Remove temp data and scripts used in debugging

dataCollectedFrom20Rounds.sl

-(constraint (inShape  26.6152701008448 0.9678239104943458 0.21114638865049587 2.345564365386963 (- 0.14508944749832153)))
-(constraint (inShape  26.61529433389539 0.967828326685563 0.21114590159461266 2.4930434226989746 (- 0.1531599760055542)))
-(constraint (inShape  26.61534953561334 0.9678393284980444 0.21114628135388033 2.510728359222412 (- 0.15152986347675323)))
-(constraint (inShape  19.375177724969767 0.967824356037088 0.21114631866326478 3.4791932106018066 (- 0.22473394870758057)))
-(constraint (inShape  19.37517508326423 0.9678238569539328 0.21114658296554917 3.5184550285339355 (- 0.22579112648963928)))
-(constraint (inShape  19.375182233263544 0.967825497133969 0.21114633517139236 3.5097079277038574 (- 0.2239835113286972)))
-(constraint (inShape  19.37518834132608 0.9678268184284384 0.21114626941534817 3.5298871994018555 (- 0.22639496624469757)))
-(constraint (inShape  10.235571424573456 0.9678239111315996 0.21114638837361643 3.438933849334717 (- 0.21554206311702728)))
-(constraint (inShape  10.235571539824214 0.9678240672511116 0.21114626519871993 3.436929702758789 (- 0.21290093660354614)))
-(constraint (inShape  10.235574707144886 0.9678247544784639 0.21114635158339712 3.445437431335449 (- 0.21383893489837646)))
-(constraint (inShape  10.235580857800862 0.9678260840358703 0.21114631984957144 3.4564030170440674 (- 0.21499930322170258)))
-(constraint (inShape  3.8539052024320735 0.9678239099543191 0.21114638869176813 1.4183670282363892 (- 0.09801661968231201)))
-(constraint (inShape  3.8539075220129626 0.9678245456809051 0.2111461465021146 1.60621976852417 (- 0.11350981146097183)))
-(constraint (inShape  3.8539106462580315 0.9678252255298361 0.21114641134134055 1.6671497821807861 (- 0.11667919158935547)))
-(constraint (inShape  3.853916709485315 0.9678265364059513 0.2111463338846634 2.38948392868042 (- 0.1834786981344223)))
-(constraint (inShape  2.148526343357085 0.9678239101001935 0.21114638873517305 3.5696678161621094 (- 0.2203296720981598)))
-(constraint (inShape  2.148528512694049 0.9678245109850732 0.21114624022727377 3.563772678375244 (- 0.21956664323806763)))
-(constraint (inShape  2.148531637917875 0.9678251862298772 0.2111463826103695 3.5739736557006836 (- 0.22020605206489563)))
-(constraint (inShape  2.1485376981887327 0.9678264979904956 0.2111463365188309 3.59548282623291 (- 0.2222861349582672)))
-(constraint (inShape  30.64333925200089 0.9678237509999992 0.211146388 3.3627007007598877 (- 0.2056111842393875)))
-(constraint (not (inShape  (- 0.13435869420323682) (- 1.899551057941262) (- 0.28484593314155127) 0.0 0.0)))
-(constraint (not (inShape  (- 0.1357230736889143) (- 0.06896000765390979) (- 0.22565356332402542) (- 0.13792001530781958) 0.0)))
-(constraint (not (inShape  0.031336154284762455 (- 0.6144592699844698) 1.485540123743981 2.0 0.0)))
-(constraint (not (inShape  (- 0.13404045455201255) 2.0 (- 0.31717354626777816) 2.0 0.6343470925355563)))
-(constraint (not (inShape  0.054857568457900144 (- 1.7840911757006543) (- 1.3634267523794492) 2.0 (- 0.9427623290582445))))
-(constraint (not (inShape  0.08020144441406736 (- 0.1386182570450704) (- 1.5707963267948966) 2.0 (- 1.2772365140901407))))
-(constraint (not (inShape  0.08020144441406737 1.1247414813760792 (- 1.5707963267948966) 2.0 (- 1.2494829627521584))))
-(constraint (not (inShape  0.07880745577985629 1.9509699384018293 (- 1.5587035427760474) (- 1.1174070855520948) (- 1.0))))
-(constraint (not (inShape  (- 0.12497763257869772) (- 0.02210191139819711) (- 0.23609212684430714) 1.5278157463113857 (- 0.4721842536886143))))
-(constraint (not (inShape  (- 0.02352354216660577) 2.0 1.3555842891942411 0.2888314216115177 0.0)))
-(constraint (not (inShape  (- 0.12238683784721333) (- 0.03674154677771748) (- 0.1983859678838836) (- 1.983859678838836) 0.0)))
-(constraint (not (inShape  (- 0.040430820847654904) 0.0 0.6678319322055949 0.0 0.6643361355888102)))
-(constraint (not (inShape  (- 0.12031953894476077) 0.0 0.02539164591081542 2.0 (- 0.8730417704459228))))
-(constraint (not (inShape  (- 0.1103297666085696) 2.0 0.411967253854291 2.0 (- 0.05983626927145515))))
-(constraint (not (inShape  0.0 0.5076765232177733 (- 1.0227481658397863) 2.0 (- 0.9846469535644533))))
-(constraint (not (inShape  (- 0.11974449498937859) 0.23016658550473063 (- 0.06536763447759253) 1.9346323655224076 1.5396668289905389)))
-(constraint (not (inShape  0.08020144441406735 0.7075142733814768 (- 1.5707963267948966) (- 0.15576778003194303) (- 0.5849714532370465))))
-(constraint (not (inShape  0.08005426932065733 0.5695169602836916 (- 1.5695169602836918) (- 2.0) (- 0.8609660794326169))))
-(constraint (not (inShape  0.08020144441406735 1.451479337228988 (- 1.5707963267948966) (- 0.23863397913181705) (- 0.9029586744579761))))
-(constraint (not (inShape  (- 0.13373748526757237) 1.9998255257227473 (- 0.30976749003865545) 0.0 0.6195349800773109)))

