MCPcopy Create free account

hub / github.com/KareemYousrii/SPL / functions

Functions1,219 in github.com/KareemYousrii/SPL

⨍ Functions 1,219◇ Types & classes 137↳ Endpoints 4
↓ 9 callersMethodsize
Returns the aggregate size of decision nodes in the SDD
C-HMCNN/hmc-utils/pypsdd/pypsdd/sdd.py:167
↓ 8 callersFunctionrun_test_basename
(basename,N=2**14)
C-HMCNN/hmc-utils/pypsdd/sdd/tests/testdata.py:220
↓ 8 callersFunctionrun_test_basename
(basename,N=2**14)
C-HMCNN/hmc-utils/pypsdd/pypsdd/tests/testdata.py:220
↓ 8 callersFunctionrun_test_basename
(basename,N=2**14)
grids/pypsdd/sdd/tests/testdata.py:220
↓ 8 callersFunctionrun_test_basename
(basename,N=2**14)
grids/pypsdd/pypsdd/tests/testdata.py:220
↓ 8 callersMethodset_params
(self, thetas, log_space=True)
C-HMCNN/hmc-utils/compute_mpe.py:39
↓ 8 callersMethodset_params
(self, thetas, log_space=True)
grids/compute_mpe.py:29
↓ 7 callersMethodclear_bits
Recursively clears bits. For use when recursively navigating an SDD by marking bits (not for use with SddNode.as_list). Set clear_da
C-HMCNN/hmc-utils/pypsdd/sdd/sdd.py:123
↓ 7 callersMethodclear_bits
Recursively clears bits. For use when recursively navigating an SDD by marking bits (not for use with SddNode.as_list). Set clear_da
grids/pypsdd/sdd/sdd.py:123
↓ 7 callersFunctioncmp
(x, y)
C-HMCNN/hmc-utils/pypsdd/sdd/manager.py:7
↓ 7 callersFunctioncmp
(x, y)
C-HMCNN/hmc-utils/pypsdd/pypsdd/manager.py:7
↓ 7 callersFunctioncmp
(x, y)
grids/pypsdd/sdd/manager.py:7
↓ 7 callersFunctioncmp
(x, y)
grids/pypsdd/pypsdd/manager.py:7
↓ 7 callersMethodcopy_and_normalize_sdd
Copy an SDD alpha from another manager to the self manager, and normalize it with respect to the given vtree.
C-HMCNN/hmc-utils/pypsdd/pypsdd/manager.py:125
↓ 7 callersMethodcopy_and_normalize_sdd
Copy an SDD alpha from another manager to the self manager, and normalize it with respect to the given vtree.
grids/pypsdd/pypsdd/manager.py:125
↓ 7 callersMethodget_mpe_inst
(self, batch_size)
grids/compute_mpe.py:61
↓ 7 callersMethodis_mixing
Returns true if node is MIXING, and false otherwise
grids/pypsdd/pypsdd/sdd.py:155
↓ 7 callersMethodmodels
A generator for the models of an SDD. If lexical is True, then models will be given in lexical (sorted) order. This is typic
grids/pypsdd/sdd/sdd.py:258
↓ 6 callersMethodas_list
iterating over an SDD's nodes, as a list This is faster than recursive traversal of an SDD, as done in __iter__() and pre_order(). I
C-HMCNN/hmc-utils/pypsdd/sdd/sdd.py:136
↓ 6 callersMethodas_list
iterating over an SDD's nodes, as a list This is faster than recursive traversal of an SDD, as done in __iter__() and pre_order(). I
grids/pypsdd/sdd/sdd.py:136
↓ 6 callersMethodis_model_marker
Returns None if inst is not a model, otherwise it returns the value/element that is satisfied. inst should be of type Inst or InstMap
C-HMCNN/hmc-utils/pypsdd/pypsdd/sdd.py:357
↓ 6 callersMethodis_model_marker
Returns None if inst is not a model, otherwise it returns the value/element that is satisfied. inst should be of type Inst or InstMap
grids/pypsdd/pypsdd/sdd.py:357
↓ 6 callersMethodkl_psdd
Compute KL-divergence between two PSDDs, recursively. The PSDDs must have the same structure, but may have different parameters.
