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Trying to get plotting working
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2 changed files with 12 additions and 11 deletions
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@ -90,9 +90,11 @@ extensions = ['sphinx.ext.autodoc',
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'ipython_directive',
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'ipython_directive',
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'ipython_console_highlighting',
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'ipython_console_highlighting',
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#'mathmpl',
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#'mathmpl',
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'only_directives',
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#'only_directives',
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'plot_directive',
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'matplotlib.sphinxext.plot_directive'
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#'plot_directive'
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]
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]
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plot_formats = [('png', 80), ('pdf', 50)]
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print "finished importing"
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print "finished importing"
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@ -122,7 +124,7 @@ class Mock(object):
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#import mock
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#import mock
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print "Mocking"
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print "Mocking"
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MOCK_MODULES = ['pylab', 'matplotlib', 'sympy', 'sympy.utilities', 'sympy.utilities.codegen', 'sympy.core.cache', 'sympy.core', 'sympy.parsing', 'sympy.parsing.sympy_parser']
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MOCK_MODULES = ['pylab', 'sympy', 'sympy.utilities', 'sympy.utilities.codegen', 'sympy.core.cache', 'sympy.core', 'sympy.parsing', 'sympy.parsing.sympy_parser']
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#'matplotlib', 'matplotlib.color', 'matplotlib.pyplot', 'pylab' ]
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#'matplotlib', 'matplotlib.color', 'matplotlib.pyplot', 'pylab' ]
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for mod_name in MOCK_MODULES:
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for mod_name in MOCK_MODULES:
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sys.modules[mod_name] = Mock()
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sys.modules[mod_name] = Mock()
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@ -9,14 +9,13 @@ Gaussian process regression tutorial
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.. plot::
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.. plot::
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import matplotlib.pyplot as plt
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import matplotlib.pyplot as plt
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import numpy as np
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import numpy as np
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x = np.random.randn(1000)
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x = np.random.randn(1000)
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plt.hist( x, 20)
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plt.hist( x, 20)
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plt.grid()
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plt.grid()
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plt.title(r'Normal: $\mu=%.2f, \sigma=%.2f$'%(x.mean(), x.std()))
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plt.title(r'Normal: $\mu=%.2f, \sigma=%.2f$'%(x.mean(), x.std()))
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plt.show()
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plt.show()
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We will see in this tutorial the basics for building a 1 dimensional and a 2 dimensional Gaussian process regression model, also known as a kriging model.
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We will see in this tutorial the basics for building a 1 dimensional and a 2 dimensional Gaussian process regression model, also known as a kriging model.
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