コード例 #1
0
ファイル: test_OMPTD.py プロジェクト: MLDL/rlpy
def test_bag_creation():
    """
    Ensure create appropriate # of conjunctions, that they have been 
    instantiated properly, and there are no duplicates. 
    """
    mapDir = os.path.join(__rlpy_location__, "Domains", "GridWorldMaps")
    mapname=os.path.join(mapDir, "4x5.txt") # expect 4*5 = 20 states
    domain = GridWorld(mapname=mapname)
    
    initial_representation = IndependentDiscretization(domain)
    maxBatchDiscovery=np.inf
    batchThreshold=1e-10
    discretization=20
    bagSize=100000 # We add all possible features
    
    rep = OMPTD(domain, initial_representation, discretization, 
                maxBatchDiscovery, batchThreshold, bagSize, sparsify=False)
    assert rep.totalFeatureSize == 9+20
    assert rep.features_num == 9
    
    # Compute full (including non-discovered) feature vec for a few states
    states = np.array([[0,0], [0,1], [1,0], [1,1]])
    s0_unused = domain.s0() # just to initialize domain.state, etc
    rep.calculateFullPhiNormalized(states)
    phi_states = rep.fullphi
    phi_states[phi_states>0] = True
    true_phi_s1 = np.zeros(len(phi_states[0,:]))
    true_phi_s1[0] = True
    true_phi_s1[4] = True # TODO - could be [4] depending on axes, check.
    true_phi_s1[9] = True # The conjunction of [0,0]
    assert np.all(true_phi_s1 == phi_states[0,:]) # expected feature vec returned
    assert sum(phi_states[0,:]) == 3 # 2 original basic feats and 1 conjunction
    
    true_phi_s2 = np.zeros(len(phi_states[0,:]))
    true_phi_s2[0] = True
    true_phi_s2[5] = True # TODO - could be [4] depending on axes, check.
    true_phi_s2[10] = True # The conjunction of [0,0]
    assert np.all(true_phi_s2 == phi_states[1,:]) # expected feature vec returned
    assert sum(phi_states[1,:]) == 3 # 2 original basic feats and 1 conjunction
    
    true_phi_s3 = np.zeros(len(phi_states[0,:]))
    true_phi_s3[1] = True
    true_phi_s3[4] = True # TODO - could be [4] depending on axes, check.
    true_phi_s3[14] = True # The conjunction of [0,0]
    assert np.all(true_phi_s3 == phi_states[2,:]) # expected feature vec returned
    assert sum(phi_states[2,:]) == 3 # 2 original basic feats and 1 conjunction
    
    true_phi_s4 = np.zeros(len(phi_states[0,:]))
    true_phi_s4[1] = True
    true_phi_s4[5] = True # TODO - could be [4] depending on axes, check.
    true_phi_s4[15] = True # The conjunction of [0,0]
    assert np.all(true_phi_s4 == phi_states[3,:]) # expected feature vec returned
    assert sum(phi_states[3,:]) == 3 # 2 original basic feats and 1 conjunction
コード例 #2
0
ファイル: test_OMPTD.py プロジェクト: zhuzhenping/rlpy
def test_batch_discovery():
    """
    Test feature discovery from features available in bag, and that appropriate
    feats are activiated in later calls to phi_nonterminal()
    
    """
    mapDir = os.path.join(__rlpy_location__, "Domains", "GridWorldMaps")
    mapname = os.path.join(mapDir, "4x5.txt")  # expect 4*5 = 20 states
    domain = GridWorld(mapname=mapname)

    s0_unused = domain.s0()  # just to initialize domain.state, etc

    initial_representation = IndependentDiscretization(domain)
    maxBatchDiscovery = np.inf
    batchThreshold = 1e-10
    discretization = 20
    bagSize = 100000  # We add all possible features

    rep = OMPTD(domain,
                initial_representation,
                discretization,
                maxBatchDiscovery,
                batchThreshold,
                bagSize,
                sparsify=False)
    states = np.array([[0, 0], [0, 2]])
    activePhi_s1 = rep.phi_nonTerminal(states[0, :])
    activePhi_s2 = rep.phi_nonTerminal(states[1, :])
    phiMatr = np.zeros((2, len(activePhi_s1)))
    phiMatr[0, :] = activePhi_s1
    phiMatr[1, :] = activePhi_s2
    td_errors = np.array([2, 5])
    flagAddedFeat = rep.batchDiscover(td_errors, phiMatr, states)
    assert flagAddedFeat  # should have added at least one
    assert rep.selectedFeatures[-1] == 9  # feat conj that yields state [0,2]
    assert rep.selectedFeatures[-2] == 11  # feat conj that yields state [0,0]

    # Ensure that discovered features are now active
    true_phi_s1 = np.zeros(rep.features_num)
    true_phi_s1[0] = True
    true_phi_s1[4] = True  # TODO - could be [4] depending on axes, check.
    true_phi_s1[10] = True  # The conjunction of [0,0]
    assert np.all(true_phi_s1 == rep.phi_nonTerminal(states[0, :]))

    true_phi_s2 = np.zeros(rep.features_num)
    true_phi_s2[0] = True
    true_phi_s2[6] = True  # TODO - could be [4] depending on axes, check.
    true_phi_s2[
        9] = True  # The conjunction of [0,2] [[note actual id is 11, but in index 10]]
    assert np.all(true_phi_s2 == rep.phi_nonTerminal(states[1, :]))
コード例 #3
0
ファイル: test_OMPTD.py プロジェクト: MLDL/rlpy
def test_batch_discovery():
    """
    Test feature discovery from features available in bag, and that appropriate
    feats are activiated in later calls to phi_nonterminal()
    
