From fa353a34ca4d7b9ca615fcc549b21c4faa829470 Mon Sep 17 00:00:00 2001
From: Alex Rubinsteyn <alex.rubinsteyn@gmail.com>
Date: Tue, 10 May 2016 13:08:59 -0400
Subject: [PATCH] fixed obscure shape bug on empty arrays
---
.../class1_allele_specific_kmer_ic50_predictor_base.py | 2 +-
mhcflurry/dataset.py | 8 ++++----
mhcflurry/training_helpers.py | 6 ++----
3 files changed, 7 insertions(+), 9 deletions(-)
diff --git a/mhcflurry/class1_allele_specific_kmer_ic50_predictor_base.py b/mhcflurry/class1_allele_specific_kmer_ic50_predictor_base.py
index 0d2ffd70..3a242d8b 100644
--- a/mhcflurry/class1_allele_specific_kmer_ic50_predictor_base.py
+++ b/mhcflurry/class1_allele_specific_kmer_ic50_predictor_base.py
@@ -175,5 +175,5 @@ class Class1AlleleSpecificKmerIC50PredictorBase(IC50PredictorBase):
sample_weights=sample_weights,
X_pretrain=X_pretrain,
ic50_pretrain=ic50_pretrain,
- sample_weights_pretrain=sample_weights,
+ sample_weights_pretrain=sample_weights_pretrain,
**kwargs)
diff --git a/mhcflurry/dataset.py b/mhcflurry/dataset.py
index 67fed68d..d58180d6 100644
--- a/mhcflurry/dataset.py
+++ b/mhcflurry/dataset.py
@@ -437,10 +437,10 @@ class Dataset(object):
"""
if len(self.peptides) == 0:
return (
- np.array([[]], dtype=int),
- np.array([], dtype=float),
- np.array([], dtype=float),
- np.array([], dtype=int)
+ np.empty((0, kmer_size), dtype=int),
+ np.empty((0,), dtype=float),
+ np.empty((0,), dtype=float),
+ np.empty((0,), dtype=int)
)
X_index, _, original_peptide_indices, counts = \
diff --git a/mhcflurry/training_helpers.py b/mhcflurry/training_helpers.py
index c61adac8..5a3be5c4 100644
--- a/mhcflurry/training_helpers.py
+++ b/mhcflurry/training_helpers.py
@@ -49,7 +49,6 @@ def check_encoded_array_shapes(X, Y, sample_weights):
sample_weights.shape,))
n_samples, n_dims = X.shape
-
if len(Y) != n_samples:
raise ValueError("Mismatch between len(X) = %d and len(Y) = %d" % (
n_samples, len(Y)))
@@ -78,7 +77,6 @@ def combine_training_arrays(
"""
X = np.asarray(X)
Y = np.asarray(Y)
-
if sample_weights is None:
sample_weights = np.ones_like(Y)
else:
@@ -87,8 +85,8 @@ def combine_training_arrays(
n_samples, n_dims = check_encoded_array_shapes(X, Y, sample_weights)
if X_pretrain is None or Y_pretrain is None:
- X_pretrain = np.empty((0, n_dims), dtype=X.dtype)
- Y_pretrain = np.empty((0,), dtype=Y.dtype)
+ X_pretrain = np.zeros((0, n_dims), dtype=X.dtype)
+ Y_pretrain = np.zeros((0,), dtype=Y.dtype)
else:
X_pretrain = np.asarray(X_pretrain)
Y_pretrain = np.asarray(Y_pretrain)
--
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