History of sp_baboons

The changes to the source code of this entry in the repository, newest first, each with the differences it made to the entry's files. They are also listed on GitLab.

2026-11-03 [entries] Add the date when each entry was added, and remove icon_hash by Tiago de Paula Peixoto beff7c9

The dates are those of the commits that first added the entries' files
(2020-08-11 for the entries of the initial commit); renamed entries keep
the date of their first name.

Changed: none

diff --git a/entries/sp_baboons/__init__.py b/entries/sp_baboons/__init__.py
index 22421aa..31a41ef 100644
--- a/entries/sp_baboons/__init__.py
+++ b/entries/sp_baboons/__init__.py
@@ -47,7 +47,7 @@ The data file consists of 4 columns:
 tags = ['Social', 'Animal', 'Offline', 'Unweighted', 'Weighted', 'Temporal', 'Metadata']
 url = 'https://sociopatterns.org/datasets/baboons-interactions/'
 citation = [('V. Gelardi, J. Godard, D. Paleressompoulle, N. Claidière, A. Barrat, "Measuring social networks in primates: wearable sensors vs. direct observations", Proc. R. Soc. A 476:20190737 (2020)', 'https://doi.org/10.1098/rspa.2019.0737')]
-icon_hash = None
+date_added = '2021-08-07'
 upstream_license = ("Creative Commons Attribution-NonCommercial-ShareAlike",
                    "http://creativecommons.org/licenses/by-nc-sa/3.0/")
 upstream_prefix = 'https://sociopatterns.org/assets/data'

2026-11-02 [entries] Remove unneeded code from the entries by Tiago de Paula Peixoto 2c69f19

Unneeded "global files" statements, unused imports and variables,
f-strings without placeholders, duplicate keys in foodweb_little_rock
(keeping the order and the values used), and the second definition of
get_lines() in twitter_higgs. Nothing changes in the networks or
descriptions.

Changed: none

diff --git a/entries/sp_baboons/__init__.py b/entries/sp_baboons/__init__.py
index 80de2c0..22421aa 100644
--- a/entries/sp_baboons/__init__.py
+++ b/entries/sp_baboons/__init__.py
@@ -62,7 +62,6 @@ def fetch_upstream(force=False):
 @coerce_props()
 @annotate()
 def parse(alts=None):
-    global files
     name = __name__.split(".")[-1]
     for fnames, alt, fmt in files:
         if alts is not None and alt not in alts:

2026-10-25 [entries] Fix parse bugs and improve descriptions and metadata by Tiago de Paula Peixoto 6bb6851

- parse fixes from the review of the descriptions, e.g. us_patents
  (directed), celegans_2019 (synapse direction), ecoli_transcription and
  yeast_transcription (regulator to target), bitcoin (direction, phantom
  node), ego_social (Google+ features and circles), scotus_majority,
  arxiv_authors and social_location (as in SNAP), caida_as, dnc, dom,
  mist, reuters and bibsonomy (names on the right nodes), uci_zoo
- every description now states explicitly what the nodes and edges
  represent; corrected titles, years, tags, citations and licences
- the "Hypergraph" tag is removed; very large entries are marked
  `huge = True` (see --skip-huge)
- ICON ids of partial duplicates added (hiv_transmission, congress_bills,
  openflights, dutch_school)

diff --git a/entries/sp_baboons/__init__.py b/entries/sp_baboons/__init__.py
index d121952..80de2c0 100644
--- a/entries/sp_baboons/__init__.py
+++ b/entries/sp_baboons/__init__.py
@@ -22,7 +22,7 @@ import csv
 import datetime
 
 title = "Baboons' interactions (2020)"
-description = """Network of interactions between a group of 20 Guinea baboons living in an enclosure of a Primate Center in France, between June 13th 2019 and July 10th 2019. The data set contains observational and wearable sensors data.
+description = r"""Network of interactions between a group of 20 Guinea baboons living in an enclosure of a Primate Center in France, between June 13th 2019 and July 10th 2019. The data set contains observational and wearable sensors data. Nodes are baboons. In the `observational` network, each directed edge $i \to j$ is a behavioral event registered by the observer, in which baboon $i$ (the actor) acts upon baboon $j$ (the recipient), so that a pair of baboons is connected by one edge per event; in the `sensor` network, each undirected edge is a contact between two baboons recorded by the proximity sensors, one edge per recorded contact.
 
