added frolov to gaus2d

Author: Vlad-Kor

model/distributions/gaus2d/gaus2d.py

@@ -3,15 +3,15 @@
 import dash
 import pandas
 from urllib.error import HTTPError
-from dash import dcc, html, Input, Output, callback, Patch, ctx, no_update
+from dash import dcc, html, Input, Output, callback, Patch, ctx, no_update, State
 import plotly.graph_objects as go
 import dash_bootstrap_components as dbc
 import numpy as np
 from numpy import sqrt, linspace, vstack, hstack, pi, nan, full, exp, square, arange, array, sin, cos, diff, matmul, log10, deg2rad, identity, ones, zeros, diag, cov, mean
 from numpy.random import randn, randint
 from numpy.linalg import cholesky, eig, det, inv
 from scipy.special import erfinv
-
+import deterministic_gaussian_sampling_fibonacci as dgsf
 
 from components.popup_box import PopupBox
 from model.selfcontained_distribution import SelfContainedDistribution
@@ -33,7 +33,7 @@ def get_data(url):
 
 class Gaus2D(SelfContainedDistribution):
 	def __init__(self):
-		self.smethods = ['iid', 'Fibonacci', 'LCD', 'SP-Julier04', 'SP-Menegaz11'] # Sampling methods
+		self.smethods = ['iid', 'Fibonacci', 'LCD', 'SP-Julier04', 'SP-Menegaz11', 'Classical Frolov', 'Improved Frolov', 'Fibonacci Frolov'] # Sampling methods
 		self.tmethods = ['Cholesky', 'Eigendecomposition'] # Transformation methods
 
 		# Colors
@@ -116,6 +116,8 @@ def __init__(self):
 								value=self.smethods[randint(len(self.smethods))],
 								inline=True),
 
+					html.Br(),
+
 					# Transformation Method RadioItems
 					dbc.RadioItems(id='gauss2D-tmethod',
 								options=[{"label": x, "value": x} for x in self.tmethods],
@@ -173,27 +175,39 @@ def _register_callbacks(self):
 			Output('gauss2D-p', 'step'),
 			Output('gauss2D-p', 'tooltip'),
 			Output('gauss2D-L', 'disabled'),
+			Output('gauss2D-tmethod', 'className'),
+			Output('gauss2D-p', 'className'), # to hide when not needed
 			Input("gauss2D-smethod", "value"),
 		)
 		def update_smethod(smethod):
 			patched_tooltip = Patch()
+			patched_tooltip.always_visible = True
 			match smethod:
 				case 'iid':
 					patched_tooltip.template = "dice"
 					# min, max, value, step, tooltip
-					return 0, 1, .5, 0.001, patched_tooltip, False
+					return 0, 1, .5, 0.001, patched_tooltip, False, 'visible', 'visible'
 				case 'Fibonacci':
 					patched_tooltip.template = "z={value}"
-					return -50, 50, 0, 1, patched_tooltip, False
+					return -50, 50, 0, 1, patched_tooltip, False, 'visible', 'visible'
 				case 'LCD':
 					patched_tooltip.template = "α={value}°"
-					return -360, 360, 0, 0.1, patched_tooltip, False
+					return -360, 360, 0, 0.1, patched_tooltip, False, 'visible', 'visible'
 				case 'SP-Julier04':
 					patched_tooltip.template = "W₀={value}"
-					return -2, 1, .1, 0.001, patched_tooltip, True
+					return -2, 1, .1, 0.001, patched_tooltip, True, 'visible', 'visible'
 				case 'SP-Menegaz11':
 					patched_tooltip.template = "Wₙ₊₁={value}"
-					return 0, 1, 1/3, 0.001, patched_tooltip, True
+					return 0, 1, 1/3, 0.001, patched_tooltip, True, 'visible', 'visible'
+				case 'Classical Frolov':
+					patched_tooltip.always_visible = False
+					return no_update, no_update, no_update, no_update, patched_tooltip, False, 'invisible', 'invisible'
+				case 'Improved Frolov':
+					patched_tooltip.always_visible = False
+					return no_update, no_update, no_update, no_update, patched_tooltip, False, 'invisible', 'invisible'
+				case 'Fibonacci Frolov':
+					patched_tooltip.always_visible = False
+					return no_update, no_update, no_update, no_update, patched_tooltip, False, 'invisible', 'invisible'
 				case _:
 					raise Exception("Wrong smethod")
 
@@ -214,6 +228,8 @@ def update_smethod(smethod):
 			Input("angle", "value"),
 		)
 		def update(smethod, tmethod, p, L0, sigma_x, sigma_y, rho, angle):
+			if smethod in ['Classical Frolov', 'Improved Frolov', 'Fibonacci Frolov']:
+				tmethod = None
 			trig = ctx.triggered_id
 
 			def _rot2d(angle_deg):
@@ -298,17 +314,28 @@ def _rot2d(angle_deg):
 					# x1 = CC / sqrt(W1)
 					xySND = hstack((x0, x1))
 					weights = hstack((p, w1))
+				case 'Classical Frolov' | 'Improved Frolov' | 'Fibonacci Frolov':
+					method = smethod.replace(' ', '')
+					method = 'Fibonacci' if method == 'FibonacciFrolov' else method
+					if L > 0:
+						samples = dgsf.sample_gaussian_fibonacci(μ.flatten(), C, L, method)
+					else:
+						samples = np.empty((L, 2))
+					xyG = samples.T
+					
 				case _:
 					raise Exception("Wrong smethod")
 			match tmethod:
 				case 'Cholesky':
 					xyG = matmul(cholesky(C), xySND) + μ
 				case 'Eigendecomposition':
 					xyG = matmul(C_R, sqrt(C_D) * xySND) + μ
+				case None:
+					pass
 				case _:
 					raise Exception("Wrong smethod")
 			# Sample weights to scatter sizes
-			L2 = xySND.shape[1]  # actual number of saamples
+			L2 = xySND.shape[1] if tmethod is not None else xyG.shape[1]  # actual number of saamples
 			if L2 == 0:
 				sizes = 10
 			else: