From e55afc59840f805999e20fd6342c5efe32bf2901 Mon Sep 17 00:00:00 2001
From: Tim O'Donnell <timodonnell@gmail.com>
Date: Fri, 24 Jan 2020 21:12:40 -0500
Subject: [PATCH] fix
---
.../models_class1_presentation/make_benchmark.py | 9 ++++-----
mhcflurry/train_presentation_models_command.py | 2 +-
2 files changed, 5 insertions(+), 6 deletions(-)
diff --git a/downloads-generation/models_class1_presentation/make_benchmark.py b/downloads-generation/models_class1_presentation/make_benchmark.py
index 6a14d7b6..6d094eb4 100644
--- a/downloads-generation/models_class1_presentation/make_benchmark.py
+++ b/downloads-generation/models_class1_presentation/make_benchmark.py
@@ -53,7 +53,8 @@ parser.add_argument(
def run():
args = parser.parse_args(sys.argv[1:])
hit_df = pandas.read_csv(args.hits)
- original_sample_ids = hit_df.sample_id.unique()
+ hit_df["pmid"] = hit_df["pmid"].astype(str)
+ original_samples_pmids = hit_df.pmid.unique()
numpy.testing.assert_equal(hit_df.hit_id.nunique(), len(hit_df))
hit_df = hit_df.loc[
(hit_df.mhc_class == "I") &
@@ -69,14 +70,12 @@ def run():
print("Subselected to %d %s samples" % (
hit_df.sample_id.nunique(), args.only_format))
- hit_df["pmid"] = hit_df["pmid"].astype(str)
-
if args.only_pmid or args.exclude_pmid:
assert not (args.only_pmid and args.exclude_pmid)
pmids = list(args.only_pmid) + list(args.exclude_pmid)
- missing = [pmid for pmid in pmids if pmid not in original_sample_ids]
- assert not missing, missing
+ missing = [pmid for pmid in pmids if pmid not in original_samples_pmids]
+ assert not missing, (missing, original_samples_pmids)
mask = hit_df.pmid.isin(pmids)
if args.exclude_pmid:
diff --git a/mhcflurry/train_presentation_models_command.py b/mhcflurry/train_presentation_models_command.py
index d23d0106..ca1ac349 100644
--- a/mhcflurry/train_presentation_models_command.py
+++ b/mhcflurry/train_presentation_models_command.py
@@ -96,7 +96,7 @@ def main(args):
]
print("Subselected to 8-15mers: %s" % (str(df.shape)))
- df["experiment_id"] = df[args.hla_columns]
+ df["experiment_id"] = df[args.hla_column]
experiment_to_alleles = dict((
key, key.split()) for key in df.experiment_id.unique())
--
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