From e11bc31b55df43c0ded49672ad96fde9752e4e9e Mon Sep 17 00:00:00 2001 From: Gertjan van den Burg Date: Fri, 8 May 2020 18:34:11 +0100 Subject: Update code for public release --- app/utils/datasets.py | 9 +++++---- app/utils/tasks.py | 4 ++++ 2 files changed, 9 insertions(+), 4 deletions(-) (limited to 'app/utils') diff --git a/app/utils/datasets.py b/app/utils/datasets.py index db2c514..d348b47 100644 --- a/app/utils/datasets.py +++ b/app/utils/datasets.py @@ -1,5 +1,9 @@ # -*- coding: utf-8 -*- +# Author: G.J.J. van den Burg +# License: See LICENSE file +# Copyright: 2020 (c) The Alan Turing Institute + """ Dataset handling @@ -10,8 +14,6 @@ www.jsonschema.net or yapi.demo.qunar.com/editor/ Missing values must be denoted by 'NaN' (this is understood by the JSON decoder). -Author: Gertjan van den Burg - """ import hashlib @@ -76,7 +78,6 @@ def validate_dataset(filename): if None in data["time"]["raw"]: return "Null is not supported in time axis. Use 'NaN' instead." - has_missing = False for var in data["series"]: if len(var["raw"]) != data["n_obs"]: @@ -85,7 +86,7 @@ def validate_dataset(filename): return "Null is not supported in series. Use 'NaN' instead." has_missing = has_missing or any(map(math.isnan, var["raw"])) - # this doesn't happen in any dataset yet, so let's not implement it until + # this doesn't happen in any dataset yet, so let's not implement it until # we need it. if data["n_dim"] > 1 and has_missing: return "Missing values are not yet supported for multidimensional data" diff --git a/app/utils/tasks.py b/app/utils/tasks.py index 8356876..c082160 100644 --- a/app/utils/tasks.py +++ b/app/utils/tasks.py @@ -1,5 +1,9 @@ # -*- coding: utf-8 -*- +# Author: G.J.J. van den Burg +# License: See LICENSE file +# Copyright: 2020 (c) The Alan Turing Institute + """Utilities for task assignment """ -- cgit v1.2.3