def make_test_globals():
"""Prepare global objects used in the doctests"""
print("Prepare doctest globals", flush=True)
# Test using a small data sample of 10000 random integers 0-255
# with 16 dimensions
hsne_data = np.random.randint(256, size=(10000, 16))
tsne_data = np.random.randint(256, size=(2000, 16))
# Create a sample hsne with 3 levels and
# save this to a sample file
hsne = nptsne.HSne(True)
hsne.create_hsne(hsne_data, 3)
file_name = "rnd10000x16.hsne"
hsne.save(file_name)
top_analysis = nptsne.hsne_analysis.Analysis(hsne, nptsne.hsne_analysis.EmbedderType.CPU)
print("End prepare doctest globals", flush=True)
return {
"sample_hsne": hsne,
"sample_analysis": top_analysis,
"sample_scale0": hsne.get_scale(0),
"sample_scale1": hsne.get_scale(1),
"sample_scale2": hsne.get_scale(2),
"sample_hsne_file": file_name,
"sample_hsne_data": hsne_data,
"sample_tsne_data": tsne_data,
"sample_texture_tsne": nptsne.TextureTsne(),
"sample_texture_tsne_extended": nptsne.TextureTsneExtended()
}
def step_impl(context):
context.tsne = nptsne.TextureTsneExtended(False)
'data': mnist_raw['data'].T,
'target': mnist_raw['label'][0],
'COL_NAMES': ['label', 'data']
}
colors = [
'#EE3333', '#FF9900', '#FFEE00', '#AACC11', '#44AA77', '#0099EE',
'#0066BB', '#443388', '#992288', '#EE0077'
]
# norm = mcolors.Normalize(vmin=0, vmax=9)
# mcolors.ListedColormap(colors)
rc('lines', linewidth=2)
rc('lines', markersize=1)
tsne = nptsne.TextureTsneExtended(False)
embeddings = []
if tsne.init_transform(mnist['data']):
print('Init succeeded')
for i in range(20):
plt.figure(i + 1)
start = timer()
# reduce the forces from iteration 1000
if i == 10:
tsne.start_exaggeration_decay()
print(f'exaggeration stopping at {tsne.decay_started_at}')
embedding = tsne.run_transform(verbose=False, iterations=100)
end = timer()
print(f'got embedding in {end - start}')
print(f'iteration count {tsne.iteration_count}')
umap_embed = umap.UMAP().fit_transform(subData)
print(umap_embed.shape)
plt.figure(40)
print(subLabel)
print(umap_embed)
plt.scatter(umap_embed[..., 0],
umap_embed[..., 1],
c=subLabel,
cmap=mcolors.ListedColormap(colors),
facecolors='None',
marker='o')
plt.draw()
plt.savefig(f'testexum_00.png')
tsne = nptsne.TextureTsneExtended(verbose=True)
print(f'Init tSNE from umap, shape: {umap_embed.shape}')
if tsne.init_transform(subData, umap_embed):
print('Init from umap succeeded')
step_size = 100
for i in range(20):
plt.figure(i + 1)
start = timer()
exaggeration_iter = 100
# reduce the forces from 1000
if i == 10:
tsne.start_exaggeration_decay()
print(f'exaggeration stopping at {tsne.decay_started_at}')