C-HMCNN/hmc-utils/pypsdd/sdd/psdd.py:298
↓ 6 callersMethodkl_psdd
Compute KL-divergence between two PSDDs, recursively. The PSDDs must have the same structure, but may have different parameters.
grids/pypsdd/sdd/psdd.py:298
↓ 6 callersMethodlookup_node
Unique table lookup for DECOMPOSITION nodes. Elements is a list of prime,sub pairs: [ (p1,s1),(p2,s2),...,(pn,sn) ]
C-HMCNN/hmc-utils/pypsdd/sdd/manager.py:57
↓ 6 callersMethodlookup_node
Unique table lookup for DECOMPOSITION nodes. Elements is a list of prime,sub pairs: [ (p1,s1),(p2,s2),...,(pn,sn) ]
C-HMCNN/hmc-utils/pypsdd/pypsdd/manager.py:57
↓ 6 callersMethodlookup_node
Unique table lookup for DECOMPOSITION nodes. Elements is a list of prime,sub pairs: [ (p1,s1),(p2,s2),...,(pn,sn) ]
grids/pypsdd/sdd/manager.py:57
↓ 6 callersMethodlookup_node
Unique table lookup for DECOMPOSITION nodes. Elements is a list of prime,sub pairs: [ (p1,s1),(p2,s2),...,(pn,sn) ]
grids/pypsdd/pypsdd/manager.py:57
↓ 6 callersMethodmodels
A generator for the models of an SDD. If lexical is True, then models will be given in lexical (sorted) order. This is typic
C-HMCNN/hmc-utils/pypsdd/sdd/sdd.py:258
↓ 6 callersMethodread
Read vtree from file
C-HMCNN/hmc-utils/pypsdd/pypsdd/vtree.py:117
↓ 6 callersMethodread
Read vtree from file
grids/pypsdd/pypsdd/vtree.py:117
↓ 5 callersMethodconcat
concatenates self with other and returns new Inst
C-HMCNN/hmc-utils/pypsdd/sdd/data.py:385
↓ 5 callersMethodconcat
concatenates self with other and returns new Inst
C-HMCNN/hmc-utils/pypsdd/pypsdd/data.py:385
↓ 5 callersMethodconcat
concatenates self with other and returns new Inst
grids/pypsdd/sdd/data.py:385
↓ 5 callersMethodconcat
concatenates self with other and returns new Inst
grids/pypsdd/pypsdd/data.py:385
↓ 5 callersMethodcross_entropy
(self, target, log_space=True)
grids/compute_mpe.py:109
↓ 5 callersMethodempty
(self)
C-HMCNN/hmc-utils/pypsdd/sdd/sdd.py:656
↓ 5 callersMethodempty
(self)
C-HMCNN/hmc-utils/pypsdd/pypsdd/sdd.py:1442
↓ 5 callersMethodempty
(self)
grids/pypsdd/sdd/sdd.py:656
↓ 5 callersMethodempty
(self)
grids/pypsdd/pypsdd/sdd.py:1595
↓ 5 callersMethodfrom_bitset
new (complete) Inst from bitstring
C-HMCNN/hmc-utils/pypsdd/sdd/data.py:165
↓ 5 callersMethodfrom_bitset
new (complete) Inst from bitstring
C-HMCNN/hmc-utils/pypsdd/pypsdd/data.py:165
↓ 5 callersMethodfrom_bitset
new (complete) Inst from bitstring
grids/pypsdd/sdd/data.py:165
↓ 5 callersMethodfrom_bitset
new (complete) Inst from bitstring
grids/pypsdd/pypsdd/data.py:165
↓ 5 callersFunctionget_model
(model_name, out_features, in_channels, arch_params)
WarcraftShortestPath/models.py:9
↓ 5 callersMethodkl_psdd
Compute KL-divergence between two PSDDs, recursively. The PSDDs must have the same structure, but may have different parameters.
C-HMCNN/hmc-utils/pypsdd/pypsdd/psdd.py:298
↓ 5 callersMethodkl_psdd
Compute KL-divergence between two PSDDs, recursively. The PSDDs must have the same structure, but may have different parameters.
