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Build and deploy the backend to staging / Build and push image (pull_request) Successful in 2m23s
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@ -54,7 +54,7 @@ def test_turckheim(client, request): # pylint: disable=redefined-outer-name
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assert duration_minutes*0.8 < int(result['total_time']) < duration_minutes*1.2
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assert len(landmarks) > 2 # check that there is something to visit
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assert comp_time < 30, f"Computation time exceeded 30 seconds: {comp_time:.2f} seconds"
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assert 2==3
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# assert 2==3
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'''
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def test_bellecour(client, request) : # pylint: disable=redefined-outer-name
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"""
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@ -136,11 +136,13 @@ class Optimizer:
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# A = np.zeros((len(up_ind_x[1:]),L*L), dtype=np.int8)
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# Fill-in rows L to 2*L-1
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for i in range(int((L*L-L)/2)) :
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incr = 0
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for i in range(int((L*L+L)/2)) :
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if up_ind_x[i] != up_ind_y[i] :
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A[L+i, up_ind_x[i]*L + up_ind_y[i]] = 1
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A[L+i, up_ind_y[i]*L + up_ind_x[i]] = 1
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b[L+i] = 1
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A[L+incr, up_ind_x[i]*L + up_ind_y[i]] = 1
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A[L+incr, up_ind_y[i]*L + up_ind_x[i]] = 1
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b[L+incr] = 1
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incr += 1
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# return A[~np.all(A == 0, axis=1)], b
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@ -525,13 +527,10 @@ class Optimizer:
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self.logger.debug(f"Optimizing with {A_ub.shape[0]} + {A_eq.shape[0]} = {A_ub.shape[0] + A_eq.shape[0]} constraints.")
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print(A_ub)
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print('\n\n')
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print(b_ub)
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print('\n\n')
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print(A_eq)
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print('\n\n')
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print(b_eq)
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print('\n\n')
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# A, b = self.respect_user_must_do(landmarks) # Check if there are user_defined must_see. Also takes care of start/goal
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