import numpy as np
import pandas as pd
import plotly.express as px
from sklearn.manifold import MDS as sklearn_MDS
import time

from mdscuda import MDS, mds_fit, minkowski_pairs

df = px.data.iris()
X = df.iloc[:, :4].to_numpy()

tick = time.perf_counter()
DELTA = minkowski_pairs(X, sqform = False)
mds = MDS(n_dims = 2, max_iter = 100, n_init = 100, verbosity = 1)
x = mds.fit(DELTA)
#print("mds r2: {}".format(mds.r2))
print('mdscuda time: ', time.perf_counter() - tick)

fig = px.scatter(x=x[:, 0], y=x[:, 1], color=df['species'], title='Iris mdscuda.MDS embedding')
fig.update_traces(marker=dict(size=9, opacity=.8))
fig.show()
#fig.write_html("iris-mdscuda.html")

tick = time.perf_counter()
embedding = sklearn_MDS(n_components = 2, max_iter=100, n_init = 100, verbose = 1)
X_transformed = embedding.fit_transform(X)
print(embedding.stress_)
print('sklearn', time.perf_counter() - tick)

fig = px.scatter(x=X_transformed[:, 0], y=X_transformed[:, 1], color=df['species'], title='Iris sklearn.manifold.MDS embedding')
fig.update_traces(marker=dict(size=9, opacity=.8))
fig.show()
#fig.write_html("iris-sklearn.html")
import numpy as np
import pandas as pd
import plotly.express as px
from sklearn.manifold import MDS as sklearn_MDS
import time

from mdscuda import MDS, mds_fit, minkowski_pairs

df = px.data.iris()
X = df.iloc[:, :4].to_numpy()

tick = time.perf_counter()
DELTA = minkowski_pairs(X, sqform = False)
mds = MDS(n_dims = 2, max_iter = 100, n_init = 100, verbosity = 1)
x = mds.fit(DELTA)
#print("mds r2: {}".format(mds.r2))
print('mdscuda time: ', time.perf_counter() - tick)

fig = px.scatter(x=x[:, 0], y=x[:, 1], color=df['species'], title='Iris mdscuda.MDS embedding')
fig.update_traces(marker=dict(size=9, opacity=.8))
fig.show()
#fig.write_html("iris-mdscuda.html")

tick = time.perf_counter()
embedding = sklearn_MDS(n_components = 2, max_iter=100, n_init = 100, verbose = 1)
X_transformed = embedding.fit_transform(X)
print(embedding.stress_)
print('sklearn', time.perf_counter() - tick)

fig = px.scatter(x=X_transformed[:, 0], y=X_transformed[:, 1], color=df['species'], title='Iris sklearn.manifold.MDS embedding')
fig.update_traces(marker=dict(size=9, opacity=.8))
fig.show()
#fig.write_html("iris-sklearn.html")
#print("mds r2: {}".format(mds.r2)) #fig.write_html("iris-mdscuda.html") #fig.write_html("iris-sklearn.html")