50 lines
1.4 KiB
Python
50 lines
1.4 KiB
Python
# based on: https://github.com/eakbas/tf-svm/blob/master/plot_boundary_on_data.py
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import numpy as np
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from matplotlib import pyplot as plt
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from matplotlib import colors
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def plotTwoFeatures(X,T,pred_func):
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if X.ndim!=2:
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raise ValueError('X be a matrix (2 dimensional array).')
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tp=False
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if X.shape[0]!=2 and X.shape[1]==2:
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X=X.T
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tp=True
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if X.shape[0]!=2:
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raise ValueError('X must contain exactly 2 features.')
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# determine canvas borders
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mins = np.amin(X,1);
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mins = mins - 0.1*np.abs(mins);
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maxs = np.amax(X,1);
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maxs = maxs + 0.1*maxs;
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## generate dense grid
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xs,ys = np.meshgrid(np.linspace(mins[0],maxs[0],300),
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np.linspace(mins[1], maxs[1], 300));
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# evaluate model on the dense grid
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try:
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Z = pred_func(np.c_[xs.flatten(), ys.flatten()].T);
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except:
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Z = pred_func(np.c_[xs.flatten(), ys.flatten()]);
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if tp:
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Z=Z.T
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T=T.T
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if Z.ndim>1 and Z.shape[0]>1: # onehot? -> convert
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Z=Z.argmax(0)
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Z = Z.reshape(xs.shape)
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if T.ndim>1 and T.shape[0]>1: # onehot? -> convert
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T=T.argmax(0)
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# Plot the contour and training examples
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plt.contourf(xs, ys, Z, cmap=plt.cm.Spectral)
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plt.scatter(X[0,:], X[1,:], c=T, s=50,
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cmap=colors.ListedColormap(['orange', 'blue', 'green']))
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plt.show()
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