From 9f1bb326b1af2320d13da04adfa5977afd781589 Mon Sep 17 00:00:00 2001
From: Tim O'Donnell <timodonnell@gmail.com>
Date: Wed, 14 Feb 2018 16:25:23 -0500
Subject: [PATCH] fix
---
.../train_allele_specific_models_command.py | 30 +++++++++----------
1 file changed, 15 insertions(+), 15 deletions(-)
diff --git a/mhcflurry/train_allele_specific_models_command.py b/mhcflurry/train_allele_specific_models_command.py
index decd4b98..d075167d 100644
--- a/mhcflurry/train_allele_specific_models_command.py
+++ b/mhcflurry/train_allele_specific_models_command.py
@@ -200,7 +200,6 @@ def run(argv=sys.argv[1:]):
print("Training data: %s" % (str(df.shape)))
GLOBAL_DATA["train_data"] = df
- GLOBAL_DATA["train_data_size_by_allele"] = df.allele.value_counts()
GLOBAL_DATA["args"] = args
if not os.path.exists(args.out_models_dir):
@@ -477,7 +476,18 @@ def train_model(
pretrain_min_points = hyperparameters['train_data']['pretrain_min_points']
full_data = GLOBAL_DATA["train_data"]
- data_size_by_allele = GLOBAL_DATA["train_data_size_by_allele"]
+
+ subset = hyperparameters.get("train_data", {}).get("subset", "all")
+ if subset == "quantitative":
+ data = full_data.loc[
+ full_data.measurement_type == "quantitative"
+ ]
+ elif subset == "all":
+ pass
+ else:
+ raise ValueError("Unsupported subset: %s" % subset)
+
+ data_size_by_allele = data.allele.value_counts()
if pretrain_min_points:
similar_alleles = alleles_by_similarity(allele)
@@ -485,22 +495,12 @@ def train_model(
while not alleles or data_size_by_allele.loc[alleles].sum() < pretrain_min_points:
alleles.append(similar_alleles.pop(0))
print(alleles)
- data = full_data.loc[full_data.allele.isin(alleles)]
+ data = data.loc[data.allele.isin(alleles)]
assert len(data) >= pretrain_min_points, (len(data), pretrain_min_points)
- train_rounds = (data.allele == allele).astype(int).values
+ data = (data.allele == allele).astype(int).values
else:
train_rounds = None
- data = full_data.loc[full_data.allele == allele]
-
- subset = hyperparameters.get("train_data", {}).get("subset", "all")
- if subset == "quantitative":
- data = data.loc[
- data.measurement_type == "quantitative"
- ]
- elif subset == "all":
- pass
- else:
- raise ValueError("Unsupported subset: %s" % subset)
+ data = data.loc[data.allele == allele]
progress_preamble = (
"[%2d / %2d hyperparameters] "
--
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