@@ -46,14 +46,15 @@ def InformedRRTStarSearch(self, animation=True):
4646 # Computing the sampling space
4747 cMin = math .sqrt (pow (self .start .x - self .goal .x , 2 ) +
4848 pow (self .start .y - self .goal .y , 2 ))
49- xCenter = np .matrix ([[(self .start .x + self .goal .x ) / 2.0 ],
50- [(self .start .y + self .goal .y ) / 2.0 ], [0 ]])
51- a1 = np .matrix ([[(self .goal .x - self .start .x ) / cMin ],
52- [(self .goal .y - self .start .y ) / cMin ], [0 ]])
49+ xCenter = np .array ([[(self .start .x + self .goal .x ) / 2.0 ],
50+ [(self .start .y + self .goal .y ) / 2.0 ], [0 ]])
51+ a1 = np .array ([[(self .goal .x - self .start .x ) / cMin ],
52+ [(self .goal .y - self .start .y ) / cMin ], [0 ]])
53+
5354 etheta = math .atan2 (a1 [1 ], a1 [0 ])
5455 # first column of idenity matrix transposed
55- id1_t = np .matrix ([1.0 , 0.0 , 0.0 ])
56- M = np . dot ( a1 , id1_t )
56+ id1_t = np .array ([1.0 , 0.0 , 0.0 ]). reshape ( 1 , 3 )
57+ M = a1 @ id1_t
5758 U , S , Vh = np .linalg .svd (M , 1 , 1 )
5859 C = np .dot (np .dot (U , np .diag (
5960 [1.0 , 1.0 , np .linalg .det (U ) * np .linalg .det (np .transpose (Vh ))])), Vh )
@@ -285,9 +286,9 @@ def plot_ellipse(self, xCenter, cBest, cMin, etheta):
285286 t = np .arange (0 , 2 * math .pi + 0.1 , 0.1 )
286287 x = [a * math .cos (it ) for it in t ]
287288 y = [b * math .sin (it ) for it in t ]
288- R = np .matrix ([[math .cos (angle ), math .sin (angle )],
289- [- math .sin (angle ), math .cos (angle )]])
290- fx = R * np .matrix ([x , y ])
289+ R = np .array ([[math .cos (angle ), math .sin (angle )],
290+ [- math .sin (angle ), math .cos (angle )]])
291+ fx = R @ np .array ([x , y ])
291292 px = np .array (fx [0 , :] + cx ).flatten ()
292293 py = np .array (fx [1 , :] + cy ).flatten ()
293294 plt .plot (cx , cy , "xc" )
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