refactor: Update procedures class names

Author: Ангелина

src/procedures/__init__.py

@@ -1,45 +1,45 @@
 from src.procedures.semiparametric.nm_semi_param_algorithms.g_estimation_convolution import (
-    NMSemiParametricGEstimation,
+    NMEstimationDensityInvMT,
 )
 from src.procedures.semiparametric.nm_semi_param_algorithms.sigma_estimation_eigenvalue_based import (
-    SemiParametricMeanSigmaEstimationEigenvalueBased,
+    NMEstimationSigmaEigenvals,
 )
 from src.procedures.semiparametric.nm_semi_param_algorithms.sigma_estimation_empirical import (
-    SemiParametricMeanSigmaEstimationEmpirical,
+    NMEstimationSigmaLaplace,
 )
 from src.procedures.semiparametric.nv_semi_param_algorithms.g_estimation_given_mu import (
-    SemiParametricNVEstimation,
+    NVEstimationDensityInvMT,
 )
 from src.procedures.semiparametric.nv_semi_param_algorithms.g_estimation_post_widder import (
-    NVSemiParametricGEstimationPostWidder,
+    NMVEstimationDensityPW,
 )
 from src.procedures.semiparametric.nvm_semi_param_algorithms.g_estimation_given_mu import (
-    SemiParametricGEstimationGivenMu,
+    NMVEstimationDensityInvMTquad,
 )
 from src.procedures.semiparametric.nvm_semi_param_algorithms.g_estimation_given_mu_rqmc_based import (
-    SemiParametricGEstimationGivenMuRQMCBased,
+    NMVEstimationDensityInvMTquadRQMCBased,
 )
 from src.procedures.semiparametric.nvm_semi_param_algorithms.g_estimation_post_widder import (
     SemiParametricGEstimationPostWidder,
 )
-from src.procedures.semiparametric.nvm_semi_param_algorithms.mu_estimation import (SemiParametricMuEstimation)
+from src.procedures.semiparametric.nvm_semi_param_algorithms.mu_estimation import (NMVEstimationMu)
 from src.register.algorithm_purpose import AlgorithmPurpose
 from src.register.register import Registry
 
 ALGORITHM_REGISTRY: Registry = Registry()
-ALGORITHM_REGISTRY.register("mu_estimation", AlgorithmPurpose.NMV_SEMIPARAMETRIC)(SemiParametricMuEstimation)
+ALGORITHM_REGISTRY.register("mu_estimation", AlgorithmPurpose.NMV_SEMIPARAMETRIC)(NMVEstimationMu)
 ALGORITHM_REGISTRY.register("density_estim_inv_mellin_quad_int", AlgorithmPurpose.NMV_SEMIPARAMETRIC)(
-    SemiParametricGEstimationGivenMu
+    NMVEstimationDensityInvMTquad
 )
-ALGORITHM_REGISTRY.register("density_estim_deconv", AlgorithmPurpose.NM_SEMIPARAMETRIC)(NMSemiParametricGEstimation)
+ALGORITHM_REGISTRY.register("density_estim_deconv", AlgorithmPurpose.NM_SEMIPARAMETRIC)(NMEstimationDensityInvMT)
 ALGORITHM_REGISTRY.register("sigma_estimation_eigenvalue", AlgorithmPurpose.NM_SEMIPARAMETRIC)(
-    SemiParametricMeanSigmaEstimationEigenvalueBased
+    NMEstimationSigmaEigenvals
 )
 ALGORITHM_REGISTRY.register("sigma_estimation_laplace", AlgorithmPurpose.NM_SEMIPARAMETRIC)(
-    SemiParametricMeanSigmaEstimationEmpirical
+    NMEstimationSigmaLaplace
 )
 ALGORITHM_REGISTRY.register("density_estim_inv_mellin_rqmc_int", AlgorithmPurpose.NMV_SEMIPARAMETRIC)(
-    SemiParametricGEstimationGivenMuRQMCBased
+    NMVEstimationDensityInvMTquadRQMCBased
 )
 ALGORITHM_REGISTRY.register("density_estim_post_widder", AlgorithmPurpose.NMV_SEMIPARAMETRIC)(
     SemiParametricGEstimationPostWidder

src/procedures/semiparametric/nm_semi_param_algorithms/g_estimation_convolution.py

@@ -12,7 +12,7 @@
 X_DATA_DEFAULT_VALUE: List[float] = [1.0]
 
 
-class NMSemiParametricGEstimation:
+class NMEstimationDensityInvMT:
     """Estimation of mixing density function g (xi density function) of NM mixture
     represented in canonical form Y = xi + sigma*N.
 

src/procedures/semiparametric/nm_semi_param_algorithms/sigma_estimation_eigenvalue_based.py

@@ -14,7 +14,7 @@
 PARAMETER_KEYS = ["l", "k", "eps", "search_area", "search_density"]
 
 
-class SemiParametricMeanSigmaEstimationEigenvalueBased:
+class NMEstimationSigmaEigenvals:
     """Estimation of sigma parameter of NM mixture represented in canonical form Y = xi + sigma*N.
 
     Args:

src/procedures/semiparametric/nm_semi_param_algorithms/sigma_estimation_empirical.py

@@ -9,7 +9,7 @@
 PARAMETER_KEYS = ["t"]
 
 
-class SemiParametricMeanSigmaEstimationEmpirical:
+class NMEstimationSigmaLaplace:
     """Estimation of sigma parameter of NM mixture represented in canonical form Y = xi + sigma*N.
 
     Args:

src/procedures/semiparametric/nv_semi_param_algorithms/g_estimation_given_mu.py

@@ -30,7 +30,7 @@ def v_sequence_default_value(n: float) -> float:
 INTEGRATION_LIMIT_DEFAULT_VALUE: int = 50
 
 
-class SemiParametricNVEstimation:
+class NVEstimationDensityInvMT:
     """Estimation of mixing density function g (xi density function) of NV mixture represented in canonical form Y =
     alpha + sqrt(xi)*N, where alpha = 0 and mu = 0.
 

src/procedures/semiparametric/nv_semi_param_algorithms/g_estimation_post_widder.py

@@ -13,7 +13,7 @@
 X_DATA_DEFAULT_VALUE = [1.0]
 
 
-class NVSemiParametricGEstimationPostWidder:
+class NMVEstimationDensityPW:
     """Estimation of mixing density function g (xi density function) of NVM mixture represented in classical form Y =
     alpha + sigma*sqrt(xi)*N, where alpha = 0 and mu, sigma are given.
 

src/procedures/semiparametric/nvm_semi_param_algorithms/g_estimation_given_mu.py

@@ -31,7 +31,7 @@ def v_sequence_default_value(n: float) -> float:
 INTEGRATION_LIMIT_DEFAULT_VALUE: int = 50
 
 
-class SemiParametricGEstimationGivenMu:
+class NMVEstimationDensityInvMTquad:
     """Estimation of mixing density function g (xi density function) of NVM mixture represented in canonical form Y =
     alpha + mu*xi + sqrt(xi)*N, where alpha = 0 and mu is given.
 

src/procedures/semiparametric/nvm_semi_param_algorithms/g_estimation_given_mu_rqmc_based.py

@@ -32,7 +32,7 @@ def v_sequence_default_value(n: float) -> float:
 INTEGRATION_LIMIT_DEFAULT_VALUE: int = 50
 
 
-class SemiParametricGEstimationGivenMuRQMCBased:
+class NMVEstimationDensityInvMTquadRQMCBased:
     """Estimation of mixing density function g (xi density function) of NVM mixture represented in canonical form Y =
     alpha + mu*xi + sqrt(xi)*N, where alpha = 0 and mu is given.
 

src/procedures/semiparametric/nvm_semi_param_algorithms/mu_estimation.py

@@ -14,7 +14,7 @@
 PARAMETER_KEYS = ["m", "tolerance", "omega", "max_iterations"]
 
 
-class SemiParametricMuEstimation:
+class NMVEstimationMu:
     """Estimation of mu parameter of NVM mixture represented in canonical form Y = alpha + mu*xi + sqrt(xi)*N,
     where alpha = 0