In [1]:

    

import numpy as np
from matplotlib import pyplot as plt
import matplotlib
from matplotlib import ticker

from sklearn import manifold, datasets, decomposition


    

In [2]:

    

from astroML.plotting import setup_text_plots
setup_text_plots(fontsize=8, usetex=True)


    

In [3]:

    

np.random.seed(0)

n_points = 1100
n_neighbors = 10
out_dim = 2

X, color = datasets.samples_generator.make_s_curve(n_points)


    

In [4]:

    

X[:, 1] -= 1
X[:, 1] *= 1.5
X[:, 2] *= 0.5


    

In [5]:

    

pca = decomposition.PCA(out_dim)
Y_pca = pca.fit_transform(X)

lle = manifold.LocallyLinearEmbedding(n_neighbors, out_dim, method='modified')
Y_lle = lle.fit_transform(X)

iso = manifold.Isomap(n_neighbors, out_dim)
Y_iso = iso.fit_transform(X)


    

In [6]:

    

fig = plt.figure(figsize=(5, 5))
fig.subplots_adjust(left=0.05, right=0.95,
                    bottom=0.05, top=0.9)


    

In [7]:

    

try:
    # matplotlib 1.0+ has a toolkit for generating 3D plots
    from mpl_toolkits.mplot3d import Axes3D
    ax1 = fig.add_subplot(221, projection='3d',
                          xticks=[], yticks=[], zticks=[])
    ax1.scatter(X[:, 0], X[:, 1], X[:, 2], c=color,
                cmap=plt.cm.jet, s=9, lw=0)
    ax1.view_init(11, -73)


    

    




  File "<ipython-input-7-16bf9b8130d2>", line 8
    ax1.view_init(11, -73)
                          ^
SyntaxError: invalid syntax

In [8]:

    

except:
    # In older versions, we'll have to wing it with a 2D plot
    ax1 = fig.add_subplot(221)

    # Create a projection to mimic 3D scatter-plot
    X_proj = X / (X.max(0) - X.min(0))
    X_proj -= X_proj.mean(0)
    R = np.array([[0.5, 0.0],
                  [0.1, 0.1],
                  [0.0, 0.5]])
    R /= np.sqrt(np.sum(R ** 2, 0))
    X_proj = np.dot(X_proj, R)

    # change line width with depth
    lw = X[:, 1].copy()
    lw -= lw.min()
    lw /= lw.max()
    lw = 1 - lw

    ax1.scatter(X_proj[:, 0], X_proj[:, 1], c=color,
                cmap=plt.cm.jet, s=9, lw=lw, zorder=10)

    # draw the shaded axes
    ax1.fill([-0.7, -0.3, -0.3, -0.7, -0.7],
             [-0.7, -0.3, 0.7, 0.3, -0.7], ec='k', fc='#DDDDDD', zorder=0)
    ax1.fill([-0.3, 0.7, 0.7, -0.3, -0.3],
             [-0.3, -0.3, 0.7, 0.7, -0.3], ec='k', fc='#DDDDDD', zorder=0)
    ax1.fill([-0.7, 0.3, 0.7, -0.3, -0.7],
             [-0.7, -0.7, -0.3, -0.3, -0.7], ec='k', fc='#DDDDDD', zorder=0)

    ax1.xaxis.set_major_locator(ticker.NullLocator())
    ax1.yaxis.set_major_locator(ticker.NullLocator())

#------------------------------------------------------------
# Plot the projections
subplots = [222, 223, 224]
titles = ['PCA projection', 'LLE projection', 'IsoMap projection']
Yvals = [Y_pca, Y_lle, Y_iso]


    

    




  File "<ipython-input-8-d11ecb0fedc0>", line 1
    except:
         ^
SyntaxError: invalid syntax

In [9]:

    

for (Y, title, subplot) in zip(Yvals, titles, subplots):
    ax = fig.add_subplot(subplot)
    ax.scatter(Y[:, 0], Y[:, 1], c=color, cmap=plt.cm.jet, s=9, lw=0)
    ax.set_title(title)
    ax.set_xticks([])
    ax.set_yticks([])


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-9-a9c86bf77ddf> in <module>()
----> 1 for (Y, title, subplot) in zip(Yvals, titles, subplots):
      2     ax = fig.add_subplot(subplot)
      3     ax.scatter(Y[:, 0], Y[:, 1], c=color, cmap=plt.cm.jet, s=9, lw=0)
      4     ax.set_title(title)
      5     ax.set_xticks([])

NameError: name 'Yvals' is not defined

In [10]:

    

%matplotlib inline


    

In [11]:

    

plt.show()


    

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