void ncm_data_gauss_cov_use_norma (NcmDataGaussCov *gauss
,gboolean use_norma
);
Sets whether the value of $-2\ln(L)$ will be properly normalized.
void ncm_data_gauss_cov_replace_mean (NcmDataGaussCov *gauss
,NcmVector *mean
);
Replaces the current mean vector for mean
.
void ncm_data_gauss_cov_set_cov (NcmDataGaussCov *gauss
,NcmMatrix *cov
);
Sets a NcmMatrix representing the covariance matrix in each bin.
NcmMatrix * ncm_data_gauss_cov_compute_cov (NcmDataGaussCov *gauss
,NcmMSet *mset
,gboolean *updated
);
Computes the covariance matrix based on the models in mset
. If
the “cov_func” is not set, returns NULL
.
NcmVector * ncm_data_gauss_cov_compute_mean (NcmDataGaussCov *gauss
,NcmMSet *mset
);
Computes the mean vector based on the models in mset
. If
the “mean_func” is not set, returns NULL
.
gdouble ncm_data_gauss_cov_get_log_norma (NcmDataGaussCov *gauss
,NcmMSet *mset
);
void ncm_data_gauss_cov_bulk_resample (NcmDataGaussCov *gauss
,NcmMSet *mset
,NcmMatrix *resample
,NcmRNG *rng
);
Resamples the data based on the models in mset
according to the current
data distribution. The resampled data is stored in resample
. The resampling
is done in bulk, i.e., all the data is resampled at once.