How to use test_projection method in Airtest

Best Python code snippet using Airtest Github


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...48 return best_theta, best_ratio, best_w, best_h, best_l49@jit(nopython=True)50def hill_climb(p2, p2_inv, box_2d, x2d, y2d, z2d, w3d, h3d, l3d, ry3d, step_r_init, r_lim=0.0,min_ol_dif=0.0):51 step_r = step_r_init52 ol_best = test_projection(p2, p2_inv, box_2d, x2d, y2d, z2d, w3d, h3d, l3d, ry3d)53 # attempt to fit z/rot more properly54 while (step_r > r_lim):55 if step_r > r_lim:56 ol_neg = test_projection(p2, p2_inv, box_2d, x2d, y2d, z2d, w3d, h3d, l3d, ry3d - step_r)57 ol_pos = test_projection(p2, p2_inv, box_2d, x2d, y2d, z2d, w3d, h3d, l3d, ry3d + step_r)58 59 invalid = ((ol_pos - ol_best) <= min_ol_dif) and ((ol_neg - ol_best) <= min_ol_dif)60 if invalid:61 step_r = step_r * 0.562 elif (ol_pos - ol_best) > min_ol_dif and ol_pos > ol_neg:63 ry3d += step_r64 ol_best = ol_pos65 elif (ol_neg - ol_best) > min_ol_dif:66 ry3d -= step_r67 ol_best = ol_neg68 else:69 step_r = step_r * 0.570 while ry3d > 3.14: ry3d -= 3.14 * 271 while ry3d < (-3.14): ry3d += np.pi * 272 return ry3d, ol_best73@jit(nopython=True)74def test_projection(p2, p2_inv, box_2d, cx, cy, z, w3d, h3d, l3d, rotY):75 x = box_2d[0]76 y = box_2d[1]77 x2 = box_2d[2]78 y2 = box_2d[3]79 coord3d =[cx * z, cy * z, z, 1]))80 cx3d = coord3d[0]81 cy3d = coord3d[1]82 cz3d = coord3d[2]83 #top_3d =[cx * z, (cy-h3d/2) * z, z, 1]))84 # put back on ground first85 #cy3d += h3d/286 fy = p2[1, 1]87 # re-compute the 2D box using 3D (finally, avoids clipped boxes)88 verts3d, corners_3d = project_3d(p2, cx3d, cy3d, cz3d, w3d, h3d, l3d, rotY)...

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1"""2.. module:: test_projection3 :synopsis: Test Projection strategy4.. moduleauthor:: David Eriksson <>5"""6from pySOT import check_opt_prob, SyncStrategyProjection, \7 LatinHypercube, RBFInterpolant, CubicKernel, LinearTail, \8 CandidateDYCORS9from poap.controller import ThreadController, BasicWorkerThread10import numpy as np11import os.path12import logging13class AckleyUnit:14 def __init__(self, dim=10):15 self.xlow = -1 * np.ones(dim)16 self.xup = 1 * np.ones(dim)17 self.dim = dim18 = str(dim)+"-dimensional Ackley function on the unit sphere \n" +\19 "Global optimum: f(1,0,...,0) = ... = f(0,0,...,1) = " +\20 str(np.round(20*(1-np.exp(-0.2/np.sqrt(dim))), 3))21 self.min = 20*(1 - np.exp(-0.2/np.sqrt(dim)))22 self.integer = []23 self.continuous = np.arange(0, dim)24 check_opt_prob(self)25 def objfunction(self, x):26 n = float(len(x))27 return -20.0 * np.exp(-0.2*np.sqrt(np.sum(x**2)/n)) - \28 np.exp(np.sum(np.cos(2.0*np.pi*x))/n) + 20 + np.exp(1)29 def eval_eq_constraints(self, x):30 return np.linalg.norm(x) - 131def main():32 if not os.path.exists("./logfiles"):33 os.makedirs("logfiles")34 if os.path.exists("./logfiles/test_projection.log"):35 os.remove("./logfiles/test_projection.log")36 logging.basicConfig(filename="./logfiles/test_projection.log",37 level=logging.INFO)38 print("\nNumber of threads: 4")39 print("Maximum number of evaluations: 1000")40 print("Sampling method: CandidateDYCORS")41 print("Experimental design: Latin Hypercube")42 print("Surrogate: Cubic RBF")43 nthreads = 444 maxeval = 100045 nsamples = nthreads46 data = AckleyUnit(dim=10)47 print( def projection(x):49 return x / np.linalg.norm(x)50 # Create a strategy and a controller51 controller = ThreadController()52 controller.strategy = \53 SyncStrategyProjection(54 worker_id=0, data=data,55 maxeval=maxeval, nsamples=nsamples,56 exp_design=LatinHypercube(dim=data.dim, npts=2*(data.dim+1)),57 response_surface=RBFInterpolant(kernel=CubicKernel, tail=LinearTail, maxp=maxeval),58 sampling_method=CandidateDYCORS(data=data, numcand=100*data.dim),59 proj_fun=projection60 )61 # Launch the threads and give them access to the objective function62 for _ in range(nthreads):63 worker = BasicWorkerThread(controller, data.objfunction)64 controller.launch_worker(worker)65 # Run the optimization strategy66 result = print('Best value found: {0}'.format(result.value))68 print('Best solution found: {0}'.format(69 np.array_str(result.params[0], max_line_width=np.inf,70 precision=5, suppress_small=True)))71 print('||x||_2 = {0}\n'.format(np.linalg.norm(result.params[0])))72if __name__ == '__main__':...

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