 The observational data contains all the behavioral events registered by an observer, with 8 columns:

2026-10-25 [entries] Fix parse bugs and improve the metadata of existing entries by Tiago de Paula Peixoto c996a0e

From a review of the dataset descriptions against the upstream sources
and papers, and from user reports:

- parse fixes (wrong edge direction or directedness, shifted or
  misnamed properties, merged node identities, duplicated or missing
  edges and nodes, wrong types), e.g. arxiv_citation (the HepTh dates
  were a copy of the HepPh ones; now from the KDD Cup 2003 data),
  eu_procurements, foursquare_global, hiv_transmission, genetic_multiplex,
  gnutella (adds the 05 snapshot), roadnet, macaque_neural, python_dependency
- descriptions rewritten from the upstream sources, documenting every
  property
- corrected titles, citations and DOIs, licences (ustream_license typo,
  the data's own terms), tags and ICON ids
- url lists for entries with several sources or dataset pages
- SocioPatterns entries moved to the site's new data location, with the
  daily networks of sp_infectious and sp_primary_school
- the Michael Fire entries marked as orphans (served from the mirror)
- redundant type forcings removed after the graph-tool coercion fixes

diff --git a/entries/sp_baboons/__init__.py b/entries/sp_baboons/__init__.py
index f1bf21f..d121952 100644
--- a/entries/sp_baboons/__init__.py
+++ b/entries/sp_baboons/__init__.py
@@ -45,14 +45,14 @@ The data file consists of 4 columns:
 
 """
 tags = ['Social', 'Animal', 'Offline', 'Unweighted', 'Weighted', 'Temporal', 'Metadata']
-url = 'http://www.sociopatterns.org/datasets/baboons-interactions/'
+url = 'https://sociopatterns.org/datasets/baboons-interactions/'
 citation = [('V. Gelardi, J. Godard, D. Paleressompoulle, N. Claidière, A. Barrat, "Measuring social networks in primates: wearable sensors vs. direct observations", Proc. R. Soc. A 476:20190737 (2020)', 'https://doi.org/10.1098/rspa.2019.0737')]
 icon_hash = None
-ustream_license = ("Creative Commons Attribution-NonCommercial-ShareAlike",
+upstream_license = ("Creative Commons Attribution-NonCommercial-ShareAlike",
                    "http://creativecommons.org/licenses/by-nc-sa/3.0/")
-upstream_prefix = 'http://www.sociopatterns.org/wp-content/uploads/2020/12/'
-files = [('OBS_data.txt.gz', 'observational', None),
-         ('RFID_data.txt.gz', 'sensor', None)]
+upstream_prefix = 'https://sociopatterns.org/assets/data'
+files = [('baboons_obs_data.txt.gz', 'observational', None),
+         ('baboons_proximity_data.txt.gz', 'sensor', None)]
 
 def fetch_upstream(force=False):
     return fetch_upstream_files(__name__.split(".")[-1], upstream_prefix, files,

2026-10-24 Update copyright information by Tiago de Paula Peixoto 73a4f0d

diff --git a/entries/sp_baboons/__init__.py b/entries/sp_baboons/__init__.py
index a361d61..f1bf21f 100644
--- a/entries/sp_baboons/__init__.py
+++ b/entries/sp_baboons/__init__.py
@@ -1,7 +1,7 @@
 #! /usr/bin/env python
 # -*- coding: utf-8 -*-
 #
-# Copyright (C) 2020-2024 Tiago de Paula Peixoto <tiago@skewed.de>
+# Copyright (C) 2020-2026 Tiago de Paula Peixoto <tiago@skewed.de>
 #
 # This program is free software: you can redistribute it and/or modify it under
 # the terms of the GNU Affero General Public License as published by the Free

