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#self.table = np.load('fingerprinting_tables/Julian_1cm_precision_corrected_antenas.npy') # corrected table made by Ihm (No ferrite) |
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#self.table = np.load('fingerprinting_tables/Julian_1cm_precision_corrected_antenas.npy') # corrected table made by Ihm (No ferrite) |
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#self.table = np.load('fingerprinting_tables/SmallManualFingerprint_Ferrite.npy') # manual fingerprinting table (Ferrite) [A bit off] |
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#self.table = np.load('fingerprinting_tables/SmallManualFingerprint_Ferrite.npy') # manual fingerprinting table (Ferrite) [A bit off] |
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#self.table = np.load('fingerprinting_tables/Julian_BThesis_table2_switchedAnt5&6 and 7&8.npy') # Switched Ant5<->6 and 7<->8 in Excel (No Ferrite) [Does not work!] |
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#self.table = np.load('fingerprinting_tables/Julian_BThesis_table2_switchedAnt5&6 and 7&8.npy') # Switched Ant5<->6 and 7<->8 in Excel (No Ferrite) [Does not work!] |
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self.table = np.load('fingerprinting_tables/Julian_THIS_ONE_IS_IT.npy') # 2cm precision this definetly worked for (No ferrite) |
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self.data = np.load('recorded_data/current_recording.npy') |
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self.data = np.load('recorded_data/current_recording.npy') |
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Output: - position [type = np.array[3]]: |
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Output: - position [type = np.array[3]]: |
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The estimated position of the object in this sample x,y,z |
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The estimated position of the object in this sample x,y,z |
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""" |
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""" |
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print("fv =", fv) |
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#print("fv =", fv) |
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feature_vector = fv * self.scale_factor |
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feature_vector = fv * self.scale_factor |
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print("table=", self.table) |
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repeated_feature_vector = np.square(self.table[:, 9:] - feature_vector) |
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repeated_feature_vector = np.square(self.table[:, 9:] - feature_vector) |
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euclidean_distances = np.sum(repeated_feature_vector, 1) |
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euclidean_distances = np.sum(repeated_feature_vector, 1) |