grids/pypsdd/pypsdd/psdd.py:298
↓ 5 callersMethodmodels
A generator for the models of an SDD. If lexical is True, then models will be given in lexical (sorted) order. This is typic
C-HMCNN/hmc-utils/pypsdd/pypsdd/sdd.py:403
↓ 5 callersMethodmodels
A generator for the models of an SDD. If lexical is True, then models will be given in lexical (sorted) order. This is typic
grids/pypsdd/pypsdd/sdd.py:403
↓ 5 callersMethodoverparameterize
(self, S=2)
C-HMCNN/hmc-utils/compute_mpe.py:32
↓ 5 callersMethodoverparameterize
(self, S=2)
grids/compute_mpe.py:23
↓ 5 callersMethodpr_model
Returns Pr(inst) for a complete instantiation inst (where inst is an Inst or InstMap). Performs recursive test, which can be faster t
C-HMCNN/hmc-utils/pypsdd/sdd/psdd.py:115
↓ 5 callersMethodpr_model
Returns Pr(inst) for a complete instantiation inst (where inst is an Inst or InstMap). Performs recursive test, which can be faster t
C-HMCNN/hmc-utils/pypsdd/pypsdd/psdd.py:115
↓ 5 callersMethodpr_model
Returns Pr(inst) for a complete instantiation inst (where inst is an Inst or InstMap). Performs recursive test, which can be faster t
grids/pypsdd/sdd/psdd.py:115
↓ 5 callersMethodpr_model
Returns Pr(inst) for a complete instantiation inst (where inst is an Inst or InstMap). Performs recursive test, which can be faster t
grids/pypsdd/pypsdd/psdd.py:115
↓ 5 callersMethodsample
If input is a list of tuples (item,probability), randomly return an item based according to their probability
grids/pypsdd/pypsdd/psdd.py:344
↓ 4 callersFunction_node_label
return/create symbol for terminal SDD
C-HMCNN/hmc-utils/pypsdd/sdd/io.py:135
↓ 4 callersFunction_node_label
return/create symbol for terminal SDD
C-HMCNN/hmc-utils/pypsdd/pypsdd/io.py:135
↓ 4 callersFunction_node_label
return/create symbol for terminal SDD
grids/pypsdd/sdd/io.py:135
↓ 4 callersFunction_node_label
return/create symbol for terminal SDD
grids/pypsdd/pypsdd/io.py:135
↓ 4 callersFunction_set_index
set up index for saving SDD to file
C-HMCNN/hmc-utils/pypsdd/sdd/io.py:67
↓ 4 callersFunction_set_index
set up index for saving SDD to file
C-HMCNN/hmc-utils/pypsdd/pypsdd/io.py:67
↓ 4 callersFunction_set_index
set up index for saving SDD to file
grids/pypsdd/sdd/io.py:67
↓ 4 callersFunction_set_index
set up index for saving SDD to file
grids/pypsdd/pypsdd/io.py:67
↓ 4 callersMethodcheck_key_value
(self, key, value)
C-HMCNN/hmc-utils/pypsdd/sdd/data.py:180
↓ 4 callersMethodcheck_key_value
(self, key, value)
C-HMCNN/hmc-utils/pypsdd/pypsdd/data.py:180
↓ 4 callersMethodcheck_key_value
(self, key, value)
grids/pypsdd/sdd/data.py:180
↓ 4 callersMethodcheck_key_value
(self, key, value)
grids/pypsdd/pypsdd/data.py:180
↓ 4 callersFunctiondijkstra
(matrix, neighbourhood_fn="8-grid", request_transitions=False, graph=None)
WarcraftShortestPath/comb_modules/dijkstra.py:12
↓ 4 callersMethodempty
(self)
C-HMCNN/hmc-utils/pypsdd/sdd/sdd.py:578
↓ 4 callersMethodempty
(self)
C-HMCNN/hmc-utils/pypsdd/pypsdd/sdd.py:1364
↓ 4 callersMethodempty
(self)
grids/pypsdd/sdd/sdd.py:578
↓ 4 callersMethodempty
(self)
grids/pypsdd/pypsdd/sdd.py:1517
↓ 4 callersMethodinitialize_psdd
Initialize the parameters of a PSDD.
C-HMCNN/hmc-utils/pypsdd/sdd/prior.py:121
↓ 4 callersMethodinitialize_psdd
Initialize the parameters of a PSDD.
