sf.apps.similarity.feature_vector_events_sampling¶
-
feature_vector_events_sampling
(samples, event_photon_numbers, max_count_per_mode=2)[source]¶ Calculates feature vector of given events with respect to input samples.
The feature vector is composed of event probabilities reconstructed by measuring the occurrence of given events in the input
samples
.Example usage:
>>> from strawberryfields.apps import data >>> samples = data.Mutag0() >>> feature_vector_events_sampling(samples, [2, 4, 6], 2) [0.19035, 0.2047, 0.1539]
- Parameters
samples (list[list[int]]) – a list of samples
event_photon_numbers (list[int]) – a list of events described by their total photon number
max_count_per_mode (int) – maximum number of photons per mode for all events
- Returns
a feature vector made up of estimated event probabilities in the same order as
event_photon_numbers
- Return type
list[float]
code/api/strawberryfields.apps.similarity.feature_vector_events_sampling
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