def __init__(self,
fm_infile,
seed_hv_infile,
num_folds,
is_early_fusion=True):
# Feature Memory
self.feature_memory = memory.FeatureMemory(fm_infile)
self.feature_memory.normalize()
self.feature_memory.downSample(self.downsample_interval)
self.feature_memory.discretize()
self.feature_memory.genTrainData(self.learning_rate)
# Seed HV progress over time
self.seed_hv = memory.Memory(seed_hv_infile).getRow(0).tolist()
# Associative Memory
memory.AssociativeMemory.dimension = self.dimension
self.associative_memory = memory.AssociativeMemory()
# Spatial Encoder
spatial_encoder.SpatialEncoder.dimension = self.dimension
self.spatial_encoder_GSR = spatial_encoder.SpatialEncoder(
self.num_channel_GSR)
self.spatial_encoder_ECG = spatial_encoder.SpatialEncoder(
self.num_channel_ECG)
self.spatial_encoder_EEG = spatial_encoder.SpatialEncoder(
self.num_channel_EEG)
# Temporal Encoder
temporal_encoder.TemporalEncoder.dimension = self.dimension
temporal_encoder.TemporalEncoder.ngram_size = self.ngram_size
self.temporal_encoder = temporal_encoder.TemporalEncoder(
) # used only when is_early_fusion is True
self.temporal_encoder_GSR = temporal_encoder.TemporalEncoder(
) # used only when is_early_fusion is False
self.temporal_encoder_ECG = temporal_encoder.TemporalEncoder(
) # used only when is_early_fusion is False
self.temporal_encoder_EEG = temporal_encoder.TemporalEncoder(
) # used only when is_early_fusion is False
self.is_early_fusion = is_early_fusion
self.num_folds = num_folds
# Prediction Statistics
self.correct_prediction = 0
self.wrong_prediction = 0
self.prediction_success_rate = 0
self.correct_v_prediction = 0
self.wrong_v_prediction = 0
self.prediction_v_success_rate = 0
self.correct_a_prediction = 0
self.wrong_a_prediction = 0
self.prediction_a_success_rate = 0
self.predicted_v_history = []
self.predicted_a_history = []
def __init__(self,
fm_infile,
pm_plus_GSR_infile,
pm_neg_GSR_infile,
pm_plus_ECG_infile,
pm_neg_ECG_infile,
pm_plus_EEG_infile,
pm_neg_EEG_infile,
im_infile,
is_early_fusion=True):
# Feature Memory
self.feature_memory = memory.FeatureMemory(fm_infile)
self.feature_memory.normalize()
self.feature_memory.downSample(self.downsample_interval)
self.feature_memory.discretize()
self.feature_memory.genTrainData(self.learning_rate)
# Projection Memory
self.projection_memory_GSR = memory.ProjectionMemory(
pm_plus_GSR_infile, pm_neg_GSR_infile)
self.projection_memory_ECG = memory.ProjectionMemory(
pm_plus_ECG_infile, pm_neg_ECG_infile)
self.projection_memory_EEG = memory.ProjectionMemory(
pm_plus_EEG_infile, pm_neg_EEG_infile)
# Item Memory
self.item_memory = memory.Memory(im_infile)
# Associative Memory
memory.AssociativeMemory.dimension = self.dimension
self.associative_memory = memory.AssociativeMemory()
# Spatial Encoder
spatial_encoder.SpatialEncoder.dimension = self.dimension
self.spatial_encoder_GSR = spatial_encoder.SpatialEncoder(
self.num_channel_GSR)
self.spatial_encoder_ECG = spatial_encoder.SpatialEncoder(
self.num_channel_ECG)
self.spatial_encoder_EEG = spatial_encoder.SpatialEncoder(
self.num_channel_EEG)
# Temporal Encoder
temporal_encoder.TemporalEncoder.dimension = self.dimension
temporal_encoder.TemporalEncoder.ngram_size = self.ngram_size
self.temporal_encoder = temporal_encoder.TemporalEncoder(
) # used only when is_early_fusion is True
self.temporal_encoder_GSR = temporal_encoder.TemporalEncoder(
) # used only when is_early_fusion is False
self.temporal_encoder_ECG = temporal_encoder.TemporalEncoder(
) # used only when is_early_fusion is False
self.temporal_encoder_EEG = temporal_encoder.TemporalEncoder(
) # used only when is_early_fusion is False
self.is_early_fusion = is_early_fusion
# Prediction Statistics
self.correct_prediction = 0
self.wrong_prediction = 0
self.prediction_success_rate = 0
self.correct_v_prediction = 0
self.wrong_v_prediction = 0
self.prediction_v_success_rate = 0
self.correct_a_prediction = 0
self.wrong_a_prediction = 0
self.prediction_a_success_rate = 0
self.predicted_v_history = []
self.predicted_a_history = []