IFS
Distance measures
- pyifdm.methods.ifs.distance.euclidean_distance(a, b)[source]
Calculates the distance between two Intuitionistic Fuzzy Sets (u, v) using Euclidean distance
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Sets (u, v)
b (ndarray) – Intuitionistic Fuzzy Sets (u, v)
- Returns:
Crisp value representing distance
- Return type:
float
- pyifdm.methods.ifs.distance.grzegorzewski_distance(a, b)[source]
Calculates the distance between two Intuitionistic Fuzzy Sets (u, v) using Grzegorzewski distance
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Sets (u, v)
b (ndarray) – Intuitionistic Fuzzy Sets (u, v)
- Returns:
Crisp value representing distance
- Return type:
float
- pyifdm.methods.ifs.distance.hamming_distance(a, b)[source]
Calculates the distance between two Intuitionistic Fuzzy Sets (u, v) using Hamming distance
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Sets (u, v)
b (ndarray) – Intuitionistic Fuzzy Sets (u, v)
- Returns:
Crisp value representing distance
- Return type:
float
- pyifdm.methods.ifs.distance.hausdorf_euclidean_distance(a, b)[source]
Calculates the distance between two Intuitionistic Fuzzy Sets (u, v) using Hausdorf measure-based Euclidean distance
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Sets (u, v)
b (ndarray) – Intuitionistic Fuzzy Sets (u, v)
- Returns:
Crisp value representing distance
- Return type:
float
- pyifdm.methods.ifs.distance.luo_distance(a, b)[source]
Calculates the distance between two Intuitionistic Fuzzy Sets (u, v) using Luo distance
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Sets (u, v)
b (ndarray) – Intuitionistic Fuzzy Sets (u, v)
- Returns:
Crisp value representing distance
- Return type:
float
- pyifdm.methods.ifs.distance.normalized_euclidean_distance(a, b)[source]
Calculates the distance between two Intuitionistic Fuzzy Sets (u, v) using normalized Euclidean distance
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Sets (u, v)
b (ndarray) – Intuitionistic Fuzzy Sets (u, v)
- Returns:
Crisp value representing distance
- Return type:
float
- pyifdm.methods.ifs.distance.normalized_hamming_distance(a, b)[source]
Calculates the distance between two Intuitionistic Fuzzy Sets (u, v) using normalized Hamming distance
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Sets (u, v)
b (ndarray) – Intuitionistic Fuzzy Sets (u, v)
- Returns:
Crisp value representing distance
- Return type:
float
- pyifdm.methods.ifs.distance.wang_xin_distance_1(a, b)[source]
Calculates the distance between two Intuitionistic Fuzzy Sets (u, v) using Wang Xin distance 1
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Sets (u, v)
b (ndarray) – Intuitionistic Fuzzy Sets (u, v)
- Returns:
Crisp value representing distance
- Return type:
float
- pyifdm.methods.ifs.distance.wang_xin_distance_2(a, b)[source]
Calculates the distance between two Intuitionistic Fuzzy Sets (u, v) using Wang Xin distance 2
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Sets (u, v)
b (ndarray) – Intuitionistic Fuzzy Sets (u, v)
- Returns:
Crisp value representing distance
- Return type:
float
- pyifdm.methods.ifs.distance.yang_chiclana_distance(a, b)[source]
Calculates the distance between two Intuitionistic Fuzzy Sets (u, v) using Yang & Chiclana distance
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Sets (u, v)
b (ndarray) – Intuitionistic Fuzzy Sets (u, v)
- Returns:
Crisp value representing distance
- Return type:
float
Normalizations
- pyifdm.methods.ifs.normalization.ecer_normalization(matrix, types)[source]
Calculates the normalized value of Intuitionistic Fuzzy matrix using Ecer normalization
- Parameters:
matrix (ndarray) – Matrix with Intuitionistic Fuzzy Sets
types (ndarray) – Types of criteria, 1 profit, -1 cost
- Returns:
Normalized Intuitionistic Fuzzy matrix
- Return type:
ndarray
- pyifdm.methods.ifs.normalization.max_normalization(matrix, types)[source]
Calculates the normalized value of Intuitionistic Fuzzy matrix using Max normalization
- Parameters:
matrix (ndarray) – Matrix with Intuitionistic Fuzzy Sets