2024-05-27 Update copyright information by Tiago de Paula Peixoto 3d288ea

diff --git a/entries/sp_baboons/__init__.py b/entries/sp_baboons/__init__.py
index 504e930..a361d61 100644
--- a/entries/sp_baboons/__init__.py
+++ b/entries/sp_baboons/__init__.py
@@ -1,7 +1,7 @@
 #! /usr/bin/env python
 # -*- coding: utf-8 -*-
 #
-# Copyright (C) 2020-2023 Tiago de Paula Peixoto <tiago@skewed.de>
+# Copyright (C) 2020-2024 Tiago de Paula Peixoto <tiago@skewed.de>
 #
 # This program is free software: you can redistribute it and/or modify it under
 # the terms of the GNU Affero General Public License as published by the Free

2023-02-19 Update copyright information by Tiago de Paula Peixoto 8d005ae

diff --git a/entries/sp_baboons/__init__.py b/entries/sp_baboons/__init__.py
index 86aa8c5..504e930 100644
--- a/entries/sp_baboons/__init__.py
+++ b/entries/sp_baboons/__init__.py
@@ -1,7 +1,7 @@
 #! /usr/bin/env python
 # -*- coding: utf-8 -*-
 #
-# Copyright (C) 2021 Tiago de Paula Peixoto <tiago@skewed.de>
+# Copyright (C) 2020-2023 Tiago de Paula Peixoto <tiago@skewed.de>
 #
 # This program is free software: you can redistribute it and/or modify it under
 # the terms of the GNU Affero General Public License as published by the Free

