"""!

@brief Unit-tests for other cluster functionality

@authors Andrei Novikov (pyclustering@yandex.ru)
@date 2014-2020
@copyright BSD-3-Clause

"""

import unittest;

# Generate images without having a window appear.
import matplotlib;
matplotlib.use('Agg');

import matplotlib.pyplot as plt;

import random;

from pyclustering.samples.definitions import SIMPLE_SAMPLES, FCPS_SAMPLES;

from pyclustering.utils import read_sample;

from pyclustering.cluster import cluster_visualizer;
from pyclustering.cluster.dbscan import dbscan;
from pyclustering.cluster.cure import cure;


class Test(unittest.TestCase):
    def testVisualize1DClustersOneCanvas(self):
        sample = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE8);
 
        dbscan_instance = dbscan(sample, 1.0, 3, False);
        dbscan_instance.process();
        clusters = dbscan_instance.get_clusters();
          
        visualizer = cluster_visualizer();
        visualizer.append_clusters(clusters, sample, markersize = 5);
        visualizer.show();
 
    def testVisualize1DClustersOneCanvasSampleOnly(self):
        clusters = [ [[0.1], [0.2], [0.5]], [[0.1], [0.2], [0.5]] ];
          
        visualizer = cluster_visualizer();
        visualizer.append_clusters(clusters, markersize = 5);
        visualizer.show();
     
    def testVisualize1DClustersTwoCanvases(self):
        sample_simple7 = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE7);
        sample_simple8 = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE8);
     
        # Two canvas visualization
        visualizer = cluster_visualizer(2);
        visualizer.append_clusters([ sample_simple7 ], None, 0, markersize = 30);
        visualizer.append_clusters([ sample_simple8 ], None, 1, markersize = 30);
        visualizer.show();
 
    def testVisualize3DClustersOneCanvas(self):
        sample = read_sample(FCPS_SAMPLES.SAMPLE_HEPTA);
          
        dbscan_instance = dbscan(sample, 0.5, 3, False);
        dbscan_instance.process();
        clusters = dbscan_instance.get_clusters();
          
        visualizer = cluster_visualizer();
        visualizer.append_clusters(clusters, sample, markersize = 30);
        visualizer.show();
 
    def testVisualize3DClustersTwoCanvases(self):
        sample_tetra = read_sample(FCPS_SAMPLES.SAMPLE_TETRA);
        sample_hepta = read_sample(FCPS_SAMPLES.SAMPLE_HEPTA);
              
        # Two canvas visualization
        visualizer = cluster_visualizer(2);
        visualizer.append_clusters([ sample_tetra ], None, 0, markersize = 30);
        visualizer.append_clusters([ sample_hepta ], None, 1, markersize = 30);
        visualizer.show();
      
    def testVisualize2DClustersOneCanvas(self):
        sample = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE4);
 
        dbscan_instance = dbscan(sample, 0.7, 3, False);
        dbscan_instance.process();
        clusters = dbscan_instance.get_clusters();
          
        visualizer = cluster_visualizer();
        visualizer.append_clusters(clusters, sample, markersize = 5);
        visualizer.show();
          
    def testVisualize2DClustersThreeCanvases(self):
        sample_simple1 = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE1);
        sample_simple2 = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE2);
        sample_simple3 = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE3);
              
        dbscan_instance = dbscan(sample_simple1, 0.4, 2, False);
        dbscan_instance.process();
        clusters_sample1 = dbscan_instance.get_clusters();
              
        dbscan_instance = dbscan(sample_simple2, 1, 2, False);
        dbscan_instance.process();
        clusters_sample2 = dbscan_instance.get_clusters();
      
        dbscan_instance = dbscan(sample_simple3, 0.7, 3, False);
        dbscan_instance.process();
        clusters_sample3 = dbscan_instance.get_clusters();
              
        visualizer = cluster_visualizer(3);
        visualizer.append_clusters(clusters_sample1, sample_simple1, 0, markersize = 5);
        visualizer.append_clusters(clusters_sample2, sample_simple2, 1, markersize = 5);
        visualizer.append_clusters(clusters_sample3, sample_simple3, 2, markersize = 5);
        visualizer.show();
      
    def testVisualize2DAnd3DClusters(self):
        sample_2d = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE1);
        sample_3d = read_sample(FCPS_SAMPLES.SAMPLE_HEPTA);
          
        visualizer = cluster_visualizer(2, 2);
        visualizer.append_clusters([ sample_2d ], None, 0, markersize = 5);
        visualizer.append_clusters([ sample_3d ], None, 1, markersize = 30);
        visualizer.show();
     
    def testVisualizeRectangeRepresentation2x2(self):
        sample_simple1 = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE1);
        sample_simple2 = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE2);
        sample_simple3 = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE3);
           
        visualizer = cluster_visualizer(3, 2);
        visualizer.append_clusters([ sample_simple1 ], None, 0, markersize = 5);
        visualizer.append_clusters([ sample_simple2 ], None, 1, markersize = 5);
        visualizer.append_clusters([ sample_simple3 ], None, 2, markersize = 5);
        visualizer.show();
     
    def testVisualizeRectangeRepresentation3x5(self):
        visualizer = cluster_visualizer(15, 5);
         
        for i in range(15):
            sample = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE1);
            visualizer.append_clusters([ sample ], None, i, markersize = 5);
         
        visualizer.show();
     
    def testVisualizeByDataOnly(self):
        visualizer = cluster_visualizer();
         
        sample = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE1);
        visualizer.append_clusters([ sample ]);
         
        visualizer.show();
     
    def testVisualizeHugeAmountClusters(self):
        visualizer = cluster_visualizer();
         
        data_clusters = [ [ [ random.random() ] ] for _ in range(0, 100) ];
        visualizer.append_clusters(data_clusters);

        visualizer.show();

    def testVisualizeOnExistedFigure(self):
        figure = plt.figure();
         
        sample = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE1);
         
        visualizer = cluster_visualizer();
        visualizer.append_clusters([ sample ]);
        visualizer.show(figure);
     
    def testVisualizeOnExistedFigureWithContent(self):
        figure = plt.figure();
        axis = figure.add_subplot(121);
        axis.plot(range(0, 10, 1), range(0, 10, 1), marker = 'o', color = 'blue', ls = '');
         
        sample = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE1);
         
        visualizer = cluster_visualizer(size_row = 2);
        visualizer.append_clusters([ sample ]);
        visualizer.show(figure);
    
    def testVisualizeOnExistedFigureWithContentByDefault(self):
        figure = plt.figure();
        axis = figure.add_subplot(211);
        axis.plot(range(0, 10, 1), range(0, 10, 1), marker = 'o', color = 'blue', ls = '');
        
        sample = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE1);
        
        visualizer = cluster_visualizer();
        visualizer.append_clusters([ sample ]);
        visualizer.show(figure);
    
    def testVisualizeClusterWithAttributes(self):
        sample = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE1);
        cure_instance = cure(sample, 2, 5, 0.5, False);
        cure_instance.process();
        
        clusters = cure_instance.get_clusters();
        representors = cure_instance.get_representors();
        means = cure_instance.get_means();
        
        visualizer = cluster_visualizer();
        visualizer.append_clusters(clusters, sample);
        
        for cluster_index in range(len(clusters)):
            visualizer.append_cluster_attribute(0, cluster_index, representors[cluster_index], '*', 10);
            visualizer.append_cluster_attribute(0, cluster_index, [ means[cluster_index] ], 'o');
        
        visualizer.show();