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# GPy

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```    """
from GPy.likelihoods.gaussian import Gaussian
import GPy

num_inputs = 13
```
```def gplvm_oil_100(optimize=True, verbose=1, plot=True):
import GPy
data = GPy.util.datasets.oil_100()
Y = data['X']
# create simple GP model
```
```def sparse_gplvm_oil(optimize=True, verbose=0, plot=True, N=100, Q=6, num_inducing=15, max_iters=50):
import GPy
_np.random.seed(0)
data = GPy.util.datasets.oil()
Y = data['X'][:N]
```
```def swiss_roll(optimize=True, verbose=1, plot=True, N=1000, num_inducing=15, Q=4, sigma=.2):
import GPy
from GPy.util.datasets import swiss_roll_generated
from GPy.models import BayesianGPLVM

```
```def bgplvm_oil(optimize=True, verbose=1, plot=True, N=200, Q=7, num_inducing=40, max_iters=1000, **k):
import GPy
from GPy.likelihoods import Gaussian
from matplotlib import pyplot as plt

```

```    """
from GPy.likelihoods.gaussian import Gaussian
import GPy

num_inputs = 13
```
```def gplvm_oil_100(optimize=True, verbose=1, plot=True):
import GPy
data = GPy.util.datasets.oil_100()
Y = data['X']
# create simple GP model
```
```def sparse_gplvm_oil(optimize=True, verbose=0, plot=True, N=100, Q=6, num_inducing=15, max_iters=50):
import GPy
_np.random.seed(0)
data = GPy.util.datasets.oil()
Y = data['X'][:N]
```
```def swiss_roll(optimize=True, verbose=1, plot=True, N=1000, num_inducing=15, Q=4, sigma=.2):
import GPy
from GPy.util.datasets import swiss_roll_generated
from GPy.models import BayesianGPLVM

```
```def bgplvm_oil(optimize=True, verbose=1, plot=True, N=200, Q=7, num_inducing=40, max_iters=1000, **k):
import GPy
from GPy.likelihoods import Gaussian
from matplotlib import pyplot as plt

```

```import unittest
import numpy as np
import GPy
import inspect
import pkgutil
```

```pb.ion()
import numpy as np
import GPy

def tuto_GP_regression(optimize=True, plot=True):
```

```import pylab as pb
import numpy as np
import GPy

def toy_1d(optimize=True, plot=True):
```

```import pylab as pb
import numpy as np
import GPy

def olympic_marathon_men(optimize=True, plot=True):
```

```import GPy
import numpy as np
import matplotlib.pyplot as plt
from GPy.util import datasets

```

```"""
import pylab as pb
import GPy

default_seed = 10000
```

```import unittest
import numpy as np
import GPy
import inspect
import pkgutil
```

```pb.ion()