Mit matplotlib auf Mac für Python 2.7

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Http://scikit-learn.org/stable/auto_examples/linear_model/plot_iris_logistic.html

#!/usr/bin/python # -*- coding: utf-8 -*- """ ========================================================= Logistic Regression 3-class Classifier ========================================================= Show below is a logistic-regression classifiers decision boundaries on the `iris <http://en.wikipedia.org/wiki/Iris_flower_data_set>`_ dataset. The datapoints are colored according to their labels. """ print(__doc__) # Code source: Gaël Varoquaux # Modified for documentation by Jaques Grobler # License: BSD 3 clause import numpy as np import matplotlib.pyplot as plt from sklearn import linear_model, datasets # import some data to play with iris = datasets.load_iris() X = iris.data[:, :2] # we only take the first two features. Y = iris.target h = .02 # step size in the mesh logreg = linear_model.LogisticRegression(C=1e5) # we create an instance of Neighbours Classifier and fit the data. logreg.fit(X, Y) # Plot the decision boundary. For that, we will assign a color to each # point in the mesh [x_min, m_max]x[y_min, y_max]. x_min, x_max = X[:, 0].min() - .5, X[:, 0].max() + .5 y_min, y_max = X[:, 1].min() - .5, X[:, 1].max() + .5 xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h)) Z = logreg.predict(np.c_[xx.ravel(), yy.ravel()]) # Put the result into a color plot Z = Z.reshape(xx.shape) plt.figure(1, figsize=(4, 3)) plt.pcolormesh(xx, yy, Z, cmap=plt.cm.Paired) # Plot also the training points plt.scatter(X[:, 0], X[:, 1], c=Y, edgecolors='k', cmap=plt.cm.Paired) plt.xlabel('Sepal length') plt.ylabel('Sepal width') plt.xlim(xx.min(), xx.max()) plt.ylim(yy.min(), yy.max()) plt.xticks(()) plt.yticks(()) plt.show() 

 Traceback (most recent call last): File "/Users/foo/personal/law/justech/featureExtraction/testLogisticRegression.py", line 22, in <module> import matplotlib.pyplot as plt File "/Users/foo/miniconda2/lib/python2.7/site-packages/matplotlib/pyplot.py", line 114, in <module> _backend_mod, new_figure_manager, draw_if_interactive, _show = pylab_setup() File "/Users/foo/miniconda2/lib/python2.7/site-packages/matplotlib/backends/__init__.py", line 32, in pylab_setup globals(),locals(),[backend_name],0) File "/Users/foo/miniconda2/lib/python2.7/site-packages/matplotlib/backends/backend_macosx.py", line 24, in <module> from matplotlib.backends import _macosx RuntimeError: Python is not installed as a framework. The Mac OS X backend will not be able to function correctly if Python is not installed as a framework. See the Python documentation for more information on installing Python as a framework on Mac OS X. Please either reinstall Python as a framework, or try one of the other backends. If you are Working with Matplotlib in a virtual enviroment see 'Working with Matplotlib in Virtual environments' in the Matplotlib FAQ 

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