2021-08-07 Add sp_baboons by Tiago de Paula Peixoto 64ddddc

diff --git a/entries/sp_baboons/__init__.py b/entries/sp_baboons/__init__.py
new file mode 100644
index 0000000..86aa8c5
--- /dev/null
+++ b/entries/sp_baboons/__init__.py
@@ -0,0 +1,107 @@
+#! /usr/bin/env python
+# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2021 Tiago de Paula Peixoto <tiago@skewed.de>
+#
+# This program is free software: you can redistribute it and/or modify it under
+# the terms of the GNU Affero General Public License as published by the Free
+# Software Foundation, either version 3 of the License, or (at your option) any
+# later version.
+#
+# This program is distributed in the hope that it will be useful, but WITHOUT
+# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
+# FOR A PARTICULAR PURPOSE.  See the GNU Affero General Public License for more
+# details.
+#
+# You should have received a copy of the GNU Affero General Public License along
+# with this program.  If not, see <http://www.gnu.org/licenses/>.
+
+from .. import *
+
+import csv
+import datetime
+
+title = "Baboons' interactions (2020)"
+description = """Network of interactions between a group of 20 Guinea baboons living in an enclosure of a Primate Center in France, between June 13th 2019 and July 10th 2019. The data set contains observational and wearable sensors data.
+
+The observational data contains all the behavioral events registered by an observer, with 8 columns:
+
+- DateTime: Time stamp of the event, namely the moment the observed behavior was registered. In case of STATE events (events with duration > 0), it refers to the beginning of the behavior
+- Actor: The name of the actor
+- Recipient:  The name of the individual the Actor is acting upon
+- Behavior:  The behavior the Actor. 14 types of behaviors are registered:’Resting’, ‘Grooming’, ‘Presenting’,’Playing with’, ‘Grunting-Lipsmacking’, ‘Supplanting’,’Threatening’, ‘Submission’, ‘Touching’, ‘Avoiding’, ‘Attacking’,’Carrying’, ‘Embracing’, ‘Mounting’, ‘Copulating’, ‘Chasing’. In addition two other categories were included: ‘Invisible’ and ‘Other’
+- Category:  The classification of the behavior. It can be ‘Affiliative’, ‘Agonistic’, ‘Other’
+- Duration:  Duration of the observed behavior. POINT events have no duration
+- Localisation:  Zone of the enclosure where the observed behavior takes place
+- Point:  indicates if the event is a POINT event (YES) or a STATE event (NO).
+
+The sensor data contains contacts recorded in the same period by the SocioPatterns infrastructure. The proximity sensors were worn by 13 of the 20 individuals cited above.
+The data file consists of 4 columns:
+
+- t:  time of the beginning of the contact in Epoch format (Unix timestamps)
+- i:  Name of the first individual
+- j:  Name of the second individual
+- DateTime
+
+"""
+tags = ['Social', 'Animal', 'Offline', 'Unweighted', 'Weighted', 'Temporal', 'Metadata']
+url = 'http://www.sociopatterns.org/datasets/baboons-interactions/'
+citation = [('V. Gelardi, J. Godard, D. Paleressompoulle, N. Claidière, A. Barrat, "Measuring social networks in primates: wearable sensors vs. direct observations", Proc. R. Soc. A 476:20190737 (2020)', 'https://doi.org/10.1098/rspa.2019.0737')]
+icon_hash = None
+ustream_license = ("Creative Commons Attribution-NonCommercial-ShareAlike",
+                   "http://creativecommons.org/licenses/by-nc-sa/3.0/")
+upstream_prefix = 'http://www.sociopatterns.org/wp-content/uploads/2020/12/'
+files = [('OBS_data.txt.gz', 'observational', None),
+         ('RFID_data.txt.gz', 'sensor', None)]
+
+def fetch_upstream(force=False):
+    return fetch_upstream_files(__name__.split(".")[-1], upstream_prefix, files,
+                                force)
+
+@cache_network()
+@coerce_props()
+@annotate()
+def parse(alts=None):
+    global files
+    name = __name__.split(".")[-1]
+    for fnames, alt, fmt in files:
+        if alts is not None and alt not in alts:
+            continue
+        if isinstance(fnames, str):
+            fnames = [fnames]
+        with ExitStack() as stack:
+            fs = [stack.enter_context(open_upstream_file(name, fn, "r")) for fn in fnames]
+            reader = csv.reader(fs[0], delimiter="\t")
+
+            if alt == "sensor":
+                def get_edges():
+                    next(reader)
+                    for rows in reader:
+                        t, u, v = rows[:3]
+                        yield u, v, t
+                g = Graph(directed=False)
+                g.ep.time = g.new_ep("int")
+                g.vp.name = g.add_edge_list(get_edges(), hashed=True,
+                                            hash_type="string", eprops=[g.ep.time])
+            elif alt == "observational":
+                def get_edges():
+                    next(reader)
+                    for rows in reader:
+                        if rows[2] == "":
+                            continue
+                        t = datetime.datetime.strptime(rows[0], "%d/%m/%Y %H:%M").timestamp()
+                        yield rows[1:3] + [t] + rows[3:-1] + [True if rows[-1] == "YES" else False]
+                g = Graph(directed=True)
+                g.ep.time = g.new_ep("int")
+                g.ep.behavior = g.new_ep("string")
+                g.ep.category = g.new_ep("string")
+                g.ep.duration = g.new_ep("double")
+                g.ep.localization = g.new_ep("string")
+                g.ep.point = g.new_ep("bool")
+                g.vp.name = g.add_edge_list(get_edges(), hashed=True,
+                                            hash_type="string",
+                                            eprops=[g.ep.time, g.ep.behavior,
+                                                    g.ep.category,
+                                                    g.ep.duration, g.ep.localization,
+                                                    g.ep.point])
+        yield alt, g