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better handling of missing pods in examples

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This commit is contained in:
James Hensman 2014-11-05 14:09:52 +00:00
parent 6f06646437
commit facd24cd5f
1 changed files with 24 additions and 8 deletions
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32
GPy/examples/regression.py
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@ -14,7 +14,9 @@ import GPy
def olympic_marathon_men(optimize=True, plot=True):
"""Run a standard Gaussian process regression on the Olympic marathon data."""
try:import pods
except ImportError:print 'pods unavailable, see https://github.com/sods/ods for example datasets'
except ImportError:
print 'pods unavailable, see https://github.com/sods/ods for example datasets'
return
data = pods.datasets.olympic_marathon_men()
# create simple GP Model
@ -85,7 +87,9 @@ def epomeo_gpx(max_iters=200, optimize=True, plot=True):
to load in the data.
"""
try:import pods
except ImportError:print 'pods unavailable, see https://github.com/sods/ods for example datasets'
except ImportError:
print 'pods unavailable, see https://github.com/sods/ods for example datasets'
return
data = pods.datasets.epomeo_gpx()
num_data_list = []
for Xpart in data['X']:
@ -130,7 +134,9 @@ def multiple_optima(gene_number=937, resolution=80, model_restarts=10, seed=1000
log_SNRs = np.linspace(-3., 4., resolution)
try:import pods
except ImportError:print 'pods unavailable, see https://github.com/sods/ods for example datasets'
except ImportError:
print 'pods unavailable, see https://github.com/sods/ods for example datasets'
return
data = pods.datasets.della_gatta_TRP63_gene_expression(data_set='della_gatta',gene_number=gene_number)
# data['Y'] = data['Y'][0::2, :]
# data['X'] = data['X'][0::2, :]
@ -212,7 +218,9 @@ def _contour_data(data, length_scales, log_SNRs, kernel_call=GPy.kern.RBF):
def olympic_100m_men(optimize=True, plot=True):
"""Run a standard Gaussian process regression on the Rogers and Girolami olympics data."""
try:import pods
except ImportError:print 'pods unavailable, see https://github.com/sods/ods for example datasets'
except ImportError:
print 'pods unavailable, see https://github.com/sods/ods for example datasets'
return
data = pods.datasets.olympic_100m_men()
# create simple GP Model
@ -231,7 +239,9 @@ def olympic_100m_men(optimize=True, plot=True):
def toy_rbf_1d(optimize=True, plot=True):
"""Run a simple demonstration of a standard Gaussian process fitting it to data sampled from an RBF covariance."""
try:import pods
except ImportError:print 'pods unavailable, see https://github.com/sods/ods for example datasets'
except ImportError:
print 'pods unavailable, see https://github.com/sods/ods for example datasets'
return
data = pods.datasets.toy_rbf_1d()
# create simple GP Model
@ -247,7 +257,9 @@ def toy_rbf_1d(optimize=True, plot=True):
def toy_rbf_1d_50(optimize=True, plot=True):
"""Run a simple demonstration of a standard Gaussian process fitting it to data sampled from an RBF covariance."""
try:import pods
except ImportError:print 'pods unavailable, see https://github.com/sods/ods for example datasets'
except ImportError:
print 'pods unavailable, see https://github.com/sods/ods for example datasets'
return
data = pods.datasets.toy_rbf_1d_50()
# create simple GP Model
@ -364,7 +376,9 @@ def toy_ARD_sparse(max_iters=1000, kernel_type='linear', num_samples=300, D=4, o
def robot_wireless(max_iters=100, kernel=None, optimize=True, plot=True):
"""Predict the location of a robot given wirelss signal strength readings."""
try:import pods
except ImportError:print 'pods unavailable, see https://github.com/sods/ods for example datasets'
except ImportError:
print 'pods unavailable, see https://github.com/sods/ods for example datasets'
return
data = pods.datasets.robot_wireless()
# create simple GP Model
@ -390,7 +404,9 @@ def robot_wireless(max_iters=100, kernel=None, optimize=True, plot=True):
def silhouette(max_iters=100, optimize=True, plot=True):
"""Predict the pose of a figure given a silhouette. This is a task from Agarwal and Triggs 2004 ICML paper."""
try:import pods
except ImportError:print 'pods unavailable, see https://github.com/sods/ods for example datasets'
except ImportError:
print 'pods unavailable, see https://github.com/sods/ods for example datasets'
return
data = pods.datasets.silhouette()
# create simple GP Model