def test_on_random_sized():
data_obj = trivial_gen.balanced_random_size_gauss_blobs(
10.0, 2.0, 5, 100, 5, 0.5)
data_obj = partitioning.k_means(data_obj)
visu.plot_coords_label_color(data_obj)
visu.plot_centers_by_label_color(data_obj)
plt.show()
def _screenshot(data_obj):
global n
visu.plot_coords_label_color(data_obj)
visu.plot_centers_by_label_color(data_obj)
n += 1
plt.savefig("kmeans_frame_" + str(n) + ".png")
plt.close()
def croissants():
data = trivial_gen.croissants(100, 5.0, 0.5)
visu.plot_coords_label_color(data)
visu.plot_centers_by_label_color(data)
plt.show()
data = partitioning.k_means(data, initialisation="kmeans_++")
visu.plot_coords_label_color(data)
visu.plot_centers_by_label_color(data)
plt.show()
def pront(data_obj,name):
print("scikit_silhouette_score :"+str(standalone.scikit_silhouette_score(data_obj)))
print("scikit_calinski_harabaz_score :"+str(standalone.scikit_calinski_harabaz_score(data_obj)))
print("dunn_index :"+str(standalone.dunn_index(data_obj)))
print(result_to_string(standalone.general_evaluate_clustered_object(data_obj)))
visu.plot_coords_label_color(data_obj)
visu.plot_centers_by_label_color(data_obj)
plt.savefig(name+".png")
plt.close()
def showfiles():
for i in [
"balanced_gauss", "big_gauss", "difficult_gauss", "scars",
"different_sizes"
]:
for j in range(10):
data_obj = Coords()
data_obj.read_file("k_means_data" + "/" + i + "/data" + str(j))
visu.plot_coords_label_color(data_obj)
visu.plot_centers_by_label_color(data_obj)
plt.show()
def add_step(self, data_obj):
print("frame:" + str(self.step_count))
self.step_count = self.step_count + 1
name = str(self.step_count)
self.filenames.append(name)
if self.draw_labels:
visu.plot_coords_label_color(data_obj)
else:
visu.plot_coords_label_num(data_obj)
if self.draw_centers:
visu.plot_centers_by_label_color(data_obj)
plt.savefig(self.filename + "/" + name + ".png")
plt.close()
from py_osm_cluster.generator import trivial_gen as trivial_gen import py_osm_cluster.visualisation.visualisation as visu from py_osm_cluster.util.coords import Coords as C import matplotlib.pyplot as plt data_obj = trivial_gen.balanced_multiple_weighted_gauss_blobs(10.0,[0.5,2.0],50,5,[0.2,2.0]) visu.plot_coords_label_color(data_obj) visu.plot_centers_by_label_color(data_obj) plt.show()
#coords = trivial_gen.croissants(30,5.0,0.5)
anim_obj = anim.Animation("anim_1",True,True,0.8)
def pront(data_obj):
print("hello")
print(data_obj.c_positions)
newcoords = deepcopy(coords)
newcoords = partitioning.k_means(newcoords,on_step=anim_obj.add_step,initialisation="forgy")
anim_obj.compile()
#print(Std.statistics_distance_multi_cluster(newcoords))
#print(Std.triangulation_distance_within(newcoords.coords))
#visu.plot_coords(newcoords)
visu.plot_coords_label_color(newcoords)
visu.plot_centers_by_label_color(newcoords)
plt.show()
"""
coords = trivial_gen.balanced_multiple_weighted_gauss_blobs(
10.0, [1.0, 0.5], 20, 5, [1.5, 0.5])
#print(coords)
visu.plot_coords_label_color(coords)
visu.plot_centers_by_label_color(coords)
plt.show()
def visualise(data_obj, name):
#plt.xlabel(name)
visu.plot_coords_label_color(data_obj)
visu.plot_centers_by_label_color(data_obj)
plt.savefig(name + ".png")
plt.close()