types (ndarray) – Types of criteria, 1 profit, -1 cost
- Returns:
Normalized Intuitionistic Fuzzy matrix
- Return type:
ndarray
- pyifdm.methods.ifs.normalization.minmax_normalization(matrix, types)[source]
Calculates the normalized value of Intuitionistic Fuzzy matrix using Min-Max normalization
- Parameters:
matrix (ndarray) – Matrix with Intuitionistic Fuzzy Sets
types (ndarray) – Types of criteria, 1 profit, -1 cost
- Returns:
Normalized Intuitionistic Fuzzy matrix
- Return type:
ndarray
- pyifdm.methods.ifs.normalization.supriya_normalization(matrix, *args)[source]
Calculates the normalized value of Intuitionistic Fuzzy matrix using Supriya normalization
- Parameters:
matrix (ndarray) – Matrix with Intuitionistic Fuzzy Sets
*args – Additional parameters
- Returns:
Normalized Intuitionistic Fuzzy matrix
- Return type:
ndarray
- pyifdm.methods.ifs.normalization.swap_normalization(matrix, types)[source]
Calculates the normalized value of Intuitionistic Fuzzy matrix using Swap normalization
- Parameters:
matrix (ndarray) – Matrix with Intuitionistic Fuzzy Sets
types (ndarray) – Types of criteria, 1 profit, -1 cost
- Returns:
Normalized Intuitionistic Fuzzy matrix
- Return type:
ndarray
Score functions
- pyifdm.methods.ifs.score.chen_score_1(a)[source]
Calculates score of the Intuitionistic Fuzzy Set (u, v) and returns a crisp value. Uses a formula: (u - v)
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Set (u, v)
- Returns:
Crisp value
- Return type:
float
- pyifdm.methods.ifs.score.chen_score_2(a, y=0.5)[source]
Calculates score of the Intuitionistic Fuzzy Set (u, v) and returns a crisp value. Uses a formula: (y * u + (1 - y) * (1 - v))
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Set (u, v)
y (float, default=0.5) – Adjusting parameter
- Returns:
Crisp value
- Return type:
float
- pyifdm.methods.ifs.score.kharal_score_1(a)[source]
Calculates score of the Intuitionistic Fuzzy Set (u, v) and returns a crisp value. Uses a formula: (u - (v + (1 - u - v)) / 2)
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Set (u, v)
- Returns:
Crisp value
- Return type:
float
- pyifdm.methods.ifs.score.kharal_score_2(a)[source]
Calculates score of the Intuitionistic Fuzzy Set (u, v) and returns a crisp value. Uses a formula: (u + v) / 2 - (1 - u - v)
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Set (u, v)
- Returns:
Crisp value
- Return type:
float
- pyifdm.methods.ifs.score.liu_wang_score(a)[source]
Calculates score of the Intuitionistic Fuzzy Set (u, v) and returns a crisp value. Uses a formula: u + u * (1 - u - v)
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Set (u, v)
- Returns:
Crisp value
- Return type:
float
- pyifdm.methods.ifs.score.supriya_score(a)[source]
Calculates score of the Intuitionistic Fuzzy Set (u, v) and returns a crisp value. Uses a formula: (u - v * (1 - u - v))
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Set (u, v)
- Returns:
Crisp value
- Return type:
float
- pyifdm.methods.ifs.score.thakur_score(a)[source]
Calculates score of the Intuitionistic Fuzzy Set (u, v) and returns a crisp value. Uses a formula: (u**v - v**2)
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Set (u, v)
- Returns:
Crisp value
- Return type:
float
- pyifdm.methods.ifs.score.wan_dong_score_1(a)[source]
Calculates score of the Intuitionistic Fuzzy Set (u, v) and returns a crisp value. Uses a formula: 1/2 * ((u - v) / 2 + 1)
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Set (u, v)
- Returns:
Crisp value
- Return type:
float
- pyifdm.methods.ifs.score.wan_dong_score_2(a)[source]
Calculates score of the Intuitionistic Fuzzy Set (u, v) and returns a crisp value. Uses a formula: ((u - v) + 1) / 2
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Set (u, v)
- Returns:
Crisp value
- Return type:
float
- pyifdm.methods.ifs.score.wei_score(a)[source]
Calculates score of the Intuitionistic Fuzzy Set (u, v) and returns a crisp value. Uses a formula (1 - u - v)
- Parameters:
a (ndarray) – Intuitionistic Fuzzy Set (u, v)
- Returns:
Crisp value
- Return type:
float