pyrepo_mcda.distance_metrics ============================ .. py:module:: pyrepo_mcda.distance_metrics Functions --------- .. autoapisummary:: pyrepo_mcda.distance_metrics.euclidean pyrepo_mcda.distance_metrics.manhattan pyrepo_mcda.distance_metrics.hausdorff_distance pyrepo_mcda.distance_metrics.hausdorff pyrepo_mcda.distance_metrics.correlation pyrepo_mcda.distance_metrics.chebyshev pyrepo_mcda.distance_metrics.std_euclidean pyrepo_mcda.distance_metrics.cosine pyrepo_mcda.distance_metrics.csm pyrepo_mcda.distance_metrics.squared_euclidean pyrepo_mcda.distance_metrics.bray_curtis pyrepo_mcda.distance_metrics.canberra pyrepo_mcda.distance_metrics.lorentzian pyrepo_mcda.distance_metrics.jaccard pyrepo_mcda.distance_metrics.dice pyrepo_mcda.distance_metrics.bhattacharyya pyrepo_mcda.distance_metrics.hellinger pyrepo_mcda.distance_metrics.matusita pyrepo_mcda.distance_metrics.squared_chord pyrepo_mcda.distance_metrics.pearson_chi_square pyrepo_mcda.distance_metrics.squared_chi_square Module Contents --------------- .. py:function:: euclidean(A, B) Calculate Euclidean distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples ---------- >>> distance = euclidean(A, B) .. py:function:: manhattan(A, B) Calculate Manhattan (Taxicab) distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples ---------- >>> distance = manhattan(A, B) .. py:function:: hausdorff_distance(A, B) .. py:function:: hausdorff(A, B) Calculate Hausdorff distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples ---------- >>> distance = hausdorff(A, B) .. py:function:: correlation(A, B) Calculate Correlation distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples ---------- >>> distance = correlation(A, B) .. py:function:: chebyshev(A, B) Calculate Chebyshev distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples ---------- >>> distance = chebyshev(A, B) .. py:function:: std_euclidean(A, B) Calculate Standardized Euclidean distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples ---------- >>> distance = std_euclidean(A, B) .. py:function:: cosine(A, B) Calculate Cosine distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples ---------- >>> distance = cosine(A, B) .. py:function:: csm(A, B) Calculate Cosine similarity measure of distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples --------- >>> distance = csm(A, B) .. py:function:: squared_euclidean(A, B) Calculate Squared Euclidean distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples ---------- >>> distance = squared_euclidean(A, B) .. py:function:: bray_curtis(A, B) Calculate Bray-Curtis distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples ---------- >>> distance = bray_curtis(A, B) .. py:function:: canberra(A, B) Calculate Canberra distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples ---------- >>> distance = canberra(A, B) .. py:function:: lorentzian(A, B) Calculate Lorentzian distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples ---------- >>> distance = lorentzian(A, B) .. py:function:: jaccard(A, B) Calculate Jaccard distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples ----------- >>> distance = jaccard(A, B) .. py:function:: dice(A, B) Calculate Dice distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples ---------- >>> distance = dice(A, B) .. py:function:: bhattacharyya(A, B) Calculate Bhattacharyya distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples --------- >>> distance = bhattacharyya(A, B) .. py:function:: hellinger(A, B) Calculate Hellinger distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples ----------- >>> distance = hellinger(A, B) .. py:function:: matusita(A, B) Calculate Matusita distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples ---------- >>> distance = matusita(A, B) .. py:function:: squared_chord(A, B) Calculate Squared-Chord distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples --------- >>> distance = squared_chord(A, B) .. py:function:: pearson_chi_square(A, B) Calculate Pearson Chi Square distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples --------- >>> distance = pearson_chi_square(A, B) .. py:function:: squared_chi_square(A, B) Calculate Squared Chi Sqaure distance between two vectors `A` and `B`. Parameters ----------- A : ndarray First vector containing values B : ndarray Second vector containing values Returns -------- float distance value between two vectors Examples ---------- >>> distance = squared_chi_square(A, B)