Cluster Iterator¶
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class
blocksci.cluster.
ClusterIterator
¶ -
address_count
() → numpy.ndarray[int]¶ For each item: The number of addresses in the cluster
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property
addresses
¶ For each item: Get a iterable over all the addresses in the cluster
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balance
(height: int = - 1) → numpy.ndarray[int]¶ For each item: Calculates the balance held by this cluster at the height (Defaults to the full chain)
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count_of_type
(address_type: blocksci::AddressType::Enum) → numpy.ndarray[int]¶ For each item: Return the number of addresses of the given type in the cluster
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in_txes_count
() → numpy.ndarray[int]¶ For each item: Return the number of transactions where this cluster was an input
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property
index
¶ For each item: The internal identifier of the cluster
- Type
numpy.ndarray[int]
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input_txes_count
() → numpy.ndarray[int]¶ For each item: Return the number of transactions where this cluster was an input
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inputs
() → blocksci.InputIterator¶ For each item: Returns an iterator over all inputs spent from this cluster
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ins
() → blocksci.InputIterator¶ For each item: Returns an iterator over all inputs spent from this cluster
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out_txes_count
() → numpy.ndarray[int]¶ For each item: Return the number of transactions where an address in this cluster was used in an output
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output_txes_count
() → numpy.ndarray[int]¶ For each item: Return the number of transactions where an address in this cluster was used in an output
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outputs
() → blocksci.OutputIterator¶ For each item: Returns an iterator over all outputs sent to this cluster
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outs
() → blocksci.OutputIterator¶ For each item: Returns an iterator over all outputs sent to this cluster
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tagged_addresses
(tagged_addresses: Dict[Address, str]) → blocksci.cluster.TaggedAddressIterator¶ For each item: Given a dictionary of tags, return a range of TaggedAddress objects for any tagged addresses in the cluster
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property
type_equiv_size
¶ For each item: The number of addresses in the cluster not counting type equivalent addresses
- Type
numpy.ndarray[int]
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