plot_abstractions.py

-from typing import List, Tuple
-
-import numpy as np
-import matplotlib.pyplot as plt
-
-
-def plot_dtree_abs(state: np.ndarray, dnf: List[Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]]):
-    d_lim = 2.0  # PRE_Y_LIM
-    psi_lim = np.pi/3  # PRE_YAW_LIM
-    d_space = np.linspace(-d_lim, d_lim, 800)
-    psi_space = np.linspace(-psi_lim, psi_lim, 800)
-    d, psi = np.meshgrid(d_space, psi_space)
-
-    disjunct_bool_arr = np.zeros((len(d_space)*len(psi_space),))
-    for a_mat, b_vec, coeff_mat, cut_vec in dnf:
-        center = a_mat @ state + b_vec
-        dbar = d - center[0]
-        psibar = psi - center[1]
-        v_arr = np.dot(coeff_mat, [dbar.ravel(), psibar.ravel()])
-        bool_arr = np.all(v_arr.T <= cut_vec, axis=1)
-        disjunct_bool_arr = np.logical_or(disjunct_bool_arr, bool_arr)
-
-    disjunct_bool_arr = disjunct_bool_arr.reshape(d.shape)
-    im = plt.imshow(disjunct_bool_arr.astype(int),
-                    extent=(d.min(), d.max(), psi.min(), psi.max()),
-                    aspect="auto",
-                    origin="lower", cmap="Greens")
-
-    plt.savefig("temp.png")
-
-
-def plot_sygus_abs():
-    pass
-
-
-state = np.array([0., 0., 0.])
-
-a_mat_0 = np.array([[0., -1., 0.],
-                    [0., 0., -1.]])
-b_vec_0 = np.zeros(2)
-coeff_mat_0 = np.array(
-    [[1., 1.],
-     [-1., 0.],
-     [0., 1.],
-     [1., -1.]])
-
-coeff_mat_1 = np.array(
-    [[1., 0.],
-     [-1., 0.],
-     [0., 1.],
-     [0., -1.]])
-
-cut_vec_0 = np.array(
-    [0.5, 0.5, 0.75, 0.75])
-
-candidate_dnf_0 = [
-    # (a_mat_0, b_vec_0, coeff_mat_0, cut_vec_0),
-    (a_mat_0, b_vec_0, coeff_mat_1, cut_vec_0)
-]
-plot_dtree_abs(state, candidate_dnf_0)