    """
    mapDir = os.path.join(__rlpy_location__, "Domains", "GridWorldMaps")
    mapname=os.path.join(mapDir, "4x5.txt") # expect 4*5 = 20 states
    domain = GridWorld(mapname=mapname)
    
    s0_unused = domain.s0() # just to initialize domain.state, etc
    
    initial_representation = IndependentDiscretization(domain)
    maxBatchDiscovery=np.inf
    batchThreshold=1e-10
    discretization=20
    bagSize=100000 # We add all possible features
    
    rep = OMPTD(domain, initial_representation, discretization, 
                maxBatchDiscovery, batchThreshold, bagSize, sparsify=False)
    states = np.array([[0,0], [0,2]])
    activePhi_s1 = rep.phi_nonTerminal(states[0,:])
    activePhi_s2 = rep.phi_nonTerminal(states[1,:])
    phiMatr = np.zeros(( 2, len(activePhi_s1) ))
    phiMatr[0,:] = activePhi_s1
    phiMatr[1,:] = activePhi_s2
    td_errors = np.array([2, 5])
    flagAddedFeat = rep.batchDiscover(td_errors, phiMatr, states)
    assert flagAddedFeat # should have added at least one
    assert rep.selectedFeatures[-1] == 9 # feat conj that yields state [0,2]
    assert rep.selectedFeatures[-2] == 11 # feat conj that yields state [0,0]
    
    # Ensure that discovered features are now active
    true_phi_s1 = np.zeros(rep.features_num)
    true_phi_s1[0] = True
    true_phi_s1[4] = True # TODO - could be [4] depending on axes, check.
    true_phi_s1[10] = True # The conjunction of [0,0]
    assert np.all(true_phi_s1 == rep.phi_nonTerminal(states[0,:]))
    
    true_phi_s2 = np.zeros(rep.features_num)
    true_phi_s2[0] = True
    true_phi_s2[6] = True # TODO - could be [4] depending on axes, check.
    true_phi_s2[9] = True # The conjunction of [0,2] [[note actual id is 11, but in index 10]]
    assert np.all(true_phi_s2 == rep.phi_nonTerminal(states[1,:]))
    
コード例 #4
0
ファイル: test_OMPTD.py プロジェクト: zhuzhenping/rlpy
def test_bag_creation():
    """
    Ensure create appropriate # of conjunctions, that they have been 
    instantiated properly, and there are no duplicates. 
    """
    mapDir = os.path.join(__rlpy_location__, "Domains", "GridWorldMaps")
    mapname = os.path.join(mapDir, "4x5.txt")  # expect 4*5 = 20 states
    domain = GridWorld(mapname=mapname)

    initial_representation = IndependentDiscretization(domain)
    maxBatchDiscovery = np.inf
    batchThreshold = 1e-10
    discretization = 20
    bagSize = 100000  # We add all possible features

    rep = OMPTD(domain,
                initial_representation,
                discretization,
                maxBatchDiscovery,
                batchThreshold,
                bagSize,
                sparsify=False)
    assert rep.totalFeatureSize == 9 + 20
    assert rep.features_num == 9

    # Compute full (including non-discovered) feature vec for a few states
    states = np.array([[0, 0], [0, 1], [1, 0], [1, 1]])
    s0_unused = domain.s0()  # just to initialize domain.state, etc
    rep.calculateFullPhiNormalized(states)
    phi_states = rep.fullphi
    phi_states[phi_states > 0] = True
    true_phi_s1 = np.zeros(len(phi_states[0, :]))
    true_phi_s1[0] = True
    true_phi_s1[4] = True  # TODO - could be [4] depending on axes, check.
    true_phi_s1[9] = True  # The conjunction of [0,0]
    assert np.all(
        true_phi_s1 == phi_states[0, :])  # expected feature vec returned
    assert sum(
        phi_states[0, :]) == 3  # 2 original basic feats and 1 conjunction

    true_phi_s2 = np.zeros(len(phi_states[0, :]))
    true_phi_s2[0] = True
    true_phi_s2[5] = True  # TODO - could be [4] depending on axes, check.
    true_phi_s2[10] = True  # The conjunction of [0,0]
    assert np.all(
        true_phi_s2 == phi_states[1, :])  # expected feature vec returned
    assert sum(
        phi_states[1, :]) == 3  # 2 original basic feats and 1 conjunction

    true_phi_s3 = np.zeros(len(phi_states[0, :]))
    true_phi_s3[1] = True
    true_phi_s3[4] = True  # TODO - could be [4] depending on axes, check.
    true_phi_s3[14] = True  # The conjunction of [0,0]
    assert np.all(
        true_phi_s3 == phi_states[2, :])  # expected feature vec returned
    assert sum(
        phi_states[2, :]) == 3  # 2 original basic feats and 1 conjunction

    true_phi_s4 = np.zeros(len(phi_states[0, :]))
    true_phi_s4[1] = True
    true_phi_s4[5] = True  # TODO - could be [4] depending on axes, check.
    true_phi_s4[15] = True  # The conjunction of [0,0]
    assert np.all(
        true_phi_s4 == phi_states[3, :])  # expected feature vec returned
    assert sum(
        phi_states[3, :]) == 3  # 2 original basic feats and 1 conjunction