From f8357f4bd2798dda832a8c3f8510baa7331b6c3e Mon Sep 17 00:00:00 2001
From: Tim O'Donnell <timodonnell@gmail.com>
Date: Mon, 24 Jun 2019 12:56:25 -0400
Subject: [PATCH] fix
---
mhcflurry/class1_neural_network.py | 10 +++++++---
1 file changed, 7 insertions(+), 3 deletions(-)
diff --git a/mhcflurry/class1_neural_network.py b/mhcflurry/class1_neural_network.py
index db7be791..d2d36761 100644
--- a/mhcflurry/class1_neural_network.py
+++ b/mhcflurry/class1_neural_network.py
@@ -612,7 +612,7 @@ class Class1NeuralNetwork(object):
"Using amino acid distribution for random negative:\n%s" % (
str(aa_distribution.to_dict())))
- y_values = from_ic50(affinities)
+ y_values = from_ic50(numpy.array(affinities, copy=False))
assert numpy.isnan(y_values).sum() == 0, y_values
if inequalities is not None:
# Reverse inequalities because from_ic50() flips the direction
@@ -649,9 +649,13 @@ class Class1NeuralNetwork(object):
x_dict_without_random_negatives[key] = (
x_dict_without_random_negatives[key][shuffle_permutation])
if sample_weights is not None:
- sample_weights = sample_weights[shuffle_permutation]
+ sample_weights = numpy.array(sample_weights, copy=False)[
+ shuffle_permutation
+ ]
if output_indices is not None:
- output_indices = output_indices[shuffle_permutation]
+ output_indices = numpy.array(output_indices, copy=False)[
+ shuffle_permutation
+ ]
loss = get_loss(self.hyperparameters['loss'])
--
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