# Path: alfpy/word_distance.py
# def geometric_mean(values):
#     def pwdist_euclid_squared(self, seq1idx, seq2idx):
#     def pwdist_euclid_norm(self, seq1idx, seq2idx):
#     def pwdist_euclid_seqlen1(self, seq1idx, seq2idx):
#     def pwdist_euclid_seqlen2(self, seq1idx, seq2idx):
#     def __angle_cos(self, seq1idx, seq2idx):
#     def pwdist_angle_cos_diss(self, seq1idx, seq2idx):
#     def pwdist_angle_cos_evol(self, seq1idx, seq2idx):
#     def pwdist_manhattan(self, seq1idx, seq2idx):
#     def pwdist_diff_abs_add(self, seq1idx, seq2idx):
#     def pwdist_chebyshev(self, seq1idx, seq2idx):
#     def pwdist_braycurtis(self, seq1idx, seq2idx):
#     def pwdist_diff_abs_mult(self, seq1idx, seq2idx):
#     def pwdist_diff_abs_mult1(self, seq1idx, seq2idx):
#     def pwdist_diff_abs_mult2(self, seq1idx, seq2idx):
#     def pwdist_kld(self, seq1idx, seq2idx):
#     def pwdist_jsd(self, seq1idx, seq2idx):
#         def entropy(p, q):
#     def pwdist_google(self, seq1idx, seq2idx):
#     def pwdist_lcc(self, seq1idx, seq2idx):
#     def pwdist_canberra(self, seq1idx, seq2idx):
#     def pwdist_minkowski(self, seq1idx, seq2idx, p=2):
# def main():
# class Distance(distance.Distance):
#         _P = x + 0.0000001
#         _Q = y + 0.0000001
#         _M = 0.5 * (_P + _Q)
# 
# Path: alfpy/utils/distmatrix.py
# def create(id_list, distance):
# def read_highcharts_matrix(id_list, data):
#     def __init__(self, id_list, data):
#     def normalize(self):
#     def __iter__(self):
#     def writer(self, handle, f, decimal_places):
#     def display(self, f="phylip", decimal_places=7):
#     def write_to_file(self, handle, f="phylip", decimal_places=7):
#     def highcharts(self):
#     def format(self, decimal_places=7):
#     def min(self):
#     def max(self):
#     def is_zero(self):
#     def __repr__(self):
# class Matrix():


import numpy as np
import os
import unittest
from alfpy import word_distance
from alfpy.utils import distmatrix
from . import utils




class TestDistMatrix(unittest.TestCase):

    def setUp(self):
        id_list = ['seq1', 'seq2', 'seq3']
        data = np.array([[0, 0.3531587, 0.35509333],
                         [0.3531587, 0, 0.295394],
                         [0.35509333, 0.295394, 0.]
                         ])

# Path: alfpy/word_distance.py
# def geometric_mean(values):
#     def pwdist_euclid_squared(self, seq1idx, seq2idx):
#     def pwdist_euclid_norm(self, seq1idx, seq2idx):
#     def pwdist_euclid_seqlen1(self, seq1idx, seq2idx):
#     def pwdist_euclid_seqlen2(self, seq1idx, seq2idx):
#     def __angle_cos(self, seq1idx, seq2idx):
#     def pwdist_angle_cos_diss(self, seq1idx, seq2idx):
#     def pwdist_angle_cos_evol(self, seq1idx, seq2idx):
#     def pwdist_manhattan(self, seq1idx, seq2idx):
#     def pwdist_diff_abs_add(self, seq1idx, seq2idx):
#     def pwdist_chebyshev(self, seq1idx, seq2idx):
#     def pwdist_braycurtis(self, seq1idx, seq2idx):
#     def pwdist_diff_abs_mult(self, seq1idx, seq2idx):
#     def pwdist_diff_abs_mult1(self, seq1idx, seq2idx):
#     def pwdist_diff_abs_mult2(self, seq1idx, seq2idx):
#     def pwdist_kld(self, seq1idx, seq2idx):
#     def pwdist_jsd(self, seq1idx, seq2idx):
#         def entropy(p, q):
#     def pwdist_google(self, seq1idx, seq2idx):
#     def pwdist_lcc(self, seq1idx, seq2idx):
#     def pwdist_canberra(self, seq1idx, seq2idx):
#     def pwdist_minkowski(self, seq1idx, seq2idx, p=2):
# def main():
# class Distance(distance.Distance):
#         _P = x + 0.0000001
#         _Q = y + 0.0000001
#         _M = 0.5 * (_P + _Q)
# 
# Path: alfpy/utils/distmatrix.py
# def create(id_list, distance):
# def read_highcharts_matrix(id_list, data):
#     def __init__(self, id_list, data):
#     def normalize(self):
#     def __iter__(self):
#     def writer(self, handle, f, decimal_places):
#     def display(self, f="phylip", decimal_places=7):
#     def write_to_file(self, handle, f="phylip", decimal_places=7):
#     def highcharts(self):
#     def format(self, decimal_places=7):
#     def min(self):
#     def max(self):
#     def is_zero(self):
#     def __repr__(self):
# class Matrix():


# Path: tests/test_distmatrix.py
import numpy as np
import os
import unittest
from alfpy import word_distance
from alfpy.utils import distmatrix
from . import utils





class TestDistMatrix(unittest.TestCase):

    def setUp(self):
        id_list = ['seq1', 'seq2', 'seq3']
        data = np.array([[0, 0.3531587, 0.35509333],
                         [0.3531587, 0, 0.295394],
                         [0.35509333, 0.295394, 0.]
                         ])

        self.matrix = distmatrix.Matrix(id_list, data)