grids/pypsdd/sdd/prior.py:121
↓ 4 callersMethodis_model_marker
Returns None if inst is not a model, otherwise it returns the value/element that is satisfied. inst should be of type Inst or InstMap
C-HMCNN/hmc-utils/pypsdd/sdd/sdd.py:213
↓ 4 callersMethodis_model_marker
Returns None if inst is not a model, otherwise it returns the value/element that is satisfied. inst should be of type Inst or InstMap
grids/pypsdd/sdd/sdd.py:213
↓ 4 callersMethodkl
Compute KL-divergence between two (list) distributions pr1 and pr2
C-HMCNN/hmc-utils/pypsdd/sdd/psdd.py:275
↓ 4 callersMethodkl
Compute KL-divergence between two (list) distributions pr1 and pr2
C-HMCNN/hmc-utils/pypsdd/pypsdd/psdd.py:275
↓ 4 callersMethodkl
Compute KL-divergence between two (list) distributions pr1 and pr2
grids/pypsdd/sdd/psdd.py:275
↓ 4 callersMethodkl
Compute KL-divergence between two (list) distributions pr1 and pr2
grids/pypsdd/pypsdd/psdd.py:275
↓ 4 callersMethodkl_psdd_alt
Alternative computation of the KL-divergence between two PSDDs. The PSDDs must have the same structure, but may have different paramet
C-HMCNN/hmc-utils/pypsdd/sdd/psdd.py:319
↓ 4 callersMethodkl_psdd_alt
Alternative computation of the KL-divergence between two PSDDs. The PSDDs must have the same structure, but may have different paramet
C-HMCNN/hmc-utils/pypsdd/pypsdd/psdd.py:319
↓ 4 callersMethodkl_psdd_alt
Alternative computation of the KL-divergence between two PSDDs. The PSDDs must have the same structure, but may have different paramet
grids/pypsdd/sdd/psdd.py:319
↓ 4 callersMethodkl_psdd_alt
Alternative computation of the KL-divergence between two PSDDs. The PSDDs must have the same structure, but may have different paramet
grids/pypsdd/pypsdd/psdd.py:319
↓ 4 callersMethodkl_psdd_brute_force
Brute-force (enumerative) computation of KL-divergence between two PSDDs
C-HMCNN/hmc-utils/pypsdd/sdd/psdd.py:284
↓ 4 callersMethodkl_psdd_brute_force
Brute-force (enumerative) computation of KL-divergence between two PSDDs
C-HMCNN/hmc-utils/pypsdd/pypsdd/psdd.py:284
↓ 4 callersMethodkl_psdd_brute_force
Brute-force (enumerative) computation of KL-divergence between two PSDDs
grids/pypsdd/sdd/psdd.py:284
↓ 4 callersMethodkl_psdd_brute_force
Brute-force (enumerative) computation of KL-divergence between two PSDDs
grids/pypsdd/pypsdd/psdd.py:284
↓ 4 callersFunctionnested_to_dict
(nested_items)
WarcraftShortestPath/utils.py:348
↓ 4 callersMethodprobability
Compute the probability of evidence in a PSDD
C-HMCNN/hmc-utils/pypsdd/sdd/psdd.py:163
↓ 4 callersMethodprobability
Compute the probability of evidence in a PSDD
C-HMCNN/hmc-utils/pypsdd/pypsdd/psdd.py:163
↓ 4 callersMethodprobability
Compute the probability of evidence in a PSDD
grids/pypsdd/sdd/psdd.py:163
↓ 4 callersMethodprobability
Compute the probability of evidence in a PSDD
grids/pypsdd/pypsdd/psdd.py:163
↓ 4 callersMethodsample
Compute the MPE instation given weights associated with literals. Assumes the SDD is normalized.
C-HMCNN/hmc-utils/pypsdd/pypsdd/sdd.py:772
↓ 4 callersMethodsave
Save vtree to file
grids/pypsdd/sdd/vtree.py:147
↓ 4 callersMethodtheta_count
Counts the number of free parameters in a PSDD. Only 'live' nodes are considered. i.e., we do not count (sub)-nodes of primes with fa
C-HMCNN/hmc-utils/pypsdd/sdd/psdd.py:69
↓ 4 callersMethodtheta_count
Counts the number of free parameters in a PSDD. Only 'live' nodes are considered. i.e., we do not count (sub)-nodes of primes with fa
C-HMCNN/hmc-utils/pypsdd/pypsdd/psdd.py:69
↓ 4 callersMethodtheta_count
Counts the number of free parameters in a PSDD. Only 'live' nodes are considered. i.e., we do not count (sub)-nodes of primes with fa
grids/pypsdd/sdd/psdd.py:69
↓ 4 callersMethodtheta_count
Counts the number of free parameters in a PSDD. Only 'live' nodes are considered. i.e., we do not count (sub)-nodes of primes with fa
grids/pypsdd/pypsdd/psdd.py:69
← previousnext →101–200 of 1,219, ranked by callers