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Fixed array2string bug for N > 1000 default printing

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This commit is contained in:
Alan Saul 2015-08-25 17:30:09 +03:00
parent f221a3b1fa
commit 12c335c62e
1 changed files with 13 additions and 9 deletions
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22
GPy/inference/optimization/stochastics.py
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@ -5,7 +5,7 @@ class StochasticStorage(object):
'''
This is a container for holding the stochastic parameters,
such as subset indices or step length and so on.
self.d has to be a list of lists:
[dimension indices, nan indices for those dimensions]
so that the minibatches can be used as efficiently as possible.10
@ -38,16 +38,17 @@ class SparseGPMissing(StochasticStorage):
import numpy as np
self.Y = model.Y_normalized
bdict = {}
#For N > 1000 array2string default crops
opt = np.get_printoptions()
np.set_printoptions(threshold='nan')
for d in range(self.Y.shape[1]):
inan = np.isnan(self.Y[:, d])
arr_str = np.array2string(inan,
np.inf, 0,
True, '',
formatter={'bool':lambda x: '1' if x else '0'})
inan = np.isnan(self.Y)[:, d]
arr_str = np.array2string(~inan, np.inf, 0, True, '', formatter={'bool':lambda x: '1' if x else '0'})
try:
bdict[arr_str][0].append(d)
except:
bdict[arr_str] = [[d], ~inan]
np.set_printoptions(**opt)
self.d = bdict.values()
class SparseGPStochastics(StochasticStorage):
@ -70,16 +71,19 @@ class SparseGPStochastics(StochasticStorage):
import numpy as np
self.d = np.random.choice(self.output_dim, size=self.batchsize, replace=False)
bdict = {}
opt = np.get_printoptions()
np.set_printoptions(threshold='nan')
for d in self.d:
inan = np.isnan(self.Y[:, d])
arr_str = int(np.array2string(inan,
np.inf, 0,
True, '',
arr_str = int(np.array2string(inan,
np.inf, 0,
True, '',
formatter={'bool':lambda x: '1' if x else '0'}), 2)
try:
bdict[arr_str][0].append(d)
except:
bdict[arr_str] = [[d], ~inan]
np.set_printoptions(**opt)
self.d = bdict.values()
def reset(self):